Coupling a Reactive Transport Code with a Global Land Surface Model for Mechanistic Biogeochemistry Representation: 1. Addressing the Challenge of Nonnegativity

DOE PAGES

Tang, Guoping; Yuan, Fengming; Bisht, Gautam; ...

2016-01-01

Reactive transport codes (e.g., PFLOTRAN) are increasingly used to improve the representation of biogeochemical processes in terrestrial ecosystem models (e.g., the Community Land Model, CLM). As CLM and PFLOTRAN use explicit and implicit time stepping, implementation of CLM biogeochemical reactions in PFLOTRAN can result in negative concentration, which is not physical and can cause numerical instability and errors. The objective of this work is to address the nonnegativity challenge to obtain accurate, efficient, and robust solutions. We illustrate the implementation of a reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant nitrogen uptake reactions and test the implementation atmore » arctic, temperate, and tropical sites. We examine use of scaling back the update during each iteration (SU), log transformation (LT), and downregulating the reaction rate to account for reactant availability limitation to enforce nonnegativity. Both SU and LT guarantee nonnegativity but with implications. When a very small scaling factor occurs due to either consumption or numerical overshoot, and the iterations are deemed converged because of too small an update, SU can introduce excessive numerical error. LT involves multiplication of the Jacobian matrix by the concentration vector, which increases the condition number, decreases the time step size, and increases the computational cost. Neither SU nor SE prevents zero concentration. When the concentration is close to machine precision or 0, a small positive update stops all reactions for SU, and LT can fail due to a singular Jacobian matrix. The consumption rate has to be downregulated such that the solution to the mathematical representation is positive. A first-order rate downregulates consumption and is nonnegative, and adding a residual concentration makes it positive. For zero-order rate or when the reaction rate is not a function of a reactant, representing the availability limitation of each reactant with a Monod substrate limiting function provides a smooth transition between a zero-order rate when the reactant is abundant and first-order rate when the reactant becomes limiting. When the half saturation is small, marching through the transition may require small time step sizes to resolve the sharp change within a small range of concentration values. Our results from simple tests and CLM-PFLOTRAN simulations caution against use of SU and indicate that accurate, stable, and relatively efficient solutions can be achieved with LT and downregulation with Monod substrate limiting function and residual concentration.« less

Evaluation of snowmelt simulation in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Jin, Jiming; Wen, Lijuan

2012-05-01

The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

Addressing numerical challenges in introducing a reactive transport code into a land surface model: A biogeochemical modeling proof-of-concept with CLM-PFLOTRAN 1.0: Modeling Archive

DOE Data Explorer

Tang, G.; Andre, B.; Hoffman, F. M.; Painter, S. L.; Thornton, P. E.; Yuan, F.; Bisht, G.; Hammond, G. E.; Lichtner, P. C.; Kumar, J.; Mills, R. T.; Xu, X.

2016-04-19

This Modeling Archive is in support of an NGEE Arctic discussion paper under review and available at doi:10.5194/gmd-9-927-2016. The purpose is to document the simulations to allow verification, reproducibility, and follow-up studies. This dataset contains shell scripts to create the CLM-PFLOTRAN cases, specific input files for PFLOTRAN and CLM, outputs, and python scripts to make the figures using the outputs in the publication. Through these results, we demonstrate that CLM-PFLOTRAN can approximately reproduce CLM results in selected cases for the Arctic, temperate and tropic sites. In addition, the new framework facilitates mechanistic representations of soil biogeochemistry processes in the land surface model.

An economic analysis of adherence engineering to improve use of best practices during central line maintenance procedures.

PubMed

Nelson, Richard E; Angelovic, Aaron W; Nelson, Scott D; Gleed, Jeremy R; Drews, Frank A

2015-05-01

Adherence engineering applies human factors principles to examine non-adherence within a specific task and to guide the development of materials or equipment to increase protocol adherence and reduce human error. Central line maintenance (CLM) for intensive care unit (ICU) patients is a task through which error or non-adherence to protocols can cause central line-associated bloodstream infections (CLABSIs). We conducted an economic analysis of an adherence engineering CLM kit designed to improve the CLM task and reduce the risk of CLABSI. We constructed a Markov model to compare the cost-effectiveness of the CLM kit, which contains each of the 27 items necessary for performing the CLM procedure, compared with the standard care procedure for CLM, in which each item for dressing maintenance is gathered separately. We estimated the model using the cost of CLABSI overall ($45,685) as well as the excess LOS (6.9 excess ICU days, 3.5 excess general ward days). Assuming the CLM kit reduces the risk of CLABSI by 100% and 50%, this strategy was less costly (cost savings between $306 and $860) and more effective (between 0.05 and 0.13 more quality-adjusted life-years) compared with not using the pre-packaged kit. We identified threshold values for the effectiveness of the kit in reducing CLABSI for which the kit strategy was no longer less costly. An adherence engineering-based intervention to streamline the CLM process can improve patient outcomes and lower costs. Patient safety can be improved by adopting new approaches that are based on human factors principles.

Coupling of Community Land Model with RegCM4 for Indian Summer Monsoon Simulation

NASA Astrophysics Data System (ADS)

Maurya, R. K. S.; Sinha, P.; Mohanty, M. R.; Mohanty, U. C.

2017-11-01

Three land surface schemes available in the regional climate model RegCM4 have been examined to understand the coupling between land and atmosphere for simulation of the Indian summer monsoon rainfall. The RegCM4 is coupled with biosphere-atmosphere transfer scheme (BATS) and the National Center for Atmospheric Research (NCAR) Community Land Model versions 3.5, and 4.5 (CLM3.5 and CLM4.5, respectively) and model performance is evaluated for recent drought (2009) and normal (2011) monsoon years. The CLM4.5 has a more distinct category of surface and it is capable of representing better the land surface characteristics. National Centers for Environmental Prediction (NCEP) and Department of Energy (DOE) reanalysis version 2 (NNRP2) datasets are considered as driving force to conduct the experiments for the Indian monsoon region (30°E-120°E; 30°S-50°N). The NNRP2 and India Meteorological Department (IMD) gridded precipitation data are used for verification analysis. The results indicate that RegCM4 simulations with CLM4.5 (RegCM4-CLM4.5) and CLM3.5 (RegCM4-CLM3.5) surface temperature (at 2 ms) have very low warm biases ( 1 °C), while with BATS (RegCM4-BATS) has a cold bias of about 1-3 °C in peninsular India and some parts of central India. Warm bias in the RegCM4-BATS is observed over the Indo-Gangetic plain and northwest India and the bias is more for the deficit year as compared to the normal year. However, the warm (cold) bias is less in RegCM4-CLM4.5 than other schemes for both the deficit and normal years. The model-simulated maximum (minimum) surface temperature and sensible heat flux at the surface are positively (negatively) biased in all the schemes; however, the bias is higher in RegCM4-BATS and lower in RegCM4-CLM4.5 over India. All the land surface schemes overestimated the precipitation in peninsular India and underestimated in central parts of India for both the years; however, the biases are less in RegCM4-CLM4.5 and more in RegCM4-CLM3.5 and RegCM4-BATS. During both the years, BATS scheme in RegCM4 failed to represent low precipitation over the leeward than windward side of the Western Ghats, while CLM schemes (both versions) in the RegCM4 are able to depict this feature. In the topographic regions, such as the Western Ghats, northeast India and state of Jammu and Kashmir, RegCM4-BATS overestimates the rainfall amount with higher bias. Statistical analysis using anomaly correlation coefficient, root mean square error, equitable threat score, and critical success index confirms that RegCM4-CLM performs better than RegCM4-BATS in the simulation of the Indian summer monsoon.

Bayesian calibration of the Community Land Model using surrogates

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

Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi

2014-02-01

We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural errormore » in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.« less

Global Parameter Optimization of CLM4.5 Using Sparse-Grid Based Surrogates

NASA Astrophysics Data System (ADS)

Lu, D.; Ricciuto, D. M.; Gu, L.

2016-12-01

Calibration of the Community Land Model (CLM) is challenging because of its model complexity, large parameter sets, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time. The goal of this study is to calibrate some of the CLM parameters in order to improve model projection of carbon fluxes. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first use advanced sparse grid (SG) interpolation to construct a surrogate system of the actual CLM model, and then we calibrate the surrogate model in the optimization process. As the surrogate model is a polynomial whose evaluation is fast, it can be efficiently evaluated with sufficiently large number of times in the optimization, which facilitates the global search. We calibrate five parameters against 12 months of GPP, NEP, and TLAI data from the U.S. Missouri Ozark (US-MOz) tower. The results indicate that an accurate surrogate model can be created for the CLM4.5 with a relatively small number of SG points (i.e., CLM4.5 simulations), and the application of the optimized parameters leads to a higher predictive capacity than the default parameter values in the CLM4.5 for the US-MOz site.

Evaluation of the Snow Simulations from the Community Land Model, Version 4 (CLM4)

NASA Technical Reports Server (NTRS)

Toure, Ally M.; Rodell, Matthew; Yang, Zong-Liang; Beaudoing, Hiroko; Kim, Edward; Zhang, Yongfei; Kwon, Yonghwan

2015-01-01

This paper evaluates the simulation of snow by the Community Land Model, version 4 (CLM4), the land model component of the Community Earth System Model, version 1.0.4 (CESM1.0.4). CLM4 was run in an offline mode forced with the corrected land-only replay of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-Land) and the output was evaluated for the period from January 2001 to January 2011 over the Northern Hemisphere poleward of 30 deg N. Simulated snow-cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Moderate Resolution Imaging Spectroradiometer (MODIS) SCF, the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover, the Canadian Meteorological Centre (CMC) daily snow analysis products, snow depth from the National Weather Service Cooperative Observer (COOP) program, and Snowpack Telemetry (SNOTEL) SWE observations. CLM4 SCF was converted into snow-cover extent (SCE) to compare with MODIS SCE. It showed good agreement, with a correlation coefficient of 0.91 and an average bias of -1.54 x 10(exp 2) sq km. Overall, CLM4 agreed well with IMS snow cover, with the percentage of correctly modeled snow-no snow being 94%. CLM4 snow depth and SWE agreed reasonably well with the CMC product, with the average bias (RMSE) of snow depth and SWE being 0.044m (0.19 m) and -0.010m (0.04 m), respectively. CLM4 underestimated SNOTEL SWE and COOP snow depth. This study demonstrates the need to improve the CLM4 snow estimates and constitutes a benchmark against which improvement of the model through data assimilation can be measured.

Responses of the terrestrial carbon cycle to drought: modeling sensitivities of the interactive nitrogen and dynamic vegetation

NASA Astrophysics Data System (ADS)

Jia, B.; Wang, Y.; Xie, Z.

2016-12-01

Drought can trigger both immediate and time-lagged responses of terrestrial ecosystems and even cause sizeable positive feedbacks to climate warming. In this study, the influences of interactive nitrogen (N) and dynamic vegetation (DV) on the response of the carbon cycle in terrestrial ecosystems of China to drought were investigated using the Community Land Model version 4.5 (CLM4.5). Model simulations from three configurations of CLM4.5 (C, carbon cycle only; CN, dynamic carbon and nitrogen cycle; CNDV, dynamic carbon and nitrogen cycle as well as dynamic vegetation) between 1961 and 2010 showed that the incorporation of a prognostic N cycle and DV into CLM4.5 reduce the predicted annual means and inter-annual variability of predicted gross primary production (GPP) and net ecosystem production (NEP), except for a slight increase in NEP for CNDV compared to CN. These model improvements resulted in better agreement with observations (7.0 PgC yr-1) of annual GPP over the terrestrial ecosystems in China for CLM45-CN (7.5 PgC yr-1) and CLM45-CNDV (7.3 PgC yr-1) than for CLM45-C (10.9 PgC yr-1). Compared to the CLM45-C, the carbon-nitrogen coupling strengthened the predicted response of GPP to drought, resulting in a higher correlation with the standardized precipitation index (SPI; rC = 0.62, rCN = 0.67), but led to a weaker sensitivity of NEP to SPI (rC = 0.51, rCN = 0.45). The CLM45-CNDV had the longest lagged responses of GPP to drought among the three configurations. These results enhance our understanding of the response of the terrestrial carbon cycle to drought.

Volumetric‐modulated arc therapy planning using multicriteria optimization for localized prostate cancer

PubMed Central

Ghandour, Sarah; Matzinger, Oscar

2015-01-01

The purpose of this work is to evaluate the volumetric‐modulated arc therapy (VMAT) multicriteria optimization (MCO) algorithm clinically available in the RayStation treatment planning system (TPS) and its ability to reduce treatment planning time while providing high dosimetric plan quality. Nine patients with localized prostate cancer who were previously treated with 78 Gy in 39 fractions using VMAT plans and rayArc system based on the direct machine parameter optimization (DMPO) algorithm were selected and replanned using the VMAT‐MCO system. First, the dosimetric quality of the plans was evaluated using multiple conformity metrics that account for target coverage and sparing of healthy tissue, used in our departmental clinical protocols. The conformity and homogeneity index, number of monitor units, and treatment planning time for both modalities were assessed. Next, the effects of the technical plan parameters, such as constraint leaf motion CLM (cm/°) and maximum arc delivery time T (s), on the accuracy of delivered dose were evaluated using quality assurance passing rates (QAs) measured using the Delta4 phantom from ScandiDos. For the dosimetric plan's quality analysis, the results show that the VMAT‐MCO system provides plans comparable to the rayArc system with no statistical difference for V95% (p<0.01), D1% (p<0.01), CI (p<0.01), and HI (p<0.01) of the PTV, bladder (p<0.01), and rectum (p<0.01) constraints, except for the femoral heads and healthy tissues, for which a dose reduction was observed using MCO compared with rayArc (p<0.01). The technical parameter study showed that a combination of CLM equal to 0.5 cm/degree and a maximum delivery time of 72 s allowed the accurate delivery of the VMAT‐MCO plan on the Elekta Versa HD linear accelerator. Planning evaluation and dosimetric measurements showed that VMAT‐MCO can be used clinically with the advantage of enhanced planning process efficiency by reducing the treatment planning time without impairing dosimetric quality. PACS numbers: 87.55.D, 87.55.de, 87.55.Qr PMID:26103500

Parsing multiple processes of high temperature impacts on corn/soybean yield using a newly developed CLM-APSIM modeling framework

NASA Astrophysics Data System (ADS)

Peng, B.; Guan, K.; Chen, M.

2016-12-01

Future agricultural production faces a grand challenge of higher temperature under climate change. There are multiple physiological or metabolic processes of how high temperature affects crop yield. Specifically, we consider the following major processes: (1) direct temperature effects on photosynthesis and respiration; (2) speed-up growth rate and the shortening of growing season; (3) heat stress during reproductive stage (flowering and grain-filling); (4) high-temperature induced increase of atmospheric water demands. In this work, we use a newly developed modeling framework (CLM-APSIM) to simulate the corn and soybean growth and explicitly parse the above four processes. By combining the strength of CLM in modeling surface biophysical (e.g., hydrology and energy balance) and biogeochemical (e.g., photosynthesis and carbon-nitrogen interactions), as well as that of APSIM in modeling crop phenology and reproductive stress, the newly developed CLM-APSIM modeling framework enables us to diagnose the impacts of high temperature stress through different processes at various crop phenology stages. Ground measurements from the advanced SoyFACE facility at University of Illinois is used here to calibrate, validate, and improve the CLM-APSIM modeling framework at the site level. We finally use the CLM-APSIM modeling framework to project crop yield for the whole US Corn Belt under different climate scenarios.

Simulation of Soil Frost and Thaw Fronts Dynamics with Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Gao, J.; Xie, Z.

2016-12-01

Freeze-thaw processes in soils, including changes in frost and thaw fronts (FTFs) , are important physical processes. The movement of FTFs affects soil water and thermal characteristics, as well as energy and water exchanges between land surface and the atmosphere, and then the land surface hydrothermal process. In this study, a two-directional freeze and thaw algorithm for simulating FTFs is incorporated into the community land surface model CLM4.5, which is called CLM4.5-FTF. The simulated FTFs depth and soil temperature of CLM4.5-FTF compared well with the observed data both in D66 station (permafrost) and Hulugou station (seasonally frozen soil). Because the soil temperature profile within a soil layer can be estimated according to the position of FTFs, CLM4.5 performed better in soil temperature simulation. Permafrost and seasonally frozen ground conditions in China from 1980 to 2010 were simulated using the CLM4.5-FTF. Numerical experiments show that the spatial distribution of simulated maximum frost depth by CLM4.5-FTF has seasonal variation obviously. Significant positive active-layer depth trends for permafrost regions and negative maximum freezing depth trends for seasonal frozen soil regions are simulated in response to positive air temperature trends except west of Black Sea.

Remote sensing evaluation of CLM4 GPP for the period 2000 to 2009

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

Mao, Jiafu; Thornton, Peter E; Shi, Xiaoying

2012-01-01

The ability of a process-based ecosystem model like Version 4 of the Community Land Model (CLM4) to provide accurate estimates of CO2 flux is a top priority for researchers, modelers and policy makers. Remote sensing can provide long-term and large scale products suitable for ecosystem model evaluation. Global estimations of gross primary production (GPP) at the 1 km spatial resolution from years 2000 to 2009 from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor offer a unique opportunity for evaluating the temporal and spatial patterns of global GPP and its relationship with climate for CLM4. We compare monthly GPP simulated bymore » CLM4 at half-degree resolution with satellite estimates of GPP from the MODIS GPP (MOD17) dataset for the 10-yr period, January 2000 December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intra-annual and inter-annual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and later decline of GPP in autumn. Empirical Orthogonal Function (EOF) analysis of the monthly GPP changes indicates that on the intra-annual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and the very dry region in central Australia. For 2000-2009, CLM4 simulates increases in annual averaged GPP over both hemispheres, however estimates from MODIS suggest a reduction in the Southern Hemisphere (-0.2173 PgC/year) balancing the significant increase over the Northern Hemisphere (0.2157 PgC/year).« less

Global Soil Moisture Estimation through a Coupled CLM4-RTM-DART Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Zhao, L.; Yang, Z. L.; Hoar, T. J.

2016-12-01

Very few frameworks exist that estimate global-scale soil moisture through microwave land data assimilation (DA). Toward this goal, we have developed such a framework by linking the Community Land Model version 4 (CLM4) and a microwave radiative transfer model (RTM) with the Data Assimilation Research Testbed (DART). The deterministic Ensemble Adjustment Kalman Filter (EAKF) within the DART is utilized to estimate global multi-layer soil moisture by assimilating brightness temperature observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). A 40-member of Community Atmosphere Model version 4 (CAM4) reanalysis is adopted to drive CLM4 simulations. Spatial-specific time-invariant microwave parameters are pre-calibrated to minimize uncertainties in RTM. Besides, various methods are designed in consideration of computational efficiency. A series of experiments are conducted to quantify the DA sensitivity to microwave parameters, choice of assimilated observations, and different CLM4 updating schemes. Evaluation results indicate that the newly established CLM4-RTM-DART framework improves the open-loop CLM4 simulated soil moisture. Pre-calibrated microwave parameters, rather than their default values, can ensure a more robust global-scale performance. In addition, updating near-surface soil moisture is capable of improving soil moisture in deeper layers, while simultaneously updating multi-layer soil moisture fails to obtain intended improvements. We will show in this presentation the architecture of the CLM4-RTM-DART system and the evaluations on AMSR-E DA. Preliminary results on multi-sensor DA that integrates various satellite observations including GRACE, MODIS, and AMSR-E will also be presented. ReferenceZhao, L., Z.-L. Yang, and T. J. Hoar, 2016. Global Soil Moisture Estimation by Assimilating AMSR-E Brightness Temperatures in a Coupled CLM4-RTM-DART System. Journal of Hydrometeorology, DOI: 10.1175/JHM-D-15-0218.1.

The Shifting Paradigm of Prognostic Factors of Colorectal Liver Metastases: From Tumor-Centered to Host Immune-Centered Factors

PubMed Central

Donadon, Matteo; Lleo, Ana; Di Tommaso, Luca; Soldani, Cristiana; Franceschini, Barbara; Roncalli, Massimo; Torzilli, Guido

2018-01-01

The determinants of prognosis in patients with colorectal liver metastases (CLM) have been traditionally searched among the tumoral factors, either of the primary colorectal tumor or of the CLM. While many different scoring systems have been developed based on those clinic-pathological factors with disparate results, there has been the introduction of genetic biological markers that added a theranostic perspective. More recently, other important elements, such as those factors related to the host immune system, have been proposed as determinants of prognosis of CLM patients. In the present work, we review the current prognostic factors of CLM patients as well as the burgeoning shifting paradigm of prognostication that relies on the host immune system. PMID:29892573

Performance of broilers fed on diets containing different amounts of chaya (Cnidoscolus aconitifolius) leaf meal.

PubMed

Sarmiento-Franco, L; McNab, J M; Pearson, R A; Belmar-Casso, R

2002-05-01

The performance and gut measurements of broilers fed on diets containing different amounts of chaya (Cnidoscolus aconitifolius) leaf meal (CLM) were examined in two experiments. In the first experiment, 60 Hubbard chickens (30 males and 30 females; 2 weeks old) were fed on five maize diets; these were formulated using 0, 150 (CLM150), 250 (CLM250) or 350 (CLM350) g CLM/kg, and the fifth diet contained soyabean. In the second experiment, 148 Ross male chicks, 1 day old, were fed on three isonitrogenous and isoenergetic maize-soyabean-based diets, which included 0 (control), 150 (C150) or 250 (C250) g CLM/kg. The diets were offered ad libitum for 2 or 3 weeks in the first and second experiments, respectively. Food intake, weight gain and the food:weight gain ratio were recorded. The weight of the gizzard and intestine and the weight and length of the caeca were also determined in the second experiment. In experiment 1, the birds fed on the maize-soyabean diet had a higher (p < 0.05) weight gain and final weight than birds fed on maize only or on the CLM150 diets. There were no differences for any of the variables studied between the birds fed on the maize-soyabean diet and those fed on the CLM250, nor between males and females. In the second experiment, weight gain, food intake and the food:weight gain ratio for birds fed on C250 were lower (p < 0.05) than those in birds fed on either the control or C150 diets. The weights of the gizzard and intestine were the lowest and the highest, respectively, in birds fed on C250 (p < 0.05). The length and weight of the caecum from birds fed on the control diet were lower (p < 0.05) than those of birds fed on either the C150 or C250 diets. The results from this study suggest that CLM may be included up to 150 g/kg in commercial diets without having an adverse effect on poultry performance, and may also be mixed with maize up to 250 g/kg to improve the performance of chickens fed on low-protein diets.

Risks and benefits of compost-like materials prepared by the thermal treatment of raw scallop hepatopancreas for supplying cadmium and the growth of alfalfa (Medicago sativa L.).

PubMed

Ushijima, Kensuke; Fukushima, Masami; Kanno, Shinya; Kanno, Itoko; Ohnishi, Mitsuhiro

2016-01-01

Scallop hepatopancreas, fishery waste, contains relatively high levels of Cd and organic nitrogen compounds, the latter of which represent a fertilizer. In this study, raw scallop hepatopancreas tissue was thermally treated with sawdust and red loam in the presence of an iron catalyst to produce compost-like materials (CLMs). Two CLM samples were prepared by varying the content of raw scallop hepatopancreas tissue: 46 wt.% for CLM-1 and 18 wt.% for CLM-2. Mixtures of control soil (CTL) and CLMs (CLM content: 10 and 25 wt.%) were examined for the growth of alfalfa (Medicago sativa L.) to evaluate the risks and benefits of using this material for fertilization. The Cd content in shoots and roots of alfalfa, that were grown in the presence of CLMs, was significantly higher than those for the plants grown in the CTL, indicating that Cd had accumulated in the plants from CLMs. The accumulation of Cd in the alfalfa roots was quite high in the case of the 25% CLM-1 sample. However, alfalfa growth was significantly promoted in the presence of 10% CLM-1. This can be attributed to the higher levels of nitrogen and humic substances, which serve as fertilizer components. Although the fertilization effect in case of CLM-1showed a potential benefit, the accumulation of Cd in alfalfa was clearly increased in the presence of both CLMs. In conclusion, the use of CLMs produced from raw scallop hepatopancreas tissue can be considered to have a desirable benefit from standpoint of its use as fertilizer, but is accompanied by a risk of the accumulation of Cd in alfalfa plants.

Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes

NASA Astrophysics Data System (ADS)

Chen, Ming; Griffis, Tim J.; Baker, John; Wood, Jeffrey D.; Xiao, Ke

2015-02-01

A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water, and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to Earth system models is relatively rare. Here we evaluated two such models (CLM4-Crop and CLM3.5-CornSoy), both implemented within the Community Land Model (CLM) framework, at two AmeriFlux corn-soybean sites to assess their ability to simulate phenology, energy, and carbon fluxes. Our results indicated that the accuracy of net ecosystem exchange and gross primary production simulations was intimately connected to the phenology simulations. The CLM4-Crop model consistently overestimated early growing season leaf area index, causing an overestimation of gross primary production, to such an extent that the model simulated a carbon sink instead of the measured carbon source for corn. The CLM3.5-CornSoy-simulated leaf area index (LAI), energy, and carbon fluxes showed stronger correlations with observations compared to CLM4-Crop. Net radiation was biased high in both models and was especially pronounced for soybeans. This was primarily caused by the positive LAI bias, which led to a positive net long-wave radiation bias. CLM4-Crop underestimated soil water content during midgrowing season in all soil layers at the two sites, which caused unrealistic water stress, especially for soybean. Future work regarding the mechanisms that drive early growing season phenology and soil water dynamics is needed to better represent crops including their net radiation balance, energy partitioning, and carbon cycle processes.

Evaluating runoff simulations from the Community Land Model 4.0 using observations from flux towers and a mountainous watershed

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

Li, Hongyi; Huang, Maoyi; Wigmosta, Mark S.

2011-12-24

Previous studies using the Community Land Model (CLM) focused on simulating landatmosphere interactions and water balance at continental to global scales, with limited attention paid to its capability for hydrologic simulations at watershed or regional scales. This study evaluates the performance of CLM 4.0 (CLM4) for hydrologic simulations, and explores possible directions of improvement. Specifically, it is found that CLM4 tends to produce unrealistically large temporal variation of runoff for applications at a mountainous catchment in the Northwest United States where subsurface runoff is dominant, as well as at a few flux tower sites. We show that runoff simulations frommore » CLM4 can be improved by: (1) increasing spatial resolution of the land surface representations; (2) calibrating parameter values; (3) replacing the subsurface formulation with a more general nonlinear function; (4) implementing the runoff generation schemes from the Variability Infiltration Capacity (VIC) model. This study also highlights the importance of evaluating both the energy and water fluxes application of land surface models across multiple scales.« less

Recent Advances in Chemotherapy and Surgery for Colorectal Liver Metastases

PubMed Central

Passot, Guillaume; Soubrane, Olivier; Giuliante, Felice; Zimmitti, Giuseppe; Goéré, Diane; Yamashita, Suguru; Vauthey, Jean-Nicolas

2016-01-01

Background The liver is the most common site of metastases for colorectal cancer, and combined resection with systemic chemotherapy is the most effective strategy for survival. The aim of this article is to provide a comprehensive summary on four hot topics related to chemotherapy and surgery for colorectal liver metastases (CLM), namely: (1) chemotherapy-related liver injuries: prediction and impact, (2) surgery for initially unresectable CLM, (3) the emerging role of RAS mutations, and (4) the role of hepatic arterial infusion of chemotherapy (HAIC). Summary and Key Messages (1) The use of chemotherapy before liver resection for CLM leads to drug-specific hepatic toxicity, which negatively impacts posthepatectomy outcomes. (2) Curative liver resection of initially unresectable CLM following conversion chemotherapy should be attempted whenever possible, provided that a safe future liver remnant volume is achieved. (3) For CLM, RAS mutation status is needed to guide the use of targeted chemotherapy with anti-epithelial growth factor receptor (EGFR) agents, and is a major prognostic factor that may contribute to optimize surgical strategy. (4) HAIC agents increase the rate of objective response and the rate of complete pathological response. PMID:27995091

Recent Advances in Chemotherapy and Surgery for Colorectal Liver Metastases.

PubMed

Passot, Guillaume; Soubrane, Olivier; Giuliante, Felice; Zimmitti, Giuseppe; Goéré, Diane; Yamashita, Suguru; Vauthey, Jean-Nicolas

2016-11-01

The liver is the most common site of metastases for colorectal cancer, and combined resection with systemic chemotherapy is the most effective strategy for survival. The aim of this article is to provide a comprehensive summary on four hot topics related to chemotherapy and surgery for colorectal liver metastases (CLM), namely: (1) chemotherapy-related liver injuries: prediction and impact, (2) surgery for initially unresectable CLM, (3) the emerging role of RAS mutations, and (4) the role of hepatic arterial infusion of chemotherapy (HAIC). (1) The use of chemotherapy before liver resection for CLM leads to drug-specific hepatic toxicity, which negatively impacts posthepatectomy outcomes. (2) Curative liver resection of initially unresectable CLM following conversion chemotherapy should be attempted whenever possible, provided that a safe future liver remnant volume is achieved. (3) For CLM, RAS mutation status is needed to guide the use of targeted chemotherapy with anti-epithelial growth factor receptor (EGFR) agents, and is a major prognostic factor that may contribute to optimize surgical strategy. (4) HAIC agents increase the rate of objective response and the rate of complete pathological response.

Phenology of forest-grassland transition zones in the Community Land Model

NASA Astrophysics Data System (ADS)

Dahlin, K.; Fisher, R. A.

2013-12-01

Forest-grassland transition zones (savannas, woodlands, wooded grasslands, and shrublands) are highly sensitive to climate and may already be changing due to warming, changes in precipitation patterns, and/or CO2 fertilization. Shifts between closed canopy forest and open grassland, as well as shifts in phenology, could have large impacts on the global carbon cycle, water balance, albedo, and on the humans and other animals that depend on these regions. From an earth system perspective these impacts may then feed back into the climate system and impact how, when, and where climate change occurs. Here we compare 29 years of monthly leaf area index (LAI) outputs from several offline versions of the Community Land Model (CLM), the land component of the Community Earth System Model, to LAI derived from the AVHRR NDVI3g product (LAI3g). Specifically, we focus on seasonal patterns in regions dominated by tropical broadleaved deciduous trees (T-BDT), broadleaved deciduous shrubs (BDS) and grasslands (C3 and C4) in CLM, all of which follow a 'stress deciduous' phenological algorithm. We consider and compare two versions of CLM (v. 4CN and v. 4.5BGC) to the satellite derived product. We found that both versions of CLM were able to capture seasonal variations in grasslands relatively well at the regional scale, but that the 'stress deciduous' phenology algorithm did not perform well in areas dominated by T-BDT or BDS. When we compared the performance of the models at single points we found slight improvements in CLM4.5BGC over CLM4CN, but generally that the magnitude of seasonality was too low in CLM as compared to the LAI3g satellite product. To explore the parameters within CLM that had the most leverage on seasonality of LAI, we used a Latin hypercube approach to vary values for critical soil water potential (threshold at which plants drop leaves), the critical number of days that soil water potential must be too low for leaves to drop, and the carbon allocation scheme. In single-point simulations we found that changing how carbon is allocated improved the 'flat-topped' nature of the CLM LAI during summer, which is not present in LAI3g, while adjustments to the soil water potential parameters allowed for less extreme and fewer switches between leaf-on and leaf-off. Future work will include applying a subset of the new parameter values to global runs of the model to assess whether the improvements to phenology at single points improve global phenological patterns and/or other components of the CLM carbon cycle.

Ozone-induced reductions in photosynthesis and transpiration: Parameterizing the Community Land Model (CLM)

NASA Astrophysics Data System (ADS)

Lombardozzi, D.; Bonan, G. B.; Levis, S.; Sparks, J. P.

2010-12-01

Humans are indirectly increasing concentrations of surface ozone (O3) through industrial processes. Ozone is known to have negative impacts on plants, including reductions in crop yields, plant growth, and visible leaf injury. Research also suggests that O3 exposure differentially affects photosynthesis and transpiration because biochemical aspects of photosynthesis are damaged in addition to stomatal conductance, the common link that controls both processes. However, most models incorporate O3 damage as a decrease in photosynthesis, with stomatal conductance responding linearly through the coupling of photosynthesis and conductance calculations. The observed differential effects of O3 on photosynthesis and conductance are not explicitly expressed in most modeling efforts, potentially causing larger decreases in transpiration. We ran five independent simulations of the CLM that compare current methods of incorporating O3 as a decrease in photosynthesis to a new method of separating photosynthesis and transpiration responses to O3 by independently modifying each parameter. We also determine the magnitude of both direct decreases to photosynthesis and transpiration and decreases caused by feedbacks in each parameter. Results show that traditional methods of modeling O3 effects by decreasing photosynthesis cause linear decreases in predicted transpiration that are ~20% larger than observed decreases in transpiration. However, modeled decreases in photosynthesis and transpiration that are incorporated independently of one another predict observed decreases in photosynthesis and improve transpiration predictions by ~13%. Therefore, models best predict carbon and water fluxes when incorporating O3-induced decreases in photosynthesis and transpiration independently.

Surgical Management of Metastatic Colorectal Cancer: A Single-Centre Experience on Oncological Outcomes of Pulmonary Resection vs Cytoreductive Surgery and HIPEC.

PubMed

Wong, Evelyn Yi Ting; Tan, Grace Hwei Ching; Ng, Deanna Wan Jie; Koh, Tina Puay Theng; Kumar, Mrinal; Teo, Melissa Ching Ching

2017-12-01

Metastasectomy is accepted as standard of care for selected patients with colorectal pulmonary metastases (CLM); however, the role of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) for colorectal peritoneal metastases (CPM) is not universally accepted. We aim to compare oncological outcomes of patients with CLM and CPM after pulmonary resection and CRS-HIPEC, respectively, by comparing overall survival (OS) and disease-free survival (DFS). A retrospective review of 49 CLM patients who underwent pulmonary resection, and 52 CPM patients who underwent CRS-HIPEC in a single institution from January 2003 to March 2015, was performed. The 5-year OS for CLM patients and CPM patients were 59.6 and 40.5%, respectively (p = 0.100), while the 5-year DFS were 24.0 and 14.2%, respectively (p = 0.173). CPM patients had longer median operative time (8.38 vs. 1.75 h, p < 0.001), median hospital stay (13 vs. 5 days, p < 0.001), a higher rate of intensive care unit (ICU) admissions (67.3 vs. 8.2%, p < 0.001), and a higher rate of high-grade complications (17.3 vs. 4.1%, p < 0.001). Multivariate analysis demonstrated that recurrent lung metastasis after metastasectomy was an independent prognostic factor for OS of CLM patients (OR = 0.045, 95%, CL 0.003-0.622, p = 0.021). There were no independent prognostic factors for OS in CPM patients by multivariate analysis. There were no independent prognostic factors for DFS in CLM patients by multivariate analysis, but peritoneal cancer index score, bladder involvement, and higher nodal stage at presentation of the initial malignancy were independent prognostic factors for DFS in CPM patients. OS and DFS for CPM patients after CRS and HIPEC are comparable to CLM patients after lung resection, although morbidity appears higher. The prognostic factors affecting survival after surgery are different between CPM and CLM patients and must be considered when selecting patients for metastasectomy.

Evaluation of the Community Land Model (CLM-Crop) in the United States Corn Belt

NASA Astrophysics Data System (ADS)

Chen, M.; Griffis, T.

2013-12-01

An accurate representation of crop phenology in land surface models is crucial for predicting the carbon, water and energy budgets of managed ecosystems. Soybean and corn are cultivated in approximately 600,000 km2 in the Corn Belt- an area greater than the entire State of California. Accurate prediction of the radiation, energy, and carbon budgets of this region is especially important for understanding its influence on radiative forcing, the thermodynamic properties of the atmospheric boundary layer, and changes in climate. Recently, key algorithms describing crop biophysics and interactive crop management (planting, fertilization, irrigation, harvesting) have been implemented in the Community Land Model (CLM-Crop). CLM-Crop provides a framework for prognostic simulation of crop phenology and evaluation of human management decisions under future climate scenarios. However, there is an important need to evaluate CLM-Crop against a broad range of agricultural site observations in order to understand its limitations and to help optimize the crop biophysical parameterization. Here we evaluated CLM-Crop version 4.5 at 9 AmeriFlux corn/soybean sites that are located within the United States Corn Belt. The following questions were addressed: 1) How well does CLM perform for the 9 crop sites with different management techniques (e.g., tillage vs. no-till, rainfed vs. irrigated)? 2) What are the model's strengths and weaknesses of simulating crop phenology, energy fluxes and carbon fluxes? 3) What steps are needed in order to improve the reliability of the CLM-Crop simulations? Our preliminary results indicate that CLM-Crop can simulate the radiation, energy, and carbon fluxes with reasonable accuracy during the mid growing season. The model performance degrades substantially during the early and late growing seasons, which we attribute to a bias in crop phenology. For instance, we observed that the simulated corn and soybean phenology (LAI) has an earlier phase than the observations by about 15 days at many sites. Here, we show how the optimization of carbon allocation and crop phenology influences the modeled radiation, energy, and carbon fluxes and discuss other model deficiencies associated with the crop biophysics scheme.

Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

2017-12-01

Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the reality. Our results demonstrate that with improved paramterization of crop growth, the ESMs can be powerful tools for realistically simulating agricultural production, which is gaining increasing interests and critical to study of global food security and food-energy-water nexus.

Evaluating the Community Land Model in a pine stand with shading manipulations and 13CO 2 labeling

DOE PAGES

Mao, Jiafu; Ricciuto, Daniel M.; Thornton, Peter E.; ...

2016-02-03

Carbon partitioning and flow through ecosystems regulates land surface atmosphere CO 2 exchange and thus is a key, albeit uncertain component of mechanistic models. The Partitioning in Trees and Soil (PiTS) experiment-model project tracked C partitioning through a young Pinus taeda stand following pulse-labeling with 13CO 2 and two levels of shading. The field component of this project provided process-oriented data that was used to evaluate and improve terrestrial biosphere model simulations of rapid shifts in carbon partitioning and hydrological dynamics under varying environmental conditions. Here we tested the performance of the Community Land Model version 4 (CLM4) in capturingmore » short-term carbon and water dynamics in relation to manipulative shading treatments, and the timing and magnitude of carbon fluxes through various compartments of the ecosystem. To constrain CLM4 to closely simulate pretreatment conditions, we calibrated select model parameters with the pretreatment observational data. Compared to CLM4 simulations with default parameters, CLM4 with calibrated model parameters was better able to simulate pretreatment vegetation carbon pools, light response curves, and other initial states and fluxes of carbon and water. Over a 3-week treatment period, the calibrated CLM4 generally reproduced the impacts of shading on average soil moisture at 15-95 cm depth, transpiration, relative change in stem carbon, and soil CO 2 efflux rate, although some discrepancies in the estimation of magnitudes and temporal evolutions existed. CLM4, however, was not able to track the progression of the 13CO 2 label from the atmosphere through foliage, phloem, roots or surface soil CO 2 efflux, even when optimized model parameters were used. This model bias arises, in part, from the lack of a short-term non-structural carbohydrate storage pool and progressive timing of within-plant transport, thus indicating a need for future work to improve the allocation routines in CLM4. Overall, these types of detailed evaluations of CLM4, paired with intensive field manipulations, can help to identify model strengths and weaknesses, model uncertainties, and additional observations necessary for future model development.« less

Cholesterol, Cholesterol-Lowering Medication Use, and Breast Cancer Outcome in the BIG 1-98 Study.

PubMed

Borgquist, Signe; Giobbie-Hurder, Anita; Ahern, Thomas P; Garber, Judy E; Colleoni, Marco; Láng, István; Debled, Marc; Ejlertsen, Bent; von Moos, Roger; Smith, Ian; Coates, Alan S; Goldhirsch, Aron; Rabaglio, Manuela; Price, Karen N; Gelber, Richard D; Regan, Meredith M; Thürlimann, Beat

2017-04-10

Purpose Cholesterol-lowering medication (CLM) has been reported to have a role in preventing breast cancer recurrence. CLM may attenuate signaling through the estrogen receptor by reducing levels of the estrogenic cholesterol metabolite 27-hydroxycholesterol. The impact of endocrine treatment on cholesterol levels and hypercholesterolemia per se may counteract the intended effect of aromatase inhibitors. Patients and Methods The Breast International Group (BIG) conducted a randomized, phase III, double-blind trial, BIG 1-98, which enrolled 8,010 postmenopausal women with early-stage, hormone receptor-positive invasive breast cancer from 1998 to 2003. Systemic levels of total cholesterol and use of CLM were measured at study entry and every 6 months up to 5.5 years. Cumulative incidence functions were used to describe the initiation of CLM in the presence of competing risks. Marginal structural Cox proportional hazards modeling investigated the relationships between initiation of CLM during endocrine therapy and outcome. Three time-to-event end points were considered: disease-free-survival, breast cancer-free interval, and distant recurrence-free interval. Results Cholesterol levels were reduced during tamoxifen therapy. Of 789 patients who initiated CLM during endocrine therapy, the majority came from the letrozole monotherapy arm (n = 318), followed by sequential tamoxifen-letrozole (n = 189), letrozole-tamoxifen (n = 176), and tamoxifen monotherapy (n = 106). Initiation of CLM during endocrine therapy was related to improved disease-free-survival (hazard ratio [HR], 0.79; 95% CI, 0.66 to 0.95; P = .01), breast cancer-free interval (HR, 0.76; 95% CI, 0.60 to 0.97; P = .02), and distant recurrence-free interval (HR, 0.74; 95% CI, 0.56 to 0.97; P = .03). Conclusion Cholesterol-lowering medication during adjuvant endocrine therapy may have a role in preventing breast cancer recurrence in hormone receptor-positive early-stage breast cancer. We recommend that these observational results be addressed in prospective randomized trials.

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

Wang, Guiling; Yu, Miao; Pal, Jeremy

This paper presents a regional climate system model RCM-CLM-CN-DV and its validation over Tropical Africa. The model development involves the initial coupling between the ICTP regional climate model RegCM4.3.4 (RCM) and the Community Land Model version 4 (CLM4) including models of carbon-nitrogen dynamics (CN) and vegetation dynamics (DV), and further improvements of the models. Model improvements derive from the new parameterization from CLM4.5 that addresses the well documented overestimation of gross primary production (GPP), a refinement of stress deciduous phenology scheme in CN that addresses a spurious LAI fluctuation for drought-deciduous plants, and the incorporation of a survival rule intomore » the DV model to prevent tropical broadleaf evergreens trees from growing in areas with a prolonged drought season. The impact of the modifications on model results is documented based on numerical experiments using various subcomponents of the model. The performance of the coupled model is then validated against observational data based on three configurations with increasing capacity: RCM-CLM with prescribed leaf area index and fractional coverage of different plant functional types (PFTs); RCM-CLM-CN with prescribed PFTs coverage but prognostic plant phenology; RCM-CLM-CN-DV in which both the plant phenology and PFTs coverage are simulated by the model. Results from these three models are compared against the FLUXNET up-scaled GPP and ET data, LAI and PFT coverages from remote sensing data including MODIS and GIMMS, University of Delaware precipitation and temperature data, and surface radiation data from MVIRI and SRB. Our results indicate that the models perform well in reproducing the physical climate and surface radiative budgets in the domain of interest. However, PFTs coverage is significantly underestimated by the model over arid and semi-arid regions of Tropical Africa, caused by an underestimation of LAI in these regions by the CN model that gets exacerbated through vegetation dynamics in RCM-CLM-CN-DV.« less

Optimization of conditions for thermal treatment of rice bran using an accelerator including an organo-iron compound.

PubMed

Kanno, Hikari; Tachibana, Naoya; Fukushima, Masami

2011-02-01

A method for thermal conversion of raw organic waste (ROW) to a compost-like material (CLM) with higher levels of unsaturated carbohydrates, nitrogen- and oxygen-containing compounds was developed, in which rice bran and an organo-iron compound were employed as a model ROW and the accelerator, respectively. To evaluate the qualities of CLMs, organic substances of an acid insoluble fraction of alkaline extracts (AIAEs) from a CLM were structurally characterized by elemental analysis, pyrolysis-gas chromatography/mass spectrometry and FT-IR. The levels of unsaturated carbohydrates, and nitrogen- and oxygen-containing compounds in the CLM samples were increased by long-term treatment (60°C for 5 days, 170°C for 3 days). In particular, the high lipid content of the AIAEs, which was indicative of inadequate digestion of CLM components, was dramatically reduced in the presence of the accelerator. Copyright © 2010 Elsevier Ltd. All rights reserved.

Direct and social genetic effects on body weight at 270 days and carcass and ham quality traits in heavy pigs.

PubMed

Rostellato, R; Sartori, C; Bonfatti, V; Chiarot, G; Carnier, P

2015-01-01

The aims of this study were to estimate covariance components for BW at 270 d (BW270) and carcass and ham quality traits in heavy pigs using models accounting for social effects and to compare the ability of such models to fit the data relative to models ignoring social interactions. Phenotypic records were from 9,871 pigs sired by 293 purebred boars mated to 456 crossbred sows. Piglets were born and reared at the same farm and randomly assigned at 60 d of age to groups (6.1 pigs per group on average) housed in finishing pens, each having an area of 6 m(2). The average additive genetic relationship among group mates was 0.11. Pigs were slaughtered at 277 ± 3 d of age and 169.7 ± 13.9 kg BW in groups of nearly 70 animals each. Four univariate animal models were compared: a basic model (M1) including only direct additive genetic effects, a model (M2) with nonheritable social group (pen) effects in addition to effects in M1, a model (M3) accounting for litter effects in addition to M2, and a model (M4) accounting for social genetic effects in addition to effects in M3. Restricted maximum likelihood estimates of covariance components were obtained for BW270; carcass backfat depth; carcass lean meat content (CLM); iodine number (IOD); and linoleic acid content (LIA) of raw ham subcutaneous fat; subcutaneous fat depth in the proximity of semimembranosus muscle (SFD1) and quadriceps femoris muscle (SFD2); and linear scores for ham round shape (RS), subcutaneous fat (SF), and marbling. Likelihood ratio tests indicated that, for all traits, M2 fit the data better than M1 and that M3 was superior to M2 except for SFD1 and SFD2. Model M4 was significantly better than M3 for BW270 (P < 0.001) and CLM, IOD, RS, and SF (P < 0.05). The contribution of social genetic effects to the total heritable variance was large for CLM and BW270, ranging from 33.2 to 35%, whereas the one for ham quality traits ranged from 6.8 (RS) to 11.2% (SF). Direct and social genetic effects on BW270 were uncorrelated, whereas there was a negative genetic covariance between direct and social effects on CLM, IOD, RS, and SF, which reduced the total heritable variance. This variance, measured relative to phenotypic variance, ranged from 21 (CLM) to 54% (BW270). Results indicate that social genetic effects affect variation in traits relevant for heavy pigs used in dry-cured hams manufacturing. Such effects should be exploited and taken into account in design of breeding programs for heavy pigs.

Effect of thiolated polymers to textural and mucoadhesive properties of vaginal gel formulations prepared with polycarbophil and chitosan.

PubMed

Cevher, Erdal; Sensoy, Demet; Taha, Mohamed A M; Araman, Ahmet

2008-01-01

The aim of this study was to design and evaluate of mucoadhesive gel formulations for the vaginal application of clomiphene citrate (CLM) for local treatment of human papilloma virus (HPV) infections. Chitosan (CHI) and polycarbophil (PC) were covalently modified using the thioglycolic acid and L-cysteine, respectively. The formation of thiol conjugates of chitosan (CHI-TG) and polycarbophil (PC-CYS) were confirmed by FT-IR analysis and PC-CYS and CHI-TG were found to have 148.42 +/- 4.16 and 41.17 +/- 2.34 micromol of thiol groups per gram of polymer, respectively. One percent CLM gels were prepared by combination of various concentrations of PC and CHI with thiolated conjugates of these polymers. Hardness, compressibility, elasticity, adhesiveness and cohesiveness of the gels were measured by Texture profile analysis and the vaginal mucoadhesion was investigated by mucoadhesion test. The increasing in the amount of the thiol conjugates was found to enhance the elasticity, cohesiveness, adhesiveness and mucoadhesion of the gel formulations but not their hardness and compressibility when compared to gels prepared using their respective parent formulations. Slower release rate of CLM from gels was achieved when the polymer concentrations were increased in the gel formulations. PC and its thiol conjugate were found to prolong the release of CLM longer than 70 h unlike gel formulations prepared using CHI and its thiol conjugate which were able to release CLM up to 12 h. Stability of CLM was preserved during the 3 month stability analysis under controlled room temperature and accelerated conditions.

Sensitivity of simulated South America Climate to the Land Surface Schemes in RegCM4

NASA Astrophysics Data System (ADS)

Llopart, Marta; da Rocha, Rosmeri; Reboita, Michelle; Cuadra, Santiago

2017-04-01

This work evaluates the impact of two land surface parameterizations on the simulated climate and its variability over South America (SA). Two numerical experiments using RegCM4 coupled with Biosphere-Atmosphere Transfer Scheme (RegBATS) and Community Land Model version 3.5 (RegCLM) land surface schemes are compared. For the period 1979-2008, RegCM4 simulations used 50 km horizontal grid spacing and the ERA-Interim reanalysis as initial and boundary conditions. For the period studied, both simulations represent the main observed spatial patterns of rainfall, air temperature and low level circulation over SA. However, concerning the precipitation intensity, RegCLM values are closer to the observations than RegBATS (it is in general, wetter) over most of SA. RegCLM also provides smaller biases for air temperature. Over the Amazon basin, the amplitudes of the annual cycles of the soil moisture, evapotranspiration and sensible heat flux are higher in RegBATS than in RegCLM. This indicates that RegBATS provides large amounts of water vapor to the atmosphere and has more available energy to increase the boundary layer and make it reach the level of free convection (higher sensible heat flux values) resulting in higher precipitation rates and a large wet bias. RegCLM is closer to the observations than RegBATS, presenting smaller wet and warm biases over the Amazon basin. On an interannual scale, the magnitudes of the anomalies of the precipitation and air temperature simulated by RegCLM are closer to the observations. In general, RegBATS simulates higher magnitude for the interannual variability signal.

A Model-Data Intercomparison of Carbon Fluxes, Pools, and LAI in the Community Land Model (CLM) and Alternative Carbon Allocation Schemes

NASA Astrophysics Data System (ADS)

Montane, F.; Fox, A. M.; Arellano, A. F.; Alexander, M. R.; Moore, D. J.

2016-12-01

Carbon (C) allocation to different plant tissues (leaves, stem and roots) remains a central challenge for understanding the global C cycle, as it determines C residence time. We used a diverse set of observations (AmeriFlux eddy covariance towers, biomass estimates from tree-ring data, and Leaf Area Index measurements) to compare C fluxes, pools, and Leaf Area Index (LAI) data with the Community Land Model (CLM). We ran CLM for seven temperate forests in North America (including evergreen and deciduous sites) between 1980 and 2013 using different C allocation schemes: i) standard C allocation scheme in CLM, which allocates C to the stem and leaves as a dynamic function of annual net primary productivity (NPP); ii) two fixed C allocation schemes, one representative of evergreen and the other one of deciduous forests, based on Luyssaert et al. 2007; iii) an alternative C allocation scheme, which allocated C to stem and leaves, and to stem and coarse roots, as a dynamic function of annual NPP, based on Litton et al. 2007. At our sites CLM usually overestimated gross primary production and ecosystem respiration, and underestimated net ecosystem exchange. Initial aboveground biomass in 1980 was largely overestimated for deciduous forests, whereas aboveground biomass accumulation between 1980 and 2011 was highly underestimated for both evergreen and deciduous sites due to the lower turnover rate in the sites than the one used in the model. CLM overestimated LAI in both evergreen and deciduous sites because the Leaf C-LAI relationship in the model did not match the observed Leaf C-LAI relationship in our sites. Although the different C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, one of the alternative C allocation schemes used (iii) gave more realistic stem C/leaf C ratios, and highly reduced the overestimation of initial aboveground biomass, and accumulated aboveground NPP for deciduous forests by CLM. Our results would suggest using different C allocation schemes for evergreen and deciduous forests. It is crucial to improve CLM in the near future to minimize data-model mismatches, and to address some of the current model structural errors and parameter uncertainties.

Evaluation of an operational real-time irrigation scheduling scheme for drip irrigated citrus fields in Picassent, Spain

NASA Astrophysics Data System (ADS)

Li, Dazhi; Hendricks-Franssen, Harrie-Jan; Han, Xujun; Jiménez Bello, Miguel Angel; Martínez Alzamora, Fernando; Vereecken, Harry

2017-04-01

Irrigated agriculture accounts worldwide for 40% of food production and 70% of fresh water withdrawals. Irrigation scheduling aims to minimize water use while maintaining the agricultural production. In this study we were concerned with the real-time automatic control of irrigation, which calculates daily water allocation by combining information from soil moisture sensors and a land surface model. The combination of soil moisture measurements and predictions by the Community Land Model (CLM) using sequential data assimilation (DA) is a promising alternative to improve the estimate of soil and plant water status. The LETKF (Local Ensemble Transform Kalman Filter) was chosen to assimilate soil water content measured by FDR (Frequency Domain Reflectometry) into CLM and improve the initial (soil moisture) conditions for the next model run. In addition, predictions by the GFS (Global Forecast System) atmospheric simulation model were used as atmospheric input data for CLM to predict an ensemble of possible soil moisture evolutions for the next days. The difference between predicted and target soil water content is defined as the water deficit, and the irrigation amount was calculated by the integrated water deficit over the root zone. The corresponding irrigation time to apply the required water was introduced in SCADA (supervisory control and data acquisition system) for each citrus field. In total 6 fields were irrigated according our optimization approach including data assimilation (CLM-DA) and there were also 2 fields following the FAO (Food and Agriculture Organization) water balance method and 4 fields controlled by farmers as reference. During the real-time irrigation campaign in Valencia from July to October in 2015 and June to October in 2016, the applied irrigation amount, stem water potential and soil moisture content were recorded. The data indicated that 5% 20% less irrigation water was needed for the CLM-DA scheduled fields than for the other fields following the FAO or farmers' method. Stem water potential data indicated that the CLM-DA fields were not suffering from water stress during most of the irrigation period. Even though the CLM-DA fields received the least irrigation water, the orange production was not suppressed either. Our results show the water saving potential of the CLM-DA method compared to other traditional irrigation methods.

[Taste disturbance after general anesthesia with classic laryngeal mask airway (CLM)].

PubMed

Arimune, Mutsuaki

2007-07-01

A 27-year-old man underwent the right knee joint operation under general anesthesia with CLM. After the operation, he complained of taste disturbance of the left side of the tongue. We measured electrical taste threshold and the serum level of zinc, copper and iron. The taste threshold was elevated in the two nerve areas of the left side of the tongue (chorda tympani, N. glossopharyngeus) and the serum levels of zinc and iron were low. We concluded that he had been short of zinc and iron and the insertion of CLM had triggered taste disturbance.

Crop physiology calibration in the CLM

DOE PAGES

Bilionis, I.; Drewniak, B. A.; Constantinescu, E. M.

2015-04-15

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

Crop physiology calibration in the CLM

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

Bilionis, I.; Drewniak, B. A.; Constantinescu, E. M.

Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurementsmore » of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.« less

Assessment of simulated water balance from Noah, Noah-MP, CLM, and VIC over CONUS using the NLDAS test bed

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

Cai, Xitian; Yang, Zong-Liang; Xia, Youlong

2014-12-27

This study assesses the hydrologic performance of four land surface models (LSMs) for the conterminous United States using the North American Land Data Assimilation System (NLDAS) test bed. The four LSMs are the baseline community Noah LSM (Noah, version 2.8), the Variable Infiltration Capacity (VIC, version 4.0.5) model, the substantially augmented Noah LSM with multiparameterization options (hence Noah-MP), and the Community Land Model version 4 (CLM4). All four models are driven by the same NLDAS-2 atmospheric forcing. Modeled terrestrial water storage (TWS), streamflow, evapotranspiration (ET), and soil moisture are compared with each other and evaluated against the identical observations. Relativemore » to Noah, the other three models offer significant improvements in simulating TWS and streamflow and moderate improvements in simulating ET and soil moisture. Noah-MP provides the best performance in simulating soil moisture and is among the best in simulating TWS, CLM4 shows the best performance in simulating ET, and VIC ranks the highest in performing the streamflow simulations. Despite these improvements, CLM4, Noah-MP, and VIC exhibit deficiencies, such as the low variability of soil moisture in CLM4, the fast growth of spring ET in Noah-MP, and the constant overestimation of ET in VIC.« less

Validation on wheat response to irrigation, CO2 and nitrogen fertilization in the Community Land Model

NASA Astrophysics Data System (ADS)

Lu, Y.

2016-12-01

Wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of earth's croplands. As such, it plays an important role in soil carbon balance, and land-atmosphere interactions in these key regions. Understanding whether the Community Land Model (CLM) appropriate response to elevated CO2 and different levels of nitrogen fertilization and irrigation is a crucial question. We participated the AgMIP-wheat project and run 72 simulations at Maricopa spring wheat FACE sites and five winter wheat sites in North America forcing with site observed meteorology data. After calibration on the phenology, carbon allocation, and soil hydrology parameters, wheat in CLM45 has reasonable response to irrigation and elevated CO2. However, wheat in CLM45 has no response to low or high N fertilization because the low amount of N fertilization is sufficient for wheat growth in CLM45. We plan to further extend the same simulations for CLM5 (will release in Fall 2016), which has substantial improvements on soil hydrology (improved soil evaporation and plant hydraulic parameterization) and nitrogen dynamics (flexible leaf CN ratio and Vcmax25, plant pays for carbon to get nitrogen). We will evaluate the uncertainties of wheat response to nitrogen fertilization, irrigation, CO2 due to model improvements.

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

DOE PAGES

Duarte, Henrique F.; Raczka, Brett M.; Ricciuto, Daniel M.; ...

2017-09-28

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site ormore » at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13C: 12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball–Berry stomatal conductance slope ( m bb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised m bb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. Here, this study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.« less

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

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

Duarte, Henrique F.; Raczka, Brett M.; Ricciuto, Daniel M.

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site ormore » at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13C: 12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball–Berry stomatal conductance slope ( m bb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised m bb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. Here, this study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.« less

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

NASA Astrophysics Data System (ADS)

Duarte, Henrique F.; Raczka, Brett M.; Ricciuto, Daniel M.; Lin, John C.; Koven, Charles D.; Thornton, Peter E.; Bowling, David R.; Lai, Chun-Ta; Bible, Kenneth J.; Ehleringer, James R.

2017-09-01

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest site in the Pacific Northwest region of the United States (Wind River AmeriFlux site), characterized by a Mediterranean climate that subjects trees to water stress each summer. CLM was driven by site-observed meteorology and calibrated primarily using parameter values observed at the site or at similar stands in the region. Key model adjustments included parameters controlling specific leaf area and stomatal conductance. Default values of these parameters led to significant underestimation of gross primary production, overestimation of evapotranspiration, and consequently overestimation of photosynthetic 13C discrimination, reflected in reduced 13C : 12C ratios of carbon fluxes and pools. Adjustments in soil hydraulic parameters within CLM were also critical, preventing significant underestimation of soil water content and unrealistic soil moisture stress during summer. After calibration, CLM was able to simulate energy and carbon fluxes, leaf area index, biomass stocks, and carbon isotope ratios of carbon fluxes and pools in reasonable agreement with site observations. Overall, the calibrated CLM was able to simulate the observed response of canopy conductance to atmospheric vapor pressure deficit (VPD) and soil water content, reasonably capturing the impact of water stress on ecosystem functioning. Both simulations and observations indicate that stomatal response from water stress at Wind River was primarily driven by VPD and not soil moisture. The calibration of the Ball-Berry stomatal conductance slope (mbb) at Wind River aligned with findings from recent CLM experiments at sites characterized by the same plant functional type (needleleaf evergreen temperate forest), despite significant differences in stand composition and age and climatology, suggesting that CLM could benefit from a revised mbb value of 6, rather than the default value of 9, for this plant functional type. Conversely, Wind River required a unique calibration of the hydrology submodel to simulate soil moisture, suggesting that the default hydrology has a more limited applicability. This study demonstrates that carbon isotope data can be used to constrain stomatal conductance and intrinsic water use efficiency in CLM, as an alternative to eddy covariance flux measurements. It also demonstrates that carbon isotopes can expose structural weaknesses in the model and provide a key constraint that may guide future model development.

Embryonic origin of primary colon cancer predicts survival in patients undergoing ablation for colorectal liver metastases.

PubMed

Yamashita, S; Odisio, B C; Huang, S Y; Kopetz, S E; Ahrar, K; Chun, Y S; Conrad, C; Aloia, T A; Gupta, S; Harmoush, S; Hicks, M E; Vauthey, J-N

2017-06-01

In patients with primary colorectal cancer (CRC) or unresectable metastatic CRC, midgut embryonic origin is associated with worse prognosis. The impact of embryonic origin on survival after ablation of colorectal liver metastases (CLM) is unclear. We identified 74 patients with CLM who underwent percutaneous ablation during 2004-2015. Survival and recurrence after ablation of CLM from midgut origin (n = 18) and hindgut origin (n = 56) were analyzed. Prognostic value of embryonic origin was evaluated. Recurrence-free survival (RFS) and overall survival (OS) after percutaneous ablation were worse in patients from midgut origin (3-year RFS: 5.6% vs. 24%, P = 0.004; 3-year OS: 25% vs. 70%, P 0.001). In multivariable analysis, factors associated with worse OS were midgut origin (hazard ratio [HR] 4.87, 95% CI 2.14-10.9, P 0.001), multiple CLM (HR 2.35, 95% CI 1.02-5.39, P = 0.044), and RAS mutation (HR 2.78, 95% CI 1.25-6.36, P = 0.013). At a median follow-up of 25 months, 56 patients (76%) had developed recurrence, 16 (89%) with midgut origin and 40 (71%) with hindgut origin (P = 0.133). Recurrent disease was treated with local therapy in 20 patients (36%), 2 (13%) with midgut origin and 18 (45%) with hindgut origin (P = 0.022). Compared to CLM from hindgut origin tumors, CLM from midgut origin tumors were associated with worse survival after ablation, which was partly attributable to the fact that patients with hindgut origin were more frequently candidates for local therapy at recurrence. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

NASA Astrophysics Data System (ADS)

Bonan, Gordon B.; Patton, Edward G.; Harman, Ian N.; Oleson, Keith W.; Finnigan, John J.; Lu, Yaqiong; Burakowski, Elizabeth A.

2018-04-01

Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin-Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.

Sensitivity of simulated South America climate to the land surface schemes in RegCM4

NASA Astrophysics Data System (ADS)

Llopart, Marta; da Rocha, Rosmeri P.; Reboita, Michelle; Cuadra, Santiago

2017-12-01

This work evaluates the impact of two land surface parameterizations on the simulated climate and its variability over South America (SA). Two numerical experiments using RegCM4 coupled with the Biosphere-Atmosphere Transfer Scheme (RegBATS) and the Community Land Model version 3.5 (RegCLM) land surface schemes are compared. For the period 1979-2008, RegCM4 simulations used 50 km horizontal grid spacing and the ERA-Interim reanalysis as initial and boundary conditions. For the period studied, both simulations represent the main observed spatial patterns of rainfall, air temperature and low level circulation over SA. However, with regard to the precipitation intensity, RegCLM values are closer to the observations than RegBATS (it is wetter in general) over most of SA. RegCLM also produces smaller biases for air temperature. Over the Amazon basin, the amplitudes of the annual cycles of the soil moisture, evapotranspiration and sensible heat flux are higher in RegBATS than in RegCLM. This indicates that RegBATS provides large amounts of water vapor to the atmosphere and has more available energy to increase the boundary layer thickness and cause it to reach the level of free convection (higher sensible heat flux values) resulting in higher precipitation rates and a large wet bias. RegCLM is closer to the observations than RegBATS, presenting smaller wet and warm biases over the Amazon basin. On an interannual scale, the magnitudes of the anomalies of the precipitation and air temperature simulated by RegCLM are closer to the observations. In general, RegBATS simulates higher magnitude for the interannual variability signal.

Investigation of a tubular dual-stator flux-switching permanent-magnet linear generator for free-piston energy converter

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Tong, Chengde; Yu, Bin; Zhu, Shaohong; Zhu, Jianguo

2015-05-01

This paper describes a tubular dual-stator flux-switching permanent-magnet (PM) linear generator for free-piston energy converter. The operating principle, topology, and design considerations of the machine are investigated. Combining the motion characteristic of free-piston Stirling engine, a tubular dual-stator PM linear generator is designed by finite element method. Some major structural parameters, such as the outer and inner radii of the mover, PM thickness, mover tooth width, tooth width of the outer and inner stators, etc., are optimized to improve the machine performances like thrust capability and power density. In comparison with conventional single-stator PM machines like moving-magnet linear machine and flux-switching linear machine, the proposed dual-stator flux-switching PM machine shows advantages in higher mass power density, higher volume power density, and lighter mover.

Estimating the relative contributions of human withdrawals and climate variability to changes in groundwater

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2014-12-01

Estimating the relative contributions of human withdrawals and climate variability to changes in groundwater is a challenging task at present. One method that has been used recently is a model-data synthesis combining GRACE total water storage estimates with simulated water storage estimates from land surface models. In this method, water storage changes due to natural climate variations simulated by a model are removed from total water storage changes observed by GRACE; the residual is then interpreted as anthropogenic groundwater change. If the modeled water storage estimate contains systematic errors, these errors will also be present in the residual groundwater estimate. For example, simulations performed with the Community Land Model (CLM; the land component of the Community Earth System Model) generally show a weak (as much as 50% smaller) seasonal cycle of water storage in semi-arid regions when compared to GRACE satellite water storage estimates. This bias propagates into GRACE-CLM anthropogenic groundwater change estimates, which then exhibit unphysical seasonal variability. The CLM bias can be traced to the parameterization of soil evaporative resistance. Incorporating a new soil resistance parameterization in CLM greatly reduces the seasonal bias with respect to GRACE. In this study, we compare the improved CLM water storage estimates to GRACE and discuss the implications for estimates of anthropogenic groundwater withdrawal, showing examples for the Middle East and Southwestern United States.

Prospective Evaluation of Intrahepatic Microscopic Occult Tumor Foci in Patients with Numerous Colorectal Liver Metastases.

PubMed

Vigano, Luca; Di Tommaso, Luca; Mimmo, Antonio; Sollai, Mauro; Cimino, Matteo; Donadon, Matteo; Roncalli, Massimo; Torzilli, Guido

2018-06-07

Patients with numerous colorectal liver metastases (CLM) have high risk of early recurrence after liver resection (LR). The presence of intrahepatic occult microscopic metastases missed by imaging has been hypothesized, but it has never been assessed by pathology analyses. All patients with > 10 CLM who underwent LR between September 2015 and September 2016 were considered. A large sample of liver without evidence of disease ("healthy liver") was taken from the resected specimen and sent to the pathologist. One mm-thick sections were analyzed. Any metastasis, undetected by preoperative and intraoperative imaging, but identified by the pathologist was classified as occult microscopic metastasis. Ten patients were prospectively enrolled (median number of CLM n = 15). In a per-lesion analysis, the sensitivity of computed tomography and magnetic resonance imaging was 91 and 98% respectively. The pathology examination confirmed all the CLM. All patients had an adequate sample of "healthy liver" (median number of examined blocks per sample n = 14 [5-33]). No occult microscopic metastases were detected. After a median follow-up of 15 months, 5 patients were disease-free. Recurrence was hepatic and bilobar in all patients. Clinically relevant occult microscopic disease in patients with numerous CLM is excluded. These results support the indication to resection in such patients and exclude the need for de principe major hepatectomy to increase the completeness of surgery. © 2018 S. Karger AG, Basel.

A microbial biogeochemistry network for soil carbon and nitrogen cycling and methane flux: model structure and application to Asia

NASA Astrophysics Data System (ADS)

Xu, X.; Song, C.; Wang, Y.; Ricciuto, D. M.; Lipson, D.; Shi, X.; Zona, D.; Song, X.; Yuan, F.; Oechel, W. C.; Thornton, P. E.

2017-12-01

A microbial model is introduced for simulating microbial mechanisms controlling soil carbon and nitrogen biogeochemical cycling and methane fluxes. The model is built within the CN (carbon-nitrogen) framework of Community Land Model 4.5, named as CLM-Microbe to emphasize its explicit representation of microbial mechanisms to biogeochemistry. Based on the CLM4.5, three new pools were added: bacteria, fungi, and dissolved organic matter. It has 11 pools and 34 transitional processes, compared with 8 pools and 9 transitional flow in the CLM4.5. The dissolve organic carbon was linked with a new microbial functional group based methane module to explicitly simulate methane production, oxidation, transport and their microbial controls. Comparing with CLM4.5-CN, the CLM-Microbe model has a number of new features, (1) microbial control on carbon and nitrogen flows between soil carbon/nitrogen pools; (2) an implicit representation of microbial community structure as bacteria and fungi; (3) a microbial functional-group based methane module. The model sensitivity analysis suggests the importance of microbial carbon allocation parameters on soil biogeochemistry and microbial controls on methane dynamics. Preliminary simulations validate the model's capability for simulating carbon and nitrogen dynamics and methane at a number of sites across the globe. The regional application to Asia has verified the model in simulating microbial mechanisms in controlling methane dynamics at multiple scales.

Development and analysis of a leak-based blast attenuator and scaling laws for primary blast peak overpressure for a large caliber muzzleloaded cannon

NASA Astrophysics Data System (ADS)

Carson, Robert Andrew

One of the primary aspects of the research and development work carried out at Benet Laboratories is the Soldier. Maintenance of their health in the field is the first priority while the second priority is the enhancement of their performance. Therefore, a new concept for a weapon system that targets these two priorities is highly desirable. This is the case with a new concept that can reduce the peak overpressure without the use of a muzzle device for a muzzle loaded cannon system. Such a novel concept was developed in this thesis through the application of propellant leak into the precursor region, i.e., when the projectile is still in the bore. A 3D hydrocode (ALE3D) was employed to predict the blast overpressure for the baseline and propellant leak configurations. However, a 3D hydrocode is computationally very expensive to predict peak overpressure in the far-field and an efficient method to predict peak overpressure in the far-field is of significance. Therefore, scaling laws for primary blast peak overpressure were also developed in this thesis. Initially, two propellant leak concepts were examined. A bulge leak method and a channel leak method, which were compared to the baseline configuration. The initial channel leak configuration (referred to as CLM-1) significantly reduced the exit pressure ratio during projectile ejection, and thereby, resulted in a weaker blast. This in-turn substantially attenuated the peak overpressure to the rear of the muzzle without the aid of a muzzle device while having a marginal loss in the projectile exit velocity. For CLM-1, at one monitored location with the largest peak overpressure, a reduction of about 38% in peak overpressure was observed as compared to the baseline case. In order to compare different leak configurations, a performance metric was defined by comparing the ratio of peak overpressure and projectile exit velocity for a leak configuration to that for the baseline configuration. This metric was referred to as the Figure of Merit (FoM) and defined for any probe location. An average FoM was also defined based on the average of local FoM over different locations/probes. The greater the FoM is above zero, the better the configuration. The average FoM for the CLM-1 configuration was 0.221. In addition to FoM, shock structure and strength were also analyzed for the bulge and channel configurations at both the precursor and blast stages. With the success of the CLM-1 configuration, we then performed a parametric study of the channel leak geometry and examined the effect of different geometric parameters on peak overpressure attenuation. The idea was to further improve the performance of the channel leak method. We divided our parametric study into five groups (i.e., A through E), referred to as CLM-A through CLM-E configurations. The focus in these five groups was on geometric parameters that were expected to be the most influential or relevant. Three relevant geometric parameters were considered in this work. In groups A and B, we focused on channel leak volume. Group C analyzed the effect of channel length while groups D and E investigated the effect of aspect ratio. The five groups were ordered in this way because we anticipated the total leak volume to be the most influential parameter, then the channel length which was followed by the aspect ratio. The total leak volume of 7.5% resulted in a relatively high average FoM. On the other hand, the use of channels with a shorter length was found to be detrimental while a lower value of aspect ratio was beneficial. Three leak configurations of CLM-A1, CLM-E1 and CLM-E2 provided excellent peak overpressure attenuation (i.e., above 45% and up to 63%). Each led to an average FoM above 0.5 while CLM-E configurations resulted in lower local FoM for probes near the muzzle and higher FoM for probes farther from the muzzle, and thus, a higher variation of FoM over the probes. The average FoM based on the far-field probes was about 0.575 and 0.560 for CLM-E1 and CLM-E2, respectively, and 0.520 for CLM-A1. Blast structure and strength were also analyzed for these three configurations. In the last part of this thesis, we focused on the baseline and CLM-A1 configurations in order to develop scaling laws for the primary blast peak overpressure. Two different power-law scaling techniques were considered. In the first power-law, scaling parameters were defined from the muzzle center. The second power-law scaling was defined based on the blast center. The muzzle center based power-law has been used in the past while the blast center based power-law is a newly developed scaling law in this thesis. For the baseline configuration, both scaling laws performed well and for many locations absolute difference was below 10%. For the CLM-A1 configuration, blast center based power-law predictions were better than those from the muzzle center based power-law and showed a better overall correlation with the ALE3D predictions.

Finnish policy approach and measures for the promotion of sustainability in contaminated land management.

PubMed

Reinikainen, Jussi; Sorvari, Jaana; Tikkanen, Sarianne

2016-12-15

The importance of sustainability considerations in contaminated land management (CLM) is highlighted in policy frameworks all around the world. It means that while the reduction of risks to human health and the environment remains the main goal of CLM, a variety of other environmental factors as well as economic and social aspects have an increasing role in decision making. The success of finding the right balance between these considerations and incorporating them in the risk management approach defines the overall sustainability of the outcome. Although the concept and principles of sustainable CLM are already widely accepted, they have not been fully realized in national procedures. According to several studies this often results from the lack of explicit policy measures. A sound policy framework in conjunction with functional policy instruments is therefore a prerequisite for the attainment of sustainable practices. In Finland, the environmental administration along with other key stakeholder groups, including regional authorities, landowners, consultants, industries, research institutes and academia, has developed a national strategy and associated policy measures in order to promote sustainable CLM. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of the coupled COSMO-CLM+NEMO-Nordic model with focus on North and Baltic seas

NASA Astrophysics Data System (ADS)

Lenhardt, J.; Pham, T. V.; Früh, B.; Brauch, J.

2017-12-01

The region east of the Baltic Sea has been identified as a hot-spot of climate change by Giorgi, 2006, on the base of temperature and precipitation variability. For this purpose, the atmosphere model COSMO-CLM has been coupled to the ocean model NEMO, including the sea ice model LIM3, via the OASIS3-MCT coupler (Pham et al., 2014). The coupler interpolates heat, fresh water, momentum fluxes, sea level pressure and the fraction of sea ice at the interface in space and time. Our aim is to find an optimal configuration of the already existing coupled regional atmospheric-ocean model COSMO-CLM+NEMO-Nordic. So far results for the North- and Baltic seas show that the coupled run has large biases compared with the E-OBS reference data. Therefore, additional simulation evaluations are planned by the use of independent satellite observation data (e.g. Copernicus, EURO4M). We have performed a series of runs with the coupled COSMO-CLM+NEMO-Nordic model to find out about differences of model outputs due to different coupling time steps. First analyses of COSMO-CLM 2m temperatures let presume that different coupling time steps have an impact on the results of the coupled model run. Additional tests over a longer period of time are conducted to understand whether the signal-to-noise ratio could influence the bias. The results will be presented in our poster.

Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

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

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra

Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by themore » observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.« less

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

NASA Astrophysics Data System (ADS)

Montané, Francesc; Fox, Andrew M.; Arellano, Avelino F.; MacBean, Natasha; Alexander, M. Ross; Dye, Alex; Bishop, Daniel A.; Trouet, Valerie; Babst, Flurin; Hessl, Amy E.; Pederson, Neil; Blanken, Peter D.; Bohrer, Gil; Gough, Christopher M.; Litvak, Marcy E.; Novick, Kimberly A.; Phillips, Richard P.; Wood, Jeffrey D.; Moore, David J. P.

2017-09-01

How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.-iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m-2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m-2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C-LAI relationship in the model did not match the observed leaf C-LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem / Cleaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

DOE PAGES

Montané, Francesc; Fox, Andrew M.; Arellano, Avelino F.; ...

2017-09-22

How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocationmore » schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m -2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m -2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the observed leaf C–LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic C stem/C leaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.« less

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

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

Montané, Francesc; Fox, Andrew M.; Arellano, Avelino F.

How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocationmore » schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m -2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m -2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the observed leaf C–LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic C stem/C leaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.« less

Modeling of Geometric Error in Linear Guide Way to Improved the vertical three-axis CNC Milling machine’s accuracy

NASA Astrophysics Data System (ADS)

Kwintarini, Widiyanti; Wibowo, Agung; Arthaya, Bagus M.; Yuwana Martawirya, Yatna

2018-03-01

The purpose of this study was to improve the accuracy of three-axis CNC Milling Vertical engines with a general approach by using mathematical modeling methods of machine tool geometric errors. The inaccuracy of CNC machines can be caused by geometric errors that are an important factor during the manufacturing process and during the assembly phase, and are factors for being able to build machines with high-accuracy. To improve the accuracy of the three-axis vertical milling machine, by knowing geometric errors and identifying the error position parameters in the machine tool by arranging the mathematical modeling. The geometric error in the machine tool consists of twenty-one error parameters consisting of nine linear error parameters, nine angle error parameters and three perpendicular error parameters. The mathematical modeling approach of geometric error with the calculated alignment error and angle error in the supporting components of the machine motion is linear guide way and linear motion. The purpose of using this mathematical modeling approach is the identification of geometric errors that can be helpful as reference during the design, assembly and maintenance stages to improve the accuracy of CNC machines. Mathematically modeling geometric errors in CNC machine tools can illustrate the relationship between alignment error, position and angle on a linear guide way of three-axis vertical milling machines.

Linear positioning laser calibration setup of CNC machine tools

NASA Astrophysics Data System (ADS)

Sui, Xiulin; Yang, Congjing

2002-10-01

The linear positioning laser calibration setup of CNC machine tools is capable of executing machine tool laser calibraiotn and backlash compensation. Using this setup, hole locations on CNC machien tools will be correct and machien tool geometry will be evaluated and adjusted. Machien tool laser calibration and backlash compensation is a simple and straightforward process. First the setup is to 'find' the stroke limits of the axis. Then the laser head is then brought into correct alignment. Second is to move the machine axis to the other extreme, the laser head is now aligned, using rotation and elevation adjustments. Finally the machine is moved to the start position and final alignment is verified. The stroke of the machine, and the machine compensation interval dictate the amount of data required for each axis. These factors determine the amount of time required for a through compensation of the linear positioning accuracy. The Laser Calibrator System monitors the material temperature and the air density; this takes into consideration machine thermal growth and laser beam frequency. This linear positioning laser calibration setup can be used on CNC machine tools, CNC lathes, horizontal centers and vertical machining centers.

Comparisons between designs for single-sided linear electric motors: Homopolar synchronous and induction

NASA Astrophysics Data System (ADS)

Nondahl, T. A.; Richter, E.

1980-09-01

A design study of two types of single sided (with a passive rail) linear electric machine designs, namely homopolar linear synchronous machines (LSM's) and linear induction machines (LIM's), is described. It is assumed the machines provide tractive effort for several types of light rail vehicles and locomotives. These vehicles are wheel supported and require tractive powers ranging from 200 kW to 3735 kW and top speeds ranging from 112 km/hr to 400 km/hr. All designs are made according to specified magnetic and thermal criteria. The LSM advantages are a higher power factor, much greater restoring forces for track misalignments, and less track heating. The LIM advantages are no need to synchronize the excitation frequency precisely to vehicle speed, simpler machine construction, and a more easily anchored track structure. The relative weights of the two machine types vary with excitation frequency and speed; low frequencies and low speeds favor the LSM.

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

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

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

Repeat liver resection for recurrent colorectal metastases: a single-centre, 13-year experience.

PubMed

Battula, Narendra; Tsapralis, Dimitrios; Mayer, David; Isaac, John; Muiesan, Paolo; Sutcliffe, Robert P; Bramhall, Simon; Mirza, Darius; Marudanayagam, Ravi

2014-02-01

Isolated intrahepatic recurrence is noted in up to 40% of patients following curative liver resection for colorectal liver metastases (CLM). The aims of this study were to analyse the outcomes of repeat hepatectomy for recurrent CLM and to identify factors predicting survival. Data for all liver resections for CLM carried out at one centre between 1998 and 2011 were analysed. A total of 1027 liver resections were performed for CLM. Of these, 58 were repeat liver resections performed in 53 patients. Median time intervals were 10.5 months between the primary resection and first hepatectomy, and 15.4 months between the first and repeat hepatectomies. The median tumour size was 3.0 cm and the median number of tumours was one. Six patients had a positive margin (R1) resection following first hepatectomy. There were no perioperative deaths. Significant complications included transient liver dysfunction in one and bile leak in two patients. Rates of 1-, 3- and 5-year overall survival following repeat liver resection were 85%, 61% and 52%, respectively, at a median follow-up of 23 months. R1 resection at first hepatectomy (P = 0.002), a shorter time interval between the first and second hepatectomies (P = 0.02) and the presence of extrahepatic disease (P = 0.02) were associated with significantly worse overall survival. Repeat resection of CLM is safe and can achieve longterm survival in carefully selected patients. A preoperative knowledge of poor prognostic factors helps to facilitate better patient selection. © 2013 International Hepato-Pancreato-Biliary Association.

Cure model survival analysis after hepatic resection for colorectal liver metastases.

PubMed

Cucchetti, Alessando; Ferrero, Alessandro; Cescon, Matteo; Donadon, Matteo; Russolillo, Nadia; Ercolani, Giorgio; Stacchini, Giacomo; Mazzotti, Federico; Torzilli, Guido; Pinna, Antonio Daniele

2015-01-01

Statistical cure is achieved when a patient population has the same mortality as cancer-free individuals; however, data regarding the probability of cure after hepatectomy of colorectal liver metastases (CLM) have never been provided. We aimed to assess the probability of being statistically cured from CLM by hepatic resection. Data from 1,012 consecutive patients undergoing curative resection for CLM (2001-2012) were used to fit a nonmixture cure model to compare mortality after surgery to that expected for the general population matched by sex and age. The 5- and 10-year disease-free survival was 18.9 and 15.8 %; the corresponding overall survival was 44.3 and 32.7 %. In the entire study population, the probability of being cured from CLM was 20 % (95 % confidence interval 16.5-23.5). After the first year, the mortality excess of resected patients, in comparison to the general population, starts to decline until it approaches zero 6 years after surgery. After 6.48 years, patients alive without tumor recurrence can be considered cured with 99 % certainty. Multivariate analysis showed that cure probabilities range from 40.9 % in patients with node-negative primary tumors and metachronous presentation of a single lesion <3 cm, to 1.5 % in patients with node positivity, and synchronous presentation of multiple, large CLMs. A model for the calculation of a cure fraction for each possible clinical scenario is provided. Using a cure model, the present results indicate that statistical cure of CLM is possible after hepatectomy; providing this information can help clinicians give more precise answer to patients' questions.

The prognostic significance of lymphatics in colorectal liver metastases.

PubMed

Muralidharan, Vijayaragavan; Nguyen, Linh; Banting, Jonathan; Christophi, Christopher

2014-01-01

Background. Colorectal Cancer (CRC) is the most common form of cancer diagnosed in Australia across both genders. Approximately, 40%-60% of patients with CRC develop metastasis, the liver being the most common site. Almost 70% of CRC mortality can be attributed to the development of liver metastasis. This study examines the pattern and density of lymphatics in colorectal liver metastases (CLM) as predictors of survival following hepatic resection for CLM. Methods. Patient tissue samples were obtained from the Victorian Cancer Biobank. Immunohistochemistry was used to examine the spatial differences in blood and lymphatic vessel densities between different regions within the tumor (CLM) and surrounding host tissue. Lymphatic vessel density (LVD) was assessed as a potential prognostic marker. Results. Patients with low lymphatic vessel density in the tumor centre, tumor periphery, and adjacent normal liver demonstrated a significant disease-free survival advantage compared to patients with high lymphatic vessel density (P = 0.01, P > 0.01, and P = 0.05, resp.). Lymphatic vessel density in the tumor centre and periphery and adjacent normal liver was an accurate predictive marker of disease-free survival (P = 0.05). Conclusion. Lymphatic vessel density in CLM appears to be an accurate predictor of recurrence and disease-free survival.

Numerical study of the Kitaev-Heisenberg chain

NASA Astrophysics Data System (ADS)

Agrapidis, Cliò Efthimia; van den Brink, Jeroen; Nishimoto, Satoshi

2018-05-01

We study the one-dimensional Kitaev-Heisenberg model as a possible realization of magnetic degrees of freedom of the K-intercalated honeycomb-lattice ruthenium trichloride α-RuCl3, denoted as K0.5RuClm. First, we discuss the possible charge ordering pattern in K0.5RuClm, where half of the j =1/2 spins are replaced by nonmagnetic ions in the honeycomb layer. Next, we investigate the low-energy excitations of the 1D Kitaev-Heisenberg model by calculating the dynamical spin structure factor using the Lanczos exact-diagonalization method. In the vicinity of Kitaev limit, there exist two well-separated dispersions. The bandwidth of each dispersion depends on the Heisenberg and Kitaev terms. This result may be relevant to the low-lying magnetic excitations of K0.5RuClm.

Correlations between the enantio- and regio-selective metabolisms of warfarin.

PubMed

Takahashi, Harumi; Ohara, Minami; Shibata, Soichi; Lee, Ming Ta Michael; Cavallari, Larisa H; Nutescu, Edith A; Scordo, Maria G; Pengo, Vittorio; Padrini, Roberto; Atsuda, Koichiro; Matsubara, Hajime; Chen, Yuan Tsong; Echizen, Hirotoshi

2017-01-01

To clarify whether the activities of multiple CYPs associated with warfarin metabolism would be correlated with each other. Oral clearances (CLpo) of warfarin enantiomers were estimated in 378 Chinese, Caucasians and African-Americans. The partial metabolic clearances (CLm) for 7-hydroxywarfarin enantiomers were also measured. In addition, CLpo and CLm were determined in a patient on warfarin and rifampicin. Correlations between CLpo for warfarin enantiomers existed across the three populations. In addition, there was a significant correlation between the CLm for 7-hydroxylation of warfarin enantiomers. Under induced conditions by rifampicin, there were significant correlations between the enantio- and regio-selective metabolisms of warfarin. Metabolic activities of CYP2C9, CYP1A2 and CYP3A4 may be regulated by common transcriptional mechanism(s).

A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes.

PubMed

Vogl, Gregory W; Weiss, Brian A; Donmez, M Alkan

2015-01-01

A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a 'sensor box' to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality.

A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes

PubMed Central

Vogl, Gregory W.; Weiss, Brian A.; Donmez, M. Alkan

2017-01-01

A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a ‘sensor box’ to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality. PMID:28691039

Effects of Spatial N nutrient mobility relevant to plants, soils and microtopograhy on plant growth and soil organic matter accumulation by using coupled CLM-PFLOTRAN biogeochemical model in an Area in NGEE-Arctic Intensive Study Sites, Barrow, AK.

NASA Astrophysics Data System (ADS)

Yuan, F.; Thornton, P. E.; Tang, G.; Xu, X.; Kumar, J.; Iversen, C. M.; Bisht, G.; Hammond, G. E.; Mills, R. T.; Wullschleger, S. D.

2015-12-01

At fine-scale spatially-explicit reactive-transport (RT) and hydrological coupled modeling for likely soil nutrient N transport mechanisms driven by gradients, soil properties and micro-topography is critical to spatial distribution of plants and thus soil organic matter stocks accumulation or changes. In this study we successfully carried out a fully coupled fine-scale CLM-PFLOTRAN soil biogeochemical (BGC) RT model simulation on Titan at 2.5mx2.5m resolution for the Area C of 100mx100m in the NGEE-Arctic Intensive Study Sites, Barrow, AK. The Area spatially varies in terms of plant function types (PFT) and soil thermal-hydraulic properties associated with locally polygonal landscape features. The spatially explicit CLM-PFLOTRAN coupled RT model allows soil N nutrient mobility driven either by diffusion or by advection or both. The modeling experiments are conducted with three soil nutrient N (NH4+ and NO3-) mobility mechanisms within the CLM-PFLOTAN: no transport, diffusion only, and diffusion and advection in 3-D soils. It shows that CLM-PFLOTRAN model simulated higher SOM C density in both lower troughs and neighbored areas when transport mechanism allowed, compared to no-transport, although with similar ranges (about 0.1~20 kgC m-3). It also simulates slightly higher LAI (0.16~0.84 vs. 0.11~0.85) in growing season, especially in lower troughs and neighbored regions. It's likely because CLM-PFLOTRAN can explicitly simulate transport of nutrients and others both vertically and laterally. So it can more mechanically mimic plant root N extract caused relatively low concentration in root zone and thus allow transport from surrounding high N concentration regions. The lateral mobility also implies that N nutrient can transport from initially high-production columns to the neighbored low-production area where then production could be improved. The results suggest that taking account of locally mobility of soil N nutrients may be critical to plant growth and thus long-term soil organic carbon stocks in this polygonal coastal tundra ecosystem at fine scale. It also implies that regional or global scale modelings should consider vertical transport (2D) due to shallow soil root zones, for which a feature in CLM-PFLOTRAN is available as well.

A single-phase axially-magnetized permanent-magnet oscillating machine for miniature aerospace power sources

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Cheng, Luming; Wang, Weinan; Liu, Jiaqi

2017-05-01

A single-phase axially-magnetized permanent-magnet (PM) oscillating machine which can be integrated with a free-piston Stirling engine to generate electric power, is investigated for miniature aerospace power sources. Machine structure, operating principle and detent force characteristic are elaborately studied. With the sinusoidal speed characteristic of the mover considered, the proposed machine is designed by 2D finite-element analysis (FEA), and some main structural parameters such as air gap diameter, dimensions of PMs, pole pitches of both stator and mover, and the pole-pitch combinations, etc., are optimized to improve both the power density and force capability. Compared with the three-phase PM linear machines, the proposed single-phase machine features less PM use, simple control and low controller cost. The power density of the proposed machine is higher than that of the three-phase radially-magnetized PM linear machine, but lower than the three-phase axially-magnetized PM linear machine.

Linking quality of care and training costs: cost-effectiveness in health professions education.

PubMed

Tolsgaard, Martin G; Tabor, Ann; Madsen, Mette E; Wulff, Camilla B; Dyre, Liv; Ringsted, Charlotte; Nørgaard, Lone N

2015-12-01

To provide a model for conducting cost-effectiveness analyses in medical education. The model was based on a randomised trial examining the effects of training midwives to perform cervical length measurement (CLM) as compared with obstetricians on patients' waiting times. (CLM), as compared with obstetricians. The model included four steps: (i) gathering data on training outcomes, (ii) assessing total costs and effects, (iii) calculating the incremental cost-effectiveness ratio (ICER) and (iv) estimating cost-effectiveness probability for different willingness to pay (WTP) values. To provide a model example, we conducted a randomised cost-effectiveness trial. Midwives were randomised to CLM training (midwife-performed CLMs) or no training (initial management by midwife, and CLM performed by obstetrician). Intervention-group participants underwent simulation-based and clinical training until they were proficient. During the following 6 months, waiting times from arrival to admission or discharge were recorded for women who presented with symptoms of pre-term labour. Outcomes for women managed by intervention and control-group participants were compared. These data were then used for the remaining steps of the cost-effectiveness model. Intervention-group participants needed a mean 268.2 (95% confidence interval [CI], 140.2-392.2) minutes of simulator training and a mean 7.3 (95% CI, 4.4-10.3) supervised scans to attain proficiency. Women who were scanned by intervention-group participants had significantly reduced waiting time compared with those managed by the control group (n = 65; mean difference, 36.6 [95% CI 7.3-65.8] minutes; p = 0.008), which corresponded to an ICER of 0.45 EUR minute(-1) . For WTP values less than EUR 0.26 minute(-1) , obstetrician-performed CLM was the most cost-effective strategy, whereas midwife-performed CLM was cost-effective for WTP values above EUR 0.73 minute(-1) . Cost-effectiveness models can be used to link quality of care to training costs. The example used in the present study demonstrated that different training strategies could be recommended as the most cost-effective depending on administrators' willingness to pay per unit of the outcome variable. © 2015 Medical Education Published by John Wiley & Sons Ltd.

Specification for Teaching Machines and Programmes (Interchangeability of Programmes). Part 1, Linear Machines and Programmes.

ERIC Educational Resources Information Center

British Standards Institution, London (England).

To promote interchangeability of teaching machines and programs, so that the user is not so limited in his choice of programs, the British Standards Institute has offered a standard. Part I of the standard deals with linear teaching machines and programs that make use of the roll or sheet methods of presentation. Requirements cover: spools,…

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites: SURROGATE-BASED MCMC FOR CLM

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

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

2016-07-04

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically-average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

A generic biogeochemical module for earth system models

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Fluorine-18-fluorodeoxyglucose positron emission tomography as an objective substitute for CT morphologic response criteria in patients undergoing chemotherapy for colorectal liver metastases.

PubMed

Nishioka, Yujiro; Yoshioka, Ryuji; Gonoi, Wataru; Sugawara, Toshitaka; Yoshida, Shuntaro; Hashimoto, Masaji; Shindoh, Junichi

2018-05-01

The computed tomography (CT) morphologic response of colorectal liver metastases (CLM) after chemotherapy is reportedly correlated with pathologic response and survival outcomes of patients undergoing surgery. However, they are rather subjective criteria and not evaluable without adequate quality of contrast-enhanced CT images. This study sought the potential use of fluorine-18-fluorodeoxyglucose (FDG) positron emission tomography (PET) as an objective substitute for predicting pathological viability of CLM after chemotherapy. Predictive ability of tumor viability of ≤10% was compared between FDG-PET/CT and contrast-enhanced CT in 34 patients who underwent curative surgical resection for CLM after chemotherapy. The CT morphology and response were defined according to the reported criteria (Chun YS, JAMA 2009). The mean standard uptake value (SUV-mean) in CLM was significantly lower in patients with group 1 and group 2 CT morphology (median, 2.53 and 3.00, respectively) than in group 3 (median, 3.32). The tumor SUV-mean showed moderate correlation with the tumor pathologic viability (r = 0.660, P < 0.0001). A receiver operating characteristic curve analysis revealed that both the tumor SUV-mean (area under the curve [AUC], 0.916; the cut-off value, 3.00) and the CT morphology (AUC, 0.882) have excellent predictive power for ≤10% of tumor viability, while degree of tumor shrinkage showed lower predictive power (AUC, 0.692). FDG-PET shows significant correlation with pathologic viability of CLM after chemotherapy and may offer additional objective information for estimating tumor viability when the CT morphologic response is not evaluable.

Comparative Profiling of Primary Colorectal Carcinomas and Liver Metastases Identifies LEF1 as a Prognostic Biomarker

PubMed Central

Lin, Albert Y.; Chua, Mei-Sze; Choi, Yoon-La; Yeh, William; Kim, Young H.; Azzi, Raymond; Adams, Gregg A.; Sainani, Kristin; van de Rijn, Matt; So, Samuel K.; Pollack, Jonathan R.

2011-01-01

Purpose We sought to identify genes of clinical significance to predict survival and the risk for colorectal liver metastasis (CLM), the most common site of metastasis from colorectal cancer (CRC). Patients and Methods We profiled gene expression in 31 specimens from primary CRC and 32 unmatched specimens of CLM, and performed Significance Analysis of Microarrays (SAM) to identify genes differentially expressed between these two groups. To characterize the clinical relevance of two highly-ranked differentially-expressed genes, we analyzed the expression of secreted phosphoprotein 1 (SPP1 or osteopontin) and lymphoid enhancer factor-1 (LEF1) by immunohistochemistry using a tissue microarray (TMA) representing an independent set of 154 patients with primary CRC. Results Supervised analysis using SAM identified 963 genes with significantly higher expression in CLM compared to primary CRC, with a false discovery rate of <0.5%. TMA analysis showed SPP1 and LEF1 protein overexpression in 60% and 44% of CRC cases, respectively. Subsequent occurrence of CLM was significantly correlated with the overexpression of LEF1 (chi-square p = 0.042), but not SPP1 (p = 0.14). Kaplan Meier analysis revealed significantly worse survival in patients with overexpression of LEF1 (p<0.01), but not SPP1 (p = 0.11). Both univariate and multivariate analyses identified stage (p<0.0001) and LEF1 overexpression (p<0.05) as important prognostic markers, but not tumor grade or SPP1. Conclusion Among genes differentially expressed between CLM and primary CRC, we demonstrate overexpression of LEF1 in primary CRC to be a prognostic factor for poor survival and increased risk for liver metastasis. PMID:21383983

Simulation of the Indian Summer Monsoon Using Comprehensive Atmosphere-land Interactions, in the Absence of Two-way Air-sea Interactions

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Shin, D. W.; Cocke, Steven; Kang, Sung-Dae; Kim, Hae-Dong

2011-01-01

Community Land Model version 2 (CLM2) as a comprehensive land surface model and a simple land surface model (SLM) were coupled to an atmospheric climate model to investigate the role of land surface processes in the development and the persistence of the South Asian summer monsoon. Two-way air-sea interactions were not considered in order to identify the reproducibility of the monsoon evolution by the comprehensive land model, which includes more realistic vertical soil moisture structures, vegetation and 2-way atmosphere-land interactions at hourly intervals. In the monsoon development phase (May and June). comprehensive land-surface treatment improves the representation of atmospheric circulations and the resulting convergence/divergence through the improvements in differential heating patterns and surface energy fluxes. Coupling with CLM2 also improves the timing and spatial distribution of rainfall maxima, reducing the seasonal rainfall overestimation by approx.60 % (1.8 mm/d for SLM, 0.7 mm/dI for CLM2). As for the interannual variation of the simulated rainfall, correlation coefficients of the Indian seasonal rainfall with observation increased from 0.21 (SLM) to 0.45 (CLM2). However, in the mature monsoon phase (July to September), coupling with the CLM2 does not exhibit a clear improvement. In contrast to the development phase, latent heat flux is underestimated and sensible heat flux and surface temperature over India are markedly overestimated. In addition, the moisture fluxes do not correlate well with lower-level atmospheric convergence, yielding correlation coefficients and root mean square errors worse than those produced by coupling with the SLM. A more realistic representation of the surface temperature and energy fluxes is needed to achieve an improved simulation for the mature monsoon period.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

NASA Astrophysics Data System (ADS)

Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

2017-08-01

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

NASA Astrophysics Data System (ADS)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis

NASA Astrophysics Data System (ADS)

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; Asrar, Ghassem R.; Leng, Guoyong; Wang, Yingping; Luo, Yiqi

2016-07-01

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted ˜ 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time (τE), the predicted difference in the storage capacity between the two models results from differences in either NPP or τE or both. Our analysis showed that CLM-CASA' simulated 37 % higher NPP than CABLE. On the other hand, τE, which was a function of the baseline carbon residence time (τ'E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τE was mainly caused by longer τ'E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ'E. Overall, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

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

Jiao, Yang; Lei, Huimin; Yang, Dawen

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis

DOE PAGES

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; ...

2016-07-29

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted – 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivitymore » (NPP) and ecosystem residence time ( τ E), the predicted difference in the storage capacity between the two models results from differences in either NPP or τ E or both. Our analysis showed that CLM-CASA'simulated 37 % higher NPP than CABLE. On the other hand, τ E, which was a function of the baseline carbon residence time ( τ' E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τ E was mainly caused by longer τ' E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ' E. Altogether, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.« less

Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis

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

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted – 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivitymore » (NPP) and ecosystem residence time ( τ E), the predicted difference in the storage capacity between the two models results from differences in either NPP or τ E or both. Our analysis showed that CLM-CASA'simulated 37 % higher NPP than CABLE. On the other hand, τ E, which was a function of the baseline carbon residence time ( τ' E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τ E was mainly caused by longer τ' E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ' E. Altogether, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.« less

Study of Environmental Data Complexity using Extreme Learning Machine

NASA Astrophysics Data System (ADS)

Leuenberger, Michael; Kanevski, Mikhail

2017-04-01

The main goals of environmental data science using machine learning algorithm deal, in a broad sense, around the calibration, the prediction and the visualization of hidden relationship between input and output variables. In order to optimize the models and to understand the phenomenon under study, the characterization of the complexity (at different levels) should be taken into account. Therefore, the identification of the linear or non-linear behavior between input and output variables adds valuable information for the knowledge of the phenomenon complexity. The present research highlights and investigates the different issues that can occur when identifying the complexity (linear/non-linear) of environmental data using machine learning algorithm. In particular, the main attention is paid to the description of a self-consistent methodology for the use of Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. By applying two ELM models (with linear and non-linear activation functions) and by comparing their efficiency, quantification of the linearity can be evaluated. The considered approach is accompanied by simulated and real high dimensional and multivariate data case studies. In conclusion, the current challenges and future development in complexity quantification using environmental data mining are discussed. References - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

NK sensitivity of neuroblastoma cells determined by a highly sensitive coupled luminescent method

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

Ogbomo, Henry; Hahn, Anke; Geiler, Janina

2006-01-06

The measurement of natural killer (NK) cells toxicity against tumor or virus-infected cells especially in cases with small blood samples requires highly sensitive methods. Here, a coupled luminescent method (CLM) based on glyceraldehyde-3-phosphate dehydrogenase release from injured target cells was used to evaluate the cytotoxicity of interleukin-2 activated NK cells against neuroblastoma cell lines. In contrast to most other methods, CLM does not require the pretreatment of target cells with labeling substances which could be toxic or radioactive. The effective killing of tumor cells was achieved by low effector/target ratios ranging from 0.5:1 to 4:1. CLM provides highly sensitive, safe,more » and fast procedure for measurement of NK cell activity with small blood samples such as those obtained from pediatric patients.« less

Training and Doctrine Command Acquisition Management and Oversight Supplement

DTIC Science & Technology

2011-06-01

the foundation for all future procurement decisions. Chapter 4 of TR 5-14 requires the RA to gain approval and certification by the designated...CLM013-Work-Breakdown Structure CLM031-Improved Statement of Work ACQ265-Mission Focused Services Acquisition Army eLearning https...will be returned to acceptable levels, and how recurrence of the cause will be prevented in the future . 53 7.3. Performance Requirements Summary

The microcomputer scientific software series 9: user's guide to Geo-CLM: geostatistical interpolation of the historical climatic record in the Lake States.

Treesearch

Margaret R. Holdaway

1994-01-01

Describes Geo-CLM, a computer application (for Mac or DOS) whose primary aim is to perform multiple kriging runs to interpolate the historic climatic record at research plots in the Lake States. It is an exploration and analysis tool. Addition capabilities include climatic databases, a flexible test mode, cross validation, lat/long conversion, English/metric units,...

Sensitivity analysis with the regional climate model COSMO-CLM over the CORDEX-MENA domain

NASA Astrophysics Data System (ADS)

Bucchignani, E.; Cattaneo, L.; Panitz, H.-J.; Mercogliano, P.

2016-02-01

The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure.

Current Status of Whole-Slide Imaging in Education.

PubMed

Saco, Adela; Bombi, Jose Antoni; Garcia, Adriana; Ramírez, Jose; Ordi, Jaume

2016-01-01

Conventional light microscopy (CLM) has classically been the basic tool to teach histology and pathology. In recent years, whole-slide imaging (WSI), which consists of generating a high-magnification digital image of an entire histological glass slide, has emerged as a useful alternative to CLM offering a myriad of opportunities for education. Navigation through the digitized slides closely simulates viewing glass slides with a microscope and is also referred to as virtual microscopy. WSI has many advantages for education. Students feel more comfortable with its use, and it can be used in any classroom as it only requires a computer with Internet access and it allows remote access from anywhere and from any device. WSI can be used simultaneously by a large number of people, stimulating cooperation between students and improving the interaction with the teachers. It allows making marks and annotations on specific fields, which enable specific directed questions to the teacher. Finally, WSI supports are cost-effective compared with CLM. Consequently, WSI has begun to replace CLM in many institutions. WSI has shown to be an extremely useful tool for undergraduate education (medical, dental and veterinary schools), for the training of residents of pathology, tele-education and in tumor boards. © 2016 S. Karger AG, Basel.

Applying ILAMB to data from several generations of the Community Land Model to assess the relative contribution of model improvements and forcing uncertainty to model-data agreement

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Fisher, R.; Koven, C.; Oleson, K. W.; Swenson, S. C.; Hoffman, F. M.; Randerson, J. T.; Collier, N.; Mu, M.

2017-12-01

The International Land Model Benchmarking (ILAMB) project is a model-data intercomparison and integration project designed to assess and help improve land models. The current package includes assessment of more than 25 land variables across more than 60 global, regional, and site-level (e.g., FLUXNET) datasets. ILAMB employs a broad range of metrics including RMSE, mean error, spatial distributions, interannual variability, and functional relationships. Here, we apply ILAMB for the purpose of assessment of several generations of the Community Land Model (CLM4, CLM4.5, and CLM5). Encouragingly, CLM5, which is the result of model development over the last several years by more than 50 researchers from 15 different institutions, shows broad improvements across many ILAMB metrics including LAI, GPP, vegetation carbon stocks, and the historical net ecosystem carbon balance among others. We will also show that considerable uncertainty arises from the historical climate forcing data used (GSWP3v1 and CRUNCEPv7). ILAMB score variations due to forcing data can be as large for many variables as that due to model structural differences. Strengths and weaknesses and persistent biases across model generations will also be presented.

The increasing incidence of foetal echogenic congenital lung malformations: an observational study.

PubMed

Stocker, Linden J; Wellesley, Diana G; Stanton, Michael P; Parasuraman, Rajeswari; Howe, David T

2015-02-01

The aim of this study was to investigate the incidence of congenital lung malformations over the past 19 years. Congenital lung malformations (CLM) are a heterogeneous group of lung abnormalities. The antenatal diagnosis is important for foetal and neonatal management but there have been no studies examining whether the reported incidence of this abnormality is constant. A retrospective cross-sectional study of cases identified from the Wessex Antenatally Detected Anomalies (WANDA) register 1994-2012. One hundred and thirty-three cases of CLM in 524 372 live and stillbirths were identified. All but seven were identified on antenatal ultrasound. During the early registry (1994-1998) the average incidence of CLM was 1.27 per 10,000 births. By the last 4 years (2008-2012) this had risen to 4.15 per 10,000 births, with a progressive increase during the intervening years. There was over a three-fold increase in the antenatally detected CLM in the Wessex region 1994-2012. Comparison with the antenatal detection of diaphragmatic hernia suggests that this is a true rise in incidence rather than an artefactual increase due to increased antenatal recognition secondary to improved ultrasound resolution and operator experience. These results have clinical and cost implications for practitioners of foetal medicine, neonatology and paediatric surgery services. © 2014 John Wiley & Sons, Ltd.

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

Treesearch

Henrique F. Duarte; Brett M. Raczka; Daniel M. Ricciuto; John C. Lin; Charles D. Koven; Peter E. Thornton; David R. Bowling; Chun-Ta Lai; Kenneth J. Bible; James R. Ehleringer

2017-01-01

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest...

Chronic granulomatous mastitis: review of 26 cases with special reference to chronic lobular mastitis.

PubMed

Bhaskaran, C S; Prasad, K R; Rao, G; Kameshwari, R; Saheb, D A; Aruna, C A

1992-01-01

Twenty six cases of chronic granulomatous mastitis are reported in a 5 year period and the slides are reviewed. They are sub-classified into Chronic lobular mastitis (CLM), Plasma cell mastitis and subareolar granuloma. There are 10 cases each of CLM and plasma cell mastitis and one of subareolar granuloma. All the three conditions are associated with duct ectasia. Fat necrosis and infective granulomas were 2 each and one of foreign body granuloma. These lesions can be easily differentiated by histology. While most of the CLM occurred in younger age group, plasma cell mastitis is seen in older women. Histologically, there is a florid inflammatory cell reaction of the stroma with dilatation and destruction of some ducts, with microabscess formation. In plasma cell mastitis, the lesion is more chronic with predominance of plasma cells and involutionary changes of the ducts are seen.

Testing the criterion for correct convergence in the complex Langevin method

NASA Astrophysics Data System (ADS)

Nagata, Keitaro; Nishimura, Jun; Shimasaki, Shinji

2018-05-01

Recently the complex Langevin method (CLM) has been attracting attention as a solution to the sign problem, which occurs in Monte Carlo calculations when the effective Boltzmann weight is not real positive. An undesirable feature of the method, however, was that it can happen in some parameter regions that the method yields wrong results even if the Langevin process reaches equilibrium without any problem. In our previous work, we proposed a practical criterion for correct convergence based on the probability distribution of the drift term that appears in the complex Langevin equation. Here we demonstrate the usefulness of this criterion in two solvable theories with many dynamical degrees of freedom, i.e., two-dimensional Yang-Mills theory with a complex coupling constant and the chiral Random Matrix Theory for finite density QCD, which were studied by the CLM before. Our criterion can indeed tell the parameter regions in which the CLM gives correct results.

A novel single-phase flux-switching permanent magnet linear generator used for free-piston Stirling engine

NASA Astrophysics Data System (ADS)

Zheng, Ping; Sui, Yi; Tong, Chengde; Bai, Jingang; Yu, Bin; Lin, Fei

2014-05-01

This paper investigates a novel single-phase flux-switching permanent-magnet (PM) linear machine used for free-piston Stirling engines. The machine topology and operating principle are studied. A flux-switching PM linear machine is designed based on the quasi-sinusoidal speed characteristic of the resonant piston. Considering the performance of back electromotive force and thrust capability, some leading structural parameters, including the air gap length, the PM thickness, the ratio of the outer radius of mover to that of stator, the mover tooth width, the stator tooth width, etc., are optimized by finite element analysis. Compared with conventional three-phase moving-magnet linear machine, the proposed single-phase flux-switching topology shows advantages in less PM use, lighter mover, and higher volume power density.

On the Stability of Jump-Linear Systems Driven by Finite-State Machines with Markovian Inputs

NASA Technical Reports Server (NTRS)

Patilkulkarni, Sudarshan; Herencia-Zapana, Heber; Gray, W. Steven; Gonzalez, Oscar R.

2004-01-01

This paper presents two mean-square stability tests for a jump-linear system driven by a finite-state machine with a first-order Markovian input process. The first test is based on conventional Markov jump-linear theory and avoids the use of any higher-order statistics. The second test is developed directly using the higher-order statistics of the machine s output process. The two approaches are illustrated with a simple model for a recoverable computer control system.

State and parameter estimation of two land surface models using the ensemble Kalman filter and the particle filter

NASA Astrophysics Data System (ADS)

Zhang, Hongjuan; Hendricks Franssen, Harrie-Jan; Han, Xujun; Vrugt, Jasper A.; Vereecken, Harry

2017-09-01

Land surface models (LSMs) use a large cohort of parameters and state variables to simulate the water and energy balance at the soil-atmosphere interface. Many of these model parameters cannot be measured directly in the field, and require calibration against measured fluxes of carbon dioxide, sensible and/or latent heat, and/or observations of the thermal and/or moisture state of the soil. Here, we evaluate the usefulness and applicability of four different data assimilation methods for joint parameter and state estimation of the Variable Infiltration Capacity Model (VIC-3L) and the Community Land Model (CLM) using a 5-month calibration (assimilation) period (March-July 2012) of areal-averaged SPADE soil moisture measurements at 5, 20, and 50 cm depths in the Rollesbroich experimental test site in the Eifel mountain range in western Germany. We used the EnKF with state augmentation or dual estimation, respectively, and the residual resampling PF with a simple, statistically deficient, or more sophisticated, MCMC-based parameter resampling method. The performance of the calibrated LSM models was investigated using SPADE water content measurements of a 5-month evaluation period (August-December 2012). As expected, all DA methods enhance the ability of the VIC and CLM models to describe spatiotemporal patterns of moisture storage within the vadose zone of the Rollesbroich site, particularly if the maximum baseflow velocity (VIC) or fractions of sand, clay, and organic matter of each layer (CLM) are estimated jointly with the model states of each soil layer. The differences between the soil moisture simulations of VIC-3L and CLM are much larger than the discrepancies among the four data assimilation methods. The EnKF with state augmentation or dual estimation yields the best performance of VIC-3L and CLM during the calibration and evaluation period, yet results are in close agreement with the PF using MCMC resampling. Overall, CLM demonstrated the best performance for the Rollesbroich site. The large systematic underestimation of water storage at 50 cm depth by VIC-3L during the first few months of the evaluation period questions, in part, the validity of its fixed water table depth at the bottom of the modeled soil domain.

Using reactive transport codes to provide mechanistic biogeochemistry representations in global land surface models: CLM-PFLOTRAN 1.0

DOE PAGES

Tang, G.; Yuan, F.; Bisht, G.; ...

2015-12-17

We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models; our goal is to facilitate testing of alternative models and incorporation of new understanding. A reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN code, coupled with the Community Land Model (CLM), and test at Arctic, temperate, and tropical sites. To make the reaction network designed for use in explicit time stepping in CLM compatible with the implicit time stepping used in PFLOTRAN,more » the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. To achieve accurate, efficient, and robust numerical solutions, care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10 −3 to 10 −9 mol m −3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %; computing time can be doubled for log transformation. Caution needs to be taken in choosing the appropriate scaling factor because a small value caused by a negative update to a small concentration may diminish the update and result in false convergence even with very tight relative update tolerance. As some biogeochemical processes (e.g., methane and nitrous oxide production and consumption) involve very low half saturation and threshold concentrations, this work provides insights for addressing nonphysical negativity issues and facilitates the representation of a mechanistic biogeochemical description in earth system models to reduce climate prediction uncertainty.« less

High efficiency machining technology and equipment for edge chamfer of KDP crystals

NASA Astrophysics Data System (ADS)

Chen, Dongsheng; Wang, Baorui; Chen, Jihong

2016-10-01

Potassium dihydrogen phosphate (KDP) is a type of nonlinear optical crystal material. To Inhibit the transverse stimulated Raman scattering of laser beam and then enhance the optical performance of the optics, the edges of the large-sized KDP crystal needs to be removed to form chamfered faces with high surface quality (RMS<5 nm). However, as the depth of cut (DOC) of fly cutting is usually several, its machining efficiency is too low to be accepted for chamfering of the KDP crystal as the amount of materials to be removed is in the order of millimeter. This paper proposes a novel hybrid machining method, which combines precision grinding with fly cutting, for crackless and high efficiency chamfer of KDP crystal. A specialized machine tool, which adopts aerostatic bearing linear slide and aerostatic bearing spindle, was developed for chamfer of the KDP crystal. The aerostatic bearing linear slide consists of an aerostatic bearing guide with linearity of 0.1 μm/100mm and a linear motor to achieve linear feeding with high precision and high dynamic performance. The vertical spindle consists of an aerostatic bearing spindle with the rotation accuracy (axial) of 0.05 microns and Fork type flexible connection precision driving mechanism. The machining experiment on flying and grinding was carried out, the optimize machining parameters was gained by a series of experiment. Surface roughness of 2.4 nm has been obtained. The machining efficiency can be improved by six times using the combined method to produce the same machined surface quality.

Evaluation of CLM4 Solar Radiation Partitioning Scheme Using Remote Sensing and Site Level FPAR Datasets

DOE PAGES

Wang, Kai; Mao, Jiafu; Dickinson, Robert; ...

2013-06-05

This paper examines a land surface solar radiation partitioning scheme, i.e., that of the Community Land Model version 4 (CLM4) with coupled carbon and nitrogen cycles. Taking advantage of a unique 30-year fraction of absorbed photosynthetically active radiation (FPAR) dataset derived from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data set, multiple other remote sensing datasets, and site level observations, we evaluated the CLM4 FPAR ’s seasonal cycle, diurnal cycle, long-term trends and spatial patterns. These findings show that the model generally agrees with observations in the seasonal cycle, long-term trends, and spatial patterns,more » but does not reproduce the diurnal cycle. Discrepancies also exist in seasonality magnitudes, peak value months, and spatial heterogeneity. Here, we identify the discrepancy in the diurnal cycle as, due to, the absence of dependence on sun angle in the model. Implementation of sun angle dependence in a one-dimensional (1-D) model is proposed. The need for better relating of vegetation to climate in the model, indicated by long-term trends, is also noted. Evaluation of the CLM4 land surface solar radiation partitioning scheme using remote sensing and site level FPAR datasets provides targets for future development in its representation of this naturally complicated process.« less

Optimal management of colorectal liver metastases in older patients: a decision analysis

PubMed Central

Yang, Simon; Alibhai, Shabbir MH; Kennedy, Erin D; El-Sedfy, Abraham; Dixon, Matthew; Coburn, Natalie; Kiss, Alex; Law, Calvin HL

2014-01-01

Background Comparative trials evaluating management strategies for colorectal cancer liver metastases (CLM) are lacking, especially for older patients. This study developed a decision-analytic model to quantify outcomes associated with treatment strategies for CLM in older patients. Methods A Markov-decision model was built to examine the effect on life expectancy (LE) and quality-adjusted life expectancy (QALE) for best supportive care (BSC), systemic chemotherapy (SC), radiofrequency ablation (RFA) and hepatic resection (HR). The baseline patient cohort assumptions included healthy 70-year-old CLM patients after a primary cancer resection. Event and transition probabilities and utilities were derived from a literature review. Deterministic and probabilistic sensitivity analyses were performed on all study parameters. Results In base case analysis, BSC, SC, RFA and HR yielded LEs of 11.9, 23.1, 34.8 and 37.0 months, and QALEs of 7.8, 13.2, 22.0 and 25.0 months, respectively. Model results were sensitive to age, comorbidity, length of model simulation and utility after HR. Probabilistic sensitivity analysis showed increasing preference for RFA over HR with increasing patient age. Conclusions HR may be optimal for healthy 70-year-old patients with CLM. In older patients with comorbidities, RFA may provide better LE and QALE. Treatment decisions in older cancer patients should account for patient age, comorbidities, local expertise and individual values. PMID:24961482

Effects of pole flux distribution in a homopolar linear synchronous machine

NASA Astrophysics Data System (ADS)

Balchin, M. J.; Eastham, J. F.; Coles, P. C.

1994-05-01

Linear forms of synchronous electrical machine are at present being considered as the propulsion means in high-speed, magnetically levitated (Maglev) ground transportation systems. A homopolar form of machine is considered in which the primary member, which carries both ac and dc windings, is supported on the vehicle. Test results and theoretical predictions are presented for a design of machine intended for driving a 100 passenger vehicle at a top speed of 400 km/h. The layout of the dc magnetic circuit is examined to locate the best position for the dc winding from the point of view of minimum core weight. Measurements of flux build-up under the machine at different operating speeds are given for two types of secondary pole: solid and laminated. The solid pole results, which are confirmed theoretically, show that this form of construction is impractical for high-speed drives. Measured motoring characteristics are presented for a short length of machine which simulates conditions at the leading and trailing ends of the full-sized machine. Combination of the results with those from a cylindrical version of the machine make it possible to infer the performance of the full-sized traction machine. This gives 0.8 pf and 0.9 efficiency at 300 km/h, which is much better than the reported performance of a comparable linear induction motor (0.52 pf and 0.82 efficiency). It is therefore concluded that in any projected high-speed Maglev systems, a linear synchronous machine should be the first choice as the propulsion means.

A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands

DOE PAGES

Xu, Xiyan; Riley, William J.; Koven, Charles D.; ...

2016-09-13

Wetlands are the largest global natural methane (CH 4) source, and emissions between 50 and 70° N latitude contribute 10-30 % to this source. Predictive capability of land models for northern wetland CH 4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH 4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with site- to regional-scale observations. A comparison of the CH 4 fluxes with eddy flux data highlighted needed changes to the model's estimate of aerenchyma area,more » which we implemented and tested. The model modification substantially reduced biases in CH 4 emissions when compared with CarbonTracker CH 4 predictions. CLM4.5 CH 4 emission predictions agree well with growing season (May–September) CarbonTracker Alaskan regional-level CH 4 predictions and site-level observations. However, CLM4.5 underestimated CH 4 emissions in the cold season (October–April). The monthly atmospheric CH 4 mole fraction enhancements due to wetland emissions are also assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model coupled with daily emissions from CLM4.5 and compared with aircraft CH 4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold-season CH 4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH 4 cycle are from the wetland extent, cold-season CH 4 production and CH 4 transport processes. We recommend more cold-season experimental studies in high-latitude systems, which could improve the understanding and parameterization of ecosystem structure and function during this period. Predicted CH 4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements.« less

Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

NASA Astrophysics Data System (ADS)

Tang, Jinyun; Riley, William J.; Niu, Jie

2015-12-01

We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in better agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d-1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological dynamics in CLM4.5.

Effects of nitrogen deposition on carbon and nitrogen dynamics: a model-data comparison at an alpine meadow on the Qinghai Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhang, L.; Li, P.; Fang, H.; Ren, X.; He, H.; Li, Y.; Yu, G.

2015-12-01

Significant increases in atmospheric nitrogen (N) deposition due to human activities are likely to alter the carbon (C) and nitrogen cycles of terrestrial ecosystems. N deposition has the potential to affect photosynthesis, plant and soil respiration, and thus vegetation and soil C storages. Accurate estimation of the change in plant uptake of carbon dioxide due to N deposition is essential to dealing with the climate change. Among the 11 earth system models which provide climate projection for the Fifth Assessment Report of the Intergovernmental Panel for Climate Change, only the community land model (CLM-CN) used in two of them includes a dynamic terrestrial nitrogen cycle. However, the responses of carbon and nitrogen dynamics to nitrogen deposition in CLM-CN have not been well evaluated. In this study, we examine the performance of CLM-CN (version 4.0) in simulating how leaf N content, leaf area index (LAI), aboveground biomass, soil respiration, and soil organic C and N respond to low-level N addition (40 kg N m-2 yr-1) using observations at an alpine meadow on the Qinghai Tibetan Plateau. CLM-CN well reproduced the positive responses of LAI and soil respiration (+13% and +8%) to the N addition, compared to observed increases (+14% and +12%). However, the CLM-CN leaf N content response to N addition (+13%) was larger than observed (+5%), and modeled response of aboveground biomass C (+5%) was smaller than observed (+12%). Moreover, modeled slight positive response (+0.2%) of soil organic C to N addition was inconsistent with observed decrease of 8.8%. Additional manipulation experimental data are required for evaluating and improving models in simulating responses of plant N uptake, C and N allocation, litter and soil organic matter decomposition to N deposition.

A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands

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

Xu, Xiyan; Riley, William J.; Koven, Charles D.

Wetlands are the largest global natural methane (CH 4) source, and emissions between 50 and 70° N latitude contribute 10-30 % to this source. Predictive capability of land models for northern wetland CH 4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH 4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with site- to regional-scale observations. A comparison of the CH 4 fluxes with eddy flux data highlighted needed changes to the model's estimate of aerenchyma area,more » which we implemented and tested. The model modification substantially reduced biases in CH 4 emissions when compared with CarbonTracker CH 4 predictions. CLM4.5 CH 4 emission predictions agree well with growing season (May–September) CarbonTracker Alaskan regional-level CH 4 predictions and site-level observations. However, CLM4.5 underestimated CH 4 emissions in the cold season (October–April). The monthly atmospheric CH 4 mole fraction enhancements due to wetland emissions are also assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model coupled with daily emissions from CLM4.5 and compared with aircraft CH 4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold-season CH 4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH 4 cycle are from the wetland extent, cold-season CH 4 production and CH 4 transport processes. We recommend more cold-season experimental studies in high-latitude systems, which could improve the understanding and parameterization of ecosystem structure and function during this period. Predicted CH 4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements.« less

Use of endogenous cortisol 6β-hydroxylation clearance for phenotyping in vivo CYP3A activity in women after sequential administration of an oral contraceptive (OC) containing ethinylestradiol and levonorgestrel as weak CYP3A inhibitors.

PubMed

Shibasaki, Hiromi; Kuroiwa, Miyuki; Uchikura, Shinobu; Tsuboyama, Sayuri; Yokokawa, Akitomo; Kume, Miyoko; Furuta, Takashi

2014-09-01

The present study was undertaken to evaluate the time courses of in vivo cytochrome P450 3A (CYP3A) inhibition in four healthy women after sequential administration of an oral contraceptive (OC) containing ethinylestradiol and levonorgestrel, using 6β-hydroxylation clearance of endogenous cortisol (CLm(6β)) as a new index for CYP3A phenotyping. The 6β-hydroxylation clearance (CLm(6β)) was followed every 2h from 9:00 or 11:00 to 17:00 on days 0 (baseline), 1, 2, 21, and 28 during a single menstrual cycle. The serum concentrations of endogenous estradiol and progesterone were also measured. The time course data of CLm(6β) clearly demonstrated 43-64% inhibition of CYP3A activity in women taking a low daily dose of the OC for 21days. The average CLm(6β) levels that were suppressed by the OC in four women were extremely low (0.60-1.23mL/min) compared with the normal CLm(6β) range (1.5-3.5mL/min) that was obtained from 49 healthy subjects in our previous study. The in vivo inhibitory potencies (43-64%) obtained in this study were stronger than expected from reported in vitro studies (∼20%). Furthermore, it would take at least seven days to return to the baseline activity of CYP3A after discontinuation of the OC. The results presented here should provide important information on the inhibitory effect of OC on the CYP3A activities in women, which are involved in the metabolism of a number of drugs with a narrow therapeutic range. Copyright © 2014 Elsevier Inc. All rights reserved.

Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

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

Tang, Jinyun; Riley, William J.; Niu, Jie

We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in bettermore » agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d -1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological dynamics in CLM4.5.« less

Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

DOE PAGES

Tang, Jinyun; Riley, William J.; Niu, Jie

2015-11-12

We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in bettermore » agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d -1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological dynamics in CLM4.5.« less

Adjuvant Chemotherapy With FOLFOX for Primary Colorectal Cancer Is Associated With Increased Somatic Gene Mutations and Inferior Survival in Patients Undergoing Hepatectomy for Metachronous Liver Metastases

PubMed Central

Andreou, Andreas; Kopetz, Scott; Maru, Dipen M.; Chen, Su S.; Zimmitti, Giuseppe; Brouquet, Antoine; Shindoh, Junichi; Curley, Steven A.; Garrett, Christopher; Overman, Michael J.; Aloia, Thomas A.; Vauthey, Jean-Nicolas

2013-01-01

Objective We hypothesized that metachronous colorectal liver metastases (CLM) have different biology after failure of oxaliplatin (FOLFOX) compared to 5-fluorouracil (5-FU) or no chemotherapy for adjuvant treatment of colorectal cancer (CRC). Background It is unclear whether patients treated with liver resection for metachronous CLM after adjuvant FOLFOX for CRC have worse outcomes than those who received 5-FU or no chemotherapy. Methods We identified 341 patients who underwent hepatectomy for metachronous CLM (disease-free interval ≥12 months, 1993–2010). Mass-spectroscopy genotyping for somatic gene mutations in CLM was performed in a subset of 129 patients. Results Adjuvant treatment for primary CRC was FOLFOX in 77 patients, 5-FU in 169 patients, and no chemotherapy in 95 patients. Node-positive primary was comparable between FOLFOX and 5-FU but lower in the no-chemotherapy group (P < 0.0001). Median metastasis size was smaller in the FOLFOX group (2.5 cm) than in the 5-FU (3.0 cm) or no-chemotherapy (3.5 cm) groups, (P = 0.008) although prehepatectomy chemotherapy utilization, metastases number, and carcinoembryonic antigen levels were similar. Disease-free survival (DFS) and overall survival (OS) rates after hepatectomy were worse in patients treated with adjuvant FOLFOX [DFS at 3 years: 14% vs 38% (5-FU) vs 45% (no-chemo), OS at 3 years: 58% vs 70% (5-FU) vs 84% (no-chemo)]. On multivariate analysis, adjuvant FOLFOX was associated with worse DFS (P < 0.0001) and OS (P < 0.0001). Mutation analysis revealed ≥1 mutations in 57% of patients (27/47) after FOLFOX, 29% (12/41) after 5-FU, and 32% (13/41) after no chemotherapy (P = 0.011). Conclusions Adjuvant FOLFOX for primary CRC is associated with a high rate of somatic mutations in liver metastases and inferior outcomes after hepatectomy for metachronous CLM. PMID:22968062

Adjuvant chemotherapy with FOLFOX for primary colorectal cancer is associated with increased somatic gene mutations and inferior survival in patients undergoing hepatectomy for metachronous liver metastases.

PubMed

Andreou, Andreas; Kopetz, Scott; Maru, Dipen M; Chen, Su S; Zimmitti, Giuseppe; Brouquet, Antoine; Shindoh, Junichi; Curley, Steven A; Garrett, Christopher; Overman, Michael J; Aloia, Thomas A; Vauthey, Jean-Nicolas

2012-10-01

We hypothesized that metachronous colorectal liver metastases (CLM) have different biology after failure of oxaliplatin (FOLFOX) compared to 5-fluorouracil (5-FU) or no chemotherapy for adjuvant treatment of colorectal cancer (CRC). It is unclear whether patients treated with liver resection for metachronous CLM after adjuvant FOLFOX for CRC have worse outcomes than those who received 5-FU or no chemotherapy. We identified 341 patients who underwent hepatectomy for metachronous CLM (disease-free interval ≥12 months, 1993-2010). Mass-spectroscopy genotyping for somatic gene mutations in CLM was performed in a subset of 129 patients. Adjuvant treatment for primary CRC was FOLFOX in 77 patients, 5-FU in 169 patients, and no chemotherapy in 95 patients. Node-positive primary was comparable between FOLFOX and 5-FU but lower in the no-chemotherapy group (P < 0.0001). Median metastasis size was smaller in the FOLFOX group (2.5 cm) than in the 5-FU (3.0 cm) or no-chemotherapy (3.5 cm) groups, (P = 0.008) although prehepatectomy chemotherapy utilization, metastases number, and carcinoembryonic antigen levels were similar. Disease-free survival (DFS) and overall survival (OS) rates after hepatectomy were worse in patients treated with adjuvant FOLFOX [DFS at 3 years: 14% vs 38% (5-FU) vs 45% (no-chemo), OS at 3 years: 58% vs 70% (5-FU) vs 84% (no-chemo)]. On multivariate analysis, adjuvant FOLFOX was associated with worse DFS (P < 0.0001) and OS (P < 0.0001). Mutation analysis revealed ≥1 mutations in 57% of patients (27/47) after FOLFOX, 29% (12/41) after 5-FU, and 32% (13/41) after no chemotherapy (P = 0.011). Adjuvant FOLFOX for primary CRC is associated with a high rate of somatic mutations in liver metastases and inferior outcomes after hepatectomy for metachronous CLM.

Global scale analysis and evaluation of an improved mechanistic representation of plant nitrogen and carbon dynamics in the Community Land Model (CLM)

NASA Astrophysics Data System (ADS)

Ghimire, B.; Riley, W. J.; Koven, C. D.; Randerson, J. T.; Mu, M.; Kattge, J.; Rogers, A.; Reich, P. B.

2014-12-01

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However mechanistic representation of nitrogen uptake linked to root traits, and functional nitrogen allocation among different leaf enzymes involved in respiration and photosynthesis is currently lacking in Earth System models. The linkage between nitrogen availability and plant productivity is simplistically represented by potential photosynthesis rates, and is subsequently downregulated depending on nitrogen supply and other nitrogen consumers in the model (e.g., nitrification). This type of potential photosynthesis rate calculation is problematic for several reasons. Firstly, plants do not photosynthesize at potential rates and then downregulate. Secondly, there is considerable subjectivity on the meaning of potential photosynthesis rates. Thirdly, there exists lack of understanding on modeling these potential photosynthesis rates in a changing climate. In addition to model structural issues in representing photosynthesis rates, the role of plant roots in nutrient acquisition have been largely ignored in Earth System models. For example, in CLM4.5, nitrogen uptake is linked to leaf level processes (e.g., primarily productivity) rather than root scale process involved in nitrogen uptake. We present a new plant model for CLM with an improved mechanistic presentation of plant nitrogen uptake based on root scale Michaelis Menten kinetics, and stronger linkages between leaf nitrogen and plant productivity by inferring relationships observed in global databases of plant traits (including the TRY database and several individual studies). We also incorporate improved representation of plant nitrogen leaf allocation, especially in tropical regions where significant over-prediction of plant growth and productivity in CLM4.5 simulations exist. We evaluate our improved global model simulations using the International Land Model Benchmarking (ILAMB) framework. We conclude that mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers leads to overall improvements in CLM4.5's global carbon cycling predictions.

Volumetric Verification of Multiaxis Machine Tool Using Laser Tracker

PubMed Central

Aguilar, Juan José

2014-01-01

This paper aims to present a method of volumetric verification in machine tools with linear and rotary axes using a laser tracker. Beyond a method for a particular machine, it presents a methodology that can be used in any machine type. Along this paper, the schema and kinematic model of a machine with three axes of movement, two linear and one rotational axes, including the measurement system and the nominal rotation matrix of the rotational axis are presented. Using this, the machine tool volumetric error is obtained and nonlinear optimization techniques are employed to improve the accuracy of the machine tool. The verification provides a mathematical, not physical, compensation, in less time than other methods of verification by means of the indirect measurement of geometric errors of the machine from the linear and rotary axes. This paper presents an extensive study about the appropriateness and drawbacks of the regression function employed depending on the types of movement of the axes of any machine. In the same way, strengths and weaknesses of measurement methods and optimization techniques depending on the space available to place the measurement system are presented. These studies provide the most appropriate strategies to verify each machine tool taking into consideration its configuration and its available work space. PMID:25202744

Interpreting linear support vector machine models with heat map molecule coloring

PubMed Central

2011-01-01

Background Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. Results We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor. Conclusions In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor. PMID:21439031

Cutaneous larva migrans in a gardener

NASA Astrophysics Data System (ADS)

Agustiningtyas, I.

2018-03-01

Cutaneous larva migrans is parasitic infestation caused by animal hookworm larva which attacks the epidermis. Contact with soil which is the contaminated larva of hookworm. Cat and dog are the most popular hosts which exceed the egg of hookworm. Ancylostoma caninum and braziliensi are the most common. Diagnosis of CLM is the feature of theserpiginous eruption, lesion erythematous in and itching approximately a week after contact with contaminated soil. In this case report, we describe a case of CLM in a gardener.

PiTS-1: Carbon Partitioning in Loblolly Pine after 13C Labeling and Shade Treatments

DOE Data Explorer

Warren, J. M.; Iversen, C. M.; Garten, Jr., C. T.; Norby, R. J.; Childs, J.; Brice, D.; Evans, R. M.; Gu, L.; Thornton, P.; Weston, D. J.

2013-01-01

The PiTS task was established with the objective of improving the C partitioning routines in existing ecosystem models by exploring mechanistic model representations of partitioning tested against field observations. We used short-term field manipulations of C flow, through 13CO2 labeling, canopy shading and stem girdling, to dramatically alter C partitioning, and resultant data are being used to test model representation of C partitioning processes in the Community Land Model (CLM4 or CLM4.5).

Reduced uncertainty of regional scale CLM predictions of net carbon fluxes and leaf area indices with estimated plant-specific parameters

NASA Astrophysics Data System (ADS)

Post, Hanna; Hendricks Franssen, Harrie-Jan; Han, Xujun; Baatz, Roland; Montzka, Carsten; Schmidt, Marius; Vereecken, Harry

2016-04-01

Reliable estimates of carbon fluxes and states at regional scales are required to reduce uncertainties in regional carbon balance estimates and to support decision making in environmental politics. In this work the Community Land Model version 4.5 (CLM4.5-BGC) was applied at a high spatial resolution (1 km2) for the Rur catchment in western Germany. In order to improve the model-data consistency of net ecosystem exchange (NEE) and leaf area index (LAI) for this study area, five plant functional type (PFT)-specific CLM4.5-BGC parameters were estimated with time series of half-hourly NEE data for one year in 2011/2012, using the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, a Markov Chain Monte Carlo (MCMC) approach. The parameters were estimated separately for four different plant functional types (needleleaf evergreen temperate tree, broadleaf deciduous temperate tree, C3-grass and C3-crop) at four different sites. The four sites are located inside or close to the Rur catchment. We evaluated modeled NEE for one year in 2012/2013 with NEE measured at seven eddy covariance sites in the catchment, including the four parameter estimation sites. Modeled LAI was evaluated by means of LAI derived from remotely sensed RapidEye images of about 18 days in 2011/2012. Performance indices were based on a comparison between measurements and (i) a reference run with CLM default parameters, and (ii) a 60 instance CLM ensemble with parameters sampled from the DREAM posterior probability density functions (pdfs). The difference between the observed and simulated NEE sum reduced 23% if estimated parameters instead of default parameters were used as input. The mean absolute difference between modeled and measured LAI was reduced by 59% on average. Simulated LAI was not only improved in terms of the absolute value but in some cases also in terms of the timing (beginning of vegetation onset), which was directly related to a substantial improvement of the NEE estimates in spring. In order to obtain a more comprehensive estimate of the model uncertainty, a second CLM ensemble was set up, where initial conditions and atmospheric forcings were perturbed in addition to the parameter estimates. This resulted in very high standard deviations (STD) of the modeled annual NEE sums for C3-grass and C3-crop PFTs, ranging between 24.1 and 225.9 gC m-2 y-1, compared to STD = 0.1 - 3.4 gC m-2 y-1 (effect of parameter uncertainty only, without additional perturbation of initial states and atmospheric forcings). The higher spread of modeled NEE for the C3-crop and C3-grass indicated that the model uncertainty was notably higher for those PFTs compared to the forest-PFTs. Our findings highlight the potential of parameter and uncertainty estimation to support the understanding and further development of land surface models such as CLM.

Leptospira venezuelensis sp. nov., a new member of the intermediate group isolated from rodents, cattle and humans.

PubMed

Puche, Rafael; Ferrés, Ignacio; Caraballo, Lizeth; Rangel, Yaritza; Picardeau, Mathieu; Takiff, Howard; Iraola, Gregorio

2018-02-01

Three strains, CLM-U50 T , CLM-R50 and IVIC-Bov1, belonging to the genus Leptospira, were isolated in Venezuela from a patient with leptospirosis, a domestic rat (Rattus norvegicus) and a cow (Bos taurus), respectively. The initial characterisation of these strains based on the rrs gene (16S rRNA) suggested their designation as a novel species within the 'intermediates' group of the genus Leptospira. Further phylogenomic characterisation based on single copy core genes was consistent with their separation into a novel species. The average nucleotide identity between these three strains was >99 %, but below 89 % with respect to any previously described leptospiral species, also supporting their designation as a novel species. Given this evidence, these three isolates were considered to represent a novel species, for which the name Leptospiravenezuelensis sp. nov. is proposed, with CLM-U50 T (=CIP 111407 T =DSM 105752 T ) as the type strain.

Machine learning-based methods for prediction of linear B-cell epitopes.

PubMed

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

Predicting the dissolution kinetics of silicate glasses using machine learning

NASA Astrophysics Data System (ADS)

Anoop Krishnan, N. M.; Mangalathu, Sujith; Smedskjaer, Morten M.; Tandia, Adama; Burton, Henry; Bauchy, Mathieu

2018-05-01

Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can depend on a large number of intrinsic and extrinsic factors. Here, we assess the potential of data-driven models based on machine learning to predict the dissolution rates of various aluminosilicate glasses exposed to a wide range of solution pH values, from acidic to caustic conditions. Four classes of machine learning methods are investigated, namely, linear regression, support vector machine regression, random forest, and artificial neural network. We observe that, although linear methods all fail to describe the dissolution kinetics, the artificial neural network approach offers excellent predictions, thanks to its inherent ability to handle non-linear data. Overall, we suggest that a more extensive use of machine learning approaches could significantly accelerate the design of novel glasses with tailored properties.

Understanding the interaction between wild fire and vegetation distribution within the NCAR CESM framework

NASA Astrophysics Data System (ADS)

Seo, H.; Kim, Y.; Kim, H. J.

2017-12-01

Every year wild fire brings about 400Mha of land burned therefore 2Pg of carbon emissions from the surface occur. In this way fire not only affects the carbon circulation but also has an effect on the terrestrial ecosystems. This study aims to understand role of fire on the geographic vegetation distribution and the terrestrial carbon balances within the NCAR CESM framework, specifically with the CLM-BGC and CLM-BGC-DV. Global climate data from Climate Research Unit (CRU)-National Centers for Environmental Prediction (NCEP) data ranging from 1901 to 2010 are used to drive the land models. First, by comparing fire-on and fire-off simulations with the CLM-BGC-DV, the fire impacts in dynamic vegetation are quantified by the fractional land areas of the different plant functional types. In addition, we examine how changes in vegetation distribution affect the total sum of the burned areas and the carbon balances. This study would provide the limits of and suggestions for the fire and dynamic vegetation modules of the CLM-BGC. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. This work was also supported by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

The RAS mutation status predicts survival in patients undergoing hepatic resection for colorectal liver metastases: The results from a genetic analysis of all-RAS.

PubMed

Amikura, Katsumi; Akagi, Kiwamu; Ogura, Toshiro; Takahashi, Amane; Sakamoto, Hirohiko

2018-03-01

We investigated the impact of mutations in KRAS exons 3-4 and NRAS exons 2-3 in addition to KRAS exon 2, so-called all-RAS mutations, in patients with colorectal liver metastasis (CLM) undergoing hepatic resection. We analyzed 421 samples from CLM patients for their all-RAS mutation status to compare the overall survival rate (OS), recurrence-free survival rate (RFS), and the pattern of recurrence between the patients with and without RAS mutations. RAS mutations were detected in 191 (43.8%). Thirty-two rare mutations (12.2%) were detected in 262 patients with KRAS exon 2 wild-type. After excluding 79 patients who received anti-EGFR antibody therapy, 168 were classified as all-RAS wild-type, and 174 as RAS mutant-type. A multivariate analysis of factors associated with OS and RFS identified the RAS status as an independent factor (OS; hazard ratio [HR] = 1.672, P = 0.0031, RFS; HR = 1.703, P = 0.0024). Recurrence with lung metastasis was observed significantly more frequent in patients with RAS mutations than in patients with RAS wild-type (P = 0.0005). Approximately half of CLM patients may have a RAS mutation. CLM patients with RAS mutations had a significantly worse survival rate in comparison to patients with RAS wild-type, regardless of the administration of anti-EGFR antibody therapy. © 2017 Wiley Periodicals, Inc.

Soybean Physiology Calibration in the Community Land Model

NASA Astrophysics Data System (ADS)

Drewniak, B. A.; Bilionis, I.; Constantinescu, E. M.

2014-12-01

With the large influence of agricultural land use on biophysical and biogeochemical cycles, integrating cultivation into Earth System Models (ESMs) is increasingly important. The Community Land Model (CLM) was augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. However, the strong nonlinearity of ESMs makes parameter fitting a difficult task. In this study, our goal is to calibrate ten of the CLM-Crop parameters for one crop type, soybean, in order to improve model projection of plant development and carbon fluxes. We used measurements of gross primary productivity, net ecosystem exchange, and plant biomass from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). Our scheme can perform model calibration using very few evaluations and, by exploiting parallelism, at a fraction of the time required by plain vanilla Markov Chain Monte Carlo (MCMC). We present the results from a twin experiment (self-validation) and calibration results and validation using real observations from an AmeriFlux tower site in the Midwestern United States, for the soybean crop type. The improved model will help researchers understand how climate affects crop production and resulting carbon fluxes, and additionally, how cultivation impacts climate.

Are all pulmonary hypoplasias the same? A comparison of pulmonary outcomes in neonates with congenital diaphragmatic hernia, omphalocele and congenital lung malformation.

PubMed

Akinkuotu, Adesola C; Sheikh, Fariha; Cass, Darrell L; Zamora, Irving J; Lee, Timothy C; Cassady, Christopher I; Mehollin-Ray, Amy R; Williams, Jennifer L; Ruano, Rodrigo; Welty, Stephen E; Olutoye, Oluyinka O

2015-01-01

Patients with congenital diaphragmatic hernias (CDH), omphaloceles, and congenital lung malformations (CLM) may have pulmonary hypoplasia and experience respiratory insufficiency. We hypothesize that given equivalent lung volumes, the degree of respiratory insufficiency will be comparable regardless of the etiology. Records of all fetuses with CDH, omphalocele, and CLM between January 2000 and June 2013 were reviewed. MRI-based observed-to-expected total fetal lung volumes (O/E-TFLV) were calculated. An analysis of outcomes in patients with O/E-TFLV between 40% and 60%, the most inclusive range, was performed. 285 patients were evaluated (161, CDH; 24, omphalocele; 100, CLM). Fetuses with CDH had the smallest mean O/E-TFLV. CDH patients were intubated for longer and had a higher incidence of pulmonary hypertension. Fifty-six patients with the three diagnoses had an O/E-TFLV of 40%-60%. The need for ECMO, supplemental oxygen at 30days of life, and 6-month mortality were similar among groups. CDH patients had a significantly longer duration of intubation and higher incidence of pulmonary hypertension than the other two diagnoses. Given equivalent lung volumes (40%-60% of expected), CDH patients require more pulmonary support initially than omphalocele and CLM patients. In addition to lung volumes, disease-specific factors, such as pulmonary hypertension in CDH, also contribute to pulmonary morbidity and overall outcome. Copyright © 2015 Elsevier Inc. All rights reserved.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

NASA Astrophysics Data System (ADS)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Comparison of the Snow Simulations in Community Land Model Using Two Snow Cover Fraction Parameterizations

NASA Astrophysics Data System (ADS)

Xie, Zhipeng; Hu, Zeyong

2016-04-01

Snow cover is an important component of local- and regional-scale energy and water budgets, especially in mountainous areas. This paper evaluates the snow simulations by using two snow cover fraction schemes in CLM4.5 (NY07 is the original snow-covered area parameterization used in CLM4, and SL12 is the default scheme in CLM4.5). Off-line simulations are carried out forced by the China Meteorological forcing dataset from January 1, 2001 to December 31, 2010 over the Tibetan Plateau. Simulated snow cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover product, the daily snow depth dataset of China, and China Meteorological Administration (CMA) in-situ snow depth and SWE observations. The comparison results indicate significant differences existing between those two SCF parameterizations simulations. Overall, the SL12 formulation shows a certain improvement compared to the NY07 scheme used in CLM4, with the percentage of correctly modeled snow/no snow being 75.8% and 81.8% when compared with the IMS snow product, respectively. Yet, this improvement varies both temporally and spatially. Both these two snow cover schemes overestimated the snow depth, in comparison with the daily snow depth dataset of China, the average biases of simulated snow depth are 7.38cm (8.77cm), 6.97cm (8.2cm) and 5.49cm (5.76cm) NY07 (and SL12) in the snow accumulation period (September through next February), snowmelt period (March through May) and snow-free period (June through August), respectively. When compared with the CMA in-situ snow depth observations, averaged biases are 3.18cm (4.38cm), 2.85cm (4.34cm) and 0.34cm (0.34cm) for NY07 (SL12), respectively. Though SL12 does worse snow depth simulation than NY07, the simulated SWE by SL12 is better than that by NY07, with average biases being 2.64mm, 6.22mm, 1.33mm for NY07, and 1.47mm, 2.63mm, 0.31mm for SL12, respectively. This study demonstrates that future improvements on snow simulation over the Tibetan Plateau are in urgent need for better representing the variability of snow in CLM. Furthermore, these findings lay a foundation for follow-up studies on the modification of snow cover parameterization in the land surface model. Keywords: snow cover, CLM, Tibetan Plateau, simulation.

Investigating the climate and carbon cycle impacts of CMIP6 Land Use and Land Cover Change in the Community Earth System Model (CESM2)

NASA Astrophysics Data System (ADS)

Lawrence, P.; Lawrence, D. M.; O'Neill, B. C.; Hurtt, G. C.

2017-12-01

For the next round of CMIP6 climate simulations there are new historical and SSP - RCP land use and land cover change (LULCC) data sets that have been compiled through the Land Use Model Intercomparison Project (LUMIP). The new time series data include new functionality following lessons learned through CMIP5 project and include new developments in the Community Land Model (CLM5) that will be used in all the CESM2 simulations of CMIP6. These changes include representing explicit crop modeling and better forest representation through the extended to 12 land units of the Global Land Model (GLM). To include this new information in CESM2 and CLM5 simulations new transient land surface data sets have been generated for the historical period 1850 - 2015 and for preliminary SSP - RCP paired future scenarios. The new data sets use updated MODIS Land Cover, Vegetation Continuous Fields, Leaf Area Index and Albedo to describe Primary and Secondary, Forested and Non Forested land units, as well as Rangelands and Pasture. Current day crop distributions are taken from the MIRCA2000 crop data set as done with the CLM 4.5 crop model and used to guide historical and future crop distributions. Preliminary "land only" simulations with CLM5 have been performed for the historical period and for the SSP1-RCP2.6 and SSP3-RCP7 land use and land cover change time series data. Equivalent no land use and land cover change simulations have been run for these periods under the same meteorological forcing data. The "land only" simulations use GSWP3 historical atmospheric forcing data from 1850 to 2010 and then time increasing RCP 8.5 atmospheric CO2 and climate anomalies on top of the current day GSWP3 atmospheric forcing data from 2011 to 2100. The offline simulations provide a basis to evaluate the surface climate, carbon cycle and crop production impacts of changing land use and land cover for each of these periods. To further evaluate the impacts of the new CLM5 model and the CMIP6 land use data, these results are compared to the equivalent investigations performed in CMIP5 with the CLM4/CESM1 model. We find the role of land use and land cover change in a changing climate is strongly dependent on both of these.

Computer-aided design studies of the homopolar linear synchronous motor

NASA Astrophysics Data System (ADS)

Dawson, G. E.; Eastham, A. R.; Ong, R.

1984-09-01

The linear induction motor (LIM), as an urban transit drive, can provide good grade-climbing capabilities and propulsion/braking performance that is independent of steel wheel-rail adhesion. In view of its 10-12 mm airgap, the LIM is characterized by a low power factor-efficiency product of order 0.4. A synchronous machine offers high efficiency and controllable power factor. An assessment of the linear homopolar configuration of this machine is presented as an alternative to the LIM. Computer-aided design studies using the finite element technique have been conducted to identify a suitable machine design for urban transit propulsion.

Design and Analysis of Linear Fault-Tolerant Permanent-Magnet Vernier Machines

PubMed Central

Xu, Liang; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis. PMID:24982959

Design and analysis of linear fault-tolerant permanent-magnet vernier machines.

PubMed

Xu, Liang; Ji, Jinghua; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis.

A Double-Sided Linear Primary Permanent Magnet Vernier Machine

PubMed Central

2015-01-01

The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed. PMID:25874250

A double-sided linear primary permanent magnet vernier machine.

PubMed

Du, Yi; Zou, Chunhua; Liu, Xianxing

2015-01-01

The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed.

Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

PubMed

Held, Elizabeth; Cape, Joshua; Tintle, Nathan

2016-01-01

Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

Effects of agricultural land-management practices on water quality in northeastern Guilford County, North Carolina, 1985-90

USGS Publications Warehouse

Harned, Douglas A.

1995-01-01

The effects of selected agricultural land-management practices on water quality were assessed in a comparative study of four small basins in the Piedmont province of North Carolina. Agricultural practices, such as tillage and applications of fertilizer and pesticides, are major sources of sediment, nutrients, and pesticides in surface water, and of nutrients and pesticides in ground water. The four study basins included two adjacent row-crop fields, a mixed land-use basin, and a forested basin. One of the row-crop fields (7.4 acres) was farmed by using conservation land-management (CLM) practices, which included strip cropping, contour plowing, field borders, and grassed waterways. The other row-crop field (4.8 acres) was farmed by using standard land-management (SLM) practices, which included continuous cropping, straight-row plowing without regard to land topography, and poorly maintained waterways. The mixed land-use basin (665 acres) was monitored to compare water quality in surface water as SLM practices were converted to CLM practices during the project. The forested basin (44 acres) provided background surface-water hydrologic and chemical-quality conditions. Surface-water flow was reduced by 18 percent by CLM practices compared to surface-water flow from the SLM practices basin. The thickness of the unsaturated zone in the row-crop basins ranged from a few feet to 25 feet. Areas with thick unsaturated zones have a greater capacity to intercept and store nutrients and pesticides than do areas with thinner zones. Sediment concentrations and yields for the SLM practices basin were considerably higher than those for the other basins. The median sediment concentration in surface water for the SLM basin was 3.4 times that of the CLM basin, 8.2 times that of the mixed land-use basin, and 38.4 times that of the forested basin. The total sediment yield for the SLM basin was 2.3 times that observed for the CLM basin, 14.1 times that observed for the mixed land-use basin, and 19.5 times the yield observed for the forested basin. Nutrient concentrations in surface water from the row-crop and mixed land-use basins were higher than those measured in the forested basin and in precipitation collected near the row-crop basins. The SLM basin generally had the highest concentrations of total nitrogen, nitrite plus nitrate, total phosphorus (equivalent to the mixed land-use basin), and potassium. Nutrient concentrations in soil water and ground water were less than concentrations in surface water for the row-crop basins. Nutrient concentrations generally were at least slightly below the root zone (3-foot depth) and in ground water. Differences in nutrient yields among basins had patterns similar to those observed for nutrient concentrations. The total nitrogen yield for the SLM basin was 1.2 times the yield for the CLM basin, 1.9 times the yield for the mixed land-use basin, and 4.2 times the yield for the forested basin. The total phosphorus yield for the SLM basin was 1.7 times the yield for the CLM basin, 3.3 times the yield for the mixed land-use basin, and 7.8 times the yield for the forested basin. No significant differences in pesticide concentrations in surface water were identified between those measured in the SLM basin and those measured in the CLM basin. Significantly higher pesticide concentrations were observed at the row-crop basins compared with those observed at the mixed land-use basin probably because sampling sites for the row-crop basins were closer to the pesticide sources. No pesticides were detected in the forested basin. Comparisons of pesticide concentrations in soil from the two row-crop basins indicated some differences. Concentrations of the soil pesticides isopropalin and flumetralin were higher in the SLM basin than in the CLM basin. The surface-water quality of the mixed land-use basin generally was less affected by agricultural nonpoint sources than that of the smaller row-crop b

Simulation of Longwave Enhancement beneath Montane and Boreal Forests in CLM4.5

NASA Astrophysics Data System (ADS)

Todt, M.; Rutter, N.; Fletcher, C. G.; Wake, L. M.; Loranty, M. M.

2017-12-01

CMIP5 models have been shown to underestimate both trend and variability in northern hemisphere spring snow cover extent. A substantial fraction of this area is covered by boreal forests, in which the snow energy balance is dominated by radiation. Forest coverage impacts the surface radiation budget by shading the ground and enhancing longwave radiation. Longwave enhancement in boreal forests is a potential mechanism that contributes to uncertainty in snowmelt modelling, however, its impact on snowmelt in global land models has not been analysed yet. This study assesses the simulation of sub-canopy longwave radiation and longwave enhancement by CLM4.5, the land component of the NCAR Community Earth System Model, in which boreal forests are represented by three plant functional types (PFT): evergreen needleleaf trees (ENT), deciduous needleleaf trees (DNT), and deciduous broadleaf trees (DBT). Simulation of sub-canopy longwave enhancement is evaluated at boreal forest sites covering the three boreal PFT in CLM4.5 to assess the dependence of simulation errors on meteorological forcing, vegetation type and vegetation density. ENT are evaluated over a total of six snowmelt seasons in Swiss alpine and subalpine forests, as well as a single season at a Finnish arctic site with varying vegetation density. A Swedish artic site features varying vegetation density for DBT for a single winter, and two sites in Eastern Siberia are included covering a total of four snowmelt seasons in DNT forests. CLM4.5 overestimates the diurnal range of sub-canopy longwave radiation and consequently longwave enhancement, overestimating daytime values and underestimating nighttime values. Simulation errors result mainly from clear sky conditions, due to high absorption of shortwave radiation during daytime and radiative cooling during nighttime. Using recent improvements to the canopy parameterisations of SNOWPACK as a guideline, CLM4.5 simulations of sub-canopy longwave radiation improved through the implementation of a heat mass parameterisation, i.e. including thermal inertia due to biomass. However, this improvement does not substantially reduce the amplitude of the diurnal cycle, a result also found during the development of SNOWPACK.

The role of groundwater in hydrological processes and memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui

The interactions between soil moisture and groundwater play important roles in controlling Earth's climate, by changing the terrestrial water cycle. However, most contemporary land surface models (LSMs) used for climate modeling lack any representation of groundwater aquifers. In this dissertation, the effects of water table dynamics on the National Center for Atmospheric Research (NCAR) Community Land Model (CLM) and Community Atmosphere Model (CAM) hydrology and land-atmosphere simulations are investigated. First, a simple, lumped unconfined aquifer model is incorporated into the CLM, in which the water table is interactively coupled to the soil moisture through groundwater recharge fluxes. The recent availability of GRACE water storage data provides a unique opportunity to constrain LSMs simulations of terrestrial hydrology. A multi-objective calibration framework using GRACE and streamflow data is developed. This approach improves parameter estimation and reduces the uncertainty of water table simulations in the CLM. Next, experiments are conducted with the off-line CLM to explore the effects of groundwater on land surface memory. Results show that feedbacks of groundwater on land surface memory can be positive, negative, or neutral depending on water table dynamics. The CAM-CLM is further utilized to investigate the effects of water table dynamics on spatial-temporal variations of precipitation. Results indicate that groundwater can increase short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth. Finally, lower tropospheric water vapor is increased due to the presence of groundwater in the model. However, the impact of groundwater on the spatial distribution of precipitation is not globally homogeneous. In the boreal summer, tropical land regions show a positive (negative) anomaly over the Northern (Southern) Hemisphere. The increased tropical precipitation follows the climatology of the convective zone rather than that of evapotranspiration. In contrast, evapotranspiration is the major contribution to the increased precipitation in the transition climatic zone (e.g., Central North America), where the land and atmosphere are strongly coupled. This dissertation reveals the highly nonlinear responses of precipitation and soil moisture to the groundwater representation in the model, and also underscores the importance of subsurface hydrological memory processes in the climate system.

Analysis of high-resolution simulations for the Black Forest region from a point of view of tourism climatology - a comparison between two regional climate models (REMO and CLM)

NASA Astrophysics Data System (ADS)

Endler, Christina; Matzarakis, Andreas

2011-03-01

An analysis of climate simulations from a point of view of tourism climatology based on two regional climate models, namely REMO and CLM, was performed for a regional domain in the southwest of Germany, the Black Forest region, for two time frames, 1971-2000 that represents the twentieth century climate and 2021-2050 that represents the future climate. In that context, the Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and B1 are used. The analysis focuses on human-biometeorological and applied climatologic issues, especially for tourism purposes - that means parameters belonging to thermal (physiologically equivalent temperature, PET), physical (precipitation, snow, wind), and aesthetic (fog, cloud cover) facets of climate in tourism. In general, both models reveal similar trends, but differ in their extent. The trend of thermal comfort is contradicting: it tends to decrease in REMO, while it shows a slight increase in CLM. Moreover, REMO reveals a wider range of future climate trends than CLM, especially for sunshine, dry days, and heat stress. Both models are driven by the same global coupled atmosphere-ocean model ECHAM5/MPI-OM. Because both models are not able to resolve meso- and micro-scale processes such as cloud microphysics, differences between model results and discrepancies in the development of even those parameters (e.g., cloud formation and cover) are due to different model parameterization and formulation. Climatic changes expected by 2050 are small compared to 2100, but may have major impacts on tourism as for example, snow cover and its duration are highly vulnerable to a warmer climate directly affecting tourism in winter. Beyond indirect impacts are of high relevance as they influence tourism as well. Thus, changes in climate, natural environment, demography, tourists' demands, among other things affect economy in general. The analysis of the CLM results and its comparison with the REMO results complete the analysis performed within the project Climate Trends and Sustainable Development of Tourism in Coastal and Low Mountain Range Regions (CAST) funded by the German Federal Ministry of Education and Research (BMBF).

Efficiency of autonomous soft nanomachines at maximum power.

PubMed

Seifert, Udo

2011-01-14

We consider nanosized artificial or biological machines working in steady state enforced by imposing nonequilibrium concentrations of solutes or by applying external forces, torques, or electric fields. For unicyclic and strongly coupled multicyclic machines, efficiency at maximum power is not bounded by the linear response value 1/2. For strong driving, it can even approach the thermodynamic limit 1. Quite generally, such machines fall into three different classes characterized, respectively, as "strong and efficient," "strong and inefficient," and "balanced." For weakly coupled multicyclic machines, efficiency at maximum power has lost any universality even in the linear response regime.

A new model of the global biogeochemical cycle of carbonyl sulfide - Part 2: Use of carbonyl sulfide to constrain gross primary productivity in current vegetation models

NASA Astrophysics Data System (ADS)

Launois, T.; Peylin, P.; Belviso, S.; Poulter, B.

2015-08-01

Clear analogies between carbonyl sulfide (OCS) and carbon dioxide (CO2) diffusion pathways through leaves have been revealed by experimental studies, with plant uptake playing an important role for the atmospheric budget of both species. Here we use atmospheric OCS to evaluate the gross primary production (GPP) of three dynamic global vegetation models (Lund-Potsdam-Jena, LPJ; National Center for Atmospheric Research - Community Land Model 4, NCAR-CLM4; and Organising Carbon and Hydrology In Dynamic Ecosystems, ORCHIDEE). Vegetation uptake of OCS is modeled as a linear function of GPP and leaf relative uptake (LRU), the ratio of OCS to CO2 deposition velocities of plants. New parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of OCS are also provided. Despite new large oceanic emissions, global OCS budgets created with each vegetation model show exceeding sinks by several hundred Gg S yr-1. An inversion of the surface fluxes (optimization of a global scalar which accounts for flux uncertainties) led to balanced OCS global budgets, as atmospheric measurements suggest, mainly by drastic reduction (up to -50 %) in soil and vegetation uptakes. The amplitude of variations in atmospheric OCS mixing ratios is mainly dictated by the vegetation sink over the Northern Hemisphere. This allows for bias recognition in the GPP representations of the three selected models. The main bias patterns are (i) the terrestrial GPP of ORCHIDEE at high northern latitudes is currently overestimated, (ii) the seasonal variations of the GPP are out of phase in the NCAR-CLM4 model, showing a maximum carbon uptake too early in spring in the northernmost ecosystems, (iii) the overall amplitude of the seasonal variations of GPP in NCAR-CLM4 is too small, and (iv) for the LPJ model, the GPP is slightly out of phase for the northernmost ecosystems and the respiration fluxes might be too large in summer in the Northern Hemisphere. These results rely on the robustness of the OCS modeling framework and, in particular, the choice of the LRU values (assumed constant in time) and the parameterization of soil OCS uptake with small seasonal variations. Refined optimization with regional-scale and seasonally varying coefficients might help to test some of these hypothesis.

Factors affecting surgical margin recurrence after hepatectomy for colorectal liver metastases.

PubMed

Akyuz, Muhammet; Aucejo, Federico; Quintini, Cristiano; Miller, Charles; Fung, John; Berber, Eren

2016-06-01

Hepatic recurrence after resection of colorectal liver metastasis (CLM) occurs in 50% of patients during follow-up, with 2.8% to 13.9% presenting with surgical margin recurrence (SMR). The aim of this study is to analyze factors that related to SMR in patients with CLM undergoing hepatectomy. Demographics, clinical and survival data of patients who underwent hepatectomy were identified from a prospectively maintained, institutional review board (IRB)-approved database between 2000 and 2012. Statistical analysis was performed using univariate Kaplan Meier and Cox proportional hazard model. There were 85 female and 121 male patients who underwent liver resection for CLM. An R0 resection was performed in 157 (76%) patients and R1 resection in 49. SMR was detected in 32 patients (15.5%) followed up for a median of 29 months (range, 3-121 months). A half of these patients had undergone R1 (n=16) and another half R0 resection (n=16). Tumor size, preoperative carcinoembryonic antigen (CEA) level and margin status were associated with SMR on univariate analysis. On multivariate analysis, a positive surgical margin was the only independent predictor of SMR. The receipt of adjuvant chemotherapy did not affect margin recurrence. SMR was an independent risk factor associated with worse disease-free (DFS) and overall survival (OS). This study shows that SMR, which can be detected in up to 15.5% of patients after liver resection for CLM, adversely affects DFS and OS. The fact that a positive surgical margin was the only predictive factor for SMR in these patients underscores the importance of achieving negative margins during hepatectomy.

Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites

NASA Astrophysics Data System (ADS)

Post, Hanna; Vrugt, Jasper A.; Fox, Andrew; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2017-03-01

The Community Land Model (CLM) contains many parameters whose values are uncertain and thus require careful estimation for model application at individual sites. Here we used Bayesian inference with the DiffeRential Evolution Adaptive Metropolis (DREAM(zs)) algorithm to estimate eight CLM v.4.5 ecosystem parameters using 1 year records of half-hourly net ecosystem CO2 exchange (NEE) observations of four central European sites with different plant functional types (PFTs). The posterior CLM parameter distributions of each site were estimated per individual season and on a yearly basis. These estimates were then evaluated using NEE data from an independent evaluation period and data from "nearby" FLUXNET sites at 600 km distance to the original sites. Latent variables (multipliers) were used to treat explicitly uncertainty in the initial carbon-nitrogen pools. The posterior parameter estimates were superior to their default values in their ability to track and explain the measured NEE data of each site. The seasonal parameter values reduced with more than 50% (averaged over all sites) the bias in the simulated NEE values. The most consistent performance of CLM during the evaluation period was found for the posterior parameter values of the forest PFTs, and contrary to the C3-grass and C3-crop sites, the latent variables of the initial pools further enhanced the quality-of-fit. The carbon sink function of the forest PFTs significantly increased with the posterior parameter estimates. We thus conclude that land surface model predictions of carbon stocks and fluxes require careful consideration of uncertain ecological parameters and initial states.

Accelerating the spin-up of the coupled carbon and nitrogen cycle model in CLM4

DOE PAGES

Fang, Yilin; Liu, Chongxuan; Leung, Lai-Yung R.

2015-03-24

The commonly adopted biogeochemistry spin-up process in an Earth system model (ESM) is to run the model for hundreds to thousands of years subject to periodic atmospheric forcing to reach dynamic steady state of the carbon–nitrogen (CN) models. A variety of approaches have been proposed to reduce the computation time of the spin-up process. Significant improvement in computational efficiency has been made recently. However, a long simulation time is still required to reach the common convergence criteria of the coupled carbon–nitrogen model. A gradient projection method was proposed and used to further reduce the computation time after examining the trendmore » of the dominant carbon pools. The Community Land Model version 4 (CLM4) with a carbon and nitrogen component was used in this study. From point-scale simulations, we found that the method can reduce the computation time by 20–69% compared to one of the fastest approaches in the literature. We also found that the cyclic stability of total carbon for some cases differs from that of the periodic atmospheric forcing, and some cases even showed instability. Close examination showed that one case has a carbon periodicity much longer than that of the atmospheric forcing due to the annual fire disturbance that is longer than half a year. The rest was caused by the instability of water table calculation in the hydrology model of CLM4. The instability issue is resolved after we replaced the hydrology scheme in CLM4 with a flow model for variably saturated porous media.« less

Coupling a three-dimensional subsurface flow model with a land surface model to simulate stream-aquifer-land interactions

NASA Astrophysics Data System (ADS)

Huang, M.; Bisht, G.; Zhou, T.; Chen, X.; Dai, H.; Hammond, G. E.; Riley, W. J.; Downs, J.; Liu, Y.; Zachara, J. M.

2016-12-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively-parallel multi-physics reactive tranport model (PFLOTRAN). The coupled model (CLM-PFLOTRAN) is applied to a 400m×400m study domain instrumented with groundwater monitoring wells in the Hanford 300 Area along the Columbia River. CLM-PFLOTRAN simulations are performed at three different spatial resolutions over the period 2011-2015 to evaluate the impact of spatial resolution on simulated variables. To demonstrate the difference in model simulations with and without lateral subsurface flow, a vertical-only CLM-PFLOTRAN simulation is also conducted for comparison. Results show that the coupled model is skillful in simulating stream-aquifer interactions, and the land-surface energy partitioning can be strongly modulated by groundwater-river water interactions in high water years due to increased soil moisture availability caused by elevated groundwater table. In addition, spatial resolution does not seem to impact the land surface energy flux simulations, although it is a key factor for accurately estimating the mass exchange rates at the boundaries and associated biogeochemical reactions in the aquifer. The coupled model developed in this study establishes a solid foundation for understanding co-evolution of hydrology and biogeochemistry along the river corridors under historical and future hydro-climate changes.

Fetal MRI lung volumes are predictive of perinatal outcomes in fetuses with congenital lung masses.

PubMed

Zamora, Irving J; Sheikh, Fariha; Cassady, Christopher I; Olutoye, Oluyinka O; Mehollin-Ray, Amy R; Ruano, Rodrigo; Lee, Timothy C; Welty, Stephen E; Belfort, Michael A; Ethun, Cecilia G; Kim, Michael E; Cass, Darrell L

2014-06-01

The purpose of this study was to evaluate fetal magnetic resonance imaging (MRI) as a modality for predicting perinatal outcomes and lung-related morbidity in fetuses with congenital lung masses (CLM). The records of all patients treated for CLM from 2002 to 2012 were reviewed retrospectively. Fetal MRI-derived lung mass volume ratio (LMVR), observed/expected normal fetal lung volume (O/E-NFLV), and lesion-to-lung volume ratio (LLV) were calculated. Multivariate regression and receiver operating characteristic analyses were applied to determine the predictive accuracy of prenatal imaging. Of 128 fetuses with CLM, 93% (n=118) survived. MRI data were available for 113 fetuses. In early gestation (<26weeks), MRI measurements of LMVR and LLV correlated with risk of fetal hydrops, mortality, and/or need for fetal intervention. In later gestation (>26weeks), LMVR, LLV, and O/E-NFLV correlated with neonatal respiratory distress, intubation, NICU admission and need for neonatal surgery. On multivariate regression, LMVR was the strongest predictor for development of fetal hydrops (OR: 6.97, 1.58-30.84; p=0.01) and neonatal respiratory distress (OR: 12.38, 3.52-43.61; p≤0.001). An LMVR >2.0 predicted worse perinatal outcome with 83% sensitivity and 99% specificity (AUC=0.94; p<0.001). Fetal MRI volumetric measurements of lung masses and residual normal lung are predictive of perinatal outcomes in fetuses with CLM. These data may assist in perinatal risk stratification, counseling, and resource utilization. Copyright © 2014 Elsevier Inc. All rights reserved.

Method for measuring the contour of a machined part

DOEpatents

Bieg, L.F.

1995-05-30

A method is disclosed for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining. 5 figs.

Method for measuring the contour of a machined part

DOEpatents

Bieg, Lothar F.

1995-05-30

A method for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining.

Modular Aero-Propulsion System Simulation

NASA Technical Reports Server (NTRS)

Parker, Khary I.; Guo, Ten-Huei

2006-01-01

The Modular Aero-Propulsion System Simulation (MAPSS) is a graphical simulation environment designed for the development of advanced control algorithms and rapid testing of these algorithms on a generic computational model of a turbofan engine and its control system. MAPSS is a nonlinear, non-real-time simulation comprising a Component Level Model (CLM) module and a Controller-and-Actuator Dynamics (CAD) module. The CLM module simulates the dynamics of engine components at a sampling rate of 2,500 Hz. The controller submodule of the CAD module simulates a digital controller, which has a typical update rate of 50 Hz. The sampling rate for the actuators in the CAD module is the same as that of the CLM. MAPSS provides a graphical user interface that affords easy access to engine-operation, engine-health, and control parameters; is used to enter such input model parameters as power lever angle (PLA), Mach number, and altitude; and can be used to change controller and engine parameters. Output variables are selectable by the user. Output data as well as any changes to constants and other parameters can be saved and reloaded into the GUI later.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

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

Meng, L.; Paudel, R.; Hess, P. G. M.

Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which themore » atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH 4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH 4 concentration gradients and growth rates. In conclusion, this study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH 4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.« less

Simulating carbon, water and energy fluxes of a rainforest and an oil palm plantation using the Community Land Model (CLM4.5)

NASA Astrophysics Data System (ADS)

Fan, Yuanchao; Bernoux, Martial; Roupsard, Olivier; Panferov, Oleg; Le Maire, Guerric; Tölle, Merja; Knohl, Alexander

2014-05-01

Deforestation and forest degradation driven by the expansion of oil palm (Elaeis guineensis) plantations has become the major source of GHG emission in Indonesia. Changes of land surface properties (e.g. vegetation composition, soil property, surface albedo) associated with rainforest to oil palm conversion might alter the patterns of land-atmosphere energy, water and carbon cycles and therefore affect local or regional climate. Land surface modeling has been widely used to characterize the two-way interactions between climate and human disturbances on land surface. The Community Land Model (CLM) is a third-generation land model that simulates a wide range of biogeophysical and biogeochemical processes. This project utilizes the land-cover/land-use change (LCLUC) capability of the latest CLM versions 4/4.5 to characterize quantitatively how anthropogenic land surface dynamics in Indonesia affect land-atmosphere carbon, water and energy fluxes. Before simulating land use changes, the first objective is to parameterize and validate the CLM model at local rainforest and oil palm plantation sites through separate point simulations. This entails creation and parameterization of a new plant functional type (PFT) for oil palm, as well as sensitivity analysis and adaptation of model parameters for the rainforest PFTs. CLM modelled fluxes for the selected sites are to be compared with field observations from eddy covariance (EC) flux towers (e.g. a rainforest site in Bariri, Sulawesi; an oil palm site in Jambi, Sumatra). After validation, the project will proceed to parameterize land-use transformation system using remote sensing data and to simulate the impacts of historical LUCs on carbon, water and energy fluxes. Last but not least, the effects of future LUCs in Indonesia on the fluxes and carbon sequestration capacity will be investigated through scenario study. Historical land cover changes, especially oil palm coverage, are retrieved from Landsat or MODIS archival images. Oil palm concession boundaries are used to define and project future land use scenarios. Initial results include outputs from a single-point simulation for the Bariri rainforest site forced with locally measured meteorological data which already showed significant advantage over global forcing data in predicting net ecosystem exchange and latent and sensible heat fluxes. Modeled fluxes are being compared with EC flux observations and with Mixfor-SVAT model outputs from another project at the same site. In the next few months, focus will be on sensitivity analyses of model parameters including PFT optical, morphological and physiological parameters that are necessary to configure the new oil palm PFT and represent rainforest to oil palm conversion. The new parameterization will contribute to the development of the CLM model and its implementation in the modelling of LUC effects in tropical regions will help understanding land-climate interactions.

Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

DOE PAGES

Meng, L.; Paudel, R.; Hess, P. G. M.; ...

2015-07-03

Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which themore » atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH 4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH 4 concentration gradients and growth rates. In conclusion, this study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH 4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.« less

A tubular hybrid Halbach/axially-magnetized permanent-magnet linear machine

NASA Astrophysics Data System (ADS)

Sui, Yi; Liu, Yong; Cheng, Luming; Liu, Jiaqi; Zheng, Ping

2017-05-01

A single-phase tubular permanent-magnet linear machine (PMLM) with hybrid Halbach/axially-magnetized PM arrays is proposed for free-piston Stirling power generation system. Machine topology and operating principle are elaborately illustrated. With the sinusoidal speed characteristic of the free-piston Stirling engine considered, the proposed machine is designed and calculated by finite-element analysis (FEA). The main structural parameters, such as outer radius of the mover, radial length of both the axially-magnetized PMs and ferromagnetic poles, axial length of both the middle and end radially-magnetized PMs, etc., are optimized to improve both the force capability and power density. Compared with the conventional PMLMs, the proposed machine features high mass and volume power density, and has the advantages of simple control and low converter cost. The proposed machine topology is applicable to tubular PMLMs with any phases.

Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.

PubMed

Oh, Jooyoung; Cho, Dongrae; Park, Jaesub; Na, Se Hee; Kim, Jongin; Heo, Jaeseok; Shin, Cheung Soo; Kim, Jae-Jin; Park, Jin Young; Lee, Boreom

2018-03-27

Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distinguished from non-delirious patients by using heart rate variability (HRV) and machine learning. Electrocardiography data of 140 patients was acquired during daily ICU care, and HRV data were analyzed. Delirium, including its type, severity, and etiologies, was evaluated daily by trained psychiatrists. HRV data and various machine learning algorithms including linear support vector machine (SVM), SVM with radial basis function (RBF) kernels, linear extreme learning machine (ELM), ELM with RBF kernels, linear discriminant analysis, and quadratic discriminant analysis were utilized to distinguish delirium patients from non-delirium patients. HRV data of 4797 ECGs were included, and 39 patients had delirium at least once during their ICU stay. The maximum classification accuracy was acquired using SVM with RBF kernels. Our prediction method based on HRV with machine learning was comparable to previous delirium prediction models using massive amounts of clinical information. Our results show that autonomic alterations could be a significant feature of patients with delirium in the ICU, suggesting the potential for the automatic prediction and early detection of delirium based on HRV with machine learning.

A Flash X-Ray Facility for the Naval Postgraduate School

DTIC Science & Technology

1985-06-01

ionizing radiation, *• NPS has had active programs with a Van de Graaff generator, a reactor, radioactive sources, X-ray machines and a linear electron ...interaction of radiation with matter and with coherent radiation. Currently the most active program is at the linear electron accelerator which over...twenty years has produced some 75 theses. The flash X-ray machine was obtained to expan-i and complement the capabilities of the linear electron

Classification of sodium MRI data of cartilage using machine learning.

PubMed

Madelin, Guillaume; Poidevin, Frederick; Makrymallis, Antonios; Regatte, Ravinder R

2015-11-01

To assess the possible utility of machine learning for classifying subjects with and subjects without osteoarthritis using sodium magnetic resonance imaging data. Theory: Support vector machine, k-nearest neighbors, naïve Bayes, discriminant analysis, linear regression, logistic regression, neural networks, decision tree, and tree bagging were tested. Sodium magnetic resonance imaging with and without fluid suppression by inversion recovery was acquired on the knee cartilage of 19 controls and 28 osteoarthritis patients. Sodium concentrations were measured in regions of interests in the knee for both acquisitions. Mean (MEAN) and standard deviation (STD) of these concentrations were measured in each regions of interest, and the minimum, maximum, and mean of these two measurements were calculated over all regions of interests for each subject. The resulting 12 variables per subject were used as predictors for classification. Either Min [STD] alone, or in combination with Mean [MEAN] or Min [MEAN], all from fluid suppressed data, were the best predictors with an accuracy >74%, mainly with linear logistic regression and linear support vector machine. Other good classifiers include discriminant analysis, linear regression, and naïve Bayes. Machine learning is a promising technique for classifying osteoarthritis patients and controls from sodium magnetic resonance imaging data. © 2014 Wiley Periodicals, Inc.

Factors affecting surgical margin recurrence after hepatectomy for colorectal liver metastases

PubMed Central

Akyuz, Muhammet; Aucejo, Federico; Quintini, Cristiano; Miller, Charles; Fung, John

2016-01-01

Background Hepatic recurrence after resection of colorectal liver metastasis (CLM) occurs in 50% of patients during follow-up, with 2.8% to 13.9% presenting with surgical margin recurrence (SMR). The aim of this study is to analyze factors that related to SMR in patients with CLM undergoing hepatectomy. Methods Demographics, clinical and survival data of patients who underwent hepatectomy were identified from a prospectively maintained, institutional review board (IRB)-approved database between 2000 and 2012. Statistical analysis was performed using univariate Kaplan Meier and Cox proportional hazard model. Results There were 85 female and 121 male patients who underwent liver resection for CLM. An R0 resection was performed in 157 (76%) patients and R1 resection in 49. SMR was detected in 32 patients (15.5%) followed up for a median of 29 months (range, 3–121 months). A half of these patients had undergone R1 (n=16) and another half R0 resection (n=16). Tumor size, preoperative carcinoembryonic antigen (CEA) level and margin status were associated with SMR on univariate analysis. On multivariate analysis, a positive surgical margin was the only independent predictor of SMR. The receipt of adjuvant chemotherapy did not affect margin recurrence. SMR was an independent risk factor associated with worse disease-free (DFS) and overall survival (OS). Conclusions This study shows that SMR, which can be detected in up to 15.5% of patients after liver resection for CLM, adversely affects DFS and OS. The fact that a positive surgical margin was the only predictive factor for SMR in these patients underscores the importance of achieving negative margins during hepatectomy. PMID:27294032

Inverse Modeling of Hydrologic Parameters Using Surface Flux and Runoff Observations in the Community Land Model

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

Sun, Yu; Hou, Zhangshuan; Huang, Maoyi

2013-12-10

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC) - Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find thatmore » using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent - as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to the different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.« less

Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon

NASA Astrophysics Data System (ADS)

Wang, Yuanyuan; Xie, Zhenghui; Jia, Binghao

2016-09-01

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon-nitrogen (CN) interactions (CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83 (BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production (GPP) and latent heat flux (LE) for the dry season, and improved the carbon (C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m-2 d-1, net ecosystem exchange by 1.96 g C m-2 d-1, LE by 5.0 W m-2, and soil moisture by 0.03 m3 m-3, at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses (including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.

A feasibility study on porting the community land model onto accelerators using OpenACC

DOE PAGES

Wang, Dali; Wu, Wei; Winkler, Frank; ...

2014-01-01

As environmental models (such as Accelerated Climate Model for Energy (ACME), Parallel Reactive Flow and Transport Model (PFLOTRAN), Arctic Terrestrial Simulator (ATS), etc.) became more and more complicated, we are facing enormous challenges regarding to porting those applications onto hybrid computing architecture. OpenACC appears as a very promising technology, therefore, we have conducted a feasibility analysis on porting the Community Land Model (CLM), a terrestrial ecosystem model within the Community Earth System Models (CESM)). Specifically, we used automatic function testing platform to extract a small computing kernel out of CLM, then we apply this kernel into the actually CLM dataflowmore » procedure, and investigate the strategy of data parallelization and the benefit of data movement provided by current implementation of OpenACC. Even it is a non-intensive kernel, on a single 16-core computing node, the performance (based on the actual computation time using one GPU) of OpenACC implementation is 2.3 time faster than that of OpenMP implementation using single OpenMP thread, but it is 2.8 times slower than the performance of OpenMP implementation using 16 threads. On multiple nodes, MPI_OpenACC implementation demonstrated very good scalability on up to 128 GPUs on 128 computing nodes. This study also provides useful information for us to look into the potential benefits of “deep copy” capability and “routine” feature of OpenACC standards. In conclusion, we believe that our experience on the environmental model, CLM, can be beneficial to many other scientific research programs who are interested to porting their large scale scientific code using OpenACC onto high-end computers, empowered by hybrid computing architecture.« less

Earth System Modeling Tested for CLM4.5 in a Costa Rican Tropical Montane Rainforest

NASA Astrophysics Data System (ADS)

Song, J.; Miller, G. R.; Cahill, A. T.; Aparecido, L. M. T.; Moore, G. W.

2017-12-01

Terrestrial ecosystems in the tropics are important for global carbon and water cycling, which makes modeling of their land-surface processes essential for accurate understanding of land-atmosphere interactions. However, modeling of tropical regions, especially mountainous ones, is known to be subject to significant errors in the prediction of evapotranspiration. Our previous work has highlighted the effects of the prolonged wetness experienced by such sites, focusing on carbon and water exchange at the leaf/stand level. Here, we explore the implications these findings have for modeling at the stand/canopy scale. This study examined the performance of the Community Land Model (CLM4.5) against measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4,000 mm of mean annual precipitation. Measurements include leaf temperatures, transpiration (sap flows), fluxes via eddy-covariance, and vertical profiles of H2O and CO2 concentrations, micrometeorological variables, and leaf wetness. In this work, results from point-scale CLM4.5 were compared to canopy data. The model fails to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). We found that soil and leaf temperatures were overestimated (≈ +2°C) at noon and underestimated (≈ -1°C) during the night; daily transpiration was approximately double than that observed. Simulated leaf wetness deviated significantly from the measurements, both in timing and extent, which affected temperatures and evapotranspiration partitioning. Slope effects appeared in the average diurnal variations of surface albedo and carbon flux from actual data but were not captured in CLM. Our investigation indicated that interception and aerodynamic resistance models contribute to model errors, suggesting potential improvements for modeling in very wet and/or mountainous regions.

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE PAGES

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; ...

2016-06-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

OCO-2 Column Carbon Dioxide and Biometric Data Jointly Constrain Parameterization and Projection of a Global Land Model

NASA Astrophysics Data System (ADS)

Shi, Z.; Crowell, S.; Luo, Y.; Rayner, P. J.; Moore, B., III

2015-12-01

Uncertainty in predicted carbon-climate feedback largely stems from poor parameterization of global land models. However, calibration of global land models with observations has been extremely challenging at least for two reasons. First we lack global data products from systematical measurements of land surface processes. Second, computational demand is insurmountable for estimation of model parameter due to complexity of global land models. In this project, we will use OCO-2 retrievals of dry air mole fraction XCO2 and solar induced fluorescence (SIF) to independently constrain estimation of net ecosystem exchange (NEE) and gross primary production (GPP). The constrained NEE and GPP will be combined with data products of global standing biomass, soil organic carbon and soil respiration to improve the community land model version 4.5 (CLM4.5). Specifically, we will first develop a high fidelity emulator of CLM4.5 according to the matrix representation of the terrestrial carbon cycle. It has been shown that the emulator fully represents the original model and can be effectively used for data assimilation to constrain parameter estimation. We will focus on calibrating those key model parameters (e.g., maximum carboxylation rate, turnover time and transfer coefficients of soil carbon pools, and temperature sensitivity of respiration) for carbon cycle. The Bayesian Markov chain Monte Carlo method (MCMC) will be used to assimilate the global databases into the high fidelity emulator to constrain the model parameters, which will be incorporated back to the original CLM4.5. The calibrated CLM4.5 will be used to make scenario-based projections. In addition, we will conduct observing system simulation experiments (OSSEs) to evaluate how the sampling frequency and length could affect the model constraining and prediction.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

2018-01-01

Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

Mechanistic Processes Controlling Persistent Changes of Forest Canopy Structure After 2005 Amazon Drought

NASA Astrophysics Data System (ADS)

Shi, Mingjie; Liu, Junjie; Zhao, Maosheng; Yu, Yifan; Saatchi, Sassan

2017-12-01

The long-term impact of Amazonian drought on canopy structure has been observed in ground and remote sensing measurements. However, it is still unclear whether it is caused by biotic (e.g., plant structure damage) or environmental (e.g., water deficiency) factors. We used the Community Land Model version 4.5 (CLM4.5) and radar backscatter observations from SeaWinds Scatterometer on board QuikSCAT (QSCAT) satellite to investigate the relative role of biotic and environmental factors in controlling the forest canopy disturbance and recovery processes after the 2005 Amazonian drought. We validated the CLM4.5 simulation of the drought impact and the recovery of leaf carbon (C) pool, an indicator of canopy structure, over southwestern Amazonia with QSCAT backscatter observations, which are sensitive to canopy structure change. We found that the leaf C pool simulated by CLM4.5 recovered to the 2000-2009 mean level (343 g C m-2) in 3 years after a sharp decrease in 2005, consistent with the QSCAT observed slow recovery. Through sensitivity experiments, we found that the slow C recovery was primarily due to biotic factors represented by the canopy damage and reduction of plant C pools. The recovery of soil water and the coupling between water and C pools, which is an environmental factor, only contributes 24% to the leaf C recovery. The results showed (1) the strength of scatterometer backscatter measurements in capturing canopy damage over tropical forests and in validating C cycle models and (2) the biotic factors play the dominant role in regulating the drought induced disturbance and persistent canopy changes in CLM4.5.

Influence of Solar and Thermal Radiation on Future Heat Stress Using CMIP5 Archive Driving the Community Land Model Version 4.5

NASA Astrophysics Data System (ADS)

Buzan, J. R.; Huber, M.

2015-12-01

The summer of 2015 has experienced major heat waves on 4 continents, and heat stress left ~4000 people dead in India and Pakistan. Heat stress is caused by a combination of meteorological factors: temperature, humidity, and radiation. The International Organization for Standardization (ISO) uses Wet Bulb Globe Temperature (WBGT)—an empirical metric this is calibrated with temperature, humidity, and radiation—for determining labor capacity during heat stress. Unfortunately, most literature studying global heat stress focuses on extreme temperature events, and a limited number of studies use the combination of temperature and humidity. Recent global assessments use WBGT, yet omit the radiation component without recalibrating the metric.Here we explicitly calculate future WBGT within a land surface model, including radiative fluxes as produced by a modeled globe thermometer. We use the Community Land Model version 4.5 (CLM4.5), which is a component model of the Community Earth System Model (CESM), and is maintained by the National Center for Atmospheric Research (NCAR). To drive our CLM4.5 simulations, we use greenhouse gasses Representative Concentration Pathway 8.5 (business as usual), and atmospheric output from the CMIP5 Archive. Humans work in a variety of environments, and we place the modeled globe thermometer in a variety of environments. We modify CLM4.5 code to calculate solar and thermal radiation fluxes below and above canopy vegetation, and in bare ground. To calculate wet bulb temperature, we implemented the HumanIndexMod into CLM4.5. The temperature, wet bulb temperature, and radiation fields are calculated at every model time step and are outputted 4x Daily. We use these fields to calculate WBGT and labor capacity for two time slices: 2026-2045 and 2081-2100.

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

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

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites

NASA Astrophysics Data System (ADS)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; Ren, Huiying; Liu, Ying; Swiler, Laura

2016-07-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

RAS mutation status predicts survival and patterns of recurrence in patients undergoing hepatectomy for colorectal liver metastases.

PubMed

Vauthey, Jean-Nicolas; Zimmitti, Giuseppe; Kopetz, Scott E; Shindoh, Junichi; Chen, Su S; Andreou, Andreas; Curley, Steven A; Aloia, Thomas A; Maru, Dipen M

2013-10-01

To determine the impact of RAS mutation status on survival and patterns of recurrence in patients undergoing curative resection of colorectal liver metastases (CLM) after preoperative modern chemotherapy. RAS mutation has been reported to be associated with aggressive tumor biology. However, the effect of RAS mutation on survival and patterns of recurrence after resection of CLM remains unclear. Somatic mutations were analyzed using mass spectroscopy in 193 patients who underwent single-regimen modern chemotherapy before resection of CLM. The relationship between RAS mutation status and survival outcomes was investigated. Detected somatic mutations included RAS (KRAS/NRAS) in 34 (18%), PIK3CA in 13 (7%), and BRAF in 2 (1%) patients. At a median follow-up of 33 months, 3-year overall survival (OS) rates were 81% in patients with wild-type versus 52.2% in patients with mutant RAS (P = 0.002); 3-year recurrence-free survival (RFS) rates were 33.5% with wild-type versus 13.5% with mutant RAS (P = 0.001). Liver and lung recurrences were observed in 89 and 83 patients, respectively. Patients with RAS mutation had a lower 3-year lung RFS rate (34.6% vs 59.3%, P < 0.001) but not a lower 3-year liver RFS rate (43.8% vs 50.2%, P = 0.181). In multivariate analyses, RAS mutation predicted worse OS [hazard ratio (HR) = 2.3, P = 0.002), overall RFS (HR = 1.9, P = 0.005), and lung RFS (HR = 2.0, P = 0.01), but not liver RFS (P = 0.181). RAS mutation predicts early lung recurrence and worse survival after curative resection of CLM. This information may be used to individualize systemic and local tumor-directed therapies and follow-up strategies.

RAS mutation status predicts survival and patterns of recurrence in patients undergoing hepatectomy for colorectal liver metastases

PubMed Central

Vauthey, Jean-Nicolas; Zimmitti, Giuseppe; Kopetz, Scott E.; Shindoh, Junichi; Chen, Su S.; Andreou, Andreas; Curley, Steven A.; Aloia, Thomas A.; Maru, Dipen M.

2013-01-01

Objective To determine the impact of RAS mutation status on survival and patterns of recurrence in patients undergoing curative resection of colorectal liver metastases (CLM) after preoperative modern chemotherapy. Summary Background Data RAS mutation has been reported to be associated with aggressive tumor biology. However, the effect of RAS mutation on survival and patterns of recurrence after resection of CLM remains unclear. Methods Somatic mutations were analyzed using mass spectroscopy in 193 patients who underwent single-regimen modern chemotherapy before resection of CLM. The relationship between RAS mutation status and survival outcomes was investigated. Results Detected somatic mutations included RAS (KRAS/NRAS) in 34 patients (18%), PIK3CA in 13 (7%), and BRAF in 2 (1%). At a median follow-up of 33 months, 3-year overall survival (OS) rates were 81% in patients with wild-type vs 52.2% in patients with mutant RAS (P=0.002); 3-year recurrence-free survival (RFS) rates were 33.5% with wild-type vs 13.5% with mutant RAS (P=0.001). Liver and lung recurrences were observed in 89 and 83 patients, respectively. Patients with RAS mutation had a lower 3-year lung RFS rate (34.6% vs 59.3%, P<0.001), but not a lower 3-year liver RFS rate (43.8% vs 50.2%, P=0.181). In multivariate analyses, RAS mutation predicted worse OS (hazard ratio [HR] 2.3, P=0.002), overall RFS (HR 1.9, P=0.005), and lung RFS (HR 2.0, P=0.01), but not liver RFS (P=0.181). Conclusions RAS mutation predicts early lung recurrence and worse survival after curative resection of CLM. This information may be used to individualize systemic and local tumor-directed therapies and follow-up strategies. PMID:24018645

Land-atmosphere coupling and climate prediction over the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Williams, Ian N.; Lu, Yaqiong; Kueppers, Lara M.; Riley, William J.; Biraud, Sebastien C.; Bagley, Justin E.; Torn, Margaret S.

2016-10-01

Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the National Center for Atmospheric Research Community Earth System Model (CESM1.2.2) and an off-line Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. To estimate the impacts of these errors on climate prediction, we modified CLM4.5 by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications improved the predicted soil moisture-evaporative fraction (EF) and LAI-EF correlations in off-line CLM4.5 and reduced the root-mean-square error in summer 2 m air temperature and precipitation in the coupled model. The modifications had the largest effect on prediction during a drought in summer 2006, when a warm bias in daytime 2 m air temperature was reduced from +6°C to a smaller cold bias of -1.3°C, and a corresponding dry bias in precipitation was reduced from -111 mm to -23 mm. The role of vegetation in droughts and heat waves is underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.

High Velocity Linear Induction Launcher with Exit-Edge Compensation for Testing of Aerospace Components

NASA Technical Reports Server (NTRS)

Kuznetsov, Stephen; Marriott, Darin

2008-01-01

Advances in ultra high speed linear induction electromagnetic launchers over the past decade have focused on magnetic compensation of the exit and entry-edge transient flux wave to produce efficient and compact linear electric machinery. The paper discusses two approaches to edge compensation in long-stator induction catapults with typical end speeds of 150 to 1,500 m/s. In classical linear induction machines, the exit-edge effect is manifest as two auxiliary traveling waves that produce a magnetic drag on the projectile and a loss of magnetic flux over the main surface of the machine. In the new design for the Stator Compensated Induction Machine (SCIM) high velocity launcher, the exit-edge effect is nulled by a dual wavelength machine or alternately the airgap flux is peaked at a location prior to the exit edge. A four (4) stage LIM catapult is presently being constructed for 180 m/s end speed operation using double-sided longitudinal flux machines. Advanced exit and entry edge compensation is being used to maximize system efficiency, and minimize stray heating of the reaction armature. Each stage will output approximately 60 kN of force and produce over 500 G s of acceleration on the armature. The advantage of this design is there is no ablation to the projectile and no sliding contacts, allowing repeated firing of the launcher without maintenance of any sort. The paper shows results of a parametric study for 500 m/s and 1,500 m/s linear induction launchers incorporating two of the latest compensation techniques for an air-core stator primary and an iron-core primary winding. Typical thrust densities for these machines are in the range of 150 kN/sq.m. to 225 kN/sq.m. and these compete favorably with permanent magnet linear synchronous machines. The operational advantages of the high speed SCIM launcher are shown by eliminating the need for pole-angle position sensors as would be required by synchronous systems. The stator power factor is also improved.

Nanoscale swimmers: hydrodynamic interactions and propulsion of molecular machines

NASA Astrophysics Data System (ADS)

Sakaue, T.; Kapral, R.; Mikhailov, A. S.

2010-06-01

Molecular machines execute nearly regular cyclic conformational changes as a result of ligand binding and product release. This cyclic conformational dynamics is generally non-reciprocal so that under time reversal a different sequence of machine conformations is visited. Since such changes occur in a solvent, coupling to solvent hydrodynamic modes will generally result in self-propulsion of the molecular machine. These effects are investigated for a class of coarse grained models of protein machines consisting of a set of beads interacting through pair-wise additive potentials. Hydrodynamic effects are incorporated through a configuration-dependent mobility tensor, and expressions for the propulsion linear and angular velocities, as well as the stall force, are obtained. In the limit where conformational changes are small so that linear response theory is applicable, it is shown that propulsion is exponentially small; thus, propulsion is nonlinear phenomenon. The results are illustrated by computations on a simple model molecular machine.

Start-up and control method and apparatus for resonant free piston Stirling engine

DOEpatents

Walsh, Michael M.

1984-01-01

A resonant free-piston Stirling engine having a new and improved start-up and control method and system. A displacer linear electrodynamic machine is provided having an armature secured to and movable with the displacer and having a stator supported by the Stirling engine housing in juxtaposition to the armature. A control excitation circuit is provided for electrically exciting the displacer linear electrodynamic machine with electrical excitation signals having substantially the same frequency as the desired frequency of operation of the Stirling engine. The excitation control circuit is designed so that it selectively and controllably causes the displacer electrodynamic machine to function either as a generator load to extract power from the displacer or the control circuit selectively can be operated to cause the displacer electrodynamic machine to operate as an electric drive motor to apply additional input power to the displacer in addition to the thermodynamic power feedback to the displacer whereby the displacer linear electrodynamic machine also is used in the electric drive motor mode as a means for initially starting the resonant free-piston Stirling engine.

Electric converters of electromagnetic strike machine with battery power

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Kargin, V. A.; Moiseev, A. P.; Chetverikov, E. A.

2018-03-01

At present, the application of pulse linear electromagnetic engines to drive strike machines for immersion of rod elements into the soil, strike drilling of shallow wells, dynamic probing of soils is recognized as quite effective. The pulse linear electromagnetic engine performs discrete consumption and conversion of electrical energy into mechanical work. Pulse dosing of a stream transmitted by the battery source to the pulse linear electromagnetic engine of the energy is provided by the electrical converter. The electric converters with the control of an electromagnetic strike machine as functions of time and armature movement, which form the unipolar supply pulses of voltage and current necessary for the normal operation of a pulse linear electromagnetic engine, are proposed. Electric converters are stable in operation, implement the necessary range of output parameters control determined by the technological process conditions, have noise immunity and automatic disconnection of power supply in emergency modes.

Extensive cutaneous larva migrans with folliculitis mimicking multimetameric herpes zoster presentation in an adult traveler returning from Thailand.

PubMed

Malvy, Denis; Ezzedine, Khaled; Pistone, Thierry; Receveur, Marie-Catherine; Longy-Boursier, Maïté

2006-01-01

Hookworm-related cutaneous larva migrans (CLM) is a frequent cutaneous disease among travelers returning from the tropics. It can be misdiagnosed or treated incorrectly. We present a 42-year-old French patient who contracted the disease during a holiday in Thailand and who experienced an extensive CLM syndrome with a less frequent abdominal localization and a pseudo-multimetameric homolateral topography. The condition was late diagnosed and secondarily efficiently cured by a unique administration of ivermectin. Simple anamnestic information--often revealing beach activities--and clinical aspect of the creeping eruption allow to prevent diagnosis delay and to avoid aggressive or inadequate intervention.

Evaluation and uncertainty analysis of regional-scale CLM4.5 net carbon flux estimates

NASA Astrophysics Data System (ADS)

Post, Hanna; Hendricks Franssen, Harrie-Jan; Han, Xujun; Baatz, Roland; Montzka, Carsten; Schmidt, Marius; Vereecken, Harry

2018-01-01

Modeling net ecosystem exchange (NEE) at the regional scale with land surface models (LSMs) is relevant for the estimation of regional carbon balances, but studies on it are very limited. Furthermore, it is essential to better understand and quantify the uncertainty of LSMs in order to improve them. An important key variable in this respect is the prognostic leaf area index (LAI), which is very sensitive to forcing data and strongly affects the modeled NEE. We applied the Community Land Model (CLM4.5-BGC) to the Rur catchment in western Germany and compared estimated and default ecological key parameters for modeling carbon fluxes and LAI. The parameter estimates were previously estimated with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) for four of the most widespread plant functional types in the catchment. It was found that the catchment-scale annual NEE was strongly positive with default parameter values but negative (and closer to observations) with the estimated values. Thus, the estimation of CLM parameters with local NEE observations can be highly relevant when determining regional carbon balances. To obtain a more comprehensive picture of model uncertainty, CLM ensembles were set up with perturbed meteorological input and uncertain initial states in addition to uncertain parameters. C3 grass and C3 crops were particularly sensitive to the perturbed meteorological input, which resulted in a strong increase in the standard deviation of the annual NEE sum (σ ∑ NEE) for the different ensemble members from ˜ 2 to 3 g C m-2 yr-1 (with uncertain parameters) to ˜ 45 g C m-2 yr-1 (C3 grass) and ˜ 75 g C m-2 yr-1 (C3 crops) with perturbed forcings. This increase in uncertainty is related to the impact of the meteorological forcings on leaf onset and senescence, and enhanced/reduced drought stress related to perturbation of precipitation. The NEE uncertainty for the forest plant functional type (PFT) was considerably lower (σ ∑ NEE ˜ 4.0-13.5 g C m-2 yr-1 with perturbed parameters, meteorological forcings and initial states). We conclude that LAI and NEE uncertainty with CLM is clearly underestimated if uncertain meteorological forcings and initial states are not taken into account.

A sub-canopy structure for simulating oil palm in the Community Land Model (CLM-Palm): phenology, allocation and yield

NASA Astrophysics Data System (ADS)

Fan, Y.; Roupsard, O.; Bernoux, M.; Le Maire, G.; Panferov, O.; Kotowska, M. M.; Knohl, A.

2015-11-01

In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land-atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but is meant of generic interest for other palm crops (e.g., coconut). The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced so that each phytomer has its own prognostic leaf growth and fruit yield capacity but with shared stem and root components. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, separated by a thermal period. An important phenological phase is identified for the oil palm - the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization and leaf pruning are represented. Parameters introduced for the oil palm were calibrated and validated with field measurements of leaf area index (LAI), yield and net primary production (NPP) from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched notably well between simulation and observation (mean percentage error = 3 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites and sufficiently represent the significant nitrogen- and age-related site-to-site variability in NPP and yield. Results also indicate that seasonal dynamics of yield and remaining small-scale site-to-site variability of NPP are driven by processes not yet implemented in the model or reflected in the input data. The new sub-canopy structure and phenology and allocation functions in CLM-Palm allow exploring the effects of tropical land-use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.

Assimilation of Remotely Sensed Leaf Area Index into the Community Land Model with Explicit Carbon and Nitrogen Components using Data Assimilation Research Testbed

NASA Astrophysics Data System (ADS)

Ling, X.; Fu, C.; Yang, Z. L.; Guo, W.

2017-12-01

Information of the spatial and temporal patterns of leaf area index (LAI) is crucial to understand the exchanges of momentum, carbon, energy, and water between the terrestrial ecosystem and the atmosphere, while both in-situ observation and model simulation usually show distinct deficiency in terms of LAI coverage and value. Land data assimilation, combined with observation and simulation together, is a promising way to provide variable estimation. The Data Assimilation Research Testbed (DART) developed and maintained by the National Centre for Atmospheric Research (NCAR) provides a powerful tool to facilitate the combination of assimilation algorithms, models, and real (as well as synthetic) observations to better understanding of all three. Here we systematically investigated the effects of data assimilation on improving LAI simulation based on NCAR Community Land Model with the prognostic carbon-nitrogen option (CLM4CN) linked with DART using the deterministic Ensemble Adjustment Kalman Filter (EAKF). Random 40-member atmospheric forcing was used to drive the CLM4CN with or without LAI assimilation. The Global Land Surface Satellite LAI data (GLASS LAI) LAI is assimilated into the CLM4CN at a frequency of 8 days, and LAI (and leaf carbon / nitrogen) are adjusted at each time step. The results show that assimilating remotely sensed LAI into the CLM4CN is an effective method for improving model performance. In detail, the CLM4-CN simulated LAI systematically overestimates global LAI, especially in low latitude with the largest bias of 5 m2/m2. While if updating both LAI and leaf carbon and leaf nitrogen simultaneously during assimilation, the analyzed LAI can be corrected, especially in low latitude regions with the bias controlled around ±1 m2/m2. Analyzed LAI could also represent the seasonal variation except for the Southern Temperate (23°S-90°S). The obviously improved regions located in the center of Africa, Amazon, the South of Eurasia, the northeast of China, and the west of Europe, where were mainly covered by evergreen/deciduous forests and mixed forests. In addition, the best method for LAI assimilation should include the EAKF method, the accepted percentage of all observation, as well as the carbon-nitrogen control.

World Association of Sleep Medicine (WASM) 2016 standards for recording and scoring leg movements in polysomnograms developed by a joint task force from the International and the European Restless Legs Syndrome Study Groups (IRLSSG and EURLSSG).

PubMed

Ferri, R; Fulda, S; Allen, R P; Zucconi, M; Bruni, O; Chokroverty, S; Ferini-Strambi, L; Frauscher, B; Garcia-Borreguero, D; Hirshkowitz, M; Högl, B; Inoue, Y; Jahangir, A; Manconi, M; Marcus, C L; Picchietti, D L; Plazzi, G; Winkelman, J W; Zak, R S

2016-10-01

This report presents the results of the work by a joint task force of the International and European Restless Legs Syndrome Study Groups and World Association of Sleep Medicine that revised and updated the current standards for recording and scoring leg movements (LM) in polysomnographic recordings (PSG). First, the background of the decisions made and the explanations of the new rules are reported and then specific standard rules are presented for recording, detecting, scoring and reporting LM activity in PSG. Each standard rule has been classified with a level of evidence. At the end of the paper, Appendix 1 provides algorithms to aid implementation of these new standards in software tools. There are two main changes introduced by these new rules: 1) Candidate LM (CLM), are any monolateral LM 0.5-10 s long or bilateral LM 0.5-15 s long; 2) periodic LM (PLM) are now defined by runs of at least four consecutive CLM with an intermovement interval ≥10 and ≤ 90 s without any CLM preceded by an interval <10 s interrupting the PLM series. There are also new options defining CLM associated with respiratory events. The PLM rate may now first be determined for all CLM not excluding any related to respiration (providing a consistent number across studies regardless of the rules used to define association with respiration) and, subsequently, the PLM rate should also be calculated without considering the respiratory related events. Finally, special considerations for pediatric studies are provided. The expert visual scoringof LM has only been altered by the new standards to require accepting all LM > 0.5 s regardless of duration, otherwise the technician scores the LM as for the old standards. There is a new criterion for the morphology of LM that applies only to computerized LM detection to better match expert visual detection. Available automatic scoring programs will incorporate all the new rules so that the new standards should reduce technician burden for scoring PLMS. Copyright © 2016 Elsevier B.V. All rights reserved.

An international land-biosphere model benchmarking activity for the IPCC Fifth Assessment Report (AR5)

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

Hoffman, Forrest M; Randerson, James T; Thornton, Peter E

2009-12-01

The need to capture important climate feedbacks in general circulation models (GCMs) has resulted in efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, called Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results (Friedlingstein et al., 2006). This work suggests that a more rigorous set of global offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are needed. The Carbon-Land Model Intercomparison Projectmore » (C-LAMP) was designed to meet this need by providing a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). Recently, a similar effort in Europe, called the International Land Model Benchmark (ILAMB) Project, was begun to assess the performance of European land surface models. These two projects will now serve as prototypes for a proposed international land-biosphere model benchmarking activity for those models participating in the IPCC Fifth Assessment Report (AR5). Initially used for model validation for terrestrial biogeochemistry models in the NCAR Community Land Model (CLM), C-LAMP incorporates a simulation protocol for both offline and partially coupled simulations using a prescribed historical trajectory of atmospheric CO2 concentrations. Models are confronted with data through comparisons against AmeriFlux site measurements, MODIS satellite observations, NOAA Globalview flask records, TRANSCOM inversions, and Free Air CO2 Enrichment (FACE) site measurements. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the CLM version 3 in the Community Climate System Model version 3 (CCSM3): the CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons of the CLM3 offline results against observational datasets have been performed and are described in Randerson et al. (2009). CLM version 4 has been evaluated using C-LAMP, showing improvement in many of the metrics. Efforts are now underway to initiate a Nitrogen-Land Model Intercomparison Project (N-LAMP) to better constrain the effects of the nitrogen cycle in biosphere models. Presented will be new results from C-LAMP for CLM4, initial N-LAMP developments, and the proposed land-biosphere model benchmarking activity.« less

Investigation of polar mesocyclones in Arctic Ocean using COSMO-CLM and WRF numerical models and remote sensing data

NASA Astrophysics Data System (ADS)

Varentsov, Mikhail; Verezemskaya, Polina; Baranyuk, Anastasia; Zabolotskikh, Elizaveta; Repina, Irina

2015-04-01

Polar lows (PL), high latitude marine mesoscale cyclones, are an enigmatic atmospheric phenomenon, which could result in windstorm damage of shipping and infrastructure in high latitudes. Because of their small spatial scales, short life times and their tendency to develop in remote data sparse regions (Zahn, Strorch, 2008), our knowledge of their behavior and climatology lags behind that of synoptic-scale cyclones. In case of continuing global warming (IPCC, 2013) and prospects of the intensification of economic activity and marine traffic in Arctic region, the problem of relevant simulation of this phenomenon by numerical models of the atmosphere, which could be used for weather and climate prediction, is especially important. The focus of this paper is researching the ability to simulate polar lows by two modern nonhydrostatic mesoscale numerical models, driven by realistic lateral boundary conditions from ERA-Interim reanalysis: regional climate model COSMO-CLM (Böhm et. al., 2009) and weather prediction and research model (WRF). Fields of wind, pressure and cloudiness, simulated by models, were compared with remote sensing data and ground meteorological observations for several cases, when polar lows were observed, in Norwegian, Kara and Laptev seas. Several types of satellite data were used: atmospheric water vapor, cloud liquid water content and surface wind fields were resampled by examining AMSR-E and AMSR-2 microwave radiometer data (MODIS Aqua, GCOM-W1), and wind fields were additionally extracted from QuickSCAT scatterometer. Infrared and visible pictures of cloud cover were obtained from MODIS (Aqua). Completed comparison shown that COSMO-CLM and WRF models could successfully reproduce evolution of polar lows and their most important characteristics such as size and wind speed in short experiments with WRF model and longer (up to half-year) experiments with COSMO-CLM model. Improvement of the quality of polar lows reproduction by these models in relation to source reanalysis fields were investigated. References: 1. Böhm U. et al. CLM - the climate version of LM: Brief description and long-term applications [Journal] // COSMO Newsletter. - 2006. - Vol. 6. 2. IPCC Fifth Assessment Report: Climate Change 2013 (AR5) Rep.,Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 3. Zahn, M., and H. von Storch (2008), A long-term climatology of North Atlantic polar lows, Geophys. Res. Lett., 35, L22702

Assessing Impacts of Selective Logging on Water, Energy, and Carbon Fluxes in Amazon Forests Using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)

NASA Astrophysics Data System (ADS)

Xu, Y.; Huang, M.; Keller, M. M.; Longo, M.; Knox, R. G.; Koven, C.; Fisher, R.

2016-12-01

As a key component in the climate system, old-growth tropical forests act as carbon sinks that remove CO2 from the atmosphere. However, these forests could be easily turned into C sources when disturbed. In fact, over half of tropical forests have been cleared or logged, and almost half of standing primary tropical forests are designated for timber production. Existing literature suggests that timber harvests alone could contribute up to 25% as much C losses as deforestation in Amazon. Yet, the spatial extent and recovery trajectory of disturbed forests in a changing climate are highly uncertain. This study constitutes our first attempt to quantify impacts of selective logging on water, energy, and carbon budgets in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). The Community Land Model version 4.5 (CLM4.5), with and without FATES turned on, are configured to run at two flux towers established in the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). One tower is located at in an old-growth forest (i.e. KM67) and the other is located in a selectively logged site (i.e., KM83). The three CLM4.5 options, (1) Satellite Phenology (CLM4.5-SP), (2) Century-based biogeochemical cycling with prognostic phenology (CLM4.5-BGC), and (3) CLM4.5-FATES, are spun up to equilibrium by recycling the observed meteorology at the towers, respectively. The simulated fluxes (i.e., sensible heat, latent heat, and net ecosystem exchange) are then compared to observations at KM67 to evaluate the capability of the models in capturing water and carbon dynamics in old-growth tropical forests. Our results suggest that all three models perform reasonably well in capturing the fluxes but demographic features simulated by FATES, such as distributions of diameter at breast height (DBH) and stem density (SD), are skewed heavily toward extremely large trees (e.g., > 100 cm in DBH) when compared to site surveys at the forest plots. Efforts are underway to evaluate parametric sensitivity in FATES to improve simulations in old-growth forests, and to implement parameterization to represent pulse disturbance to carbon pools created by logging events at different intensities, and follow-up recovery closely related to gap-phase regeneration and competition for lights within the gaps.

Land-atmosphere coupling strength determines impact of land cover change in South-East Asia

NASA Astrophysics Data System (ADS)

Toelle, M. H.

2017-12-01

In a previous modeling study of large-scale deforestation in South-East Asia, between 20° S and 20° N, a decrease of latent heat flux and an increase of sensible heat flux is found. This induced higher temperatures, and ultimately deepened the boundary layer with leading to less rainfall, but higher rainfall amounts and extreme temperatures. In order to attribute these differences to a feedback mechanism, a correlation analysis is performed. Therefore, the land-atmosphere coupling strength is compared with the impact of land cover change during seasonal periods and ENSO events. Hereby, ERA-Interim-driven COSMO-CLM simulations are analyzed for the period 1990 to 2004. The regional climate model is able to reproduce the overall soil moisture spatial pattern suggested by the observational Global Land Evaporation Amsterdam Model. However, COSMO-CLM shows more spatial variability and strength. By deforestation, the coupling strength between land and atmosphere is increased. Major changes in coupling strength occur during La Niña events. The impact due to deforestation depends non-linearly on the coupling strength exemplified by maximum temperature and evapotranspiration. It is shown that the magnitude of change in extreme temperature due to deforestation depends on the former coupling strength over the region. The rise in extreme temperatures due to deforestation occurs mainly over the mainland, where the coupling strength is strongest. The impact is less pronounced over the maritime islands due to the oceanic influence. It is suggested that the regional-scale impact depends on the model-specific coupling strength besides the physical reasoning over this region. Deforestation over South-East Asia will likely have consequences for the agricultural output and increase socio-economic vulnerability.

Power electromagnetic strike machine for engineering-geological surveys

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Chetverikov, E. A.; Kargin, V. A.; Moiseev, A. P.; Ivanova, Z. I.

2017-10-01

When implementing the processes of dynamic sensing of soils and pulsed nonexplosive seismic exploration, the most common and effective method is the strike one, which is provided by a variety of structure and parameters of pneumatic, hydraulic, electrical machines of strike action. The creation of compact portable strike machines which do not require transportation and use of mechanized means is important. A promising direction in the development of strike machines is the use of pulsed electromagnetic actuator characterized by relatively low energy consumption, relatively high specific performance and efficiency, and providing direct conversion of electrical energy into mechanical work of strike mass with linear movement trajectory. The results of these studies allowed establishing on the basis of linear electromagnetic motors the electromagnetic pulse machines with portable performance for dynamic sensing of soils and land seismic pulse of small depths.

A review on prognostic techniques for non-stationary and non-linear rotating systems

NASA Astrophysics Data System (ADS)

Kan, Man Shan; Tan, Andy C. C.; Mathew, Joseph

2015-10-01

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

[Effect of compaction pressure on the properties of dental machinable zirconia ceramic].

PubMed

Huang, Hui; Wei, Bin; Zhang, Fu-qiang; Sun, Jing; Gao, Lian

2010-10-01

To investigate the effect of compaction pressure on the linear shrinkage, sintering property and machinability of the dental zirconia ceramic. The nano-size zirconia powder was compacted at different isostatic pressure and sintered at different temperature. The linear shrinkage of sintered body was measured and the relative density was tested using the Archimedes method. The cylindrical surface of pre-sintering blanks was traversed using a hard metal tool. Surface and edge quality were checked visually using light stereo microscopy. The sintering behaviour depended on the compaction pressure. Increasing compaction pressure led to higher sintering rate and lower sintering temperature. Increasing compaction pressure also led to decreasing linear shrinkage of the sintered bodies, from 24.54% of 50 MPa to 20.9% of 400 MPa. Compaction pressure showed only a weak influence on machinability of zirconia blanks, but the higher compaction pressure resulted in the poor surface quality. The better sintering property and machinability of dental zirconia ceramic is found for 200-300 MPa compaction pressure.

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics

PubMed Central

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications. PMID:27806075

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

PubMed

Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

PubMed

Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

2017-05-01

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

Numerical analysis method for linear induction machines.

NASA Technical Reports Server (NTRS)

Elliott, D. G.

1972-01-01

A numerical analysis method has been developed for linear induction machines such as liquid metal MHD pumps and generators and linear motors. Arbitrary phase currents or voltages can be specified and the moving conductor can have arbitrary velocity and conductivity variations from point to point. The moving conductor is divided into a mesh and coefficients are calculated for the voltage induced at each mesh point by unit current at every other mesh point. Combining the coefficients with the mesh resistances yields a set of simultaneous equations which are solved for the unknown currents.

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

PubMed

Wang, Hsin-Wei; Lin, Ya-Chi; Pai, Tun-Wen; Chang, Hao-Teng

2011-01-01

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%).

A Comparison of Internal Dispositions and Career Trajectories after Collaborative versus Apprenticed Research Experiences for Undergraduates

PubMed Central

Frantz, Kyle J.; Demetrikopoulos, Melissa K.; Britner, Shari L.; Carruth, Laura L.; Williams, Brian A.; Pecore, John L.; DeHaan, Robert L.; Goode, Christopher T.

2017-01-01

Undergraduate research experiences confer benefits on students bound for science, technology, engineering, and mathematics (STEM) careers, but the low number of research professionals available to serve as mentors often limits access to research. Within the context of our summer research program (BRAIN), we tested the hypothesis that a team-based collaborative learning model (CLM) produces student outcomes at least as positive as a traditional apprenticeship model (AM). Through stratified, random assignment to conditions, CLM students were designated to work together in a teaching laboratory to conduct research according to a defined curriculum led by several instructors, whereas AM students were paired with mentors in active research groups. We used pre-, mid-, and postprogram surveys to measure internal dispositions reported to predict progress toward STEM careers, such as scientific research self-efficacy, science identity, science anxiety, and commitment to a science career. We are also tracking long-term retention in science-related career paths. For both short- and longer-term outcomes, the two program formats produced similar benefits, supporting our hypothesis that the CLM provides positive outcomes while conserving resources, such as faculty mentors. We discuss this method in comparison with course-based undergraduate research and recommend its expansion to institutional settings in which mentor resources are scarce. PMID:28130268

A New Biogeochemical Computational Framework Integrated within the Community Land Model

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

A warm-season comparison of WRF coupled to the CLM4.0, Noah-MP, and Bucket hydrology land surface schemes over the central USA

NASA Astrophysics Data System (ADS)

Van Den Broeke, Matthew S.; Kalin, Andrew; Alavez, Jose Abraham Torres; Oglesby, Robert; Hu, Qi

2017-11-01

In climate modeling studies, there is a need to choose a suitable land surface model (LSM) while adhering to available resources. In this study, the viability of three LSM options (Community Land Model version 4.0 [CLM4.0], Noah-MP, and the five-layer thermal diffusion [Bucket] scheme) in the Weather Research and Forecasting model version 3.6 (WRF3.6) was examined for the warm season in a domain centered on the central USA. Model output was compared to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, a gridded observational dataset including mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, latent heat (LH) flux, sensible heat (SH) flux, and soil water content (SWC) were compared to observations from sites in the Central and Southern Great Plains region. An overall warm bias was found in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. These three LSMs produced similar patterns of wet and dry biases. Model output of SWC and LH/SH fluxes were compared to observations, and did not show a consistent bias. Both sophisticated LSMs appear to be viable options for simulating the effects of land use change in the central USA.

Is there potential added value in COSMO-CLM forced by ERA reanalysis data?

NASA Astrophysics Data System (ADS)

Lenz, Claus-Jürgen; Früh, Barbara; Adalatpanah, Fatemeh Davary

2017-12-01

An application of the potential added value (PAV) concept suggested by Di Luca et al. (Clim Dyn 40:443-464, 2013a) is applied to ERA Interim driven runs of the regional climate model COSMO-CLM. They are performed for the time period 1979-2013 for the EURO-CORDEX domain at horizontal grid resolutions 0.11°, 0.22°, and 0.44° such that the higher resolved model grid fits into the next coarser grid. The concept of the potential added value is applied to annual, seasonal, and monthly means of the 2 m air temperature. Results show the highest potential added value at the run with the finest grid and generally increasing PAV with increasing resolution. The potential added value strongly depends on the season as well as the region of consideration. The gain of PAV is higher enhancing the resolution from 0.44° to 0.22° than from 0.22° to 0.11°. At grid aggregations to 0.88° and 1.76° the differences in PAV between the COSMO-CLM runs on the mentioned grid resolutions are maximal. They nearly vanish at aggregations to even coarser grids. In all cases the PAV is dominated by at least 80% by its stationary part.

Implementation of Coupled Skin Temperature Analysis and Bias Correction in a Global Atmospheric Data Assimilation System

NASA Technical Reports Server (NTRS)

Radakovich, Jon; Bosilovich, M.; Chern, Jiun-dar; daSilva, Arlindo

2004-01-01

The NASA/NCAR Finite Volume GCM (fvGCM) with the NCAR CLM (Community Land Model) version 2.0 was integrated into the NASA/GMAO Finite Volume Data Assimilation System (fvDAS). A new method was developed for coupled skin temperature assimilation and bias correction where the analysis increment and bias correction term is passed into the CLM2 and considered a forcing term in the solution to the energy balance. For our purposes, the fvDAS CLM2 was run at 1 deg. x 1.25 deg. horizontal resolution with 55 vertical levels. We assimilate the ISCCP-DX (30 km resolution) surface temperature product. The atmospheric analysis was performed 6-hourly, while the skin temperature analysis was performed 3-hourly. The bias correction term, which was updated at the analysis times, was added to the skin temperature tendency equation at every timestep. In this presentation, we focus on the validation of the surface energy budget at the in situ reference sites for the Coordinated Enhanced Observation Period (CEOP). We will concentrate on sites that include independent skin temperature measurements and complete energy budget observations for the month of July 2001. In addition, MODIS skin temperature will be used for validation. Several assimilations were conducted and preliminary results will be presented.

Design considerations for ultra-precision magnetic bearing supported slides

NASA Technical Reports Server (NTRS)

Slocum, Alexander H.; Eisenhaure, David B.

1993-01-01

Development plans for a prototype servocontrolled machine with 1 angstrom resolution of linear motion and 50 mm range of travel are described. Two such devices could then be combined to produce a two dimensional machine for probing large planar objects with atomic resolution, the Angstrom Resolution Measuring Machine (ARMM).

Active balance system and vibration balanced machine

NASA Technical Reports Server (NTRS)

White, Maurice A. (Inventor); Qiu, Songgang (Inventor); Augenblick, John E. (Inventor); Peterson, Allen A. (Inventor)

2005-01-01

An active balance system is provided for counterbalancing vibrations of an axially reciprocating machine. The balance system includes a support member, a flexure assembly, a counterbalance mass, and a linear motor or an actuator. The support member is configured for attachment to the machine. The flexure assembly includes at least one flat spring having connections along a central portion and an outer peripheral portion. One of the central portion and the outer peripheral portion is fixedly mounted to the support member. The counterbalance mass is fixedly carried by the flexure assembly along another of the central portion and the outer peripheral portion. The linear motor has one of a stator and a mover fixedly mounted to the support member and another of the stator and the mover fixedly mounted to the counterbalance mass. The linear motor is operative to axially reciprocate the counterbalance mass.

Effect of hole geometry and Electric-Discharge Machining (EDM) on airflow rates through small diameter holes in turbine blade material

NASA Technical Reports Server (NTRS)

Hippensteele, S. A.; Cochran, R. P.

1980-01-01

The effects of two design parameters, electrode diameter and hole angle, and two machine parameters, electrode current and current-on time, on air flow rates through small-diameter (0.257 to 0.462 mm) electric-discharge-machined holes were measured. The holes were machined individually in rows of 14 each through 1.6 mm thick IN-100 strips. The data showed linear increase in air flow rate with increases in electrode cross sectional area and current-on time and little change with changes in hole angle and electrode current. The average flow-rate deviation (from the mean flow rate for a given row) decreased linearly with electrode diameter and increased with hole angle. Burn time and finished hole diameter were also measured.

Sex differences in the representation of call stimuli in a songbird secondary auditory area

PubMed Central

Giret, Nicolas; Menardy, Fabien; Del Negro, Catherine

2015-01-01

Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM), while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer, and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird's own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of information about the bird's auditory experience in females. PMID:26578918

Quantifying the Impact of Mountain Pine Beetle Disturbances on Forest Carbon Pools and Fluxes in the Western US using the NCAR Community Land Model

NASA Astrophysics Data System (ADS)

Edburg, S. L.; Hicke, J. A.; Lawrence, D. M.; Thornton, P. E.

2009-12-01

Forest disturbances, such as fire, insects, and land-use change, significantly alter carbon budgets by changing carbon pools and fluxes. The mountain pine beetle (MPB) kills millions of hectares of trees in the western US, similar to the area killed by fire. Mountain pine beetles kill host trees by consuming the inner bark tissue, and require host tree death for reproduction. Despite being a significant disturbance to forested ecosystems, insects such as MPB are typically not represented in biogeochemical models, thus little is known about their impact on the carbon cycle. We investigate the role of past MPB outbreaks on carbon cycling in the western US using the NCAR Community Land Model with Carbon and Nitrogen cycles (CLM-CN). CLM-CN serves as the land model to the Community Climate System Model (CCSM), providing exchanges of energy, momentum, water, carbon, and nitrogen between the land and atmosphere. We run CLM-CN over the western US extending to eastern Colorado with a spatial resolution of 0.5° and a half hour time step. The model is first spun-up with repeated NCEP forcing (1948-1972) until carbon stocks and fluxes reach equilibrium (~ 3000 years), and then run from 1850 to 2004 with NCEP forcing and a dynamic plant functional type (PFT) database. Carbon stocks from this simulation are compared with stocks from the Forest Inventory Analysis (FIA) program. We prescribe MPB mortality area, once per year, in CLM-CN using USFS Aerial Detection Surveys (ADS) from the last few decades. We simulate carbon impacts of tree mortality by MPB within a model grid cell by moving carbon from live vegetative pools (leaf, stem, and roots) to dead pools (woody debris, litter, and dead roots). We compare carbon pools and fluxes for two simulations, one without MPB outbreaks and one with MPB outbreaks.

Evaluating the Community Land Model in a pine stand with shading manipulations and 13CO2 labeling

NASA Astrophysics Data System (ADS)

Mao, J.; Ricciuto, D. M.; Thornton, P. E.; Warren, J. M.; King, A. W.; Shi, X.; Iversen, C. M.; Norby, R. J.

2016-02-01

Carbon allocation and flow through ecosystems regulates land surface-atmosphere CO2 exchange and thus is a key, albeit uncertain, component of mechanistic models. The Partitioning in Trees and Soil (PiTS) experiment-model project tracked carbon allocation through a young Pinus taeda stand following pulse labeling with 13CO2 and two levels of shading. The field component of this project provided process-oriented data that were used to evaluate terrestrial biosphere model simulations of rapid shifts in carbon allocation and hydrological dynamics under varying environmental conditions. Here we tested the performance of the Community Land Model version 4 (CLM4) in capturing short-term carbon and water dynamics in relation to manipulative shading treatments and the timing and magnitude of carbon fluxes through various compartments of the ecosystem. When calibrated with pretreatment observations, CLM4 was capable of closely simulating stand-level biomass, transpiration, leaf-level photosynthesis, and pre-labeling 13C values. Over the 3-week treatment period, CLM4 generally reproduced the impacts of shading on soil moisture changes, relative change in stem carbon, and soil CO2 efflux rate. Transpiration under moderate shading was also simulated well by the model, but even with optimization we were not able to simulate the high levels of transpiration observed in the heavy shading treatment, suggesting that the Ball-Berry conductance model is inadequate for these conditions. The calibrated version of CLM4 gave reasonable estimates of label concentration in phloem and in soil surface CO2 after 3 weeks of shade treatment, but it lacks the mechanisms needed to track the labeling pulse through plant tissues on shorter timescales. We developed a conceptual model for photosynthate transport based on the experimental observations, and we discussed conditions under which the hypothesized mechanisms could have an important influence on model behavior in larger-scale applications. Implications for future experimental studies are described, some of which are already being implemented in follow-on studies.

Insights into mechanisms governing forest carbon response to nitrogen deposition: a model-data comparison using observed responses to nitrogen addition

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Bonan, G. B.; Goodale, C. L.

2013-01-01

In many forest ecosystems, nitrogen (N) deposition enhances plant uptake of carbon dioxide, thus reducing climate warming from fossil fuel emissions. Therefore, accurately modeling how forest carbon (C) sequestration responds to N deposition is critical for understanding how future changes in N availability will influence climate. Here, we use observations of forest C response to N inputs along N deposition gradients and at five temperate forest sites with fertilization experiments to test and improve a~global biogeochemical model (CLM-CN 4.0). We show that the CLM-CN plant C growth response to N deposition was smaller than observed and the modeled response to N fertilization was larger than observed. A set of modifications to the CLM-CN improved the correspondence between model predictions and observational data (1) by increasing the aboveground C storage in response to historical N deposition (1850-2004) from 14 to 34 kg C per additional kg N added through deposition and (2) by decreasing the aboveground net primary productivity response to N fertilization experiments from 91 to 57 g C m-2 yr-1. Modeled growth response to N deposition was most sensitive to altering the processes that control plant N uptake and the pathways of N loss. The response to N deposition also increased with a more closed N cycle (reduced N fixation and N gas loss) and decreased when prioritizing microbial over plant uptake of soil inorganic N. The net effect of all the modifications to the CLM-CN resulted in greater retention of N deposition and a greater role of synergy between N deposition and rising atmospheric CO2 as a mechanism governing increases in temperate forest primary production over the 20th century. Overall, testing models with both the response to gradual increases in N inputs over decades (N deposition) and N pulse additions of N over multiple years (N fertilization) allows for greater understanding of the mechanisms governing C-N coupling.

Insights into mechanisms governing forest carbon response to nitrogen deposition: a model-data comparison using observed responses to nitrogen addition

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Bonan, G. B.; Goodale, C. L.

2013-06-01

In many forest ecosystems, nitrogen (N) deposition enhances plant uptake of carbon dioxide, thus reducing climate warming from fossil fuel emissions. Therefore, accurately modeling how forest carbon (C) sequestration responds to N deposition is critical for understanding how future changes in N availability will influence climate. Here, we use observations of forest C response to N inputs along N deposition gradients and at five temperate forest sites with fertilization experiments to test and improve a global biogeochemical model (CLM-CN 4.0). We show that the CLM-CN plant C growth response to N deposition was smaller than observed and the modeled response to N fertilization was larger than observed. A set of modifications to the CLM-CN improved the correspondence between model predictions and observational data (1) by increasing the aboveground C storage in response to historical N deposition (1850-2004) from 14 to 34 kg C per additional kg N added through deposition and (2) by decreasing the aboveground net primary productivity response to N fertilization experiments from 91 to 57 g C m-2 yr-1. Modeled growth response to N deposition was most sensitive to altering the processes that control plant N uptake and the pathways of N loss. The response to N deposition also increased with a more closed N cycle (reduced N fixation and N gas loss) and decreased when prioritizing microbial over plant uptake of soil inorganic N. The net effect of all the modifications to the CLM-CN resulted in greater retention of N deposition and a greater role of synergy between N deposition and rising atmospheric CO2 as a mechanism governing increases in temperate forest primary production over the 20th century. Overall, testing models with both the response to gradual increases in N inputs over decades (N deposition) and N pulse additions of N over multiple years (N fertilization) allows for greater understanding of the mechanisms governing C-N coupling.

A generic biogeochemical module for Earth system models: Next Generation BioGeoChemical Module (NGBGC), version 1.0

NASA Astrophysics Data System (ADS)

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

2013-11-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into Earth system models (e.g., community land models (CLMs)), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module, Next Generation BioGeoChemical Module (NGBGC), version 1.0, with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter, and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into CLM. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems. The method presented here could in theory be applied to simulate biogeochemical cycles in other Earth system models.

Sex differences in the representation of call stimuli in a songbird secondary auditory area.

PubMed

Giret, Nicolas; Menardy, Fabien; Del Negro, Catherine

2015-01-01

Understanding how communication sounds are encoded in the central auditory system is critical to deciphering the neural bases of acoustic communication. Songbirds use learned or unlearned vocalizations in a variety of social interactions. They have telencephalic auditory areas specialized for processing natural sounds and considered as playing a critical role in the discrimination of behaviorally relevant vocal sounds. The zebra finch, a highly social songbird species, forms lifelong pair bonds. Only male zebra finches sing. However, both sexes produce the distance call when placed in visual isolation. This call is sexually dimorphic, is learned only in males and provides support for individual recognition in both sexes. Here, we assessed whether auditory processing of distance calls differs between paired males and females by recording spiking activity in a secondary auditory area, the caudolateral mesopallium (CLM), while presenting the distance calls of a variety of individuals, including the bird itself, the mate, familiar and unfamiliar males and females. In males, the CLM is potentially involved in auditory feedback processing important for vocal learning. Based on both the analyses of spike rates and temporal aspects of discharges, our results clearly indicate that call-evoked responses of CLM neurons are sexually dimorphic, being stronger, lasting longer, and conveying more information about calls in males than in females. In addition, how auditory responses vary among call types differ between sexes. In females, response strength differs between familiar male and female calls. In males, temporal features of responses reveal a sensitivity to the bird's own call. These findings provide evidence that sexual dimorphism occurs in higher-order processing areas within the auditory system. They suggest a sexual dimorphism in the function of the CLM, contributing to transmit information about the self-generated calls in males and to storage of information about the bird's auditory experience in females.

Multicenter Validation Study of Pathologic Response and Tumor Thickness at the Tumor–Normal Liver Interface as Independent Predictors of Disease-Free Survival after Preoperative Chemotherapy and Surgery for Colorectal Liver Metastases

PubMed Central

Brouquet, Antoine; Zimmitti, Giuseppe; Kopetz, Scott; Stift, Judith; Julié, Catherine; Lemaistre, Anne-Isabelle; Agarwal, Atin; Patel, Viren; Benoist, Stephane; Nordlinger, Bernard; Gandini, Alessandro; Rivoire, Michel; Stremitzer, Stefan; Gruenberger, Thomas; Vauthey, Jean-Nicolas; Maru, Dipen M.

2014-01-01

Purpose To validate pathologic markers of response to preoperative chemotherapy as predictors of disease-free survival (DFS) after resection of colorectal liver metastases (CLM). Patients and Methods One hundred seventy one patients who underwent resection of CLM after preoperative chemotherapy at 4 centers were studied. Pathologic response defined as proportion of tumor cells remaining (categorized complete (0%), major (<50%) or minor (≥50%)) and tumor thickness at tumor–normal liver interface (TNI) (categorized <0.5 mm, 0.5 mm-<5 mm and ≥5 mm)—were assessed by a central pathology reviewer and local pathologists. Results Pathologic response was complete in 8%, major in 49% and minor in 43%. Tumor thickness at the TNI was <0.5 mm in 21%, 0.5 mm-<5 mm in 56% and ≥5 mm in 23%.In multivariate analyses, using either pathologic response or tumor thickness at TNI, pathologic response (P=.002,.009), tumor thickness at TNI (P=0.015, <.001), duration of preoperative chemotherapy(P=.028,.043), number of CLM (P=.038,.037) and margin (P=.011,.016) were associated with DFS. In a multivariate analysis using both parameters, tumor thickness at TNI (P=.004,.015), duration of preoperative chemotherapy(P=.025), number of nodules(P=.027) and margin(P=.014) were associated with DFS. Tumor size by pathology examination was the predictor of pathologic response. Predictors of tumor thickness at the TNI were tumor size and chemotherapy regimen. There was near perfect agreement for pathologic response (κ=.82) and substantial agreement (κ=.76) for tumor thickness between central reviewer and local pathologists. Conclusion Pathologic response and tumor thickness at the TNI are valid predictors of DFS after preoperative chemotherapy and surgery for CLM. PMID:23868456

Multicenter validation study of pathologic response and tumor thickness at the tumor-normal liver interface as independent predictors of disease-free survival after preoperative chemotherapy and surgery for colorectal liver metastases.

PubMed

Brouquet, Antoine; Zimmitti, Giuseppe; Kopetz, Scott; Stift, Judith; Julié, Catherine; Lemaistre, Anne-Isabelle; Agarwal, Atin; Patel, Viren; Benoist, Stephane; Nordlinger, Bernard; Gandini, Alessandro; Rivoire, Michel; Stremitzer, Stefan; Gruenberger, Thomas; Vauthey, Jean-Nicolas; Maru, Dipen M

2013-08-01

To validate pathologic markers of response to preoperative chemotherapy as predictors of disease-free survival (DFS) after resection of colorectal liver metastases (CLM). One hundred seventy-one patients who underwent resection of CLM after preoperative chemotherapy at 4 centers were studied. Pathologic response-defined as the proportion of tumor cells remaining (complete, 0%; major, <50%; minor, ≥50%) and tumor thickness at the tumor-normal liver interface (TNI) (<0.5 mm, 0.5 to <5 mm, ≥5 mm)-was assessed by a central pathology reviewer and local pathologists. Pathologic response was complete in 8% of patients, major in 49% of patients, and minor in 43% of patients. Tumor thickness at the TNI was <0.5 mm in 21% of patients, 0.5 to <5 mm in 56% of patients, and ≥5 mm in 23% of patients. On multivariate analyses, using either pathologic response or tumor thickness at TNI, pathologic response (P = .002, .009), tumor thickness at TNI (P = 0.015, <.001), duration of preoperative chemotherapy (P = .028, .043), number of CLM (P = .038, . 037), and margin (P = .011, .016) were associated with DFS. In a multivariate analysis using both parameters, tumor thickness at TNI (P = .004, .015), duration of preoperative chemotherapy (P = .025), number of nodules (P = .027), and margin (P = .014) were associated with DFS. Tumor size by pathology examination was the predictor of pathologic response. Predictors of tumor thickness at the TNI were tumor size and chemotherapy regimen. There was near perfect agreement for pathologic response (κ = .82) and substantial agreement (κ = .76) for tumor thickness between the central reviewer and local pathologists. Pathologic response and tumor thickness at the TNI are valid predictors of DFS after preoperative chemotherapy and surgery for CLM. Copyright © 2013 American Cancer Society.

Evaluation of hydrologic components of community land model 4 and bias identification

DOE PAGES

Du, Enhao; Vittorio, Alan Di; Collins, William D.

2015-04-01

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties inmore » the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.« less

Efficacy of Preoperative Portal Vein Embolization Among Patients with Hepatocellular Carcinoma, Biliary Tract Cancer, and Colorectal Liver Metastases: A Comparative Study Based on Single-Center Experience of 319 Cases.

PubMed

Yamashita, Suguru; Sakamoto, Yoshihiro; Yamamoto, Satoshi; Takemura, Nobuyuki; Omichi, Kiyohiko; Shinkawa, Hiroji; Mori, Kazuhiro; Kaneko, Junichi; Akamatsu, Nobuhisa; Arita, Junichi; Hasegawa, Kiyoshi; Kokudo, Norihiro

2017-06-01

Efficacy of preoperative portal vein embolization (PVE) has been established; however, differences of outcomes among diseases, including hepatocellular carcinoma (HCC), biliary tract cancer (BTC), and colorectal liver metastases (CLM), are unclear. Subjects included patients in a prospectively collected database undergoing PVE (from 1995 to 2013). A future liver remnant (FLR) volume ≥40% is the minimal requirement for patients with an indocyanine green retention rate at 15 min (ICGR15) <10%, and stricter criteria (FLR volume ≥50%) have been applied for patients with 20% > ICGR15 ≥ 10%. Patient characteristics and survivals were compared among those three diseases, and predictors of dropout and better FLR hypertrophy were determined. In 319 consecutive patients undergoing PVE for HCC (n = 70), BTC (n = 172), and CLM (n = 77), the degree of hypertrophy did not significantly differ by cancer types (median 10, 9.6, and 10%, respectively). Eighty percent (256 of 319) of patients completed subsequent hepatectomy after a median waiting interval of 24 days (range 5-90), while dropout after PVE was more common in BTC or CLM (odds ratio 2.75, p = 0.018), mainly because of disease progression. Ninety-day liver-related mortality after hepatectomy was 0% in the entire cohort, and 5-year overall survival of patients with HCC, BTC, and CLM was 56, 50, and 51%, respectively (p = 0.948). No patients who dropped out survived more than 2.5 years after PVE. PVE produced equivalent FLR hypertrophy among the three diseases as long as liver function was fulfilling the preset criteria; however, the completion rate of subsequent hepatectomy was highest in HCC. PVE followed by hepatectomy was a safe and feasible strategy for otherwise unresectable disease irrespective of cancer types.

Lawrence Livermore National Laboratory ULTRA-350 Test Bed

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

Hopkins, D J; Wulff, T A; Carlisle, K

2001-04-10

LLNL has many in-house designed high precision machine tools. Some of these tools include the Large Optics Diamond Turning Machine (LODTM) [1], Diamond Turning Machine No.3 (DTM-3) and two Precision Engineering Research Lathes (PERL-1 and PERL-11). These machines have accuracy in the sub-micron range and in most cases position resolution in the couple of nanometers range. All of these machines are built with similar underlying technologies. The machines use capstan drive technology, laser interferometer position feedback, tachometer velocity feedback, permanent magnet (PM) brush motors and analog velocity and position loop servo compensation [2]. The machine controller does not perform anymore » servo compensation it simply computes the differences between the commanded position and the actual position (the following error) and sends this to a D/A for the analog servo position loop. LLNL is designing a new high precision diamond turning machine. The machine is called the ULTRA 350 [3]. In contrast to many of the proven technologies discussed above, the plan for the new machine is to use brushless linear motors, high precision linear scales, machine controller motor commutation and digital servo compensation for the velocity and position loops. Although none of these technologies are new and have been in use in industry, applications of these technologies to high precision diamond turning is limited. To minimize the risks of these technologies in the new machine design, LLNL has established a test bed to evaluate these technologies for application in high precision diamond turning. The test bed is primarily composed of commercially available components. This includes the slide with opposed hydrostatic bearings, the oil system, the brushless PM linear motor, the two-phase input three-phase output linear motor amplifier and the system controller. The linear scales are not yet commercially available but use a common electronic output format. As of this writing, the final verdict for the use of these technologies is still out but the first part of the work has been completed with promising results. The goal of this part of the work was to close a servo position loop around a slide incorporating these technologies and to measure the performance. This paper discusses the tests that were setup for system evaluation and the results of the measurements made. Some very promising results include; slide positioning to nanometer level and slow speed slide direction reversal at less than 100nm/min with no observed discontinuities. This is very important for machine contouring in diamond turning. As a point of reference, at 100 nm/min it would take the slide almost 7 years to complete the full designed travel of 350 mm. This speed has been demonstrated without the use of a velocity sensor. The velocity is derived from the position sensor. With what has been learned on the test bed, the paper finishes with a brief comparison of the old and new technologies. The emphasis of this comparison will be on the servo performance as illustrated with bode plot diagrams.« less

Lawrence Livermore National Laboratory ULTRA-350 Test Bed

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

Hopkins, D J; Wulff, T A; Carlisle, K

2001-04-10

LLNL has many in-house designed high precision machine tools. Some of these tools include the Large Optics Diamond Turning Machine (LODTM) [1], Diamond Turning Machine No.3 (DTM-3) and two Precision Engineering Research Lathes (PERL-I and PERL-II). These machines have accuracy in the sub-micron range and in most cases position resolution in the couple of nanometers range. All of these machines are built with similar underlying technologies. The machines use capstan drive technology, laser interferometer position feedback, tachometer velocity feedback, permanent magnet (PM) brush motors and analog velocity and position loop servo compensation [2]. The machine controller does not perform anymore » servo compensation it simply computes the differences between the commanded position and the actual position (the following error) and sends this to a D/A for the analog servo position loop. LLNL is designing a new high precision diamond turning machine. The machine is called the ULTRA 350 [3]. In contrast to many of the proven technologies discussed above, the plan for the new machine is to use brushless linear motors, high precision linear scales, machine controller motor commutation and digital servo compensation for the velocity and position loops. Although none of these technologies are new and have been in use in industry, applications of these technologies to high precision diamond turning is limited. To minimize the risks of these technologies in the new machine design, LLNL has established a test bed to evaluate these technologies for application in high precision diamond turning. The test bed is primarily composed of commercially available components. This includes the slide with opposed hydrostatic bearings, the oil system, the brushless PM linear motor, the two-phase input three-phase output linear motor amplifier and the system controller. The linear scales are not yet commercially available but use a common electronic output format. As of this writing, the final verdict for the use of these technologies is still out but the first part of the work has been completed with promising results. The goal of this part of the work was to close a servo position loop around a slide incorporating these technologies and to measure the performance. This paper discusses the tests that were setup for system evaluation and the results of the measurements made. Some very promising results include; slide positioning to nanometer level and slow speed slide direction reversal at less than 100nm/min with no observed discontinuities. This is very important for machine contouring in diamond turning. As a point of reference, at 100 nm/min it would take the slide almost 7 years to complete the full designed travel of 350 mm. This speed has been demonstrated without the use of a velocity sensor. The velocity is derived from the position sensor. With what has been learned on the test bed, the paper finishes with a brief comparison of the old and new technologies. The emphasis of this comparison will be on the servo performance as illustrated with bode plot diagrams.« less

Assessment of the water and energy budget simulation of three land surface models: CLM4.5, CoLM2014, and CoLM2005

NASA Astrophysics Data System (ADS)

Li, C.; Lu, H.; Wen, X.

2015-12-01

Land surface model (LSM), which simulates energy, water and momentum exchanges between land and atmosphere, is an important component of Earth System Models (ESM). As shown in CMIP5, different ESMs usually use different LSMs and represent various land surface status. In order to select a land surface model which could be embedded into the ESM developed in Tsinghua University, we firstly evaluate the performance of three LSMs: Community Land Model (CLM4.5) and two different versions of Common Land Model (CoLM2005 and CoLM2014). All of three models were driven by CRUNCEP data and simulation results from 1980 to 2010 were used in this study. Diagnostic data provided by NCAR, global latent and sensible heat flux map estimated by Jung, net radiation from SRB, and in situ observation collected from FluxNet were used as reference data. Two variables, surface runoff and snow depth, were used for evaluating the model performance in water budget simulation, while three variables including net radiation, sensible heat, and latent heat were used for assessing energy budget simulation. For 30 years averaged runoff, global average value of Colm2014 is 0.44mm/day and close to the diagnostic value of 0.75 mm/day, while that of Colm2005 is 0.44mm/day and that of CLM is 0.20mm/day. For snow depth simulation, three models all have overestimation in the Northern Hemisphere and underestimation in the Southern Hemisphere compare to diagnostic data. For 30 years energy budget simulation, at global scale, CoLM2005 performs best in latent heat estimation, CoLM2014 performs best in sensible heat simulation, and CoLM2005 and CoLM2014 make similar performance in net radiation estimation but is still better than CLM. At regional and local scale, comparing to the four years average of flux tower observation, RMSE of CoLM2005 is the smallest for latent heat (9.717 W/m2) , and for sensible heat simulation, RMSE of CoLM2005 (13.048 W/m2) is slightly greater than CLM(10.767 W/m2) but still better than CoLM2014(30.085 W/m2). Our analysis shows that both CoLM 2005 and CoLM 2014 are able to reproduce comparable land surface water and energy fluxes. It implies that the ESM developed in Tsinghua University may use CoLM, a LSM developed and maintained in China, as the land surface component. .

Modelling daily water temperature from air temperature for the Missouri River.

PubMed

Zhu, Senlin; Nyarko, Emmanuel Karlo; Hadzima-Nyarko, Marijana

2018-01-01

The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature. Modelling of river water temperature is usually based on a suitable mathematical model and field measurements of various atmospheric factors. In this article, the air-water temperature relationship of the Missouri River is investigated by developing three different machine learning models (Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and Bootstrap Aggregated Decision Trees (BA-DT)). Standard models (linear regression, non-linear regression, and stochastic models) are also developed and compared to machine learning models. Analyzing the three standard models, the stochastic model clearly outperforms the standard linear model and nonlinear model. All the three machine learning models have comparable results and outperform the stochastic model, with GPR having slightly better results for stations No. 2 and 3, while BA-DT has slightly better results for station No. 1. The machine learning models are very effective tools which can be used for the prediction of daily river temperature.

A Navier-Strokes Chimera Code on the Connection Machine CM-5: Design and Performance

NASA Technical Reports Server (NTRS)

Jespersen, Dennis C.; Levit, Creon; Kwak, Dochan (Technical Monitor)

1994-01-01

We have implemented a three-dimensional compressible Navier-Stokes code on the Connection Machine CM-5. The code is set up for implicit time-stepping on single or multiple structured grids. For multiple grids and geometrically complex problems, we follow the 'chimera' approach, where flow data on one zone is interpolated onto another in the region of overlap. We will describe our design philosophy and give some timing results for the current code. A parallel machine like the CM-5 is well-suited for finite-difference methods on structured grids. The regular pattern of connections of a structured mesh maps well onto the architecture of the machine. So the first design choice, finite differences on a structured mesh, is natural. We use centered differences in space, with added artificial dissipation terms. When numerically solving the Navier-Stokes equations, there are liable to be some mesh cells near a solid body that are small in at least one direction. This mesh cell geometry can impose a very severe CFL (Courant-Friedrichs-Lewy) condition on the time step for explicit time-stepping methods. Thus, though explicit time-stepping is well-suited to the architecture of the machine, we have adopted implicit time-stepping. We have further taken the approximate factorization approach. This creates the need to solve large banded linear systems and creates the first possible barrier to an efficient algorithm. To overcome this first possible barrier we have considered two options. The first is just to solve the banded linear systems with data spread over the whole machine, using whatever fast method is available. This option is adequate for solving scalar tridiagonal systems, but for scalar pentadiagonal or block tridiagonal systems it is somewhat slower than desired. The second option is to 'transpose' the flow and geometry variables as part of the time-stepping process: Start with x-lines of data in-processor. Form explicit terms in x, then transpose so y-lines of data are in-processor. Form explicit terms in y, then transpose so z-lines are in processor. Form explicit terms in z, then solve linear systems in the z-direction. Transpose to the y-direction, then solve linear systems in the y-direction. Finally transpose to the x direction and solve linear systems in the x-direction. This strategy avoids inter-processor communication when differencing and solving linear systems, but requires a large amount of communication when doing the transposes. The transpose method is more efficient than the non-transpose strategy when dealing with scalar pentadiagonal or block tridiagonal systems. For handling geometrically complex problems the chimera strategy was adopted. For multiple zone cases we compute on each zone sequentially (using the whole parallel machine), then send the chimera interpolation data to a distributed data structure (array) laid out over the whole machine. This information transfer implies an irregular communication pattern, and is the second possible barrier to an efficient algorithm. We have implemented these ideas on the CM-5 using CMF (Connection Machine Fortran), a data parallel language which combines elements of Fortran 90 and certain extensions, and which bears a strong similarity to High Performance Fortran. We make use of the Connection Machine Scientific Software Library (CMSSL) for the linear solver and array transpose operations.

Applications of Support Vector Machines In Chemo And Bioinformatics

NASA Astrophysics Data System (ADS)

Jayaraman, V. K.; Sundararajan, V.

2010-10-01

Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.

SPRUCE Representing Northern Peatland Microtopography and Hydrology within the Community Land Model: Modeling Archive

DOE Data Explorer

Shi, X. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Thornton, P. E. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Ricciuto, D. M. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Hanson, P. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Mao, J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Sebestyen, S. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Griffiths, N. A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Bisht, G. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.

2016-09-01

Here we provide model code, inputs, outputs and evaluation datasets for a new configuration of the Community Land Model (CLM) for SPRUCE, which includes a fully prognostic water table calculation for SPRUCE. Our structural and process changes to CLM focus on modifications needed to represent the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of SPRUCE and other peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE).

Linear microbunching analysis for recirculation machines

DOE PAGES

Tsai, C. -Y.; Douglas, D.; Li, R.; ...

2016-11-28

Microbunching instability (MBI) has been one of the most challenging issues in designs of magnetic chicanes for short-wavelength free-electron lasers or linear colliders, as well as those of transport lines for recirculating or energy-recovery-linac machines. To quantify MBI for a recirculating machine and for more systematic analyses, we have recently developed a linear Vlasov solver and incorporated relevant collective effects into the code, including the longitudinal space charge, coherent synchrotron radiation, and linac geometric impedances, with extension of the existing formulation to include beam acceleration. In our code, we semianalytically solve the linearized Vlasov equation for microbunching amplification factor formore » an arbitrary linear lattice. In this study we apply our code to beam line lattices of two comparative isochronous recirculation arcs and one arc lattice preceded by a linac section. The resultant microbunching gain functions and spectral responses are presented, with some results compared to particle tracking simulation by elegant (M. Borland, APS Light Source Note No. LS-287, 2002). These results demonstrate clearly the impact of arc lattice design on the microbunching development. Lastly, the underlying physics with inclusion of those collective effects is elucidated and the limitation of the existing formulation is also discussed.« less

Active vibration and balance system for closed cycle thermodynamic machines

NASA Technical Reports Server (NTRS)

Augenblick, John E. (Inventor); Peterson, Allen A. (Inventor); White, Maurice A. (Inventor); Qiu, Songgang (Inventor)

2004-01-01

An active balance system is provided for counterbalancing vibrations of an axially reciprocating machine. The balance system includes a support member, a flexure assembly, a counterbalance mass, and a linear motor or an actuator. The support member is configured for attachment to the machine. The flexure assembly includes at least one flat spring having connections along a central portion and an outer peripheral portion. One of the central portion and the outer peripheral portion is fixedly mounted to the support member. The counterbalance mass is fixedly carried by the flexure assembly along another of the central portion and the outer peripheral portion. The linear motor has one of a stator and a mover fixedly mounted to the support member and another of the stator and the mover fixedly mounted to the counterbalance mass. The linear motor is operative to axially reciprocate the counterbalance mass. A method is also provided.

Nonautonomous linear system of the terrestrial carbon cycle

NASA Astrophysics Data System (ADS)

Luo, Y.

2012-12-01

Carbon cycle has been studied by uses of observation through various networks, field and laboratory experiments, and simulation models. Much less has been done on theoretical thinking and analysis to understand fundament properties of carbon cycle and then guide observatory, experimental, and modeling research. This presentation is to explore what would be the theoretical properties of terrestrial carbon cycle and how those properties can be used to make observatory, experimental, and modeling research more effective. Thousands of published data sets from litter decomposition and soil incubation studies almost all indicate that decay processes of litter and soil organic carbon can be well described by first order differential equations with one or more pools. Carbon pool dynamics in plants and soil after disturbances (e.g., wildfire, clear-cut of forests, and plows of soil for cropping) and during natural recovery or ecosystem restoration also exhibit characteristics of first-order linear systems. Thus, numerous lines of empirical evidence indicate that the terrestrial carbon cycle can be adequately described as a nonautonomous linear system. The linearity reflects the nature of the carbon cycle that carbon, once fixed by photosynthesis, is linearly transferred among pools within an ecosystem. The linear carbon transfer, however, is modified by nonlinear functions of external forcing variables. In addition, photosynthetic carbon influx is also nonlinearly influenced by external variables. This nonautonomous linear system can be mathematically expressed by a first-order linear ordinary matrix equation. We have recently used this theoretical property of terrestrial carbon cycle to develop a semi-analytic solution of spinup. The new methods have been applied to five global land models, including NCAR's CLM and CABLE models and can computationally accelerate spinup by two orders of magnitude. We also use this theoretical property to develop an analytic framework to decompose modeled carbon cycle into a few traceable components so as to facilitate model intercompsirosn, benchmark analysis, and data assimilation of global land models.

Design and analysis of an unconventional permanent magnet linear machine for energy harvesting

NASA Astrophysics Data System (ADS)

Zeng, Peng

This Ph.D. dissertation proposes an unconventional high power density linear electromagnetic kinetic energy harvester, and a high-performance two-stage interface power electronics to maintain maximum power abstraction from the energy source and charge the Li-ion battery load with constant current. The proposed machine architecture is composed of a double-sided flat type silicon steel stator with winding slots, a permanent magnet mover, coil windings, a linear motion guide and an adjustable spring bearing. The unconventional design of the machine is that NdFeB magnet bars in the mover are placed with magnetic fields in horizontal direction instead of vertical direction and the same magnetic poles are facing each other. The derived magnetic equivalent circuit model proves the average air-gap flux density of the novel topology is as high as 0.73 T with 17.7% improvement over that of the conventional topology at the given geometric dimensions of the proof-of-concept machine. Subsequently, the improved output voltage and power are achieved. The dynamic model of the linear generator is also developed, and the analytical equations of output maximum power are derived for the case of driving vibration with amplitude that is equal, smaller and larger than the relative displacement between the mover and the stator of the machine respectively. Furthermore, the finite element analysis (FEA) model has been simulated to prove the derived analytical results and the improved power generation capability. Also, an optimization framework is explored to extend to the multi-Degree-of-Freedom (n-DOF) vibration based linear energy harvesting devices. Moreover, a boost-buck cascaded switch mode converter with current controller is designed to extract the maximum power from the harvester and charge the Li-ion battery with trickle current. Meanwhile, a maximum power point tracking (MPPT) algorithm is proposed and optimized for low frequency driving vibrations. Finally, a proof-of-concept unconventional permanent magnet (PM) linear generator is prototyped and tested to verify the simulation results of the FEA model. For the coil windings of 33, 66 and 165 turns, the output power of the machine is tested to have the output power of 65.6 mW, 189.1 mW, and 497.7 mW respectively with the maximum power density of 2.486 mW/cm3.

An M-step preconditioned conjugate gradient method for parallel computation

NASA Technical Reports Server (NTRS)

Adams, L.

1983-01-01

This paper describes a preconditioned conjugate gradient method that can be effectively implemented on both vector machines and parallel arrays to solve sparse symmetric and positive definite systems of linear equations. The implementation on the CYBER 203/205 and on the Finite Element Machine is discussed and results obtained using the method on these machines are given.

Machine learning approaches to the social determinants of health in the health and retirement study.

PubMed

Seligman, Benjamin; Tuljapurkar, Shripad; Rehkopf, David

2018-04-01

Social and economic factors are important predictors of health and of recognized importance for health systems. However, machine learning, used elsewhere in the biomedical literature, has not been extensively applied to study relationships between society and health. We investigate how machine learning may add to our understanding of social determinants of health using data from the Health and Retirement Study. A linear regression of age and gender, and a parsimonious theory-based regression additionally incorporating income, wealth, and education, were used to predict systolic blood pressure, body mass index, waist circumference, and telomere length. Prediction, fit, and interpretability were compared across four machine learning methods: linear regression, penalized regressions, random forests, and neural networks. All models had poor out-of-sample prediction. Most machine learning models performed similarly to the simpler models. However, neural networks greatly outperformed the three other methods. Neural networks also had good fit to the data ( R 2 between 0.4-0.6, versus <0.3 for all others). Across machine learning models, nine variables were frequently selected or highly weighted as predictors: dental visits, current smoking, self-rated health, serial-seven subtractions, probability of receiving an inheritance, probability of leaving an inheritance of at least $10,000, number of children ever born, African-American race, and gender. Some of the machine learning methods do not improve prediction or fit beyond simpler models, however, neural networks performed well. The predictors identified across models suggest underlying social factors that are important predictors of biological indicators of chronic disease, and that the non-linear and interactive relationships between variables fundamental to the neural network approach may be important to consider.

Generation of Custom DSP Transform IP Cores: Case Study Walsh-Hadamard Transform

DTIC Science & Technology

2002-09-01

mathematics and hardware design What I know: Finite state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing...state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing Adaptive filter theory … A math guy A hardware engineer...Synthesis Technology Libary Bit-width (8) HF factor (1,2,3,6) VF factor (1,2,4, ... 32) Xilinx FPGA Place&Route Xilinx FPGA Place&Route Performance

Decline in rotavirus hospitalizations following the first three years of vaccination in Castile-La Mancha, Spain

PubMed Central

Redondo, Olga; Cano, Rosa; Simón, Lorena

2015-01-01

Rotavirus is a major burden on the Spanish Healthcare System. Rotarix® and RotaTeq® were simultaneously commercialized in Spain by February, 2007. The objective is to analyze the incidence and seasonality of rotavirus hospitalizations (RH) in Castile-La Mancha (CLM), following the first 3 y of commercialization. A cross-sectional study of the hospital discharge registry's Minimum Basic Data Set (MBDS) in CLM between 2003 and 2009 was performed. We used the Poisson regression model to quantify the percentage of change in the rotavirus incidence rate (IR) for 2007–09 vs. 2003–05, adjusting for age, sex, and province. To analyze changes between epidemic seasons the chi-square test was used. The median IR in 2003–09 was 224.71 per 105 [interquartile range (IQR): 185.24–274.70], which represents 60% of hospital admissions due to infectious acute gastroenteritis. The median rate in 2007–09 decreased [incidence rate ratio (IRR): 0.86, 95% CI: 0.78–0.96], significantly in Toledo (IRR: 0.54, 95% CI: 0.39–0.75). An incipient decline at the beginning of the last cold season was observed, preceded by a significant decrease of 68% in the autumn season of 2009. Despite its limited coverage, the rotavirus vaccine may have contributed to decrease RH in CLM. PMID:25644531

Creation and Evaluation of a Laboratory Administration Curriculum for Pathology Residents.

PubMed

Guarner, Jeannette; Hill, Charles E; Amukele, Timothy

2017-10-01

A clinical laboratory management (CLM) curriculum that can objectively assess the Accreditation Council for Graduate Medical Education pathology systems-based practice milestones and can provide consistent resident training across institutions is needed. Faculty at Emory University created a curriculum that consists of assay verification exercises and interactive, case-based online modules. Beta testing was done at Emory University and Johns Hopkins. Residents were required to obtain a score of more than 80% in the online modules to achieve levels 3 to 4 in the milestones. In addition, residents shadowed a laboratory director, performed an inspection of a laboratory section, and completed training in human subjects research and test utilization. Fourteen residents took and evaluated the laboratory administration curriculum. The printed certificates from the modules were used for objective faculty evaluation of mastery of concepts. Of all the activities the residents performed during the rotation, the online modules were ranked most helpful by all residents. A 25-question knowledge assessment was performed before and after the rotation and showed an average increase of 8 points (P = .0001). The multimodal CLM training described here is an easily adoptable, objective system for teaching CLM. It was well liked by residents and provided an objective measurement of mastery of concepts for faculty. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Chemical Composition and Source Apportionment of Size ...

EPA Pesticide Factsheets

The Cleveland airshed comprises a complex mixture of industrial source emissions that contribute to periods of non-attainment for fine particulate matter (PM 2.5 ) and are associated with increased adverse health outcomes in the exposed population. Specific PM sources responsible for health effects however are not fully understood. Size-fractionated PM (coarse, fine, and ultrafine) samples were collected using a ChemVol sampler at an urban site (G.T. Craig (GTC)) and rural site (Chippewa Lake (CLM)) from July 2009 to June 2010, and then chemically analyzed. The resulting speciated PM data were apportioned by EPA positive matrix factorization to identify emission sources for each size fraction and location. For comparisons with the ChemVol results, PM samples were also collected with sequential dichotomous and passive samplers, and evaluated for source contributions to each sampling site. The ChemVol results showed that annual average concentrations of PM, elemental carbon, and inorganic elements in the coarse fraction at GTC were ~ 2, ~7, and ~3 times higher than those at CLM, respectively, while the smaller size fractions at both sites showed similar annual average concentrat ions. Seasonal variations of secondary aerosols (e.g., high N03- level in winter and high SO42- level in summer) were observed at both sites. Source apportionment results demonstrated that the PM samples at GTC and CLM were enriched with local industrial sources (e.g., steel plant and coa

Modeling the Effects of Drought, Fire, Beetles, and Management on Future Carbon Cycling in the Western US

NASA Astrophysics Data System (ADS)

Buotte, P.; Law, B. E.; Hicke, J. A.; Hudiburg, T. W.; Levis, S.; Kent, J.

2017-12-01

Fire and beetle outbreaks can have substantial impacts on forest structure, composition, and function and these types of disturbances are expected to increase in the future. Therefore understanding the ecological impacts of these disturbances into the future is important. We used ecosystem process modeling to estimate the future occurrence of fire and beetle outbreaks and their impacts on forest resilience and carbon sequestration. We modified the Community Land Model (CLM4.5) to better represent forest growth and mortality in the western US through multiple avenues: 1) we increased the ecological resolution to recognize 14 forest types common to the region; 2) we improved CLM4.5's ability to handle drought stress by adding forest type-specific controls on stomatal conductance and increased rates of leaf shed during periods of low soil moisture; 3) we developed and implemented a mechanistic model of beetle population growth and subsequent tree mortality; 4) we modified the current fire module to account for more refined forest types; and 5) we developed multiple scenarios of harvest based on past harvest rates and proposed changes in land management policies. We ran CLM4.5 in offline mode with climate forcing data. We compare future forest growth rates and carbon sequestration with historical metrics to estimate the combined influence of future disturbances on forest composition and carbon sequestration in the western US.

Non-linear effects in bunch compressor of TARLA

NASA Astrophysics Data System (ADS)

Yildiz, Hüseyin; Aksoy, Avni; Arikan, Pervin

2016-03-01

Transport of a beam through an accelerator beamline is affected by high order and non-linear effects such as space charge, coherent synchrotron radiation, wakefield, etc. These effects damage form of the beam, and they lead particle loss, emittance growth, bunch length variation, beam halo formation, etc. One of the known non-linear effects on low energy machine is space charge effect. In this study we focus on space charge effect for Turkish Accelerator and Radiation Laboratory in Ankara (TARLA) machine which is designed to drive InfraRed Free Electron Laser covering the range of 3-250 µm. Moreover, we discuss second order effects on bunch compressor of TARLA.

Single-machine common/slack due window assignment problems with linear decreasing processing times

NASA Astrophysics Data System (ADS)

Zhang, Xingong; Lin, Win-Chin; Wu, Wen-Hsiang; Wu, Chin-Chia

2017-08-01

This paper studies linear non-increasing processing times and the common/slack due window assignment problems on a single machine, where the actual processing time of a job is a linear non-increasing function of its starting time. The aim is to minimize the sum of the earliness cost, tardiness cost, due window location and due window size. Some optimality results are discussed for the common/slack due window assignment problems and two O(n log n) time algorithms are presented to solve the two problems. Finally, two examples are provided to illustrate the correctness of the corresponding algorithms.

Electric converters of electromagnetic strike machine with capacitor supply

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Kargin, V. A.; Moiseev, A. P.; Chetverikov, E. A.

2018-03-01

The application of pulse linear electromagnetic engines in small power strike machines (energy impact is 0.01...1.0 kJ), where the characteristic mode of rare beats (pulse seismic vibrator, the arch crash device bins bulk materials), is quite effective. At the same time, the technical and economic performance of such machines is largely determined by the ability of the power source to provide a large instantaneous power of the supply pulses in the winding of the linear electromagnetic motor. The use of intermediate energy storage devices in power systems of rare-shock LEME makes it possible to obtain easily large instantaneous powers, forced energy conversion, and increase the performance of the machine. A capacitor power supply of a pulsed source of seismic waves is proposed for the exploration of shallow depths. The sections of the capacitor storage (CS) are connected to the winding of the linear electromagnetic motor by thyristor dischargers, the sequence of activation of which is determined by the control device. The charge of the capacitors to the required voltage is made directly from the battery source, or through the converter from a battery source with a smaller number of batteries.

Matrix approaches to assess terrestrial nitrogen scheme in CLM4.5

NASA Astrophysics Data System (ADS)

Du, Z.

2017-12-01

Terrestrial carbon (C) and nitrogen (N) cycles have been commonly represented by a series of balance equations to track their influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C and N cycle processes well but makes it difficult to track model behaviors. To overcome these challenges, we developed a matrix approach, which reorganizes the series of terrestrial C and N balance equations in the CLM4.5 into two matrix equations based on original representation of C and N cycle processes and mechanisms. The matrix approach would consequently help improve the comparability of models and data, evaluate impacts of additional model components, facilitate benchmark analyses, model intercomparisons, and data-model fusion, and improve model predictive power.

Dimension Reduction With Extreme Learning Machine.

PubMed

Kasun, Liyanaarachchi Lekamalage Chamara; Yang, Yan; Huang, Guang-Bin; Zhang, Zhengyou

2016-08-01

Data may often contain noise or irrelevant information, which negatively affect the generalization capability of machine learning algorithms. The objective of dimension reduction algorithms, such as principal component analysis (PCA), non-negative matrix factorization (NMF), random projection (RP), and auto-encoder (AE), is to reduce the noise or irrelevant information of the data. The features of PCA (eigenvectors) and linear AE are not able to represent data as parts (e.g. nose in a face image). On the other hand, NMF and non-linear AE are maimed by slow learning speed and RP only represents a subspace of original data. This paper introduces a dimension reduction framework which to some extend represents data as parts, has fast learning speed, and learns the between-class scatter subspace. To this end, this paper investigates a linear and non-linear dimension reduction framework referred to as extreme learning machine AE (ELM-AE) and sparse ELM-AE (SELM-AE). In contrast to tied weight AE, the hidden neurons in ELM-AE and SELM-AE need not be tuned, and their parameters (e.g, input weights in additive neurons) are initialized using orthogonal and sparse random weights, respectively. Experimental results on USPS handwritten digit recognition data set, CIFAR-10 object recognition, and NORB object recognition data set show the efficacy of linear and non-linear ELM-AE and SELM-AE in terms of discriminative capability, sparsity, training time, and normalized mean square error.

Vowel Imagery Decoding toward Silent Speech BCI Using Extreme Learning Machine with Electroencephalogram

PubMed Central

Kim, Jongin; Park, Hyeong-jun

2016-01-01

The purpose of this study is to classify EEG data on imagined speech in a single trial. We recorded EEG data while five subjects imagined different vowels, /a/, /e/, /i/, /o/, and /u/. We divided each single trial dataset into thirty segments and extracted features (mean, variance, standard deviation, and skewness) from all segments. To reduce the dimension of the feature vector, we applied a feature selection algorithm based on the sparse regression model. These features were classified using a support vector machine with a radial basis function kernel, an extreme learning machine, and two variants of an extreme learning machine with different kernels. Because each single trial consisted of thirty segments, our algorithm decided the label of the single trial by selecting the most frequent output among the outputs of the thirty segments. As a result, we observed that the extreme learning machine and its variants achieved better classification rates than the support vector machine with a radial basis function kernel and linear discrimination analysis. Thus, our results suggested that EEG responses to imagined speech could be successfully classified in a single trial using an extreme learning machine with a radial basis function and linear kernel. This study with classification of imagined speech might contribute to the development of silent speech BCI systems. PMID:28097128

High Energy Colliders

NASA Astrophysics Data System (ADS)

Palmer, R. B.; Gallardo, J. C.

INTRODUCTION PHYSICS CONSIDERATIONS GENERAL REQUIRED LUMINOSITY FOR LEPTON COLLIDERS THE EFFECTIVE PHYSICS ENERGIES OF HADRON COLLIDERS HADRON-HADRON MACHINES LUMINOSITY SIZE AND COST CIRCULAR e^{+}e^- MACHINES LUMINOSITY SIZE AND COST e^{+}e^- LINEAR COLLIDERS LUMINOSITY CONVENTIONAL RF SUPERCONDUCTING RF AT HIGHER ENERGIES γ - γ COLLIDERS μ ^{+} μ^- COLLIDERS ADVANTAGES AND DISADVANTAGES DESIGN STUDIES STATUS AND REQUIRED R AND D COMPARISION OF MACHINES CONCLUSIONS DISCUSSION

[Cutaneous larva migrans: report of three cases from the Western Black Sea Region, Turkey].

PubMed

Çalışkan, Emel; Uslu, Esma; Turan, Hakan; Başkan, Elife; Kılıç, Nida

2016-01-01

Cutaneous larva migrans (CLM) is a parasitosis frequently seen in persons who have travelled to tropical or subtropical regions and in those who have worked in contact with soil. The disease frequently develops due to Ancylostoma braziliensis and Ancylostoma caninum species. After penetrating the skin and entering the body, the hookworm larva proceeds to bore tunnels through the epidermis, creating pruritic, erythematous, serpiginous lesions. Secondary bacterial infections of the lesions can often be seen, especially on the legs and buttocks. In this article we presented three atypical local cases which have not been declared previously in our country. The first case, a 54-year-old male who was admitted to hospital in August with complaints of an obverse body rash and itching lasting for a week. Eruptions were observed over a small area on the right side of the abdomen, consisting of itchy, raised, erythematous, curvilinear string-like lesions. Moreover, no eosinophilia was detected in the patient, whose culture showed a growth of Streptococcus pyogenes. The patient was clinically diagnosed with CLM accompanied by secondary bacterial infection and treated for three days with 1 g of amoxicillin-clavulanic acid, mupirocin cream and albendazole 400 mg/d. Under this regime, the lesions were seen to decline. The second case, a 38-year-old male was also admitted in August, complaining of itching and redness on his body. The patient, whose blood count values were normal, exhibited itchy, raised, serpiginous string-like lesions located on the left side of his body. The patient, whose bacterial culture was negative, was clinically diagnosed as CLM and treated for three days with albendazole 400 mg/d and the lesions were seen to improve. The third case, a 23-year old male was admitted in September complaining of itching and redness on his neck. An itchy, crescent-shaped erythematous lesion was detected on his neck; bacteriological cultures and blood count were normal. The common feature for all three cases was the story of working in a hazelnut orchard and mowing weeds using a motorized string trimmer (weed whacker). None of them had a history of travel outside the country. Therefore CLM assumed to be occurred due to the aeration of surface earth layer with the force of motorized string trimmer and entrance of the larvae were from the open parts of the body. In conclusion, it should be keep in mind that hookworm larva-related CLM can be encountered in our country, and reporting of the patients with similar findings are necessary to determine the prevalence of this parasitosis in our country.

Simulations with COSMO-CLM over Turin including TERRA-URB parameterization

NASA Astrophysics Data System (ADS)

Bucchignani, Edoardo; Mercogliano, Paola; Milelli, Massimo; Raffa, Mario

2017-04-01

The increase of built surfaces constitutes the main reason for the formation of Urban Heat Islands (UHIs), since urban canyons block the release of the reflected radiation. The main contribution to the formation of UHIs is the missing night-cooling of horizontal surfaces, together with cloudless sky and light winds. Of course, there is also a contribution from indoor heating, vehicles presence, and waste heat from air conditioning and refrigeration systems. The COSMO-CLM model, even at high resolution, is currently not able to cope with this effect. Nevertheless, the increase of applications in which a high number of grid points is located over urban areas, requires that COSMO-CLM becomes able to take into account also urban climate features. In fact, they are crucial for better forecast of temperature and for a better characterization of the local patterns of several atmospherical variables (wind, surface fluxes). Recently TERRA-URB, a bulk parameterisation scheme with a prescribed anthropogenic heat flux, has been incorporated into COSMO-CLM for the standard land-surface module TERRA-ML. It offers an intrinsic representation of the urban physics with modifications of input data, soil module and land atmospheric interactions. In the first half of July 2015, Piemonte region and Turin in particular experienced extreme temperature values and uncomfortable conditions for the population. In Turin, the maximum temperature since 1990 (38.5°) has been recorded in July 2015. Ground stations data highlighted the presence of a UHI effect over Turin. This is the reason why this area and this period represent a suitable benchmark to test the capabilities of COSMO-CLM, and in particular of the urban parameterization. The computational domain considered is centered over Turin, discretized with 100 x 100 grid-points, employing a spatial resolution of 0.009° (about 1 km). The ECMWF IFS analysis at 0.075° have been used as forcing data. Two simulations have been performed over the period 1 to 7 July 2015, respectively activating and deactivating TERRA-URB, in order to highlight its effects on the model results. Moreover, a third simulation has been performed with TERRA-URB activated, but employing an optimized model configuration. Validation has been carried out against an observational dataset for daily values of temperature, provided by ARPA Piemonte. More specifically, Consolata and Bauducchi stations have been considered, respectively representative of urban and rural areas. Results have highlighted that in Consolata the minimum temperature is simulated better when TERRA-URB is activated, while in Bauducchi no significant differences have been recorded among the simulations. The daily maximum temperature is always overestimated in both stations. Finally, the usage of an optimized configuration allowed a slight improvement of the results.

The circular form of the linear superconducting machine for marine propulsion

NASA Astrophysics Data System (ADS)

Rakels, J. H.; Mahtani, J. L.; Rhodes, R. G.

1981-01-01

The superconducting linear synchronous machine (LSM) is an efficient method of propulsion of advanced ground transport systems and can also be used in marine engineering for the propulsion of large commercial vessels, tankers, and military ships. It provides high torque at low shaft speeds and ease of reversibility; a circular LSM design is proposed as a drive motor. The equipment is compared with the superconducting homopolar motors, showing flexibility in design, built in redundancy features, and reliability.

A Very Fast and Angular Momentum Conserving Tree Code

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

Marcello, Dominic C., E-mail: dmarce504@gmail.com

There are many methods used to compute the classical gravitational field in astrophysical simulation codes. With the exception of the typically impractical method of direct computation, none ensure conservation of angular momentum to machine precision. Under uniform time-stepping, the Cartesian fast multipole method of Dehnen (also known as the very fast tree code) conserves linear momentum to machine precision. We show that it is possible to modify this method in a way that conserves both angular and linear momenta.

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

Imidacloprid soil movement under micro-sprinkler irrigation and soil-drench applications to control Asian citrus psyllid (ACP) and citrus leafminer (CLM).

PubMed

Fletcher, Evelyn; Morgan, Kelly T; Qureshi, Jawwad A; Leiva, Jorge A; Nkedi-Kizza, Peter

2018-01-01

Imidacloprid (IM) is used to control the Asian Citrus Psyllid (ACP) and citrus leafminer (CLM), which are related to the spread of huanglongbing (HLB or citrus greening) and citrus canker diseases, respectively. In Florida citrus, imidacloprid is mainly soil-drenched around the trees for proper root uptake and translocation into plant canopy to impact ACP and CLM. The objective of this study was to determine the effect of imidacloprid rate, and irrigate amount on concentration of imidacloprid in the soil following drench application to citrus trees in three age classes. The plots were established at the Southwest Florida Research and Education Center, Immokalee, using a randomized complete-block design for three age classes of trees: one-year-old trees (B1), three to five-year-old trees (B2), and eight-year-old trees (B3). The treatments were a combination of two rates each of imidacloprid (1D, 2D) and micro-sprinkling irrigation (1I, 2I). Imidacloprid and bromide (Br-) used as tracer were applied simultaneously. Soil moisture and concentrations of imidacloprid and Br were monitored using soil cores from hand held augers. Soil moisture content (θV) did not differ under two irrigation rates at any given observation day or depth, except following heavy rainfall events. Br- was lost from the observation depths (0-45 cm) about two weeks after soil-drench. Contrarily, imidacloprid persisted for a much longer time (4-8 weeks) at all soil depths, regardless of treatment combinations. The higher retardation of imidacloprid was related to the predominantly unsaturated conditions of the soil (which in turn reduced soil hydraulic conductivities by orders of magnitude), the imidacloprid sorption on soil organic matter, and the citrus root uptake. Findings of this study are important for citrus growers coping with the citrus greening and citrus canker diseases because they suggest that imidacloprid soil drenches can still be an effective control measure of ACP and CLM, and the potential for imidacloprid leaching to groundwater is minimal.

Sensitivity of volatile organic compounds (VOCs) and ozone to land surface processes and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, C.; Huang, M.; Fast, J. D.; Berg, L. K.; Qian, Y.; Guenther, A. B.; Gu, D.; Shrivastava, M. B.; Liu, Y.; Walters, S.; Jin, J.

2014-12-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect secondary organic aerosol (SOA) formation and ultimately aerosol radiative forcing. These uncertainties result from many factors, including coupling strategy between biogenic emissions and land-surface schemes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (VOCs). In this study, sensitivity experiments are conducted using the Weather Research and Forecasting model with chemistry (WRF-Chem) to examine the sensitivity of simulated VOCs and ozone to land surface processes and vegetation distributions in California. The measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010 provide a good opportunity to evaluate the simulations. First, the biogenic VOC emissions in the WRF-Chem simulations with the two land surface schemes, Noah and CLM4, are estimated by the Model of Emissions of Gases and Aerosols from Nature version one (MEGANv1), which has been publicly released and widely used with WRF-Chem. The impacts of land surface processes on estimating biogenic VOC emissions and simulating VOCs and ozone are investigated. Second, in this study, a newer version of MEGAN (MEGANv2.1) is coupled with CLM4 as part of WRF-Chem to examine the sensitivity of biogenic VOC emissions to the MEGAN schemes used and determine the importance of using a consistent vegetation map between a land surface scheme and the biogenic VOC emission scheme. Specifically, MEGANv2.1 is embedded into the CLM4 scheme and shares a consistent vegetation map for estimating biogenic VOC emissions. This is unlike MEGANv1 in WRF-Chem that uses a standalone vegetation map that differs from what is used in land surface schemes. Furthermore, we examine the impact of vegetation distribution on simulating VOCs and ozone by comparing coupled WRF-Chem-CLM-MEGANv2.1 simulations using multiple vegetation maps.

Initializing carbon cycle predictions from the Community Land Model by assimilating global biomass observations

NASA Astrophysics Data System (ADS)

Fox, A. M.; Hoar, T. J.; Smith, W. K.; Moore, D. J.

2017-12-01

The locations and longevity of terrestrial carbon sinks remain uncertain, however it is clear that in order to predict long-term climate changes the role of the biosphere in surface energy and carbon balance must be understood and incorporated into earth system models (ESMs). Aboveground biomass, the amount of carbon stored in vegetation, is a key component of the terrestrial carbon cycle, representing the balance of uptake through gross primary productivity (GPP), losses from respiration, senescence and mortality over hundreds of years. The best predictions of current and future land-atmosphere fluxes are likely from the integration of process-based knowledge contained in models and information from observations of changes in carbon stocks using data assimilation (DA). By exploiting long times series, it is possible to accurately detect variability and change in carbon cycle dynamics through monitoring ecosystem states, for example biomass derived from vegetation optical depth (VOD), and use this information to initialize models before making predictions. To make maximum use of information about the current state of global ecosystems when using models we have developed a system that combines the Community Land Model (CLM) with the Data Assimilation Research Testbed (DART), a community tool for ensemble DA. This DA system is highly innovative in its complexity, completeness and capabilities. Here we described a series of activities, using both Observation System Simulation Experiments (OSSEs) and real observations, that have allowed us to quantify the potential impact of assimilating VOD data into CLM-DART on future land-atmosphere fluxes. VOD data are particularly suitable to use in this activity due to their long temporal coverage and appropriate scale when combined with CLM, but their absolute values rely on many assumptions. Therefore, we have had to assess the implications of the VOD retrieval algorithms, with an emphasis on detecting uncertainty due to assumptions and inputs in the algorithms that are incompatible with those encoded within CLM. It is probable that VOD describes changes in biomass more accurately than absolute values, so in additional to sequential assimilation of observations, we have tested alternative filter algorithms, and assimilating VOD anomalies.

20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models

DOE PAGES

Keller, Kathrin M.; Lienert, Sebastian; Bozbiyik, Anil; ...

2017-05-24

Measurements of the stable carbon isotope ratio ( δ 13C) on annual tree rings offer new opportunities to evaluate mechanisms of variations in photosynthesis and stomatal conductance under changing CO 2 and climate conditions, especially in conjunction with process-based biogeochemical model simulations. The isotopic discrimination is indicative of the ratio between the CO 2 partial pressure in the intercellular cavities and the atmosphere ( c i/ c a) and of the ratio of assimilation to stomatal conductance, termed intrinsic water-use efficiency (iWUE). We performed isotope-enabled simulations over the industrial period with the land biosphere module (CLM4.5) of the Community Earthmore » System Model and the Land Surface Processes and Exchanges (LPX-Bern) dynamic global vegetation model. Results for C3 tree species show good agreement with a global compilation of δ 13C measurements on leaves, though modeled 13C discrimination by C3 trees is smaller in arid regions than measured. A compilation of 76 tree-ring records, mainly from Europe, boreal Asia, and western North America, suggests on average small 20th century changes in isotopic discrimination and in c i/ c a and an increase in iWUE of about 27% since 1900. LPX-Bern results match these century-scale reconstructions, supporting the idea that the physiology of stomata has evolved to optimize trade-offs between carbon gain by assimilation and water loss by transpiration. In contrast, CLM4.5 simulates an increase in discrimination and in turn a change in iWUE that is almost twice as large as that revealed by the tree-ring data. Factorial simulations show that these changes are mainly in response to rising atmospheric CO 2. The results suggest that the downregulation of c i/ c a and of photosynthesis by nitrogen limitation is possibly too strong in the standard setup of CLM4.5 or that there may be problems associated with the implementation of conductance, assimilation, and related adjustment processes on long-term environmental changes.« less

20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models

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

Keller, Kathrin M.; Lienert, Sebastian; Bozbiyik, Anil

Measurements of the stable carbon isotope ratio ( δ 13C) on annual tree rings offer new opportunities to evaluate mechanisms of variations in photosynthesis and stomatal conductance under changing CO 2 and climate conditions, especially in conjunction with process-based biogeochemical model simulations. The isotopic discrimination is indicative of the ratio between the CO 2 partial pressure in the intercellular cavities and the atmosphere ( c i/ c a) and of the ratio of assimilation to stomatal conductance, termed intrinsic water-use efficiency (iWUE). We performed isotope-enabled simulations over the industrial period with the land biosphere module (CLM4.5) of the Community Earthmore » System Model and the Land Surface Processes and Exchanges (LPX-Bern) dynamic global vegetation model. Results for C3 tree species show good agreement with a global compilation of δ 13C measurements on leaves, though modeled 13C discrimination by C3 trees is smaller in arid regions than measured. A compilation of 76 tree-ring records, mainly from Europe, boreal Asia, and western North America, suggests on average small 20th century changes in isotopic discrimination and in c i/ c a and an increase in iWUE of about 27% since 1900. LPX-Bern results match these century-scale reconstructions, supporting the idea that the physiology of stomata has evolved to optimize trade-offs between carbon gain by assimilation and water loss by transpiration. In contrast, CLM4.5 simulates an increase in discrimination and in turn a change in iWUE that is almost twice as large as that revealed by the tree-ring data. Factorial simulations show that these changes are mainly in response to rising atmospheric CO 2. The results suggest that the downregulation of c i/ c a and of photosynthesis by nitrogen limitation is possibly too strong in the standard setup of CLM4.5 or that there may be problems associated with the implementation of conductance, assimilation, and related adjustment processes on long-term environmental changes.« less

Ethanol production potential from AFEX™ and steam-exploded sugarcane residues for sugarcane biorefineries.

PubMed

Mokomele, Thapelo; da Costa Sousa, Leonardo; Balan, Venkatesh; van Rensburg, Eugéne; Dale, Bruce E; Görgens, Johann F

2018-01-01

Expanding biofuel markets are challenged by the need to meet future biofuel demands and mitigate greenhouse gas emissions, while using domestically available feedstock sustainably. In the context of the sugar industry, exploiting under-utilized cane leaf matter (CLM) in addition to surplus sugarcane bagasse as supplementary feedstock for second-generation ethanol production has the potential to improve bioenergy yields per unit land. In this study, the ethanol yields and processing bottlenecks of ammonia fibre expansion (AFEX™) and steam explosion (StEx) as adopted technologies for pretreating sugarcane bagasse and CLM were experimentally measured and compared for the first time. Ethanol yields between 249 and 256 kg Mg -1 raw dry biomass (RDM) were obtained with AFEX™-pretreated sugarcane bagasse and CLM after high solids loading enzymatic hydrolysis and fermentation. In contrast, StEx-pretreated sugarcane bagasse and CLM resulted in substantially lower ethanol yields that ranged between 162 and 203 kg Mg -1 RDM. The ethanol yields from StEx-treated sugarcane residues were limited by the aggregated effect of sugar degradation during pretreatment, enzyme inhibition during enzymatic hydrolysis and microbial inhibition of S. cerevisiae 424A (LNH-ST) during fermentation. However, relatively high enzyme dosages (> 20 mg g -1 glucan) were required irrespective of pretreatment method to reach 75% carbohydrate conversion, even when optimal combinations of Cellic ® CTec3, Cellic ® HTec3 and Pectinex Ultra-SP were used. Ethanol yields per hectare sugarcane cultivation area were estimated at 4496 and 3416 L ha -1 for biorefineries using AFEX™- or StEx-treated sugarcane residues, respectively. AFEX™ proved to be a more effective pretreatment method for sugarcane residues relative to StEx due to the higher fermentable sugar recovery and enzymatic hydrolysate fermentability after high solids loading enzymatic hydrolysis and fermentation by S. cerevisiae 424A (LNH-ST). The identification of auxiliary enzyme activities, adequate process integration and the use of robust xylose-fermenting ethanologens were identified as opportunities to further improve ethanol yields from AFEX™- and StEx-treated sugarcane residues.

Imidacloprid soil movement under micro-sprinkler irrigation and soil-drench applications to control Asian citrus psyllid (ACP) and citrus leafminer (CLM)

PubMed Central

Fletcher, Evelyn; Qureshi, Jawwad A.; Leiva, Jorge A.; Nkedi-Kizza, Peter

2018-01-01

Imidacloprid (IM) is used to control the Asian Citrus Psyllid (ACP) and citrus leafminer (CLM), which are related to the spread of huanglongbing (HLB or citrus greening) and citrus canker diseases, respectively. In Florida citrus, imidacloprid is mainly soil-drenched around the trees for proper root uptake and translocation into plant canopy to impact ACP and CLM. The objective of this study was to determine the effect of imidacloprid rate, and irrigate amount on concentration of imidacloprid in the soil following drench application to citrus trees in three age classes. The plots were established at the Southwest Florida Research and Education Center, Immokalee, using a randomized complete-block design for three age classes of trees: one-year-old trees (B1), three to five-year-old trees (B2), and eight-year-old trees (B3). The treatments were a combination of two rates each of imidacloprid (1D, 2D) and micro-sprinkling irrigation (1I, 2I). Imidacloprid and bromide (Br-) used as tracer were applied simultaneously. Soil moisture and concentrations of imidacloprid and Br were monitored using soil cores from hand held augers. Soil moisture content (θV) did not differ under two irrigation rates at any given observation day or depth, except following heavy rainfall events. Br- was lost from the observation depths (0–45 cm) about two weeks after soil-drench. Contrarily, imidacloprid persisted for a much longer time (4–8 weeks) at all soil depths, regardless of treatment combinations. The higher retardation of imidacloprid was related to the predominantly unsaturated conditions of the soil (which in turn reduced soil hydraulic conductivities by orders of magnitude), the imidacloprid sorption on soil organic matter, and the citrus root uptake. Findings of this study are important for citrus growers coping with the citrus greening and citrus canker diseases because they suggest that imidacloprid soil drenches can still be an effective control measure of ACP and CLM, and the potential for imidacloprid leaching to groundwater is minimal. PMID:29518086

Contrastive Analysis of Meteorological Element Effect Simulated by parameterization schemes Land Surface Process of Noah and CLM4 over the Yellow River Source Region

NASA Astrophysics Data System (ADS)

Zhang, Y.; Wen, X.

2017-12-01

The Yellow River source region is situated in the northeast Tibetan Plateau, which is considered as a global climate change hot-spot and one of the most sensitive areas in terms of response to global warming in view of its fragile ecosystem. This region plays an irreplaceable role for downstream water supply of The Yellow River because of its unique topography and variable climate. The water energy cycle processes of the Yellow River source Region from July to September in 2015 were simulated by using the WRF mesoscale numerical model. The two groups respectively used Noah and CLM4 parameterization schemes of land surface process. Based on the observation data of GLDAS data set, ground automatic weather station and Zoige plateau wetland ecosystem research station, the simulated values of near surface meteorological elements and surface energy parameters of two different schemes were compared. The results showed that the daily variations about meteorological factors in Zoige station in September were simulated quite well by the model. The correlation coefficient between the simulated temperature and humidity of the CLM scheme were 0.88 and 0.83, the RMSE were 1.94 ° and 9.97%, and the deviation Bias were 0.04 ° and 3.30%, which was closer to the observation data than the Noah scheme. The correlation coefficients of net radiation, surface heat flux, upward short wave and upward longwave radiation were respectively 0.86, 0.81, 0.84 and 0.88, which corresponded better than the observation data. The sensible heat flux and latent heat flux distribution of the Noah scheme corresponded quite well to GLDAS. the distribution and magnitude of 2m relative humidity and soil moisture were closer to surface observation data because the CLM scheme described the photosynthesis and evapotranspiration of land surface vegetation more rationally. The simulating abilities of precipitation and downward longwave radiation need to be improved. This study provides a theoretical basis for the numerical simulation of water energy cycle in the source region over the Yellow River basin.

20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models

NASA Astrophysics Data System (ADS)

Keller, Kathrin M.; Lienert, Sebastian; Bozbiyik, Anil; Stocker, Thomas F.; Churakova (Sidorova), Olga V.; Frank, David C.; Klesse, Stefan; Koven, Charles D.; Leuenberger, Markus; Riley, William J.; Saurer, Matthias; Siegwolf, Rolf; Weigt, Rosemarie B.; Joos, Fortunat

2017-05-01

Measurements of the stable carbon isotope ratio (δ13C) on annual tree rings offer new opportunities to evaluate mechanisms of variations in photosynthesis and stomatal conductance under changing CO2 and climate conditions, especially in conjunction with process-based biogeochemical model simulations. The isotopic discrimination is indicative of the ratio between the CO2 partial pressure in the intercellular cavities and the atmosphere (ci/ca) and of the ratio of assimilation to stomatal conductance, termed intrinsic water-use efficiency (iWUE). We performed isotope-enabled simulations over the industrial period with the land biosphere module (CLM4.5) of the Community Earth System Model and the Land Surface Processes and Exchanges (LPX-Bern) dynamic global vegetation model. Results for C3 tree species show good agreement with a global compilation of δ13C measurements on leaves, though modeled 13C discrimination by C3 trees is smaller in arid regions than measured. A compilation of 76 tree-ring records, mainly from Europe, boreal Asia, and western North America, suggests on average small 20th century changes in isotopic discrimination and in ci/ca and an increase in iWUE of about 27 % since 1900. LPX-Bern results match these century-scale reconstructions, supporting the idea that the physiology of stomata has evolved to optimize trade-offs between carbon gain by assimilation and water loss by transpiration. In contrast, CLM4.5 simulates an increase in discrimination and in turn a change in iWUE that is almost twice as large as that revealed by the tree-ring data. Factorial simulations show that these changes are mainly in response to rising atmospheric CO2. The results suggest that the downregulation of ci/ca and of photosynthesis by nitrogen limitation is possibly too strong in the standard setup of CLM4.5 or that there may be problems associated with the implementation of conductance, assimilation, and related adjustment processes on long-term environmental changes.

Quick-Turn Finite Element Analysis for Plug-and-Play Satellite Structures

DTIC Science & Technology

2007-03-01

produced from 0.375 inch round stock and turned on a machine lathe to achieve the shoulder feature and drilled to make it hollow. Figure 3.1...component, a linear taper was machined from the connection shoulder to the solar panel connecting fork. The part was then turned using the machine lathe ...utilizing a modern five-axis Computer Numerical Code ( CNC ) machine mill, the process time could be reduced by as much as seventy-five percent and the

Magnetic Flux Distribution of Linear Machines with Novel Three-Dimensional Hybrid Magnet Arrays

PubMed Central

Yao, Nan; Yan, Liang; Wang, Tianyi; Wang, Shaoping

2017-01-01

The objective of this paper is to propose a novel tubular linear machine with hybrid permanent magnet arrays and multiple movers, which could be employed for either actuation or sensing technology. The hybrid magnet array produces flux distribution on both sides of windings, and thus helps to increase the signal strength in the windings. The multiple movers are important for airspace technology, because they can improve the system’s redundancy and reliability. The proposed design concept is presented, and the governing equations are obtained based on source free property and Maxwell equations. The magnetic field distribution in the linear machine is thus analytically formulated by using Bessel functions and harmonic expansion of magnetization vector. Numerical simulation is then conducted to validate the analytical solutions of the magnetic flux field. It is proved that the analytical model agrees with the numerical results well. Therefore, it can be utilized for the formulation of signal or force output subsequently, depending on its particular implementation. PMID:29156577

A comparison of optimal MIMO linear and nonlinear models for brain machine interfaces

NASA Astrophysics Data System (ADS)

Kim, S.-P.; Sanchez, J. C.; Rao, Y. N.; Erdogmus, D.; Carmena, J. M.; Lebedev, M. A.; Nicolelis, M. A. L.; Principe, J. C.

2006-06-01

The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.

Magnetic Flux Distribution of Linear Machines with Novel Three-Dimensional Hybrid Magnet Arrays.

PubMed

Yao, Nan; Yan, Liang; Wang, Tianyi; Wang, Shaoping

2017-11-18

The objective of this paper is to propose a novel tubular linear machine with hybrid permanent magnet arrays and multiple movers, which could be employed for either actuation or sensing technology. The hybrid magnet array produces flux distribution on both sides of windings, and thus helps to increase the signal strength in the windings. The multiple movers are important for airspace technology, because they can improve the system's redundancy and reliability. The proposed design concept is presented, and the governing equations are obtained based on source free property and Maxwell equations. The magnetic field distribution in the linear machine is thus analytically formulated by using Bessel functions and harmonic expansion of magnetization vector. Numerical simulation is then conducted to validate the analytical solutions of the magnetic flux field. It is proved that the analytical model agrees with the numerical results well. Therefore, it can be utilized for the formulation of signal or force output subsequently, depending on its particular implementation.

A comparison of optimal MIMO linear and nonlinear models for brain-machine interfaces.

PubMed

Kim, S-P; Sanchez, J C; Rao, Y N; Erdogmus, D; Carmena, J M; Lebedev, M A; Nicolelis, M A L; Principe, J C

2006-06-01

The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.

Gender classification of running subjects using full-body kinematics

NASA Astrophysics Data System (ADS)

Williams, Christina M.; Flora, Jeffrey B.; Iftekharuddin, Khan M.

2016-05-01

This paper proposes novel automated gender classification of subjects while engaged in running activity. The machine learning techniques include preprocessing steps using principal component analysis followed by classification with linear discriminant analysis, and nonlinear support vector machines, and decision-stump with AdaBoost. The dataset consists of 49 subjects (25 males, 24 females, 2 trials each) all equipped with approximately 80 retroreflective markers. The trials are reflective of the subject's entire body moving unrestrained through a capture volume at a self-selected running speed, thus producing highly realistic data. The classification accuracy using leave-one-out cross validation for the 49 subjects is improved from 66.33% using linear discriminant analysis to 86.74% using the nonlinear support vector machine. Results are further improved to 87.76% by means of implementing a nonlinear decision stump with AdaBoost classifier. The experimental findings suggest that the linear classification approaches are inadequate in classifying gender for a large dataset with subjects running in a moderately uninhibited environment.

Feedback control of plasma instabilities with charged particle beams and study of plasma turbulence

NASA Technical Reports Server (NTRS)

Tham, Philip Kin-Wah

1994-01-01

A new non-perturbing technique for feedback control of plasma instabilities has been developed in the Columbia Linear Machine (CLM). The feedback control scheme involves the injection of a feedback modulated ion beam as a remote suppressor. The ion beam was obtained from a compact ion beam source which was developed for this purpose. A Langmuir probe was used as the feedback sensor. The feedback controller consisted of a phase-shifter and amplifiers. This technique was demonstrated by stabilizing various plasma instabilities to the background noise level, like the trapped particle instability, the ExB instability and the ion-temperature-gradient (ITG) driven instability. An important feature of this scheme is that the injected ion beam is non-perturbing to the plasma equilibrium parameters. The robustness of this feedback stabilization scheme was also investigated. The principal result is that the scheme is fairly robust, tolerating about 100% variation about the nominal parameter values. Next, this scheme is extended to the unsolved general problem of controlling multimode plasma instabilities simultaneously with a single sensor-suppressor pair. A single sensor-suppressor pair of feedback probes is desirable to reduce the perturbation caused by the probes. Two plasma instabilities the ExB and the ITG modes, were simultaneously stabilized. A simple 'state' feedback type method was used where more state information was generated from the single sensor Langmuir probe by appropriate signal processing, in this case, by differentiation. This proof-of-principle experiment demonstrated for the first time that by designing a more sophisticated electronic feedback controller, many plasma instabilities may be simultaneously controlled. Simple theoretical models showed generally good agreement with the feedback experimental results. On a parallel research front, a better understanding of the saturated state of a plasma instability was sought partly with the help of feedback. A plasma instability is usually observed in its saturated state and appears as a single feature in the frequency spectrum with a single azimuthal and parallel wavenumbers. The physics of the non-zero spectral width was investigated in detail because the finite spectral width can cause "turbulent" transport. One aspect of the "turbulence" was investigated by obtaining the scaling of the linear growth rate of the instabilities with the fluctuation levels. The linear growth rates were measured with the established gated feedback technique. The research showed that the ExB instability evolves into a quasi-coherent state when the fluctuation level is high. The coherent aspects were studied with a bispectral analysis. Moreover, the single spectral feature was discovered to be actually composed of a few radial harmonics. The radial harmonics play a role in the nonlinear saturation of the instability via three-wave coupling.

Non-linear effects in bunch compressor of TARLA

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

Yildiz, Hüseyin, E-mail: huseyinyildiz006@gmail.com, E-mail: huseyinyildiz@gazi.edu.tr; Aksoy, Avni; Arikan, Pervin

2016-03-25

Transport of a beam through an accelerator beamline is affected by high order and non-linear effects such as space charge, coherent synchrotron radiation, wakefield, etc. These effects damage form of the beam, and they lead particle loss, emittance growth, bunch length variation, beam halo formation, etc. One of the known non-linear effects on low energy machine is space charge effect. In this study we focus on space charge effect for Turkish Accelerator and Radiation Laboratory in Ankara (TARLA) machine which is designed to drive InfraRed Free Electron Laser covering the range of 3-250 µm. Moreover, we discuss second order effects onmore » bunch compressor of TARLA.« less

Forest-stressing climate factors on the US West Coast as simulated by CMIP5

NASA Astrophysics Data System (ADS)

Rupp, D. E.; Buotte, P.; Hicke, J. A.; Law, B. E.; Mote, P.; Sharp, D.; Zhenlin, Y.

2013-12-01

The rate of forest mortality has increased significantly in western North America since the 1970s. Causes include insect attacks, fire, and soil water deficit, all of which are interdependent. We first identify climate factors that stress forests by reducing photosynthesis and hydraulic conductance, and by promoting bark beetle infestation and wildfire. Examples of such factors may be two consecutive years of extreme summer precipitation deficit, or prolonged vapor pressure deficit exceeding some threshold. Second, we quantify the frequency and magnitude of these climate factors in 20th and 21st century climates, as simulated by global climate models (GCMs) in Coupled Model Intercomparison Project phase 5 (CMIP5), of Washington, Oregon, and California in the western US. Both ';raw' (i.e., original spatial resolution) and statistically downscaled simulations are considered, the latter generated using the Multivariate Adaptive Constructed Analogs (MACA) method. CMIP5 models that most faithfully reproduce the observed historical statistics of these climate factors are identified. Furthermore, significant changes in the statistics between the 20th and 21st centuries are reported. A subsequent task will be to use a selected subset of MACA-downscaled CMIP5 simulations to force the Community Land Model, version 4.5 (CLM 4.5). CLM 4.5 will be modified to better simulate forest mortality and to couple CLM with an economic model. The ultimate goal of this study is to understand the interactions and the feedbacks by which the market and the forest ecosystem influence each other.

Modeling the Effects of Irrigation on Land Surface Fluxes and States over the Conterminous United States: Sensitivity to Input Data and Model Parameters

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

Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong

2013-09-16

Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to producemore » unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.« less

Factors Associated with Gastric Black Spot, White Flat Elevated Mucosa, and Cobblestone-Like Mucosa: A Cross-Sectional Study.

PubMed

Hatano, Yu; Haruma, Ken; Kamada, Tomoari; Shiotani, Akiko; Takahari, Kosuke; Matsumoto, Masatoshi; Uchida, Osamu

2018-06-05

Previous studies have reported a possible relevance between proton pump inhibitor (PPI) use and 3 new gastric mucosal changes: black spots (BSs), white flat elevated mucosa (WFEM), and cobblestone-like mucosa (CLM). The aim of this study was to investigate the association between these mucosal changes and multiple factors including PPI use. All subjects who underwent a routine esophagogastroduodenoscopy (EGD) were successively enrolled. Endoscopists carried out the EGD after being blinded about -information on patient PPI usage and determined the presence of these mucosal changes. The ratio of each factor was -compared in cases with and without each gastric finding. Out of 1,214 patients, BSs were recognized in 75 (6.2%) cases, WFEM in 59 (4.9%), and CLM in 41 (3.4%). In logistic regression analysis, PPI use was significantly correlated with all of these findings (BSs: OR 2.94; 95% CI 1.66-5.21), (WFEM: OR 3.58; 95% CI 1.94-6.61), and (CLM: OR 4.57; 95% CI 2.34-9.96), and Helicobacter pylori eradication was related to BSs (OR 3.01; 95% CI 1.73-5.24) and WFEM (OR 2.11; 95% CI 1.08-4.11). Decision-tree analyses showed that H. pylori eradication was associated with all findings. All of the considered findings were correlated with PPI and H. pylori eradication. © 2018 S. Karger AG, Basel.

Long-term survival in laparoscopic vs open resection for colorectal liver metastases: inverse probability of treatment weighting using propensity scores.

PubMed

Lewin, Joel W; O'Rourke, Nicholas A; Chiow, Adrian K H; Bryant, Richard; Martin, Ian; Nathanson, Leslie K; Cavallucci, David J

2016-02-01

This study compares long-term outcomes between intention-to-treat laparoscopic and open approaches to colorectal liver metastases (CLM), using inverse probability of treatment weighting (IPTW) based on propensity scores to control for selection bias. Patients undergoing liver resection for CLM by 5 surgeons at 3 institutions from 2000 to early 2014 were analysed. IPTW based on propensity scores were generated and used to assess the marginal treatment effect of the laparoscopic approach via a weighted Cox proportional hazards model. A total of 298 operations were performed in 256 patients. 7 patients with planned two-stage resections were excluded leaving 284 operations in 249 patients for analysis. After IPTW, the population was well balanced. With a median follow up of 36 months, 5-year overall survival (OS) and recurrence-free survival (RFS) for the cohort were 59% and 38%. 146 laparoscopic procedures were performed in 140 patients, with weighted 5-year OS and RFS of 54% and 36% respectively. In the open group, 138 procedures were performed in 122 patients, with a weighted 5-year OS and RFS of 63% and 38% respectively. There was no significant difference between the two groups in terms of OS or RFS. In the Brisbane experience, after accounting for bias in treatment assignment, long term survival after LLR for CLM is equivalent to outcomes in open surgery. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Long-term survival in laparoscopic vs open resection for colorectal liver metastases: inverse probability of treatment weighting using propensity scores

PubMed Central

Lewin, Joel W.; O'Rourke, Nicholas A.; Chiow, Adrian K.H.; Bryant, Richard; Martin, Ian; Nathanson, Leslie K.; Cavallucci, David J.

2015-01-01

Background This study compares long-term outcomes between intention-to-treat laparoscopic and open approaches to colorectal liver metastases (CLM), using inverse probability of treatment weighting (IPTW) based on propensity scores to control for selection bias. Method Patients undergoing liver resection for CLM by 5 surgeons at 3 institutions from 2000 to early 2014 were analysed. IPTW based on propensity scores were generated and used to assess the marginal treatment effect of the laparoscopic approach via a weighted Cox proportional hazards model. Results A total of 298 operations were performed in 256 patients. 7 patients with planned two-stage resections were excluded leaving 284 operations in 249 patients for analysis. After IPTW, the population was well balanced. With a median follow up of 36 months, 5-year overall survival (OS) and recurrence-free survival (RFS) for the cohort were 59% and 38%. 146 laparoscopic procedures were performed in 140 patients, with weighted 5-year OS and RFS of 54% and 36% respectively. In the open group, 138 procedures were performed in 122 patients, with a weighted 5-year OS and RFS of 63% and 38% respectively. There was no significant difference between the two groups in terms of OS or RFS. Conclusion In the Brisbane experience, after accounting for bias in treatment assignment, long term survival after LLR for CLM is equivalent to outcomes in open surgery. PMID:26902138

Stochastic subset selection for learning with kernel machines.

PubMed

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty

2017-12-01

Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.

A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)

DTIC Science & Technology

2008-11-01

retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for...estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity...and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach

Teaching Machines, Programming, Computers, and Instructional Technology: The Roots of Performance Technology.

ERIC Educational Resources Information Center

Deutsch, William

1992-01-01

Reviews the history of the development of the field of performance technology. Highlights include early teaching machines, instructional technology, learning theory, programed instruction, the systems approach, needs assessment, branching versus linear program formats, programing languages, and computer-assisted instruction. (LRW)

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

2016-01-01

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

P-T Equilibrium Conditions of Xenoliths from the Udachnaya Kimberlite Pipe: Thermal Perturbations in the Lithospheric Mantle

NASA Astrophysics Data System (ADS)

Tychkov, Nikolay; Agashev, Alexey; Malygina, Elena; Pokhilenko, Nikolay

2014-05-01

Integrated study of 250 peridotite xenoliths from Udachnaya -East pipe show difference in mineral paragenesises and textural-structural peculiarities in the different level of cratonic lithosphere mantle (CLM). The compositions of minerals were determined using EPMA. Thermobarometric parameters (Brey, Kohller, 1990) were determined for all rocks occupying different fields on geothermal curve. The deepest layer (the pressure interval of 5.0-7.0 GPa) contains mostly pophyroclastic lherzolites. Anyway, some rocks of this layer have an idiomorphic texture being also enriched in incompatible components. Higher in the CLM sequence, the interval (4.2-6.3 GPa) is composed of the most depleted rocks: megacristalline ultradepleted harzburgite-dunites and depleted granular harzburgite-dunites, as well as lherzolites in a subordinate amount. They correspond strate to 35 mW/m2 and partly overlap the deeper layer in dapth. It is likely that rocks of this layer are in equilibrium and were not subject to significant secondary changes due to kimberlite magma intrusion. Thus, this interval of the CLM sequence reflects the true (relic) geotherm for the area of the Udachnaya kimberlite pipe. Moreover, it is obvious that this interval was a major supplier of diamonds into kimberlites of the Udachnaya pipe. The interval of 4.2-2.0 GPa in the CLM sequence is also composed of coarse depleted lherzolites and harzburgites. Rocks of this interval are slightly more enriched than those of the underlying interval. This is confirmed by the distinct predominance of lherzolites over harzburgite-dunites. The heat flow in this layer varies in the range of 38-45 mW/m2 and shows a general tendency to increase with decreasing depth. According to occurrence of nonequilibrium mineral assemblages and increased heat flow relative to the major heat flow of 35 mW/m2, this interval is similar to the deepest interval of secondary enriched rocks. Interval of less than 2.0 GPa composed of spinel lherzolites and harzburgites. The temperature range of stability of these rocks is 600-900oC (average 754oC) for the geotherm curve of 45 mW/m2. The paleogeotherm obtained as a result of our study has a relatively complicated stepped structure. The geotherm knee in the deep part of the sequence, described for different regions, is connected with the temperature perturbations at the lithosphere-asthenosphere boundary. The increased heat flow at the depth corresponding to a pressure of <4.2 GPa is rather unusual. It is obvious that it is not connected with deep processes on the CLM bottom. We assume, that thermal perturbations of this interval are due to large-scale crystallization and heating when going up silicate-carbonate kimberlitic magma reach the depth of peridotite+CO2 solidus curve bend. 11-05-91060-PICS

Solid-state resistor for pulsed power machines

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

Stoltzfus, Brian; Savage, Mark E.; Hutsel, Brian Thomas

2016-12-06

A flexible solid-state resistor comprises a string of ceramic resistors that can be used to charge the capacitors of a linear transformer driver (LTD) used in a pulsed power machine. The solid-state resistor is able to absorb the energy of a switch prefire, thereby limiting LTD cavity damage, yet has a sufficiently low RC charge time to allow the capacitor to be recharged without disrupting the operation of the pulsed power machine.

Source localization in an ocean waveguide using supervised machine learning.

PubMed

Niu, Haiqiang; Reeves, Emma; Gerstoft, Peter

2017-09-01

Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data. The pressure received by a vertical linear array is preprocessed by constructing a normalized sample covariance matrix and used as the input for three machine learning methods: feed-forward neural networks (FNN), support vector machines (SVM), and random forests (RF). The range estimation problem is solved both as a classification problem and as a regression problem by these three machine learning algorithms. The results of range estimation for the Noise09 experiment are compared for FNN, SVM, RF, and conventional matched-field processing and demonstrate the potential of machine learning for underwater source localization.

Applying spectral unmixing and support vector machine to airborne hyperspectral imagery for detecting giant reed

USDA-ARS?s Scientific Manuscript database

This study evaluated linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and support vector machine (SVM) techniques for detecting and mapping giant reed (Arundo donax L.), an invasive weed that presents a severe threat to agroecosystems and riparian areas throughout the southern ...

Teaching Machines and Programmed Instruction.

ERIC Educational Resources Information Center

Kay, Harry; And Others

The various devices used in programed instruction range from the simple linear programed book to branching and skip branching programs, adaptive teaching machines, and even complex computer based systems. In order to provide a background for the would-be programer, the essential principles of each of these devices is outlined. Different ideas of…

Linear- and Repetitive Feature Detection Within Remotely Sensed Imagery

DTIC Science & Technology

2017-04-01

applicable to Python or other pro- gramming languages with image- processing capabilities. 4.1 Classification machine learning The first methodology uses...remotely sensed images that are in panchromatic or true-color formats. Image- processing techniques, in- cluding Hough transforms, machine learning, and...data fusion .................................................................................................... 44 6.3 Context-based processing

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

Sen, Amiya K.

The goal of this grant has been to study the basic physics of various sources of anomalous transport in tokamaks. Anomalous transport in tokamaks continues to be one of the major problems in magnetic fusion research. As a tokamak is not a physics device by design, direct experimental observation and identification of the instabilities responsible for transport, as well as physics studies of the transport in tokamaks, have been difficult and of limited value. It is noted that direct experimental observation, identification and physics study of microinstabilities including ITG, ETG, and trapped electron/ion modes in tokamaks has been very difficultmore » and nearly impossible. The primary reasons are co-existence of many instabilities, their broadband fluctuation spectra, lack of flexibility for parameter scans and absence of good local diagnostics. This has motivated us to study the suspected tokamak instabilities and their transport consequences in a simpler, steady state Columbia Linear Machine (CLM) with collisionless plasma and the flexibility of wide parameter variations. Earlier work as part of this grant was focused on both ITG turbulence, widely believed to be a primary source of ion thermal transport in tokamaks, and the effects of isotope scaling on transport levels. Prior work from our research team has produced and definitively identified both the slab and toroidal branches of this instability and determined the physics criteria for their existence. All the experimentally observed linear physics corroborate well with theoretical predictions. However, one of the large areas of research dealt with turbulent transport results that indicate some significant differences between our experimental results and most theoretical predictions. Latter years of this proposal were focused on anomalous electron transport with a special focus on ETG. There are several advanced tokamak scenarios with internal transport barriers (ITB), when the ion transport is reduced to neoclassical values by combined mechanisms of ExB and diamagnetic flow shear suppression of the ion temperature gradient (ITG) instabilities. However, even when the ion transport is strongly suppressed, the electron transport remains highly anomalous. The most plausible physics scenario for the anomalous electron transport is based on electron temperature gradient (ETG) instabilities. This instability is an electron analog of and nearly isomorphic to the ITG instability, which we had studied before extensively. However, this isomorphism is broken nonlinearily. It is noted that as the typical ETG mode growth rates are larger (in contrast to ITG modes) than ExB shearing rates in usual tokamaks, the flow shear suppression of ETG modes is highly unlikely. This motivated a broader range of investigations of other physics scenarios of nonlinear saturation and transport scaling of ETG modes.« less

Ecosystem function in complex mountain terrain: Combining models and long-term observations to advance process-based understanding

NASA Astrophysics Data System (ADS)

Wieder, William R.; Knowles, John F.; Blanken, Peter D.; Swenson, Sean C.; Suding, Katharine N.

2017-04-01

Abiotic factors structure plant community composition and ecosystem function across many different spatial scales. Often, such variation is considered at regional or global scales, but here we ask whether ecosystem-scale simulations can be used to better understand landscape-level variation that might be particularly important in complex terrain, such as high-elevation mountains. We performed ecosystem-scale simulations by using the Community Land Model (CLM) version 4.5 to better understand how the increased length of growing seasons may impact carbon, water, and energy fluxes in an alpine tundra landscape. The model was forced with meteorological data and validated with observations from the Niwot Ridge Long Term Ecological Research Program site. Our results demonstrate that CLM is capable of reproducing the observed carbon, water, and energy fluxes for discrete vegetation patches across this heterogeneous ecosystem. We subsequently accelerated snowmelt and increased spring and summer air temperatures in order to simulate potential effects of climate change in this region. We found that vegetation communities that were characterized by different snow accumulation dynamics showed divergent biogeochemical responses to a longer growing season. Contrary to expectations, wet meadow ecosystems showed the strongest decreases in plant productivity under extended summer scenarios because of disruptions in hydrologic connectivity. These findings illustrate how Earth system models such as CLM can be used to generate testable hypotheses about the shifting nature of energy, water, and nutrient limitations across space and through time in heterogeneous landscapes; these hypotheses may ultimately guide further experimental work and model development.

Representing leaf and root physiological traits in CLM improves global carbon and nitrogen cycling predictions

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

Ghimire, Bardan; Riley, William J.; Koven, Charles D.

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis ratesmore » are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO 2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.« less

Representing leaf and root physiological traits in CLM improves global carbon and nitrogen cycling predictions

DOE PAGES

Ghimire, Bardan; Riley, William J.; Koven, Charles D.; ...

2016-05-01

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis ratesmore » are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO 2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.« less

Molecular analyses of 6 different types of uterine smooth muscle tumors: Emphasis in atypical leiomyoma.

PubMed

Zhang, Qing; Ubago, Julianne; Li, Li; Guo, Haiyang; Liu, Yugang; Qiang, Wenan; Kim, J Julie; Kong, Beihua; Wei, Jian-Jun

2014-10-15

Uterine smooth muscle tumors (USMTs) constitute a group of histologic, genetic, and clinical heterogeneous tumors that include at least 6 major histologically defined tumor types: leiomyoma (ULM), mitotically active leiomyoma (MALM), cellular leiomyoma (CLM), atypical leiomyoma (ALM), uncertain malignant potential (STUMP), and leiomyosarcoma (LMS). Apart from ULM and LMS, the nature of these variants is not well defined. A total of 167 cases of different USMT variants were collected, reviewed, and diagnostically confirmed based on the World Health Organization and Stanford schemes. These included 38 cases of LMS, 18 cases of STUMP, 42 cases of ALM, 22 cases of CLM, 7 cases of MALM, and 40 cases of ULM. Molecular analysis included selected microRNAs (miRNAs), oncogenes, and tumor suppressors that are highly relevant to USMT. Overall, 49% (17/35) of LMS cases and 7% (1/14) of STUMP cases died due to their USMT, but no deaths were attributed to ALM. miRNA profiling revealed that ALM and LMS shared similar miRNA signatures. P53 mutations and PTEN deletions were significantly higher in LMS, ALM, and STUMP compared with other USMT variants (P < .01). In contrast, MED12 mutations were extremely common in ULM and MALM (> 74%) but were significantly less common (< 15%) in CLM, ALM, STUMP, and LMS (P < .01). Six types of USMT have different gene mutation fingerprints. ALM shares many molecular alterations with LMS. Our findings suggest that ALM may be a precursor lesion of LMS or have similar genetic changes during its early stage. © 2014 American Cancer Society.

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models

DOE PAGES

Bouskill, N. J.; Riley, W. J.; Tang, J. Y.

2014-12-11

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowgroundmore » respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model–observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha -1 yr -1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.« less

Two-stage hepatectomy: who will not jump over the second hurdle?

PubMed

Turrini, O; Ewald, J; Viret, F; Sarran, A; Goncalves, A; Delpero, J-R

2012-03-01

Two-stage hepatectomy uses compensatory liver regeneration after a first noncurative hepatectomy to enable a second curative resection in patients with bilobar colorectal liver metastasis (CLM). To determine the predictive factors of failure of two-stage hepatectomy. Between 2000 and 2010, 48 patients with irresectable CLM were eligible for two-stage hepatectomy. The planned strategy was a) cleaning of the left hepatic lobe (first hepatectomy), b) right portal vein embolisation and c) right hepatectomy (second hepatectomy). Six patients had occult CLM (n = 5) or extra-hepatic disease (n = 1), which was discovered during the first hepatectomy. Thus, 42 patients completed the first hepatectomy and underwent portal vein embolisation in order to receive the second hepatectomy. Eight patients did not undergo a second hepatectomy due to disease progression. Upon univariate analysis, two factors were identified that precluded patients from having the second hepatectomy: the combined resection of a primary tumour during the first hepatectomy (p = 0.01) and administration of chemotherapy between the two hepatectomies (p = 0.03). An independent association with impairment to perform the two-stage strategy was demonstrated by multivariate analysis for only the combined resection of the primary colorectal cancer during the first hepatectomy (p = 0.04). Due to the small number of patients and the absence of equivalent conclusions in other studies, we cannot recommend performance of an isolated colorectal resection prior to chemotherapy. However, resection of an asymptomatic primary tumour before chemotherapy should not be considered as an outdated procedure. Copyright © 2011 Elsevier Ltd. All rights reserved.

Meta-analysis of high-latitude nitrogen-addition and warming studies implies ecological mechanisms overlooked by land models

NASA Astrophysics Data System (ADS)

Bouskill, N. J.; Riley, W. J.; Tang, J. Y.

2014-12-01

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowground respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model-observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.

Sensitivity of Drought Processes to Runoff Parameterizations in East Asia with the Community Land Model

NASA Astrophysics Data System (ADS)

Kim, J. B.; Um, M. J.; Kim, Y.

2016-12-01

Drought is one of the most powerful and extensive disasters and has the highest annual average damage among all the disasters. Focusing on East Asia, where over one fifth of all the people in the world live, drought has impacted as well as been projected to impact the region significantly. .Therefore it is critical to reasonably simulate the drought phenomenon in the region and thus this study would focus on the reproducibility of drought with the NCAR CLM. In this study, we examine the propagation of drought processes with different runoff parameterization of CLM in East Asia. Two different schemes are used; TOPMODEL-based and VIC-based schemes, which differentiate the result of runoff through the surface and subsurface runoff parameterization. CLM with different runoff scheme are driven with two atmospheric forcings from CRU/NCEP and NCEP reanalysis data. Specifically, propagation of drought from meteorological, agricultural to hydrologic drought is investigated with different drought indices, estimated with not only model simulated results but also observational data. The indices include the standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI) and standardized soil moisture index (SSMI). Based on these indices, the drought characteristics such as intensity, frequency and spatial extent are investigated. At last, such drought assessments would reveal the possible model deficiencies in East Asia. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180.

Discrepancy between recurrence-free survival and overall survival in patients with resectable colorectal liver metastases: a potential surrogate endpoint for time to surgical failure.

PubMed

Oba, Masaru; Hasegawa, Kiyoshi; Matsuyama, Yutaka; Shindoh, Junichi; Mise, Yoshihiro; Aoki, Taku; Sakamoto, Yoshihiro; Sugawara, Yasuhiko; Makuuchi, Masatoshi; Kokudo, Norihiro

2014-06-01

Recurrence-free survival (RFS) may not be a surrogate for overall survival (OS) in patients with resectable colorectal liver metastases (CLM). We investigated whether a new composite tool-time to surgical failure (TSF)-is a suitable endpoint. The medical records of consecutive patients who underwent curative resection for CLM at our center over a 17-year period were reviewed. Patients with liver-limited tumors (n = 371) who had not received previous treatment for metastasis were eligible for analysis. TSF was defined as the time until unresectable relapse or death. The correlations between TSF and OS, and between RFS and OS, were assessed for all the eligible patients. The median OS, TSF, and RFS were 5.7, 2.7, and 0.7 years, respectively, and the 5-year OS, TSF, and RFS rates were 52.6, 39.8, and 23.7 %, respectively, for all patients. The rates of first, second, and third relapse were 75.5, 77.6, and 70.8 %, respectively, and repeat resections were performed in 54.3 % (first relapses), 40.7 % (second relapses), and 47.1 % (third relapses) of patients. The concordance proportions of TSF and RFS for OS events were 0.83 and 0.65, respectively. The correlation between TSF and OS was stronger than that between RFS and OS in terms of the predicted probabilities. The correlation between TSF and OS was stronger than that between RFS and OS after curative hepatic resection. TSF could be a suitable endpoint for CLM overall management.

Optimal morphologic response to preoperative chemotherapy: an alternate outcome end point before resection of hepatic colorectal metastases.

PubMed

Shindoh, Junichi; Loyer, Evelyne M; Kopetz, Scott; Boonsirikamchai, Piyaporn; Maru, Dipen M; Chun, Yun Shin; Zimmitti, Giuseppe; Curley, Steven A; Charnsangavej, Chusilp; Aloia, Thomas A; Vauthey, Jean-Nicolas

2012-12-20

The purposes of this study were to confirm the prognostic value of an optimal morphologic response to preoperative chemotherapy in patients undergoing chemotherapy with or without bevacizumab before resection of colorectal liver metastases (CLM) and to identify predictors of the optimal morphologic response. The study included 209 patients who underwent resection of CLM after preoperative chemotherapy with oxaliplatin- or irinotecan-based regimens with or without bevacizumab. Radiologic responses were classified as optimal or suboptimal according to the morphologic response criteria. Overall survival (OS) was determined, and prognostic factors associated with an optimal response were identified in multivariate analysis. An optimal morphologic response was observed in 47% of patients treated with bevacizumab and 12% of patients treated without bevacizumab (P < .001). The 3- and 5-year OS rates were higher in the optimal response group (82% and 74%, respectively) compared with the suboptimal response group (60% and 45%, respectively; P < .001). On multivariate analysis, suboptimal morphologic response was an independent predictor of worse OS (hazard ratio, 2.09; P = .007). Receipt of bevacizumab (odds ratio, 6.71; P < .001) and largest metastasis before chemotherapy of ≤ 3 cm (odds ratio, 2.12; P = .025) were significantly associated with optimal morphologic response. The morphologic response showed no specific correlation with conventional size-based RECIST criteria, and it was superior to RECIST in predicting major pathologic response. Independent of preoperative chemotherapy regimen, optimal morphologic response is sufficiently correlated with OS to be considered a surrogate therapeutic end point for patients with CLM.

Optimal Morphologic Response to Preoperative Chemotherapy: An Alternate Outcome End Point Before Resection of Hepatic Colorectal Metastases

PubMed Central

Shindoh, Junichi; Loyer, Evelyne M.; Kopetz, Scott; Boonsirikamchai, Piyaporn; Maru, Dipen M.; Chun, Yun Shin; Zimmitti, Giuseppe; Curley, Steven A.; Charnsangavej, Chusilp; Aloia, Thomas A.; Vauthey, Jean-Nicolas

2012-01-01

Purpose The purposes of this study were to confirm the prognostic value of an optimal morphologic response to preoperative chemotherapy in patients undergoing chemotherapy with or without bevacizumab before resection of colorectal liver metastases (CLM) and to identify predictors of the optimal morphologic response. Patients and Methods The study included 209 patients who underwent resection of CLM after preoperative chemotherapy with oxaliplatin- or irinotecan-based regimens with or without bevacizumab. Radiologic responses were classified as optimal or suboptimal according to the morphologic response criteria. Overall survival (OS) was determined, and prognostic factors associated with an optimal response were identified in multivariate analysis. Results An optimal morphologic response was observed in 47% of patients treated with bevacizumab and 12% of patients treated without bevacizumab (P < .001). The 3- and 5-year OS rates were higher in the optimal response group (82% and 74%, respectively) compared with the suboptimal response group (60% and 45%, respectively; P < .001). On multivariate analysis, suboptimal morphologic response was an independent predictor of worse OS (hazard ratio, 2.09; P = .007). Receipt of bevacizumab (odds ratio, 6.71; P < .001) and largest metastasis before chemotherapy of ≤ 3 cm (odds ratio, 2.12; P = .025) were significantly associated with optimal morphologic response. The morphologic response showed no specific correlation with conventional size-based RECIST criteria, and it was superior to RECIST in predicting major pathologic response. Conclusion Independent of preoperative chemotherapy regimen, optimal morphologic response is sufficiently correlated with OS to be considered a surrogate therapeutic end point for patients with CLM. PMID:23150701

Positive Impact of Epidural Analgesia on Oncologic Outcomes in Patients Undergoing Resection of Colorectal Liver Metastases.

PubMed

Zimmitti, Giuseppe; Soliz, Jose; Aloia, Thomas A; Gottumukkala, Vijaya; Cata, Juan P; Tzeng, Ching-Wei D; Vauthey, Jean-Nicolas

2016-03-01

Previous studies have suggested that the use of regional anesthesia can reduce recurrence risk after oncologic surgery. The purpose of this study was to assess the effect of epidural anesthesia on recurrence-free (RFS) and overall survival (OS) after hepatic resection for colorectal liver metastases (CLM). After approval of the institutional review board, the records of all adult patients who underwent elective hepatic resection between January 2006 and October 2011 were retrospectively reviewed. Patients were categorized according to use of perioperative epidural analgesia versus intravenous analgesia. Univariate and multivariate analyses were performed to identify factors influencing RFS and OS. Of 510 total patients, 390 received epidural analgesia (EA group) and 120 patients received intravenous analgesia (IVA group). Compared with the IVA group, more patients in the EA group underwent associated surgical procedures with consequently longer operative times (p < 0.001). In addition, the EA group received more intraoperative fluids and had higher urine output volumes (p ≤ 0.001). Five-year RFS was longer in the EA group (34.7%) compared with the IVA group (21.1%). On multivariate analysis, the receipt of epidural analgesia was an independent predictor of improved RFS (p = 0.036, hazard ratio [HR] 0.74; 95% confidence interval [CI] 0.56-0.95), but not OS (p = 0.102, HR 0.72; 95% CI 0.49-1.07). This study suggests an association between epidural analgesia and improved RFS, but not OS, after CLM resection. These results warrant further prospective, randomized studies on the benefits of regional anesthesia on oncologic outcomes after hepatic resection for CLM.

Representing leaf and root physiological traits in CLM improves global carbon and nitrogen cycling predictions

NASA Astrophysics Data System (ADS)

Ghimire, Bardan; Riley, William J.; Koven, Charles D.; Mu, Mingquan; Randerson, James T.

2016-06-01

In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis rates are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.

Improving irrigation and groundwater parameterizations in the Community Land Model (CLM) using in-situ observations and satellite data

NASA Astrophysics Data System (ADS)

Felfelani, F.; Pokhrel, Y. N.

2017-12-01

In this study, we use in-situ observations and satellite data of soil moisture and groundwater to improve irrigation and groundwater parameterizations in the version 4.5 of the Community Land Model (CLM). The irrigation application trigger, which is based on the soil moisture deficit mechanism, is enhanced by integrating soil moisture observations and the data from the Soil Moisture Active Passive (SMAP) mission which is available since 2015. Further, we incorporate different irrigation application mechanisms based on schemes used in various other land surface models (LSMs) and carry out a sensitivity analysis using point simulations at two different irrigated sites in Mead, Nebraska where data from the AmeriFlux observational network are available. We then conduct regional simulations over the entire High Plains region and evaluate model results with the available irrigation water use data at the county-scale. Finally, we present results of groundwater simulations by implementing a simple pumping scheme based on our previous studies. Results from the implementation of current irrigation parameterization used in various LSMs show relatively large difference in vertical soil moisture content profile (e.g., 0.2 mm3/mm3) at point scale which is mostly decreased when averaged over relatively large regions (e.g., 0.04 mm3/mm3 in the High Plains region). It is found that original irrigation module in CLM 4.5 tends to overestimate the soil moisture content compared to both point observations and SMAP, and the results from the improved scheme linked with the groundwater pumping scheme show better agreement with the observations.

Colorectal liver metastases.

PubMed

Tzeng, Ching-Wei D; Aloia, Thomas A

2013-01-01

With modern multimodality therapy, patients with resected colorectal cancer (CRC) liver metastases (CLM) can experience up to 50-60 % 5-year survival. These improved outcomes have become more commonplace via achievements in multidisciplinary care, improved definition of resectability, and advances in technical skill. Even patients with synchronous and/or extensive bilateral disease have benefited from novel surgical strategies. Treatment sequencing of synchronous CRC with CLM can be simplified into the following three paradigms: (classic colorectal-first), simultaneous (combined), or reverse approach (liver-first). The decision of whether to treat the CLM or CRC first depends on which site dominates oncologically and symptomatically. Oxaliplatin with 5-fluorouracil/leucovorin (FOLFOX) and irinotecan with 5-fluorouracil/leucovorin (FOLFIRI) are the foundations of modern chemotherapy. Although each regimen has positively impacted survivals, both have the potential for negative effects on the non-tumor liver. Oxaliplatin is associated with vascular injury (sinusoidal ballooning, microvascular injury, nodular regenerative hyperplasia, and long-term fibrosis) but not steatosis. Irinotecan has been associated with steatohepatitis, especially in patients with obesity and diabetes. Steatohepatitis from irinotecan is the only chemotherapy-associated liver injury (CALI) associated with increased mortality from postoperative hepatic insufficiency. Extended duration of preoperative chemotherapy is also associated with CALI. To determine resectability and to prevent overtreatment with systemic therapy, all patients should receive high-quality cross-sectional imaging and be evaluated by a hepatobiliary surgeon before starting chemotherapy. Even as chemotherapy improves, liver surgeons will continue to play a central role in treatment planning by offering the best chance for prolonged survival-safe R0 resection with curative intent.

Optical realization of optimal symmetric real state quantum cloning machine

NASA Astrophysics Data System (ADS)

Hu, Gui-Yu; Zhang, Wen-Hai; Ye, Liu

2010-01-01

We present an experimentally uniform linear optical scheme to implement the optimal 1→2 symmetric and optimal 1→3 symmetric economical real state quantum cloning machine of the polarization state of the single photon. This scheme requires single-photon sources and two-photon polarization entangled state as input states. It also involves linear optical elements and three-photon coincidence. Then we consider the realistic realization of the scheme by using the parametric down-conversion as photon resources. It is shown that under certain condition, the scheme is feasible by current experimental technology.

Estimation of perceptible water vapor of atmosphere using artificial neural network, support vector machine and multiple linear regression algorithm and their comparative study

NASA Astrophysics Data System (ADS)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.

Model developments in TERRA_URB, the upcoming standard urban parametrization of the atmospheric numerical model COSMO(-CLM)

NASA Astrophysics Data System (ADS)

Wouters, Hendrik; Blahak, Ulrich; Helmert, Jürgen; Raschendorfer, Matthias; Demuzere, Matthias; Fay, Barbara; Trusilova, Kristina; Mironov, Dmitrii; Reinert, Daniel; Lüthi, Daniel; Machulskaya, Ekaterina

2015-04-01

In order to address urban climate at the regional scales, a new efficient urban land-surface parametrization TERRA_URB has been developed and coupled to the atmospheric numerical model COSMO-CLM. Hereby, several new advancements for urban land-surface models are introduced which are crucial for capturing the urban surface-energy balance and its seasonal dependency in the mid-latitudes. This includes a new PDF-based water-storage parametrization for impervious land, the representation of radiative absorption and emission by greenhouse gases in the infra-red spectrum in the urban canopy layer, and the inclusion of heat emission from human activity. TERRA_URB has been applied in offline urban-climate studies during European observation campaigns at Basel (BUBBLE), Toulouse (CAPITOUL), and Singapore, and currently applied in online studies for urban areas in Belgium, Germany, Switzerland, Helsinki, Singapore, and Melbourne. Because of its computational efficiency, high accuracy and its to-the-point conceptual easiness, TERRA_URB has been selected to become the standard urban parametrization of the atmospheric numerical model COSMO(-CLM). This allows for better weather forecasts for temperature and precipitation in cities with COSMO, and an improved assessment of urban outdoor hazards in the context of global climate change and urban expansion with COSMO-CLM. We propose additional extensions to TERRA_URB towards a more robust representation of cities over the world including their structural design. In a first step, COSMO's standard EXTernal PARarameter (EXTPAR) tool is updated for representing the cities into the land cover over the entire globe. Hereby, global datasets in the standard EXTPAR tool are used to retrieve the 'Paved' or 'sealed' surface Fraction (PF) referring to the presence of buildings and streets. Furthermore, new global data sets are incorporated in EXTPAR for describing the Anthropogenic Heat Flux (AHF) due to human activity, and optionally the Surface Area Index (SAI) derived from the Floor Space Index (FSI). In a second step, it is focussed on the urban/rural contrast in terms of turbulent transport in the surface layer by means of model sensivity experiments: On the theoretical basis of the TKE-based surface-layer transfer scheme of COSMO, we investigate the consistency between empirical functions for thermal roughness lengths and the urban/rural canopy morphology.

Dynamics of carbon, water and energy cycles in a heterogeneous landscape and a changing climate

NASA Astrophysics Data System (ADS)

Schmidt, A.; Law, B. E.; Still, C. J.; Hilker, T.

2016-12-01

The combined effects of changes in land-use and land cover (LULC) and climate on carbon and water cycling need to be assessed at regional scales. LULC changes over time have many drivers such as expanding urban areas, exploration of new agricultural areas due to overused natural resources of current agricultural areas (e.g. degraded soil), economical reasons, or policy changes that encourage the use of alternative energy resources. Our study assesses the effects of conversion of semi-arid sagebrush and agricultural crops to bioenergy production on carbon, water and energy cycling, and resulting heating or cooling effects. Our project focusses on Oregon, where agricultural crops, significant forest area, and urban expansion are coupled with a strong spatial climate gradient that allows us to examine influences on carbon sequestration by the terrestrial biosphere. Our inverse modeling results showed that the prior fluxes modelled with CLM4.5 underestimated NEE in the highly productive western Douglas fir forests by more than 50%. Based on the results of our Bayesian inversion, we optimized ecosystem fluxes and changed CLM model parameters accordingly. By integrating remote sensing LULC data, eddy covariance data from flux sites, tall tower CO2 observations, biomass estimates from field samples, and CLM4.5, we predict current and future statewide carbon sequestration with unprecedented accuracy. Using inventories and tower flux data, we determined the effect of conversion of hay and grass seed cropland (323,200 ha) to hybrid poplar and found the state NEP increased from 4 TgCO2 per year to 13 TgCO2 per year for that area. The last coal power plant in the state (Boardman) is in the process of switching from coal combustion to biofuel burning to meet the state's goal for the reduction of greenhouse gas emissions. Our results show that the 7816 tons of biomass per day to keep the 518 MW power plant running at base load would amount to 35,000 hectares of hybrid poplar per year under current climate conditions. The improved CLM4.5 model will be used to evaluate the impacts of this land use change on the net ecosystem carbon balance under future climate conditions.

Impacts of Stratospheric Black Carbon on Agriculture

NASA Astrophysics Data System (ADS)

Xia, L.; Robock, A.; Elliott, J. W.

2017-12-01

A regional nuclear war between India and Pakistan could inject 5 Tg of soot into the stratosphere, which would absorb sunlight, decrease global surface temperature by about 1°C for 5-10 years and have major impacts on precipitation and the amount of solar radiation reaching Earth's surface. Using two global gridded crop models forced by one global climate model simulation, we investigate the impacts on agricultural productivity in various nations. The crop model in the Community Land Model 4.5 (CLM-crop4.5) and the parallel Decision Support System for Agricultural Technology (pDSSAT) in the parallel System for Integrating Impact Models and Sectors are participating in the Global Gridded Crop Model Intercomparison. We force these two crop models with output from the Whole Atmospheric Community Climate Model to characterize the global agricultural impact from climate changes due to a regional nuclear war. Crops in CLM-crop4.5 include maize, rice, soybean, cotton and sugarcane, and crops in pDSSAT include maize, rice, soybean and wheat. Although the two crop models require a different time frequency of weather input, we downscale the climate model output to provide consistent temperature, precipitation and solar radiation inputs. In general, CLM-crop4.5 simulates a larger global average reduction of maize and soybean production relative to pDSSAT. Global rice production shows negligible change with climate anomalies from a regional nuclear war. Cotton and sugarcane benefit from a regional nuclear war from CLM-crop4.5 simulation, and global wheat production would decrease significantly in the pDSSAT simulation. The regional crop yield responses to a regional nuclear conflict are different for each crop, and we present the changes in production on a national basis. These models do not include the crop responses to changes in ozone, ultraviolet radiation, or diffuse radiation, and we would like to encourage more modelers to improve crop models to account for those impacts. We present these results as a demonstration of using different crop models to study this problem, and we invite more global crop modeling groups to use the same climate forcing, which we would be happy to provide, to gain a better understanding of global agricultural responses under different future climate scenarios with stratospheric aerosols.

Comparison between the Community Land Model and the Terra Urb model in COSMO 5.0 over tropical Africa

NASA Astrophysics Data System (ADS)

Brousse, Oscar; Wouters, Hendrik; Thiery, Wim; Demuzere, Matthias; Van Lipzig, Nicole

2017-04-01

African urban inhabitants are expected to rise up to 75% of the continent's population at the horizon of 2050 (United Nations, 2014). This unprecedented demographic rise has led to an uncontrolled urbanization, and hence to a lack of public health infrastructures and administration within African cities. During the past decades, as an example, malaria's mitigating infrastructures have been constructed without considering the impact of urbanization. Indexes of malaria's risks have been based on rural areas, driving huge biases by not taking into account characteristics of the urban environment. In response to this challenge, the REACT project sets out to develop an index for malaria risk in urban tropical Africa. In particular, we aim to create two indexes that apply to the regional and local scale, respectively. Especially, intra-urban variability of the near-surface climate and the malaria's epidemiology thus needs to be described. To start, we first conduct a series of sensitivity simulations over a one-year period to determine which Land Surface Model (LSM) implemented within COSMO 5.0 is most suited for the purpose of this research. The model domain will cover the Lake Victoria area, integrating Kampala within its boundaries. The regional climate is considered as tropical and interactions between Lake Victoria and its surroundings have been proven (Thiery et al., 2015; 2016). Since malaria depends on typical meteorological and climatic factors such as precipitation, relative humidity, wind speed and temperature, the first part of the project aims at finding which of the LSMs able to assess the more conveniently those epidemiological drivers. Indeed, the results of those runs will serve both the scales for inter- and intra-urban analysis (through a downscaling approach) and hence need to be as detailed as possible. The coupling of COSMO-CLM with the Community Land Model (COSMO-CLM2; Davin and Seneviratne, 2012) is known to have a better integration of vegetation's influence on the meteorological circulations, while the COSMO-CLM coupled with the TerraUrb Urban Canopy Model (Wouters et al., 2015; 2016) is evaluated to have a robust representation of the urban areas' interactions with the atmosphere. Both couplings will be subject to the same boundary conditions and period of study before being compared with a reference run, only vegetated, performed with the COSMO-CLM2, and with a suite of observational products.

Management Perspectives Pertaining to Root Cause Analyses of Nunn-McCurdy Breaches. Volume 4

DTIC Science & Technology

2013-01-01

the FY2012 NDAA, the Army revised its initial budget request, allocating money from the purchase of new M2 .50 caliber machine guns to the...Quick-change machine gun barrel Explosive reactive armor Linear demolition charge system Full width, surface mine ploughs On-board vehicle power...Quantity Oversight of ACAT II Programs 45 for a restart to the program citing a “critical shortage of serviceable machine guns for our Soldiers who

A Two-Layer Least Squares Support Vector Machine Approach to Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Liu, Jingli; Li, Jianping; Xu, Weixuan; Shi, Yong

Least squares support vector machine (LS-SVM) is a revised version of support vector machine (SVM) and has been proved to be a useful tool for pattern recognition. LS-SVM had excellent generalization performance and low computational cost. In this paper, we propose a new method called two-layer least squares support vector machine which combines kernel principle component analysis (KPCA) and linear programming form of least square support vector machine. With this method sparseness and robustness is obtained while solving large dimensional and large scale database. A U.S. commercial credit card database is used to test the efficiency of our method and the result proved to be a satisfactory one.

Simulations of Moscow megacity heat island with the COSMO-CLM model using two different urban canopy schemes and realistic building parameters, derived from OpenStreetMap data

NASA Astrophysics Data System (ADS)

Varentsov, Mikhail; Wouters, Hendrik; Trusilova, Kristina; Samsonov, Timofey; Konstantinov, Pavel

2017-04-01

In this study we present the application of the regional climate model COSMO-CLM to simulate urban heat island (UHI) phenomenon for Moscow megacity, which is the biggest agglomeration in Europe (with modern population of more than 17 million people). Significant differences of Moscow from the cities of Western Europe are related with much more continental climate with higher diurnal and annual temperature variations, and with specific building features such as its high density and almost total predominance of high-rise and low-rise blocks of flats on the private low-rise houses. Because of these building and climate features, the UHI of Moscow megacity is stronger than UHIs of many other cities of the similar size, with a mean intensity is about 2 °C and maximum intensity reaching up to 13 °C (Lokoschenko, 2014). Such a pronounced UHI together with the existence of an extensive observation network (more than 50 weather and air quality monitoring stations and few microwave temperature profilers) within the city and its surrounding make Moscow an especially interesting place for urban climate researches and good testbed for urban canopy models. In our numerical experiments, regional climate model firstly was adapted for investigated region with aim to improve quality of its simulations of rural areas. Then, to take into account urban canopy effects on thermal regime of the urbanized areas, we used two different versions of COSMO-CLM model. First is coupled with TEB (Town Energy Balance) single layer urban canopy model (Trusilova, 2013), and second is extended with bulk urban canopy scheme TERRA_URB using the Semi-empircal URban-canopY dependency parametriation SURY (Wouters et. al, 2016). Numerical experiments with these two versions of the model were run with spatial resolution about 1 km for several summer and winter months. To provide specific parameters, required for urban parameterizations, such as urban fraction, building height and street canyon aspect ratio, we used originally technology of GIS-based processing of realistic OpenStreetMap data, which includes size and shape of the most of the in the city (Samsonov et al., 2015). Our testbed allows to make more detailed comparison between the modelling approaches, and also reveals the importance of correct definition of the of turbulent mixing in the ABL in the atmospheric model, and the realistic specification of the building morphology parameters and anthropogenic heat fluxes. In addition, strong seasonal variation of the importance of different factors, responsible for UHI appearance, was shown. Moreover, the framework allows to identify and solve issues regarding the different model approaches: detailed analysis of spatial and temporal variations of modelled urban temperature anomalies and their vertical extent has shown that version of COSMO-CLM model with TERRA-URB scheme simulate UHI effect in more realistic way. Research was supported by Russian Foundation for Basic Research (RFBR) and Russian Geographic Society (RGS): RFBR projects № 16-35-00474, 15-35-21129 and 16-05-00704 A, RGS-RFBR project № 13-05-41306. References: 1. Lokoshchenko, M. A. (2014). Urban 'heat island' in Moscow. Urban Climate, 10, 550-562. 2. Samsonov, T. E., Konstantinov, P. I., & Varentsov, M. I. (2015). Object-oriented approach to urban canyon analysis and its applications in meteorological modeling. Urban Climate, 13, 122-139. 3. Trusilova K., Früh, B., Brienen, S., Walter, A., Masson, V., Pigeon, G., Becker, P. Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM// Journal of Applied Meteorology and Climatology. 2013. Vol. 52. P. 2296-2311. 4. Wouters, H., Demuzere, M., Blahak, U., Fortuniak, K., Maiheu, B., Camps, J., & van Lipzig, N. P. (2016). The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer. Geoscientific Model Development, 9(9), 3027-3054.

Gesture-controlled interfaces for self-service machines and other applications

NASA Technical Reports Server (NTRS)

Cohen, Charles J. (Inventor); Jacobus, Charles J. (Inventor); Paul, George (Inventor); Beach, Glenn (Inventor); Foulk, Gene (Inventor); Obermark, Jay (Inventor); Cavell, Brook (Inventor)

2004-01-01

A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.

Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

PubMed

Jongin Kim; Boreom Lee

2017-07-01

The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

Transducer-actuator systems and methods for performing on-machine measurements and automatic part alignment

DOEpatents

Barkman, William E.; Dow, Thomas A.; Garrard, Kenneth P.; Marston, Zachary

2016-07-12

Systems and methods for performing on-machine measurements and automatic part alignment, including: a measurement component operable for determining the position of a part on a machine; and an actuation component operable for adjusting the position of the part by contacting the part with a predetermined force responsive to the determined position of the part. The measurement component consists of a transducer. The actuation component consists of a linear actuator. Optionally, the measurement component and the actuation component consist of a single linear actuator operable for contacting the part with a first lighter force for determining the position of the part and with a second harder force for adjusting the position of the part. The actuation component is utilized in a substantially horizontal configuration and the effects of gravitational drop of the part are accounted for in the force applied and the timing of the contact.

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

Bartolac, S; Letourneau, D; University of Toronto, Toronto, Ontario

Purpose: Application of process control theory in quality assurance programs promises to allow earlier identification of problems and potentially better quality in delivery than traditional paradigms based primarily on tolerances and action levels. The purpose of this project was to characterize underlying seasonal variations in linear accelerator output that can be used to improve performance or trigger preemptive maintenance. Methods: Review of runtime plots of daily (6 MV) output data acquired using in house ion chamber based devices over three years and for fifteen linear accelerators of varying make and model were evaluated. Shifts in output due to known interventionsmore » with the machines were subtracted from the data to model an uncorrected scenario for each linear accelerator. Observable linear trends were also removed from the data prior to evaluation of periodic variations. Results: Runtime plots of output revealed sinusoidal, seasonal variations that were consistent across all units, irrespective of manufacturer, model or age of machine. The average amplitude of the variation was on the order of 1%. Peak and minimum variations were found to correspond to early April and September, respectively. Approximately 48% of output adjustments made over the period examined were potentially avoidable if baseline levels had corresponded to the mean output, rather than to points near a peak or valley. Linear trends were observed for three of the fifteen units, with annual increases in output ranging from 2–3%. Conclusion: Characterization of cyclical seasonal trends allows for better separation of potentially innate accelerator behaviour from other behaviours (e.g. linear trends) that may be better described as true out of control states (i.e. non-stochastic deviations from otherwise expected behavior) and could indicate service requirements. Results also pointed to an optimal setpoint for accelerators such that output of machines is maintained within set tolerances and interventions are required less frequently.« less

Color line scan camera technology and machine vision: requirements to consider

NASA Astrophysics Data System (ADS)

Paernaenen, Pekka H. T.

1997-08-01

Color machine vision has shown a dynamic uptrend in use within the past few years as the introduction of new cameras and scanner technologies itself underscores. In the future, the movement from monochrome imaging to color will hasten, as machine vision system users demand more knowledge about their product stream. As color has come to the machine vision, certain requirements for the equipment used to digitize color images are needed. Color machine vision needs not only a good color separation but also a high dynamic range and a good linear response from the camera used. Good dynamic range and linear response is necessary for color machine vision. The importance of these features becomes even more important when the image is converted to another color space. There is always lost some information when converting integer data to another form. Traditionally the color image processing has been much slower technique than the gray level image processing due to the three times greater data amount per image. The same has applied for the three times more memory needed. The advancements in computers, memory and processing units has made it possible to handle even large color images today cost efficiently. In some cases he image analysis in color images can in fact even be easier and faster than with a similar gray level image because of more information per pixel. Color machine vision sets new requirements for lighting, too. High intensity and white color light is required in order to acquire good images for further image processing or analysis. New development in lighting technology is bringing eventually solutions for color imaging.

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

NASA Astrophysics Data System (ADS)

Huttunen, Jani; Kokkola, Harri; Mielonen, Tero; Esa Juhani Mononen, Mika; Lipponen, Antti; Reunanen, Juha; Vilhelm Lindfors, Anders; Mikkonen, Santtu; Erkki Juhani Lehtinen, Kari; Kouremeti, Natalia; Bais, Alkiviadis; Niska, Harri; Arola, Antti

2016-07-01

In order to have a good estimate of the current forcing by anthropogenic aerosols, knowledge on past aerosol levels is needed. Aerosol optical depth (AOD) is a good measure for aerosol loading. However, dedicated measurements of AOD are only available from the 1990s onward. One option to lengthen the AOD time series beyond the 1990s is to retrieve AOD from surface solar radiation (SSR) measurements taken with pyranometers. In this work, we have evaluated several inversion methods designed for this task. We compared a look-up table method based on radiative transfer modelling, a non-linear regression method and four machine learning methods (Gaussian process, neural network, random forest and support vector machine) with AOD observations carried out with a sun photometer at an Aerosol Robotic Network (AERONET) site in Thessaloniki, Greece. Our results show that most of the machine learning methods produce AOD estimates comparable to the look-up table and non-linear regression methods. All of the applied methods produced AOD values that corresponded well to the AERONET observations with the lowest correlation coefficient value being 0.87 for the random forest method. While many of the methods tended to slightly overestimate low AODs and underestimate high AODs, neural network and support vector machine showed overall better correspondence for the whole AOD range. The differences in producing both ends of the AOD range seem to be caused by differences in the aerosol composition. High AODs were in most cases those with high water vapour content which might affect the aerosol single scattering albedo (SSA) through uptake of water into aerosols. Our study indicates that machine learning methods benefit from the fact that they do not constrain the aerosol SSA in the retrieval, whereas the LUT method assumes a constant value for it. This would also mean that machine learning methods could have potential in reproducing AOD from SSR even though SSA would have changed during the observation period.

Tool setting device

DOEpatents

Brown, Raymond J.

1977-01-01

The present invention relates to a tool setting device for use with numerically controlled machine tools, such as lathes and milling machines. A reference position of the machine tool relative to the workpiece along both the X and Y axes is utilized by the control circuit for driving the tool through its program. This reference position is determined for both axes by displacing a single linear variable displacement transducer (LVDT) with the machine tool through a T-shaped pivotal bar. The use of the T-shaped bar allows the cutting tool to be moved sequentially in the X or Y direction for indicating the actual position of the machine tool relative to the predetermined desired position in the numerical control circuit by using a single LVDT.

Intelligent image processing for machine safety

NASA Astrophysics Data System (ADS)

Harvey, Dennis N.

1994-10-01

This paper describes the use of intelligent image processing as a machine guarding technology. One or more color, linear array cameras are positioned to view the critical region(s) around a machine tool or other piece of manufacturing equipment. The image data is processed to provide indicators of conditions dangerous to the equipment via color content, shape content, and motion content. The data from these analyses is then sent to a threat evaluator. The purpose of the evaluator is to determine if a potentially machine-damaging condition exists based on the analyses of color, shape, and motion, and on `knowledge' of the specific environment of the machine. The threat evaluator employs fuzzy logic as a means of dealing with uncertainty in the vision data.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders.

PubMed

Viejo, Guillaume; Cortier, Thomas; Peyrache, Adrien

2018-03-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders

PubMed Central

Cortier, Thomas; Peyrache, Adrien

2018-01-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains. PMID:29565979

Micro-Machined High-Frequency (80 MHz) PZT Thick Film Linear Arrays

PubMed Central

Zhou, Qifa; Wu, Dawei; Liu, Changgeng; Zhu, Benpeng; Djuth, Frank; Shung, K. Kirk

2010-01-01

This paper presents the development of a micro-machined high-frequency linear array using PZT piezoelectric thick films. The linear array has 32 elements with an element width of 24 μm and an element length of 4 mm. Array elements were fabricated by deep reactive ion etching of PZT thick films, which were prepared from spin-coating of PZT solgel composite. Detailed fabrication processes, especially PZT thick film etching conditions and a novel transferring-and-etching method, are presented and discussed. Array designs were evaluated by simulation. Experimental measurements show that the array had a center frequency of 80 MHz and a fractional bandwidth (−6 dB) of 60%. An insertion loss of −41 dB and adjacent element crosstalk of −21 dB were found at the center frequency. PMID:20889407

Effect of changing driving conditions on driver behavior towards design of a safe and efficient traffic system.

DOT National Transportation Integrated Search

2013-12-01

This simulation-based study explores the effects of different work zone configurations, varying distances : between traffic signs, traffic density and individual differences on drivers behavior. Conventional Lane : Merge (CLM) and Joint Lane Merge...

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Improving representation of nitrogen uptake, allocation, and carbon assimilation in the Community Land Model

NASA Astrophysics Data System (ADS)

Ghimire, B.; Riley, W. J.; Koven, C.

2013-12-01

Nitrogen is the most important nutrient limiting plant carbon assimilation and growth, and is required for production of photosynthetic enzymes, growth and maintenance respiration, and maintaining cell structure. The forecasted rise in plant available nitrogen through atmospheric nitrogen deposition and the release of locked soil nitrogen by permafrost thaw in high latitude ecosystems is likely to result in an increase in plant productivity. However a mechanistic representation of plant nitrogen dynamics is lacking in earth system models. Most earth system models ignore the dynamic nature of plant nutrient uptake and allocation, and further lack tight coupling of below- and above-ground processes. In these models, the increase in nitrogen uptake does not translate to a corresponding increase in photosynthesis parameters, such as maximum Rubisco capacity and electron transfer rate. We present an improved modeling framework implemented in the Community Land Model version 4.5 (CLM4.5) for dynamic plant nutrient uptake, and allocation to different plant parts, including leaf enzymes. This modeling framework relies on imposing a more realistic flexible carbon to nitrogen stoichiometric ratio for different plant parts. The model mechanistically responds to plant nitrogen uptake and leaf allocation though changes in photosynthesis parameters. We produce global simulations, and examine the impacts of the improved nitrogen cycling. The improved model is evaluated against multiple observations including TRY database of global plant traits, nitrogen fertilization observations and 15N tracer studies. Global simulations with this new version of CLM4.5 showed better agreement with the observations than the default CLM4.5-CN model, and captured the underlying mechanisms associated with plant nitrogen cycle.

Significance of R1 Resection for Advanced Colorectal Liver Metastases in the Era of Modern Effective Chemotherapy.

PubMed

Laurent, Christophe; Adam, Jean-Philippe; Denost, Quentin; Smith, Denis; Saric, Jean; Chiche, Laurence

2016-05-01

The prognosis impact of positive margins after resection of colorectal liver metastases (CLM) in patients treated with modern effective chemotherapy has not been elucidated. The objective was to compare oncologic outcomes after R0 and R1 resections in the era of modern effective chemotherapy. Between 1999 and 2010, all consecutive patients undergoing liver resection for CLM were analyzed retrospectively. Patients with extrahepatic metastases, macroscopic residual tumor, treated with combined radiofrequency, or not treated with chemotherapy were excluded. Survival and recurrence after R0 (tumor-free margin >0 mm) and R1 resections were analyzed. Among 466 patients undergoing hepatectomy for CLM, 191 were eligible. Of them, 164 (86 %) received preoperative chemotherapy and 105 (55 %) received postoperative chemotherapy. R1 resection (10 %) was comparable in patients treated or not by preoperative chemotherapy. R1 status was associated with more intrahepatic recurrences. Overall survival (OS) (44 vs. 61 %; p = 0.047) and disease-free survival (DFS) (8 vs. 26 %; p = 0.082) were lower in patients after R1 compared to R0 resection (32 months of median follow-up). Preoperative chemotherapy and major hepatectomy were prognostic factors of survival, whereas postoperative chemotherapy was a protective factor from recurrences. In patients treated with preoperative chemotherapy, OS and DFS were similar between R1 and R0 resections (40 vs. 55 %, p = 0.104 and 9 vs. 22 %, p = 0.174, respectively). In the era of modern effective chemotherapy, R1 resection leads to more intrahepatic recurrences but did not affect OS in selected patient responders to neoadjuvant chemotherapy. Postoperative chemotherapy protects from recurrences whatever the margin resection status.

Tropical forest response to a drier future: Measurement and modeling of soil organic matter stocks and turnover

NASA Astrophysics Data System (ADS)

Finstad, K. M.; Campbell, A.; Pett-Ridge, J.; Zhang, N.; McFarlane, K. J.

2017-12-01

Tropical forests account for over 50% of the global terrestrial carbon sink and 29% of global soil carbon, but the stability of carbon in these ecosystems under a changing climate is unknown. Recent work suggests moisture may be more important than temperature in driving soil carbon storage and emissions in the tropics. However, data on belowground carbon cycling in the tropics is sparse, and the role of moisture on soil carbon dynamics is underrepresented in current land surface models limiting our ability to extrapolate from field experiments to the entire region. We measured radiocarbon (14C) and calculated turnover rates of organic matter from 37 soil profiles from the Neotropics including sites in Mexico, Brazil, Costa Rica, Puerto Rico, and Peru. Our sites represent a large range of moisture, spanning 710 to 4200 mm of mean annual precipitation, and include Andisols, Oxisols, Inceptisols, and Ultisols. We found a large range in soil 14C profiles between sites, and in some locations, we also found a large spatial variation within a site. We compared measured soil C stocks and 14C profiles to data generated from the Community Land Model (CLM) v.4.5 and have begun to generate data from the ACME Land Model (ALM) v.1. We found that the CLM consistently overestimated carbon stocks and the mean age of soil carbon at the surface (upper 50 cm), and underestimated the mean age of deep soil carbon. Additionally, the CLM did not capture the variation in 14C and C stock profiles that exists between and within the sites across the Neotropics. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-736060.

Evaluation of high-resolution climate simulations for West Africa using COSMO-CLM

NASA Astrophysics Data System (ADS)

Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Laux, Patrick; Heinzeller, Dominikus; Kunstmann, Harald; Sarr, Abdoulaye; Thierno Gaye, Amadou

2017-04-01

The climate change modeling activities within the WASCAL program (West African Science Service Center on Climate Change and Adapted Land Use) concentrate on the provisioning of future climate change scenario data at high spatial and temporal resolution and quality in West Africa. Such information is highly required for impact studies in water resources and agriculture for the development of reliable climate change adaptation and mitigation strategies. In this study, we present a detailed evaluation of high simulation runs based on the regional climate model, COSMO model in CLimate Mode (COSMO-CLM). The model is applied over West Africa in a nested approach with two simulation domains at 0.44° and 0.11° resolution using reanalysis data from ERA-Interim (1979-2013). The models runs are compared to several state-of-the-art observational references (e.g., CRU, CHIRPS) including daily precipitation data provided by national meteorological services in West Africa. Special attention is paid to the reproduction of the dynamics of the West African Monsoon (WMA), its associated precipitation patterns and crucial agro-climatological indices such as the onset of the rainy season. In addition, first outcomes of the regional climate change simulations driven by MPI-ESM-LR are presented for a historical period (1980 to 2010) and two future periods (2020 to 2050, 2070 to 2100). The evaluation of the reanalysis runs shows that COSMO-CLM is able to reproduce the observed major climate characteristics including the West African Monsoon within the range of comparable RCM evaluations studies. However, substantial uncertainties remain, especially in the Sahel zone. The added value of the higher resolution of the nested run is reflected in a smaller bias in extreme precipitation statistics with respect to the reference data.

A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios.

PubMed

Chen, Min; Melaas, Eli K; Gray, Josh M; Friedl, Mark A; Richardson, Andrew D

2016-11-01

A spring phenology model that combines photoperiod with accumulated heating and chilling to predict spring leaf-out dates is optimized using PhenoCam observations and coupled into the Community Land Model (CLM) 4.5. In head-to-head comparison (using satellite data from 2003 to 2013 for validation) for model grid cells over the Northern Hemisphere deciduous broadleaf forests (5.5 million km 2 ), we found that the revised model substantially outperformed the standard CLM seasonal-deciduous spring phenology submodel at both coarse (0.9 × 1.25°) and fine (1 km) scales. The revised model also does a better job of representing recent (decadal) phenological trends observed globally by MODIS, as well as long-term trends (1950-2014) in the PEP725 European phenology dataset. Moreover, forward model runs suggested a stronger advancement (up to 11 days) of spring leaf-out by the end of the 21st century for the revised model. Trends toward earlier advancement are predicted for deciduous forests across the whole Northern Hemisphere boreal and temperate deciduous forest region for the revised model, whereas the standard model predicts earlier leaf-out in colder regions, but later leaf-out in warmer regions, and no trend globally. The earlier spring leaf-out predicted by the revised model resulted in enhanced gross primary production (up to 0.6 Pg C yr -1 ) and evapotranspiration (up to 24 mm yr -1 ) when results were integrated across the study region. These results suggest that the standard seasonal-deciduous submodel in CLM should be reconsidered, otherwise substantial errors in predictions of key land-atmosphere interactions and feedbacks may result. © 2016 John Wiley & Sons Ltd.

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.; Berg, Larry K.; Qian, Yun; Guenther, Alex; Gu, Dasa; Shrivastava, Manish; Liu, Ying; Walters, Stacy; Pfister, Gabriele; Jin, Jiming; Shilling, John E.; Warneke, Carsten

2016-05-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

Modeling the impact of agricultural land use and management on US carbon budgets

DOE PAGES

Drewniak, B. A.; Mishra, U.; Song, J.; ...

2014-09-22

Cultivation of the terrestrial land surface can create either a source or sink of atmospheric CO 2, depending on land management practices. The Community Land Model (CLM) provides a useful tool to explore how land use and management impact the soil carbon pool at regional to global scales. CLM was recently updated to include representation of managed lands growing maize, soybean, and spring wheat. In this study, CLM-Crop is used to investigate the impacts of various management practices, including fertilizer use and differential rates of crop residue removal, on the soil organic carbon (SOC) storage of croplands in the continentalmore » United States over approximately a 170 year period. Results indicate that total US SOC stocks have already lost over 8 Pg C (10%) due to land cultivation practices (e.g., fertilizer application, cultivar choice, and residue removal), compared to a land surface composed of native vegetation (i.e., grasslands). After long periods of cultivation, individual plots growing maize and soybean lost up to 65% of the carbon stored, compared to a grassland site. Crop residue management showed the greatest effect on soil carbon storage, with low and medium residue returns resulting in additional losses of 5% and 3.5%, respectively, in US carbon storage, while plots with high residue returns stored 2% more carbon. Nitrogenous fertilizer can alter the amount of soil carbon stocks significantly. Under current levels of crop residue return, not applying fertilizer resulted in a 5% loss of soil carbon. Our simulations indicate that disturbance through cultivation will always result in a loss of soil carbon, and management practices will have a large influence on the magnitude of SOC loss.« less

Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

NASA Astrophysics Data System (ADS)

Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

2015-12-01

Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

Simulating Canopy-Level Solar Induced Fluorescence with CLM-SIF 4.5 at a Sub-Alpine Conifer Forest in the Colorado Rockies

NASA Astrophysics Data System (ADS)

Raczka, B. M.; Bowling, D. R.; Lin, J. C.; Lee, J. E.; Yang, X.; Duarte, H.; Zuromski, L.

2017-12-01

Forests of the Western United States are prone to drought, temperature extremes, forest fires and insect infestation. These disturbance render carbon stocks and land-atmosphere carbon exchanges highly variable and vulnerable to change. Regional estimates of carbon exchange from terrestrial ecosystem models are challenged, in part, by a lack of net ecosystem exchange observations (e.g. flux towers) due to the complex mountainous terrain. Alternatively, carbon estimates based on light use efficiency models that depend upon remotely-sensed greenness indices are challenged due to a weak relationship with GPP during the winter season. Recent advances in the retrieval of remotely sensed solar induced fluorescence (SIF) have demonstrated a strong seasonal relationship between GPP and SIF for deciduous, grass and, to a lesser extent, conifer species. This provides an important opportunity to use remotely-sensed SIF to calibrate terrestrial ecosystem models providing a more accurate regional representation of biomass and carbon exchange across mountainous terrain. Here we incorporate both leaf-level fluorescence and leaf-to-canopy radiative transfer represented by the SCOPE model into CLM 4.5 (CLM-SIF). We simulate canopy level fluorescence at a sub-alpine forest site (Niwot Ridge, Colorado) and test whether these simulations reproduce remotely-sensed SIF from a satellite (GOME2). We found that the average peak SIF during the growing season (yrs 2007-2013) was similar between the model and satellite observations (within 15%); however, simulated SIF during the winter season was significantly greater than the satellite observations (5x higher). This implies that the fluorescence yield is overestimated by the model during the winter season. It is important that the modeled representation of seasonal fluorescence yield is improved to provide an accurate seasonal representation of SIF across the Western United States.

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

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model withmore » chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.« less

Antidepressants and mood stabilizers effects on histone deacetylase expression in C57BL/6 mice: Brain region specific changes.

PubMed

Ookubo, Masanori; Kanai, Hirohiko; Aoki, Harusuke; Yamada, Naoto

2013-09-01

To determine whether treatment with various antidepressants or mood stabilizers leads to region-specific changes, we investigated the effects of their subchronic (14 days of intraperitoneal injection) administration on the tissue concentration of monoamines, dopamine, serotonin, and norepinephrine, and the protein expression of acetylated histone H3 (AcH3) and histone deacetylases (HDACs) in the mouse striatum (ST), nucleus accumbens (Acb), hippocampus (Hip), cingulate cortex (Cg), and amygdala (Amy). Subchronic administration with the antidepressants (S)-citalopram oxalate (ECM), duloxetine hydrochloride (DLX), and mirtazapine (MIR) commonly induced significant increases in dopamine and serotonin levels in the ST and Cg. By contrast, no common profiles for dopamine, serotonin, or norepinephrine were identified in the Acb, Hip, or Amy. Treatment with sodium valproate (VPA), lithium chloride (Li), lamotrigine (LTG), levetiracetam (LTM), olanzapine (OLZ), clozapine (CLZ), clomipramine (CLM), ECM, and DLX induced significant increases in AcH3 expression in the Acb, while treatment with CLM, ECM, DLX, MIR, carbamazepine (CBZ), LTG, LTM, OLZ, or CLZ induced significant increases in HDAC2 and HDAC3 in the ST. CLM, MIR, VPA, CBZ, LTG, LTM, OLZ, or CLZ induced significant increases in HDAC3 in the Cg, and ECM, DLX, MIR, VPA, CBZ, LTG, LTM, or OLZ resulted in significant increases in HDAC5 in the Amy. Collectively, the changes of monoamine content were restricted for mood stabilizer effects, but increased expression of HDAC2, HDAC3, or HDAC5 in the ST, Cg, or Amy was often found, supporting the possibility that antidepressant-like effects involve epigenetic modifications associated with changes in HDAC expression. Copyright © 2013 Elsevier Ltd. All rights reserved.

Modeling the Effects of Groundwater-fed Irrigation on Terrestrial Hydrology over the Conterminous United States

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

Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong

2014-06-01

Human alteration of the land surface hydrologic cycle is substantial. Recent studies suggest that local water management practices including groundwater pumping and irrigation could significantly alter the quantity and distribution of water in the terrestrial system, with potential impacts on weather and climate through land-atmosphere feedbacks. In this study, we incorporated a groundwater withdrawal scheme into the Community Land Model version 4 (CLM4). To simulate the impact of irrigation realistically, we calibrated the CLM4 simulated irrigation amount against observations from agriculture census at the county scale over the conterminous United States (CONUS). The water used for irrigation was then removedmore » from the surface runoff and groundwater aquifer according to a ratio determined from the county-level agricultural census data. Based on the simulations, the impact of groundwater withdrawals for irrigation on land surface and subsurface fluxes were investigated. Our results suggest that the impacts of irrigation on latent heat flux and potential recharge when water is withdrawn from surface water alone or from both surface and groundwater are comparable and local to the irrigation areas. However, when water is withdrawn from groundwater for irrigation, greater effects on the subsurface water balance were found, leading to significant depletion of groundwater storage in regions with low recharge rate and high groundwater exploitation rate. Our results underscore the importance of local hydrologic feedbacks in governing hydrologic response to anthropogenic change in CLM4 and the need to more realistically simulate the two-way interactions among surface water, groundwater, and atmosphere to better understand the impacts of groundwater pumping on irrigation efficiency and climate.« less

Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

NASA Astrophysics Data System (ADS)

Fu, Congsheng; Wang, Guiling; Goulden, Michael L.; Scott, Russell L.; Bible, Kenneth; Cardon, Zoe G.

2016-05-01

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site comparisons for contrasting climate regimes and multiple vegetation types via the integration of measurement and modeling. Here, we incorporated the HR scheme of Ryel et al. (2002) into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture the magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on land surface water and energy budgets, and to explore how the impact may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites with contrasting climate regimes and multiple vegetation types were studied, including the Wind River Crane site in Washington State, the Santa Rita Mesquite savanna site in southern Arizona, and six sites along the Southern California Climate Gradient. HR flux, evapotranspiration (ET), and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement matches of evapotranspiration, Bowen ratio, and soil moisture particularly during dry seasons. Our results also reveal that HR has important hydrological impact in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.

Constraints on Nitrous Oxide emissions within the US Corn Belt using tall tower observations and an Eulerian Modeling Approach

NASA Astrophysics Data System (ADS)

Chen, Z.; Griffis, T. J.; Lee, X.; Fu, C.; Dlugokencky, E. J.; Andrews, A. E.

2017-12-01

Mitigation of nitrous oxide (N2O) emissions requires a sound understanding of N2O production processes and a robust estimate of N2O budgets. It is critical to understand how emissions vary spatially and temporally, and how they are likely to change given future climate and land management decisions. To address these challenges we have coupled two models including WRF-Chem version 3.8.1 and CLM-GBC-CROP version 4.5 to simulate retrospective and future N2O emissions for the US Corn Belt. Using 7 years (2010-2016) of N2O mixing ratio data from 6 tall tower sites within the US Midwest, we ran the coupled model at a spatial resolution of 0.125o× 0.125o and tested and optimized the simulation of N2O emissions at hourly, seasonal, and inter-annual timescales. Our preliminary results indicate:1) The simulated tall tower mixing ratios for 6 tall towers were all significantly higher than the observations in the growing seasons, indicating a high bias of N2O emissions when using the default N2O production mechanisms in CLM. 2) Following the optimization of N2O production in CLM, the simulated tall tower mixing ratios were strongly correlated with the KCMP and WBI towers, and had moderate correlation with the BAO tower. Overall, the absolute biases in mixing ratios were relatively small. Our next step is to examine 7 years of simulations to assess the spatiotemporal variations of direct and indirect emissions within the US Corn Belt to help identify potential N2O hotspots and hot moments.

Constraining Earth System Models in the Tropics with Multiple Satellite Observations

NASA Astrophysics Data System (ADS)

Shi, M.; Liu, J.; Saatchi, S. S.; Chan, S.; Yu, Y.; Zhao, M.

2016-12-01

Because of the impacts of cloud and atmospheric aerosol on spectral observations and the saturation of spectral observations over dense forests, the current spectral observations (e.g., Moderate Resolution Imaging Spectroradiometer) have large uncertainties in the tropics. Nevertheless, the backscatter observations from the SeaWinds Scatterometer onboard QuikSCAT (QSCAT) are sensitive to the variations of canopy water content and structure of forest canopy, and are not affected by clouds and atmospheric aerosols. In addition, the lack of sensitivity of the Soil Moisture Active Passive (SMAP) Level 1C brightness temperature (TB) to soil moisture under dense forest canopies (e.g., forests in tropics) makes the SMAP TB data a direct indicator of canopy properties. In this study, we use a variety of new satellite observations, including the QSCAT backscatter observations, the Gravity Recovery and Climate Experiment (GRACE) satellite's observed temporal gravity field variations, and the SMAP Level 1C TB, to constrain the carbon (C) cycle simulated by the Community Land Model version 4.5 BGC (CLM4.5) for the 2005 Amazonia drought and 2015 El Nino. Our results show that the leaf C pool size simulated by CLM4.5 decreases dramatically in southwest Amazonia in the 2005 drought, and recovers slowly afterward (after about 3 years). This result is consistent with the long-term C-recovery after the 2005 Amazonia drought observed by QSCAT. The slow C pool recovery is associated with large fire disturbance and the slow water storage recovery simulated by CLM4.5 and observed by GRACE. We will also discuss the impact of the 2015 El Nino on the tropical C dynamics constrained by SMAP Level 1C data. This study represents an innovative way of using satellite microwave observations to constrain C cycle in an Earth system model.

RAS mutations predict radiologic and pathologic response in patients treated with chemotherapy prior to resection of colorectal liver metastases

PubMed Central

Mise, Yoshihiro; Kopetz, Scott; Loyer, Evelyne M.; Andreou, Andreas; Cooper, Amanda B.; Kaur, Harmeet; Aloia, Thomas A.; Maru, Dipen M.; Vauthey, Jean-Nicolas

2014-01-01

Purpose RAS mutations have been reported to be a potential prognostic factor in patients with colorectal liver metastases (CLM). However, the impact of RAS mutations on response to chemotherapy remains unclear. We sought to determine the association between RAS mutations and response to preoperative chemotherapy and their impact on survival in patients undergoing curative resection of CLM. Methods RAS mutational status was assessed and its relation to morphologic response and pathologic response was investigated in 184 patients meeting inclusion criteria. Predictors of survival were assessed. The prognostic impact of RAS mutational status was then analyzed using two different multivariate models including either radiologic morphologic response (model 1) or pathologic response (model 2). Results Optimal morphologic response and major pathologic response were more common in patients with wild-type RAS (32.9% and 58.9%, respectively) than in patients with RAS mutations (10.5% and 36.8%; P =.006 and .015, respectively). Multivariate analysis confirmed that wild-type RAS was a strong predictor of optimal morphologic response (odds ratio [OR], 4.38; 95% CI, 1.45-13.2) and major pathologic response (OR,2.79; 95% CI, 1.29-6.04). RAS mutations were independently correlated with both overall survival and recurrence free-survival (hazard ratios, 3.25 and 2.02, respectively, in model 1, and 3.19 and 2.23, respectively, in model 2). Subanalysis revealed that RAS mutational status clearly stratified prognosis in patients with inadequate response to preoperative chemotherapy. Conclusion RAS mutational status can be used to complement the current prognostic indicators for patients undergoing curative resection of CLM after preoperative modern chemotherapy. PMID:25227306

RAS mutations predict radiologic and pathologic response in patients treated with chemotherapy before resection of colorectal liver metastases.

PubMed

Zimmitti, Giuseppe; Shindoh, Junichi; Mise, Yoshihiro; Kopetz, Scott; Loyer, Evelyne M; Andreou, Andreas; Cooper, Amanda B; Kaur, Harmeet; Aloia, Thomas A; Maru, Dipen M; Vauthey, Jean-Nicolas

2015-03-01

RAS mutations have been reported to be a potential prognostic factor in patients with colorectal liver metastases (CLM). However, the impact of RAS mutations on response to chemotherapy remains unclear. The purpose of this study was to investigate the correlation between RAS mutations and response to preoperative chemotherapy and their impact on survival in patients undergoing curative resection of CLM. RAS mutational status was assessed and its relation to morphologic response and pathologic response was investigated in 184 patients meeting inclusion criteria. Predictors of survival were assessed. The prognostic impact of RAS mutational status was then analyzed using two different multivariate models, including either radiologic morphologic response (model 1) or pathologic response (model 2). Optimal morphologic response and major pathologic response were more common in patients with wild-type RAS (32.9 and 58.9%, respectively) than in patients with RAS mutations (10.5 and 36.8%; P = 0.006 and 0.015, respectively). Multivariate analysis confirmed that wild-type RAS was a strong predictor of optimal morphologic response [odds ratio (OR), 4.38; 95% CI 1.45-13.15] and major pathologic response (OR, 2.61; 95% CI 1.17-5.80). RAS mutations were independently correlated with both overall survival and recurrence free-survival (hazard ratios, 3.57 and 2.30, respectively, in model 1, and 3.19 and 2.09, respectively, in model 2). Subanalysis revealed that RAS mutational status clearly stratified survival in patients with inadequate response to preoperative chemotherapy. RAS mutational status can be used to complement the current prognostic indicators for patients undergoing curative resection of CLM after preoperative modern chemotherapy.

A Comparison of Internal Dispositions and Career Trajectories after Collaborative versus Apprenticed Research Experiences for Undergraduates.

PubMed

Frantz, Kyle J; Demetrikopoulos, Melissa K; Britner, Shari L; Carruth, Laura L; Williams, Brian A; Pecore, John L; DeHaan, Robert L; Goode, Christopher T

2017-01-01

Undergraduate research experiences confer benefits on students bound for science, technology, engineering, and mathematics (STEM) careers, but the low number of research professionals available to serve as mentors often limits access to research. Within the context of our summer research program (BRAIN), we tested the hypothesis that a team-based collaborative learning model (CLM) produces student outcomes at least as positive as a traditional apprenticeship model (AM). Through stratified, random assignment to conditions, CLM students were designated to work together in a teaching laboratory to conduct research according to a defined curriculum led by several instructors, whereas AM students were paired with mentors in active research groups. We used pre-, mid-, and postprogram surveys to measure internal dispositions reported to predict progress toward STEM careers, such as scientific research self-efficacy, science identity, science anxiety, and commitment to a science career. We are also tracking long-term retention in science-related career paths. For both short- and longer-term outcomes, the two program formats produced similar benefits, supporting our hypothesis that the CLM provides positive outcomes while conserving resources, such as faculty mentors. We discuss this method in comparison with course-based undergraduate research and recommend its expansion to institutional settings in which mentor resources are scarce. © 2017 K. J. Frantz et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Modeling the impact of agricultural land use and management on US carbon budgets

DOE PAGES

Drewniak, B. A.; Mishra, U.; Song, J.; ...

2015-04-09

Cultivation of the terrestrial land surface can create either a source or sink of atmospheric CO₂, depending on land management practices. The Community Land Model (CLM) provides a useful tool for exploring how land use and management impact the soil carbon pool at regional to global scales. CLM was recently updated to include representation of managed lands growing maize, soybean, and spring wheat. In this study, CLM-Crop is used to investigate the impacts of various management practices, including fertilizer use and differential rates of crop residue removal, on the soil organic carbon (SOC) storage of croplands in the continental Unitedmore » States over approximately a 170-year period. Results indicate that total US SOC stocks have already lost over 8 Pg C (10%) due to land cultivation practices (e.g., fertilizer application, cultivar choice, and residue removal), compared to a land surface composed of native vegetation (i.e., grasslands). After long periods of cultivation, individual subgrids (the equivalent of a field plot) growing maize and soybean lost up to 65% of the carbon stored compared to a grassland site. Crop residue management showed the greatest effect on soil carbon storage, with low and medium residue returns resulting in additional losses of 5 and 3.5%, respectively, in US carbon storage, while plots with high residue returns stored 2% more carbon. Nitrogenous fertilizer can alter the amount of soil carbon stocks significantly. Under current levels of crop residue return, not applying fertilizer resulted in a 5% loss of soil carbon. Our simulations indicate that disturbance through cultivation will always result in a loss of soil carbon, and management practices will have a large influence on the magnitude of SOC loss.« less

Chemical treatment of wastewater from flue gas desulphurisation

NASA Astrophysics Data System (ADS)

Pasiecznik, Iwona; Szczepaniak, Włodzimierz

2017-11-01

The article presents results of laboratory tests of removing boron and arsenium from non-ideal solutions using double-layered magnesium/aluminium hydroxides (Mg/Al Double-Layered Hydroxide - DLH) produced with nitrate-chloride method. In research, wastewater from an installation for flue gas desulfurization was examined. Double-layered hydroxides are perfect absorbents for anionic compounds. The research proved high effectiveness of preparation with reference to arsenium, as well as confirmed the effect of presence of sulfatic and arsenate ions on the effectiveness of boron removal. On the basis of research on absorption kinetics a theoretical dose of DLH/NO3-Cl/M preparation was calculated and compared with a dose that ensures emimination of boron below the limit standarized by the national regulations. Application of double-layered magnesium/aluminium hydroxides for boron elimination from industrial wastewater requires significantly higher doses of preparation than those calculated in model investigations. It is due to the priority of removal of multivalent ions, such as sulfatic, arsenate or phosphate ions, by DLH/NO3-Cl/M.

Solar Heating And Cooling Of Buildings (SHACOB): Requirements definition and impact analysis-2. Volume 3: Customer load management systems

NASA Astrophysics Data System (ADS)

Cretcher, C. K.; Rountredd, R. C.

1980-11-01

Customer Load Management Systems, using off-peak storage and control at the residences, are analyzed to determine their potential for capacity and energy savings by the electric utility. Areas broadly representative of utilities in the regions around Washington, DC and Albuquerque, NM were of interest. Near optimum tank volumes were determined for both service areas, and charging duration/off-time were identified as having the greatest influence on tank performance. The impacts on utility operations and corresponding utility/customer economics were determined in terms of delta demands used to estimate the utilities' generating capacity differences between the conventional load management, (CLM) direct solar with load management (DSLM), and electric resistive systems. Energy differences are also determined. These capacity and energy deltas are translated into changes in utility costs due to penetration of the CLM or DSLM systems into electric resistive markets in the snapshot years of 1990 and 2000.

Complex Langevin analysis of the spontaneous symmetry breaking in dimensionally reduced super Yang-Mills models

NASA Astrophysics Data System (ADS)

Anagnostopoulos, Konstantinos N.; Azuma, Takehiro; Ito, Yuta; Nishimura, Jun; Papadoudis, Stratos Kovalkov

2018-02-01

In recent years the complex Langevin method (CLM) has proven a powerful method in studying statistical systems which suffer from the sign problem. Here we show that it can also be applied to an important problem concerning why we live in four-dimensional spacetime. Our target system is the type IIB matrix model, which is conjectured to be a nonperturbative definition of type IIB superstring theory in ten dimensions. The fermion determinant of the model becomes complex upon Euclideanization, which causes a severe sign problem in its Monte Carlo studies. It is speculated that the phase of the fermion determinant actually induces the spontaneous breaking of the SO(10) rotational symmetry, which has direct consequences on the aforementioned question. In this paper, we apply the CLM to the 6D version of the type IIB matrix model and show clear evidence that the SO(6) symmetry is broken down to SO(3). Our results are consistent with those obtained previously by the Gaussian expansion method.

SU-F-T-459: ArcCHECK Machine QA : Highly Efficient Quality Assurance Tool for VMAT, SRS & SBRT Linear Accelerator Delivery

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

Mhatre, V; Patwe, P; Dandekar, P

Purpose: Quality assurance (QA) of complex linear accelerators is critical and highly time consuming. ArcCHECK Machine QA tool is used to test geometric and delivery aspects of linear accelerator. In this study we evaluated the performance of this tool. Methods: Machine QA feature allows user to perform quality assurance tests using ArcCHECK phantom. Following tests were performed 1) Gantry Speed 2) Gantry Rotation 3) Gantry Angle 4)MLC/Collimator QA 5)Beam Profile Flatness & Symmetry. Data was collected on trueBEAM stX machine for 6 MV for a period of one year. The Gantry QA test allows to view errors in gantry angle,more » rotation & assess how accurately the gantry moves around the isocentre. The MLC/Collimator QA tool is used to analyze & locate the differences between leaf bank & jaw position of linac. The flatness & Symmetry test quantifies beam flatness & symmetry in IEC-y & x direction. The Gantry & Flatness/Symmetry test can be performed for static & dynamic delivery. Results: The Gantry speed was 3.9 deg/sec with speed maximum deviation around 0.3 deg/sec. The Gantry Isocentre for arc delivery was 0.9mm & static delivery was 0.4mm. The maximum percent positive & negative difference was found to be 1.9 % & – 0.25 % & maximum distance positive & negative diff was 0.4mm & – 0.3 mm for MLC/Collimator QA. The Flatness for Arc delivery was 1.8 % & Symmetry for Y was 0.8 % & X was 1.8 %. The Flatness for gantry 0°,270°,90° & 180° was 1.75,1.9,1.8 & 1.6% respectively & Symmetry for X & Y was 0.8,0.6% for 0°, 0.6,0.7% for 270°, 0.6,1% for 90° & 0.6,0.7% for 180°. Conclusion: ArcCHECK Machine QA is an useful tool for QA of Modern linear accelerators as it tests both geometric & delivery aspects. This is very important for VMAT, SRS & SBRT treatments.« less

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

Methods, systems and apparatus for adjusting modulation index to improve linearity of phase voltage commands

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

Gallegos-Lopez, Gabriel; Perisic, Milun; Kinoshita, Michael H.

2017-03-14

Embodiments of the present invention relate to methods, systems and apparatus for controlling operation of a multi-phase machine in a motor drive system. The disclosed embodiments provide a mechanism for adjusting modulation index of voltage commands to improve linearity of the voltage commands.

Optical Coherence Tomography Machine Learning Classifiers for Glaucoma Detection: A Preliminary Study

PubMed Central

Burgansky-Eliash, Zvia; Wollstein, Gadi; Chu, Tianjiao; Ramsey, Joseph D.; Glymour, Clark; Noecker, Robert J.; Ishikawa, Hiroshi; Schuman, Joel S.

2007-01-01

Purpose Machine-learning classifiers are trained computerized systems with the ability to detect the relationship between multiple input parameters and a diagnosis. The present study investigated whether the use of machine-learning classifiers improves optical coherence tomography (OCT) glaucoma detection. Methods Forty-seven patients with glaucoma (47 eyes) and 42 healthy subjects (42 eyes) were included in this cross-sectional study. Of the glaucoma patients, 27 had early disease (visual field mean deviation [MD] ≥ −6 dB) and 20 had advanced glaucoma (MD < −6 dB). Machine-learning classifiers were trained to discriminate between glaucomatous and healthy eyes using parameters derived from OCT output. The classifiers were trained with all 38 parameters as well as with only 8 parameters that correlated best with the visual field MD. Five classifiers were tested: linear discriminant analysis, support vector machine, recursive partitioning and regression tree, generalized linear model, and generalized additive model. For the last two classifiers, a backward feature selection was used to find the minimal number of parameters that resulted in the best and most simple prediction. The cross-validated receiver operating characteristic (ROC) curve and accuracies were calculated. Results The largest area under the ROC curve (AROC) for glaucoma detection was achieved with the support vector machine using eight parameters (0.981). The sensitivity at 80% and 95% specificity was 97.9% and 92.5%, respectively. This classifier also performed best when judged by cross-validated accuracy (0.966). The best classification between early glaucoma and advanced glaucoma was obtained with the generalized additive model using only three parameters (AROC = 0.854). Conclusions Automated machine classifiers of OCT data might be useful for enhancing the utility of this technology for detecting glaucomatous abnormality. PMID:16249492

Self-Centering Reciprocating-Permanent-Magnet Machine

NASA Technical Reports Server (NTRS)

Bhate, Suresh; Vitale, Nick

1988-01-01

New design for monocoil reciprocating-permanent-magnet electric machine provides self-centering force. Linear permanent-magnet electrical motor includes outer stator, inner stator, and permanent-magnet plunger oscillateing axially between extreme left and right positions. Magnets arranged to produce centering force and allows use of only one coil of arbitrary axial length. Axial length of coil chosen to provide required efficiency and power output.

Pursuing optimal electric machines transient diagnosis: The adaptive slope transform

NASA Astrophysics Data System (ADS)

Pons-Llinares, Joan; Riera-Guasp, Martín; Antonino-Daviu, Jose A.; Habetler, Thomas G.

2016-12-01

The aim of this paper is to introduce a new linear time-frequency transform to improve the detection of fault components in electric machines transient currents. Linear transforms are analysed from the perspective of the atoms used. A criterion to select the atoms at every point of the time-frequency plane is proposed, taking into account the characteristics of the searched component at each point. This criterion leads to the definition of the Adaptive Slope Transform, which enables a complete and optimal capture of the different components evolutions in a transient current. A comparison with conventional linear transforms (Short-Time Fourier Transform and Wavelet Transform) is carried out, showing their inherent limitations. The approach is tested with laboratory and field motors, and the Lower Sideband Harmonic is captured for the first time during an induction motor startup and subsequent load oscillations, accurately tracking its evolution.

Toward an Improvement of the Analysis of Neural Coding.

PubMed

Alegre-Cortés, Javier; Soto-Sánchez, Cristina; Albarracín, Ana L; Farfán, Fernando D; Val-Calvo, Mikel; Ferrandez, José M; Fernandez, Eduardo

2017-01-01

Machine learning and artificial intelligence have strong roots on principles of neural computation. Some examples are the structure of the first perceptron, inspired in the retina, neuroprosthetics based on ganglion cell recordings or Hopfield networks. In addition, machine learning provides a powerful set of tools to analyze neural data, which has already proved its efficacy in so distant fields of research as speech recognition, behavioral states classification, or LFP recordings. However, despite the huge technological advances in neural data reduction of dimensionality, pattern selection, and clustering during the last years, there has not been a proportional development of the analytical tools used for Time-Frequency (T-F) analysis in neuroscience. Bearing this in mind, we introduce the convenience of using non-linear, non-stationary tools, EMD algorithms in particular, for the transformation of the oscillatory neural data (EEG, EMG, spike oscillations…) into the T-F domain prior to its analysis with machine learning tools. We support that to achieve meaningful conclusions, the transformed data we analyze has to be as faithful as possible to the original recording, so that the transformations forced into the data due to restrictions in the T-F computation are not extended to the results of the machine learning analysis. Moreover, bioinspired computation such as brain-machine interface may be enriched from a more precise definition of neuronal coding where non-linearities of the neuronal dynamics are considered.

Performance of Ti-multilayer coated tool during machining of MDN431 alloyed steel

NASA Astrophysics Data System (ADS)

Badiger, Pradeep V.; Desai, Vijay; Ramesh, M. R.

2018-04-01

Turbine forgings and other components are required to be high resistance to corrosion and oxidation because which they are highly alloyed with Ni and Cr. Midhani manufactures one of such material MDN431. It's a hard-to-machine steel with high hardness and strength. PVD coated insert provide an answer to problem with its state of art technique on the WC tool. Machinability studies is carried out on MDN431 steel using uncoated and Ti-multilayer coated WC tool insert using Taguchi optimisation technique. During the present investigation, speed (398-625rpm), feed (0.093-0.175mm/rev), and depth of cut (0.2-0.4mm) varied according to Taguchi L9 orthogonal array, subsequently cutting forces and surface roughness (Ra) were measured. Optimizations of the obtained results are done using Taguchi technique for cutting forces and surface roughness. Using Taguchi technique linear fit model regression analysis carried out for the combination of each input variable. Experimented results are compared and found the developed model is adequate which supported by proof trials. Speed, feed and depth of cut are linearly dependent on the cutting force and surface roughness for uncoated insert whereas Speed and depth of cut feed is inversely dependent in coated insert for both cutting force and surface roughness. Machined surface for coated and uncoated inserts during machining of MDN431 is studied using optical profilometer.

Energy landscapes for machine learning

NASA Astrophysics Data System (ADS)

Ballard, Andrew J.; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D.; Wales, David J.

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

Regional impacts of Atlantic Forest deforestation on climate and vegetation dynamics

NASA Astrophysics Data System (ADS)

Holm, J. A.; Chambers, J. Q.

2012-12-01

The Brazilian Atlantic Forest was a large and important forest due to its high biodiversity, endemism, range in climate, and complex geography. The original Atlantic Forest was estimated to cover 150 million hectares, spanning large latitudinal, longitudinal, and elevation gradients. This unique environment helped contribute to a diverse assemblage of plants, mammals, birds, and reptiles. Unfortunately, due to land conversion into agriculture, pasture, urban areas, and increased forest fragmentation, only ~8-10% of the original Atlantic Forest remains. Tropical deforestation in the Americas can have considerable effects on local to global climates, and surrounding vegetation growth and survival. This study uses a fully coupled, global climate model (Community Earth System Model, CESM v.1.0.1) to simulate the full removal of the historical Atlantic Forest, and evaluate the regional climatic and vegetation responses due to deforestation. We used the fully coupled atmosphere and land surface components in CESM, and a partially interacting ocean component. The vegetated grid cell portion of the land surface component, the Community Landscape Model (CLM), is divided into 4 of 16 plant functional types (PFTs) with vertical layers of canopy, leaf area index, soil physical properties, and interacting hydrological features all tracking energy, water, and carbon state and flux variables, making CLM highly capable in predicting the complex nature and outcomes of large-scale deforestation. The Atlantic Forest removal (i.e. deforestation) was conducted my converting all woody stem PFTs to grasses in CLM, creating a land-use change from forest to pasture. By comparing the simulated historical Atlantic Forest (pre human alteration) to a deforested Atlantic Forest (close to current conditions) in CLM and CESM we found that live stem carbon, NPP (gC m-2 yr-1), and other vegetation dynamics inside and outside the Atlantic Forest region were largely altered. In addition to vegetation effects, regional surface air temperature (C°), precipitation (mm day-1), and emitted longwave radiation (W m-2) were highly affected in the location of the removed forest, and throughout surrounding areas of South America. For example climate patterns of increased temperature and decreased precipitation were affected as far as the Amazon Forest region. The use of fully coupled global climate and terrestrial models to study the effects of large-scale forest removal have been rarely applied. This study successfully showed the valuation of an important tropical forest, and the consequences of large deforestation through the reporting of complex earth-atmosphere interactions between vegetation dynamics and climate.

An observational constraint on stomatal function in forests: evaluating coupled carbon and water vapor exchange with carbon isotopes in the Community Land Model (CLM4.5)

NASA Astrophysics Data System (ADS)

Raczka, Brett; Duarte, Henrique F.; Koven, Charles D.; Ricciuto, Daniel; Thornton, Peter E.; Lin, John C.; Bowling, David R.

2016-09-01

Land surface models are useful tools to quantify contemporary and future climate impact on terrestrial carbon cycle processes, provided they can be appropriately constrained and tested with observations. Stable carbon isotopes of CO2 offer the potential to improve model representation of the coupled carbon and water cycles because they are strongly influenced by stomatal function. Recently, a representation of stable carbon isotope discrimination was incorporated into the Community Land Model component of the Community Earth System Model. Here, we tested the model's capability to simulate whole-forest isotope discrimination in a subalpine conifer forest at Niwot Ridge, Colorado, USA. We distinguished between isotopic behavior in response to a decrease of δ13C within atmospheric CO2 (Suess effect) vs. photosynthetic discrimination (Δcanopy), by creating a site-customized atmospheric CO2 and δ13C of CO2 time series. We implemented a seasonally varying Vcmax model calibration that best matched site observations of net CO2 carbon exchange, latent heat exchange, and biomass. The model accurately simulated observed δ13C of needle and stem tissue, but underestimated the δ13C of bulk soil carbon by 1-2 ‰. The model overestimated the multiyear (2006-2012) average Δcanopy relative to prior data-based estimates by 2-4 ‰. The amplitude of the average seasonal cycle of Δcanopy (i.e., higher in spring/fall as compared to summer) was correctly modeled but only when using a revised, fully coupled An - gs (net assimilation rate, stomatal conductance) version of the model in contrast to the partially coupled An - gs version used in the default model. The model attributed most of the seasonal variation in discrimination to An, whereas interannual variation in simulated Δcanopy during the summer months was driven by stomatal response to vapor pressure deficit (VPD). The model simulated a 10 % increase in both photosynthetic discrimination and water-use efficiency (WUE) since 1850 which is counter to established relationships between discrimination and WUE. The isotope observations used here to constrain CLM suggest (1) the model overestimated stomatal conductance and (2) the default CLM approach to representing nitrogen limitation (partially coupled model) was not capable of reproducing observed trends in discrimination. These findings demonstrate that isotope observations can provide important information related to stomatal function driven by environmental stress from VPD and nitrogen limitation. Future versions of CLM that incorporate carbon isotope discrimination are likely to benefit from explicit inclusion of mesophyll conductance.

Evaluating litter decomposition and soil organic matter dynamics in earth system models: contrasting analysis of long-term litter decomposition and steady-state soil carbon

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Wieder, W. R.

2012-12-01

Decomposition is a large term in the global carbon budget, but models of the earth system that simulate carbon cycle-climate feedbacks are largely untested with respect to litter decomposition. Here, we demonstrate a protocol to document model performance with respect to both long-term (10 year) litter decomposition and steady-state soil carbon stocks. First, we test the soil organic matter parameterization of the Community Land Model version 4 (CLM4), the terrestrial component of the Community Earth System Model, with data from the Long-term Intersite Decomposition Experiment Team (LIDET). The LIDET dataset is a 10-year study of litter decomposition at multiple sites across North America and Central America. We show results for 10-year litter decomposition simulations compared with LIDET for 9 litter types and 20 sites in tundra, grassland, and boreal, conifer, deciduous, and tropical forest biomes. We show additional simulations with DAYCENT, a version of the CENTURY model, to ask how well an established ecosystem model matches the observations. The results reveal large discrepancy between the laboratory microcosm studies used to parameterize the CLM4 litter decomposition and the LIDET field study. Simulated carbon loss is more rapid than the observations across all sites, despite using the LIDET-provided climatic decomposition index to constrain temperature and moisture effects on decomposition. Nitrogen immobilization is similarly biased high. Closer agreement with the observations requires much lower decomposition rates, obtained with the assumption that nitrogen severely limits decomposition. DAYCENT better replicates the observations, for both carbon mass remaining and nitrogen, without requirement for nitrogen limitation of decomposition. Second, we compare global observationally-based datasets of soil carbon with simulated steady-state soil carbon stocks for both models. The models simulations were forced with observationally-based estimates of annual litterfall and model-derived climatic decomposition index. While comparison with the LIDET 10-year litterbag study reveals sharp contrasts between CLM4 and DAYCENT, simulations of steady-state soil carbon show less difference between models. Both CLM4 and DAYCENT significantly underestimate soil carbon. Sensitivity analyses highlight causes of the low soil carbon bias. The terrestrial biogeochemistry of earth system models must be critically tested with observations, and the consequences of particular model choices must be documented. Long-term litter decomposition experiments such as LIDET provide a real-world process-oriented benchmark to evaluate models and can critically inform model development. Analysis of steady-state soil carbon estimates reveal additional, but here different, inferences about model performance.

Black carbon and trace gases over South Asia: Measurements and Regional Climate model simulations

NASA Astrophysics Data System (ADS)

Bhuyan, Pradip; Pathak, Binita; Parottil, Ajay

2016-07-01

Trace gases and aerosols are simulated with 50 km spatial resolution over South Asian CORDEX domain enclosing the Indian sub-continent and North-East India for the year 2012 using two regional climate models RegCM4 coupled with CLM4.5 and WRF-Chem 3.5. Both models are found to capture the seasonality in the simulated O3 and its precursors, NOx and CO and black carbon concentrations together with the meteorological variables over the Indian Subcontinent as well as over the sub-Himalayan North-Eastern region of India including Bangladesh. The model simulations are compared with the measurements made at Dibrugarh (27.3°N, 94.6°E, 111 m amsl). Both the models are found to capture the observed diurnal and seasonal variations in O3 concentrations with maximum in spring and minimum in monsoon, the correlation being better for WRF-Chem (R~0.77) than RegCM (R~0.54). Simulated NOx and CO is underestimated in all the seasons by both the models, the performance being better in the case of WRF-Chem. The observed difference may be contributed by the bias in the estimation of the O3 precursors NOx and CO in the emission inventories or the error in the simulation of the meteorological variables which influences O3 concentration in both the models. For example, in the pre-monsoon and winter season, the WRF-Chem model simulated shortwave flux overestimates the observation by ~500 Wm-2 while in the monsoon and post monsoon season, simulated shortwave flux is equivalent to the observation. The model predicts higher wind speed in all the seasons especially during night-time. In the post-monsoon and winter season, the simulated wind pattern is reverse to observation with daytime low and night-time high values. Rainfall is overestimated in all the seasons. RegCM-CLM4.5 is found to underestimate rainfall and other meteorological parameters. The WRF-Chem model closely captured the observed values of black carbon mass concentrations during pre-monsoon and summer monsoon seasons, but deviated significantly during the winter season. On the other hand RegCM-CLM4.5 underestimates BC throughout the year. This may be attributed to the inaccuracy in the emission inventories, where the small scale local burnings those generating black carbon over this region is not accounted for either by the satellite (due to detection limit) as well as in the emission inventories considered in the model. Thus further improvement in the emission inventories is recommended in RegCM-CLM4.5.

Modeling stomatal conductance in the earth system: linking leaf water-use efficiency and water transport along the soil-plant-atmosphere continuum

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Williams, M.; Fisher, R. A.; Oleson, K. W.

2014-09-01

The Ball-Berry stomatal conductance model is commonly used in earth system models to simulate biotic regulation of evapotranspiration. However, the dependence of stomatal conductance (gs) on vapor pressure deficit (Ds) and soil moisture must be empirically parameterized. We evaluated the Ball-Berry model used in the Community Land Model version 4.5 (CLM4.5) and an alternative stomatal conductance model that links leaf gas exchange, plant hydraulic constraints, and the soil-plant-atmosphere continuum (SPA). The SPA model simulates stomatal conductance numerically by (1) optimizing photosynthetic carbon gain per unit water loss while (2) constraining stomatal opening to prevent leaf water potential from dropping below a critical minimum. We evaluated two optimization algorithms: intrinsic water-use efficiency (ΔAn /Δgs, the marginal carbon gain of stomatal opening) and water-use efficiency (ΔAn /ΔEl, the marginal carbon gain of transpiration water loss). We implemented the stomatal models in a multi-layer plant canopy model to resolve profiles of gas exchange, leaf water potential, and plant hydraulics within the canopy, and evaluated the simulations using leaf analyses, eddy covariance fluxes at six forest sites, and parameter sensitivity analyses. The primary differences among stomatal models relate to soil moisture stress and vapor pressure deficit responses. Without soil moisture stress, the performance of the SPA stomatal model was comparable to or slightly better than the CLM Ball-Berry model in flux tower simulations, but was significantly better than the CLM Ball-Berry model when there was soil moisture stress. Functional dependence of gs on soil moisture emerged from water flow along the soil-to-leaf pathway rather than being imposed a priori, as in the CLM Ball-Berry model. Similar functional dependence of gs on Ds emerged from the ΔAn/ΔEl optimization, but not the ΔAn /gs optimization. Two parameters (stomatal efficiency and root hydraulic conductivity) minimized errors with the SPA stomatal model. The critical stomatal efficiency for optimization (ι) gave results consistent with relationships between maximum An and gs seen in leaf trait data sets and is related to the slope (g1) of the Ball-Berry model. Root hydraulic conductivity (Rr*) was consistent with estimates from literature surveys. The two central concepts embodied in the SPA stomatal model, that plants account for both water-use efficiency and for hydraulic safety in regulating stomatal conductance, imply a notion of optimal plant strategies and provide testable model hypotheses, rather than empirical descriptions of plant behavior.

Parallel spatial direct numerical simulations on the Intel iPSC/860 hypercube

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.; Zubair, Mohammad

1993-01-01

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube is documented. The direct numerical simulation approach is used to compute spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows. The feasibility of using the PSDNS on the hypercube to perform transition studies is examined. The results indicate that the direct numerical simulation approach can effectively be parallelized on a distributed-memory parallel machine. By increasing the number of processors nearly ideal linear speedups are achieved with nonoptimized routines; slower than linear speedups are achieved with optimized (machine dependent library) routines. This slower than linear speedup results because the Fast Fourier Transform (FFT) routine dominates the computational cost and because the routine indicates less than ideal speedups. However with the machine-dependent routines the total computational cost decreases by a factor of 4 to 5 compared with standard FORTRAN routines. The computational cost increases linearly with spanwise wall-normal and streamwise grid refinements. The hypercube with 32 processors was estimated to require approximately twice the amount of Cray supercomputer single processor time to complete a comparable simulation; however it is estimated that a subgrid-scale model which reduces the required number of grid points and becomes a large-eddy simulation (PSLES) would reduce the computational cost and memory requirements by a factor of 10 over the PSDNS. This PSLES implementation would enable transition simulations on the hypercube at a reasonable computational cost.

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

Physics with e{sup +}e{sup -} Linear Colliders

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

Barklow, Timothy L

2003-05-05

We describe the physics potential of e{sup +}e{sup -} linear colliders in this report. These machines are planned to operate in the first phase at a center-of-mass energy of 500 GeV, before being scaled up to about 1 TeV. In the second phase of the operation, a final energy of about 2 TeV is expected. The machines will allow us to perform precision tests of the heavy particles in the Standard Model, the top quark and the electroweak bosons. They are ideal facilities for exploring the properties of Higgs particles, in particular in the intermediate mass range. New vector bosonsmore » and novel matter particles in extended gauge theories can be searched for and studied thoroughly. The machines provide unique opportunities for the discovery of particles in supersymmetric extensions of the Standard Model, the spectrum of Higgs particles, the supersymmetric partners of the electroweak gauge and Higgs bosons, and of the matter particles. High precision analyses of their properties and interactions will allow for extrapolations to energy scales close to the Planck scale where gravity becomes significant. In alternative scenarios, like compositeness models, novel matter particles and interactions can be discovered and investigated in the energy range above the existing colliders up to the TeV scale. Whatever scenario is realized in Nature, the discovery potential of e{sup +}e{sup -} linear colliders and the high-precision with which the properties of particles and their interactions can be analyzed, define an exciting physics programme complementary to hadron machines.« less

Turbofan Engine Simulated in a Graphical Simulation Environment

NASA Technical Reports Server (NTRS)

Parker, Khary I.; Guo, Ten-Huei

2004-01-01

Recently, there has been an increase in the development of intelligent engine technology with advanced active component control. The computer engine models used in these control studies are component-level models (CLM), models that link individual component models of state space and nonlinear algebraic equations, written in a computer language such as Fortran. The difficulty faced in performing control studies on Fortran-based models is that Fortran is not supported with control design and analysis tools, so there is no means for implementing real-time control. It is desirable to have a simulation environment that is straightforward, has modular graphical components, and allows easy access to health, control, and engine parameters through a graphical user interface. Such a tool should also provide the ability to convert a control design into real-time code, helping to make it an extremely powerful tool in control and diagnostic system development. Simulation time management is shown: Mach number versus time, power level angle versus time, altitude versus time, ambient temperature change versus time, afterburner fuel flow versus time, controller and actuator dynamics, collect initial conditions, CAD output, and component-level model: CLM sensor, CAD input, and model output. The Controls and Dynamics Technologies Branch at the NASA Glenn Research Center has developed and demonstrated a flexible, generic turbofan engine simulation platform that can meet these objectives, known as the Modular Aero-Propulsion System Simulation (MAPSS). MAPSS is a Simulink-based implementation of a Fortran-based, modern high pressure ratio, dual-spool, low-bypass, military-type variable-cycle engine with a digital controller. Simulink (The Mathworks, Natick, MA) is a computer-aided control design and simulation package allows the graphical representation of dynamic systems in a block diagram form. MAPSS is a nonlinear, non-real-time system composed of controller and actuator dynamics (CAD) and component-level model (CLM) modules. The controller in the CAD module emulates the functionality of a digital controller, which has a typical update rate of 50 Hz. The CLM module simulates the dynamics of the engine components and uses an update rate of 2500 Hz, which is needed to iterate to balance mass and energy among system components. The actuators in the CAD module use the same sampling rate as those in the CLM. Two graphs of normalized spool speed versus time in seconds and one graph of normalized average metal temperature versus time in seconds is shown. MAPSS was validated via open-loop and closed-loop comparisons with the Fortran simulation. The preceding plots show the normalized results of a closed-loop comparison looking at three states of the model: low-pressure spool speed, high-pressure spool speed, and the average metal temperature measured from the combustor to the high-pressure turbine. In steady state, the error between the simulations is less than 1 percent. During a transient, the difference between the simulations is due to a correction in MAPSS that prevents the gas flow in the bypass duct inlet from flowing forward instead of toward the aft end, which occurs in the Fortran simulation. A comparison between MAPSS and the Fortran model of the bypass duct inlet flow for power lever angles greater than 35 degrees is shown.

Fundamental aspects of steady-state conversion of heat to work at the nanoscale

NASA Astrophysics Data System (ADS)

Benenti, Giuliano; Casati, Giulio; Saito, Keiji; Whitney, Robert S.

2017-06-01

In recent years, the study of heat to work conversion has been re-invigorated by nanotechnology. Steady-state devices do this conversion without any macroscopic moving parts, through steady-state flows of microscopic particles such as electrons, photons, phonons, etc. This review aims to introduce some of the theories used to describe these steady-state flows in a variety of mesoscopic or nanoscale systems. These theories are introduced in the context of idealized machines which convert heat into electrical power (heat-engines) or convert electrical power into a heat flow (refrigerators). In this sense, the machines could be categorized as thermoelectrics, although this should be understood to include photovoltaics when the heat source is the sun. As quantum mechanics is important for most such machines, they fall into the field of quantum thermodynamics. In many cases, the machines we consider have few degrees of freedom, however the reservoirs of heat and work that they interact with are assumed to be macroscopic. This review discusses different theories which can take into account different aspects of mesoscopic and nanoscale physics, such as coherent quantum transport, magnetic-field induced effects (including topological ones such as the quantum Hall effect), and single electron charging effects. It discusses the efficiency of thermoelectric conversion, and the thermoelectric figure of merit. More specifically, the theories presented are (i) linear response theory with or without magnetic fields, (ii) Landauer scattering theory in the linear response regime and far from equilibrium, (iii) Green-Kubo formula for strongly interacting systems within the linear response regime, (iv) rate equation analysis for small quantum machines with or without interaction effects, (v) stochastic thermodynamic for fluctuating small systems. In all cases, we place particular emphasis on the fundamental questions about the bounds on ideal machines. Can magnetic-fields change the bounds on power or efficiency? What is the relationship between quantum theories of transport and the laws of thermodynamics? Does quantum mechanics place fundamental bounds on heat to work conversion which are absent in the thermodynamics of classical systems?

SU-F-T-284: The Effect of Linear Accelerator Output Variation On the Quality of Patient Specific Rapid Arc Verification Plans

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

Sandhu, G; Cao, F; Szpala, S

2016-06-15

Purpose: The aim of the current study is to investigate the effect of machine output variation on the delivery of the RapidArc verification plans. Methods: Three verification plans were generated using Eclipse™ treatment planning system (V11.031) with plan normalization value 100.0%. These plans were delivered on the linear accelerators using ArcCHECK− device, with machine output 1.000 cGy/MU at calibration point. These planned and delivered dose distributions were used as reference plans. Additional plans were created in Eclipse− with normalization values ranging 92.80%–102% to mimic the machine output ranging 1.072cGy/MU-0.980cGy/MU, at the calibration point. These plans were compared against the referencemore » plans using gamma indices (3%, 3mm) and (2%, 2mm). Calculated gammas were studied for its dependence on machine output. Plans were considered passed if 90% of the points satisfy the defined gamma criteria. Results: The gamma index (3%, 3mm) was insensitive to output fluctuation within the output tolerance level (2% of calibration), and showed failures, when the machine output exceeds ≥3%. Gamma (2%, 2mm) was found to be more sensitive to the output variation compared to the gamma (3%, 3mm), and showed failures, when output exceeds ≥1.7%. The variation of the gamma indices with output variability also showed dependence upon the plan parameters (e.g. MLC movement and gantry rotation). The variation of the percentage points passing gamma criteria with output variation followed a non-linear decrease beyond the output tolerance level. Conclusion: Data from the limited plans and output conditions showed that gamma (2%, 2mm) is more sensitive to the output fluctuations compared to Gamma (3%,3mm). Work under progress, including detail data from a large number of plans and a wide range of output conditions, may be able to conclude the quantitative dependence of gammas on machine output, and hence the effect on the quality of delivered rapid arc plans.« less

Possible limits of plasma linear colliders

NASA Astrophysics Data System (ADS)

Zimmermann, F.

2017-07-01

Plasma linear colliders have been proposed as next or next-next generation energy-frontier machines for high-energy physics. I investigate possible fundamental limits on energy and luminosity of such type of colliders, considering acceleration, multiple scattering off plasma ions, intrabeam scattering, bremsstrahlung, and betatron radiation. The question of energy efficiency is also addressed.

Reactive power generation in high speed induction machines by continuously occurring space-transients

NASA Astrophysics Data System (ADS)

Laithwaite, E. R.; Kuznetsov, S. B.

1980-09-01

A new technique of continuously generating reactive power from the stator of a brushless induction machine is conceived and tested on a 10-kw linear machine and on 35 and 150 rotary cage motors. An auxiliary magnetic wave traveling at rotor speed is artificially created by the space-transient attributable to the asymmetrical stator winding. At least two distinct windings of different pole-pitch must be incorporated. This rotor wave drifts in and out of phase repeatedly with the stator MMF wave proper and the resulting modulation of the airgap flux is used to generate reactive VA apart from that required for magnetization or leakage flux. The VAR generation effect increases with machine size, and leading power factor operation of the entire machine is viable for large industrial motors and power system induction generators.

Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation.

PubMed

Caravaca, Juan; Soria-Olivas, Emilio; Bataller, Manuel; Serrano, Antonio J; Such-Miquel, Luis; Vila-Francés, Joan; Guerrero, Juan F

2014-02-01

This work presents the application of machine learning techniques to analyse the influence of physical exercise in the physiological properties of the heart, during ventricular fibrillation. To this end, different kinds of classifiers (linear and neural models) are used to classify between trained and sedentary rabbit hearts. The use of those classifiers in combination with a wrapper feature selection algorithm allows to extract knowledge about the most relevant features in the problem. The obtained results show that neural models outperform linear classifiers (better performance indices and a better dimensionality reduction). The most relevant features to describe the benefits of physical exercise are those related to myocardial heterogeneity, mean activation rate and activation complexity. © 2013 Published by Elsevier Ltd.

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.

PubMed

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2017-01-01

Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of intestinal absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are large numbers of individual predictive models available for absorption using machine learning approaches. Six Artificial intelligence methods namely, Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis were used for prediction of absorption of compounds. Prediction accuracy of Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis for prediction of intestinal absorption of compounds was found to be 91.54%, 88.33%, 84.30%, 86.51%, 79.07% and 80.08% respectively. Comparative analysis of all the six prediction models suggested that Support vector machine with Radial basis function based kernel is comparatively better for binary classification of compounds using human intestinal absorption and may be useful at preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Spin dynamics in storage rings and linear accelerators

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

Irwin, J.

1994-12-01

The purpose of these lectures is to survey the subject of spin dynamics in accelerators: to give a sense of the underlying physics, the typical analytic and numeric methods used, and an overview of results achieved. Consideration will be limited to electrons and protons. Examples of experimental and theoretical results in both linear and circular machines are included.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Powering the programmed nanostructure and function of gold nanoparticles with catenated DNA machines

NASA Astrophysics Data System (ADS)

Elbaz, Johann; Cecconello, Alessandro; Fan, Zhiyuan; Govorov, Alexander O.; Willner, Itamar

2013-06-01

DNA nanotechnology is a rapidly developing research area in nanoscience. It includes the development of DNA machines, tailoring of DNA nanostructures, application of DNA nanostructures for computing, and more. Different DNA machines were reported in the past and DNA-guided assembly of nanoparticles represents an active research effort in DNA nanotechnology. Several DNA-dictated nanoparticle structures were reported, including a tetrahedron, a triangle or linear nanoengineered nanoparticle structures; however, the programmed, dynamic reversible switching of nanoparticle structures and, particularly, the dictated switchable functions emerging from the nanostructures, are missing elements in DNA nanotechnology. Here we introduce DNA catenane systems (interlocked DNA rings) as molecular DNA machines for the programmed, reversible and switchable arrangement of different-sized gold nanoparticles. We further demonstrate that the machine-powered gold nanoparticle structures reveal unique emerging switchable spectroscopic features, such as plasmonic coupling or surface-enhanced fluorescence.

A Real-Time Tool Positioning Sensor for Machine-Tools

PubMed Central

Ruiz, Antonio Ramon Jimenez; Rosas, Jorge Guevara; Granja, Fernando Seco; Honorato, Jose Carlos Prieto; Taboada, Jose Juan Esteve; Serrano, Vicente Mico; Jimenez, Teresa Molina

2009-01-01

In machining, natural oscillations, and elastic, gravitational or temperature deformations, are still a problem to guarantee the quality of fabricated parts. In this paper we present an optical measurement system designed to track and localize in 3D a reference retro-reflector close to the machine-tool's drill. The complete system and its components are described in detail. Several tests, some static (including impacts and rotations) and others dynamic (by executing linear and circular trajectories), were performed on two different machine tools. It has been integrated, for the first time, a laser tracking system into the position control loop of a machine-tool. Results indicate that oscillations and deformations close to the tool can be estimated with micrometric resolution and a bandwidth from 0 to more than 100 Hz. Therefore this sensor opens the possibility for on-line compensation of oscillations and deformations. PMID:22408472

Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

USDA-ARS?s Scientific Manuscript database

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating ...

Importance of biophysical effects on climate warming mitigation potential of biofuel crops over the conterminous United States

USDA-ARS?s Scientific Manuscript database

Current quantification of Climate Warming Mitigation Potential (CWMP) of biomass-derived energy has focused primarily on its biogeochemical effects. This study used site-level observations of carbon, water, and energy fluxes of biofuel crops to parameterize and evaluate the Community Land Model (CLM...

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Gray, A.

2014-04-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Astronomy Data Centre, Canadian

2014-01-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors, and the local outlier factor. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Morphology in the Digital Age: Integrating High Resolution Description of Structural Alterations with Phenotypes and Genotypes

PubMed Central

Nast, Cynthia C.; Lemley, Kevin V.; Hodgin, Jeffrey B.; Bagnasco, Serena; Avila-Casado, Carmen; Hewitt, Stephen M; Barisoni, Laura

2015-01-01

Conventional light microscopy (CLM) has been used to characterize and classify renal diseases, evaluate histopathology in studies and trials, and educate renal pathologists and nephrologists. The advent of digital pathology, in which a glass slide can be scanned to create whole slide images (WSI) for viewing and manipulating on a computer monitor, provides real and potential advantages over CLM. Software tools such as annotation, morphometry and image analysis can be applied to WSIs for studies or educational purposes, and the digital images are globally available to clinicians, pathologists and investigators. New ways of assessing renal pathology with observational data collection may allow better morphologic correlations and integration with molecular and genetic signatures, refinements of classification schema, and understanding of disease pathogenesis. In multicenter studies, WSI, which require additional quality assurance steps, provide efficiencies by reducing slide shipping and consensus conference costs, and allowing anytime anywhere slide viewing. While validation studies for the routine diagnostic use of digital pathology still are needed, this is a powerful tool currently available for translational research, clinical trials and education in renal pathology. PMID:26215864

Representing Plant Hydraulics in a Global Model: Updates to the Community Land Model

NASA Astrophysics Data System (ADS)

Kennedy, D.; Swenson, S. C.; Oleson, K. W.; Lawrence, D. M.; Fisher, R.; Gentine, P.

2017-12-01

In previous versions, the Community Land Model has used soil moisture to stand in for plant water status, with transpiration and photosynthesis driven directly by soil water potential. This eschews significant literature demonstrating the importance of plant hydraulic traits in the dynamics of water flow through the soil-plant-atmosphere continuum and in the regulation of stomatal aperture. In this study we install a simplified hydraulic framework to represent vegetation water potential and to regulate root water uptake and turbulent fluxes. Plant hydraulics allow for a more explicit representation of plant water status, which improves the physical basis for many processes represented in CLM. This includes root water uptake and the attenuation of photosynthesis and transpiration with drought. Model description is accompanied by results from a point simulation based at the Caxiuanã flux tower site in Eastern Amazonia, covering a throughfall exclusion experiment from 2001-2003. Including plant hydraulics improves the response to drought forcing compared to previous versions of CLM. Parameter sensitivity is examined at the same site and presented in the context of estimating hydraulic parameters in a global model.

Quality characteristics of battered and fried chicken: comparison of pressure frying and conventional frying.

PubMed

Das, Rashmi; Pawar, Deepthi P; Modi, Vinod Kumar

2013-04-01

The marinated and battered chicken leg meat and breast meat were pressure fried and their physico-chemical qualities were compared to the conventional fried product (open pan deep fat frying). Shrinkage due to frying process was significantly lesser in case of pressure fried leg meat (PLM) and breast meat (PBM) as compared to products prepared by conventional frying leg meat (CLM) and breast meat (CBM). Also, juiciness of pressure fried chicken products was superior (p ≤ 0.05) than fried products obtained by the conventional method. PLM and PBM had lower fat content (p ≤ 0.05) compared to conventionally fried CLM and CBM. Lipid oxidation was higher (p ≤ 0.05) in conventional frying as compared to pressure frying. Irrespective of the type of chicken meat, conventionally fried meat required higher shear force as compared to pressure fried products. Salmonella, Staphylococcus aureus, Shigella and E. coli were not detected. The study indicates the usefulness and superiority of pressure frying in comparison to conventional deep fat frying.

Mycorrhizal Controls on Nitrogen Uptake Drive Carbon Cycling at the Global Scale

NASA Astrophysics Data System (ADS)

Shi, M.; Fisher, J. B.; Brzostek, E. R.; Phillips, R.

2015-12-01

Nearly all plants form symbiotic relationships with one of two types of mycorrhizal fungi—arbuscular mycorrhizae (AM) and ectomycorrhizal (ECM) fungi, which are essential to global biogeochemical cycling of nutrient elements. In soils with higher rates of nitrogen and phosphorus mineralization from organic matter, AM-associated plants can be better adapted than ECM-associated plants. Importantly, the photosynthate costs of nutrient uptake for AM-associated plants are usually lower than that for ECM-associated plants. Thus, the global carbon cycle is closely coupled with mycorrhizal controls on N uptake. To investigate the potential climate dependence of terrestrial environments from AM- and ECM-associated plants, this study uses the Community Atmosphere Model (CAM) with a plant productivity-optimized N acquisition model—the Fixation and Uptake of Nitrogen (FUN) model—integrated into its land model—the Community Land Model (CLM). This latest version of CLM coupled with FUN allows for the assessment of mycorrhizal controls on global biogeochemical cycling. Here, we show how the historical evolution of AM- and ECM-associations altered regional and global biogeochemical cycling and climate, and future projections over the next century.

Double Arm Linkage precision Linear motion (DALL) Carriage, a simplified, rugged, high performance linear motion stage for the moving mirror of an Fourier Transform Spectrometer or other system requiring precision linear motion

NASA Astrophysics Data System (ADS)

Johnson, Kendall B.; Hopkins, Greg

2017-08-01

The Double Arm Linkage precision Linear motion (DALL) carriage has been developed as a simplified, rugged, high performance linear motion stage. Initially conceived as a moving mirror stage for the moving mirror of a Fourier Transform Spectrometer (FTS), it is applicable to any system requiring high performance linear motion. It is based on rigid double arm linkages connecting a base to a moving carriage through flexures. It is a monolithic design. The system is fabricated from one piece of material including the flexural elements, using high precision machining. The monolithic design has many advantages. There are no joints to slip or creep and there are no CTE (coefficient of thermal expansion) issues. This provides a stable, robust design, both mechanically and thermally and is expected to provide a wide operating temperature range, including cryogenic temperatures, and high tolerance to vibration and shock. Furthermore, it provides simplicity and ease of implementation, as there is no assembly or alignment of the mechanism. It comes out of the machining operation aligned and there are no adjustments. A prototype has been fabricated and tested, showing superb shear performance and very promising tilt performance. This makes it applicable to both corner cube and flat mirror FTS systems respectively.

A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

NASA Astrophysics Data System (ADS)

Khawaja, Taimoor Saleem

A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior and any abnormal or novel data during real-time operation. The results of the scheme are interpreted as a posterior probability of health (1 - probability of fault). As shown through two case studies in Chapter 3, the scheme is well suited for diagnosing imminent faults in dynamical non-linear systems. Finally, the failure prognosis scheme is based on an incremental weighted Bayesian LS-SVR machine. It is particularly suited for online deployment given the incremental nature of the algorithm and the quick optimization problem solved in the LS-SVR algorithm. By way of kernelization and a Gaussian Mixture Modeling (GMM) scheme, the algorithm can estimate "possibly" non-Gaussian posterior distributions for complex non-linear systems. An efficient regression scheme associated with the more rigorous core algorithm allows for long-term predictions, fault growth estimation with confidence bounds and remaining useful life (RUL) estimation after a fault is detected. The leading contributions of this thesis are (a) the development of a novel Bayesian Anomaly Detector for efficient and reliable Fault Detection and Identification (FDI) based on Least Squares Support Vector Machines, (b) the development of a data-driven real-time architecture for long-term Failure Prognosis using Least Squares Support Vector Machines, (c) Uncertainty representation and management using Bayesian Inference for posterior distribution estimation and hyper-parameter tuning, and finally (d) the statistical characterization of the performance of diagnosis and prognosis algorithms in order to relate the efficiency and reliability of the proposed schemes.

Correlation between gross anatomical topography, sectional sheet plastination, microscopic anatomy and endoanal sonography of the anal sphincter complex in human males

PubMed Central

Al-Ali, S; Blyth, P; Beatty, S; Duang, A; Parry, B; Bissett, I P

2009-01-01

This study elucidates the structure of the anal sphincter complex (ASC) and correlates the individual layers, namely the external anal sphincter (EAS), conjoint longitudinal muscle (CLM) and internal anal sphincter (IAS), with their ultrasonographic images. Eighteen male cadavers, with an average age of 72 years (range 62–82 years), were used in this study. Multiple methods were used including gross dissection, coronal and axial sheet plastination, different histological staining techniques and endoanal sonography. The EAS was a continuous layer but with different relations, an upper part (corresponding to the deep and superficial parts in the traditional description) and a lower (subcutaneous) part that was located distal to the IAS, and was the only muscle encircling the anal orifice below the IAS. The CLM was a fibro-fatty-muscular layer occupying the intersphincteric space and was continuous superiorly with the longitudinal muscle layer of the rectum. In its middle and lower parts it consisted of collagen and elastic fibres with fatty tissue filling the spaces between the fibrous septa. The IAS was a markedly thickened extension of the terminal circular smooth muscle layer of the rectum and it terminated proximal to the lower part of the EAS. On endoanal sonography, the EAS appeared as an irregular hyperechoic band; CLM was poorly represented by a thin irregular hyperechoic line and IAS was represented by a hypoechoic band. Data on the measurements of the thickness of the ASC layers are presented and vary between dissection and sonographic imaging. The layers of the ASC were precisely identified in situ, in sections, in isolated dissected specimens and the same structures were correlated with their sonographic appearance. The results of the measurements of ASC components in this study on male cadavers were variable, suggesting that these should be used with caution in diagnostic and management settings. PMID:19486204

Using ARM Observations to Evaluate Climate Model Representation of Land-Atmosphere Coupling on the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Phillips, T. J.; Klein, S. A.; Ma, H. Y.; Tang, Q.

2016-12-01

Statistically significant coupling between summertime soil moisture and various atmospheric variables has been observed at the U.S. Southern Great Plains (SGP) facilities maintained by the U.S. DOE Atmospheric Radiation Measurement (ARM) program (Phillips and Klein, 2014 JGR). In the current study, we employ several independent measurements of shallow-depth soil moisture (SM) and of the surface evaporative fraction (EF) over multiple summers in order to estimate the range of SM-EF coupling strength at seven sites, and to approximate the SGP regional-scale coupling strength (and its uncertainty). We will use this estimate of regional-scale SM-EF coupling strength to evaluate its representation in version 5.1 of the global Community Atmosphere Model (CAM5.1) coupled to the CLM4 Land Model. Two experimental cases are considered for the 2003-2011 study period: 1) an Atmospheric Model Intercomparison Project (AMIP) run with historically observed sea surface temperatures specified, and 2) a more constrained hindcast run in which the CAM5.1 atmospheric state is initialized each day from the ERA Interim reanalysis, while the CLM4 initial conditions are obtained from an offline run of the land model using observed surface net radiation, precipitation, and wind as forcings. These twin experimental cases allow a distinction to be drawn between the land-atmosphere coupling in the free-running CAM5.1/CLM4 model and that in which the land and atmospheric states are constrained to remain closer to "reality". The constrained hindcast case, for example, should allow model errors in coupling strength to be related more closely to potential deficiencies in land-surface or atmospheric boundary-layer parameterizations. AcknowledgmentsThis work was funded by the U.S. Department of Energy Office of Science and was performed at the Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

In vivo challenging of polymyxins and levofloxacin eye drop against multidrug-resistant Pseudomonas aeruginosa keratitis.

PubMed

Tajima, Kazuki; Miyake, Taku; Koike, Naohito; Hattori, Takaaki; Kumakura, Shigeto; Yamaguchi, Tetsuo; Matsumoto, Tetsuya; Fujita, Koji; Kuroda, Masahiko; Ito, Norihiko; Goto, Hiroshi

2014-06-01

The purposes of this study were to establish a rabbit multidrug-resistant Pseudomonas aeruginosa (MDRP) keratitis model, and test the efficacy of levofloxacin, colistin methanesulfate (CL-M), colistin sulfate (CL-S) and polymyxin B (PL-B) against MDRP infection. In a rabbit eye, making a 2-mm circular corneal excision, and MDRP strain #601 or representative P. aeruginosa strain IID1210 were instilled into the corneal concavity. IID1210 was used to confirm this model developed P. aeruginosa keratitis. After MDRP keratitis developed, we treated the eyes with levofloxacin, CL-M, CL-S or PL-B eye drops. The infected eyes were evaluated by clinical score, histopathological examination and viable bacterial count (CFU). Rabbits developed MDRP keratitis reproducibly after instilled the bacteria into the corneal lesion. MDRP produced severe keratitis similarly with IID1210, as shown by slit lamp examination and clinical score. In MDRP keratitis models, clinical scores and viable bacterial counts were significantly lower in levofloxacin- and CL-M-treated groups compared with PBS-treated group, but the magnitudes of reduction were not remarkable. However, clinical scores were dramatically lowered in CL-S- and PL-B-treated groups compared with PBS-treated group. CL-S- and PL-B-treated group were kept corneal translucency and little influx of polymorphonuclear neutrophils in histopathological examination. In addition, both CL-S- and PL-B-treated groups were not detected viable bacteria in infected cornea. Using our MDRP keratitis model, we showed that topical levofloxacin and CL-M are not adequately effective, while CL-S and PL-B are efficacious in controlling MDRP keratitis. Especially, PL-B, which is commercially available eye drop, might be most effective against MDRP. Copyright © 2014 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

CESM-simulated 21st Century Changes in Large Scale Crop Water Requirements and Yields

NASA Astrophysics Data System (ADS)

Levis, S.; Badger, A.; Drewniak, B. A.; O'Neill, B. C.; Ren, X.

2014-12-01

We assess potential changes in crop water requirements and corresponding yields relative to the late 20th century in major crop producing regions of the world by using the Community Land Model (CLM) driven with 21st century meteorology from RCP8.5 and RCP4.5 Community Earth System Model (CESM) simulations. The RCP4.5 simulation allows us to explore the potential for averted societal impacts when compared to the RCP8.5 simulation. We consider the possibility for increased yields and improved water use efficiency under conditions of elevated atmospheric CO2 due to the CO2 fertilization effect (also known as concentration-carbon feedback). We address uncertainty in the current understanding of plant CO2 fertilization by repeating the simulations with and without the CO2 fertilization effect. Simulations without CO2 fertilization represent the radiative effect of elevated CO2 (i.e., warming) without representing the physiological effect of elevated CO2 (enhanced carbon uptake and increased water use efficiency by plants during photosynthesis). Preliminary results suggest that some plants may suffer from increasing heat and drought in much of the world without the CO2 fertilization effect. On the other hand plants (especially C3) tend to grow more with less water when models include the CO2 fertilization effect. Performing 21st century simulations with and without the CO2 fertilization effect brackets the potential range of outcomes. In this work we use the CLM crop model, which includes specific crop types that differ from the model's default plant functional types in that the crops get planted, harvested, and potentially fertilized and irrigated according to algorithms that attempt to capture human management decisions. We use an updated version of the CLM4.5 that includes cotton, rice, and sugarcane, spring wheat, spring barley, and spring rye, as well as temperate and tropical maize and soybean.

Use of Neoadjuvant Chemotherapy Plus Molecular Targeted Therapy in Colorectal Liver Metastases: A Systematic Review and Meta-analysis.

PubMed

Sabanathan, Dhanusha; Eslick, Guy D; Shannon, Jenny

2016-12-01

Surgery remains the standard of care for patients with colorectal liver metastases (CLMs), with a 5-year survival rate approaching 35%. Perioperative chemotherapy confers a survival benefit in selected patients with CLMs. The use of molecular targeted therapy combined with neoadjuvant chemotherapy for CLMs, however, remains controversial. We reviewed the published data on combination neoadjuvant chemotherapy and molecular targeted therapy for resectable and initially unresectable CLMs. A literature search of the Medline and PubMed databases was conducted to identify studies of neoadjuvant chemotherapy plus molecular targeted therapy in the management of resectable or initially unresectable CLMs. We calculated the pooled proportion and 95% confidence intervals using a random effects model for the relationship of the combination neoadjuvant treatment on the overall response rate and performed a systematic review of all identified studies. The analysis was stratified according to the study design. The data from 11 studies of 908 patients who had undergone systemic chemotherapy plus targeted therapy for CLM were analyzed. The use of combination neoadjuvant therapy was associated with an overall response rate of 68% (95% confidence interval, 63%-73%), with significant heterogeneity observed in the studies (I 2  = 89.35; P < .001). Of the 11 studies, 4 used a combination that included oxaliplatin, 2 included irinotecan, and 5 included a combination of both. Also, 7 studies used cetuximab and 4 bevacizumab. The overall progression-free survival was estimated at 14.4 months. Current evidence suggests that neoadjuvant chemotherapy plus molecular targeted agents for CLM confers high overall response rates. Combination treatment might also increase the resectability rates in initially unresectable CLM. Further studies are needed to examine the survival outcomes, with a focus on the differential role of molecular targeted therapy in the neoadjuvant versus adjuvant setting. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

The Ups and Downs of Rhizosphere Resource Exchange

NASA Astrophysics Data System (ADS)

Cardon, Z. G.; Fu, C.; Wang, G.; Stark, J.

2014-12-01

Hydraulic redistribution (HR) of soil water by plants occurs in seasonally dry ecosystems worldwide. During HR, soil water flows from wet soil into roots, through the root system, and out of roots into dry rhizosphere soil. Hydraulic redistribution affects plant physiology and landscape hydrology, and it has long been hypothesized that upward HR of deep water to dry, nutrient-rich surface soil may also stimulate soil nutrient cycling and thus enhance nutrient availability to plants in the field. We report results from a sagebrush-steppe field experiment in northern Utah, USA, showing that stimulation of sagebrush-mediated HL increased rates of nitrogen cycling in the surface soil layer around shrubs at summer's end, and more than quadrupled uptake of nitrogen into developing sagebrush inflorescences. We have built on these empirical data by folding Ryel et al.'s (2002) HR formulation into CLM4.5 and examining how well the combined model can simultaneously simulate measured evapotranspiration, the vertical profile of soil moisture, and the amplitude of HR-associated diel changes in water content, at multiple seasonally-dry Ameriflux sites: Wind River Crane (US-Wrc), Southern California Climate Gradient (US-SCs,g,f,w,d,&c), and Santa Rita Mesquite Savanna (US-SRM). The simulated hydraulic lift during the dry periods has an average value in the range from 0.09 (at US-SCc) to 0.64 (at US-SCf) mm H2O d-1. In many cases, the combined model reproduced seasonal and daily (diel) observations with reasonable accuracy. Among the many model parameters tested, the Clapp and Hornberger parameter "B" in CLM4.5 was critical for a realistic simulation of soil moisture. Modeled HR was also sensitive to the maximum radial soil-root conductance and the soil water potential where that conductance is reduced by 50%. Our next step is to explore how modeled carbon and nutrient cycling in soil layers are affected by redistributed water in the soil column caused by inclusion of HR in CLM4.5.

Modeling the impact of hydraulic redistribution on the carbon flux and storages using CLM4.5 at four AmeriFlux Sites

NASA Astrophysics Data System (ADS)

Fu, C.; Wang, G.; Cardon, Z. G.

2015-12-01

Effects of hydraulic redistribution (HR) on the hydrological cycle and ecosystem dynamics have been demonstrated in the field, but few modeling studies have compared HR's influences on the carbon cycle in different ecosystems and climate regions. The soil moisture changes associated with HR could influence plant carbon gain via two mechanisms: (1) improved plant water status supporting stomatal opening, and/or (2) enhanced nutrient availability to plants caused by enhanced soil microbial activity. In this study, using a modified version of the Community Land Model with Century-based soil carbon pool kinetics that includes the "Ryel et al. 2002" scheme for hydraulic redistribution (HR), the influence of HR on the carbon flux and storage is investigated at four Ameriflux sites where HR was detected from soil moisture measurements. The study sites include a Douglas-fir site (US-Wrc) in Washington State with a mediterranean climate, a savanna site (US-SRM) in Arizona with a semi-arid climate, an oak/pine forest site (US-SCf) in Southern California with a mediterranean climate, and an evergreen broadleaf forest site (BR-Sa1) with tropical monsoon climate. Simulations revealed that HR tended to enhance plant growth at all four sites, and incorporating HR into CLM4.5 reduces the temporal fluctuation of soil carbon storage at all four sites. Simulations with HR can capture the net carbon exchange between ecosystem and the atmosphere (NEE) at the US-Wrc, US-SRM, and BR-Sa1 sites over the annual cycle. Incorporation of HR into CLM4.5 clearly improved the weekly and sub-daily NEE simulation during dry periods at US-SCf and BR-Sa1 site. HR-induced increase in Net Primary Productivity (NPP) at the US-Wrc and US-SRM sites was driven approximately equally by the two distinct mechanisms we investigated: increased stomatal conductance and increased nutrient availability to plants.

Reconstructing Native American migrations from whole-genome and whole-exome data.

PubMed

Gravel, Simon; Zakharia, Fouad; Moreno-Estrada, Andres; Byrnes, Jake K; Muzzio, Marina; Rodriguez-Flores, Juan L; Kenny, Eimear E; Gignoux, Christopher R; Maples, Brian K; Guiblet, Wilfried; Dutil, Julie; Via, Marc; Sandoval, Karla; Bedoya, Gabriel; Oleksyk, Taras K; Ruiz-Linares, Andres; Burchard, Esteban G; Martinez-Cruzado, Juan Carlos; Bustamante, Carlos D

2013-01-01

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is 48% in MXL, 25% in CLM, and 13% in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern American ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas 16 thousand years ago (kya), supports that the MXL Ancestors split 12.2kya, with a subsequent split of the ancestors to CLM and PUR 11.7kya. The model also features effective populations of 62,000 in Mexico, 8,700 in Colombia, and 1,900 in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.

Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models.

PubMed

Song, Xiang; Zeng, Xiaodong

2017-02-01

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO 2 , and few studies have considered how and to what extent climate change and CO 2 influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP-DGVM coupled with CLM3 and CLM4-CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO 2 concentration. In the temperature sensitivity tests, warming reduced the global area-averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (Δ F tree ; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether Δ F tree was positive or negative, while the tree fractional coverage ( F tree ; %) played a decisive role in the amplitude of Δ F tree around the globe, and the dependence was more remarkable in IAP-DGVM. In cases with precipitation change, F tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% <  F tree  < 60%) for IAP-DGVM and in semiarid and arid regions for CLM4-CNDV. Moreover, Δ F tree had a stronger dependence on F tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO 2 concentration.

SMAD4 gene mutation predicts poor prognosis in patients undergoing resection for colorectal liver metastases.

PubMed

Mizuno, Takashi; Cloyd, Jordan M; Vicente, Diego; Omichi, Kiyohiko; Chun, Yun Shin; Kopetz, Scott E; Maru, Dipen; Conrad, Claudius; Tzeng, Ching-Wei D; Wei, Steven H; Aloia, Thomas A; Vauthey, Jean-Nicolas

2018-05-01

Dorsophilia protein, mothers against decapentaplegic homolog 4 (SMAD4) is a key mediator in the transforming growth factor (TGF)-β signaling pathway and SMAD4 gene mutations are thought to play a critical role in colorectal cancer (CRC) progression. However, little is known about its influence on survival in patients undergoing resection for colorectal liver metastases (CLM). Between 2005 and 2015, all patients with known SMAD4 mutation status who underwent resection of CLM were identified. Patients with SMAD4 mutation were compared to those with SMAD4 wild type. Next, the prognostic value of SMAD4 mutation was validated in a separate cohort of patients with synchronous stage IV CRC who underwent systemic therapy alone. Of 278 patients, 37 (13%) were SMAD4 mutant while 241 (87%) were wild type. Overall survival (OS) after hepatic resection was worse in SMAD4-mutant patients compared to SMAD4 wild type (OS rate at 3 years, 62% vs. 82%; P < 0.0001). Independent predictors for worse OS were poor differentiation (hazard ratio [HR] 2.586; P = 0.007), multiple tumors (HR 1.970; P = 0.01), diameter greater than 3 cm (HR 1.752; P = 0.017), R1 margin status (HR 2.452; P = 0.014), RAS mutation (HR 2.044; P = 0.002), and SMAD4 mutation (HR 2.773; P < 0.0001). Among 237 patients in the validation cohort, SMAD4-mutations were significantly associated with worse 3-year OS rate (22% vs. 38%; P = 0.012) and was an independent predictor for worse OS (HR, 1.647; P = 0.032). SMAD4 mutation is independently associated with worse outcomes among patients undergoing resection of CLM. Copyright © 2018 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

DOE PAGES

Fu, Congsheng; Wang, Guiling; Goulden, Michael L.; ...

2016-05-17

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site comparisons for contrasting climate regimes and multiple vegetation types via the integration of measurement and modeling. Here, we incorporated the HR scheme of Ryel et al. (2002) into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture themore » magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on land surface water and energy budgets, and to explore how the impact may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites with contrasting climate regimes and multiple vegetation types were studied, including the Wind River Crane site in Washington State, the Santa Rita Mesquite savanna site in southern Arizona, and six sites along the Southern California Climate Gradient. HR flux, evapotranspiration (ET), and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement matches of evapotranspiration, Bowen ratio, and soil moisture particularly during dry seasons. Lastly, our results also reveal that HR has important hydrological impact in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.« less

Reconstructing Native American Migrations from Whole-Genome and Whole-Exome Data

PubMed Central

Gravel, Simon; Muzzio, Marina; Rodriguez-Flores, Juan L.; Kenny, Eimear E.; Gignoux, Christopher R.; Maples, Brian K.; Guiblet, Wilfried; Dutil, Julie; Via, Marc; Sandoval, Karla; Bedoya, Gabriel; Oleksyk, Taras K.; Ruiz-Linares, Andres; Burchard, Esteban G.; Martinez-Cruzado, Juan Carlos; Bustamante, Carlos D.

2013-01-01

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is in MXL, in CLM, and in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern America ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas thousand years ago (kya), supports that the MXL Ancestors split kya, with a subsequent split of the ancestors to CLM and PUR kya. The model also features effective populations of in Mexico, in Colombia, and in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations. PMID:24385924

Effects of leaf area index on the coupling between water table, land surface energy fluxes, and planetary boundary layer at the regional scale

NASA Astrophysics Data System (ADS)

Lu, Y.; Rihani, J.; Langensiepen, M.; Simmer, C.

2013-12-01

Vegetation plays an important role in the exchange of moisture and energy at the land surface. Previous studies indicate that vegetation increases the complexity of the feedbacks between the atmosphere and subsurface through processes such as interception, root water uptake, leaf surface evaporation, and transpiration. Vegetation cover can affect not only the interaction between water table depth and energy fluxes, but also the development of the planetary boundary layer. Leaf Area Index (LAI) is shown to be a major factor influencing these interactions. In this work, we investigate the sensitivity of water table, surface energy fluxes, and atmospheric boundary layer interactions to LAI as a model input. We particularly focus on the role LAI plays on the location and extent of transition zones of strongest coupling and how this role changes over seasonal timescales for a real catchment. The Terrestrial System Modelling Platform (TerrSysMP), developed within the Transregional Collaborative Research Centre 32 (TR32), is used in this study. TerrSysMP consists of the variably saturated groundwater model ParFlow, the land surface model Community Land Model (CLM), and the regional climate and weather forecast model COSMO (COnsortium for Small-scale Modeling). The sensitivity analysis is performed over a range of LAI values for different vegetation types as extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset for the Rur catchment in Germany. In the first part of this work, effects of vegetation structure on land surface energy fluxes and their connection to water table dynamics are studied using the stand-alone CLM and the coupled subsurface-surface components of TerrSysMP (ParFlow-CLM), respectively. The interconnection between LAI and transition zones of strongest coupling are investigated and analyzed through a subsequent set of subsurface-surface-atmosphere coupled simulations implementing the full TerrSysMP model system.

Drought, Fire and Insects in Western US Forests: Observations to Improve Regional Land System Modeling

NASA Astrophysics Data System (ADS)

Law, B. E.; Yang, Z.; Berner, L. T.; Hicke, J. A.; Buotte, P.; Hudiburg, T. W.

2015-12-01

Drought, fire and insects are major disturbances in the western US, and conditions are expected to get warmer and drier in the future. We combine multi-scale observations and modeling with CLM4.5 to examine the effects of these disturbances on forests in the western US. We modified the Community Land Model, CLM4.5, to improve simulated drought-related mortality in forests, and prediction of insect outbreaks under future climate conditions. We examined differences in plant traits that represent species variation in sensitivity to drought, and redefined plant groupings in PFTs. Plant traits, including sapwood area: leaf area ratio and stemwood density were strongly correlated with water availability during the ecohydrologic year. Our database of co-located observations of traits for 30 tree species was used to produce parameterization of the model by species groupings according to similar traits. Burn area predicted by the new fire model in CLM4.5 compares well with recent years of GFED data, but has a positive bias compared with Landsat-based MTBS. Biomass mortality over recent decades increased, and was captured well by the model in general, but missed mortality trends of some species. Comparisons with AmeriFlux data showed that the model with dynamic tree mortality only (no species trait improvements) overestimated GPP in dry years compared with flux data at semi-arid sites, and underestimated GPP at more mesic sites that experience dry summers. Simulations with both dynamic tree mortality and species trait parameters improved estimates of GPP by 17-22%; differences between predicted and observed NEE were larger. Future projections show higher productivity from increased atmospheric CO2 and warming that somewhat offsets drought and fire effects over the next few decades. Challenges include representation of hydraulic failure in models, and availability of species trait and carbon/water process data in disturbance- and drought-impacted regions.

Efficacy of Ketorolac Buccal Infiltrations and Inferior Alveolar Nerve Blocks in Patients with Irreversible Pulpitis: A Prospective, Double-blind, Randomized Clinical Trial.

PubMed

Akhlaghi, Nahid Mohammadzadeh; Hormozi, Behnoush; Abbott, Paul V; Khalilak, Zohreh

2016-05-01

The purpose of this prospective, randomized, double-blind, placebo-controlled study was to determine whether ketorolac buccal infiltrations (BIs) helped to improve the success of inferior alveolar nerve blocks (IANBs) in patients with acute irreversible pulpitis (AIP). Forty adult volunteers with AIP in a mandibular molar were included in this study. Patients were instructed to evaluate their pain by using a Heft-Parker visual analog scale. They were randomly divided into 2 groups (n = 20). All patients received standard IANB injection and after that a BI of 4% articaine with 1:100,000 epinephrine. After 5 minutes, 20 patients received a BI of 30 mg/mL ketorolac, and the other received a BI of normal saline (control group). Endodontic access cavity preparation (ACP) was initiated 15 minutes after the IANB when the patient reported lip numbness and had 2 electric pulp tests with no responses. The patient's pain during caries and dentin removal, ACP, and canal length measurements (CLM) was recorded by using Heft-Parker visual analog scale. Successful anesthesia was defined as no or mild pain during any of these steps, without the need for additional injection. Data were statistically analyzed by using Mann-Whitney U and χ(2) tests. Successful anesthesia after an IANB plus BI of articaine was obtained in 15% of patients in the control group at the end of CLM. Adding BI of ketorolac significantly increased the success rate to 40% (P < .05). Patient's pain during ACP and CLM was significantly lower in the ketorolac group (P < .05). Ketorolac BI can increase the success rate of anesthesia after IANB and BI with articaine in patients with AIP. Copyright © 2016 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Chemical composition and source apportionment of size fractionated particulate matter in Cleveland, Ohio, USA.

PubMed

Kim, Yong Ho; Krantz, Q Todd; McGee, John; Kovalcik, Kasey D; Duvall, Rachelle M; Willis, Robert D; Kamal, Ali S; Landis, Matthew S; Norris, Gary A; Gilmour, M Ian

2016-11-01

The Cleveland airshed comprises a complex mixture of industrial source emissions that contribute to periods of non-attainment for fine particulate matter (PM 2.5 ) and are associated with increased adverse health outcomes in the exposed population. Specific PM sources responsible for health effects however are not fully understood. Size-fractionated PM (coarse, fine, and ultrafine) samples were collected using a ChemVol sampler at an urban site (G.T. Craig (GTC)) and rural site (Chippewa Lake (CLM)) from July 2009 to June 2010, and then chemically analyzed. The resulting speciated PM data were apportioned by EPA positive matrix factorization to identify emission sources for each size fraction and location. For comparisons with the ChemVol results, PM samples were also collected with sequential dichotomous and passive samplers, and evaluated for source contributions to each sampling site. The ChemVol results showed that annual average concentrations of PM, elemental carbon, and inorganic elements in the coarse fraction at GTC were ∼2, ∼7, and ∼3 times higher than those at CLM, respectively, while the smaller size fractions at both sites showed similar annual average concentrations. Seasonal variations of secondary aerosols (e.g., high NO 3 - level in winter and high SO 4 2- level in summer) were observed at both sites. Source apportionment results demonstrated that the PM samples at GTC and CLM were enriched with local industrial sources (e.g., steel plant and coal-fired power plant) but their contributions were influenced by meteorological conditions and the emission source's operation conditions. Taken together the year-long PM collection and data analysis provides valuable insights into the characteristics and sources of PM impacting the Cleveland airshed in both the urban center and the rural upwind background locations. These data will be used to classify the PM samples for toxicology studies to determine which PM sources, species, and size fractions are of greatest health concern. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessing Ecosystem Drought Response in CLM 4.5 Using Site-Level Flux and Carbon-Isotope Measurements: Results From a Pacific Northwest Coniferous Forest

NASA Astrophysics Data System (ADS)

Duarte, H.; Raczka, B. M.; Koven, C. D.; Ricciuto, D. M.; Lin, J. C.; Bowling, D. R.; Ehleringer, J. R.

2015-12-01

The frequency, extent, and severity of droughts are expected to increase in the western United States as climate changes occur. The combination of warmer temperature, larger vapor pressure deficit, reduced snowfall and snow pack, earlier snow melt, and extended growing seasons is expected to lead to an intensification of summer droughts, with a direct impact on ecosystem productivity and therefore on the carbon budget of the region. In this scenario, an accurate representation of ecosystem drought response in land models becomes fundamental, but the task is challenging, especially in regards to stomatal response to drought. In this study we used the most recent release of the Community Land Model (CLM 4.5), which now includes photosynthetic carbon isotope discrimination and revised photosynthesis and hydrology schemes, among an extensive list of updates. We evaluated the model's performance at a coniferous forest site in the Pacific northwest (Wind River AmeriFlux Site), characterized by a climate that has a strong winter precipitation component followed by a summer drought. We ran the model in offline mode (i.e., decoupled from an atmospheric model), forced by observed meteorological data, and used site observations (e.g., surface fluxes, biomass values, and carbon isotope data) to assess the model. Previous field observations indicated a significant negative correlation between soil water content and the carbon isotope ratio of ecosystem respiration (δ13CR), suggesting that δ13CR was closely related to the photosynthetic discrimination against 13CO2 as controlled by stomatal conductance. We used these observations and latent-heat flux measurements to assess the modeled stomatal conductance values and their responses to extended summer drought. We first present the model results, followed by a discussion of potential CLM model improvements in stomatal conductance responses and in the representation of soil water stress (parameter βt) that would more precisely incorporate features that would allow the model to correctly simulate field observations.

Induction linear accelerators

NASA Astrophysics Data System (ADS)

Birx, Daniel

1992-03-01

Among the family of particle accelerators, the Induction Linear Accelerator is the best suited for the acceleration of high current electron beams. Because the electromagnetic radiation used to accelerate the electron beam is not stored in the cavities but is supplied by transmission lines during the beam pulse it is possible to utilize very low Q (typically<10) structures and very large beam pipes. This combination increases the beam breakup limited maximum currents to of order kiloamperes. The micropulse lengths of these machines are measured in 10's of nanoseconds and duty factors as high as 10-4 have been achieved. Until recently the major problem with these machines has been associated with the pulse power drive. Beam currents of kiloamperes and accelerating potentials of megavolts require peak power drives of gigawatts since no energy is stored in the structure. The marriage of liner accelerator technology and nonlinear magnetic compressors has produced some unique capabilities. It now appears possible to produce electron beams with average currents measured in amperes, peak currents in kiloamperes and gradients exceeding 1 MeV/meter, with power efficiencies approaching 50%. The nonlinear magnetic compression technology has replaced the spark gap drivers used on earlier accelerators with state-of-the-art all-solid-state SCR commutated compression chains. The reliability of these machines is now approaching 1010 shot MTBF. In the following paper we will briefly review the historical development of induction linear accelerators and then discuss the design considerations.

Review of the energy check of an electron-only linear accelerator over a 6 year period: sensitivity of the technique to energy shift.

PubMed

Biggs, Peter J

2003-04-01

The calibration and monthly QA of an electron-only linear accelerator dedicated to intra-operative radiation therapy has been reviewed. Since this machine is calibrated prior to every procedure, there was no necessity to adjust the output calibration at any time except, perhaps, when the magnetron is changed, provided the machine output is reasonably stable. This gives a unique opportunity to study the dose output of the machine per monitor unit, variation in the timer error, flatness and symmetry of the beam and the energy check as a function of time. The results show that, although the dose per monitor unit varied within +/- 2%, the timer error within +/- 0.005 MU and the asymmetry within 1-2%, none of these parameters showed any systematic change with time. On the other hand, the energy check showed a linear drift with time for 6, 9, and 12 MeV (2.1, 3.5, and 2.5%, respectively, over 5 years), while at 15 and 18 MeV, the energy check was relatively constant. It is further shown that based on annual calibrations and RPC TLD checks, the energy of each beam is constant and that therefore the energy check is an exquisitely sensitive one. The consistency of the independent checks is demonstrated.

Wear resistance of machine tools' bionic linear rolling guides by laser cladding

NASA Astrophysics Data System (ADS)

Wang, Yiqiang; Liu, Botao; Guo, Zhengcai

2017-06-01

In order to improve the rolling wear resistance (RWR) of linear rolling guides (LRG) as well as prolong the life of machine tools, various shape samples with different units spaces ranged from 1 to 5 mm are designed through the observation of animals in the desert and manufactured by laser cladding. Wear resistance tests reproducing closely the real operational condition are conducted by using a homemade linear reciprocating wear test machine, and wear resistance is evaluated by means of weight loss measurement. Results indicate that the samples with bionic units have better RWR than the untreated one, of which the reticulate treated sample with unit space 3 mm present the best RWR. More specifically, among the punctuate treated samples, the mass loss increases with the increase of unit space; among the striate treated samples, the mass loss changes slightly with the increase of unit space, attaining a minimum at the unit space of 4 mm; among the reticulate treated samples, with the increase of unit space, the mass loss initially decreases, but turns to increase after reaching a minimum at the unit space of 3 mm. Additionally, the samples with striate shape perform better wear resistance than the other shape groups on the whole. From the ratio value of laser treated area to contacted area perspective, that the samples with ratio value between 0.15 and 0.3 possess better wear resistance is concluded.

Comparison of Classifiers for Decoding Sensory and Cognitive Information from Prefrontal Neuronal Populations

PubMed Central

Astrand, Elaine; Enel, Pierre; Ibos, Guilhem; Dominey, Peter Ford; Baraduc, Pierre; Ben Hamed, Suliann

2014-01-01

Decoding neuronal information is important in neuroscience, both as a basic means to understand how neuronal activity is related to cerebral function and as a processing stage in driving neuroprosthetic effectors. Here, we compare the readout performance of six commonly used classifiers at decoding two different variables encoded by the spiking activity of the non-human primate frontal eye fields (FEF): the spatial position of a visual cue, and the instructed orientation of the animal's attention. While the first variable is exogenously driven by the environment, the second variable corresponds to the interpretation of the instruction conveyed by the cue; it is endogenously driven and corresponds to the output of internal cognitive operations performed on the visual attributes of the cue. These two variables were decoded using either a regularized optimal linear estimator in its explicit formulation, an optimal linear artificial neural network estimator, a non-linear artificial neural network estimator, a non-linear naïve Bayesian estimator, a non-linear Reservoir recurrent network classifier or a non-linear Support Vector Machine classifier. Our results suggest that endogenous information such as the orientation of attention can be decoded from the FEF with the same accuracy as exogenous visual information. All classifiers did not behave equally in the face of population size and heterogeneity, the available training and testing trials, the subject's behavior and the temporal structure of the variable of interest. In most situations, the regularized optimal linear estimator and the non-linear Support Vector Machine classifiers outperformed the other tested decoders. PMID:24466019

An observational constraint on stomatal function in forests: evaluating coupled carbon and water vapor exchange with carbon isotopes in the Community Land Model (CLM4.5)

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

Raczka, Brett; Duarte, Henrique F.; Koven, Charles D.

Land surface models are useful tools to quantify contemporary and future climate impact on terrestrial carbon cycle processes, provided they can be appropriately constrained and tested with observations. Stable carbon isotopes of CO 2 offer the potential to improve model representation of the coupled carbon and water cycles because they are strongly influenced by stomatal function. Recently, a representation of stable carbon isotope discrimination was incorporated into the Community Land Model component of the Community Earth System Model. Here, we tested the model's capability to simulate whole-forest isotope discrimination in a subalpine conifer forest at Niwot Ridge, Colorado, USA. Wemore » distinguished between isotopic behavior in response to a decrease of δ 13C within atmospheric CO 2 (Suess effect) vs. photosynthetic discrimination (Δ canopy), by creating a site-customized atmospheric CO 2 and δ 13C of CO 2 time series. We implemented a seasonally varying V cmax model calibration that best matched site observations of net CO 2 carbon exchange, latent heat exchange, and biomass. The model accurately simulated observed δ 13C of needle and stem tissue, but underestimated the δ 13C of bulk soil carbon by 1–2 ‰. The model overestimated the multiyear (2006–2012) average Δ canopy relative to prior data-based estimates by 2–4 ‰. The amplitude of the average seasonal cycle of Δ canopy (i.e., higher in spring/fall as compared to summer) was correctly modeled but only when using a revised, fully coupled A n- g s (net assimilation rate, stomatal conductance) version of the model in contrast to the partially coupled A n- g s version used in the default model. The model attributed most of the seasonal variation in discrimination to A n, whereas interannual variation in simulated Δ canopy during the summer months was driven by stomatal response to vapor pressure deficit (VPD). The model simulated a 10 % increase in both photosynthetic discrimination and water-use efficiency (WUE) since 1850 which is counter to established relationships between discrimination and WUE. The isotope observations used here to constrain CLM suggest (1) the model overestimated stomatal conductance and (2) the default CLM approach to representing nitrogen limitation (partially coupled model) was not capable of reproducing observed trends in discrimination. These findings demonstrate that isotope observations can provide important information related to stomatal function driven by environmental stress from VPD and nitrogen limitation. Future versions of CLM that incorporate carbon isotope discrimination are likely to benefit from explicit inclusion of mesophyll conductance.« less

An observational constraint on stomatal function in forests: evaluating coupled carbon and water vapor exchange with carbon isotopes in the Community Land Model (CLM4.5)

DOE PAGES

Raczka, Brett; Duarte, Henrique F.; Koven, Charles D.; ...

2016-09-19

Land surface models are useful tools to quantify contemporary and future climate impact on terrestrial carbon cycle processes, provided they can be appropriately constrained and tested with observations. Stable carbon isotopes of CO 2 offer the potential to improve model representation of the coupled carbon and water cycles because they are strongly influenced by stomatal function. Recently, a representation of stable carbon isotope discrimination was incorporated into the Community Land Model component of the Community Earth System Model. Here, we tested the model's capability to simulate whole-forest isotope discrimination in a subalpine conifer forest at Niwot Ridge, Colorado, USA. Wemore » distinguished between isotopic behavior in response to a decrease of δ 13C within atmospheric CO 2 (Suess effect) vs. photosynthetic discrimination (Δ canopy), by creating a site-customized atmospheric CO 2 and δ 13C of CO 2 time series. We implemented a seasonally varying V cmax model calibration that best matched site observations of net CO 2 carbon exchange, latent heat exchange, and biomass. The model accurately simulated observed δ 13C of needle and stem tissue, but underestimated the δ 13C of bulk soil carbon by 1–2 ‰. The model overestimated the multiyear (2006–2012) average Δ canopy relative to prior data-based estimates by 2–4 ‰. The amplitude of the average seasonal cycle of Δ canopy (i.e., higher in spring/fall as compared to summer) was correctly modeled but only when using a revised, fully coupled A n- g s (net assimilation rate, stomatal conductance) version of the model in contrast to the partially coupled A n- g s version used in the default model. The model attributed most of the seasonal variation in discrimination to A n, whereas interannual variation in simulated Δ canopy during the summer months was driven by stomatal response to vapor pressure deficit (VPD). The model simulated a 10 % increase in both photosynthetic discrimination and water-use efficiency (WUE) since 1850 which is counter to established relationships between discrimination and WUE. The isotope observations used here to constrain CLM suggest (1) the model overestimated stomatal conductance and (2) the default CLM approach to representing nitrogen limitation (partially coupled model) was not capable of reproducing observed trends in discrimination. These findings demonstrate that isotope observations can provide important information related to stomatal function driven by environmental stress from VPD and nitrogen limitation. Future versions of CLM that incorporate carbon isotope discrimination are likely to benefit from explicit inclusion of mesophyll conductance.« less

Mesoscale atmospheric modelling technology as a tool for the long-term meteorological dataset development

NASA Astrophysics Data System (ADS)

Platonov, Vladimir; Kislov, Alexander; Rivin, Gdaly; Varentsov, Mikhail; Rozinkina, Inna; Nikitin, Mikhail; Chumakov, Mikhail

2017-04-01

The detailed hydrodynamic modelling of meteorological parameters during the last 30 years (1985 - 2014) was performed for the Okhotsk Sea and the Sakhalin island regions. The regional non-hydrostatic atmospheric model COSMO-CLM used for this long-term simulation with 13.2, 6.6 and 2.2 km horizontal resolutions. The main objective of creation this dataset was the outlook of the investigation of statistical characteristics and the physical mechanisms of extreme weather events (primarily, wind speed extremes) on the small spatio-temporal scales. COSMO-CLM is the climate version of the well-known mesoscale COSMO model, including some modifications and extensions adapting to the long-term numerical experiments. The downscaling technique was realized and developed for the long-term simulations with three consequent nesting domains. ERA-Interim reanalysis ( 0.75 degrees resolution) used as global forcing data for the starting domain ( 13.2 km horizontal resolution), then these simulation data used as initial and boundary conditions for the next model runs over the domain with 6.6 km resolution, and similarly, for the next step to 2.2 km domain. Besides, the COSMO-CLM model configuration for 13.2 km run included the spectral nudging technique, i.e. an additional assimilation of reanalysis data not only at boundaries, but also inside the whole domain. Practically, this computational scheme realized on the SGI Altix 4700 supercomputer system in the Main Computer Center of Roshydromet and used 2,400 hours of CPU time total. According to modelling results, the verification of the obtained dataset was performed on the observation data. Estimations showed the mean error -0.5 0C, up to 2 - 3 0C RMSE in temperature, and overestimation in wind speed (RMSE is up to 2 m/s). Overall, analysis showed that the used downscaling technique with applying the COSMO-CLM model reproduced the meteorological conditions, spatial distribution, seasonal and synoptic variability of temperature and wind speed for the study area adequately. The dependences between reproduction quality of mesoscale atmospheric circulation features and the horizontal resolution of the model were revealed. In particular, it is shown that the use of 6 km resolution does not give any significant improvement comparing to 13 km resolution, whereas 2.2 km resolution provides an appreciable quality enhancement. Detailed synoptic analysis of extreme wind speed situations identified the main types of favorable to their genesis, associated with developing of cyclones over the Japan Islands or the Primorsky Kray of Russia, and penetration of intensified cyclones from Pacific Ocean through the Kamchatka peninsula, Kuril or Japan Islands. The obtained dataset will continue to be used for a full and comprehensive analysis of the reproduction quality of hydrometeorological fields, their statistical estimates, climatological trends and many other objectives.

An Analysis of the Multiple Objective Capital Budgeting Problem via Fuzzy Linear Integer (0-1) Programming.

DTIC Science & Technology

1980-05-31

34 International Journal of Man- Machine Studies , Vol. 9, No. 1, 1977, pp. 1-68. [16] Zimmermann, H. J., Theory and Applications of Fuzzy Sets, Institut...Boston, Inc., Hingham, MA, 1978. [18] Yager, R. R., "Multiple Objective Decision-Making Using Fuzzy Sets," International Journal of Man- Machine Studies ...Professor of Industria Engineering ... iv t TABLE OF CONTENTS page ABSTRACT .. .. . ...... . .... ...... ........ iii LIST OF TABLES

A new measuring machine in Paris

NASA Technical Reports Server (NTRS)

Guibert, J.; Charvin, P.

1984-01-01

A new photographic measuring machine is under construction at the Paris Observatory. The amount of transmitted light is measured by a linear array of 1024 photodiodes. Carriage control, data acquisition and on line processing are performed by microprocessors, a S.E.L. 32/27 computer, and an AP 120-B Array Processor. It is expected that a Schmidt telescope plate of size 360 mm square will be scanned in one hour with pixel size of ten microns.

Monocoil reciprocating permanent magnet electric machine with self-centering force

NASA Technical Reports Server (NTRS)

Bhate, Suresh K. (Inventor); Vitale, Nicholas G. (Inventor)

1989-01-01

A linear reciprocating machine has a tubular outer stator housing a coil, a plunger and an inner stator. The plunger has four axially spaced rings of radially magnetized permanent magnets which cooperate two at a time with the stator to complete first or second opposite magnetic paths. The four rings of magnets and the stators are arranged so that the stroke of the plunger is independent of the axial length of the coil.

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

DTIC Science & Technology

2013-01-02

Compilation JVM Java Virtual Machine KB Kilobyte KDT Knowledge Discovery Toolbox LAPACK Linear Algebra Package LLVM Low-Level Virtual Machine LOC Lines...different starting points. Leo Meyerovich also helped solidify some of the ideas here in discussions during Par Lab retreats. I would also like to thank...multi-timestep computations by blocking in both time and space. 88 Implementation Output Approx DSL Type Language Language Parallelism LoC Graphite

Influence of magnet eddy current on magnetization characteristics of variable flux memory machine

NASA Astrophysics Data System (ADS)

Yang, Hui; Lin, Heyun; Zhu, Z. Q.; Lyu, Shukang

2018-05-01

In this paper, the magnet eddy current characteristics of a newly developed variable flux memory machine (VFMM) is investigated. Firstly, the machine structure, non-linear hysteresis characteristics and eddy current modeling of low coercive force magnet are described, respectively. Besides, the PM eddy current behaviors when applying the demagnetizing current pulses are unveiled and investigated. The mismatch of the required demagnetization currents between the cases with or without considering the magnet eddy current is identified. In addition, the influences of the magnet eddy current on the demagnetization effect of VFMM are analyzed. Finally, a prototype is manufactured and tested to verify the theoretical analyses.

Energy-free machine learning force field for aluminum.

PubMed

Kruglov, Ivan; Sergeev, Oleg; Yanilkin, Alexey; Oganov, Artem R

2017-08-17

We used the machine learning technique of Li et al. (PRL 114, 2015) for molecular dynamics simulations. Atomic configurations were described by feature matrix based on internal vectors, and linear regression was used as a learning technique. We implemented this approach in the LAMMPS code. The method was applied to crystalline and liquid aluminum and uranium at different temperatures and densities, and showed the highest accuracy among different published potentials. Phonon density of states, entropy and melting temperature of aluminum were calculated using this machine learning potential. The results are in excellent agreement with experimental data and results of full ab initio calculations.

Center for Parallel Optimization.

DTIC Science & Technology

1996-03-19

A NEW OPTIMIZATION BASED APPROACH TO IMPROVING GENERALIZATION IN MACHINE LEARNING HAS BEEN PROPOSED AND COMPUTATIONALLY VALIDATED ON SIMPLE LINEAR MODELS AS WELL AS ON HIGHLY NONLINEAR SYSTEMS SUCH AS NEURAL NETWORKS.

Building "e-rater"® Scoring Models Using Machine Learning Methods. Research Report. ETS RR-16-04

ERIC Educational Resources Information Center

Chen, Jing; Fife, James H.; Bejar, Isaac I.; Rupp, André A.

2016-01-01

The "e-rater"® automated scoring engine used at Educational Testing Service (ETS) scores the writing quality of essays. In the current practice, e-rater scores are generated via a multiple linear regression (MLR) model as a linear combination of various features evaluated for each essay and human scores as the outcome variable. This…

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

Tsai, C. -Y.; Douglas, D.; Li, R.

Microbunching instability (MBI) has been one of the most challenging issues in designs of magnetic chicanes for short-wavelength free-electron lasers or linear colliders, as well as those of transport lines for recirculating or energy-recovery-linac machines. To quantify MBI for a recirculating machine and for more systematic analyses, we have recently developed a linear Vlasov solver and incorporated relevant collective effects into the code, including the longitudinal space charge, coherent synchrotron radiation, and linac geometric impedances, with extension of the existing formulation to include beam acceleration. In our code, we semianalytically solve the linearized Vlasov equation for microbunching amplification factor formore » an arbitrary linear lattice. In this study we apply our code to beam line lattices of two comparative isochronous recirculation arcs and one arc lattice preceded by a linac section. The resultant microbunching gain functions and spectral responses are presented, with some results compared to particle tracking simulation by elegant (M. Borland, APS Light Source Note No. LS-287, 2002). These results demonstrate clearly the impact of arc lattice design on the microbunching development. Lastly, the underlying physics with inclusion of those collective effects is elucidated and the limitation of the existing formulation is also discussed.« less

Koopman Operator Framework for Time Series Modeling and Analysis

NASA Astrophysics Data System (ADS)

Surana, Amit

2018-01-01

We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.

BLAS- BASIC LINEAR ALGEBRA SUBPROGRAMS

NASA Technical Reports Server (NTRS)

Krogh, F. T.

1994-01-01

The Basic Linear Algebra Subprogram (BLAS) library is a collection of FORTRAN callable routines for employing standard techniques in performing the basic operations of numerical linear algebra. The BLAS library was developed to provide a portable and efficient source of basic operations for designers of programs involving linear algebraic computations. The subprograms available in the library cover the operations of dot product, multiplication of a scalar and a vector, vector plus a scalar times a vector, Givens transformation, modified Givens transformation, copy, swap, Euclidean norm, sum of magnitudes, and location of the largest magnitude element. Since these subprograms are to be used in an ANSI FORTRAN context, the cases of single precision, double precision, and complex data are provided for. All of the subprograms have been thoroughly tested and produce consistent results even when transported from machine to machine. BLAS contains Assembler versions and FORTRAN test code for any of the following compilers: Lahey F77L, Microsoft FORTRAN, or IBM Professional FORTRAN. It requires the Microsoft Macro Assembler and a math co-processor. The PC implementation allows individual arrays of over 64K. The BLAS library was developed in 1979. The PC version was made available in 1986 and updated in 1988.

Integrating image quality in 2nu-SVM biometric match score fusion.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2007-10-01

This paper proposes an intelligent 2nu-support vector machine based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images. The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each subband of the image. The match score and the corresponding quality score of an image are fused using 2nu-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms.

A Novel Local Learning based Approach With Application to Breast Cancer Diagnosis

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

Xu, Songhua; Tourassi, Georgia

2012-01-01

The purpose of this study is to develop and evaluate a novel local learning-based approach for computer-assisted diagnosis of breast cancer. Our new local learning based algorithm using the linear logistic regression method as its base learner is described. Overall, our algorithm will perform its stochastic searching process until the total allowed computing time is used up by our random walk process in identifying the most suitable population subdivision scheme and their corresponding individual base learners. The proposed local learning-based approach was applied for the prediction of breast cancer given 11 mammographic and clinical findings reported by physicians using themore » BI-RADS lexicon. Our database consisted of 850 patients with biopsy confirmed diagnosis (290 malignant and 560 benign). We also compared the performance of our method with a collection of publicly available state-of-the-art machine learning methods. Predictive performance for all classifiers was evaluated using 10-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Figure 1 reports the performance of 54 machine learning methods implemented in the machine learning toolkit Weka (version 3.0). We introduced a novel local learning-based classifier and compared it with an extensive list of other classifiers for the problem of breast cancer diagnosis. Our experiments show that the algorithm superior prediction performance outperforming a wide range of other well established machine learning techniques. Our conclusion complements the existing understanding in the machine learning field that local learning may capture complicated, non-linear relationships exhibited by real-world datasets.« less

Modeling Dengue vector population using remotely sensed data and machine learning.

PubMed

Scavuzzo, Juan M; Trucco, Francisco; Espinosa, Manuel; Tauro, Carolina B; Abril, Marcelo; Scavuzzo, Carlos M; Frery, Alejandro C

2018-05-16

Mosquitoes are vectors of many human diseases. In particular, Aedes ægypti (Linnaeus) is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a global threat. Public health policies that aim at combating this vector require dependable and timely information, which is usually expensive to obtain with field campaigns. For this reason, several efforts have been done to use remote sensing due to its reduced cost. The present work includes the temporal modeling of the oviposition activity (measured weekly on 50 ovitraps in a north Argentinean city) of Aedes ægypti (Linnaeus), based on time series of data extracted from operational earth observation satellite images. We use are NDVI, NDWI, LST night, LST day and TRMM-GPM rain from 2012 to 2016 as predictive variables. In contrast to previous works which use linear models, we employ Machine Learning techniques using completely accessible open source toolkits. These models have the advantages of being non-parametric and capable of describing nonlinear relationships between variables. Specifically, in addition to two linear approaches, we assess a support vector machine, an artificial neural networks, a K-nearest neighbors and a decision tree regressor. Considerations are made on parameter tuning and the validation and training approach. The results are compared to linear models used in previous works with similar data sets for generating temporal predictive models. These new tools perform better than linear approaches, in particular nearest neighbor regression (KNNR) performs the best. These results provide better alternatives to be implemented operatively on the Argentine geospatial risk system that is running since 2012. Copyright © 2018 Elsevier B.V. All rights reserved.

Improving linear accelerator service response with a real- time electronic event reporting system.

PubMed

Hoisak, Jeremy D P; Pawlicki, Todd; Kim, Gwe-Ya; Fletcher, Richard; Moore, Kevin L

2014-09-08

To track linear accelerator performance issues, an online event recording system was developed in-house for use by therapists and physicists to log the details of technical problems arising on our institution's four linear accelerators. In use since October 2010, the system was designed so that all clinical physicists would receive email notification when an event was logged. Starting in October 2012, we initiated a pilot project in collaboration with our linear accelerator vendor to explore a new model of service and support, in which event notifications were also sent electronically directly to dedicated engineers at the vendor's technical help desk, who then initiated a response to technical issues. Previously, technical issues were reported by telephone to the vendor's call center, which then disseminated information and coordinated a response with the Technical Support help desk and local service engineers. The purpose of this work was to investigate the improvements to clinical operations resulting from this new service model. The new and old service models were quantitatively compared by reviewing event logs and the oncology information system database in the nine months prior to and after initiation of the project. Here, we focus on events that resulted in an inoperative linear accelerator ("down" machine). Machine downtime, vendor response time, treatment cancellations, and event resolution were evaluated and compared over two equivalent time periods. In 389 clinical days, there were 119 machine-down events: 59 events before and 60 after introduction of the new model. In the new model, median time to service response decreased from 45 to 8 min, service engineer dispatch time decreased 44%, downtime per event decreased from 45 to 20 min, and treatment cancellations decreased 68%. The decreased vendor response time and reduced number of on-site visits by a service engineer resulted in decreased downtime and decreased patient treatment cancellations.

Survey of beam instrumentation used in SLC

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

Ecklund, S.D.

A survey of beam instruments used at SLAC in the SLC machine is presented. The basic utility and operation of each device is briefly described. The various beam instruments used at the Stanford Linear Collider (SLC), can be classified by the function they perform. Beam intensity, position and size are typical of the parameters of beam which are measured. Each type of parameter is important for adjusting or tuning the machine in order to achieve optimum performance. 39 refs.

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE PAGES

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

2017-04-26

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Figure of merit for macrouniformity based on image quality ruler evaluation and machine learning framework

NASA Astrophysics Data System (ADS)

Wang, Weibao; Overall, Gary; Riggs, Travis; Silveston-Keith, Rebecca; Whitney, Julie; Chiu, George; Allebach, Jan P.

2013-01-01

Assessment of macro-uniformity is a capability that is important for the development and manufacture of printer products. Our goal is to develop a metric that will predict macro-uniformity, as judged by human subjects, by scanning and analyzing printed pages. We consider two different machine learning frameworks for the metric: linear regression and the support vector machine. We have implemented the image quality ruler, based on the recommendations of the INCITS W1.1 macro-uniformity team. Using 12 subjects at Purdue University and 20 subjects at Lexmark, evenly balanced with respect to gender, we conducted subjective evaluations with a set of 35 uniform b/w prints from seven different printers with five levels of tint coverage. Our results suggest that the image quality ruler method provides a reliable means to assess macro-uniformity. We then defined and implemented separate features to measure graininess, mottle, large area variation, jitter, and large-scale non-uniformity. The algorithms that we used are largely based on ISO image quality standards. Finally, we used these features computed for a set of test pages and the subjects' image quality ruler assessments of these pages to train the two different predictors - one based on linear regression and the other based on the support vector machine (SVM). Using five-fold cross-validation, we confirmed the efficacy of our predictor.

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

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

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

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

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

Synchronous machines have traditionally acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, with the increased integration of distributed renewable resources and energy-storage technologies, there is a need to systematically acknowledge the dynamics of power-electronics inverters - the primary energy-conversion interface in such systems - in all aspects of modeling, analysis, and control of the bulk power network. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator, three-phase inverter, and a load. The inverter model is formulatedmore » such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less

The HumanIndexMod and New Calculations Demonstrating Heat Stress Effects All Aspects of Human Life Through Industry, Agriculture, and Daily Life.

NASA Astrophysics Data System (ADS)

Buzan, J. R.; Huber, M.

2014-12-01

We show the new climatic tool, HumanIndexMod (HIM), for quantitatively assessing key climatic variables that are critical for decision making. The HIM calculates 9 different heat stress and 4 moist thermodynamic quantities using meteorological inputs of T, P, and Q. These heat stress metrics are commonly used throughout the world. We show new methods for integrating and standardizing practices for applying these metrics with the latest Earth system models. We implemented the HIM into CLM4.5, a component of CESM, maintained by NCAR. These heat stress metrics cover philosophical approaches of comfort, physiology, and empirically based algorithms. The metrics are directly connected to the Urban, Canopy, Bare Ground, and Lake modules, to differentiate distinct regimes within each grid cell. The module calculates the instantaneous moisture-temperature covariance at every model time step and in every land surface type, capturing all aspects of non-linearity. The HIM uses the most accurate and computationally efficient moist thermodynamic algorithms available. Additionally, we show ways that the HIM may be effectively integrated into climate modeling and observations. The module is flexible. The user may decide which metrics to call, and there is an offline version of the HIM that is available to be used with weather and climate datasets. Examples include using high temporal resolution CMIP5 archive data, local weather station data, and weather and forecasting models. To provide comprehensive standards for applying the HIM to climate data, we executed a CLM4.5 simulation using the RCP8.5 boundary conditions. Preliminary results show moist thermodynamic and heat stress quantities have smaller variability in the extremes as compared to extremes in T (both at the 95th percentile). Additionally, the magnitude of the moist thermodynamic changes over land is similar to sea surface temperature changes. The metric changes from the early part of the 21st century as compared to the end of the 21st century show that many portions of the world switch from moderate levels of heat stress for the top 2 weeks of a year to severe heat stress for the top 2 weeks of a year. These changes are reflected in livestock (THI); evaporative cooling (SWMP80) and air-conditioning; and industrial, military, and athletic heat stress (sWBGT, DI, HI, etc.).

Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics

PubMed Central

Belo, David; Gamboa, Hugo

2017-01-01

The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. The study evaluates the diagnostics possibilities of the arterial hypertension by means of the short-term heart rate variability signals. Two groups were studied: 30 relatively healthy volunteers and 40 patients suffering from the arterial hypertension of II-III degree. The following machine learning approaches were studied: linear and quadratic discriminant analysis, k-nearest neighbors, support vector machine with radial basis, decision trees, and naive Bayes classifier. Moreover, in the study, different methods of feature extraction are analyzed: statistical, spectral, wavelet, and multifractal. All in all, 53 features were investigated. Investigation results show that discriminant analysis achieves the highest classification accuracy. The suggested approach of noncorrelated feature set search achieved higher results than data set based on the principal components. PMID:28831239

An implementation of support vector machine on sentiment classification of movie reviews

NASA Astrophysics Data System (ADS)

Yulietha, I. M.; Faraby, S. A.; Adiwijaya; Widyaningtyas, W. C.

2018-03-01

With technological advances, all information about movie is available on the internet. If the information is processed properly, it will get the quality of the information. This research proposes to the classify sentiments on movie review documents. This research uses Support Vector Machine (SVM) method because it can classify high dimensional data in accordance with the data used in this research in the form of text. Support Vector Machine is a popular machine learning technique for text classification because it can classify by learning from a collection of documents that have been classified previously and can provide good result. Based on number of datasets, the 90-10 composition has the best result that is 85.6%. Based on SVM kernel, kernel linear with constant 1 has the best result that is 84.9%

Remote sensing of thermal radiation from an aircraft - An analysis and evaluation of crop-freeze protection methods

NASA Technical Reports Server (NTRS)

Sutherland, R. A.; Hannah, H. E.; Cook, A. F.; Martsolf, J. D.

1981-01-01

Thermal images from an aircraft-mounted scanner are used to evaluate the effectiveness of crop-freeze protection devices. Data from flights made while using fuel oil heaters, a wind machine and an undercanopy irrigation system are compared. Results show that the overall protection provided by irrigation (at approximately 2 C) is comparable to the less energy-efficient heater-wind machine combination. Protection provided by the wind machine alone (at approximately 1 C) was found to decrease linearly with distance from the machine by approximately 1 C/100 m. The flights were made over a 1.5 hectare citrus grove at an altitude of 450 m with an 8-14 micron detector. General meteorological conditions during the experiments, conducted during the nighttime, were cold (at approximately -6 C) and calm with clear skies.

Machine learning in the string landscape

NASA Astrophysics Data System (ADS)

Carifio, Jonathan; Halverson, James; Krioukov, Dmitri; Nelson, Brent D.

2017-09-01

We utilize machine learning to study the string landscape. Deep data dives and conjecture generation are proposed as useful frameworks for utilizing machine learning in the landscape, and examples of each are presented. A decision tree accurately predicts the number of weak Fano toric threefolds arising from reflexive polytopes, each of which determines a smooth F-theory compactification, and linear regression generates a previously proven conjecture for the gauge group rank in an ensemble of 4/3× 2.96× {10}^{755} F-theory compactifications. Logistic regression generates a new conjecture for when E 6 arises in the large ensemble of F-theory compactifications, which is then rigorously proven. This result may be relevant for the appearance of visible sectors in the ensemble. Through conjecture generation, machine learning is useful not only for numerics, but also for rigorous results.

Analysis and comparison of end effects in linear switched reluctance and hybrid motors

NASA Astrophysics Data System (ADS)

Barhoumi, El Manaa; Abo-Khalil, Ahmed Galal; Berrouche, Youcef; Wurtz, Frederic

2017-03-01

This paper presents and discusses the longitudinal and transversal end effects which affects the propulsive force of linear motors. Generally, the modeling of linear machine considers the forces distortion due to the specific geometry of linear actuators. The insertion of permanent magnets on the stator allows improving the propulsive force produced by switched reluctance linear motors. Also, the inserted permanent magnets in the hybrid structure allow reducing considerably the ends effects observed in linear motors. The analysis was conducted using 2D and 3D finite elements method. The permanent magnet reinforces the flux produced by the winding and reorients it which allows modifying the impact of end effects. Presented simulations and discussions show the importance of this study to characterize the end effects in two different linear motors.

Controlling Continuous-Variable Quantum Key Distribution with Entanglement in the Middle Using Tunable Linear Optics Cloning Machines

NASA Astrophysics Data System (ADS)

Wu, Xiao Dong; Chen, Feng; Wu, Xiang Hua; Guo, Ying

2017-02-01

Continuous-variable quantum key distribution (CVQKD) can provide detection efficiency, as compared to discrete-variable quantum key distribution (DVQKD). In this paper, we demonstrate a controllable CVQKD with the entangled source in the middle, contrast to the traditional point-to-point CVQKD where the entanglement source is usually created by one honest party and the Gaussian noise added on the reference partner of the reconciliation is uncontrollable. In order to harmonize the additive noise that originates in the middle to resist the effect of malicious eavesdropper, we propose a controllable CVQKD protocol by performing a tunable linear optics cloning machine (LOCM) at one participant's side, say Alice. Simulation results show that we can achieve the optimal secret key rates by selecting the parameters of the tuned LOCM in the derived regions.

A Prototype SSVEP Based Real Time BCI Gaming System

PubMed Central

Martišius, Ignas

2016-01-01

Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel. PMID:27051414

Balancing Vibrations at Harmonic Frequencies by Injecting Harmonic Balancing Signals into the Armature of a Linear Motor/Alternator Coupled to a Stirling Machine

NASA Technical Reports Server (NTRS)

Holliday, Ezekiel S. (Inventor)

2014-01-01

Vibrations at harmonic frequencies are reduced by injecting harmonic balancing signals into the armature of a linear motor/alternator coupled to a Stirling machine. The vibrations are sensed to provide a signal representing the mechanical vibrations. A harmonic balancing signal is generated for selected harmonics of the operating frequency by processing the sensed vibration signal with adaptive filter algorithms of adaptive filters for each harmonic. Reference inputs for each harmonic are applied to the adaptive filter algorithms at the frequency of the selected harmonic. The harmonic balancing signals for all of the harmonics are summed with a principal control signal. The harmonic balancing signals modify the principal electrical drive voltage and drive the motor/alternator with a drive voltage component in opposition to the vibration at each harmonic.

Comparative decision models for anticipating shortage of food grain production in India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Manojit; Mitra, Subrata Kumar

2018-01-01

This paper attempts to predict food shortages in advance from the analysis of rainfall during the monsoon months along with other inputs used for crop production, such as land used for cereal production, percentage of area covered under irrigation and fertiliser use. We used six binary classification data mining models viz., logistic regression, Multilayer Perceptron, kernel lab-Support Vector Machines, linear discriminant analysis, quadratic discriminant analysis and k-Nearest Neighbors Network, and found that linear discriminant analysis and kernel lab-Support Vector Machines are equally suitable for predicting per capita food shortage with 89.69 % accuracy in overall prediction and 92.06 % accuracy in predicting food shortage ( true negative rate). Advance information of food shortage can help policy makers to take remedial measures in order to prevent devastating consequences arising out of food non-availability.

A Prototype SSVEP Based Real Time BCI Gaming System.

PubMed

Martišius, Ignas; Damaševičius, Robertas

2016-01-01

Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel.

High Strength P/M Gears for Vehicle Transmissions - Phase 2

DTIC Science & Technology

2008-08-15

and while it was considered amenable to standard work material transfer ("blue steel" chutes for example) from other P/M processing equipment, no...depend of the machine design but should be kept to a minimum in order to minimize part transfer times. Position control of the linear axis is...Establish design of ausform gear finishing machine for P/M gears: The "Focus" part identified in phase I (New Process Planet gear P/N 17864, component

Linear-hall sensor based force detecting unit for lower limb exoskeleton

NASA Astrophysics Data System (ADS)

Li, Hongwu; Zhu, Yanhe; Zhao, Jie; Wang, Tianshuo; Zhang, Zongwei

2018-04-01

This paper describes a knee-joint human-machine interaction force sensor for lower-limb force-assistance exoskeleton. The structure is designed based on hall sensor and series elastic actuator (SEA) structure. The work we have done includes the structure design, the parameter determination and dynamic simulation. By converting the force signal into macro displacement and output voltage, we completed the measurement of man-machine interaction force. And it is proved by experiments that the design is simple, stable and low-cost.

Developing Test Apparatus and Measurements of AC Loss of High Temperature Superconductors

DTIC Science & Technology

2012-11-01

temperature of the coil is not raised significantly. The second system, a larger machine, designed with a long term prospective to serve a test bed for...four sample chambers inside the vacuum gap, LN2 – cooled sample holder (currently only one is in use), the laminated back iron, and the outer shell...machine. accommodate a variety of different small coils and linear tapes. This assembly is surrounded by the laminated back iron and the outer shell

Anytime query-tuned kernel machine classifiers via Cholesky factorization

NASA Technical Reports Server (NTRS)

DeCoste, D.

2002-01-01

We recently demonstrated 2 to 64-fold query-time speedups of Support Vector Machine and Kernel Fisher classifiers via a new computational geometry method for anytime output bounds (DeCoste,2002). This new paper refines our approach in two key ways. First, we introduce a simple linear algebra formulation based on Cholesky factorization, yielding simpler equations and lower computational overhead. Second, this new formulation suggests new methods for achieving additional speedups, including tuning on query samples. We demonstrate effectiveness on benchmark datasets.

Error compensation for thermally induced errors on a machine tool

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

Krulewich, D.A.

1996-11-08

Heat flow from internal and external sources and the environment create machine deformations, resulting in positioning errors between the tool and workpiece. There is no industrially accepted method for thermal error compensation. A simple model has been selected that linearly relates discrete temperature measurements to the deflection. The biggest problem is how to locate the temperature sensors and to determine the number of required temperature sensors. This research develops a method to determine the number and location of temperature measurements.

Comparing crop growth and carbon budgets simulated across AmeriFlux agricultural sites using the community land model (CLM)

USDA-ARS?s Scientific Manuscript database

Improving process-based crop models is needed to achieve high fidelity forecasts of regional energy, water, and carbon exchange. However, most state-of-the-art Land Surface Models (LSMs) assessed in the fifth phase of the Coupled Model Inter-comparison project (CMIP5) simulated crops as simple C3 or...

Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River Basin

NASA Technical Reports Server (NTRS)

Long, Di; Yang, Yuting; Yoshihide, Wada; Hong, Yang; Liang, Wei; Chen, Yaning; Yong, Bin; Hou, Aizhong; Wei, Jiangfeng; Chen, Lu

2015-01-01

This study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.

Curcuma longa and Curcuma mangga leaves exhibit functional food property.

PubMed

Liu, Yunbao; Nair, Muraleedharan G

2012-11-15

Although leaves of Curcuma mangga and Curcuma longa are used in food preparations, the bioactive components in it are not known. In this study, antioxidant, antiinflammatory and anticancer activities of leave extracts and its isolates were investigated using established bioassay procedures in our laboratory. The leaf extracts of both plants gave similar bioassay and chromatographic profiles. The methanolic and water extracts of C. mangga (CMM and CMW) and C. longa (CLM and CLW), at 100 μg/mL, inhibited lipid peroxidation (LPO) by 78%, 63%, 81% and 43%, cyclooxygenase enzymes COX-1 by 55%, 33%, 43% and 24% and COX-2 by 65%, 55%, 77% and 69%, respectively. At same concentration, CMM, CMW, CLM and CLW showed growth inhibition of human tumour cell lines by 0-46%. Therefore, a bioassay-guided isolation of water and methanolic extracts of C. longa was carried out and afforded nine isolates. At 25 μg/mL, these compounds inhibited LPO by 11-87%, COX-1 and -2 enzymes by 0-35% and 0-82% and growth of human tumour cells by 0-36%, respectively. Copyright © 2012 Elsevier Ltd. All rights reserved.

The study on the nanomachining property and cutting model of single-crystal sapphire by atomic force microscopy.

PubMed

Huang, Jen-Ching; Weng, Yung-Jin

2014-01-01

This study focused on the nanomachining property and cutting model of single-crystal sapphire during nanomachining. The coated diamond probe is used to as a tool, and the atomic force microscopy (AFM) is as an experimental platform for nanomachining. To understand the effect of normal force on single-crystal sapphire machining, this study tested nano-line machining and nano-rectangular pattern machining at different normal force. In nano-line machining test, the experimental results showed that the normal force increased, the groove depth from nano-line machining also increased. And the trend is logarithmic type. In nano-rectangular pattern machining test, it is found when the normal force increases, the groove depth also increased, but rather the accumulation of small chips. This paper combined the blew by air blower, the cleaning by ultrasonic cleaning machine and using contact mode probe to scan the surface topology after nanomaching, and proposed the "criterion of nanomachining cutting model," in order to determine the cutting model of single-crystal sapphire in the nanomachining is ductile regime cutting model or brittle regime cutting model. After analysis, the single-crystal sapphire substrate is processed in small normal force during nano-linear machining; its cutting modes are ductile regime cutting model. In the nano-rectangular pattern machining, due to the impact of machined zones overlap, the cutting mode is converted into a brittle regime cutting model. © 2014 Wiley Periodicals, Inc.

New concept for in-line OLED manufacturing

NASA Astrophysics Data System (ADS)

Hoffmann, U.; Landgraf, H.; Campo, M.; Keller, S.; Koening, M.

2011-03-01

A new concept of a vertical In-Line deposition machine for large area white OLED production has been developed. The concept targets manufacturing on large substrates (>= Gen 4, 750 x 920 mm2) using linear deposition source achieving a total material utilization of >= 50 % and tact time down to 80 seconds. The continuously improved linear evaporation sources for the organic material achieve thickness uniformity on Gen 4 substrate of better than +/- 3 % and stable deposition rates down to less than 0.1 nm m/min and up to more than 100 nm m/min. For Lithium-Fluoride but also for other high evaporation temperature materials like Magnesium or Silver a linear source with uniformity better than +/- 3 % has been developed. For Aluminum we integrated a vertical oriented point source using wire feed to achieve high (> 150 nm m/min) and stable deposition rates. The machine concept includes a new vertical vacuum handling and alignment system for Gen 4 shadow masks. A complete alignment cycle for the mask can be done in less than one minute achieving alignment accuracy in the range of several 10 μm.

Four-point bend apparatus for in situ micro-Raman stress measurements

NASA Astrophysics Data System (ADS)

Ward, Shawn H.; Mann, Adrian B.

2018-06-01

A device for in situ use with a micro-Raman microscope to determine stress from the Raman peak position was designed and validated. The device is a four-point bend machine with a micro-stepping motor and load cell, allowing for fine movement and accurate readings of the applied force. The machine has a small footprint and easily fits on most optical microscope stages. The results obtained from silicon are in good agreement with published literature values for the linear relationship between stress and peak position for the 520.8 cm‑1 Raman peak. The device was used to examine 4H–SiC and a good linear relationship was found between the 798 cm‑1 Raman peak position and stress, with the proportionality coefficient being close to the theoretical value of 0.0025. The 777 cm‑1 Raman peak also showed a linear dependence on stress, but the dependence was not as strong. The device examines both the tensile and compressive sides of the beam in bending, granting the potential for many materials and crystal orientations to be examined.

Alternate approaches to future electron-positron linear colliders

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

Loew, G.A.

1998-07-01

The purpose of this article is two-fold: to review the current international status of various design approaches to the next generation of e{sup +}e{sup {minus}} linear colliders, and on the occasion of his 80th birthday, to celebrate Richard B. Neal`s many contributions to the field of linear accelerators. As it turns out, combining these two tasks is a rather natural enterprise because of Neal`s long professional involvement and insight into many of the problems and options which the international e{sup +}e{sup {minus}} linear collider community is currently studying to achieve a practical design for a future machine.

Collaborative Project: Understanding Climate Model Biases in Tropical Atlantic and Their Impact on Simulations of Extreme Climate Events

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

Chang, Ping

Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biasesmore » in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model development effort will be to optimize the performance of WRF and ROMS over several thousand of cores by focusing on both the parallel communication libraries and the I/O interfaces, in order to achieve the sustained throughput needed to perform simulations on such fine resolution grids. The CRCM model will be developed within the framework of the Coupler (CPL7) software that is part of the NCAR Community Earth System Model (CESM). Through efforts at PNNL and within the community, WRF and CLM have already been coupled via CPL7. Using the flux coupler approach for the whole CRCM model will allow us to flexibly couple WRF, ROMS, and CLM with each model running on its own grid at different resolutions. In addition, this framework will allow us to easily port parameterizations between CESM and the CRCM, and potentially allow partial coupling between the CESM and the CRCM. TAMU and PNNL will contribute cooperatively to this research endeavor. The TAMU team led by Chang and Saravanan has considerable experience in studying atmosphere-ocean interactions within tropical Atlantic sector and will focus on modeling issues that relate to coupling WRF and ROMS. The PNNL team led by Leung has extensive expertise in atmosphere-land interaction and will be responsible for improving the land surface parameterization. Both teams will jointly work on integrating WRF-ROMS and WRF-CLM to couple WRF, ROMS, and CLM through CPL7. Montuoro of the TAMU Supercomputing Center will be responsible for improving the MPI and Parallel IO interfaces of the CRCM. Both teams will contribute to the design and execution of the proposed numerical experiments and jointly perform analysis of the numerical experiments.« less

Mamdani-Fuzzy Modeling Approach for Quality Prediction of Non-Linear Laser Lathing Process

NASA Astrophysics Data System (ADS)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Lathing is a process to fashioning stock materials into desired cylindrical shapes which usually performed by traditional lathe machine. But, the recent rapid advancements in engineering materials and precision demand gives a great challenge to the traditional method. The main drawback of conventional lathe is its mechanical contact which brings to the undesirable tool wear, heat affected zone, finishing, and dimensional accuracy especially taper quality in machining of stock with high length to diameter ratio. Therefore, a novel approach has been devised to investigate in transforming a 2D flatbed CO2 laser cutting machine into 3D laser lathing capability as an alternative solution. Three significant design parameters were selected for this experiment, namely cutting speed, spinning speed, and depth of cut. Total of 24 experiments were performed with eight (8) sequential runs where they were then replicated three (3) times. The experimental results were then used to establish Mamdani - Fuzzy predictive model where it yields the accuracy of more than 95%. Thus, the proposed Mamdani - Fuzzy modelling approach is found very much suitable and practical for quality prediction of non-linear laser lathing process for cylindrical stocks of 10mm diameter.

Full-motion video analysis for improved gender classification

NASA Astrophysics Data System (ADS)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables

NASA Astrophysics Data System (ADS)

Taha, Zahari; Muazu Musa, Rabiu; Majeed, Anwar P. P. Abdul; Razali Abdullah, Mohamad; Amirul Abdullah, Muhammad; Hasnun Arif Hassan, Mohd; Khalil, Zubair

2018-04-01

The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of bio-physiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from various archery programmes completed a one end shooting score test. The bio-physiological variables namely resting heart rate, resting respiratory rate, resting diastolic blood pressure, resting systolic blood pressure, as well as calories intake, were measured prior to their shooting tests. k-means cluster analysis was applied to cluster the archers based on their scores on variables assessed. SVM models i.e. linear, quadratic and cubic kernel functions, were trained on the aforementioned variables. The k-means clustered the archers into high (HPA) and low potential archers (LPA), respectively. It was demonstrated that the linear SVM exhibited good accuracy with a classification accuracy of 94% in comparison the other tested models. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected bio-physiological variables examined.

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

PubMed

Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

2016-06-02

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Development and Implementation of a Simplified Tool Measuring System

NASA Astrophysics Data System (ADS)

Chen, Jenn-Yih; Lee, Bean-Yin; Lee, Kuang-Chyi; Chen, Zhao-Kai

2010-01-01

This paper presents a simplified system for measuring geometric profiles of end mills. Firstly, a CCD camera was used to capture images of cutting tools. Then, an image acquisition card with the encoding function was adopted to convert the source of image into an USB port of a PC, and the image could be shown on a monitor. In addition, two linear scales were mounted on the X-Y table for positioning and measuring purposes. The signals of the linear scales were transmitted into a 4-axis quadrature encoder with 4-channel counter card for position monitoring. The C++ Builder was utilized for designing the user friendly human machine interface of the measuring system of tools. There is a cross line on the image of the interface to show a coordinate for the position measurement. Finally, a well-known tool measuring and inspection machine was employed for the measuring standard. This study compares the difference of the measuring results by using the machine and the proposed system. Experimental results show that the percentage of measuring error is acceptable for some geometric parameters of the square or ball nose end mills. Therefore, the results demonstrate the effectiveness of the presented approach.

Dynamics of the process boom machine working equipment under the real law of the hydraulic distributor electric spool control

NASA Astrophysics Data System (ADS)

Tarasov, V. N.; Boyarkina, I. V.

2017-06-01

Analytical calculation methods of dynamic processes of the self-propelled boom hydraulic machines working equipment are more preferable in comparison with numerical methods. The analytical research method of dynamic processes of the boom hydraulic machines working equipment by means of differential equations of acceleration and braking of the working equipment is proposed. The real control law of a hydraulic distributor electric spool is considered containing the linear law of the electric spool activation and stepped law of the electric spool deactivation. Dependences of dynamic processes of the working equipment on reduced mass, stiffness of hydraulic power cylinder, viscous drag coefficient, piston acceleration, pressure in hydraulic cylinders, inertia force are obtained. Definite recommendations relative to the reduction of dynamic loads, appearing during the working equipment control are considered as the research result. The nature and rate of parameter variations of the speed and piston acceleration dynamic process depend on the law of the ports opening and closure of the hydraulic distributor electric spool. Dynamic loads in the working equipment are decreased during a smooth linear activation of the hydraulic distributor electric spool.

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

DiCostanzo, D; Ayan, A; Woollard, J

Purpose: To predict potential failures of hardware within the Varian TrueBeam linear accelerator in order to proactively replace parts and decrease machine downtime. Methods: Machine downtime is a problem for all radiation oncology departments and vendors. Most often it is the result of unexpected equipment failure, and increased due to lack of in-house clinical engineering support. Preventative maintenance attempts to assuage downtime, but often is ineffective at preemptively preventing many failure modes such as MLC motor failures, the need to tighten a gantry chain, or the replacement of a jaw motor, among other things. To attempt to alleviate downtime, softwaremore » was developed in house that determines the maximum value of each axis enumerated in the Truebeam trajectory log files. After patient treatments, this data is stored in a SQL database. Microsoft Power BI is used to plot the average maximum error of each day of each machine as a function of time. The results are then correlated with actual faults that occurred at the machine with the help of Varian service engineers. Results: Over the course of six months, 76,312 trajectory logs have been written into the database and plotted in Power BI. Throughout the course of analysis MLC motors have been replaced on three machines due to the early warning of the trajectory log analysis. The service engineers have also been alerted to possible gantry issues on one occasion due to the aforementioned analysis. Conclusion: Analyzing the trajectory log data is a viable and effective early warning system for potential failures of the TrueBeam linear accelerator. With further analysis and tightening of the tolerance values used to determine a possible imminent failure, it should be possible to pinpoint future issues more thoroughly and for more axes of motion.« less

Coupling machine learning with mechanistic models to study runoff production and river flow at the hillslope scale

NASA Astrophysics Data System (ADS)

Marçais, J.; Gupta, H. V.; De Dreuzy, J. R.; Troch, P. A. A.

2016-12-01

Geomorphological structure and geological heterogeneity of hillslopes are major controls on runoff responses. The diversity of hillslopes (morphological shapes and geological structures) on one hand, and the highly non linear runoff mechanism response on the other hand, make it difficult to transpose what has been learnt at one specific hillslope to another. Therefore, making reliable predictions on runoff appearance or river flow for a given hillslope is a challenge. Applying a classic model calibration (based on inverse problems technique) requires doing it for each specific hillslope and having some data available for calibration. When applied to thousands of cases it cannot always be promoted. Here we propose a novel modeling framework based on coupling process based models with data based approach. First we develop a mechanistic model, based on hillslope storage Boussinesq equations (Troch et al. 2003), able to model non linear runoff responses to rainfall at the hillslope scale. Second we set up a model database, representing thousands of non calibrated simulations. These simulations investigate different hillslope shapes (real ones obtained by analyzing 5m digital elevation model of Brittany and synthetic ones), different hillslope geological structures (i.e. different parametrizations) and different hydrologic forcing terms (i.e. different infiltration chronicles). Then, we use this model library to train a machine learning model on this physically based database. Machine learning model performance is then assessed by a classic validating phase (testing it on new hillslopes and comparing machine learning with mechanistic outputs). Finally we use this machine learning model to learn what are the hillslope properties controlling runoffs. This methodology will be further tested combining synthetic datasets with real ones.

Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach.

PubMed

Le, Laetitia Minh Maï; Kégl, Balázs; Gramfort, Alexandre; Marini, Camille; Nguyen, David; Cherti, Mehdi; Tfaili, Sana; Tfayli, Ali; Baillet-Guffroy, Arlette; Prognon, Patrice; Chaminade, Pierre; Caudron, Eric

2018-07-01

The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300 data scientists in collaborative work. Using machine learning, the prediction of the four mAbs samples was considerably improved. The best predictive model showed a combined error of 2.4% versus 14.6% using linear approach. The concentration and classification errors were 5.8% and 0.7%, only three spectra were misclassified over the 429 spectra of the test set. This large improvement obtained with machine learning techniques was uniform for all molecules but maximal for Bevacizumab with an 88.3% reduction on combined errors (2.1% versus 17.9%). Copyright © 2018 Elsevier B.V. All rights reserved.

Cobalt-60 Machines and Medical Linear Accelerators: Competing Technologies for External Beam Radiotherapy.

PubMed

Healy, B J; van der Merwe, D; Christaki, K E; Meghzifene, A

2017-02-01

Medical linear accelerators (linacs) and cobalt-60 machines are both mature technologies for external beam radiotherapy. A comparison is made between these two technologies in terms of infrastructure and maintenance, dosimetry, shielding requirements, staffing, costs, security, patient throughput and clinical use. Infrastructure and maintenance are more demanding for linacs due to the complex electric componentry. In dosimetry, a higher beam energy, modulated dose rate and smaller focal spot size mean that it is easier to create an optimised treatment with a linac for conformal dose coverage of the tumour while sparing healthy organs at risk. In shielding, the requirements for a concrete bunker are similar for cobalt-60 machines and linacs but extra shielding and protection from neutrons are required for linacs. Staffing levels can be higher for linacs and more staff training is required for linacs. Life cycle costs are higher for linacs, especially multi-energy linacs. Security is more complex for cobalt-60 machines because of the high activity radioactive source. Patient throughput can be affected by source decay for cobalt-60 machines but poor maintenance and breakdowns can severely affect patient throughput for linacs. In clinical use, more complex treatment techniques are easier to achieve with linacs, and the availability of electron beams on high-energy linacs can be useful for certain treatments. In summary, there is no simple answer to the question of the choice of either cobalt-60 machines or linacs for radiotherapy in low- and middle-income countries. In fact a radiotherapy department with a combination of technologies, including orthovoltage X-ray units, may be an option. Local needs, conditions and resources will have to be factored into any decision on technology taking into account the characteristics of both forms of teletherapy, with the primary goal being the sustainability of the radiotherapy service over the useful lifetime of the equipment. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy.

PubMed

Pande, Amit; Mohapatra, Prasant; Nicorici, Alina; Han, Jay J

2016-07-19

Children with physical impairments are at a greater risk for obesity and decreased physical activity. A better understanding of physical activity pattern and energy expenditure (EE) would lead to a more targeted approach to intervention. This study focuses on studying the use of machine-learning algorithms for EE estimation in children with disabilities. A pilot study was conducted on children with Duchenne muscular dystrophy (DMD) to identify important factors for determining EE and develop a novel algorithm to accurately estimate EE from wearable sensor-collected data. There were 7 boys with DMD, 6 healthy control boys, and 22 control adults recruited. Data were collected using smartphone accelerometer and chest-worn heart rate sensors. The gold standard EE values were obtained from the COSMED K4b2 portable cardiopulmonary metabolic unit worn by boys (aged 6-10 years) with DMD and controls. Data from this sensor setup were collected simultaneously during a series of concurrent activities. Linear regression and nonlinear machine-learning-based approaches were used to analyze the relationship between accelerometer and heart rate readings and COSMED values. Existing calorimetry equations using linear regression and nonlinear machine-learning-based models, developed for healthy adults and young children, give low correlation to actual EE values in children with disabilities (14%-40%). The proposed model for boys with DMD uses ensemble machine learning techniques and gives a 91% correlation with actual measured EE values (root mean square error of 0.017). Our results confirm that the methods developed to determine EE using accelerometer and heart rate sensor values in normal adults are not appropriate for children with disabilities and should not be used. A much more accurate model is obtained using machine-learning-based nonlinear regression specifically developed for this target population. ©Amit Pande, Prasant Mohapatra, Alina Nicorici, Jay J Han. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org), 19.07.2016.

Linear Optimization and Image Reconstruction

DTIC Science & Technology

1994-06-01

final example is again a novel one. We formulate the problem of computer assisted tomographic ( CAT ) image reconstruction as a linear optimization...possibility that a patient, Fred, suffers from a brain tumor. Further, the physician opts to make use of the CAT (Computer Aided Tomography) scan device...and examine the inside of Fred’s head without exploratory surgery. The CAT scan machine works by projecting a finite number of X-rays of known

Physics Notes.

ERIC Educational Resources Information Center

School Science Review, 1982

1982-01-01

Outlines methodology, demonstrations, and materials including: an inexpensive wave machine; speed of sound in carbon dioxide; diffraction grating method for measuring spectral line wavelength; linear electronic thermometer; analogy for bromine diffusion; direct reading refractice index meter; inexpensive integrated circuit spectrophotometer; and…

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

PubMed Central

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-01-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

Nonlinear programming for classification problems in machine learning

NASA Astrophysics Data System (ADS)

Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio

2016-10-01

We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.

Strike action electromagnetic machine for immersion of rod elements into ground

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Chetverikov, E. A.; Kargin, V. A.; Moiseev, A. P.; Ivanova, Z. I.

2017-10-01

During construction, survey work, and drilling shallow wells by striking, operations associated with dipping and removing the rod elements are the most common. At the same time relatively long, with small diameter, elements, in which the ratio of length to diameter l/d is 100 or more, constitute a significant proportion. At present, the application of power pulse linear electromagnetic motors to drive drum machines is recognized to be highly effective. However, the mechanical method of transmission of shocks does not allow dipping long longitudinally unstable core elements. In this case, mechanical energy must be transferred from the motor to the rod through its side surface. The design of the strike action electromagnetic machine with a through axial channel for non-mechanical end striking of the pile of long, longitudinally unstable metal rods is proposed. Electromagnetic striking machine for non-mechanical end striking rod elements provides operations characterized by ecological compatibility, safety and high quality.

Stirling cryocooler test results and design model verification

NASA Astrophysics Data System (ADS)

Shimko, Martin A.; Stacy, W. D.; McCormick, John A.

A long-life Stirling cycle cryocooler being developed for spaceborne applications is described. The results from tests on a preliminary breadboard version of the cryocooler used to demonstrate the feasibility of the technology and to validate the generator design code used in its development are presented. This machine achieved a cold-end temperature of 65 K while carrying a 1/2-W cooling load. The basic machine is a double-acting, flexure-bearing, split Stirling design with linear electromagnetic drives for the expander and compressors. Flat metal diaphragms replace pistons for sweeping and sealing the machine working volumes. The double-acting expander couples to a laminar-channel counterflow recuperative heat exchanger for regeneration. The PC-compatible design code developed for this design approach calculates regenerator loss, including heat transfer irreversibilities, pressure drop, and axial conduction in the regenerator walls. The code accurately predicted cooler performance and assisted in diagnosing breadboard machine flaws during shakedown and development testing.

Design and analysis of linear cascade DNA hybridization chain reactions using DNA hairpins

NASA Astrophysics Data System (ADS)

Bui, Hieu; Garg, Sudhanshu; Miao, Vincent; Song, Tianqi; Mokhtar, Reem; Reif, John

2017-01-01

DNA self-assembly has been employed non-conventionally to construct nanoscale structures and dynamic nanoscale machines. The technique of hybridization chain reactions by triggered self-assembly has been shown to form various interesting nanoscale structures ranging from simple linear DNA oligomers to dendritic DNA structures. Inspired by earlier triggered self-assembly works, we present a system for controlled self-assembly of linear cascade DNA hybridization chain reactions using nine distinct DNA hairpins. NUPACK is employed to assist in designing DNA sequences and Matlab has been used to simulate DNA hairpin interactions. Gel electrophoresis and ensemble fluorescence reaction kinetics data indicate strong evidence of linear cascade DNA hybridization chain reactions. The half-time completion of the proposed linear cascade reactions indicates a linear dependency on the number of hairpins.

The Carbon-Land Model Intercomparison Project (C-LAMP): A Model-Data Comparison System for Evaluation of Coupled Biosphere-Atmosphere Models

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

Hoffman, Forrest M; Randerson, Jim; Thornton, Peter E

2009-01-01

The need to capture important climate feebacks in general circulation models (GCMs) has resulted in new efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, now often referred to as Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results, suggesting that a more rigorous set of offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are warranted. The Carbon-Land Model Intercomparison Project (C-LAMP) providesmore » a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). C-LAMP provides feedback to the modeling community regarding model improvements and to the measurement community by suggesting new observational campaigns. C-LAMP Experiment 1 consists of a set of uncoupled simulations of terrestrial carbon models specifically designed to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to exhibit the influence of climate variability, prescribed atmospheric carbon dioxide (CO{sub 2}), nitrogen (N) deposition, and land cover change on projections of terrestrial carbon fluxes during the 20th century. Experiment 2 consists of partially coupled simulations of the terrestrial carbon model with an active atmosphere model exchanging energy and moisture fluxes. In all experiments, atmospheric CO{sub 2} follows the prescribed historical trajectory from C{sup 4}MIP. In Experiment 2, the atmosphere model is forced with prescribed sea surface temperatures (SSTs) and corresponding sea ice concentrations from the Hadley Centre; prescribed CO{sub 2} is radiatively active; and land, fossil fuel, and ocean CO{sub 2} fluxes are advected by the model. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the Community Land Model version 3 (CLM3) in the Community Climate System Model version 3 (CCSM3): The CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons against Ameriflus site measurements, MODIS satellite observations, NOAA flask records, TRANSCOM inversions, and Free Air CO{sub 2} Enrichment (FACE) site measurements, and other datasets have been performed and are described in Randerson et al. (2009). The C-LAMP diagnostics package was used to validate improvements to CASA and CN for use in the next generation model, CLM4. It is hoped that this effort will serve as a prototype for an international carbon-cycle model benchmarking activity for models being used for the Inter-governmental Panel on Climate Change (IPCC) Fifth Assessment Report. More information about C-LAMP, the experimental protocol, performance metrics, output standards, and model-data comparisons from the CLM3-CASA and CLM3-CN models are available at http://www.climatemodeling.org/c-lamp.« less

Maternal exposure to ambient PM10 during pregnancy increases the risk of congenital heart defects: Evidence from machine learning models.

PubMed

Ren, Zhoupeng; Zhu, Jun; Gao, Yanfang; Yin, Qian; Hu, Maogui; Dai, Li; Deng, Changfei; Yi, Lin; Deng, Kui; Wang, Yanping; Li, Xiaohong; Wang, Jinfeng

2018-07-15

Previous research suggested an association between maternal exposure to ambient air pollutants and risk of congenital heart defects (CHDs), though the effects of particulate matter ≤10μm in aerodynamic diameter (PM 10 ) on CHDs are inconsistent. We used two machine learning models (i.e., random forest (RF) and gradient boosting (GB)) to investigate the non-linear effects of PM 10 exposure during the critical time window, weeks 3-8 in pregnancy, on risk of CHDs. From 2009 through 2012, we carried out a population-based birth cohort study on 39,053 live-born infants in Beijing. RF and GB models were used to calculate odds ratios for CHDs associated with increase in PM 10 exposure, adjusting for maternal and perinatal characteristics. Maternal exposure to PM 10 was identified as the primary risk factor for CHDs in all machine learning models. We observed a clear non-linear effect of maternal exposure to PM 10 on CHDs risk. Compared to 40μgm -3 , the following odds ratios resulted: 1) 92μgm -3 [RF: 1.16 (95% CI: 1.06, 1.28); GB: 1.26 (95% CI: 1.17, 1.35)]; 2) 111μgm -3 [RF: 1.04 (95% CI: 0.96, 1.14); GB: 1.04 (95% CI: 0.99, 1.08)]; 3) 124μgm -3 [RF: 1.01 (95% CI: 0.94, 1.10); GB: 0.98 (95% CI: 0.93, 1.02)]; 4) 190μgm -3 [RF: 1.29 (95% CI: 1.14, 1.44); GB: 1.71 (95% CI: 1.04, 2.17)]. Overall, both machine models showed an association between maternal exposure to ambient PM 10 and CHDs in Beijing, highlighting the need for non-linear methods to investigate dose-response relationships. Copyright © 2018 Elsevier B.V. All rights reserved.

Numerical Technology for Large-Scale Computational Electromagnetics

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

Sharpe, R; Champagne, N; White, D

The key bottleneck of implicit computational electromagnetics tools for large complex geometries is the solution of the resulting linear system of equations. The goal of this effort was to research and develop critical numerical technology that alleviates this bottleneck for large-scale computational electromagnetics (CEM). The mathematical operators and numerical formulations used in this arena of CEM yield linear equations that are complex valued, unstructured, and indefinite. Also, simultaneously applying multiple mathematical modeling formulations to different portions of a complex problem (hybrid formulations) results in a mixed structure linear system, further increasing the computational difficulty. Typically, these hybrid linear systems aremore » solved using a direct solution method, which was acceptable for Cray-class machines but does not scale adequately for ASCI-class machines. Additionally, LLNL's previously existing linear solvers were not well suited for the linear systems that are created by hybrid implicit CEM codes. Hence, a new approach was required to make effective use of ASCI-class computing platforms and to enable the next generation design capabilities. Multiple approaches were investigated, including the latest sparse-direct methods developed by our ASCI collaborators. In addition, approaches that combine domain decomposition (or matrix partitioning) with general-purpose iterative methods and special purpose pre-conditioners were investigated. Special-purpose pre-conditioners that take advantage of the structure of the matrix were adapted and developed based on intimate knowledge of the matrix properties. Finally, new operator formulations were developed that radically improve the conditioning of the resulting linear systems thus greatly reducing solution time. The goal was to enable the solution of CEM problems that are 10 to 100 times larger than our previous capability.« less

Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data.

PubMed

Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A

2017-02-01

This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r  =  0.71-0.88, RMSE: 1.11-1.61 METs; p  >  0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r  =  0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r  =  0.88, RMSE: 1.10-1.11 METs; p  >  0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r  =  0.88, RMSE: 1.12 METs. Linear models-correlations: r  =  0.86, RMSE: 1.18-1.19 METs; p  <  0.05), and both ANNs had higher correlations and lower RMSE than both linear models for the wrist-worn accelerometers (ANN-correlations: r  =  0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r  =  0.71-0.73, RMSE: 1.55-1.61 METs; p  <  0.01). For studies using wrist-worn accelerometers, machine learning models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh-worn accelerometers and may be viable alternative modeling techniques for EE prediction for hip- or thigh-worn accelerometers.

Monitoring Temperature and Fan Speed Using Ganglia and Winbond Chips

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

McCaffrey, Cattie; /SLAC

2006-09-27

Effective monitoring is essential to keep a large group of machines, like the ones at Stanford Linear Accelerator Center (SLAC), up and running. SLAC currently uses Ganglia Monitoring System to observe about 2000 machines, analyzing metrics like CPU usage and I/O rate. However, metrics essential to machine hardware health, such as temperature and fan speed, are not being monitored. Many machines have a Winbond w83782d chip which monitors three temperatures, two of which come from dual CPUs, and returns the information when the sensor command is invoked. Ganglia also provides a feature, gmetric, that allows the users to monitor theirmore » own metrics and incorporate them into the monitoring system. The programming language Perl is chosen to implement a script that invokes the sensors command, extracts the temperature and fan speed information, and calls gmetric with the appropriate arguments. Two machines were used to test the script; the two CPUs on each machine run at about 65 Celsius, which is well within the operating temperature range (The maximum safe temperature range is 77-82 Celsius for the Pentium III processors being used). Installing the script on all machines with a Winbond w83782d chip allows the SLAC Scientific Computing and Computing Services group (SCCS) to better evaluate current cooling methods.« less

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

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

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

From the inception of power systems, synchronous machines have acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, power electronics interfaces are playing a growing role as they are the primary interface for several types of renewable energy sources and storage technologies. As the role of power electronics in systems continues to grow, it is crucial to investigate the properties of bulk power systems in low inertia settings. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator,more » three-phase inverter, and a load. Furthermore, the inverter model is formulated such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings and, hence, differing levels of inertia. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the interaction between the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less

Theoretical and experimental research on machine tool servo system for ultra-precision position compensation on CNC lathe

NASA Astrophysics Data System (ADS)

Ma, Zhichao; Hu, Leilei; Zhao, Hongwei; Wu, Boda; Peng, Zhenxing; Zhou, Xiaoqin; Zhang, Hongguo; Zhu, Shuai; Xing, Lifeng; Hu, Huang

2010-08-01

The theories and techniques for improving machining accuracy via position control of diamond tool's tip and raising resolution of cutting depth on precise CNC lathes have been extremely focused on. A new piezo-driven ultra-precision machine tool servo system is designed and tested to improve manufacturing accuracy of workpiece. The mathematical model of machine tool servo system is established and the finite element analysis is carried out on parallel plate flexure hinges. The output position of diamond tool's tip driven by the machine tool servo system is tested via a contact capacitive displacement sensor. Proportional, integral, derivative (PID) feedback is also implemented to accommodate and compensate dynamical change owing cutting forces as well as the inherent non-linearity factors of the piezoelectric stack during cutting process. By closed loop feedback controlling strategy, the tracking error is limited to 0.8 μm. Experimental results have shown the proposed machine tool servo system could provide a tool positioning resolution of 12 nm, which is much accurate than the inherent CNC resolution magnitude. The stepped shaft of aluminum specimen with a step increment of cutting depth of 1 μm is tested, and the obtained contour illustrates the displacement command output from controller is accurately and real-time reflected on the machined part.

Evaluation of Fatigue Behavior and Surface Characteristics of Aluminum Alloy 2024 T6 After Electric Discharge Machining

NASA Astrophysics Data System (ADS)

Mehmood, Shahid; Shah, Masood; Pasha, Riffat Asim; Sultan, Amir

2017-10-01

The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property.

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

Olivares, Stefano

We investigate the performance of a selective cloning machine based on linear optical elements and Gaussian measurements, which allows one to clone at will one of the two incoming input states. This machine is a complete generalization of a 1{yields}2 cloning scheme demonstrated by Andersen et al. [Phys. Rev. Lett. 94, 240503 (2005)]. The input-output fidelity is studied for a generic Gaussian input state, and the effect of nonunit quantum efficiency is also taken into account. We show that, if the states to be cloned are squeezed states with known squeezing parameter, then the fidelity can be enhanced using amore » third suitable squeezed state during the final stage of the cloning process. A binary communication protocol based on the selective cloning machine is also discussed.« less

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

Hand, L.N.

Some proposed techniques for using laser beams to accelerate charged particles are reviewed. Two specific ideas for 'grating-type' accelerating structures are discussed. Speculations are presented about how a successful laser accelerator could be used in a 'multi-pass collider', a type of machine which would have characteristics intermediate between those of synchrotrons and linear (single-pass) colliders. No definite conclusions about practical structures for laser accelerators are reached, but it is suggested that a serious effort be made to design a small prototype machine. Achieving a reasonable luminosity demands that the accelerator either be a cw machine or that laser peak powermore » requirements be much higher than those presently available. Use of superconducting gratings requires a wavelength in the sub-millimeter range.« less

The laser accelerator-another unicorn in the garden

NASA Astrophysics Data System (ADS)

Hand, L. N.

1981-07-01

Some proposed techniques for using laser beams to accelerate charged particles was reviewed. Two specific ideas for grating type accelerating structures are discussed. Speculations are presented about how a successful laser accelerator could be used in a multipass collider; a type of machine which would have characteristics intermediate between those of synchrotrons and linear (single pass) colliders. No definite conclusions about practical structures for laser accelerators are reached, but it is suggested that a serious effort be made to design a small prototype machine. Achieving a reasonable luminosity demands that the accelerator either be a cw machine or that laser peak power requirements to be much higher than those presently available. Use of superconducting gratings requires a wavelength in the sub-millimeter range.

Chaotic sources of noise in machine acoustics

NASA Astrophysics Data System (ADS)

Moon, F. C., Prof.; Broschart, Dipl.-Ing. T.

1994-05-01

In this paper a model is posited for deterministic, random-like noise in machines with sliding rigid parts impacting linear continuous machine structures. Such problems occur in gear transmission systems. A mathematical model is proposed to explain the random-like structure-borne and air-borne noise from such systems when the input is a periodic deterministic excitation of the quasi-rigid impacting parts. An experimental study is presented which supports the model. A thin circular plate is impacted by a chaotically vibrating mass excited by a sinusoidal moving base. The results suggest that the plate vibrations might be predicted by replacing the chaotic vibrating mass with a probabilistic forcing function. Prechaotic vibrations of the impacting mass show classical period doubling phenomena.

An evaluation of the Meditech M250 and a comparison with other CT scanners.

PubMed

Greensmith, R; Richardson, R B; Sargood, A J; Stevens, P H; Mackintosh, I P

1985-11-01

The Meditech M250 computerised tomography (CT) machine was evaluated during the first half of 1984. Measurements were made of noise, modulation transfer function, slice width, radiation dose profile, uniformity and linearity of CT number, effective photon energy and parameters relating to machine specification, such as pixel size and scan time. All breakdowns were logged to indicate machine reliability. A comparison with the established EMI CT1010 and CT5005 was made for noise, resolution and multislice radiation dose, as well as the dose efficiency or quality (Q) factor for both head and body modes of operation. The M250 was found to perform to its intended specification with an acceptable level of reliability.

Optical Implementation of the Optimal Universal and Phase-Covariant Quantum Cloning Machines

NASA Astrophysics Data System (ADS)

Ye, Liu; Song, Xue-Ke; Yang, Jie; Yang, Qun; Ma, Yang-Cheng

Quantum cloning relates to the security of quantum computation and quantum communication. In this paper, firstly we propose a feasible unified scheme to implement optimal 1 → 2 universal, 1 → 2 asymmetric and symmetric phase-covariant cloning, and 1 → 2 economical phase-covariant quantum cloning machines only via a beam splitter. Then 1 → 3 economical phase-covariant quantum cloning machines also can be realized by adding another beam splitter in context of linear optics. The scheme is based on the interference of two photons on a beam splitter with different splitting ratios for vertical and horizontal polarization components. It is shown that under certain condition, the scheme is feasible by current experimental technology.

Researcher Biographies

Science.gov Websites

interest: mechanical system design sensitivity analysis and optimization of linear and nonlinear structural systems, reliability analysis and reliability-based design optimization, computational methods in committee member, ISSMO; Associate Editor, Mechanics Based Design of Structures and Machines; Associate

DEGAS: Dynamic Exascale Global Address Space Programming Environments

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

Demmel, James

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speedmore » and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics.« less

Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: Structure-based molecular dynamics simulations

PubMed Central

Okazaki, Kei-ichi; Koga, Nobuyasu; Takada, Shoji; Onuchic, Jose N.; Wolynes, Peter G.

2006-01-01

Biomolecules often undergo large-amplitude motions when they bind or release other molecules. Unlike macroscopic machines, these biomolecular machines can partially disassemble (unfold) and then reassemble (fold) during such transitions. Here we put forward a minimal structure-based model, the “multiple-basin model,” that can directly be used for molecular dynamics simulation of even very large biomolecular systems so long as the endpoints of the conformational change are known. We investigate the model by simulating large-scale motions of four proteins: glutamine-binding protein, S100A6, dihydrofolate reductase, and HIV-1 protease. The mechanisms of conformational transition depend on the protein basin topologies and change with temperature near the folding transition. The conformational transition rate varies linearly with driving force over a fairly large range. This linearity appears to be a consequence of partial unfolding during the conformational transition. PMID:16877541

Deviation Value for Conventional X-ray in Hospitals in South Sulawesi Province from 2014 to 2016

NASA Astrophysics Data System (ADS)

Bachtiar, Ilham; Abdullah, Bualkar; Tahir, Dahlan

2018-03-01

This paper describes the conventional X-ray machine parameters tested in the region of South Sulawesi from 2014 to 2016. The objective of this research is to know deviation of every parameter of conventional X-ray machine. The testing parameters were analyzed by using quantitative methods with participatory observational approach. Data collection was performed by testing the output of conventional X-ray plane using non-invasive x-ray multimeter. The test parameters include tube voltage (kV) accuracy, radiation output linearity, reproducibility and radiation beam value (HVL) quality. The results of the analysis show four conventional X-ray test parameters have varying deviation spans, where the tube voltage (kV) accuracy has an average value of 4.12%, the average radiation output linearity is 4.47% of the average reproducibility of 0.62% and the averaged of the radiation beam (HVL) is 3.00 mm.

SABRE, a 10-MV linear induction accelerator

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

Corely, J.P.; Alexander, J.A.; Pankuch, P.J.

SABRE (Sandia Accelerator and Beam Research Experiment) is a 10-MV, 250-kA, 40-ns linear induction accelerator. It was designed to be used in positive polarity output. Positive polarity accelerators are important for application to Sandia's ICF (Inertial Confinement Fusion) and LMF (Laboratory Microfusion Facility) program efforts. SABRE was built to allow a more detailed study of pulsed power issues associated with positive polarity output machines. MITL (Magnetically Insulated Transmission Line) voltage adder efficiency, extraction ion diode development, and ion beam transport and focusing. The SABRE design allows the system to operate in either positive polarity output for ion extraction applications ormore » negative polarity output for more conventional electron beam loads. Details of the design of SABRE and the results of initial machine performance in negative polarity operation are presented in this paper. 13 refs., 12 figs., 1 tab.« less