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Sample records for predict real t3

  1. Usefulness of Serum Triiodothyronine (T3) to Predict Outcomes in Patients Hospitalized With Acute Heart Failure.

    PubMed

    Rothberger, Gary D; Gadhvi, Sonya; Michelakis, Nickolaos; Kumar, Amit; Calixte, Rose; Shapiro, Lawrence E

    2017-02-15

    Thyroid hormone plays an important role in cardiac function. Low levels of serum triiodothyronine (T3) due to nonthyroidal illness syndrome may have adverse effects in heart failure (HF). This study was designed to assess the ability of T3 to predict in-hospital outcomes in patients with acute HF. In total, 137 patients without thyroid disease or treatment with drugs which affect TH levels, who were hospitalized with acute HF were prospectively enrolled and studied. TH levels were tested upon hospital admission, and outcomes were compared between patients with low (<2.3 pg/ml) and normal (≥2.3 pg/ml) free T3 levels as well as between those with low (<0.6 ng/ml) and normal (≥0.6 ng/ml) total T3 levels. Low free T3 correlated with an increased length of stay in the hospital (median 11 vs 7 days, p <0.001) and higher rates of intensive care unit admission (31.8% vs 16.9%, p = 0.047), with a trend toward increased need for invasive mechanical ventilation (9.0% vs 1.4%, p = 0.056). Low total T3 correlated with an increased length of stay in the hospital (median 11 vs 7 days, p <0.001) and increased need for invasive mechanical ventilation (9.8% vs 1.3%, p = 0.045). In conclusion, low T3 predicts worse hospital outcomes in patients with acute HF and can be useful in the risk stratification of these patients.

  2. Prediction of Crack Growth under Variable-Amplitude Loading in Thin-Sheet 2024-T3 Aluminum Alloys

    NASA Technical Reports Server (NTRS)

    Newman, J. C., Jr.

    1997-01-01

    The present paper is concerned with the application of a "plasticity-induced" crack closure model to study fatigue crack growth under various load histories. The model was based on the Dugdale model but modified to leave plastically deformed material in the wake of the advancing crack. The model was used to correlate crack growth rates under constant-amplitude loading and then used to predict crack growth under variable-amplitude and spectrum loading on thin-sheet 2024- T3 aluminum alloys. Predicted crack-opening stresses agreed well with test data from the literature. The crack-growth lives agreed within a factor of two for single and repeated spike overloads/underloads and within 20 percent for spectrum loading. Differences were attributed to fretting-product-debris-induced closure and three-dimensional affects not included in the model.

  3. Real Time Monitoring of Inhibition of Adipogenesis and Angiogenesis by (−)-Epigallocatechin-3-Gallate in 3T3-L1 Adipocytes and Human Umbilical Vein Endothelial Cells

    PubMed Central

    Tang, Wenjing; Song, Huanlei; Cai, Wei; Shen, Xiuhua

    2015-01-01

    Little is known about the effect of (−)-epigallocatechin-3-gallate (EGCG) on angiogenesis in adipocytes. We aimed to test the effect of EGCG on the expression of vascular endothelial growth factor (VEGF) in adipocytes. The levels of VEGF secretion, the expression of VEGF message ribonucleic acid (mRNA) and VEGF protein in 3T3-L1 cells were measured by enzyme linked immunosorbent assay (ELISA), real time polymerase chain reaction (PCR), and immunofluorescence staining, respectively. The xCELLigence real time cell analysis system was used to study the growth and differentiation of 3T3-L1 preadipocytes. A coculture system was used to test the effects of 3T3-L1 cells on proliferation of human umbilical vein endothelial cells (HUVECs). The conditioned media derived from 3T3-L1 cells treated with or without EGCG was used to culture the HUVECs for a tube formation assay. Peroxisome proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer binding protein α (C/EBPα), two transcription factors related to both adipogenesis and angiogenesis, were examined to explore the potential mechanism. We found that all the three measurements of VEGF expression in adipocytes (mRNA, protein and secretion in media) were reduced after EGCG treatment. The growth of HUVECs co-cultured with 3T3-L1 cells was significantly increased and the conditioned media from EGCG treated 3T3-L1 adipocytes inhibited tube formation in HUVECs. Both PPARγ and C/EBPα expression in adipocytes were decreased with EGCG treatment. In conclusion, findings from this study suggest that EGCG may inhibit angiogenesis by regulating VEGF expression and secretion in adipocytes. PMID:26516907

  4. Real Time Monitoring of Inhibition of Adipogenesis and Angiogenesis by (-)-Epigallocatechin-3-Gallate in 3T3-L1 Adipocytes and Human Umbilical Vein Endothelial Cells.

    PubMed

    Tang, Wenjing; Song, Huanlei; Cai, Wei; Shen, Xiuhua

    2015-10-27

    Little is known about the effect of (-)-epigallocatechin-3-gallate (EGCG) on angiogenesis in adipocytes. We aimed to test the effect of EGCG on the expression of vascular endothelial growth factor (VEGF) in adipocytes. The levels of VEGF secretion, the expression of VEGF message ribonucleic acid (mRNA) and VEGF protein in 3T3-L1 cells were measured by enzyme linked immunosorbent assay (ELISA), real time polymerase chain reaction (PCR), and immunofluorescence staining, respectively. The xCELLigence real time cell analysis system was used to study the growth and differentiation of 3T3-L1 preadipocytes. A coculture system was used to test the effects of 3T3-L1 cells on proliferation of human umbilical vein endothelial cells (HUVECs). The conditioned media derived from 3T3-L1 cells treated with or without EGCG was used to culture the HUVECs for a tube formation assay. Peroxisome proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer binding protein α (C/EBPα), two transcription factors related to both adipogenesis and angiogenesis, were examined to explore the potential mechanism. We found that all the three measurements of VEGF expression in adipocytes (mRNA, protein and secretion in media) were reduced after EGCG treatment. The growth of HUVECs co-cultured with 3T3-L1 cells was significantly increased and the conditioned media from EGCG treated 3T3-L1 adipocytes inhibited tube formation in HUVECs. Both PPARγ and C/EBPα expression in adipocytes were decreased with EGCG treatment. In conclusion, findings from this study suggest that EGCG may inhibit angiogenesis by regulating VEGF expression and secretion in adipocytes.

  5. Impact of five-tiered Gleason grade groups on prognostic prediction in clinical stage T3 prostate cancer undergoing high-dose-rate brachytherapy.

    PubMed

    Tsumura, Hideyasu; Ishiyama, Hiromichi; Tabata, Ken-Ichi; Katsumata, Hiroki; Kobayashi, Momoko; Ikeda, Masaomi; Kurosaka, Shinji; Fujita, Tetsuo; Kitano, Masashi; Satoh, Takefumi; Yanagisawa, Nobuyuki; Hayakawa, Kazushige; Iwamura, Masatsugu

    2017-09-14

    We evaluated a five-tiered Gleason grade groups arising from the 2014 International Society of Urological Pathology consensus conference on prognostic prediction in clinical stage T3a (extracapsular invasion) and T3b (seminal vesicle involvement) prostate cancer undergoing high-dose-rate brachytherapy (HDR-BT). From November 2003 to December 2012, 283 patients with stage T3 prostate cancer received HDR-BT and external beam radiation therapy (EBRT) with long-term androgen deprivation therapy (ADT). Of these, 203 (72%) and 80 (28%) patients had stage T3a and T3b disease, respectively. The mean dose to 90% of the planning target volume was 7.5 Gy/fraction of HDR-BT. After five fractions, EBRT with 10 fractions of 3 Gy was administered. All patients first underwent ≥6 months of neoadjuvant ADT, and adjuvant ADT continued for 36 months. Median follow-up was 74 months from the start of radiotherapy. The 10-year biochemical recurrence (BCR) -free rate for stage T3a and T3b disease was 79% and 64%, respectively (P = 0.0083). The 10-year cancer-specific survival (CSS) rate for stage T3a and T3b was 96% and 91%, respectively (P = 0.0305). Although grade groups ≥4 were independent predictors for BCR in cT3a patients (P = 0.0270), they failed to significantly predict prostate cancer-specific mortality (PCSM) among cT3a patients. Among cT3b patients, grade group 5 was a significant predictor of both BCR (P = 0.0017) and PCSM (P = 0.0233). Among stage T3a patients, no significant difference existed in 10-year CSS between grade groups 5 and 4 (94% vs 97%, P = 0.3960). In contrast, grade group 5 had a significantly worse outcome in 10-year CSS than grade group 4 among stage T3b patients (74% vs 100%, P = 0.0350). Stage T3a patients with grade groups 4/5 and stage T3b with grade group 4 had fairly low PCSM risk. Approximately one of four patients among stage T3b patients with grade group 5 showed PCSM after combined HDR-BT and EBRT with long

  6. Prediction of stable tearing of 2024-T3 aluminum alloy using the crack-tip opening angle approach

    NASA Technical Reports Server (NTRS)

    Bakuckas, J. G., Jr.; Newman, J. C., Jr.

    1993-01-01

    In this study, the crack-tip opening angle (CTOA) approach was incorporated into a damage growth finite element program, MADGIC (Micromechanics Analysis and Damage Growth in Composites), and was used to predict stable tearing in a middle-crack tension 2024-T3 aluminum alloy specimen. The MADGIC code is a displacement based finite element program implemented with an incremental elastic-plastic algorithm used to model elastic-plastic behavior and a nodal splitting and nodal force relaxation algorithm used to generate crack surfaces. Predictions of the applied stress as a function of crack extension and applied stress as a function of load-line displacement were in good agreement with experiments and with similar predictions made using an existing finite element program, ZIP2D. In addition, path integrals, namely, the J-integral and T*-integral, were also evaluated and compared with the CTOA approach. There appears to be a weak relationship between the CTOA and the T*-integral evaluated on a specific integration path during crack extension beyond maximum applied stress. This study further verifies that the CTOA can be used as an effective elastic-plastic fracture mechanics parameter to predict crack growth.

  7. T3 test

    MedlinePlus

    Triiodothyronine; T3 radioimmunoassay; Toxic nodular goiter - T3; Thyroiditis - T3; Thyrotoxicosis - T3; Graves disease - T3 ... example, Graves disease ) T3 thyrotoxicosis (rare) Toxic nodular goiter Taking thyroid medicines or certain supplements (common) Liver ...

  8. The Real World Significance of Performance Prediction

    ERIC Educational Resources Information Center

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  9. Predicting Complexity Perception of Real World Images

    PubMed Central

    Corchs, Silvia Elena; Ciocca, Gianluigi; Bricolo, Emanuela; Gasparini, Francesca

    2016-01-01

    The aim of this work is to predict the complexity perception of real world images. We propose a new complexity measure where different image features, based on spatial, frequency and color properties are linearly combined. In order to find the optimal set of weighting coefficients we have applied a Particle Swarm Optimization. The optimal linear combination is the one that best fits the subjective data obtained in an experiment where observers evaluate the complexity of real world scenes on a web-based interface. To test the proposed complexity measure we have performed a second experiment on a different database of real world scenes, where the linear combination previously obtained is correlated with the new subjective data. Our complexity measure outperforms not only each single visual feature but also two visual clutter measures frequently used in the literature to predict image complexity. To analyze the usefulness of our proposal, we have also considered two different sets of stimuli composed of real texture images. Tuning the parameters of our measure for this kind of stimuli, we have obtained a linear combination that still outperforms the single measures. In conclusion our measure, properly tuned, can predict complexity perception of different kind of images. PMID:27336469

  10. Predicting Complexity Perception of Real World Images.

    PubMed

    Corchs, Silvia Elena; Ciocca, Gianluigi; Bricolo, Emanuela; Gasparini, Francesca

    2016-01-01

    The aim of this work is to predict the complexity perception of real world images. We propose a new complexity measure where different image features, based on spatial, frequency and color properties are linearly combined. In order to find the optimal set of weighting coefficients we have applied a Particle Swarm Optimization. The optimal linear combination is the one that best fits the subjective data obtained in an experiment where observers evaluate the complexity of real world scenes on a web-based interface. To test the proposed complexity measure we have performed a second experiment on a different database of real world scenes, where the linear combination previously obtained is correlated with the new subjective data. Our complexity measure outperforms not only each single visual feature but also two visual clutter measures frequently used in the literature to predict image complexity. To analyze the usefulness of our proposal, we have also considered two different sets of stimuli composed of real texture images. Tuning the parameters of our measure for this kind of stimuli, we have obtained a linear combination that still outperforms the single measures. In conclusion our measure, properly tuned, can predict complexity perception of different kind of images.

  11. T3 (Triiodothyronine) Test

    MedlinePlus

    ... AACC products and services. Advertising & Sponsorship: Policy | Opportunities Free T3 and Total T3 Share this page: Was ... helpful? Also known as: FT3; Triiodothyronine Formal name: Free Triiodothyronine; Total Triiodothyronine Related tests: TSH ; Free T4 ; ...

  12. Real Time Seismic Prediction while Drilling

    NASA Astrophysics Data System (ADS)

    Schilling, F. R.; Bohlen, T.; Edelmann, T.; Kassel, A.; Heim, A.; Gehring, M.; Lüth, S.; Giese, R.; Jaksch, K.; Rechlin, A.; Kopf, M.; Stahlmann, J.; Gattermann, J.; Bruns, B.

    2009-12-01

    Efficient and safe drilling is a prerequisite to enhance the mobility of people and goods, to improve the traffic as well as utility infrastructure of growing megacities, and to ensure the growing energy demand while building geothermal and in hydroelectric power plants. Construction within the underground is often building within the unknown. An enhanced risk potential for people and the underground building may arise if drilling enters fracture zones, karsts, brittle rocks, mixed solid and soft rocks, caves, or anthropogenic obstacles. Knowing about the material behavior ahead of the drilling allows reducing the risk during drilling and construction operation. In drilling operations direct observations from boreholes can be complemented with geophysical investigations. In this presentation we focus on “real time” seismic prediction while drilling which is seen as a prerequisite while using geophysical methods in modern drilling operations. In solid rocks P- and S-wave velocity, refraction and reflection as well as seismic wave attenuation can be used for the interpretation of structures ahead of the drilling. An Integrated Seismic Imaging System (ISIS) for exploration ahead of a construction is used, where a pneumatic hammer or a magnetostrictive vibration source generate repetitive signals behind the tunneling machine. Tube waves are generated which travel along the tunnel to the working face. There the tube waves are converted to mainly S- but also P-Waves which interact with the formation ahead of the heading face. The reflected or refracted waves travel back to the working front are converted back to tube waves and recorded using three-component geophones which are fit into the tips of anchor rods. In near real time, the ISIS software allows for an integrated 3D imaging and interpretation of the observed data, geological and geotechnical parameters. Fracture zones, heterogeneities, and variations in the rock properties can be revealed during the drilling

  13. Prediction of low-cycle fatigue-life by acoustic emission—1: 2024-T3 aluminum alloy, and —2: 7075-T6 aluminum alloy

    SciTech Connect

    Baram, J.; Rosen, M.

    1981-01-01

    1: In this paper, low-cycle fatigue tests were conducted by tension-tension until rupture, on a 2024-T3 aluminum alloy sheet. Initial crack sizes and orientations in the fatigue specimens were found to be randomly distributed. Acoustic emission was continuously monitored during the tests. Every few hundred cycles, the acoustic signal having the highest peak-amplitude, was recorded as an extremal event for the elapsed period. This high peak-amplitude is related to a fast crack propagation rate through a phenomenological relationship. The extremal peak amplitudes are shown by an ordered statistics treatment, to be extremally distributed. The statistical treatment enables the prediction of the number of cycles left until failure. Predictions performed a posteriori based on results gained early in each fatigue test are in good agreement with actual fatigue lives. Finally, the amplitude distribution analysis of the acoustic signals emitted during cyclic stress appears to be a promising nondestructive method of predicting fatigue life. 2: In this paper, low cycle high stress fatigue tests were conducted by tension-tension on an Alclad 7075-T6 aluminum sheet alloy, until rupture. Initial crack sizes and orientations in the fatigue specimens were randomly distributed. Acoustic emission was continuously monitored during the tests. Extremal peak-amplitudes, equivalent to extremal crack-propagation rates, are shown to be extremally Weibull distributed. The prediction of the number of cycles left until failure is made possible, using an ordered statistics treatment and an experimental equipment parameter obtained in previous experiments (Part 1). The predicted life-times are in good agreement with the actual fatigue lives. Finally, the amplitude distribution analysis of the acoustic signals emitted during cyclic stress has been proven to be a feasible nondestructive method of predicting fatigue life.

  14. Real-time monitoring of inflammation status in 3T3-L1 adipocytes possessing a secretory Gaussia luciferase gene under the control of nuclear factor-kappa B response element

    SciTech Connect

    Nagasaki, Haruka; Yoshimura, Takeshi; Aoki, Naohito

    2012-04-13

    Highlights: Black-Right-Pointing-Pointer Inflammation status in adipocytes can be monitored by the new assay system. Black-Right-Pointing-Pointer Only an aliquot of conditioned medium is required without cell lysis. Black-Right-Pointing-Pointer Inflammation-attenuating compounds can be screened more conveniently. -- Abstract: We have established 3T3-L1 cells possessing a secretory Gaussia luciferase (GLuc) gene under the control of nuclear factor-kappa B (NF-{kappa}B) response element. The 3T3-L1 cells named 3T3-L1-NF-{kappa}B-RE-GLuc could differentiate into adipocyte as comparably as parental 3T3-L1 cells. Inflammatory cytokines such as tumor necrosis factor (TNF)-{alpha} and interleukin (IL)-1{beta} induced GLuc secretion of 3T3-L1-NF-{kappa}B-RE-GLuc adipocytes in a concentration- and time-dependent manner. GLuc secretion of 3T3-L1-NF-{kappa}B-RE-GLuc adipocytes was also induced when cultured with RAW264.7 macrophages and was dramatically enhanced by lipopolysaccharide (LPS)-activated macrophages. An NF-{kappa}B activation inhibitor BAY-11-7085 and an antioxidant N-acetyl cysteine significantly suppressed GLuc secretion induced by macrophages. Finally, we found that rosemary-derived carnosic acid strongly suppressed GLuc secretion induced by macrophages and on the contrary up-regulated adiponectin secretion. Collectively, by using 3T3-L1-NF-{kappa}B-RE-GLuc adipocytes, inflammation status can be monitored in real time and inflammation-attenuating compounds can be screened more conveniently.

  15. A real-time prediction of UTC

    NASA Astrophysics Data System (ADS)

    Thomas, Claudine; Allan, David W.

    1994-05-01

    The reference time scale for all scientific and technologic applications on the Earth, the Universal Coordinated Time (UTC), must be as stable, reliable, and accurate as possible. With this in view the BIPM and before it the BIH, have always calculated and then disseminated UTC with a delay of about 80 days. There are three fundamental reasons for doing this: (1) It takes some weeks for data, gathered from some 200 clocks spread world-wide, to be collected and for errors to be eliminated; (2) changes in clock rates can only be measured with high precision well after the fact; and (3) the measurement noise originating in time links, in particular using Loran-C, is smoothed out only when averaging over an extended period. Until mid-1992, the ultimate stability of UTC was reached at averaging times of about 100 days and corresponded to an Allan deviation sigma(sub y)(tau) of about 1,5x10(exp -14) then compared to the best primary clock in the world, the PTB CS2. For several years now, a predicted UTC has been computed by the USNO through an extrapolation of the values as published in deferred time by the BIPM. This is made available through the USNO Series 4, through the USNO Automated Data Service, and through GPS signals. Due to the instability of UTC, the poor predictability of the available clocks, and the intentional SA degradation of GPS signals, the real-time access to this extrapolated UTC has represented the true deferred-time UTC only to within several hundreds of nanoseconds.

  16. A real-time prediction of UTC

    NASA Technical Reports Server (NTRS)

    Thomas, Claudine; Allan, David W.

    1994-01-01

    The reference time scale for all scientific and technologic applications on the Earth, the Universal Coordinated Time (UTC), must be as stable, reliable, and accurate as possible. With this in view the BIPM and before it the BIH, have always calculated and then disseminated UTC with a delay of about 80 days. There are three fundamental reasons for doing this: (1) It takes some weeks for data, gathered from some 200 clocks spread world-wide, to be collected and for errors to be eliminated; (2) changes in clock rates can only be measured with high precision well after the fact; and (3) the measurement noise originating in time links, in particular using Loran-C, is smoothed out only when averaging over an extended period. Until mid-1992, the ultimate stability of UTC was reached at averaging times of about 100 days and corresponded to an Allan deviation sigma(sub y)(tau) of about 1,5x10(exp -14) then compared to the best primary clock in the world, the PTB CS2. For several years now, a predicted UTC has been computed by the USNO through an extrapolation of the values as published in deferred time by the BIPM. This is made available through the USNO Series 4, through the USNO Automated Data Service, and through GPS signals. Due to the instability of UTC, the poor predictability of the available clocks, and the intentional SA degradation of GPS signals, the real-time access to this extrapolated UTC has represented the true deferred-time UTC only to within several hundreds of nanoseconds.

  17. Predicting oncologic outcomes by stratifying mesorectal extension in patients with pT3 rectal cancer: a Japanese multi-institutional study.

    PubMed

    Akagi, Yoshito; Shirouzu, Kazuo; Fujita, Shin; Ueno, Hideki; Takii, Yasumasa; Komori, Koji; Ito, Masaaki; Sugihara, Kenichi

    2012-09-01

    The goal of this study was to clarify the clinical significance of mesorectal extension in pT3 rectal cancer. This currently remains unclear. Data from 975 consecutive patients with pT3 rectal cancer that underwent curative surgery at 28 institutes were reviewed. The distance of the mesorectal extension (DME) was measured histologically. The optimal prognostic cut-off point of the DME for oncologic outcomes was determined using the receiver operating characteristic curve and Cox regression analysis. When patients were subdivided into two groups according to the optimal cut-off point, DME≤4 mm and DME>4 mm, DME was found to be a powerful independent risk factor for postoperative recurrence. A DME>4 mm was significantly correlated with distant and local recurrences at Stage IIA and IIIB diseases. The recurrence-free 5-year-survival rate was significantly higher in patients with a DME≤4 mm [86.6% at Stage IIA (p=0.00015), and 68.7% at Stage IIIB (p<0.0001)] than in patients with a DME>4 mm (71.3% at Stage IIA and 49.1% at Stage IIIB). No significant difference was noted in the oncologic outcomes between the two groups at Stage IIIC. A value of 4 mm provides the best prognostic cut-off point for patient stratification and for the prediction of oncologic outcomes. A subclassification based on a 4-mm cut-off point may improve the utility of the TNM 7th staging system except for Stage IIIC. These findings warrant further prospective studies to determine the reliability and validity of this cut-off point. Copyright © 2011 UICC.

  18. [Comparison of prediction performance of PAHs carcinogenicity between a BALB/c-E6E7 cell transformation assay and a BALB/c 3T3 cell transformation assay].

    PubMed

    Wu, Shuang; Li, Jin-Tao; Zhong, Ru-Gang; Zeng, Yi

    2012-10-01

    To predict the carcinogenicity of polycyclic aromatic hydrocarbons (PAHs) by cell transformation assay using BALB/c 3T3 cells and HPV16-E6E7-transfected BALB/c 3T3 cells (BALB/c-E6E7 cells). The cell transformation assays induced by PAHs using BALB-E6E7 cells and BALB/c 3T3 cells. The initiating and promoting activities of PAHs examined in a BALB-E6E7 cell transformation assay were similar to in a BALB/c 3T3 cell transformation assay, which was up to the standard of agents classified by the IARC. There were much more transformed foci appeared and much shorter time consumed to accomplish phenotypic alterations in the BALB/c-E6E7 cell transformation assay than in the BALB/c 3T3 cell transformation assay. The BALB/c-E6E7 cell transformation assay was superior to the BALB/c 3T3 cell transformation assay in cost and labor performance, the sensitivity of transformation response. The BALB/c-E6E7 cell transformation assay, with a satisfied prediction performance of initiating activity and promoting activity, would improve the overall process of safety and risk assessment of carcinogenicity.

  19. Runtime prediction of real programs on real machines

    SciTech Connect

    Finkler, U.; Mehlhorn, K.

    1997-06-01

    Algorithms are more and more made available as part of libraries or tool kits. For a user of such a library statements of asymptotic running times are almost meaningless as he has no way to estimate the constants involved. To choose the right algorithm for the targeted problem size and the available hardware, knowledge about these constants is important. Methods to determine the constants based on regression analysis or operation counting are not practicable in the general case due to inaccuracy and costs respectively. We present a new general method to determine the implementation and hardware specific running time constants for combinatorial algorithms. This method requires no changes of the implementation of the investigated algorithm and is applicable to a wide range of programming languages. Only some additional code is necessary. The determined constants are correct within a constant factor which depends only on the hardware platform. As an example the constants of an implementation of a hierarchy of algorithms and data structures are determined. The hierarchy consists of an algorithm for the maximum weighted bipartite matching problem (MWBM), Dijkstra`s algorithm, a Fibonacci heap and a graph representation based on adjacency lists. The errors in the running time prediction of these algorithms using exact execution frequencies are at most 50 % on the tested hardware platforms.

  20. New players in the same old game: a system level in silico study to predict type III secretion system and effector proteins in bacterial genomes reveals common themes in T3SS mediated pathogenesis.

    PubMed

    Sadarangani, Vineet; Datta, Sunando; Arunachalam, Manonmani

    2013-07-26

    Type III secretion system (T3SS) plays an important role in virulence or symbiosis of many pathogenic or symbiotic bacteria [CHM 2:291-294, 2007; Physiology (Bethesda) 20:326-339, 2005]. T3SS acts like a tunnel between a bacterium and its host through which the bacterium injects 'effector' proteins into the latter [Nature 444:567-573, 2006; COSB 18:258-266, 2008]. The effectors spatially and temporally modify the host signalling pathways [FEMS Microbiol Rev 35:1100-1125, 2011; Cell Host Microbe5:571-579, 2009]. In spite its crucial role in host-pathogen interaction, the study of T3SS and the associated effectors has been limited to a few bacteria [Cell Microbiol 13:1858-1869, 2011; Nat Rev Microbiol 6:11-16, 2008; Mol Microbiol 80:1420-1438, 2011]. Before one set out to perform systematic experimental studies on an unknown set of bacteria it would be beneficial to identify the potential candidates by developing an in silico screening algorithm. A system level study would also be advantageous over traditional laboratory methods to extract an overriding theme for host-pathogen interaction, if any, from the vast resources of data generated by sequencing multiple bacterial genomes. We have developed an in silico protocol in which the most conserved set of T3SS proteins was used as the query against the entire bacterial database with increasingly stringent search parameters. It enabled us to identify several uncharacterized T3SS positive bacteria. We adopted a similar strategy to predict the presence of the already known effectors in the newly identified T3SS positive bacteria. The huge resources of biochemical data [FEMS Microbiol Rev 35:1100-1125, 2011; Cell Host Microbe 5:571-579, 2009; BMC Bioinformatics 7(11):S4, 2010] on the T3SS effectors enabled us to search for the common theme in T3SS mediated pathogenesis. We identified few cellular signalling networks in the host, which are manipulated by most of the T3SS containing pathogens. We went on to look for

  1. Improving Predictability in Embedded Real-Time Systems

    DTIC Science & Technology

    2000-12-01

    Systems CMU/SEI-2000-SR-011 Peter H. Feiler , Software Engineering Institute Bruce Lewis, U.S. Army Aviation and Missile Command Steve Vestal...SUBTITLE Improving Predictability in Embedded Real-Time Systems 5. FUNDING NUMBERS F19628-00-C-0003 6. AUTHOR(S) Peter H. Feiler , Bruce ...Carnegie Metton Software Engineering Institute Improving Predictability in Embedded Real-Time Systems Peter H. Feiler , Software Engineering

  2. Real-time Tsunami Inundation Prediction Using High Performance Computers

    NASA Astrophysics Data System (ADS)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

  3. In vitro setting of dose-effect relationships of 32 metal compounds in the Balb/3T3 cell line, as a basis for predicting their carcinogenic potential.

    PubMed

    Mazzotti, Francesca; Sabbioni, Enrico; Ponti, Jessica; Ghiani, Michela; Fortaner, Salvador; Rossi, Gian Luigi

    2002-01-01

    The results are reported of the second stage in a programme for a systematic in vitro study on the carcinogenic potential of metal compounds with Balb/3T3 clone A31-1-1 mouse fibroblasts. Nineteen metal compounds that exhibited a strong cytotoxic effect during a previous screening run with a 100 microM fixed dose were tested with a 72-hour exposure over a wide range of concentrations (from 0.1 microM to 1000 microM), to produce dose-effect curves to permit extrapolation of the 50% inhibition concentration (IC50) values for each metal compound. This allows the establishment of a suitable range of doses for individual metal species, for use in the subsequent Balb/3T3 assay based on a two-stage concurrent cytotoxicity and morphological transformation protocol. Another 13 metal compounds were also tested, to determine whether the Balb/3T3 cell transformation assay is really a valuable in vitro model in relation to the problem of metal speciation. Of the metal compounds assayed, 26 showed a dose related cytotoxic response with calculated IC50 values ranging from 0.25 microM (CH3HgCl) to 140 microM [(C5H5)2TiCl2], whereas six metal compounds, namely (NH4)6Mo7O24*4H2O, CH3AsO(OH)2, C2H6AsNaO2(3H2O, KBr, CrCl3*6H2O and (NH4)2[TiO(C2O4)2]*H2O, displayed no observable cytotoxicity or low cytotoxicity at all the doses tested. The determination of IC50 values permits a ranking of the cytotoxicity responses of metal compounds with the highest cytotoxicities. Dose-effect curves and IC50 values of different chemical forms of individual metal compounds of As, Br, Cr, Hg, Ir, Pt, Te, Ti and V (cationic/anionic inorganic or organometallic species) showed clearly how the chemical nature of the metal strongly influences the toxic response. This confirms that the Balb/3T3 cell line is a valuable in vitro model with respect to the problem of metal speciation. This is a fundamental aspect to be considered when incorporating the results from in vitro cell transformation assays of the

  4. Impact of intraoperative MRI/TRUS fusion on dosimetric parameters in cT3a prostate cancer patients treated with high-dose-rate real-time brachytherapy

    PubMed Central

    Crook, Juanita; Casquero, Francisco; Carvajal, Claudia; Urresola, Arantxa; Canteli, Begoña; Ezquerro, Ana; Hortelano, Eduardo; Cacicedo, Jon; Espinosa, Jose Maria; Perez, Fernando; Minguez, Pablo; Bilbao, Pedro

    2014-01-01

    Purpose The purpose of this study was to evaluate the impact of intraoperative MRI/TRUS fusion procedure in cT3a prostate cancer patients treated with high-dose-rate (HDR) real-time brachytherapy. Material and methods Prostate gland, dominant intraprostatic lesions (DILs), and extracapsular extension (ECE) were delineated in the pre-brachytherapy magnetic resonance images (MRI) of 9 consecutive patients. The pre-implant P-CTVUS (prostate clinical target volume) was defined as the prostate seen in the transrectal ultrasound (TRUS) images. The CTVMR includedthe prostate with the ECE image (ECE-CTV) as defined on the MRI. Two virtual treatment plans were performed based on the MRI/TRUS fusion images, the first one prescribing 100% of the dose to the P-PTVUS, and the second prescribing to the PTVMR. The implant parameters and dose-volume histogram (DVH) related parameters of the prostate, OARs, and ECE were compared between both plans. Results Mean radial distance of ECE was 3.6 mm (SD: 1.1). No significant differences were found between prostate V100, V150, V200, and OARs DVH-related parameters between the plans. Mean values of ECE V100, V150, and V200 were 85.9% (SD: 15.1), 18.2% (SD: 17.3), and 5.85% (SD: 7) when the doses were prescribed to the PTVUS, whereas ECE V100, V150, and V200 were 99.3% (SD: 1.2), 45.8% (SD: 22.4), and 19.6% (SD: 12.6) when doses were prescribed to PTVMR (p = 0.028, p = 0.002 and p = 0.004, respectively). Conclusions TRUS/MRI fusion provides important information for prostate brachytherapy, allowing for better coverage and higher doses to extracapsular disease in patients with clinical stage T3a. PMID:25097555

  5. Impact of intraoperative MRI/TRUS fusion on dosimetric parameters in cT3a prostate cancer patients treated with high-dose-rate real-time brachytherapy.

    PubMed

    Gomez-Iturriaga, Alfonso; Crook, Juanita; Casquero, Francisco; Carvajal, Claudia; Urresola, Arantxa; Canteli, Begoña; Ezquerro, Ana; Hortelano, Eduardo; Cacicedo, Jon; Espinosa, Jose Maria; Perez, Fernando; Minguez, Pablo; Bilbao, Pedro

    2014-06-01

    The purpose of this study was to evaluate the impact of intraoperative MRI/TRUS fusion procedure in cT3a prostate cancer patients treated with high-dose-rate (HDR) real-time brachytherapy. Prostate gland, dominant intraprostatic lesions (DILs), and extracapsular extension (ECE) were delineated in the pre-brachytherapy magnetic resonance images (MRI) of 9 consecutive patients. The pre-implant P-CTVUS (prostate clinical target volume) was defined as the prostate seen in the transrectal ultrasound (TRUS) images. The CTVMR includedthe prostate with the ECE image (ECE-CTV) as defined on the MRI. Two virtual treatment plans were performed based on the MRI/TRUS fusion images, the first one prescribing 100% of the dose to the P-PTVUS, and the second prescribing to the PTVMR. The implant parameters and dose-volume histogram (DVH) related parameters of the prostate, OARs, and ECE were compared between both plans. Mean radial distance of ECE was 3.6 mm (SD: 1.1). No significant differences were found between prostate V100, V150, V200, and OARs DVH-related parameters between the plans. Mean values of ECE V100, V150, and V200 were 85.9% (SD: 15.1), 18.2% (SD: 17.3), and 5.85% (SD: 7) when the doses were prescribed to the PTVUS, whereas ECE V100, V150, and V200 were 99.3% (SD: 1.2), 45.8% (SD: 22.4), and 19.6% (SD: 12.6) when doses were prescribed to PTVMR (p = 0.028, p = 0.002 and p = 0.004, respectively). TRUS/MRI fusion provides important information for prostate brachytherapy, allowing for better coverage and higher doses to extracapsular disease in patients with clinical stage T3a.

  6. On Predictability of System Anomalies in Real World

    DTIC Science & Technology

    2011-08-01

    distributed system SETI @home [44]. Different from the above work, this work focuses on quantifying the predictability of real-world system anomalies. V...J.-M. Vincent, and D. Anderson, “Mining for statistical models of availability in large-scale distributed systems: An empirical study of seti @home,” in Proc. of MASCOTS, sept. 2009.

  7. Prospects for eruption prediction in near real-time

    USGS Publications Warehouse

    Voight, B.; Cornelius, R.R.

    1991-01-01

    THE 'materials science' method for eruption prediction1-3 arises from the application of a general law governing the failure of materials: ??-?? ??-A=0, where A and ?? are empirical constants, and ?? is an observable quantity such as ground deformation, seismicity or gas emission. This law leads to the idea of the 'inverse-rate' plot, in which the time of failure can be estimated by extrapolation of the curve of ??-1 versus time to a pre-deter-mined intercept. Here we suggest that this method can be combined with real-time seismic amplitude monitoring to provide a tool for near-real-time eruption prediction, and we demonstrate how it might have been used to predict two dome-growth episodes at Mount St Helens volcano in 1985 and 1986, and two explosive eruptions at Redoubt volcano in 1989-90.

  8. Expression of Estrogen Receptor Beta Predicts Oncologic Outcome of pT3 Upper Urinary Tract Urothelial Carcinoma Better Than Aggressive Pathological Features

    PubMed Central

    Luo, Hao Lun; Sung, Ming Tse; Tsai, Eing Mei; Lin, Chang Shen; Lee, Nai Lun; Chung, Yueh-Hua; Chiang, Po Hui

    2016-01-01

    Upper urinary tract urothelial carcinoma (UT-UC) is rare and treatment options or prognostic markers are limited. There is increasing evidence indicating that urothelial carcinoma may be an endocrine-related cancer. The aim of this study was to analyze the prognostic effect of estrogen receptor beta (ERβ) on the outcome of UT-UC. From 2005 to 2012, this study included 105 patients with pT3 UT-UC. Perioperative factors, pathological features, and ERβ immunostaining were reviewed and prognostic effects were examined by multivariate analysis. This study divided patients into either the ERβ-high (n = 52) or ERβ-low (n = 53) group and analyzed their oncologic outcomes. All pathological features except infiltrating tumor architecture (significantly higher incidence in ERβ-low group, p = 0.004) are symmetric in both groups. Low ERβ expression was significantly correlated with local recurrence and distant metastasis in univariate analysis (p = 0.035 and 0.004, respectively) and multivariate analysis (p = 0.05 and 0.008, respectively). Cell line study also proved that knock down of ERβ cause less UTUC proliferation and migration. In addition, ERβ agonist also enhanced the cytotoxic and migration inhibition effect of cisplatin and ERβ antagonist cause the UTUC cell more resistant to cisplatin. This result may help identify patients in need of adjuvant therapy or develop potential targeted therapy. PMID:27052470

  9. Online Anomaly Prediction for Real-Time Stream Processing

    NASA Astrophysics Data System (ADS)

    Huang, Yuanqiang; Luan, Zhongzhi; Qian, Depei; Du, Zhigao; Chen, Ting; Bai, Yuebin

    With the consideration of real-time stream processing technology, it's important to develop high availability mechanism to guarantee stream-based application not interfered by faults caused by potential anomalies. In this paper, we present a novel online prediction technique for predicting some anomalies which may occur in the near future. Concretely, we first present a value prediction which combines the Hidden Markov Model and the Mixture of Expert Model to predict the values of feature metrics in the near future. Then we employ the Support Vector Machine to do anomaly identification, which is a procedure to identify the kind of anomaly that we are about to alarm. The purpose of our approach is to achieve a tradeoff between fault penalty and resource cost. The experiment results show that our approach is of high accuracy for common anomaly prediction and low runtime overhead.

  10. Assessment of the predictive capacity of the 3T3 Neutral Red Uptake cytotoxicity test method to identify substances not classified for acute oral toxicity (LD50>2000 mg/kg): results of an ECVAM validation study.

    PubMed

    Prieto, Pilar; Cole, Thomas; Curren, Rodger; Gibson, Rosemary M; Liebsch, Manfred; Raabe, Hans; Tuomainen, Anita M; Whelan, Maurice; Kinsner-Ovaskainen, Agnieszka

    2013-04-01

    Assessing chemicals for acute oral toxicity is a standard information requirement of regulatory testing. However, animal testing is now prohibited in the cosmetics sector in Europe, and strongly discouraged for industrial chemicals. Building on the results of a previous international validation study, a follow up study was organised to assess if the 3T3 Neutral Red Uptake cytotoxicity assay could identify substances not requiring classification as acute oral toxicants under the EU regulations. Fifty-six coded industrial chemicals were tested in three laboratories, each using one of the following protocols: the previously validated protocol, an abbreviated version of the protocol and the protocol adapted for an automation platform. Predictions were very similar among the three laboratories. The assay exhibited high sensitivity (92-96%) but relatively low specificity (40-44%). Three chemicals were under predicted. Assuming that most industrial chemicals are not likely to be acutely toxic, this test method could prove a valuable component of an integrated testing strategy, a read-across argument, or weight-of-evidence approach to identify non toxic chemicals (LD50>2000 mg/kg). However, it is likely to under predict chemicals acting via specific mechanisms of action not captured by the 3T3 test system, or which first require biotransformation in vivo.

  11. Accepting the T3D

    SciTech Connect

    Rich, D.O.; Pope, S.C.; DeLapp, J.G.

    1994-10-01

    In April, a 128 PE Cray T3D was installed at Los Alamos National Laboratory`s Advanced Computing Laboratory as part of the DOE`s High-Performance Parallel Processor Program (H4P). In conjunction with CRI, the authors implemented a 30 day acceptance test. The test was constructed in part to help them understand the strengths and weaknesses of the T3D. In this paper, they briefly describe the H4P and its goals. They discuss the design and implementation of the T3D acceptance test and detail issues that arose during the test. They conclude with a set of system requirements that must be addressed as the T3D system evolves.

  12. Real-time Neural Network predictions of geomagnetic activity indices

    NASA Astrophysics Data System (ADS)

    Bala, R.; Reiff, P. H.

    2009-12-01

    The Boyle potential or the Boyle Index (BI), Φ (kV)=10-4 (V/(km/s))2 + 11.7 (B/nT) sin3(θ/2), is an empirically-derived formula that can characterize the Earth's polar cap potential, which is readily derivable in real time using the solar wind data from ACE (Advanced Composition Explorer). The BI has a simplistic form that utilizes a non-magnetic "viscous" and a magnetic "merging" component to characterize the magnetospheric behavior in response to the solar wind. We have investigated its correlation with two of conventional geomagnetic activity indices in Kp and the AE index. We have shown that the logarithms of both 3-hr and 1-hr averages of the BI correlate well with the subsequent Kp: Kp = 8.93 log10(BI) - 12.55 along with 1-hr BI correlating with the subsequent log10(AE): log10(AE) = 1.78 log10(BI) - 3.6. We have developed a new set of algorithms based on Artificial Neural Networks (ANNs) suitable for short term space weather forecasts with an enhanced lead-time and better accuracy in predicting Kp and AE over some leading models; the algorithms omit the time history of its targets to utilize only the solar wind data. Inputs to our ANN models benefit from the BI and its proven record as a forecasting parameter since its initiation in October, 2003. We have also performed time-sensitivity tests using cross-correlation analysis to demonstrate that our models are as efficient as those that incorporates the time history of the target indices in their inputs. Our algorithms can predict the upcoming full 3-hr Kp, purely from the solar wind data and achieve a linear correlation coefficient of 0.840, which means that it predicts the upcoming Kp value on average to within 1.3 step, which is approximately the resolution of the real-time Kp estimate. Our success in predicting Kp during a recent unexpected event (22 July ’09) is shown in the figure. Also, when predicting an equivalent "one hour Kp'', the correlation coefficient is 0.86, meaning on average a prediction

  13. Predictive models for population performance on real biological fitness landscapes.

    PubMed

    Rowe, William; Wedge, David C; Platt, Mark; Kell, Douglas B; Knowles, Joshua

    2010-09-01

    Directed evolution, in addition to its principal application of obtaining novel biomolecules, offers significant potential as a vehicle for obtaining useful information about the topologies of biomolecular fitness landscapes. In this article, we make use of a special type of model of fitness landscapes-based on finite state machines-which can be inferred from directed evolution experiments. Importantly, the model is constructed only from the fitness data and phylogeny, not sequence or structural information, which is often absent. The model, called a landscape state machine (LSM), has already been used successfully in the evolutionary computation literature to model the landscapes of artificial optimization problems. Here, we use the method for the first time to simulate a biological fitness landscape based on experimental evaluation. We demonstrate in this study that LSMs are capable not only of representing the structure of model fitness landscapes such as NK-landscapes, but also the fitness landscape of real DNA oligomers binding to a protein (allophycocyanin), data we derived from experimental evaluations on microarrays. The LSMs prove adept at modelling the progress of evolution as a function of various controlling parameters, as validated by evaluations on the real landscapes. Specifically, the ability of the model to 'predict' optimal mutation rates and other parameters of the evolution is demonstrated. A modification to the standard LSM also proves accurate at predicting the effects of recombination on the evolution.

  14. Real-time Adaptive Control Using Neural Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  15. Real-time prediction of the occurrence of GLE events

    NASA Astrophysics Data System (ADS)

    Núñez, Marlon; Reyes-Santiago, Pedro J.; Malandraki, Olga E.

    2017-07-01

    A tool for predicting the occurrence of Ground Level Enhancement (GLE) events using the UMASEP scheme is presented. This real-time tool, called HESPERIA UMASEP-500, is based on the detection of the magnetic connection, along which protons arrive in the near-Earth environment, by estimating the lag correlation between the time derivatives of 1 min soft X-ray flux (SXR) and 1 min near-Earth proton fluxes observed by the GOES satellites. Unlike current GLE warning systems, this tool can predict GLE events before the detection by any neutron monitor (NM) station. The prediction performance measured for the period from 1986 to 2016 is presented for two consecutive periods, because of their notable difference in performance. For the 2000-2016 period, this prediction tool obtained a probability of detection (POD) of 53.8% (7 of 13 GLE events), a false alarm ratio (FAR) of 30.0%, and average warning times (AWT) of 8 min with respect to the first NM station's alert and 15 min to the GLE Alert Plus's warning. We have tested the model by replacing the GOES proton data with SOHO/EPHIN proton data, and the results are similar in terms of POD, FAR, and AWT for the same period. The paper also presents a comparison with a GLE warning system.

  16. Real-time MJO Identification and Subseasonal Predictions

    NASA Astrophysics Data System (ADS)

    Berry, E. K.; Weickmann, K.

    2012-12-01

    There is evidence that the Madden-Julian Oscillation (MJO) can enhance predictability of sensible weather possibly out to lead times of ~40-50 days. This includes high impact events such as extreme surface air temperatures and extended periods of severe storms/excessive precipitation. However, identification of MJOs in real-time is challenging because the weather-climate system is dominated by noise. In fact, stochastic extratropical dynamics can organize large scale subtropical wind fields and envelopes of tropical rainfall that can be misrepresented as MJOs especially when using combined wind and outgoing longwave radiation indices (Wheeler and Hendon, 2004). These mixed global wind-tropical convective variations (Weickmann and Berry, 2009) partially reflect the Global Wind Oscillation (GWO), which is non-oscillatory and does not provide useful forecast information beyond ~15 days. An analysis of outgoing longwave radiation (OLR) and global circulation data sets is performed for the 2006-07 through 2011-12 boreal cold seasons (which included the DYNAMO field experiment). During this roughly six year period nine MJOs were identified that had the potential to extend the range of skillful or useful prediction. The breakdown of these events and their interactions with ENSO are discussed. Examples of red noise dominated variations and predictability ramifications will also be given. These include the premature ending of the 2006-07 El-Niño, extratropical feedbacks during 2010-11 leading to a strong jet stream not consistent with La-Niña, and constructive interference of an MJO and La-Niña that contributed to the March 2012 Midwest-eastern USA "heat wave". The criticality to distinguish in real time between "sustained, coherent MJOs" and other types of coherent or noisy tropical-extratropical variability is emphasized. The fast, moderate MJOs that initiated during DYNAMO might provide clues about MJO initiation and succession.

  17. Predictable Components of ENSO Evolution in Real-time Multi-Model Predictions

    PubMed Central

    Zheng, Zhihai; Hu, Zeng-Zhen; L’Heureux, Michelle

    2016-01-01

    The most predictable components of the El Niño-Southern Oscillation (ENSO) evolution in real-time multi-model predictions are identified by applying an empirical orthogonal function analysis of the model data that maximizes the signal-to-noise ratio (MSN EOF). The normalized Niño3.4 index is analyzed for nine 3-month overlapping seasons. In this sense, the first most predictable component (MSN EOF1) is the decaying phase of ENSO during the Northern Hemisphere spring, followed by persistence through autumn and winter. The second most predictable component of ENSO evolution, with lower prediction skill and smaller explained variance than MSN EOF1, corresponds to the growth during spring and then persistence in summer and autumn. This result suggests that decay phase of ENSO is more predictable than the growth phase. Also, the most predictable components and the forecast skills in dynamical and statistical models are similar overall, with some differences arising during spring season initial conditions. Finally, the reconstructed predictions, with only the first two MSN components, show higher skill than the model raw predictions. Therefore this method can be used as a diagnostic for model comparison and development, and it can provide a new perspective for the most predictable components of ENSO. PMID:27775016

  18. Predictable Components of ENSO Evolution in Real-time Multi-Model Predictions.

    PubMed

    Zheng, Zhihai; Hu, Zeng-Zhen; L'Heureux, Michelle

    2016-10-24

    The most predictable components of the El Niño-Southern Oscillation (ENSO) evolution in real-time multi-model predictions are identified by applying an empirical orthogonal function analysis of the model data that maximizes the signal-to-noise ratio (MSN EOF). The normalized Niño3.4 index is analyzed for nine 3-month overlapping seasons. In this sense, the first most predictable component (MSN EOF1) is the decaying phase of ENSO during the Northern Hemisphere spring, followed by persistence through autumn and winter. The second most predictable component of ENSO evolution, with lower prediction skill and smaller explained variance than MSN EOF1, corresponds to the growth during spring and then persistence in summer and autumn. This result suggests that decay phase of ENSO is more predictable than the growth phase. Also, the most predictable components and the forecast skills in dynamical and statistical models are similar overall, with some differences arising during spring season initial conditions. Finally, the reconstructed predictions, with only the first two MSN components, show higher skill than the model raw predictions. Therefore this method can be used as a diagnostic for model comparison and development, and it can provide a new perspective for the most predictable components of ENSO.

  19. Real-time multi-model decadal climate predictions

    NASA Astrophysics Data System (ADS)

    Smith, Doug M.; Scaife, Adam A.; Boer, George J.; Caian, Mihaela; Doblas-Reyes, Francisco J.; Guemas, Virginie; Hawkins, Ed; Hazeleger, Wilco; Hermanson, Leon; Ho, Chun Kit; Ishii, Masayoshi; Kharin, Viatcheslav; Kimoto, Masahide; Kirtman, Ben; Lean, Judith; Matei, Daniela; Merryfield, William J.; Müller, Wolfgang A.; Pohlmann, Holger; Rosati, Anthony; Wouters, Bert; Wyser, Klaus

    2013-12-01

    We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the

  20. Real-world predictions from ab initio molecular dynamics simulations.

    PubMed

    Kirchner, Barbara; di Dio, Philipp J; Hutter, Jürg

    2012-01-01

    In this review we present the techniques of ab initio molecular dynamics simulation improved to its current stage where the analysis of existing processes and the prediction of further chemical features and real-world processes are feasible. For this reason we describe the relevant developments in ab initio molecular dynamics leading to this stage. Among them, parallel implementations, different basis set functions, density functionals, and van der Waals corrections are reported. The chemical features accessible through AIMD are discussed. These are IR, NMR, as well as EXAFS spectra, sampling methods like metadynamics and others, Wannier functions, dipole moments of molecules in condensed phase, and many other properties. Electrochemical reactions investigated by ab initio molecular dynamics methods in solution, on surfaces as well as complex interfaces, are also presented.

  1. Data assimialation for real-time prediction and reanalysis

    NASA Astrophysics Data System (ADS)

    Shprits, Y.; Kellerman, A. C.; Podladchikova, T.; Kondrashov, D. A.; Ghil, M.

    2015-12-01

    We discuss the how data assimilation can be used for the analysis of individual satellite anomalies, development of long-term evolution reconstruction that can be used for the specification models, and use of data assimilation to improve the now-casting and focusing of the radiation belts. We also discuss advanced data assimilation methods such as parameter estimation and smoothing.The 3D data assimilative VERB allows us to blend together data from GOES, RBSP A and RBSP B. Real-time prediction framework operating on our web site based on GOES, RBSP A, B and ACE data and 3D VERB is presented and discussed. In this paper we present a number of application of the data assimilation with the VERB 3D code. 1) Model with data assimilation allows to propagate data to different pitch angles, energies, and L-shells and blends them together with the physics based VERB code in an optimal way. We illustrate how we use this capability for the analysis of the previous events and for obtaining a global and statistical view of the system. 2) The model predictions strongly depend on initial conditions that are set up for the model. Therefore the model is as good as the initial conditions that it uses. To produce the best possible initial condition data from different sources ( GOES, RBSP A, B, our empirical model predictions based on ACE) are all blended together in an optimal way by means of data assimilation as described above. The resulting initial condition does not have gaps. That allows us to make a more accurate predictions.

  2. T 3-Interferometer for atoms

    NASA Astrophysics Data System (ADS)

    Zimmermann, M.; Efremov, M. A.; Roura, A.; Schleich, W. P.; DeSavage, S. A.; Davis, J. P.; Srinivasan, A.; Narducci, F. A.; Werner, S. A.; Rasel, E. M.

    2017-04-01

    The quantum mechanical propagator of a massive particle in a linear gravitational potential derived already in 1927 by Kennard [2, 3] contains a phase that scales with the third power of the time T during which the particle experiences the corresponding force. Since in conventional atom interferometers the internal atomic states are all exposed to the same acceleration a, this T^3-phase cancels out and the interferometer phase scales as T^2. In contrast, by applying an external magnetic field we prepare two different accelerations a_1 and a_2 for two internal states of the atom, which translate themselves into two different cubic phases and the resulting interferometer phase scales as T^3. We present the theoretical background for, and summarize our progress towards experimentally realizing such a novel atom interferometer.

  3. Predicting Rocket or Jet Noise in Real Time

    NASA Technical Reports Server (NTRS)

    Frendi, Kader

    2007-01-01

    A semi-empirical theoretical model and a C++ computer program that implements the model have been developed for use in predicting the noise generated by a rocket or jet engine. The computer program, entitled the Realtime Rocket and Jet Engine Noise Analysis and Prediction Software, is one of two main subsystems of the Acoustic Prediction/Measurement Tool, which comprises software, acoustic instrumentation, and electronic hardware combined to afford integrated capabilities for real-time prediction and measurement of noise emitted by rocket and jet engines. [The other main subsystem, consisting largely of acoustic instrumentation and electronic hardware, is described in Wireless Acoustic Measurement System, which appears elsewhere in this section.] The theoretical model was derived from the fundamental laws of fluid mechanics, as first was done by M. J. Lighthill in his now famous theory of aerodynamically generated sound. The far-field approximation of the Lighthill theory is incorporated into this model. Many other contributions from various researchers have also been introduced into the model. The model accounts for two noise components: shear noise and self noise. The final result of the model is expressed in terms of a volume integral of the acoustic intensities attributable to these two components, subject to various directivity coefficients. The computer program was written to solve the volume integral. The inputs required by the program are two data files from a computational fluid dynamics (CFD) simulation of the flow of interest: the computational-grid file and the solution file. The CFD solution should be one that has been obtained for conditions that closely approximate those of an experimental test that is yet to be performed. In the current state of development of the model and software, it is recommended that the observation points lie along a radius at an angle >60 from the jet axis. The software provides, and is driven via, a graphical user interface

  4. Toward the Real-Time Tsunami Parameters Prediction

    NASA Astrophysics Data System (ADS)

    Lavrentyev, Mikhail; Romanenko, Alexey; Marchuk, Andrey

    2013-04-01

    Today, a wide well-developed system of deep ocean tsunami detectors operates over the Pacific. Direct measurements of tsunami-wave time series are available. However, tsunami-warning systems fail to predict basic parameters of tsunami waves on time. Dozens examples could be provided. In our view, the lack of computational power is the main reason of these failures. At the same time, modern computer technologies such as, GPU (graphic processing unit) and FPGA (field programmable gates array), can dramatically improve data processing performance, which may enhance timely tsunami-warning prediction. Thus, it is possible to address the challenge of real-time tsunami forecasting for selected geo regions. We propose to use three new techniques in the existing tsunami warning systems to achieve real-time calculation of tsunami wave parameters. First of all, measurement system (DART buoys location, e.g.) should be optimized (both in terms of wave arriving time and amplitude parameter). The corresponding software application exists today and is ready for use [1]. We consider the example of the coastal line of Japan. Numerical tests show that optimal installation of only 4 DART buoys (accounting the existing sea bed cable) will reduce the tsunami wave detection time to only 10 min after an underwater earthquake. Secondly, as was shown by this paper authors, the use of GPU/FPGA technologies accelerates the execution of the MOST (method of splitting tsunami) code by 100 times [2]. Therefore, tsunami wave propagation over the ocean area 2000*2000 km (wave propagation simulation: time step 10 sec, recording each 4th spatial point and 4th time step) could be calculated at: 3 sec with 4' mesh 50 sec with 1' mesh 5 min with 0.5' mesh The algorithm to switch from coarse mesh to the fine grain one is also available. Finally, we propose the new algorithm for tsunami source parameters determination by real-time processing the time series, obtained at DART. It is possible to approximate

  5. Geographically distributed real-time digital simulations using linear prediction

    SciTech Connect

    Liu, Ren; Mohanpurkar, Manish; Panwar, Mayank; Hovsapian, Rob; Srivastava, Anurag; Suryanarayanan, Siddharth

    2016-07-04

    Real time simulation is a powerful tool for analyzing, planning, and operating modern power systems. For analyzing the ever evolving power systems and understanding complex dynamic and transient interactions larger real time computation capabilities are essential. These facilities are interspersed all over the globe and to leverage unique facilities geographically-distributed real-time co-simulation in analyzing the power systems is pursued and presented. However, the communication latency between different simulator locations may lead to inaccuracy in geographically distributed real-time co-simulations. In this paper, the effect of communication latency on geographically distributed real-time co-simulation is introduced and discussed. In order to reduce the effect of the communication latency, a real-time data predictor, based on linear curve fitting is developed and integrated into the distributed real-time co-simulation. Two digital real time simulators are used to perform dynamic and transient co-simulations with communication latency and predictor. Results demonstrate the effect of the communication latency and the performance of the real-time data predictor to compensate it.

  6. Geographically distributed real-time digital simulations using linear prediction

    DOE PAGES

    Liu, Ren; Mohanpurkar, Manish; Panwar, Mayank; ...

    2016-07-04

    Real time simulation is a powerful tool for analyzing, planning, and operating modern power systems. For analyzing the ever evolving power systems and understanding complex dynamic and transient interactions larger real time computation capabilities are essential. These facilities are interspersed all over the globe and to leverage unique facilities geographically-distributed real-time co-simulation in analyzing the power systems is pursued and presented. However, the communication latency between different simulator locations may lead to inaccuracy in geographically distributed real-time co-simulations. In this paper, the effect of communication latency on geographically distributed real-time co-simulation is introduced and discussed. In order to reduce themore » effect of the communication latency, a real-time data predictor, based on linear curve fitting is developed and integrated into the distributed real-time co-simulation. Two digital real time simulators are used to perform dynamic and transient co-simulations with communication latency and predictor. Results demonstrate the effect of the communication latency and the performance of the real-time data predictor to compensate it.« less

  7. Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

    NASA Astrophysics Data System (ADS)

    Balasubramanian, A.; Shamsuddin, R.; Prabhakaran, B.; Sawant, A.

    2017-03-01

    Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%) (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable

  8. Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts.

    PubMed

    Balasubramanian, A; Shamsuddin, R; Prabhakaran, B; Sawant, A

    2017-03-07

    Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%); (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable

  9. Does psychophysiological predictive anticipatory activity predict real or future probable events?

    PubMed

    Tressoldi, Patrizio E; Martinelli, Massimiliano; Semenzato, Luca; Gonella, Alessandro

    2015-01-01

    The possibility of predicting random future events before any sensory clues by using human physiology as a dependent variable has been supported by the meta-analysis of Moss-bridge et al. (2012)(1) and recent findings by Tressoldi et al. (2011 and 2013)(2,3) and Mossbridge et al. (2014)(4) defined this phenomenon predictive anticipatory activity (PAA). From a theoretical point of view, one interesting question is whether PAA is related to the effective, real future presentation of these stimuli or whether it is related only to the probability of their presentation. This hypothesis was tested with four experiments, two using heart rate and two using pupil dilation as dependent variables. In all four experiments, both a neutral stimulus and a potentially threatening stimulus were predicted 7-10% above chance, independently from whether the predicted threatening stimulus was presented or not. These findings are discussed with reference to the "grandfather paradox," and some candidate explanations for this phenomena are presented. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Application of indoor noise prediction in the real world

    NASA Astrophysics Data System (ADS)

    Lewis, David N.

    2002-11-01

    Predicting indoor noise in industrial workrooms is an important part of the process of designing industrial plants. Predicted levels are used in the design process to determine compliance with occupational-noise regulations, and to estimate levels inside the walls in order to predict community noise radiated from the building. Once predicted levels are known, noise-control strategies can be developed. In this paper an overview of over 20 years of experience is given with the use of various prediction approaches to manage noise in Unilever plants. This work has applied empirical and ray-tracing approaches separately, and in combination, to design various packaging and production plants and other facilities. The advantages of prediction methods in general, and of the various approaches in particular, will be discussed. A case-study application of prediction methods to the optimization of noise-control measures in a food-packaging plant will be presented. Plans to acquire a simplified prediction model for use as a company noise-screening tool will be discussed.

  11. The value of surrogate endpoints for predicting real-world survival across five cancer types.

    PubMed

    Shafrin, Jason; Brookmeyer, Ron; Peneva, Desi; Park, Jinhee; Zhang, Jie; Figlin, Robert A; Lakdawalla, Darius N

    2016-01-01

    It is unclear how well different outcome measures in randomized controlled trials (RCTs) perform in predicting real-world cancer survival. We assess the ability of RCT overall survival (OS) and surrogate endpoints - progression-free survival (PFS) and time to progression (TTP) - to predict real-world OS across five cancers. We identified 20 treatments and 31 indications for breast, colorectal, lung, ovarian, and pancreatic cancer that had a phase III RCT reporting median OS and median PFS or TTP. Median real-world OS was determined using a Kaplan-Meier estimator applied to patients in the Surveillance and Epidemiology End Results (SEER)-Medicare database (1991-2010). Performance of RCT OS and PFS/TTP in predicting real-world OS was measured using t-tests, median absolute prediction error, and R(2) from linear regressions. Among 72,600 SEER-Medicare patients similar to RCT participants, median survival was 5.9 months for trial surrogates, 14.1 months for trial OS, and 13.4 months for real-world OS. For this sample, regression models using clinical trial OS and trial surrogates as independent variables predicted real-world OS significantly better than models using surrogates alone (P = 0.026). Among all real-world patients using sample treatments (N = 309,182), however, adding trial OS did not improve predictive power over predictions based on surrogates alone (P = 0.194). Results were qualitatively similar using median absolute prediction error and R(2) metrics. Among the five tumor types investigated, trial OS and surrogates were each independently valuable in predicting real-world OS outcomes for patients similar to trial participants. In broader real-world populations, however, trial OS added little incremental value over surrogates alone.

  12. A real-time algorithm for predicting core temperature in humans.

    PubMed

    Gribok, Andrei V; Buller, Mark J; Hoyt, Reed W; Reifman, Jaques

    2010-07-01

    In this paper, we present a real-time implementation of a previously developed offline algorithm for predicting core temperature in humans. The real-time algorithm uses a zero-phase Butterworth digital filter to smooth the data and an autoregressive (AR) model to predict core temperature. The performance of the algorithm is assessed in terms of its prediction accuracy, quantified by the root mean squared error (RMSE), and in terms of prediction uncertainty, quantified by statistically based prediction intervals (PIs). To evaluate the performance of the algorithm, we simulated real-time implementation using core-temperature data collected during two different field studies, involving ten different individuals. One of the studies includes a case of heat illness suffered by one of the participants. The results indicate that although the real-time predictions yielded RMSEs that are larger than those of the offline algorithm, the real-time algorithm does produce sufficiently accurate predictions for practically meaningful prediction horizons (approximately 20 min). The algorithm reached alert (39 degrees C) and alarm (39.5 degrees C) thresholds for the heat-ill individual but did not even attain the alert threshold for the other individuals, demonstrating the algorithm's good sensitivity and specificity. The PIs reflected, in an intuitively expected manner, the uncertainty associated with real-time forecast as a function of prediction horizon and core-temperature variability. The results also corroborate the feasibility of "universal" AR models, where an offline-developed model based on one individual's data could be used to predict any other individual in real time. We conclude that the real-time implementation of the algorithm confirms the attributes observed in the offline version and, hence, could be considered as a warning tool for impending heat illnesses.

  13. Time will show: real time predictions during interpersonal action perception.

    PubMed

    Manera, Valeria; Schouten, Ben; Verfaillie, Karl; Becchio, Cristina

    2013-01-01

    Predictive processes are crucial not only for interpreting the actions of individual agents, but also to predict how, in the context of a social interaction between two agents, the actions of one agent relate to the actions of a second agent. In the present study we investigated whether, in the context of a communicative interaction between two agents, observers can use the actions of one agent to predict when the action of a second agent will take place. Participants observed point-light displays of two agents (A and B) performing separate actions. In the communicative condition, the action performed by agent B responded to a communicative gesture performed by agent A. In the individual condition, agent A's communicative action was substituted with a non-communicative action. For each condition, we manipulated the temporal coupling of the actions of the two agents, by varying the onset of agent A's action. Using a simultaneous masking detection task, we demonstrated that the timing manipulation had a critical effect on the communicative condition, with the visual discrimination of agent B increasing linearly while approaching the original interaction timing. No effect of the timing manipulation was found for the individual condition. Our finding complements and extends previous evidence for interpersonal predictive coding, suggesting that the communicative gestures of one agent can serve not only to predict what the second agent will do, but also when his/her action will take place.

  14. Task relevance predicts gaze in videos of real moving scenes.

    PubMed

    Howard, Christina J; Gilchrist, Iain D; Troscianko, Tom; Behera, Ardhendu; Hogg, David C

    2011-09-01

    Low-level stimulus salience and task relevance together determine the human fixation priority assigned to scene locations (Fecteau and Munoz in Trends Cogn Sci 10(8):382-390, 2006). However, surprisingly little is known about the contribution of task relevance to eye movements during real-world visual search where stimuli are in constant motion and where the 'target' for the visual search is abstract and semantic in nature. Here, we investigate this issue when participants continuously search an array of four closed-circuit television (CCTV) screens for suspicious events. We recorded eye movements whilst participants watched real CCTV footage and moved a joystick to continuously indicate perceived suspiciousness. We find that when multiple areas of a display compete for attention, gaze is allocated according to relative levels of reported suspiciousness. Furthermore, this measure of task relevance accounted for twice the amount of variance in gaze likelihood as the amount of low-level visual changes over time in the video stimuli.

  15. Improved Short-Term Clock Prediction Method for Real-Time Positioning

    PubMed Central

    Lv, Yifei; Dai, Zhiqiang; Zhao, Qile; Yang, Sheng; Zhou, Jinning; Liu, Jingnan

    2017-01-01

    The application of real-time precise point positioning (PPP) requires real-time precise orbit and clock products that should be predicted within a short time to compensate for the communication delay or data gap. Unlike orbit correction, clock correction is difficult to model and predict. The widely used linear model hardly fits long periodic trends with a small data set and exhibits significant accuracy degradation in real-time prediction when a large data set is used. This study proposes a new prediction model for maintaining short-term satellite clocks to meet the high-precision requirements of real-time clocks and provide clock extrapolation without interrupting the real-time data stream. Fast Fourier transform (FFT) is used to analyze the linear prediction residuals of real-time clocks. The periodic terms obtained through FFT are adopted in the sliding window prediction to achieve a significant improvement in short-term prediction accuracy. This study also analyzes and compares the accuracy of short-term forecasts (less than 3 h) by using different length observations. Experimental results obtained from International GNSS Service (IGS) final products and our own real-time clocks show that the 3-h prediction accuracy is better than 0.85 ns. The new model can replace IGS ultra-rapid products in the application of real-time PPP. It is also found that there is a positive correlation between the prediction accuracy and the short-term stability of on-board clocks. Compared with the accuracy of the traditional linear model, the accuracy of the static PPP using the new model of the 2-h prediction clock in N, E, and U directions is improved by about 50%. Furthermore, the static PPP accuracy of 2-h clock products is better than 0.1 m. When an interruption occurs in the real-time model, the accuracy of the kinematic PPP solution using 1-h clock prediction product is better than 0.2 m, without significant accuracy degradation. This model is of practical significance

  16. Real Time Volcanic Cloud Products and Predictions for Aviation Alerts

    NASA Technical Reports Server (NTRS)

    Krotkov, Nickolay A.; Habib, Shahid; da Silva, Arlindo; Hughes, Eric; Yang, Kai; Brentzel, Kelvin; Seftor, Colin; Li, Jason Y.; Schneider, David; Guffanti, Marianne; hide

    2014-01-01

    Volcanic eruptions can inject significant amounts of sulfur dioxide (SO2) and volcanic ash into the atmosphere, posing a substantial risk to aviation safety. Ingesting near-real time and Direct Readout satellite volcanic cloud data is vital for improving reliability of volcanic ash forecasts and mitigating the effects of volcanic eruptions on aviation and the economy. NASA volcanic products from the Ozone Monitoring Insrument (OMI) aboard the Aura satellite have been incorporated into Decision Support Systems of many operational agencies. With the Aura mission approaching its 10th anniversary, there is an urgent need to replace OMI data with those from the next generation operational NASA/NOAA Suomi National Polar Partnership (SNPP) satellite. The data provided from these instruments are being incorporated into forecasting models to provide quantitative ash forecasts for air traffic management. This study demonstrates the feasibility of the volcanic near-real time and Direct Readout data products from the new Ozone Monitoring and Profiling Suite (OMPS) ultraviolet sensor onboard SNPP for monitoring and forecasting volcanic clouds. The transition of NASA data production to our operational partners is outlined. Satellite observations are used to constrain volcanic cloud simulations and improve estimates of eruption parameters, resulting in more accurate forecasts. This is demonstrated for the 2012 eruption of Copahue. Volcanic eruptions are modeled using the Goddard Earth Observing System, Version 5 (GEOS-5) and the Goddard Chemistry Aerosol and Radiation Transport (GOCART) model. A hindcast of the disruptive eruption from Iceland's Eyjafjallajokull is used to estimate aviation re-routing costs using Metron Aviation's ATM Tools.

  17. Essays on the predictability of oil shocks and yield curves for real-time output growth

    NASA Astrophysics Data System (ADS)

    Carlton, Amelie B.

    This dissertation is a collection of three essays that revisits the long-standing puzzle of the apparently disproportionate effect of oil prices in the economy by examining output growth predictability with real-time data. Each study of the predictive content of oil shocks is from a different perspective by using newly developed real-time datasets, which allows for replicating the economic environment faced by policymakers in real time. The first study extends the conventional set of models of output growth determination by investigating predictability of models that incorporate various functional forms of oil prices and real-time data. The results are supportive of the relationship of GDP and oil in the context of Granger causality with real-time data. In the second essay, I use oil shocks to predict the economy is changing direction earlier than would be predicted by solely using initial GDP releases. The model provides compelling evidence of negative GDP growth predictability in response to oil price shocks, which could shorten the "recognition lag" for successful implementation of discretionary counter-cyclical policies. In the third essay, I evaluate short-horizon output growth predictability using real-time data for different sample periods. I find strong evidence of predictability at the one-quarter and four-quarter horizon for the United States. The major result of the paper is that we reject the null hypothesis of no predictability against an alternative hypothesis of predictability with oil shocks that include yield curves in the forecasting regression. This relationship suggests the combination of monetary policy and oil shocks are important for subsequent GDP growth.

  18. GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world.

    PubMed

    Panayidou, Klea; Gsteiger, Sandro; Egger, Matthias; Kilcher, Gablu; Carreras, Máximo; Efthimiou, Orestis; Debray, Thomas P A; Trelle, Sven; Hummel, Noemi

    2016-09-01

    The performance of a drug in a clinical trial setting often does not reflect its effect in daily clinical practice. In this third of three reviews, we examine the applications that have been used in the literature to predict real-world effectiveness from randomized controlled trial efficacy data. We searched MEDLINE, EMBASE from inception to March 2014, the Cochrane Methodology Register, and websites of key journals and organisations and reference lists. We extracted data on the type of model and predictions, data sources, validation and sensitivity analyses, disease area and software. We identified 12 articles in which four approaches were used: multi-state models, discrete event simulation models, physiology-based models and survival and generalized linear models. Studies predicted outcomes over longer time periods in different patient populations, including patients with lower levels of adherence or persistence to treatment or examined doses not tested in trials. Eight studies included individual patient data. Seven examined cardiovascular and metabolic diseases and three neurological conditions. Most studies included sensitivity analyses, but external validation was performed in only three studies. We conclude that mathematical modelling to predict real-world effectiveness of drug interventions is not widely used at present and not well validated. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

  19. Evaluation of the predictability of real-time crash risk models.

    PubMed

    Xu, Chengcheng; Liu, Pan; Wang, Wei

    2016-09-01

    The primary objective of the present study was to investigate the predictability of crash risk models that were developed using high-resolution real-time traffic data. More specifically the present study sought answers to the following questions: (a) how to evaluate the predictability of a real-time crash risk model; and (b) how to improve the predictability of a real-time crash risk model. The predictability is defined as the crash probability given the crash precursor identified by the crash risk model. An equation was derived based on the Bayes' theorem for estimating approximately the predictability of crash risk models. The estimated predictability was then used to quantitatively evaluate the effects of the threshold of crash precursors, the matched and unmatched case-control design, and the control-to-case ratio on the predictability of crash risk models. It was found that: (a) the predictability of a crash risk model can be measured as the product of prior crash probability and the ratio between sensitivity and false alarm rate; (b) there is a trade-off between the predictability and sensitivity of a real-time crash risk model; (c) for a given level of sensitivity, the predictability of the crash risk model that is developed using the unmatched case-controlled sample is always better than that of the model developed using the matched case-controlled sample; and (d) when the control-to-case ratio is beyond 4:1, the increase in control-to-case ratio does not lead to clear improvements in predictability.

  20. Challenges in Real-Time Prediction of Infectious Disease: A Case Study of Dengue in Thailand

    PubMed Central

    Lauer, Stephen A.; Sakrejda, Krzysztof; Iamsirithaworn, Sopon; Hinjoy, Soawapak; Suangtho, Paphanij; Suthachana, Suthanun; Clapham, Hannah E.; Salje, Henrik; Cummings, Derek A. T.; Lessler, Justin

    2016-01-01

    Epidemics of communicable diseases place a huge burden on public health infrastructures across the world. Producing accurate and actionable forecasts of infectious disease incidence at short and long time scales will improve public health response to outbreaks. However, scientists and public health officials face many obstacles in trying to create such real-time forecasts of infectious disease incidence. Dengue is a mosquito-borne virus that annually infects over 400 million people worldwide. We developed a real-time forecasting model for dengue hemorrhagic fever in the 77 provinces of Thailand. We created a practical computational infrastructure that generated multi-step predictions of dengue incidence in Thai provinces every two weeks throughout 2014. These predictions show mixed performance across provinces, out-performing seasonal baseline models in over half of provinces at a 1.5 month horizon. Additionally, to assess the degree to which delays in case reporting make long-range prediction a challenging task, we compared the performance of our real-time predictions with predictions made with fully reported data. This paper provides valuable lessons for the implementation of real-time predictions in the context of public health decision making. PMID:27304062

  1. Predicting Pedestrian Flow: A Methodology and a Proof of Concept Based on Real-Life Data

    PubMed Central

    Davidich, Maria; Köster, Gerta

    2013-01-01

    Building a reliable predictive model of pedestrian motion is very challenging: Ideally, such models should be based on observations made in both controlled experiments and in real-world environments. De facto, models are rarely based on real-world observations due to the lack of available data; instead, they are largely based on intuition and, at best, literature values and laboratory experiments. Such an approach is insufficient for reliable simulations of complex real-life scenarios: For instance, our analysis of pedestrian motion under natural conditions at a major German railway station reveals that the values for free-flow velocities and the flow-density relationship differ significantly from widely used literature values. It is thus necessary to calibrate and validate the model against relevant real-life data to make it capable of reproducing and predicting real-life scenarios. In this work we aim at constructing such realistic pedestrian stream simulation. Based on the analysis of real-life data, we present a methodology that identifies key parameters and interdependencies that enable us to properly calibrate the model. The success of the approach is demonstrated for a benchmark model, a cellular automaton. We show that the proposed approach significantly improves the reliability of the simulation and hence the potential prediction accuracy. The simulation is validated by comparing the local density evolution of the measured data to that of the simulated data. We find that for our model the most sensitive parameters are: the source-target distribution of the pedestrian trajectories, the schedule of pedestrian appearances in the scenario and the mean free-flow velocity. Our results emphasize the need for real-life data extraction and analysis to enable predictive simulations. PMID:24386186

  2. Predicting pedestrian flow: a methodology and a proof of concept based on real-life data.

    PubMed

    Davidich, Maria; Köster, Gerta

    2013-01-01

    Building a reliable predictive model of pedestrian motion is very challenging: Ideally, such models should be based on observations made in both controlled experiments and in real-world environments. De facto, models are rarely based on real-world observations due to the lack of available data; instead, they are largely based on intuition and, at best, literature values and laboratory experiments. Such an approach is insufficient for reliable simulations of complex real-life scenarios: For instance, our analysis of pedestrian motion under natural conditions at a major German railway station reveals that the values for free-flow velocities and the flow-density relationship differ significantly from widely used literature values. It is thus necessary to calibrate and validate the model against relevant real-life data to make it capable of reproducing and predicting real-life scenarios. In this work we aim at constructing such realistic pedestrian stream simulation. Based on the analysis of real-life data, we present a methodology that identifies key parameters and interdependencies that enable us to properly calibrate the model. The success of the approach is demonstrated for a benchmark model, a cellular automaton. We show that the proposed approach significantly improves the reliability of the simulation and hence the potential prediction accuracy. The simulation is validated by comparing the local density evolution of the measured data to that of the simulated data. We find that for our model the most sensitive parameters are: the source-target distribution of the pedestrian trajectories, the schedule of pedestrian appearances in the scenario and the mean free-flow velocity. Our results emphasize the need for real-life data extraction and analysis to enable predictive simulations.

  3. Cytosolic T3-binding protein modulates dynamic alteration of T3-mediated gene expression in cells.

    PubMed

    Takeshige, Keiko; Sekido, Takashi; Kitahara, Jun-ichirou; Ohkubo, Yousuke; Hiwatashi, Dai; Ishii, Hiroaki; Nishio, Shin-ichi; Takeda, Teiji; Komatsu, Mitsuhisa; Suzuki, Satoru

    2014-01-01

    μ-Crystallin (CRYM) is also known as NADPH-dependent cytosolic T3-binding protein. A study using CRYM-null mice suggested that CRYM stores triiodothyronine (T3) in tissues. We previously established CRYM-expressing cells derived from parental GH3 cells. To examine the precise regulation of T3-responsive genes in the presence of CRYM, we evaluated serial alterations of T3-responsive gene expression by changing pericellular T3 concentrations in the media. We estimated the constitutive expression of three T3-responsive genes, growth hormone (GH), deiodinase 1 (Dio1), and deiodinase 2 (Dio2), in two cell lines. Subsequently, we measured the responsiveness of these three genes at 4, 8, 16, and 24 h after adding various concentrations of T3. We also estimated the levels of these mRNAs 24 and 48 h after removing T3. The levels of constitutive expression of GH and Dio1 were low and high in C8 cells, respectively, while Dio2 expression was not significantly different between GH3 and C8 cells. When treated with T3, Dio2 expression was significantly enhanced in C8 cells, while there were no differences in GH or Dio1 expression between GH3 and C8 cell lines. In contrast, removal of T3 retained the mRNA expression of GH and Dio2 in C8 cells. These results suggest that CRYM expression increases and sustains the T3 responsiveness of genes in cells, especially with alteration of the pericellular T3 concentration. The heterogeneity of T3-related gene expression is dependent on cellular CRYM expression in cases of dynamic changes in pericellular T3 concentration.

  4. Development and implementation of a real-time 30-day readmission predictive model.

    PubMed

    Cronin, Patrick R; Greenwald, Jeffrey L; Crevensten, Gwen C; Chueh, Henry C; Zai, Adrian H

    2014-01-01

    Hospitals are under great pressure to reduce readmissions of patients. Being able to reliably predict patients at increased risk for rehospitalization would allow for tailored interventions to be offered to them. This requires the creation of a functional predictive model specifically designed to support real-time clinical operations. A predictive model for readmissions within 30 days of discharge was developed using retrospective data from 45,924 MGH admissions between 2/1/2012 and 1/31/2013 only including factors that would be available by the day after admission. It was then validated prospectively in a real-time implementation for 3,074 MGH admissions between 10/1/2013 and 10/31/2013. The model developed retrospectively had an AUC of 0.705 with good calibration. The real-time implementation had an AUC of 0.671 although the model was overestimating readmission risk. A moderately discriminative real-time 30-day readmission predictive model can be developed and implemented in a large academic hospital.

  5. AL and Dst Predictions with the Real-Time WINDMI Model

    NASA Astrophysics Data System (ADS)

    Mays, L.; Horton, W.; Spencer, E.; Weigel, R.; Vassiliadis, D.; Kozyra, J.

    2006-12-01

    First results are presented of the space weather forecasting capability of the real-time WINDMI model that has been operating since February 2006 as a physics based AL and Dst prediction tool. The well documented WINDMI model is a network of eight coupled ordinary differential equations which describe the transfer of power from the solar wind through the geomagnetic tail, the ionosphere, and ring current in the solar WIND driven Magnetosphere-Ionosphere system. WINDMI includes ring current energization physics from substrom injections and outputs a predicted westward auroral electojet index (AL) and equatorial geomagnetic disturbance storm time index (Dst). At the time of abstract submission (August 2006) real-time WINDMI has captured two storms with the first alarm being sent by email for a moderate -150 nT storm on 14-15 April 2006 and a second -100 nT storm on 19-20 August 2006. During the August 2006 storm period the WINDMI model was a more consistent Dst predictor than the Kyoto WDC Quicklook Dst data which has an incorrect offset of ~-100 nT. Real-time WINDMI uses real-time solar wind data from received from ACE every ten minutes to derive in less than one minute of computational time a predicted AL and Dst and magnetopause standoff distance. Real-time WINDMI predicts the AL index one hour earlier than the data is available from the Kyoto WDC Quicklook website and the Dst index two hours earlier. Every ten minutes real-time AL and Dst data and WINDMI predictions are shown on this website: http://orion.ph.utexas.edu/~windmi/realtime/. The 18 physical parameters of WINDMI are approximated analytically from planetary parameters and optimized within physically allowable ranges using the genetic algorithm. Real-time WINDMI parameters are optimized every hour based on 8 hours of past model/data comparison. In addition to the geomagnetic indices the model predicts the major energy components and power transfers in the solar wind-magnetosphere-ionosphere system. The

  6. Real-time prediction of mediastinal lymph node malignancy by endobronchial ultrasound.

    PubMed

    Shafiek, Hanaa; Fiorentino, Federico; Peralta, Alejandro David; Serra, Enrique; Esteban, Blanca; Martinez, Rocío; Noguera, Maria Angels; Moyano, Pere; Sala, Ernest; Sauleda, Jaume; Cosío, Borja G

    2014-06-01

    To evaluate the utility of different ultrasonographic (US) features in differentiating benign and malignant lymph node (LN) by endobronchial ultrasound (EBUS) and validate a score for real-time clinical application. 208 mediastinal LN acquired from 141 patients were analyzed. Six different US criteria were evaluated (short axis ≥10 mm, shape, margin, echogenicity, and central hilar structure [CHS], and presence of hyperechoic density) by two observers independently. A simplified score was generated where the presence of margin distinction, round shape and short axis ≥10 mm were scored as 1 and heterogeneous echogenicity and absence of CHS were scored as 1.5. The score was evaluated prospectively for real-time clinical application in 65 LN during EBUS procedure in 39 patients undertaken by two experienced operators. These criteria were correlated with the histopathological results and the sensitivity, specificity, positive and negative predictive values (PPV and NPV) were calculated. Both heterogenicity and absence of CHS had the highest sensitivity and NPV (≥90%) for predicting LN malignancy with acceptable inter-observer agreement (92% and 87% respectively). On real-time application, the sensitivity and specificity of the score >5 were 78% and 86% respectively; only the absence of CHS, round shape and size of LN were significantly associated with malignant LN. Combination of different US criteria can be useful for prediction of mediastinal LN malignancy and valid for real-time clinical application. Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.

  7. The Neurodynamics of Affect in the Laboratory Predicts Persistence of Real-World Emotional Responses.

    PubMed

    Heller, Aaron S; Fox, Andrew S; Wing, Erik K; McQuisition, Kaitlyn M; Vack, Nathan J; Davidson, Richard J

    2015-07-22

    Failure to sustain positive affect over time is a hallmark of depression and other psychopathologies, but the mechanisms supporting the ability to sustain positive emotional responses are poorly understood. Here, we investigated the neural correlates associated with the persistence of positive affect in the real world by conducting two experiments in humans: an fMRI task of reward responses and an experience-sampling task measuring emotional responses to a reward obtained in the field. The magnitude of DLPFC engagement to rewards administered in the laboratory predicted reactivity of real-world positive emotion following a reward administered in the field. Sustained ventral striatum engagement in the laboratory positively predicted the duration of real-world positive emotional responses. These results suggest that common pathways are associated with the unfolding of neural processes over seconds and with the dynamics of emotions experienced over minutes. Examining such dynamics may facilitate a better understanding of the brain-behavior associations underlying emotion. Significance statement: How real-world emotion, experienced over seconds, minutes, and hours, is instantiated in the brain over the course of milliseconds and seconds is unknown. We combined a novel, real-world experience-sampling task with fMRI to examine how individual differences in real-world emotion, experienced over minutes and hours, is subserved by affective neurodynamics of brain activity over the course of seconds. When winning money in the real world, individuals sustaining positive emotion the longest were those with the most prolonged ventral striatal activity. These results suggest that common pathways are associated with the unfolding of neural processes over seconds and with the dynamics of emotions experienced over minutes. Examining such dynamics may facilitate a better understanding of the brain-behavior associations underlying emotion.

  8. The Neurodynamics of Affect in the Laboratory Predicts Persistence of Real-World Emotional Responses

    PubMed Central

    Fox, Andrew S.; Wing, Erik K.; McQuisition, Kaitlyn M.; Vack, Nathan J.; Davidson, Richard J.

    2015-01-01

    Failure to sustain positive affect over time is a hallmark of depression and other psychopathologies, but the mechanisms supporting the ability to sustain positive emotional responses are poorly understood. Here, we investigated the neural correlates associated with the persistence of positive affect in the real world by conducting two experiments in humans: an fMRI task of reward responses and an experience-sampling task measuring emotional responses to a reward obtained in the field. The magnitude of DLPFC engagement to rewards administered in the laboratory predicted reactivity of real-world positive emotion following a reward administered in the field. Sustained ventral striatum engagement in the laboratory positively predicted the duration of real-world positive emotional responses. These results suggest that common pathways are associated with the unfolding of neural processes over seconds and with the dynamics of emotions experienced over minutes. Examining such dynamics may facilitate a better understanding of the brain-behavior associations underlying emotion. SIGNIFICANCE STATEMENT How real-world emotion, experienced over seconds, minutes, and hours, is instantiated in the brain over the course of milliseconds and seconds is unknown. We combined a novel, real-world experience-sampling task with fMRI to examine how individual differences in real-world emotion, experienced over minutes and hours, is subserved by affective neurodynamics of brain activity over the course of seconds. When winning money in the real world, individuals sustaining positive emotion the longest were those with the most prolonged ventral striatal activity. These results suggest that common pathways are associated with the unfolding of neural processes over seconds and with the dynamics of emotions experienced over minutes. Examining such dynamics may facilitate a better understanding of the brain-behavior associations underlying emotion. PMID:26203145

  9. A Cray T3D performance study

    SciTech Connect

    Nallana, A.; Kincaid, D.R.

    1996-05-01

    We carry out a performance study using the Cray T3D parallel supercomputer to illustrate some important features of this machine. Timing experiments show the speed of various basic operations while more complicated operations give some measure of its parallel performance.

  10. T3DB: the toxic exposome database

    PubMed Central

    Wishart, David; Arndt, David; Pon, Allison; Sajed, Tanvir; Guo, An Chi; Djoumbou, Yannick; Knox, Craig; Wilson, Michael; Liang, Yongjie; Grant, Jason; Liu, Yifeng; Goldansaz, Seyed Ali; Rappaport, Stephen M.

    2015-01-01

    The exposome is defined as the totality of all human environmental exposures from conception to death. It is often regarded as the complement to the genome, with the interaction between the exposome and the genome ultimately determining one's phenotype. The ‘toxic exposome’ is the complete collection of chronically or acutely toxic compounds to which humans can be exposed. Considerable interest in defining the toxic exposome has been spurred on by the realization that most human injuries, deaths and diseases are directly or indirectly caused by toxic substances found in the air, water, food, home or workplace. The Toxin-Toxin-Target Database (T3DB - www.t3db.ca) is a resource that was specifically designed to capture information about the toxic exposome. Originally released in 2010, the first version of T3DB contained data on nearly 2900 common toxic substances along with detailed information on their chemical properties, descriptions, targets, toxic effects, toxicity thresholds, sequences (for both targets and toxins), mechanisms and references. To more closely align itself with the needs of epidemiologists, toxicologists and exposome scientists, the latest release of T3DB has been substantially upgraded to include many more compounds (>3600), targets (>2000) and gene expression datasets (>15 000 genes). It now includes extensive data on ‘normal’ toxic compound concentrations in human biofluids as well as detailed chemical taxonomies, informative chemical ontologies and a large number of referential NMR, MS/MS and GC-MS spectra. This manuscript describes the most recent update to the T3DB, which was previously featured in the 2010 NAR Database Issue. PMID:25378312

  11. Development of VIS/NIR spectroscopic system for real-time prediction of fresh pork quality

    NASA Astrophysics Data System (ADS)

    Zhang, Haiyun; Peng, Yankun; Zhao, Songwei; Sasao, Akira

    2013-05-01

    Quality attributes of fresh meat will influence nutritional value and consumers' purchasing power. The aim of the research was to develop a prototype for real-time detection of quality in meat. It consisted of hardware system and software system. A VIS/NIR spectrograph in the range of 350 to 1100 nm was used to collect the spectral data. In order to acquire more potential information of the sample, optical fiber multiplexer was used. A conveyable and cylindrical device was designed and fabricated to hold optical fibers from multiplexer. High power halogen tungsten lamp was collected as the light source. The spectral data were obtained with the exposure time of 2.17ms from the surface of the sample by press down the trigger switch on the self-developed system. The system could automatically acquire, process, display and save the data. Moreover the quality could be predicted on-line. A total of 55 fresh pork samples were used to develop prediction model for real time detection. The spectral data were pretreated with standard normalized variant (SNV) and partial least squares regression (PLSR) was used to develop prediction model. The correlation coefficient and root mean square error of the validation set for water content and pH were 0.810, 0.653, and 0.803, 0.098 respectively. The research shows that the real-time non-destructive detection system based on VIS/NIR spectroscopy can be efficient to predict the quality of fresh meat.

  12. Impact of meteorological predictions on real-time spring flow forecasting

    NASA Astrophysics Data System (ADS)

    Coulibaly, Paulin

    2003-12-01

    Meteorological predictions, such as precipitation and temperature, are commonly used to improve real-time hydrologic forecasting, despite their inherent uncertainty and their absence in the model calibration stage. In this study, we quantify the effect of meteorological prediction errors on the accuracy of daily spring reservoir inflow forecasts using weather predictions in both the model calibration and testing phases. Different modelling experiments are compared using an operational conceptual model and nonlinear empirical models to assess the effects of using daily numerical weather predictions as opposed to the use of historical observations. It is found that, even with large prediction errors, meteorological forecasts can provide significant improvement of spring flow forecast for up to 7 days lead time, particularly for low flows. Spring flow prediction errors associated with the type of hydrological model used are significantly larger than those related to the meteorological predictions, particularly for 1 to 4 days ahead forecasts. The experimental results also indicate that multiple model-based forecasting using an iterative prediction approach appears to be the most effective method for an adequate use of weather predictions. Copyright

  13. Real time numerical shake prediction incorporating attenuation structure: a case for the 2016 Kumamoto Earthquake

    NASA Astrophysics Data System (ADS)

    Ogiso, M.; Hoshiba, M.; Shito, A.; Matsumoto, S.

    2016-12-01

    Needless to say, heterogeneous attenuation structure is important for ground motion prediction, including earthquake early warning, that is, real time ground motion prediction. Hoshiba and Ogiso (2015, AGU Fall meeting) showed that the heterogeneous attenuation and scattering structure will lead to earlier and more accurate ground motion prediction in the numerical shake prediction scheme proposed by Hoshiba and Aoki (2015, BSSA). Hoshiba and Ogiso (2015) used assumed heterogeneous structure, and we discuss the effect of them in the case of 2016 Kumamoto Earthquake, using heterogeneous structure estimated by actual observation data. We conducted Multiple Lapse Time Window Analysis (Hoshiba, 1993, JGR) to the seismic stations located on western part of Japan to estimate heterogeneous attenuation and scattering structure. The characteristics are similar to the previous work of Carcole and Sato (2010, GJI), e.g. strong intrinsic and scattering attenuation around the volcanoes located on the central part of Kyushu, and relatively weak heterogeneities in the other area. Real time ground motion prediction simulation for the 2016 Kumamoto Earthquake was conducted using the numerical shake prediction scheme with 474 strong ground motion stations. Comparing the snapshot of predicted and observed wavefield showed a tendency for underprediction around the volcanic area in spite of the heterogeneous structure. These facts indicate the necessity of improving the heterogeneous structure for the numerical shake prediction scheme.In this study, we used the waveforms of Hi-net, K-NET, KiK-net stations operated by the NIED for estimating structure and conducting ground motion prediction simulation. Part of this study was supported by the Earthquake Research Institute, the University of Tokyo cooperative research program and JSPS KAKENHI Grant Number 25282114.

  14. Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations.

    PubMed

    Undey, Cenk; Tatara, Eric; Cinar, Ali

    2004-02-19

    Supervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality control. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide an efficient modeling and supervision framework. A new type of MPLS modeling technique that is especially suitable for online real-time process monitoring and the multivariate monitoring charts are presented. This online process monitoring technique is also extended to include predictions of end-of-batch quality measurements during the progress of a batch run. Process monitoring, quality estimation and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also automated through a generic rule-base for efficient alarm handling. The integrated RTKBS and the implementation of MPLS-based process monitoring and quality control are illustrated using a fed-batch penicillin production benchmark process simulator.

  15. Real-Time Eddy-Resolving Ocean Prediction in the Caribbean

    NASA Astrophysics Data System (ADS)

    Hurlburt, H. E.; Smedstad, O. M.; Shriver, J. F.; Townsend, T. L.; Murphy, S. J.

    2001-12-01

    A {1/16}o eddy-resolving, nearly global ocean prediction system has been developed by the Naval Research Laboratory (NRL), Stennis Space Center, MS. It has been run in real-time by the Naval Oceanographic Office (NAVO), Stennis Space Center, MS since 18 Oct 2000 with daily updates for the nowcast and 30-day forecasts performed every Wednesday. The model has ~8 km resolution in the Caribbean region and assimilates real-time altimeter sea surface height (SSH) data from ERS-2, GFO and TOPEX/POSEIDON plus multi-channel sea surface temperature (MCSST) from satellite IR. Real-time and archived results from the system can be seen at web site: http://www7320.nrlssc.navy.mil/global\

  16. The SGI/Cray T3E: Experiences and Insights

    NASA Technical Reports Server (NTRS)

    Bernard, Lisa Hamet

    1998-01-01

    The NASA Goddard Space Flight Center is home to the fifth most powerful supercomputer in the world, a 1024 processor SGI/Cray T3E-600. The original 512 processor system was placed at Goddard in March, 1997 as part of a cooperative agreement between the High Performance Computing and Communications Program's Earth and Space Sciences Project (ESS) and SGI/Cray Research. The goal of this system is to facilitate achievement of the Project milestones of 10, 50 and 100 GFLOPS sustained performance on selected Earth and space science application codes. The additional 512 processors were purchased in March, 1998 by the NASA Earth Science Enterprise for the NASA Seasonal to Interannual Prediction Project (NSIPP). These two "halves" still operate as a single system, and must satisfy the unique requirements of both aforementioned groups, as well as guest researchers from the Earth, space, microgravity, manned space flight and aeronautics communities. Few large scalable parallel systems are configured for capability computing, so models are hard to find. This unique environment has created a challenging system administration task, and has yielded some insights into the supercomputing needs of the various NASA Enterprises, as well as insights into the strengths and weaknesses of the T3E architecture and software. The T3E is a distributed memory system in which the processing elements (PE's) are connected by a low latency, high bandwidth bidirectional 3-D torus. Due to the focus on high speed communication between PE's, the T3E requires PE's to be allocated contiguously per job. Further, jobs will only execute on the user specified number of PE's and PE timesharing is possible but impractical. With a highly varied job mix in both size and runtime of jobs, the resulting scenario is PE fragmentation and an inability to achieve near 100% utilization. SGI/Cray has provided several scheduling and configuration tools to minimize the impact of fragmentation. These tools include PSche

  17. Structural features that predict real-value fluctuations of globular proteins.

    PubMed

    Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

    2012-05-01

    It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

  18. Real-time speech encoding based on Code-Excited Linear Prediction (CELP)

    NASA Technical Reports Server (NTRS)

    Leblanc, Wilfrid P.; Mahmoud, S. A.

    1988-01-01

    This paper reports on the work proceeding with regard to the development of a real-time voice codec for the terrestrial and satellite mobile radio environments. The codec is based on a complexity reduced version of code-excited linear prediction (CELP). The codebook search complexity was reduced to only 0.5 million floating point operations per second (MFLOPS) while maintaining excellent speech quality. Novel methods to quantize the residual and the long and short term model filters are presented.

  19. Evaluation of real-time high-resolution MM5 predictions over the Great Lakes region

    Treesearch

    Shiyuan Zhong; Hee-Jin In; Xindi Bian; Joseph Charney; Warren Heilman; Brian. Potter

    2005-01-01

    Real-time high-resolution mesoscale predictions using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) over the Great Lakes region are evaluated for the 2002/03 winter and 2003 summer seasons using surface and upper-air observations, with a focus on near-surface and boundary layer properties that are important for applications such as air...

  20. Space Weather Prediction Error Bounding for Real-Time Ionospheric Threat Adaptation of GNSS Augmentation Systems

    NASA Astrophysics Data System (ADS)

    Lee, J.; Yoon, M.; Lee, J.

    2014-12-01

    Current Global Navigation Satellite Systems (GNSS) augmentation systems attempt to consider all possible ionospheric events in their correction computations of worst-case errors. This conservatism can be mitigated by subdividing anomalous conditions and using different values of ionospheric threat-model bounds for each class. A new concept of 'real-time ionospheric threat adaptation' that adjusts the threat model in real time instead of always using the same 'worst-case' model was introduced in my previous research. The concept utilizes predicted values of space weather indices for determining the corresponding threat model based on the pre-defined worst-case threat as a function of space weather indices. Since space weather prediction is not reliable due to prediction errors, prediction errors are needed to be bounded to the required level of integrity of the system being supported. The previous research performed prediction error bounding using disturbance, storm time (Dst) index. The distribution of Dst prediction error over the 15-year data was bounded by applying 'inflated-probability density function (pdf) Gaussian bounding'. Since the error distribution has thick and non-Gaussian tails, investigation on statistical distributions which properly describe heavy tails with less conservatism is required for the system performance. This paper suggests two potential approaches for improving space weather prediction error bounding. First, we suggest using different statistical models when fit the error distribution, such as the Laplacian distribution which has fat tails, and the folded Gaussian cumulative distribution function (cdf) distribution. Second approach is to bound the error distribution by segregating data based on the overall level of solar activity. Bounding errors using only solar minimum period data will have less uncertainty and it may allow the use of 'solar cycle prediction' provided by NASA when implementing to real-time threat adaptation. Lastly

  1. Operational Precipitation prediction in Support of Real-Time Flash Flood Prediction and Reservoir Management

    NASA Astrophysics Data System (ADS)

    Georgakakos, K. P.

    2006-05-01

    The presentation will outline the implementation and performance evaluation of a number of national and international projects pertaining to operational precipitation estimation and prediction in the context of hydrologic warning systems and reservoir management support. In all cases, uncertainty measures of the estimates and predictions are an integral part of the precipitation models. Outstanding research issues whose resolution is likely to lead to improvements in the operational environment are presented. The presentation draws from the experience of the Hydrologic Research Center (http://www.hrc-lab.org) prototype implementation projects at the Panama Canal, Central America, Northern California, and South-Central US. References: Carpenter, T.M, and K.P. Georgakakos, "Discretization Scale Dependencies of the Ensemble Flow Range versus Catchment Area Relationship in Distributed Hydrologic Modeling," Journal of Hydrology, 2006, in press. Carpenter, T.M., and K.P. Georgakakos, "Impacts of Parametric and Radar Rainfall Uncertainty on the Ensemble Streamflow Simulations of a Distributed Hydrologic Model," Journal of Hydrology, 298, 202-221, 2004. Georgakakos, K.P., Graham, N.E., Carpenter, T.M., Georgakakos, A.P., and H. Yao, "Integrating Climate- Hydrology Forecasts and Multi-Objective Reservoir Management in Northern California," EOS, 86(12), 122,127, 2005. Georgakakos, K.P., and J.A. Sperfslage, "Operational Rainfall and Flow Forecasting for the Panama Canal Watershed," in The Rio Chagres: A Multidisciplinary Profile of a Tropical Watershed, R.S. Harmon, ed., Kluwer Academic Publishers, The Netherlands, Chapter 16, 323-334, 2005. Georgakakos, K. P., "Analytical results for operational flash flood guidance," Journal of Hydrology, doi:10.1016/j.jhydrol.2005.05.009, 2005.

  2. Real-time emissions from construction equipment compared with model predictions.

    PubMed

    Heidari, Bardia; Marr, Linsey C

    2015-02-01

    The construction industry is a large source of greenhouse gases and other air pollutants. Measuring and monitoring real-time emissions will provide practitioners with information to assess environmental impacts and improve the sustainability of construction. We employed a portable emission measurement system (PEMS) for real-time measurement of carbon dioxide (CO), nitrogen oxides (NOx), hydrocarbon, and carbon monoxide (CO) emissions from construction equipment to derive emission rates (mass of pollutant emitted per unit time) and emission factors (mass of pollutant emitted per unit volume of fuel consumed) under real-world operating conditions. Measurements were compared with emissions predicted by methodologies used in three models: NONROAD2008, OFFROAD2011, and a modal statistical model. Measured emission rates agreed with model predictions for some pieces of equipment but were up to 100 times lower for others. Much of the difference was driven by lower fuel consumption rates than predicted. Emission factors during idling and hauling were significantly different from each other and from those of other moving activities, such as digging and dumping. It appears that operating conditions introduce considerable variability in emission factors. Results of this research will aid researchers and practitioners in improving current emission estimation techniques, frameworks, and databases.

  3. Model-based planning and real-time predictive control for laser-induced thermal therapy.

    PubMed

    Feng, Yusheng; Fuentes, David

    2011-01-01

    In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity.

  4. Model-based planning and real-time predictive control for laser-induced thermal therapy

    PubMed Central

    Feng, Yusheng; Fuentes, David

    2014-01-01

    In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity. PMID:22098360

  5. Real-time zenith tropospheric delays in support of numerical weather prediction applications

    NASA Astrophysics Data System (ADS)

    Dousa, Jan; Vaclavovic, Pavel

    2014-05-01

    The Geodetic Observatory Pecný (GOP) routinely estimates near real-time zenith total delays (ZTD) from GPS permanent stations for assimilation in numerical weather prediction (NWP) models more than 12 years. Besides European regional, global and GPS and GLONASS solutions, we have recently developed real-time estimates aimed at supporting NWP nowcasting or severe weather event monitoring. While all previous solutions are based on data batch processing in a network mode, the real-time solution exploits real-time global orbits and clocks from the International GNSS Service (IGS) and Precise Point Positioning (PPP) processing strategy. New application G-Nut/Tefnut has been developed and real-time ZTDs have been continuously processed in the nine-month demonstration campaign (February-October, 2013) for selected 36 European and global stations. Resulting ZTDs can be characterized by mean standard deviations of 6-10 mm, but still remaining large biases up to 20 mm due to missing precise models in the software. These results fulfilled threshold requirements for the operational NWP nowcasting (i.e. 30 mm in ZTD). Since remaining ZTD biases can be effectively eliminated using the bias-reduction procedure prior to the assimilation, results are approaching the target requirements in terms of relative accuracy (i.e. 6 mm in ZTD). Real-time strategy and software are under the development and we foresee further improvements in reducing biases and in optimizing the accuracy within required timeliness. The real-time products from the International GNSS Service were found accurate and stable for supporting PPP-based tropospheric estimates for the NWP nowcasting.

  6. Mitochondrial T3 receptor and targets.

    PubMed

    Wrutniak-Cabello, Chantal; Casas, François; Cabello, Gérard

    2017-02-03

    The demonstration that TRα1 mRNA encodes a nuclear thyroid hormone receptor and two proteins imported into mitochondria with molecular masses of 43 and 28 kDa has brought new clues to better understand the pleiotropic influence of iodinated hormones. If p28 activity remains unknown, p43 binds to T3 responsive elements occurring in the organelle genome, and, in the T3 presence, stimulates mitochondrial transcription and the subsequent synthesis of mitochondrial encoded proteins. This influence increases mitochondrial activity and through changes in the mitochondrial/nuclear cross talk affects important nuclear target genes regulating cell proliferation and differentiation, oncogenesis, or apoptosis. In addition, this pathway influences muscle metabolic and contractile phenotype, as well as glycaemia regulation. Interestingly, according to the process considered, p43 exerts opposite or cooperative effects with the well-known T3 pathway, thus allowing a fine tuning of the physiological influence of this hormone. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. 3T3 cells in adipocytic conversion.

    PubMed

    O'Shea Alvarez, M S

    1991-01-01

    3T3 are murine cells of an established heteroploid cellular line. Some clones of this cellular line, when cultured under adequate conditions differentiate into adipocytes. During the process of differentiation, the cells undergo a change from the elongated fibroblastic shape to a round or oval form and accumulate small drops of lipids within their cytoplasma. These lipid drops fuse into one large drop which displaces the nucleus towards the periphery, giving the cell the aspect of a mature adipocyte of white adipose tissue. The cells not only change their morphology, but they also present important biochemical changes. They show a simultaneous increase in triglyceride synthesis and activity of lipogenic enzymes. There is also an increase in the response of the activity of various hormones and the de novo synthesis of the receptors to such hormones, as insulin and ACTH. During the process of differentiation important changes occur in the synthesis of various proteins, such as actin, tubulin, and other proteins which also make up the cellular cytoskeleton, forming part of the lipid transportation within the adipose cell. The adipocytic differentiation of 3T3 cells depends on adipogenic serum factors used in the supplementary culture medium. These adipogenic factors seem to play an important role in the development of adipose tissue. There are hormones, chemical agents and serum factors which modulate adipocytic differentiation. The clone must be susceptible to adipocytic differentiation, it must reach a quiescent state and find itself in adipogenic conditions for the 3T3 cells to differentiate into adipocytes. It must also carry out an DNA synthesis which is an expression of the new phenotype. The differentiation of 3T3 cells in terminal. The fact that these cells present an adipocytic conversion under physiologic conditions and with adipogenic hormones which exist in the whole animal has been demonstrated. All of these characteristics show that the 3T3 cells may be

  8. MO-G-18C-05: Real-Time Prediction in Free-Breathing Perfusion MRI

    SciTech Connect

    Song, H; Liu, W; Ruan, D; Jung, S; Gach, M

    2014-06-15

    Purpose: The aim is to minimize frame-wise difference errors caused by respiratory motion and eliminate the need for breath-holds in magnetic resonance imaging (MRI) sequences with long acquisitions and repeat times (TRs). The technique is being applied to perfusion MRI using arterial spin labeling (ASL). Methods: Respiratory motion prediction (RMP) using navigator echoes was implemented in ASL. A least-square method was used to extract the respiratory motion information from the 1D navigator. A generalized artificial neutral network (ANN) with three layers was developed to simultaneously predict 10 time points forward in time and correct for respiratory motion during MRI acquisition. During the training phase, the parameters of the ANN were optimized to minimize the aggregated prediction error based on acquired navigator data. During realtime prediction, the trained ANN was applied to the most recent estimated displacement trajectory to determine in real-time the amount of spatial Results: The respiratory motion information extracted from the least-square method can accurately represent the navigator profiles, with a normalized chi-square value of 0.037±0.015 across the training phase. During the 60-second training phase, the ANN successfully learned the respiratory motion pattern from the navigator training data. During real-time prediction, the ANN received displacement estimates and predicted the motion in the continuum of a 1.0 s prediction window. The ANN prediction was able to provide corrections for different respiratory states (i.e., inhalation/exhalation) during real-time scanning with a mean absolute error of < 1.8 mm. Conclusion: A new technique enabling free-breathing acquisition during MRI is being developed. A generalized ANN development has demonstrated its efficacy in predicting a continuum of motion profile for volumetric imaging based on navigator inputs. Future work will enhance the robustness of ANN and verify its effectiveness with human

  9. A framework for predicting three-dimensional prostate deformation in real time.

    PubMed

    Jahya, Alex; Herink, Mark; Misra, Sarthak

    2013-12-01

    Surgical simulation systems can be used to estimate soft tissue deformation during pre- and intra-operative planning. Such systems require a model that can accurately predict the deformation in real time. In this study, we present a back-propagation neural network for predicting three-dimensional (3D) deformation of a phantom that incorporates the anatomy of the male pelvic region, i.e. the prostate and surrounding structures that support it. In the experiments and simulations, a needle guide is used to deform the rectal wall. The neural network predicts the deformation based on the relation between the undeformed and deformed shapes of the phantom. Training data are generated using a validated finite element (FE) model of the prostate and its surrounding structures. The FE model is developed from anatomically accurate magnetic resonance (MR) images. An ultrasound-based acoustic radiation force impulse imaging technique is used to measure in situ the shear wave velocity in soft tissue. The velocity is utilized to calculate the elasticities of the phantom. In the simulation study, the displacement and angle of the needle guide are varied. The neural network then predicts 3D phantom deformation for a given input displacement. The results of the simulation study show that the maximum absolute linear and angular errors of the nodal displacement and orientation between neural network and FE predicted deformation are 0.03 mm and 0.01°, respectively. This study shows that a back-propagation neural network can be used to predict prostate deformation. Further, it is also demonstrated that a combination of ultrasound data, MR images and a neural network can be used as a framework for accurately predicting 3D prostate deformation in real time. Copyright © 2013 John Wiley & Sons, Ltd.

  10. GPS Satellite Orbit Prediction at User End for Real-Time PPP System.

    PubMed

    Yang, Hongzhou; Gao, Yang

    2017-08-30

    This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth's gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge-Kutta and multi-step Adams-Bashforth-Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively.

  11. GPS Satellite Orbit Prediction at User End for Real-Time PPP System

    PubMed Central

    Yang, Hongzhou; Gao, Yang

    2017-01-01

    This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth’s gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge–Kutta and multi-step Adams–Bashforth–Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively. PMID:28867771

  12. Real-time seismic intensity prediction using frequency-dependent site amplification factors

    NASA Astrophysics Data System (ADS)

    Ogiso, Masashi; Aoki, Shigeki; Hoshiba, Mitsuyuki

    2016-05-01

    A promising approach for the next generation of earthquake early warning system is based on predicting ground motion directly from observed ground motion, without any information of hypocenter. In this study, we predicted seismic intensity at the target stations from the observed ground motion at adjacent stations, employing two different methods of correction for site amplification factors. The first method was frequency-dependent correction prediction, in which we used a digital causal filter to correct the site amplification for the observed waveform in the time domain. The second method was scalar correction, in which we used average differences in seismic intensity between two stations for the site amplification correction. Results from thousands of station pairs that covered almost all of Japan showed that seismic intensity prediction with frequency-dependent correction prediction was more accurate than prediction with scalar correction. Frequency-dependent correction for site amplification in the time domain may lead to more accurate prediction of ground motion in real time.

  13. A real-time predictive simulation of abdominal viscera positions during quiet free breathing.

    PubMed

    Hostettler, A; Nicolau, S A; Rémond, Y; Marescaux, J; Soler, L

    2010-12-01

    Prediction of abdominal viscera and tumour positions during free breathing is a major challenge from which several medical applications could benefit. For instance, in radiotherapy it would reduce the healthy tissue irradiation. In this paper, we present a new approach to predict real-time abdominal viscera positions during free breathing. Our method needs an abdo-thoracic 3D preoperative CT or MR image, a second one limited to the diaphragmatic area, and a tracking of the patient's skin position. First, a physical analysis of the breathing motion shows it is possible to predict accurately abdominal viscera positions from the skin position and a modelling of the diaphragm motion. Secondly, a quantitative analysis of the skin and organ motion allows us to define the demands our real-time simulation has to fulfill. Then, we present in detail all the necessary steps of our original method to compute a deformation field from data extracted in both 3D preoperative image and skin surface tracking. Finally, experiments carried out with two human data show that our simulation model predicts abdominal viscera positions, such as liver, kidneys or spleen, at 50 Hz with an accuracy within 2-3 mm.

  14. Data-adaptive Harmonic Decomposition and Real-time Prediction of Arctic Sea Ice Extent

    NASA Astrophysics Data System (ADS)

    Kondrashov, Dmitri; Chekroun, Mickael; Ghil, Michael

    2017-04-01

    Decline in the Arctic sea ice extent (SIE) has profound socio-economic implications and is a focus of active scientific research. Of particular interest is prediction of SIE on subseasonal time scales, i.e. from early summer into fall, when sea ice coverage in Arctic reaches its minimum. However, subseasonal forecasting of SIE is very challenging due to the high variability of ocean and atmosphere over Arctic in summer, as well as shortness of observational data and inadequacies of the physics-based models to simulate sea-ice dynamics. The Sea Ice Outlook (SIO) by Sea Ice Prediction Network (SIPN, http://www.arcus.org/sipn) is a collaborative effort to facilitate and improve subseasonal prediction of September SIE by physics-based and data-driven statistical models. Data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) techniques [Chekroun and Kondrashov, 2017], have been successfully applied to the nonlinear stochastic modeling, as well as retrospective and real-time forecasting of Multisensor Analyzed Sea Ice Extent (MASIE) dataset in key four Arctic regions. In particular, DAH-MSLM predictions outperformed most statistical models and physics-based models in real-time 2016 SIO submissions. The key success factors are associated with DAH ability to disentangle complex regional dynamics of MASIE by data-adaptive harmonic spatio-temporal patterns that reduce the data-driven modeling effort to elemental MSLMs stacked per frequency with fixed and small number of model coefficients to estimate.

  15. Experience-based Auditory Predictions Modulate Brain Activity to Silence as do Real Sounds.

    PubMed

    Chouiter, Leila; Tzovara, Athina; Dieguez, Sebastian; Annoni, Jean-Marie; Magezi, David; De Lucia, Marzia; Spierer, Lucas

    2015-10-01

    Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accounts of filling-in phenomenon. We investigated the neurophysiological effects of internal models by testing whether single-trial electrophysiological responses to omitted sounds in a rule-based sequence of tones with varying pitch could be decoded from the responses to real sounds and by analyzing the ERPs to the omissions with data-driven electrical neuroimaging methods. The decoding of the brain responses to different expected, but omitted, tones in both passive and active listening conditions was above chance based on the responses to the real sound in active listening conditions. Topographic ERP analyses and electrical source estimations revealed that, in the absence of any stimulation, experience-based internal models elicit an electrophysiological activity different from noise and that the temporal dynamics of this activity depend on attention. We further found that the expected change in pitch direction of omitted tones modulated the activity of left posterior temporal areas 140-200 msec after the onset of omissions. Collectively, our results indicate that, even in the absence of any stimulation, internal models modulate brain activity as do real sounds, indicating that auditory filling in can be accounted for by predictive activity.

  16. Predictive factors of functional capacity and real-world functioning in patients with schizophrenia.

    PubMed

    Menendez-Miranda, I; Garcia-Portilla, M P; Garcia-Alvarez, L; Arrojo, M; Sanchez, P; Sarramea, F; Gomar, J; Bobes-Bascaran, M T; Sierra, P; Saiz, P A; Bobes, J

    2015-07-01

    This study was performed to identify the predictive factors of functional capacity assessed by the Spanish University of California Performance Skills Assessment (Sp-UPSA) and real-world functioning assessed by the Spanish Personal and Social Performance scale (PSP) in outpatients with schizophrenia. Naturalistic, 6-month follow-up, multicentre, validation study. Here, we report data on 139 patients with schizophrenia at their baseline visit. Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression-Severity (CGI-S), Sp-UPSA and PSP. Pearson's correlation coefficient (r) was used to determine the relationships between variables, and multivariable stepwise linear regression analyses to identify predictive variables of Sp-UPSA and PSP total scores. Functional capacity: scores on the PSP and PANSS-GP entered first and second at P<0.0001 and accounted for 21% of variance (R(2)=0.208, model df=2, F=15.724, P<0.0001). Real-world functioning: scores on the CGI-S (B=-5.406), PANSS-N (B=-0.657) and Sp-UPSA (B=0.230) entered first, second and third, and accounted for 51% of variance (model df=3, F=37.741, P<0.0001). In patients with schizophrenia, functional capacity and real-world functioning are two related but different constructs. Each one predicts the other along with other factors; general psychopathology for functional capacity, and severity of the illness and negative symptoms for real-world functioning. These findings have important clinical implications: (1) both types of functioning should be assessed in patients with schizophrenia and (2) strategies for improving them should be different. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  17. Operational, Real-Time, Sun-to-Earth Interplanetary Shock Predictions During Solar Cycle 23

    NASA Astrophysics Data System (ADS)

    Fry, C. D.; Dryer, M.; Sun, W.; Deehr, C. S.; Smith, Z.; Akasofu, S.

    2002-05-01

    We report on our progress in predicting interplanetary shock arrival time (SAT) in real-time, using three forecast models: the Hakamada-Akasofu-Fry (HAF) modified kinematic model, the Interplanetary Shock Propagation Model (ISPM) and the Shock Time of Arrival (STOA) model. These models are run concurrently to provide real-time predictions of the arrival time at Earth of interplanetary shocks caused by solar events. These "fearless forecasts" are the first, and presently only, publicly distributed predictions of SAT and are undergoing quantitative evaluation for operational utility and scientific benchmarking. All three models predict SAT, but the HAF model also provides a global view of the propagation of interplanetary shocks through the pre-existing, non-uniform heliospheric structure. This allows the forecaster to track the propagation of the shock and to differentiate between shocks caused by solar events and those associated with co-rotating interaction regions (CIRs). This study includes 173 events during the period February, 1997 to October, 2000. Shock predictions were compared with spacecraft observations at the L1 location to determine how well the models perform. Sixty-eight shocks were observed at L1 within 120 hours of an event. We concluded that 6 of these observed shocks were caused by CIRs, and the remainder were caused by solar events. The forecast skill of the models are presented in terms of RMS errors, contingency tables and skill scores commonly used by the weather forecasting community. The false alarm rate for HAF was higher than for ISPM or STOA but much lower than for predictions based upon empirical studies or climatology. Of the parameters used to characterize a shock source at the Sun, the initial speed of the coronal shock, as represented by the observed metric type II speed, has the largest influence on the predicted SAT. We also found that HAF model predictions based upon type II speed are generally better for shocks originating from

  18. Real-time model predictive control using a self-organizing neural network.

    PubMed

    Han, Hong-Gui; Wu, Xiao-Long; Qiao, Jun-Fei

    2013-09-01

    In this paper, a real-time model predictive control (RT-MPC) based on self-organizing radial basis function neural network (SORBFNN) is proposed for nonlinear systems. This RT-MPC has its simplicity in parallelism to model predictive control design and efficiency to deal with computational complexity. First, a SORBFNN with concurrent structure and parameter learning is developed as the predictive model of the nonlinear systems. The model performance can be significantly improved through SORBFNN, and the modeling error is uniformly ultimately bounded. Second, a fast gradient method (GM) is enhanced for the solution of optimal control problem. This proposed GM can reduce computational cost and suboptimize the RT-MPC online. Then, the conditions of the stability analysis and steady-state performance of the closed-loop systems are presented. Finally, numerical simulations reveal that the proposed control gives satisfactory tracking and disturbance rejection performances. Experimental results demonstrate its effectiveness.

  19. On the feasibility of real-time prediction of aircraft carrier motion at sea

    NASA Technical Reports Server (NTRS)

    Sidar, M. M.; Doolin, B. F.

    1983-01-01

    Landing aircraft on board carriers is a most delicate phase of flight operations at sea. The ability to predict the aircraft carrier's motion over an interval of several seconds within reasonable error bounds may allow an improvement in touchdown dispersion and reduce the value of the ramp clearance due to a smoother aircraft trajectory. Also, improved information to the landing signal officer should decrease the number of waveoffs substantially. This paper indicates and shows quantitatively that, based upon the power density spectrum data for pitch and heave measured for various ships and sea conditions, the motion can be predicted well, for up to 15 s. Moreover, the zero crossover times for both pitch and heave motions can be predicted with impressive accuracy. The predictor was designed on the basis of Kalman's optimum filtering theory (the discrete time case), being compatible with real-time digital computer operation.

  20. On the feasibility of real-time prediction of aircraft carrier motion at sea

    NASA Technical Reports Server (NTRS)

    Sidar, M.; Doolin, B. F.

    1975-01-01

    The ability to predict the aircraft carrier's motion over an interval of several seconds within reasonable error bounds may allow an improvement in touchdown dispersion and a more certain value for ramp clearance due to a smoother aircraft trajectory. Also, improved information to the landing signal officer should decrease the number of waveoffs substantially. It is quantitatively shown that, based on the power density spectrum data for pitch and heave measured for various ships and sea conditions, the motion can be predicted well for up to 15 seconds. The zero crossover times for both pitch and heave motions can be predicted with impressive accuracy. The predictor was designed on the basis of Kalman's optimum filtering theory for the discrete time case, adapted for real-time digital computer operation.

  1. Free T4, Free T3, and Reverse T3 in Critically Ill, Thermally Injured Patients

    DTIC Science & Technology

    1980-09-01

    in peripheral thyroid hormone concentrations, a second group of 20 patients was studied. We r.,C’ measured the free serum levels ofT4 (FT4) and T3...of rTi are markedly elevated. These alterations in pe- ripheral thyroid hormonal concentrations are similar to previous observations in patients with...in initiating the hormonal alterations observed. nervous system (17). T3, like its precursors, phenylala- The changes in peripheral thyroid hormone

  2. Predicting Schizophrenia Patients’ Real World Behavior with Specific Neuropsychological and Functional Capacity Measures

    PubMed Central

    Bowie, Christopher R.; Leung, Winnie W.; Reichenberg, Abraham; McClure, Margaret M.; Patterson, Thomas L.; Heaton, Robert K.; Harvey, Philip D.

    2008-01-01

    Background Significant neuropsychological (NP) and functional deficits are found in most schizophrenia patients. Previous studies have left question as to whether global NP impairment or discrete domains affect functional outcomes, and none have addressed distinctions within and between ability and performance domains. This study examined the different predictive relationships between NP domains, functional competence, social competence, symptoms, and real world behavior in domains of work skills, interpersonal relationships, and community activities. Methods 222 schizophrenic outpatients were tested with an NP battery and performance-based measures of functional and social competence and rated for positive, negative, and depressive symptoms. Case managers generated ratings of three functional disability domains. Results Four cognitive factors were derived from factor analysis. Path analyses revealed both direct and mediated effects of NP on real world outcomes. All NP domains predicted functional competence, but only processing speed and attention/working memory predicted social competence. Both competence measures mediated the effects of NP on community activities and work skills, but only social competence predicted interpersonal behaviors. The attention/working memory domain was directly related to work skills, executive functions had a direct effect on interpersonal behaviors and processing speed had direct effects on all three real world behaviors. Symptoms were directly related to outcomes, with fewer relationships with competence. Conclusions Differential predictors of functional competence and performance were found from discrete NP domains. Separating competence and performance provides a more precise perspective on correlates of disability. Changes in specific NP or functional skills might improve specific outcomes, rather than promoting global functional improvement. PMID:17662256

  3. Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables.

    PubMed

    Walton, Nephi A; Poynton, Mollie R; Gesteland, Per H; Maloney, Chris; Staes, Catherine; Facelli, Julio C

    2010-11-02

    Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks. Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008. NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley. We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years.

  4. Real-time sample entropy predicts life-saving interventions after the Boston Marathon bombing.

    PubMed

    Peev, Miroslav P; Naraghi, Leily; Chang, Yuchiao; Demoya, Marc; Fagenholz, Peter; Yeh, Daniel; Velmahos, George; King, David R

    2013-12-01

    Identifying patients in need of a life-saving intervention (LSI) during a mass casualty event is a priority. We hypothesized that real-time, instantaneous sample entropy (SampEn) could predict the need for LSI in the Boston Marathon bombing victims. Severely injured Boston Marathon bombing victims (n = 10) had sample entropy (SampEn) recorded upon presentation using a continuous 200-beat rolling average in real time. Treating clinicians were blinded to real-time results. The correlation between SampEn, injury severity, number, and type of LSI was examined. Victims were males (60%) with a mean age of 39.1 years. Injuries involved lower extremities (50.0%), head and neck (24.2%), or upper extremities (9.7%). Sample entropy negatively correlated with Injury Severity Score (r = -0.70; P = .023), number of injuries (r = -0.70; P = .026), and the number and need for LSI (r = -0.82; P = .004). Sample entropy was reduced under a variety of conditions. (Table see text). Sample entropy strongly correlates with injury severity and predicts LSI after blast injuries sustained in the Boston Marathon bombings. Sample entropy may be a useful triage tool after blast injury. © 2013.

  5. Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

    NASA Technical Reports Server (NTRS)

    Martin, Rodney Alexander; Das, Santanu

    2010-01-01

    The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction.

  6. Jump neural network for real-time prediction of glucose concentration.

    PubMed

    Zecchin, Chiara; Facchinetti, Andrea; Sparacino, Giovanni; Cobelli, Claudio

    2015-01-01

    Prediction of the future value of a variable is of central importance in a wide variety of fields, including economy and finance, meteorology, informatics, and, last but not least important, medicine. For example, in the therapy of Type 1 Diabetes (T1D), in which, for patient safety, glucose concentration in the blood should be maintained in a defined normoglycemic range, the ability to forecast glucose concentration in the short-term (with a prediction horizon of around 30 min) might be sufficient to reduce the incidence of hypoglycemic and hyperglycemic events. Neural Network (NN) approaches are suitable for prediction purposes because of their ability to model nonlinear dynamics and handle in their inputs signals coming from different domains. In this chapter we illustrate the design of a jump NN glucose prediction algorithm that exploits past glucose concentration data, measured in real-time by a minimally invasive continuous glucose monitoring (CGM) sensor, and information on ingested carbohydrates, supplied by the patient himself or herself. The methodology is assessed by tuning the NN on data of ten T1D individuals and then testing it on a dataset of ten different subjects. Results with a prediction horizon of 30 min show that prediction of glucose concentration in T1D via NN is feasible and sufficiently accurate. The average time anticipation obtained is compatible with the generation of preventive hypoglycemic and hyperglycemic alerts and the improvement of artificial pancreas performance.

  7. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates

    NASA Astrophysics Data System (ADS)

    Wessberg, Johan; Stambaugh, Christopher R.; Kralik, Jerald D.; Beck, Pamela D.; Laubach, Mark; Chapin, John K.; Kim, Jung; Biggs, S. James; Srinivasan, Mandayam A.; Nicolelis, Miguel A. L.

    2000-11-01

    Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.

  8. Fit to predict? Ecoinformatics for predicting the catchability of a pelagic fish in near real-time.

    PubMed

    Scales, Kylie L; Hazen, Elliott L; Maxwell, Sara M; Dewar, Heidi; Kohin, Suzanne; Jacox, Michael G; Edwards, Christopher A; Briscoe, Dana K; Crowder, Larry B; Lewison, Rebecca L; Bograd, Steven J

    2017-08-21

    The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing ecoinformatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 years (1990-2014) of NOAA fisheries' observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch) of broadbill swordfish Xiphias gladius in the California Current System (CCS). Using freely-available environmental datasets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely-sensed datasets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (>1500m) with surface temperatures in the 14-20°C range, isothermal layer depth (ILD) of 20-40m, positive sea surface height anomalies and during the new moon (<20% lunar illumination). We observed a greater influence of mesoscale variability (sea surface height, wind speed, isothermal layer depth, Eddy Kinetic Energy) in driving swordfish catchability (total catch) than was evident in predicting the relative probability of presence (presence-absence), confirming the utility of generating spatio-temporally dynamic predictions. Data-assimilative ROMS circumvent the limitations of satellite remote sensing in providing physical data fields for species

  9. LMO4 modulates proliferation and differentiation of 3T3-L1 preadipocytes.

    PubMed

    Wang, Ning; Wang, Xichen; Shi, Mingxin; Shi, Hongyan; Yan, Xiaohong; Li, Hui; Wang, Shouzhi; Wang, Yuxiang

    2013-09-17

    Previous microarray analyses revealed that LMO4 is expressed in 3T3-L1 preadipocytes, however, its roles in adipogenesis are unknown. In the present study, using RT-PCR sequencing and quantitative real-time RT-PCR, we confirmed that LMO4 gene is expressed in 3T3-L1 preadipocytes and its expression peaks at the early stage of 3T3-L1 preadipocyte differentiation. Further analyses showed that LMO4 knockdown decreased the proliferation of 3T3-L1 preadipocytes, and attenuated the differentiation of 3T3-L1 preadipocytes, as evidenced by reduced lipid accumulation and down-regulation of PPARγ gene expression. Collectively, our findings indicate that LMO4 is a novel modulator of adipogenesis. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  10. Real-time object tracking with correlation filtering and state prediction

    NASA Astrophysics Data System (ADS)

    Contreras, Viridiana; Díaz-Ramírez, Victor H.; Kober, Vitaly; Tapia-Armenta, Juan J.

    2013-09-01

    A real-time tracking system based on adaptive correlation filtering and state prediction is proposed. The system is able to estimate at high-rate the position of multiple targets within the observed scene by taking into account information of past and present scene-frames. The position of the targets in the current frame is estimated with the help of a bank of composite correlation filters applied to several small regions taken from the observed scene. These small regions are updated in each frame according to information from a state predictor based on the motion model of targets in a twodimensional plane. The proposed system is implemented on a graphics processing unit to take advantage of massive parallelism. Computer simulation results obtained with the proposed system are presented and discussed in terms of tracking accuracy and real-time operation efficiency.

  11. Differences between real and predicted corneal shapes after aspherical corneal ablation

    NASA Astrophysics Data System (ADS)

    Anera, Rosario G.; Villa, César; Jiménez, José R.; Gutiérrez, Ramón; Jiménez del Barco, Luis

    2005-07-01

    We study the differences between real and expected corneal shapes, using an aspherical ablation algorithm with a known equation and avoiding the limitation imposed by most studies of refractive surgery in which the ablation equations are not known. We have calculated the theoretical corneal shape predicted by this algorithm, comparing this shape with the real corneal topography. The results indicate that the deviations that appear in the corneal shape are significant for visual performance and for the correction of eye aberrations. If we include in this analysis the effect of reflection losses and nonnormal incidence on the cornea, we can reduce corneal differences, but they will remain significant. These results confirm that it is essential to minimize corneal differences to achieve effective correction in refractive surgery.

  12. Pole-placement Predictive Functional Control for under-damped systems with real numbers algebra.

    PubMed

    Zabet, K; Rossiter, J A; Haber, R; Abdullah, M

    2017-08-31

    This paper presents the new algorithm of PP-PFC (Pole-placement Predictive Functional Control) for stable, linear under-damped higher-order processes. It is shown that while conventional PFC aims to get first-order exponential behavior, this is not always straightforward with significant under-damped modes and hence a pole-placement PFC algorithm is proposed which can be tuned more precisely to achieve the desired dynamics, but exploits complex number algebra and linear combinations in order to deliver guarantees of stability and performance. Nevertheless, practical implementation is easier by avoiding complex number algebra and hence a modified formulation of the PP-PFC algorithm is also presented which utilises just real numbers while retaining the key attributes of simple algebra, coding and tuning. The potential advantages are demonstrated with numerical examples and real-time control of a laboratory plant. Copyright © 2017 ISA. All rights reserved.

  13. A multiple model approach to respiratory motion prediction for real-time IGRT.

    PubMed

    Putra, Devi; Haas, Olivier C L; Mills, John A; Burnham, Keith J

    2008-03-21

    Respiration induces significant movement of tumours in the vicinity of thoracic and abdominal structures. Real-time image-guided radiotherapy (IGRT) aims to adapt radiation delivery to tumour motion during irradiation. One of the main problems for achieving this objective is the presence of time lag between the acquisition of tumour position and the radiation delivery. Such time lag causes significant beam positioning errors and affects the dose coverage. A method to solve this problem is to employ an algorithm that is able to predict future tumour positions from available tumour position measurements. This paper presents a multiple model approach to respiratory-induced tumour motion prediction using the interacting multiple model (IMM) filter. A combination of two models, constant velocity (CV) and constant acceleration (CA), is used to capture respiratory-induced tumour motion. A Kalman filter is designed for each of the local models and the IMM filter is applied to combine the predictions of these Kalman filters for obtaining the predicted tumour position. The IMM filter, likewise the Kalman filter, is a recursive algorithm that is suitable for real-time applications. In addition, this paper proposes a confidence interval (CI) criterion to evaluate the performance of tumour motion prediction algorithms for IGRT. The proposed CI criterion provides a relevant measure for the prediction performance in terms of clinical applications and can be used to specify the margin to accommodate prediction errors. The prediction performance of the IMM filter has been evaluated using 110 traces of 4-minute free-breathing motion collected from 24 lung-cancer patients. The simulation study was carried out for prediction time 0.1-0.6 s with sampling rates 3, 5 and 10 Hz. It was found that the prediction of the IMM filter was consistently better than the prediction of the Kalman filter with the CV or CA model. There was no significant difference of prediction errors for the

  14. Study on Development of 1D-2D Coupled Real-time Urban Inundation Prediction model

    NASA Astrophysics Data System (ADS)

    Lee, Seungsoo

    2017-04-01

    In recent years, we are suffering abnormal weather condition due to climate change around the world. Therefore, countermeasures for flood defense are urgent task. In this research, study on development of 1D-2D coupled real-time urban inundation prediction model using predicted precipitation data based on remote sensing technology is conducted. 1 dimensional (1D) sewerage system analysis model which was introduced by Lee et al. (2015) is used to simulate inlet and overflow phenomena by interacting with surface flown as well as flows in conduits. 2 dimensional (2D) grid mesh refinement method is applied to depict road networks for effective calculation time. 2D surface model is coupled with 1D sewerage analysis model in order to consider bi-directional flow between both. Also parallel computing method, OpenMP, is applied to reduce calculation time. The model is estimated by applying to 25 August 2014 extreme rainfall event which caused severe inundation damages in Busan, Korea. Oncheoncheon basin is selected for study basin and observed radar data are assumed as predicted rainfall data. The model shows acceptable calculation speed with accuracy. Therefore it is expected that the model can be used for real-time urban inundation forecasting system to minimize damages.

  15. Real-time prediction of cell division timing in developing zebrafish embryo.

    PubMed

    Kozawa, Satoshi; Akanuma, Takashi; Sato, Tetsuo; Sato, Yasuomi D; Ikeda, Kazushi; Sato, Thomas N

    2016-09-06

    Combination of live-imaging and live-manipulation of developing embryos in vivo provides a useful tool to study developmental processes. Identification and selection of target cells for an in vivo live-manipulation are generally performed by experience- and knowledge-based decision-making of the observer. Computer-assisted live-prediction method would be an additional approach to facilitate the identification and selection of the appropriate target cells. Herein we report such a method using developing zebrafish embryos. We choose V2 neural progenitor cells in developing zebrafish embryo as their successive shape changes can be visualized in real-time in vivo. We developed a relatively simple mathematical method of describing cellular geometry of V2 cells to predict cell division-timing based on their successively changing shapes in vivo. Using quantitatively measured 4D live-imaging data, features of V2 cell-shape at each time point prior to division were extracted and a statistical model capturing the successive changes of the V2 cell-shape was developed. By applying sequential Bayesian inference method to the model, we successfully predicted division-timing of randomly selected individual V2 cells while the cell behavior was being live-imaged. This system could assist pre-selecting target cells desirable for real-time manipulation-thus, presenting a new opportunity for in vivo experimental systems.

  16. Real-time prediction of cell division timing in developing zebrafish embryo

    NASA Astrophysics Data System (ADS)

    Kozawa, Satoshi; Akanuma, Takashi; Sato, Tetsuo; Sato, Yasuomi D.; Ikeda, Kazushi; Sato, Thomas N.

    2016-09-01

    Combination of live-imaging and live-manipulation of developing embryos in vivo provides a useful tool to study developmental processes. Identification and selection of target cells for an in vivo live-manipulation are generally performed by experience- and knowledge-based decision-making of the observer. Computer-assisted live-prediction method would be an additional approach to facilitate the identification and selection of the appropriate target cells. Herein we report such a method using developing zebrafish embryos. We choose V2 neural progenitor cells in developing zebrafish embryo as their successive shape changes can be visualized in real-time in vivo. We developed a relatively simple mathematical method of describing cellular geometry of V2 cells to predict cell division-timing based on their successively changing shapes in vivo. Using quantitatively measured 4D live-imaging data, features of V2 cell-shape at each time point prior to division were extracted and a statistical model capturing the successive changes of the V2 cell-shape was developed. By applying sequential Bayesian inference method to the model, we successfully predicted division-timing of randomly selected individual V2 cells while the cell behavior was being live-imaged. This system could assist pre-selecting target cells desirable for real-time manipulation–thus, presenting a new opportunity for in vivo experimental systems.

  17. Fast template matching based on grey prediction for real-time object tracking

    NASA Astrophysics Data System (ADS)

    Lv, Mingming; Hou, Yuanlong; Liu, Rongzhong; Hou, Runmin

    2017-02-01

    Template matching is a basic algorithm for image processing, and real-time is a crucial requirement of object tracking. For real-time tracking, a fast template matching algorithm based on grey prediction is presented, where computation cost can be reduced dramatically by minimizing search range. First, location of the tracked object in the current image is estimated by Grey Model (GM). GM(1,1), which is the basic model of grey prediction, can use some known information to foretell the location. Second, the precise position of the object in the frame is computed by template matching. Herein, Sequential Similarity Detection Algorithm (SSDA) with a self-adaptive threshold is employed to obtain the matching position in the neighborhood of the predicted location. The role of threshold in SSDA is important, as a proper threshold can make template matching fast and accurate. Moreover, a practical weighted strategy is utilized to handle scale and rotation changes of the object, as well as illumination changes. The experimental results show the superior performance of the proposed algorithm over the conventional full-search method, especially in terms of executive time.

  18. A relaxed fusion of information from real and synthetic images to predict complex behavior

    NASA Astrophysics Data System (ADS)

    Lyons, Damian M.; Benjamin, D. Paul

    2011-05-01

    An important component of cognitive robotics is the ability to mentally simulate physical processes and to compare the expected results with the information reported by a robot's sensors. In previous work, we have proposed an approach that integrates a 3D game-engine simulation into the robot control architecture. A key part of that architecture is the Match-Mediated Difference (MMD) operation, an approach to fusing sensory data and synthetic predictions at the image level. The MMD operation insists that simulated and predicted scenes are similar in terms of the appearance of the objects in the scene. This is an overly restrictive constraint on the simulation since parts of the predicted scene may not have been previously viewed by the robot. In this paper we propose an extended MMD operation that relaxes the constraint and allows the real and synthetic scenes to differ in some features but not in (selected) other features. Image difference operations that allow a real image and synthetic image generated from an arbitrarily colored graphical model of a scene to be compared. Scenes with the same content show a zero difference. Scenes with varying foreground objects can be controlled to compare the color, size and shape of the foreground.

  19. Real-time prediction of cell division timing in developing zebrafish embryo

    PubMed Central

    Kozawa, Satoshi; Akanuma, Takashi; Sato, Tetsuo; Sato, Yasuomi D.; Ikeda, Kazushi; Sato, Thomas N.

    2016-01-01

    Combination of live-imaging and live-manipulation of developing embryos in vivo provides a useful tool to study developmental processes. Identification and selection of target cells for an in vivo live-manipulation are generally performed by experience- and knowledge-based decision-making of the observer. Computer-assisted live-prediction method would be an additional approach to facilitate the identification and selection of the appropriate target cells. Herein we report such a method using developing zebrafish embryos. We choose V2 neural progenitor cells in developing zebrafish embryo as their successive shape changes can be visualized in real-time in vivo. We developed a relatively simple mathematical method of describing cellular geometry of V2 cells to predict cell division-timing based on their successively changing shapes in vivo. Using quantitatively measured 4D live-imaging data, features of V2 cell-shape at each time point prior to division were extracted and a statistical model capturing the successive changes of the V2 cell-shape was developed. By applying sequential Bayesian inference method to the model, we successfully predicted division-timing of randomly selected individual V2 cells while the cell behavior was being live-imaged. This system could assist pre-selecting target cells desirable for real-time manipulation–thus, presenting a new opportunity for in vivo experimental systems. PMID:27597656

  20. PLIO: a generic tool for real-time operational predictive optimal control of water networks.

    PubMed

    Cembrano, G; Quevedo, J; Puig, V; Pérez, R; Figueras, J; Verdejo, J M; Escaler, I; Ramón, G; Barnet, G; Rodríguez, P; Casas, M

    2011-01-01

    This paper presents a generic tool, named PLIO, that allows to implement the real-time operational control of water networks. Control strategies are generated using predictive optimal control techniques. This tool allows the flow management in a large water supply and distribution system including reservoirs, open-flow channels for water transport, water treatment plants, pressurized water pipe networks, tanks, flow/pressure control elements and a telemetry/telecontrol system. Predictive optimal control is used to generate flow control strategies from the sources to the consumer areas to meet future demands with appropriate pressure levels, optimizing operational goals such as network safety volumes and flow control stability. PLIO allows to build the network model graphically and then to automatically generate the model equations used by the predictive optimal controller. Additionally, PLIO can work off-line (in simulation) and on-line (in real-time mode). The case study of Santiago-Chile is presented to exemplify the control results obtained using PLIO off-line (in simulation).

  1. High-resolution summer rainfall prediction in the JHWC real-time WRF system

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Kyou; Eom, Dae-Yong; Kim, Joo-Wan; Lee, Jae-Bok

    2010-08-01

    The WRF-based real-time forecast system (http://jhwc.snu.ac.kr/weather) of the Joint Center for High-impact Weather and Climate Research (JHWC) has been in operation since November 2006; this system has three nested model domains using GFS (Global Forecast System) data for its initial and boundary conditions. In this study, we evaluate the improvement in daily and hourly weather prediction, particularly the prediction of summer rainfall over the Korean Peninsula, in the JHWC WRF (Weather Research and Forecasting) model system by 3DVAR (three-Dimensional Variational) data assimilation using the data obtained from KEOP (Korea Enhanced Observation Program). KEOP was conducted during the period June 15 to July 15, 2007, and the data obtained included GTS (Global Telecommunication System) upper-air sounding, AWS (Automatic Weather System), wind profiler, and radar observation data. Rainfall prediction and its characteristics should be verified by using the precipitation observation and the difference field of each experiment. High-resolution (3 km in domain 3) summer rainfall prediction over the Korean peninsula is substantially influenced by improved synoptic-scale prediction in domains 1 (27 km) and 2 (9 km), in particular by data assimilation using the sounding and wind profiler data. The rainfall prediction in domain 3 was further improved by radar and AWS data assimilation in domain 3. The equitable threat score and bias score of the rainfall predicted in domain 3 indicated improvement for the threshold values of 0.1, 1, and 2.5 mm with data assimilation. For cases of occurrence of heavy rainfall (7 days), the equitable threat score and bias score improved considerably at all threshold values as compared to the entire period of KEOP. Radar and AWS data assimilation improved the temporal and spatial distributions of diurnal rainfall over southern Korea, and AWS data assimilation increased the predicted rainfall amount by approximately 0.3 mm 3hr-1.

  2. Real-Time Safety Monitoring and Prediction for the National Airspace System

    NASA Technical Reports Server (NTRS)

    Roychoudhury, Indranil

    2016-01-01

    As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have both an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecasts, predicted health of assets in the airspace, and so on. To this end, we have developed a Real-Time Safety Monitoring (RTSM) that first, estimates the state of the NAS using the dynamic models. Then, given the state estimate and a probability distribution of future inputs to the NAS, the framework predicts the evolution of the NAS, i.e., the future state, and analyzes these future states to predict the occurrence of unsafe events. The entire probability distribution of airspace safety metrics is computed, not just point estimates, without significant assumptions regarding the distribution type and or parameters. We demonstrate our overall approach by predicting the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress.

  3. Real time monitoring of reticle etch process tool to investigate and predict critical dimension performance

    NASA Astrophysics Data System (ADS)

    Deming, Rick; Yung, Karmen; Guglielmana, Mark; Bald, Dan; Baik, Kiho; Abboud, Frank

    2007-03-01

    As mask pattern feature sizes shrink the need for tighter control of factors affecting critical dimensions (CD) increases at all steps in the mask manufacturing process. To support this requirement Intel Mask Operation is expanding its process and equipment monitoring capability. We intend to better understand the factors affecting the process and enhance our ability to predict reticle health and critical dimension performance. This paper describes a methodology by which one can predict the contribution of the dry etch process equipment to overall CD performance. We describe the architecture used to collect critical process related information from various sources both internal and external to the process equipment and environment. In addition we discuss the method used to assess the significance of each parameter and to construct the statistical model used to generate the predictions. We further discuss the methodology used to turn this model into a functioning real time prediction of critical dimension performance. Further, these predictions will be used to modify the manufacturing decision support system to provide early detection for process excursion.

  4. Predicting the stiffness and strength of human femurs with real metastatic tumors.

    PubMed

    Yosibash, Zohar; Plitman Mayo, Romina; Dahan, Gal; Trabelsi, Nir; Amir, Gail; Milgrom, Charles

    2014-12-01

    Predicting patient specific risk of fracture in femurs with metastatic tumors and the need for surgical intervention are of major clinical importance. Recent patient-specific high-order finite element methods (p-FEMs) based on CT-scans demonstrated accurate results for healthy femurs, so that their application to metastatic affected femurs is considered herein. Radiographs of fresh frozen proximal femur specimens from donors that died of cancer were examined, and seven pairs with metastatic tumor were identified. These were CT-scanned, instrumented by strain-gauges and loaded in stance position at three inclination angles. Finally the femurs were loaded until fracture that usually occurred at the neck. Histopathology was performed to determine whether metastatic tumors are present at fractured surfaces. Following each experiment p-FE models were created based on the CT-scans mimicking the mechanical experiments. The predicted displacements, strains and yield loads were compared to experimental observations. The predicted strains and displacements showed an excellent agreement with the experimental observations with a linear regression slope of 0.95 and a coefficient of regression R(2)=0.967. A good correlation was obtained between the predicted yield load and the experimental observed yield, with a linear regression slope of 0.80 and a coefficient of regression R(2)=0.78. CT-based patient-specific p-FE models of femurs with real metastatic tumors were demonstrated to predict the mechanical response very well. A simplified yield criterion based on the computation of principal strains was also demonstrated to predict the yield force in most of the cases, especially for femurs that failed at small loads. In view of the limited capabilities to predict risk of fracture in femurs with metastatic tumors used nowadays, the p-FE methodology validated herein may be very valuable in making clinical decisions. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Obtaining Reliable Predictions of Terrestrial Energy Coupling From Real-Time Solar Wind Measurements

    NASA Technical Reports Server (NTRS)

    Weimer, Daniel R.

    2002-01-01

    Measurements of the interplanetary magnetic field (IMF) from the ACE (Advanced Composition Explorer), Wind, IMP-8 (Interplanetary Monitoring Platform), and Geotail spacecraft have revealed that the IMF variations are contained in phase planes that are tilted with respect to the propagation direction, resulting in continuously variable changes in propagation times between spacecraft, and therefore, to the Earth. Techniques for using 'minimum variance analysis' have been developed in order to be able to measure the phase front tilt angles, and better predict the actual propagation times from the L1 orbit to the Earth, using only the real-time IMF measurements from one spacecraft. The use of empirical models with the IMF measurements at L1 from ACE (or future satellites) for predicting 'space weather' effects has also been demonstrated.

  6. Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

    NASA Technical Reports Server (NTRS)

    Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

    2011-01-01

    A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

  7. Real driving at night--predicting lane departures from physiological and subjective sleepiness.

    PubMed

    Hallvig, David; Anund, Anna; Fors, Carina; Kecklund, Göran; Åkerstedt, Torbjörn

    2014-09-01

    Only limited information is available on how driving performance relates to physiological and subjective sleepiness on real roads. This relation was the focus of the present study. 33 volunteers drove for 90 min on a rural road during the afternoon and night in an instrumented car, while electroencephalography and electrooculography and lane departures were recorded continuously and subjective ratings of sleepiness were made every 5 min (Karolinska Sleepiness Scale - KSS). Data was analyzed using Bayesian multilevel modeling. Unintentional LDs increased during night driving, as did KSS and long blink durations(LBD). Lateral position moved to the left . LDs were predicted by self-reported sleepiness and LBDs across time and were significantly higher in individuals with high sleepiness. Removal of intentional LDs, enhanced the KSS/LD relation. It was concluded that LDs, KSS, and LBDs are strongly increased during night driving and that KSS predicts LDs.

  8. Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction

    NASA Technical Reports Server (NTRS)

    Su, Fengge; Gao, Huilin; Huffman, George J.; Lettenmaier, Dennis P.

    2010-01-01

    We investigate the potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product, and through evaluation of streamflow simulations over four tributaries of La Plata Basin (LPB) in South America using the two precipitation products. Our assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February, 2005 which include use of additional microwave sensors (AMSR-E and AMSU-B) and implementation of different calibration schemes. Our work suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

  9. Investigation of telomere lengths measurement by quantitative real-time PCR to predict age.

    PubMed

    Hewakapuge, Sudinna; van Oorschot, Roland A H; Lewandowski, Paul; Baindur-Hudson, Swati

    2008-09-01

    Currently DNA profiling methods only compare a suspect's DNA with DNA left at the crime scene. When there is no suspect, it would be useful for the police to be able to predict what the person of interest looks like by analysing the DNA left behind in a crime scene. Determination of the age of the suspect is an important factor in creating an identikit. Human somatic cells gradually lose telomeric repeats with age. This study investigated if one could use a correlation between telomere length and age, to predict the age of an individual from their DNA. Telomere length, in buccal cells, of 167 individuals aged between 1 and 96 years old was measured using real-time quantitative PCR. Telomere length decreased with age (r=-0.185, P<0.05) and the age of an individual could be roughly determined by the following formula: (age=relative telomere length -1.5/-0.005). The regression (R(2)) value between telomere length and age was approximately 0.04, which is too low to be use for forensics. The causes for the presence of large variation in telomere lengths in the population were further investigated. The age prediction accuracies were low even after dividing samples into non-related Caucasians, males and females (5%, 9% and 1%, respectively). Mean telomere lengths of eight age groups representing each decade of life showed non-linear decrease in telomere length with age. There were variations in telomere lengths even among similarly aged individuals aged 26 years old (n=10) and age 54 years old (n=9). Therefore, telomere length measurement by real-time quantitative PCR cannot be used to predict age of a person, due to the presence of large inter-individual variations in telomere lengths.

  10. Real-time index for predicting successful golf putting motion using multichannel EEG.

    PubMed

    Muangjaroen, Piyachat; Wongsawat, Yodchanan

    2012-01-01

    A skill in goal-directed sport performance is an ability involving with many factors of both external and internal concernment. External factors are still developed while internal factors are challenged topic to understand for improving the performance. Internal concernment is explained an effective performance as estimation, solving strategy, planning and decision on the brain. These conjunctions are relevant to somatosensory information, focus attention and fine motor control of cortical activity. Five skilled right-handed golfers were recruited to be subjected of studying the criteria on how to predict golf putt success. Each of their putts was calculated in power spectral analysis by comparing to the pre-movement period. Successful and unsuccessful putt were classified by focusing on the frontal-midline(Fz), parietal-midline(Pz), central midline(Cz), left central(C3) and right central(C4) which supported by few consistency studies that they are related to a primary sensory motor area, focus attention and working memory processing. Results were shown that high alpha power on C4, theta power on Fz, theta power and high alpha power on Pz can be calculated to use as index of predicting golf putt success. Real-time monitoring system with friendly GUI was proposed in this study as promising preliminary study. Expected goal in the future is to apply this real-time golf putting prediction system into a biofeedback system to increase the golf putting's accuracy. However, it still needs more subjects to increase credibility and accuracy of the prediction.

  11. EVALUATING AND IMPROVING REAL-TIME STRATEGIES FOR ENGINEERING GROUND MOTION PREDICTIONS

    NASA Astrophysics Data System (ADS)

    Iervolino, I.; Giorgio, M.; Manfredi, G.

    2009-12-01

    Because, from the engineering perspective, the effectiveness of earthquake early warning systems (EEWS) depends only on the possibility of immediately detecting the earthquake and estimating the expected loss, or a proxy for it, for an engineered system of interest in order to undertake actions to manage/mitigate the risk before the strike, it is worthwhile to assess the efficiency of strategies to predict in real-time the earthquake’s destructive potential. The simplest engineering ground motion parameter is the peak ground acceleration (PGA) which may be predicted through probabilistic seismic hazard analysis in the framework of EEW conditional on some measures the seismologists use to estimate the magnitude from the early recorded signal. The effects of different sources of uncertainty on the prediction of PGA are assessed with reference to the ISNet (Irpinia Seismic Network) EEWS, although results can be considered general. The analyses show how the uncertainty of the ground motion prediction equation (GMPE) dominates those of magnitude and distance, almost independently of the information available for the event. Because the uncertainty related to GMPE is usually very large, it seems that the estimation of PGA should be where to put effort rather than improving the estimation of magnitude and/or earthquake location. An attempt to reduce the uncertainty in the estimation of PGA is made by adding more information (i.e., a second parameter measured in the early part of the signal from real-time seismology) and using the intra-event spatial correlation of peak accelerations at different sites. Based on these analyses distance-related bounds to uncertainty and information-dependent lead-time maps are defined and illustratively computed for the Campania (southern Italy) region.

  12. Toward a Global Model for Predicting Earthquake-Induced Landslides in Near-Real Time

    NASA Astrophysics Data System (ADS)

    Nowicki, M. A.; Wald, D. J.; Hamburger, M. W.; Hearne, M.; Thompson, E.

    2013-12-01

    We present a newly developed statistical model for estimating the distribution of earthquake-triggered landslides in near-real time, which is designed for use in the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) and ShakeCast systems. We use standardized estimates of ground shaking from the USGS ShakeMap Atlas 2.0 to develop an empirical landslide probability model by combining shaking estimates with broadly available landslide susceptibility proxies, including topographic slope, surface geology, and climatic parameters. While the initial model was based on four earthquakes for which digitally mapped landslide inventories and well constrained ShakeMaps are available--the Guatemala (1976), Northridge, California (1994), Chi-Chi, Taiwan (1999), and Wenchuan, China (2008) earthquakes, our improved model includes observations from approximately ten other events from a variety of tectonic and geomorphic settings for which we have obtained landslide inventories. Using logistic regression, this database is used to build a predictive model of the probability of landslide occurrence. We assess the performance of the regression model using statistical goodness-of-fit metrics to determine which combination of the tested landslide proxies provides the optimum prediction of observed landslides while minimizing ';false alarms' in non-landslide zones. Our initial results indicate strong correlations with peak ground acceleration and maximum slope, and weaker correlations with surface geological and soil wetness proxies. In terms of the original four events included, the global model predicts landslides most accurately when applied to the Wenchuan and Chi-Chi events, and less accurately when applied to the Northridge and Guatemala datasets. Combined with near-real time ShakeMaps, the model can be used to make generalized predictions of whether or not landslides are likely to occur (and if so, where) for future earthquakes around the globe, and these estimates

  13. Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

    2015-01-01

    The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building

  14. One-Year Real-Time Operational Prediction Intervals for Direct Normal Irradiance

    NASA Astrophysics Data System (ADS)

    Chu, Y.; Carreira Pedro, H. T.; Coimbra, C. F.

    2015-12-01

    This work describes an algorithm to generate intra-hour prediction intervals (PIs) for the highly-variable direct normal irradiance, which is the energy source for the concentrated solar power technologies. The prediction intervals are generated using a Multi-layer Stochastic-Learning Model (MSLM), which is developed based on methods such as: sky imaging techniques, support vector machine and artificial neural network. The MSLM is trained using one year of co-located, high-quality irradiance and sky image recording in Folsom, California. In addition to being validated with historical data, the algorithm has been generating operational PI forecasts in real-time for that observatory since July 1st 2014. In the real-time scenario, without re-training or significant maintenance, the hybrid model consistently provides valid PI (PICP > 92%) and outperforms the reference persistence model (PICP ~ 85%) regardless of weather condition. This work has great impact in the field of solar energy to potentially facilitate the level of solar penetration in the grid with significantly reduced integration costs.

  15. Predicting Decisions in Human Social Interactions Using Real-Time fMRI and Pattern Classification

    PubMed Central

    Baecke, Sebastian; Lützkendorf, Ralf; Müller, Charles; Adolf, Daniela; Bernarding, Johannes

    2011-01-01

    Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives. PMID:22003388

  16. Real-time Automated Sampling of Electronic Medical Records Predicts Hospital Mortality

    PubMed Central

    Khurana, Hargobind S.; Groves, Robert H.; Simons, Michael P.; Martin, Mary; Stoffer, Brenda; Kou, Sherri; Gerkin, Richard; Reiman, Eric; Parthasarathy, Sairam

    2016-01-01

    Background Real-time automated continuous sampling of electronic medical record data may expeditiously identify patients at risk for death and enable prompt life-saving interventions. We hypothesized that a real-time electronic medical record-based alert could identify hospitalized patients at risk for mortality. Methods An automated alert was developed and implemented to continuously sample electronic medical record data and trigger when at least two of four systemic inflammatory response syndrome criteria plus at least one of 14 acute organ dysfunction parameters was detected. The SIRS/OD alert was applied real-time to 312,214 patients in 24 hospitals and analyzed in two phases: training and validation datasets. Results In the training phase, 29,317 (18.8%) triggered the alert and 5.2% of such patients died whereas only 0.2% without the alert died (unadjusted odds ratio 30.1; 95% confidence interval [95%CI] 26.1, 34.5; P<0.0001). In the validation phase, the sensitivity, specificity, area under curve (AUC), positive and negative likelihood ratios for predicting mortality were 0.86, 0.82, 0.84, 4.9, and 0.16, respectively. Multivariate Cox-proportional hazard regression model revealed greater hospital mortality when the alert was triggered (adjusted Hazards Ratio 4.0; 95%CI 3.3, 4.9; P<0.0001). Triggering the alert was associated with additional hospitalization days (+3.0 days) and ventilator days (+1.6 days; P<0.0001). Conclusion An automated alert system that continuously samples electronic medical record-data can be implemented, has excellent test characteristics, and can assist in the real-time identification of hospitalized patients at risk for death. PMID:27019043

  17. To predict sufentanil requirement for postoperative pain control using a real-time method

    PubMed Central

    Zhang, Yuhao; Duan, Guangyou; Guo, Shanna; Ying, Ying; Huang, Penghao; Zhang, Mi; Li, Ningbo; Zhang, Xianwei

    2016-01-01

    Abstract Preoperative identification of individual sensitivity to opioid analgesics could improve the quality of postoperative analgesia. We explored the feasibility and utility of a real-time assessment of sufentanil sensitivity in predicting postoperative analgesic requirement. Our primary study included 111 patients who underwent measurements of pressure and quantitative pricking pain thresholds before and 5 minutes after sufentanil infusion. Pain intensity was assessed during the first 24-hour postsurgery, and patients who reported inadequate levels of analgesia were excluded from the study. The sufentanil requirement for patient-controlled analgesia was recorded, and a subsequent exploratory study of 20 patients facilitated the interpretation of the primary study results. In the primary study, experimental pain thresholds increased (P < 0.001) 5 minutes after sufentanil infusion, and the percent change in pricking pain threshold was positively associated with sufentanil requirement at 12 and 24 hours after surgery (β = 0.318, P = 0.001; and β = 0.335, P = 0.001). A receiver-operating characteristic curve analysis showed that patients with a change in pricking pain threshold >188% were >50% likely to require more sufentanil for postoperative pain control. In the exploratory study, experimental pain thresholds significantly decreased after the operation (P < 0.001), and we observed a positive correlation (P < 0.001) between the percent change in pricking pain threshold before and after surgery. Preoperative detection of individual sensitivity to sufentanil via the above described real-time method was effective in predicting postoperative sufentanil requirement. Thus, percent change in pricking pain threshold might be a feasible predictive marker of postoperative analgesia requirement. PMID:27336880

  18. Development of a globally applicable model for near real-time prediction of seismically induced landslides

    USGS Publications Warehouse

    Nowicki, M. Anna; Wald, David J.; Hamburger, Michael W.; Hearne, Mike; Thompson, Eric M.

    2014-01-01

    Substantial effort has been invested to understand where seismically induced landslides may occur in the future, as they are a costly and frequently fatal threat in mountainous regions. The goal of this work is to develop a statistical model for estimating the spatial distribution of landslides in near real-time around the globe for use in conjunction with the U.S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system. This model uses standardized outputs of ground shaking from the USGS ShakeMap Atlas 2.0 to develop an empirical landslide probability model, combining shaking estimates with broadly available landslide susceptibility proxies, i.e., topographic slope, surface geology, and climate parameters. We focus on four earthquakes for which digitally mapped landslide inventories and well-constrainedShakeMaps are available. The resulting database is used to build a predictive model of the probability of landslide occurrence. The landslide database includes the Guatemala (1976), Northridge (1994), Chi-Chi (1999), and Wenchuan (2008) earthquakes. Performance of the regression model is assessed using statistical goodness-of-fit metrics and a qualitative review to determine which combination of the proxies provides both the optimum prediction of landslide-affected areas and minimizes the false alarms in non-landslide zones. Combined with near real-time ShakeMaps, these models can be used to make generalized predictions of whether or not landslides are likely to occur (and if so, where) for earthquakes around the globe, and eventually to inform loss estimates within the framework of the PAGER system.

  19. Real-Time Monitoring and Prediction of the Pilot Vehicle System (PVS) Closed-Loop Stability

    NASA Astrophysics Data System (ADS)

    Mandal, Tanmay Kumar

    Understanding human control behavior is an important step for improving the safety of future aircraft. Considerable resources are invested during the design phase of an aircraft to ensure that the aircraft has desirable handling qualities. However, human pilots exhibit a wide range of control behaviors that are a function of external stimulus, aircraft dynamics, and human psychological properties (such as workload, stress factor, confidence, and sense of urgency factor). This variability is difficult to address comprehensively during the design phase and may lead to undesirable pilot-aircraft interaction, such as pilot-induced oscillations (PIO). This creates the need to keep track of human pilot performance in real-time to monitor the pilot vehicle system (PVS) stability. This work focused on studying human pilot behavior for the longitudinal axis of a remotely controlled research aircraft and using human-in-the-loop (HuIL) simulations to obtain information about the human controlled system (HCS) stability. The work in this dissertation is divided into two main parts: PIO analysis and human control model parameters estimation. To replicate different flight conditions, this study included time delay and elevator rate limiting phenomena, typical of actuator dynamics during the experiments. To study human control behavior, this study employed the McRuer model for single-input single-output manual compensatory tasks. McRuer model is a lead-lag controller with time delay which has been shown to adequately model manual compensatory tasks. This dissertation presents a novel technique to estimate McRuer model parameters in real-time and associated validation using HuIL simulations to correctly predict HCS stability. The McRuer model parameters were estimated in real-time using a Kalman filter approach. The estimated parameters were then used to analyze the stability of the closed-loop HCS and verify them against the experimental data. Therefore, the main contribution of

  20. Antibubble and prediction of China's stock market and real-estate

    NASA Astrophysics Data System (ADS)

    Zhou, Wei-Xing; Sornette, Didier

    2004-06-01

    We show that the Chinese stock markets are quite different and decoupled from Western markets (which include Tokyo). We document a well-developed log-periodic power-law antibubble in China's stock market, which started in August 2001. We argue that the current stock market antibubble is sustained by a contemporary active unsustainable real-estate bubble in China. The characteristic parameters of the antibubble have exhibited remarkable stability over one year (October 2002-October 2003). Many tests, including predictability over different horizons and time periods, confirm the high significance of the antibubble detection. Based on an analysis including data up to 2003/10/28, we have predicted that the Chinese stock market will stop its negative trend around the end of 2003 and start going up, appreciating by at least 25% in the following 6 months. We present a partial assessment of this prediction at the time of revision of this manuscript (early January 2004). Notwithstanding the immature nature of the Chinese equity market and the strong influence of government policy, we have found maybe even stronger imprints of herding than in other mature markets. This is maybe due indeed to the immaturity of the Chinese market which seems to attract short-term investors more interested in fast gains than in long-term investments, thus promoting speculative herding.

  1. Evaluation of real-time hydrometeorological ensemble prediction on hydrologic scales in Northern California

    NASA Astrophysics Data System (ADS)

    Georgakakos, Konstantine P.; Graham, Nicholas E.; Modrick, Theresa M.; Murphy, Michael J.; Shamir, Eylon; Spencer, Cristopher R.; Sperfslage, Jason A.

    2014-11-01

    The paper presents an evaluation of real time ensemble forecasts produced during 2010-2012 by the demonstration project INFORM (Integrated Forecast and Reservoir Management) in Northern California. In addition, the innovative elements of the forecast component of the INFORM project are highlighted. The forecast component is designed to dynamically downscale operational multi-lead ensemble forecasts from the Global Ensemble Forecast System (GEFS) and the Climate Forecast system (CFS) of the National Centers of Environmental Prediction (NCEP), and to use adaptations of the operational hydrologic models of the US National Weather Service California Nevada River Forecast Center to provide ensemble reservoir inflow forecasts in real time. A full-physics 10-km resolution (10 km on the side) mesoscale model was implemented for the ensemble prediction of surface precipitation and temperature over the domain of Northern California with lead times out to 16 days with 6-hourly temporal resolution. An intermediate complexity regional model with a 10 km resolution was implemented to downscale the NCEP CFS ensemble forecasts for lead times out to 41.5 days. Methodologies for precipitation and temperature model forecast adjustment to comply with the corresponding observations were formulated and tested as regards their effectiveness for improving the ensemble predictions of these two variables and also for improving reservoir inflow forecasts. The evaluation is done using the real time databases of INFORM and concerns the snow accumulation and melt seasons. Performance is measured by metrics that range from those that use forecast means to those that use the entire forecast ensemble. The results show very good skill in forecasting precipitation and temperature over the subcatchments of the INFORM domain out to a week in advance for all basins, models and seasons. For temperature, in some cases, non-negligible skill has been obtained out to four weeks for the melt season

  2. Aberrant CBFA2T3B gene promoter methylation in breast tumors

    PubMed Central

    Bais, Anthony J; Gardner, Alison E; McKenzie, Olivia LD; Callen, David F; Sutherland, Grant R; Kremmidiotis, Gabriel

    2004-01-01

    Background The CBFA2T3 locus located on the human chromosome region 16q24.3 is frequently deleted in breast tumors. CBFA2T3 gene expression levels are aberrant in breast tumor cell lines and the CBFA2T3B isoform is a potential tumor suppressor gene. In the absence of identified mutations to further support a role for this gene in tumorigenesis, we explored whether the CBFA2T3B promoter region is aberrantly methylated and whether this correlates with expression. Results Aberrant hypo and hypermethylation of the CBFA2T3B promoter was detected in breast tumor cell lines and primary breast tumor samples relative to methylation index interquartile ranges in normal breast counterpart and normal whole blood samples. A statistically significant inverse correlation between aberrant CBFA2T3B promoter methylation and gene expression was established. Conclusion CBFA2T3B is a potential breast tumor suppressor gene affected by aberrant promoter methylation and gene expression. The methylation levels were quantitated using a second-round real-time methylation-specific PCR assay. The detection of both hypo and hypermethylation is a technicality regarding the methylation methodology. PMID:15301688

  3. Low T3 syndrome is a strong prognostic predictor in diffuse large B cell lymphoma.

    PubMed

    Gao, Rui; Liang, Jin-Hua; Wang, Li; Zhu, Hua-Yuan; Wu, Wei; Wu, Jia-Zhu; Xia, Yi; Cao, Lei; Fan, Lei; Yang, Tao; Li, Jian-Yong; Xu, Wei

    2017-02-01

    The aim of this study was to evaluate the prognostic effect of low triiodothyronine (T3) syndrome on patients with diffuse large B cell lymphoma (DLBCL). A hundred and eighty-eight patients with detailed thyroid hormone levels at diagnosis of DLBCL were enrolled. Low T3 syndrome was defined as a low serum free T3 (FT3) level with low or normal serum free tetraiodothyronine (FT4) and thyroid stimulating hormone levels. Multivariate Cox regression analysis was used to screen prognostic factors associated with progression-free survival (PFS) and overall survival (OS). Receiver-operator characteristic curves and the corresponding areas under the curve were calculated to assess the predictive accuracy of International Prognostic Index (IPI) and low T3 syndrome. Twenty-four patients were diagnosed with low T3 syndrome, which was associated with worse PFS and OS in the rituximab era. It was an independent prognostic factor for PFS and OS, especially for those with IPI 0-2, extranodal sites ≤1 and stage III-IV. Synchronously low FT3 and FT4 had poorer survival outcome compared to only low FT3 and adding criterion of low T3 syndrome improved the prognostic capacity of IPI for predicting PFS and OS in DLBCL. Low T3 syndrome was found to be a strong prognostic predictor in DLBCL.

  4. Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer.

    PubMed

    Ouari, Kamel; Rekioua, Toufik; Ouhrouche, Mohand

    2014-01-01

    In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller.

  5. Prediction of solar energetic particle event histories using real-time particle and solar wind measurements

    NASA Technical Reports Server (NTRS)

    Roelof, E. C.; Gold, R. E.

    1978-01-01

    The comparatively well-ordered magnetic structure in the solar corona during the decline of Solar Cycle 20 revealed a characteristic dependence of solar energetic particle injection upon heliographic longitude. When analyzed using solar wind mapping of the large scale interplanetary magnetic field line connection from the corona to the Earth, particle fluxes display an approximately exponential dependence on heliographic longitude. Since variations in the solar wind velocity (and hence the coronal connection longitude) can severely distort the simple coronal injection profile, the use of real-time solar wind velocity measurements can be of great aid in predicting the decay of solar particle events. Although such exponential injection profiles are commonplace during 1973-1975, they have also been identified earlier in Solar Cycle 20, and hence this structure may be present during the rise and maximum of the cycle, but somewhat obscured by greater temporal variations in particle injection.

  6. Predicting photoemission intensities and angular distributions with real-time density-functional theory

    NASA Astrophysics Data System (ADS)

    Dauth, M.; Kümmel, S.

    2016-02-01

    Photoemission spectroscopy is one of the most frequently used tools for characterizing the electronic structure of condensed matter systems. We discuss a scheme for simulating photoemission from finite systems based on time-dependent density-functional theory. It allows for the first-principles calculation of relative electron binding energies, ionization cross sections, and anisotropy parameters. We extract these photoemission spectroscopy observables from Kohn-Sham orbitals propagated in real time. We demonstrate that the approach is capable of estimating photoemission intensities, i.e., peak heights. It can also reliably predict the angular distribution of photoelectrons. For the example of benzene we contrast calculated angular distribution anisotropy parameters to experimental reference data. Self-interaction free Kohn-Sham theory yields meaningful outer valence single-particle states in the right energetic order. We discuss how to properly choose the complex absorbing potential that is used in the simulations.

  7. NCAR's Experimental Real-time Convection-allowing Ensemble Prediction System

    NASA Astrophysics Data System (ADS)

    Schwartz, C. S.; Romine, G. S.; Sobash, R.; Fossell, K.

    2016-12-01

    Since April 2015, the National Center for Atmospheric Research's (NCAR's) Mesoscale and Microscale Meteorology (MMM) Laboratory, in collaboration with NCAR's Computational Information Systems Laboratory (CISL), has been producing daily, real-time, 10-member, 48-hr ensemble forecasts with 3-km horizontal grid spacing over the conterminous United States (http://ensemble.ucar.edu). These computationally-intensive, next-generation forecasts are produced on the Yellowstone supercomputer, have been embraced by both amateur and professional weather forecasters, are widely used by NCAR and university researchers, and receive considerable attention on social media. Initial conditions are supplied by NCAR's Data Assimilation Research Testbed (DART) software and the forecast model is NCAR's Weather Research and Forecasting (WRF) model; both WRF and DART are community tools. This presentation will focus on cutting-edge research results leveraging the ensemble dataset, including winter weather predictability, severe weather forecasting, and power outage modeling. Additionally, the unique design of the real-time analysis and forecast system and computational challenges and solutions will be described.

  8. Real-Time Mesoscale Modeling Over Antarctica: The Antarctic Mesoscale Prediction System*.

    NASA Astrophysics Data System (ADS)

    Powers, Jordan G.; Monaghan, Andrew J.; Cayette, Arthur M.; Bromwich, David H.; Kuo, Ying-Hwa; Manning, Kevin W.

    2003-11-01

    *Byrd Polar Research Center Contribution Number 1276In support of the United States Antarctic Program (USAP), the National Center for Atmospheric Research and the Byrd Polar Research Center of The Ohio State University have created the Antarctic Mesoscale Prediction System (AMPS): an experimental, real-time mesoscale modeling system covering Antarctica. AMPS has been designed to serve flight forecasters at McMurdo Station, to support science and operations around the continent, and to be a vehicle for the development of physical parameterizations suitable for polar regions. Since 2000, AMPS has been producing high-resolution forecasts (grids to 3.3 km) with the “Polar MM5,” a version of the fifth-generation Pennsylvania State University NCAR Mesoscale Model tuned for the polar atmosphere. Beyond its basic mission of serving the USAP flight forecasters at McMurdo, AMPS has assisted both in emergency operations to save lives and in programs to explore the extreme polar environment. The former have included a medical evacuation from the South Pole and a marine rescue from the continental margin. The latter have included scientific field campaigns and the daily activities of international Antarctic forecasters and researchers. The AMPS program has been a success in terms of advancing polar mesoscale NWP, serving critical logistical operations of the USAP, and, most visibly, assisting in emergency rescue missions to save lives. The history and performance of AMPS are described and the successes of this unique real-time mesoscale modeling system in crisis support are detailed.

  9. Real-Time Aircraft Cosmic Ray Radiation Exposure Predictions from the NAIRAS Model

    NASA Astrophysics Data System (ADS)

    Mertens, C. J.; Tobiska, W.; Kress, B. T.; Xu, X.

    2012-12-01

    The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting commercial aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Thus, the NAIRAS model addresses an important national need with broad societal, public health and economic benefits. There is also interest in extending NAIRAS to the LEO environment to address radiation hazard issues for the emerging commercial spaceflight industry. The processes responsible for the variability in the solar wind, interplanetary magnetic field, solar energetic particle spectrum, and the dynamical response of the magnetosphere to these space environment inputs, strongly influence the composition and energy distribution of the atmospheric ionizing radiation field. Real-time observations are required at a variety of locations within the geospace environment. The NAIRAS model is driven by real-time input data from ground-, atmospheric-, and space-based platforms. During the development of the NAIRAS model, new science questions and observational data gaps were identified that must be addressed in order to obtain a more reliable and robust operational model of atmospheric radiation exposure. The focus of this talk is to present the current capabilities of the NAIRAS model, discuss future developments in aviation radiation modeling and instrumentation, and propose strategies and methodologies of bridging known gaps in current modeling and observational capabilities.

  10. Real-Time Prediction of Temperature Elevation During Robotic Bone Drilling Using the Torque Signal.

    PubMed

    Feldmann, Arne; Gavaghan, Kate; Stebinger, Manuel; Williamson, Tom; Weber, Stefan; Zysset, Philippe

    2017-05-05

    Bone drilling is a surgical procedure commonly required in many surgical fields, particularly orthopedics, dentistry and head and neck surgeries. While the long-term effects of thermal bone necrosis are unknown, the thermal damage to nerves in spinal or otolaryngological surgeries might lead to partial paralysis. Previous models to predict the temperature elevation have been suggested, but were not validated or have the disadvantages of computation time and complexity which does not allow real time predictions. Within this study, an analytical temperature prediction model is proposed which uses the torque signal of the drilling process to model the heat production of the drill bit. A simple Green's disk source function is used to solve the three dimensional heat equation along the drilling axis. Additionally, an extensive experimental study was carried out to validate the model. A custom CNC-setup with a load cell and a thermal camera was used to measure the axial drilling torque and force as well as temperature elevations. Bones with different sets of bone volume fraction were drilled with two drill bits ([Formula: see text]1.8 mm and [Formula: see text]2.5 mm) and repeated eight times. The model was calibrated with 5 of 40 measurements and successfully validated with the rest of the data ([Formula: see text]C). It was also found that the temperature elevation can be predicted using only the torque signal of the drilling process. In the future, the model could be used to monitor and control the drilling process of surgeries close to vulnerable structures.

  11. Real Time Monitoring and Prediction of the Monsoon Intraseasonal Oscillations: An index based on Nonlinear Laplacian Spectral Analysis Technique

    NASA Astrophysics Data System (ADS)

    Cherumadanakadan Thelliyil, S.; Ravindran, A. M.; Giannakis, D.; Majda, A.

    2016-12-01

    An improved index for real time monitoring and forecast verification of monsoon intraseasonal oscillations (MISO) is introduced using the recently developed Nonlinear Laplacian Spectral Analysis (NLSA) algorithm. Previous studies has demonstrated the proficiency of NLSA in capturing low frequency variability and intermittency of a time series. Using NLSA a hierarchy of Laplace-Beltrami (LB) eigen functions are extracted from the unfiltered daily GPCP rainfall data over the south Asian monsoon region. Two modes representing the full life cycle of complex northeastward propagating boreal summer MISO are identified from the hierarchy of Laplace-Beltrami eigen functions. These two MISO modes have a number of advantages over the conventionally used Extended Empirical Orthogonal Function (EEOF) MISO modes including higher memory and better predictability, higher fractional variance over the western Pacific, Western Ghats and adjoining Arabian Sea regions and more realistic representation of regional heat sources associated with the MISO. The skill of NLSA based MISO indices in real time prediction of MISO is demonstrated using hindcasts of CFSv2 extended range prediction runs. It is shown that these indices yield a higher prediction skill than the other conventional indices supporting the use of NLSA in real time prediction of MISO. Real time monitoring and prediction of MISO finds its application in agriculture, construction and hydro-electric power sectors and hence an important component of monsoon prediction.

  12. The occurrence of T3 thyrotoxicosis in pregancy.

    PubMed

    Martin, D H; Montgomery, D A; Harley, J M

    1976-12-01

    A case of T3 thyrotoxicosis in pregnancy is described. The condition may be overlooked if serum T3 levels are not measured routinely since the usual tests of thyroid function are unaltered in this form of hyperthyroidism.

  13. Effects of C-reactive protein on adipokines genes expression in 3T3-L1 adipocytes

    SciTech Connect

    Yuan, Guoyue; Jia, Jue; Di, Liangliang; Zhou, Libin; Dong, Sijing; Ye, Jingjing; Wang, Dong; Yang, Ling; Wang, Jifang; Li, Lianxi; Yang, Ying; Mao, Chaoming; Chen, Mingdao

    2012-08-03

    Highlights: Black-Right-Pointing-Pointer CRP increases TNF-{alpha} and IL-6 genes expression in matured 3T3-L1 adipocytes. Black-Right-Pointing-Pointer CRP suppresses adiponectin, leptin and PPAR-{gamma} mRNA levels in matured 3T3-L1 cells. Black-Right-Pointing-Pointer Wortmannin reverses effects of CRP on adiponectin, TNF-{alpha} and leptin mRNA levels. Black-Right-Pointing-Pointer CRP may regulate IR, obesity and metabolic syndrome by this mechanism. -- Abstract: Adipose tissue is now recognized to be an important endocrine organ, secreting a variety of adipokines that are involved in the regulation of energy metabolism, insulin resistance and metabolic syndrome. C-reactive protein (CRP) is considered as one of the most sensitive markers of inflammation. A number of studies have shown that elevation of CRP concentrations is an independent predictive parameter of type 2 diabetes mellitus, which is also strongly associated with various components of the metabolic syndrome. The aim of the present study is to investigate the effects of CRP on adipokines genes expression in 3T3-L1 adipocytes. Quantitative real-time PCR analysis revealed that CRP inhibited adiponectin, leptin and peroxisome proliferator-activated receptor-gamma (PPAR-{gamma}) genes expression and raised tumor necrosis factor-{alpha} (TNF-{alpha}) and interleukin-6 (IL-6) mRNA levels in matured 3T3-L1 adipocytes in a dose and time-dependent manner. Pharmacological inhibition of phosphatidylinositol (PI)-3 kinase by wortmannin partially reversed the effects of CRP on adiponectin, TNF-{alpha} and leptin genes expression. These results collectively suggest that CRP regulates adiponectin, TNF-{alpha}, leptin, IL-6 and PPAR-{gamma} genes expression, and that might represent a mechanism by which CRP regulates insulin resistance, obesity and metabolic syndrome.

  14. A simple modelling approach for prediction of standard state real gas entropy of pure materials.

    PubMed

    Bagheri, M; Borhani, T N G; Gandomi, A H; Manan, Z A

    2014-01-01

    The performance of an energy conversion system depends on exergy analysis and entropy generation minimisation. A new simple four-parameter equation is presented in this paper to predict the standard state absolute entropy of real gases (SSTD). The model development and validation were accomplished using the Linear Genetic Programming (LGP) method and a comprehensive dataset of 1727 widely used materials. The proposed model was compared with the results obtained using a three-layer feed forward neural network model (FFNN model). The root-mean-square error (RMSE) and the coefficient of determination (r(2)) of all data obtained for the LGP model were 52.24 J/(mol K) and 0.885, respectively. Several statistical assessments were used to evaluate the predictive power of the model. In addition, this study provides an appropriate understanding of the most important molecular variables for exergy analysis. Compared with the LGP based model, the application of FFNN improved the r(2) to 0.914. The developed model is useful in the design of materials to achieve a desired entropy value.

  15. Prediction-error in the context of real social relationships modulates reward system activity

    PubMed Central

    Poore, Joshua C.; Pfeifer, Jennifer H.; Berkman, Elliot T.; Inagaki, Tristen K.; Welborn, Benjamin L.; Lieberman, Matthew D.

    2012-01-01

    The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward—social validation—and this activity's relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants' expectations for their romantic partners' positive regard of them were confirmed (validated) or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust. PMID:22891055

  16. Real Time Immunophenotyping of Leukocyte Subsets Early after Double Cord Blood Transplantation Predicts Graft Function.

    PubMed

    Li, Jianqiang; Nicoud, Ian; Blake, Joseph; Oliver, David; Cox, Emily; Heimfeld, Shelly; Milano, Filippo; Imren, Suzan; Delaney, Colleen

    2017-03-01

    Cord blood transplantation (CBT) recipients are at increased risk for delayed engraftment and primary graft failure, complications that are often indistinguishable early post-transplantation. Current assays fail to accurately identify recipients with slow hematopoietic recovery and distinguish them from those with pending graft failure. To address this, we prospectively examined the kinetics of immune cell subset recovery in the peripheral blood of 39 patients on days +7 and +14 after double-unit CBT (dCBT) by multiparametric flow cytometry analysis, which we term real-time immunophenotyping (RTIP). RTIP analysis at day +14 revealed distinctive patterns of reconstitution and, importantly, identified patients with slow hematopoietic recovery who went on to engraft. Strikingly, higher absolute numbers of circulating monocytes and natural killer cells at day +14 were predictive of engraftment, but only the absolute number of circulating monocytes was significantly correlated with time to engraftment. This is the first evidence that RTIP on patient peripheral blood mononuclear cells early after dCBT is technically feasible and can be used as a "signature" for predicting the kinetics of hematopoietic recovery. Furthermore, RTIP is a time- and cost-efficient methodology that has the potential to become a clinically feasible diagnostic tool to guide therapeutic interventions in high-risk patients; therefore, its utility should be evaluated in a large cohort of patients.

  17. Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

    2015-12-01

    A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

  18. Real-time optical path control method that utilizes multiple support vector machines for traffic prediction

    NASA Astrophysics Data System (ADS)

    Kawase, Hiroshi; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi

    2016-02-01

    An effective solution to the continuous Internet traffic expansion is to offload traffic to lower layers such as the L2 or L1 optical layers. One possible approach is to introduce dynamic optical path operations such as adaptive establishment/tear down according to traffic variation. Path operations cannot be done instantaneously; hence, traffic prediction is essential. Conventional prediction techniques need optimal parameter values to be determined in advance by averaging long-term variations from the past. However, this does not allow adaptation to the ever-changing short-term variations expected to be common in future networks. In this paper, we propose a real-time optical path control method based on a machinelearning technique involving support vector machines (SVMs). A SVM learns the most recent traffic characteristics, and so enables better adaptation to temporal traffic variations than conventional techniques. The difficulty lies in determining how to minimize the time gap between optical path operation and buffer management at the originating points of those paths. The gap makes the required learning data set enormous and the learning process costly. To resolve the problem, we propose the adoption of multiple SVMs running in parallel, trained with non-overlapping subsets of the original data set. The maximum value of the outputs of these SVMs will be the estimated number of necessary paths. Numerical experiments prove that our proposed method outperforms a conventional prediction method, the autoregressive moving average method with optimal parameter values determined by Akaike's information criterion, and reduces the packet-loss ratio by up to 98%.

  19. Incidence and predictive factors of depressive symptoms in Alzheimer's disease: the REAL.FR study.

    PubMed

    Arbus, C; Gardette, V; Cantet, C E; Andrieu, S; Nourhashémi, F; Schmitt, L; Vellas, B

    2011-08-01

    Many patients develop psychiatric and behavioral disturbances in the course of Alzheimer's disease (AD). Among these disturbances, depressive symptoms are frequent and affect nearly 40% of patients. The natural history and course of such symptoms in AD, and in particular the predictive factors, are little known. We studied the incidence and risk factors for the development of the first depressive symptoms in AD. Multicenter prospective study. Three hundred twelve AD patients from the French Network on AD (REAL.FR) without depression and without antidepressant treatment at baseline were followed up and assessed every 6 months for 4 years. During follow-up, all events occurring between two visits were carefully recorded. We used the Neuropsychiatric Inventory (NPI) for comprehensive evaluation of behavioral and psychological symptoms and depressive symptoms in particular. A multivariate analysis was performed using a backward stepwise Cox proportional hazards model. The incidence of depressive symptoms was 17.45% person/years, 95%CI (13.88-21.02). Among non-time dependent variables, duration of disease (RR=0.51; 95%CI: 0.30-0.85, p=0.0102) and the number of comorbid conditions (RR=0.45; 95%CI: 0.24-0.83, p=0.0115) were protective factors against the development of depressive symptoms. Agitation/aggression (RR=1.96; 95%CI: 1.19-3.23, p=0.0078) and sleep disturbances (RR=2.65; 95%CI: 1.40-5.00, p=0.0026) were time-dependent variables predictive of depressive symptoms. Better knowledge of predictive factors of mood disturbances in AD will enable clinicians to set up appropriate management of their patients. As published longitudinal studies are few, further works should be carried out to improve knowledge of the pattern and course of depression and depressive symptoms in AD.

  20. Mobile range control center/range safety command destruct and real-time instantaneous impact prediction system

    NASA Technical Reports Server (NTRS)

    Hudson, Sandra Merritt

    1997-01-01

    The mobile range control center/range safety command destruct and real time instantaneous impact prediction system (MRCCS), designed for launching sounding rockets and expendable launch vehicles, is described. The MRCCS provides mission control and range safety support for remote launch sites and is equipped with telemetry and radar data acquisition systems, real time data computation systems, range safety display systems, and command destruct transmitters.

  1. Predicting crash likelihood and severity on freeways with real-time loop detector data.

    PubMed

    Xu, Chengcheng; Tarko, Andrew P; Wang, Wei; Liu, Pan

    2013-08-01

    Real-time crash risk prediction using traffic data collected from loop detector stations is useful in dynamic safety management systems aimed at improving traffic safety through application of proactive safety countermeasures. The major drawback of most of the existing studies is that they focus on the crash risk without consideration of crash severity. This paper presents an effort to develop a model that predicts the crash likelihood at different levels of severity with a particular focus on severe crashes. The crash data and traffic data used in this study were collected on the I-880 freeway in California, United States. This study considers three levels of crash severity: fatal/incapacitating injury crashes (KA), non-incapacitating/possible injury crashes (BC), and property-damage-only crashes (PDO). The sequential logit model was used to link the likelihood of crash occurrences at different severity levels to various traffic flow characteristics derived from detector data. The elasticity analysis was conducted to evaluate the effect of the traffic flow variables on the likelihood of crash and its severity.The results show that the traffic flow characteristics contributing to crash likelihood were quite different at different levels of severity. The PDO crashes were more likely to occur under congested traffic flow conditions with highly variable speed and frequent lane changes, while the KA and BC crashes were more likely to occur under less congested traffic flow conditions. High speed, coupled with a large speed difference between adjacent lanes under uncongested traffic conditions, was found to increase the likelihood of severe crashes (KA). This study applied the 20-fold cross-validation method to estimate the prediction performance of the developed models. The validation results show that the model's crash prediction performance at each severity level was satisfactory. The findings of this study can be used to predict the probabilities of crash at

  2. Performance of WRF-ARW model in real-time prediction of Bay of Bengal cyclone `Phailin'

    NASA Astrophysics Data System (ADS)

    Mandal, M.; Singh, K. S.; Balaji, M.; Mohapatra, M.

    2016-05-01

    This study examines the performance of the Advanced Research core of Weather Research and Forecasting (ARW-WRF) model in prediction of the Bay of Bengal cyclone `Phailin'. The two-way interactive double-nested model at 27 and 9-km resolutions customized at Indian Institute of Technology Kharagpur (IITKGP) is used to predict the storm on real-time basis and five predictions are made with five different initial conditions. The initial and boundary conditions for the model are derived from the Global Forecasting System (GFS) analysis and forecast respectively. The track of storm is well predicted in all the five forecasts. In particular, the forecast with less initial positional error led to more accurate track and landfall prediction. It is observed that the predicted peak intensity and translation speed of the storm depends strongly on initial intensity error, vertical wind shear and vertical distribution of maximum potential vorticity. The trend of intensification and dissipation of the storm is well predicted by the model in terms of central sea level pressure (CSLP). The intensity in terms of maximum surface wind (MSW) is under-predicted by the model and it is suggested that the MSW estimated from predicted pressure drop may be used as prediction guideline. The storm intensified rapidly during its passage over the high Tropical Cyclone Heat Potential zone and is reasonably well predicted by the model. Though the magnitude of the precipitation is not well predicted, distribution of precipitation is fairly well predicted by the model. The track and intensity of the storm predicted by the customized WRF-ARW is better than that of other NWP models. The landfall (time and position) is also better predicted by the model compared to other NWP models if initialized at cyclonic storm stage. The results indicate that the customized model have good potential for real-time prediction of Bay of Bengal cyclones and encourage further investigation with larger number of cyclones.

  3. GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world

    PubMed Central

    Panayidou, Klea; Gsteiger, Sandro; Kilcher, Gablu; Carreras, Máximo; Efthimiou, Orestis; Debray, Thomas P. A.; Trelle, Sven; Hummel, Noemi

    2016-01-01

    The performance of a drug in a clinical trial setting often does not reflect its effect in daily clinical practice. In this third of three reviews, we examine the applications that have been used in the literature to predict real‐world effectiveness from randomized controlled trial efficacy data. We searched MEDLINE, EMBASE from inception to March 2014, the Cochrane Methodology Register, and websites of key journals and organisations and reference lists. We extracted data on the type of model and predictions, data sources, validation and sensitivity analyses, disease area and software. We identified 12 articles in which four approaches were used: multi‐state models, discrete event simulation models, physiology‐based models and survival and generalized linear models. Studies predicted outcomes over longer time periods in different patient populations, including patients with lower levels of adherence or persistence to treatment or examined doses not tested in trials. Eight studies included individual patient data. Seven examined cardiovascular and metabolic diseases and three neurological conditions. Most studies included sensitivity analyses, but external validation was performed in only three studies. We conclude that mathematical modelling to predict real‐world effectiveness of drug interventions is not widely used at present and not well validated. © 2016 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd. PMID:27529762

  4. Improving Computational Efficiency of Model Predictive Control Genetic Algorithms for Real-Time Decision Support

    NASA Astrophysics Data System (ADS)

    Minsker, B. S.; Zimmer, A. L.; Ostfeld, A.; Schmidt, A.

    2014-12-01

    Enabling real-time decision support, particularly under conditions of uncertainty, requires computationally efficient algorithms that can rapidly generate recommendations. In this paper, a suite of model predictive control (MPC) genetic algorithms are developed and tested offline to explore their value for reducing CSOs during real-time use in a deep-tunnel sewer system. MPC approaches include the micro-GA, the probability-based compact GA, and domain-specific GA methods that reduce the number of decision variable values analyzed within the sewer hydraulic model, thus reducing algorithm search space. Minimum fitness and constraint values achieved by all GA approaches, as well as computational times required to reach the minimum values, are compared to large population sizes with long convergence times. Optimization results for a subset of the Chicago combined sewer system indicate that genetic algorithm variations with coarse decision variable representation, eventually transitioning to the entire range of decision variable values, are most efficient at addressing the CSO control problem. Although diversity-enhancing micro-GAs evaluate a larger search space and exhibit shorter convergence times, these representations do not reach minimum fitness and constraint values. The domain-specific GAs prove to be the most efficient and are used to test CSO sensitivity to energy costs, CSO penalties, and pressurization constraint values. The results show that CSO volumes are highly dependent on the tunnel pressurization constraint, with reductions of 13% to 77% possible with less conservative operational strategies. Because current management practices may not account for varying costs at CSO locations and electricity rate changes in the summer and winter, the sensitivity of the results is evaluated for variable seasonal and diurnal CSO penalty costs and electricity-related system maintenance costs, as well as different sluice gate constraint levels. These findings indicate

  5. Sequence and analysis of the gene for bacteriophage T3 RNA polymerase.

    PubMed Central

    McGraw, N J; Bailey, J N; Cleaves, G R; Dembinski, D R; Gocke, C R; Joliffe, L K; MacWright, R S; McAllister, W T

    1985-01-01

    The RNA polymerases encoded by bacteriophages T3 and T7 have similar structures, but exhibit nearly exclusive template specificities. We have determined the nucleotide sequence of the region of T3 DNA that encodes the T3 RNA polymerase (the gene 1.0 region), and have compared this sequence with the corresponding region of T7 DNA. The predicted amino acid sequence of the T3 RNA polymerase exhibits very few changes when compared to the T7 enzyme (82% of the residues are identical). Significant differences appear to cluster in three distinct regions in the amino-terminal half of the protein. Analysis of the data from both enzymes suggests features that may be important for polymerase function. In particular, a region that differs between the T3 and T7 enzymes exhibits significant homology to the bi-helical domain that is common to many sequence-specific DNA binding proteins. The region that flanks the structural gene contains a number of regulatory elements including: a promoter for the E. coli RNA polymerase, a potential processing site for RNase III and a promoter for the T3 polymerase. The promoter for the T3 RNA polymerase is located only 12 base pairs distal to the stop codon for the structural gene. PMID:3903658

  6. Collaborative Science: Human Sensor Networks for Real-time Natural Disaster Prediction

    NASA Astrophysics Data System (ADS)

    Halem, M.; Yesha, Y.; Aulov, O.; Martineau, J.; Brown, S.; Conte, T.; CenterHybrid Multicore Productivity Research

    2010-12-01

    We have implemented a ‘Human Sensor Network’ as a real time collaborative science data observing system by collecting and integrating the vast untapped information potential of digital social media data sources occurring during the oil spill situation arising from the Macondo well in the Gulf of Mexico. We collected, and archived blogs, Twitter status updates (aka tweets), photographs posted to Flicker, and videos posted to YouTube related to the Gulf oil spill and processed the meta data, text, and photos to extract quantitative physical data such as locations and estimates of the severity and dispersion of oil being collected on the beaches and marshes, frequencies of observations of tar ball sightings, correlations of sightings from different media, numbers of dead or distressed animals, trends, etc. These data were then introduced into the NOAA operational Gnome oil spill predictive model as time dependent boundary conditions employing a 2-D variational data assimilation scheme. The three participating institutions employed a distributed cloud computing system for the processing and model executions. In this presentation, we conducted preliminary forecast impact tests of the Gnome model with and without the use of social media data using a 2-D variational data assimilation technique. The 2-D VAR is used to adjust the state variables of the model by recursively minimizing the differences between oil spill predictions reaching locations across the entire coastlines of the Gulf of Mexico and the estimated positions of oil derived from analyzed social media data. Ensemble forecasts will be performed to provide estimates of the rates of oil and surface oil distributions emanating from the Deepwater Horizon. We display the derived predictions from the photos and animations from Flicker, YouTube, and extracted content from tweets and blogs in a dynamic representation on very large tiled walls of LCDs at the UCSD Cal IT2 visualization facility. We describe the

  7. Real-time Seismic Amplitude Measurement (RSAM): a volcano monitoring and prediction tool

    USGS Publications Warehouse

    Endo, E.T.; Murray, T.

    1991-01-01

    Seismicity is one of the most commonly monitored phenomena used to determine the state of a volcano and for the prediction of volcanic eruptions. Although several real-time earthquake-detection and data acquisition systems exist, few continuously measure seismic amplitude in circumstances where individual events are difficult to recognize or where volcanic tremor is prevalent. Analog seismic records provide a quick visual overview of activity; however, continuous rapid quantitative analysis to define the intensity of seismic activity for the purpose of predicing volcanic eruptions is not always possible because of clipping that results from the limited dynamic range of analog recorders. At the Cascades Volcano Observatory, an inexpensive 8-bit analog-to-digital system controlled by a laptop computer is used to provide 1-min average-amplitude information from eight telemetered seismic stations. The absolute voltage level for each station is digitized, averaged, and appended in near real-time to a data file on a multiuser computer system. Raw realtime seismic amplitude measurement (RSAM) data or transformed RSAM data are then plotted on a common time base with other available volcano-monitoring information such as tilt. Changes in earthquake activity associated with dome-building episodes, weather, and instrumental difficulties are recognized as distinct patterns in the RSAM data set. RSAM data for domebuilding episodes gradually develop into exponential increases that terminate just before the time of magma extrusion. Mount St. Helens crater earthquakes show up as isolated spikes on amplitude plots for crater seismic stations but seldom for more distant stations. Weather-related noise shows up as low-level, long-term disturbances on all seismic stations, regardless of distance from the volcano. Implemented in mid-1985, the RSAM system has proved valuable in providing up-to-date information on seismic activity for three Mount St. Helens eruptive episodes from 1985 to

  8. Real Time Numerical Weather Prediction by The Florida State University Superensemble

    NASA Astrophysics Data System (ADS)

    Ross, R. S.; Krishnamurti, T. N.

    2005-05-01

    The Florida State University (FSU) Superensemble technique as applied to real-time numerical weather prediction will be described. An evaluation of the skill of the Superensemble forecasts will be presented in comparison to the skills of the seven global numerical weather prediction models that comprise the Superensemble. Forecast variables that will be examined include lower and upper tropospheric wind fields, mean sea level pressure, mid-tropospheric geopotential height, and precipitation. Forecast skill will be evaluated globally, as well as for a number of sub-regions, such as the Indian monsoon region, North and South America, and the tropical North Atlantic Ocean. Statistical measures of forecast skill will include root mean square error, anomaly correlation, and systematic error for most variables. Forecast precipitation will also be evaluated by use of correlation, bias, and equitable threat scores. The skill scores will be presented the years 2000, 2001, and 2004. The FSU Superensemble technique uses multiple linear regression to derive coefficients from a comparison of member model forecasts to a benchmark analysis during a training period of 120 days. This procedure removes the bias of each individual forecast model and allows for an optimal linear combination of the individual model forecasts, which takes into account the relative skill of each model. The result is a forecast that has greater skill than the individual model forecasts and the ensemble mean forecast. The real-time FSU Superensemble forecasts are available on a website that shows the forecasts for the entire globe, as well as for ten sub-regions of the world. The website has links to the skill scores that are routinely updated, as well as to a number of journal articles that describe the FSU Superensemble technique in detail. Overall, the FSU Superensemble has been shown to be a valuable tool for significantly improving upon the numerical model forecasts emanating from the world

  9. 'It is Time to Prepare the Next patient' Real-Time Prediction of Procedure Duration in Laparoscopic Cholecystectomies.

    PubMed

    Guédon, Annetje C P; Paalvast, M; Meeuwsen, F C; Tax, D M J; van Dijke, A P; Wauben, L S G L; van der Elst, M; Dankelman, J; van den Dobbelsteen, J J

    2016-12-01

    Operating Room (OR) scheduling is crucial to allow efficient use of ORs. Currently, the predicted durations of surgical procedures are unreliable and the OR schedulers have to follow the progress of the procedures in order to update the daily planning accordingly. The OR schedulers often acquire the needed information through verbal communication with the OR staff, which causes undesired interruptions of the surgical process. The aim of this study was to develop a system that predicts in real-time the remaining procedure duration and to test this prediction system for reliability and usability in an OR. The prediction system was based on the activation pattern of one single piece of equipment, the electrosurgical device. The prediction system was tested during 21 laparoscopic cholecystectomies, in which the activation of the electrosurgical device was recorded and processed in real-time using pattern recognition methods. The remaining surgical procedure duration was estimated and the optimal timing to prepare the next patient for surgery was communicated to the OR staff. The mean absolute error was smaller for the prediction system (14 min) than for the OR staff (19 min). The OR staff doubted whether the prediction system could take all relevant factors into account but were positive about its potential to shorten waiting times for patients. The prediction system is a promising tool to automatically and objectively predict the remaining procedure duration, and thereby achieve optimal OR scheduling and streamline the patient flow from the nursing department to the OR.

  10. Development of an Automated, Real Time Surveillance Tool for Predicting Readmissions at a Community Hospital

    PubMed Central

    Gildersleeve, R.; Cooper, P.

    2013-01-01

    Background The Centers for Medicare and Medicaid Services’ Readmissions Reduction Program adjusts payments to hospitals based on 30-day readmission rates for patients with acute myocardial infarction, heart failure, and pneumonia. This holds hospitals accountable for a complex phenomenon about which there is little evidence regarding effective interventions. Further study may benefit from a method for efficiently and inexpensively identifying patients at risk of readmission. Several models have been developed to assess this risk, many of which may not translate to a U.S. community hospital setting. Objective To develop a real-time, automated tool to stratify risk of 30-day readmission at a semirural community hospital. Methods A derivation cohort was created by extracting demographic and clinical variables from the data repository for adult discharges from calendar year 2010. Multivariate logistic regression identified variables that were significantly associated with 30-day hospital readmission. Those variables were incorporated into a formula to produce a Risk of Readmission Score (RRS). A validation cohort from 2011 assessed the predictive value of the RRS. A SQL stored procedure was created to calculate the RRS for any patient and publish its value, along with an estimate of readmission risk and other factors, to a secure intranet site. Results Eleven variables were significantly associated with readmission in the multivariate analysis of each cohort. The RRS had an area under the receiver operating characteristic curve (c-statistic) of 0.74 (95% CI 0.73-0.75) in the derivation cohort and 0.70 (95% CI 0.69-0.71) in the validation cohort. Conclusion Clinical and administrative data available in a typical community hospital database can be used to create a validated, predictive scoring system that automatically assigns a probability of 30-day readmission to hospitalized patients. This does not require manual data extraction or manipulation and uses commonly

  11. Numerical shake prediction for Earthquake Early Warning: data assimilation, real-time shake-mapping, and simulation of wave propagation

    NASA Astrophysics Data System (ADS)

    Hoshiba, M.; Aoki, S.

    2014-12-01

    In many methods of the present Earthquake Early Warning (EEW) systems, hypocenter and magnitude are determined quickly and then strengths of ground motions are predicted. The 2011 Tohoku Earthquake (MW9.0), however, revealed some technical issues with the conventional methods: under-prediction due to the large extent of the fault rupture, and over-prediction due to confusion of the system by multiple aftershocks occurred simultaneously. To address these issues, a new concept is proposed for EEW: applying data assimilation technique, present wavefield is estimated precisely in real time (real-time shake mapping) and then future wavefield is predicted time-evolutionally using physical process of seismic wave propagation. Information of hypocenter location and magnitude are not required, which is basically different from the conventional method. In the proposed method, data assimilation technique is applied to estimate the current spatial distribution of wavefield, in which not only actual observation but also anticipated wavefield predicted from one time-step before are used. Real-time application of the data assimilation technique enables us to estimate wavefield in real time, which corresponds to real-time shake mapping. Once present situation is estimated precisely, we go forward to the prediction of future situation using simulation of wave propagation. The proposed method is applied to the 2011 Tohoku Earthquake (MW9.0) and the 2004 Mid-Niigata earthquake (Mw6.7). Future wavefield is precisely predicted, and the prediction is improved with shortening the lead time: for example, the error of 10 s prediction is smaller than that of 20 s, and that of 5 s is much smaller. By introducing this method, it becomes possible to predict ground motion precisely even for cases of the large extent of fault rupture and the multiple simultaneous earthquakes. The proposed method is based on a simulation of physical process from the precisely estimated present condition. This

  12. Application of a Rule-Based Approach in Real-Time Crash Risk Prediction Model Development Using Loop Detector Data.

    PubMed

    Pirdavani, Ali; De Pauw, Ellen; Brijs, Tom; Daniels, Stijn; Magis, Maarten; Bellemans, Tom; Wets, Geert

    2015-01-01

    There is a growing trend in development and application of real-time crash risk prediction models within dynamic safety management systems. These real-time crash risk prediction models are constructed by associating crash data with the real-time traffic surveillance data (e.g., collected by loop detectors). The main objective of this article is to develop a real-time risk model that will potentially be utilized within traffic management systems. This model aims to predict the likelihood of crash occurrence on motorways. In this study, the potential prediction variables are confined to traffic-related characteristics. Given that the dependent variable (i.e., traffic safety condition) is dichotomous (i.e., "no-crash" or "crash"), a rule-based approach is considered for model development. The performance of rule-based classifiers is further compared with the more conventional techniques like binary logistic regression and decision trees. The crash and traffic data used in this study were collected between June 2009 and December 2011 on a part of the E313 motorway in Belgium between Geel-East and Antwerp-East exits, on the direction toward Antwerp. The results of analysis show that several traffic flow characteristics such as traffic volume, average speed, and standard deviation of speed at the upstream loop detector station and the difference in average speed on upstream and downstream loop detector stations significantly contribute to the crash occurrence prediction. The final chosen classifier is able to predict 70% of crash occasions accurately, and it correctly predicts 90% of no-crash instances, indicating a 10% false alarm rate. The findings of this study can be used to predict the likelihood of crash occurrence on motorways within dynamic safety management systems.

  13. T3 expression by human thymocytes in culture.

    PubMed Central

    Aiello, F B; Musiani, P; Maggiano, N; Larocca, L M; Piantelli, M

    1985-01-01

    By panning procedures employing T6 and T3 monoclonal antibody, human thymocytes were fractionated into two subpopulations depleted of T6- or T3-positive (T6+, T3+) cells. Unfractionated thymocytes and T6- and T3-depleted subpopulations were separately cultured for 48 h in RPMI 1640 medium with 10% FCS or in HB 101 serum-free medium. Determining the phenotype of unfractionated thymocytes at various time intervals, a time-dependent increase of T3+ cells was observed. An inverse relationship was found between the percentage of T3+ cells and the T6 and peanut agglutinin (PNA) reactive thymocytes. When the surface antigen expression in the T3-depleted population (greater than 95% T6+ and PNA+ cells) was analysed, a strong increase of T3+ cells and a complementary reduction of T6+ and PNA+ cells was evidenced. During that time the surface phenotype of the T6-depleted population (greater than 80% T3+ cells) showed the same trend of differentiation, as the other thymocyte preparations. These results indicate that a conspicuous fraction of human thymocytes and particularly of those characterized by a cortical phenotype (PNA+ and T6+ cells), are able to express mature T-cell antigens when cultured in vitro in the absence of the thymic microenvironment influence. However, the in vitro acquisition of a mature phenotype is not accompanied by a parallel achievement of the capacity to respond to mitogens such as PHA or T3 monoclonal antibody. PMID:3876184

  14. Predictive transport simulations of real-time profile control in JET advanced tokamak plasmas

    NASA Astrophysics Data System (ADS)

    Tala, T.; Laborde, L.; Mazon, D.; Moreau, D.; Corrigan, G.; Crisanti, F.; Garbet, X.; Heading, D.; Joffrin, E.; Litaudon, X.; Parail, V.; Salmi, A.; EFDA-JET workprogramme, contributors to the

    2005-09-01

    Predictive, time-dependent transport simulations with a semi-empirical plasma model have been used in closed-loop simulations to control the q-profile and the strength and location of the internal transport barrier (ITB). Five transport equations (Te, Ti, q, ne, vΦ) are solved, and the power levels of lower hybrid current drive, NBI and ICRH are calculated in a feedback loop determined by the feedback controller matrix. The real-time control (RTC) technique and algorithms used in the transport simulations are identical to those implemented and used in JET experiments (Laborde L. et al 2005 Plasma Phys. Control. Fusion 47 155 and Moreau D. et al 2003 Nucl. Fusion 43 870). The closed-loop simulations with RTC demonstrate that varieties of q-profiles and pressure profiles in the ITB can be achieved and controlled simultaneously. The simulations also showed that with the same RTC technique as used in JET experiments, it is possible to sustain the q-profiles and pressure profiles close to their set-point profiles for longer than the current diffusion time. In addition, the importance of being able to handle the multiple time scales to control the location and strength of the ITB is pointed out. Several future improvements and perspectives of the RTC scheme are presented.

  15. The POLIMI forecasting chain for real time flood and drought predictions

    NASA Astrophysics Data System (ADS)

    Ceppi, Alessandro; Ravazzani, Giovanni; Corbari, Chiara; Mancini, Marco

    2016-04-01

    Nowadays coupling meteorological and hydrological models is recognized by scientific community as a necessary way to forecast extreme hydrological phenomena, in order to activate useful mitigation measurements and alert systems in advance. The development and implementation of a real-time forecasting chain with a hydro-meteorological operational alert procedure for flood and drought events is presented in this study. Different weather models are used to build the POLIMI operative chain: the probabilistic COSMO-LEPS model with 16 ensembles developed by ARPA-Emilia Romagna, the deterministic Bolam and Moloch models, developed by the Italian ISAC-CNR, and nine further simulations obtained by different runs of the WRF-ARW (3), WRF-NMM (2), ETA2012 (1) and the GFS (3), provided by the private Epson Meteo Center and Terraria companies. All the meteorological runs are then implemented with the rainfall-runoff physically-based distributed FEST-WB model, developed at Politecnico di Milano to obtain a multi-model approach system with hydrological ensemble forecasts in different areas of study over the Italian country. As far as concerning drought predictions, three test-beds are monitored: two in maize fields, one in the Puglia region (South of Italy), and another in the Po Valley area, (northern Italy), and one in a golf course in Milan city. The hydrological model was here calibrated and validated against measurements of latent heat flux and soil moisture acquired by an eddy-covariance station, TDR probes and remote sensing images. Regarding flood forecasts, two test-sites are chosen: the first one is the urban area northern Milan where three catchments (the Seveso, Olona, and Lambro River basins) are used to show how early warning systems are an effective complement to structural measures for flood control in Milan city which flooded frequently in the last 25 years, while the second test-site is the Idro Lake, located between the Lombardy and Trentino region where the

  16. Neural network-based real-time prediction of glucose in patients with insulin-dependent diabetes.

    PubMed

    Pappada, Scott M; Cameron, Brent D; Rosman, Paul M; Bourey, Raymond E; Papadimos, Thomas J; Olorunto, William; Borst, Marilyn J

    2011-02-01

    Continuous glucose monitoring (CGM) technologies report measurements of interstitial glucose concentration every 5 min. CGM technologies have the potential to be utilized for prediction of prospective glucose concentrations with subsequent optimization of glycemic control. This article outlines a feed-forward neural network model (NNM) utilized for real-time prediction of glucose. A feed-forward NNM was designed for real-time prediction of glucose in patients with diabetes implementing a prediction horizon of 75 min. Inputs to the NNM included CGM values, insulin dosages, metered glucose values, nutritional intake, lifestyle, and emotional factors. Performance of the NNM was assessed in 10 patients not included in the model training set. The NNM had a root mean squared error of 43.9 mg/dL and a mean absolute difference percentage of 22.1. The NNM routinely overestimates hypoglycemic extremes, which can be attributed to the limited number of hypoglycemic reactions in the model training set. The model predicts 88.6% of normal glucose concentrations (> 70 and < 180 mg/dL), 72.6% of hyperglycemia (≥ 180 mg/dL), and 2.1% of hypoglycemia (≤ 70 mg/dL). Clarke Error Grid Analysis of model predictions indicated that 92.3% of predictions could be regarded as clinically acceptable and not leading to adverse therapeutic direction. Of these predicted values, 62.3% and 30.0% were located within Zones A and B, respectively, of the error grid. Real-time prediction of glucose via the proposed NNM may provide a means of intelligent therapeutic guidance and direction.

  17. Implementation of reactive and predictive real-time control strategies to optimize dry stormwater detention ponds

    NASA Astrophysics Data System (ADS)

    Gaborit, Étienne; Anctil, François; Vanrolleghem, Peter A.; Pelletier, Geneviève

    2013-04-01

    Dry detention ponds have been widely implemented in U.S.A (National Research Council, 1993) and Canada (Shammaa et al. 2002) to mitigate the impacts of urban runoff on receiving water bodies. The aim of such structures is to allow a temporary retention of the water during rainfall events, decreasing runoff velocities and volumes (by infiltration in the pond) as well as providing some water quality improvement from sedimentation. The management of dry detention ponds currently relies on static control through a fixed pre-designed limitation of their maximum outflow (Middleton and Barrett 2008), for example via a proper choice of their outlet pipe diameter. Because these ponds are designed for large storms, typically 1- or 2-hour duration rainfall events with return periods comprised between 5 and 100 years, one of their main drawbacks is that they generally offer almost no retention for smaller rainfall events (Middleton and Barrett 2008), which are by definition much more common. Real-Time Control (RTC) has a high potential for optimizing retention time (Marsalek 2005) because it allows adopting operating strategies that are flexible and hence more suitable to the prevailing fluctuating conditions than static control. For dry ponds, this would basically imply adapting the outlet opening percentage to maximize water retention time, while being able to open it completely for severe storms. This study developed several enhanced RTC scenarios of a dry detention pond located at the outlet of a small urban catchment near Québec City, Canada, following the previous work of Muschalla et al. (2009). The catchment's runoff quantity and TSS concentration were simulated by a SWMM5 model with an improved wash-off formulation. The control procedures rely on rainfall detection and measures of the pond's water height for the reactive schemes, and on rainfall forecasts in addition to these variables for the predictive schemes. The automatic reactive control schemes implemented

  18. Linearized Aeroelastic Solver Applied to the Flutter Prediction of Real Configurations

    NASA Technical Reports Server (NTRS)

    Reddy, Tondapu S.; Bakhle, Milind A.

    2004-01-01

    A fast-running unsteady aerodynamics code, LINFLUX, was previously developed for predicting turbomachinery flutter. This linearized code, based on a frequency domain method, models the effects of steady blade loading through a nonlinear steady flow field. The LINFLUX code, which is 6 to 7 times faster than the corresponding nonlinear time domain code, is suitable for use in the initial design phase. Earlier, this code was verified through application to a research fan, and it was shown that the predictions of work per cycle and flutter compared well with those from a nonlinear time-marching aeroelastic code, TURBO-AE. Now, the LINFLUX code has been applied to real configurations: fans developed under the Energy Efficient Engine (E-cubed) Program and the Quiet Aircraft Technology (QAT) project. The LINFLUX code starts with a steady nonlinear aerodynamic flow field and solves the unsteady linearized Euler equations to calculate the unsteady aerodynamic forces on the turbomachinery blades. First, a steady aerodynamic solution is computed for given operating conditions using the nonlinear unsteady aerodynamic code TURBO-AE. A blade vibration analysis is done to determine the frequencies and mode shapes of the vibrating blades, and an interface code is used to convert the steady aerodynamic solution to a form required by LINFLUX. A preprocessor is used to interpolate the mode shapes from the structural dynamics mesh onto the computational fluid dynamics mesh. Then, LINFLUX is used to calculate the unsteady aerodynamic pressure distribution for a given vibration mode, frequency, and interblade phase angle. Finally, a post-processor uses the unsteady pressures to calculate the generalized aerodynamic forces, eigenvalues, an esponse amplitudes. The eigenvalues determine the flutter frequency and damping. Results of flutter calculations from the LINFLUX code are presented for (1) the E-cubed fan developed under the E-cubed program and (2) the Quiet High Speed Fan (QHSF

  19. Evaluation of the AIRS near-real-time channel selection for application to numerical weather prediction

    NASA Astrophysics Data System (ADS)

    Fourrié, Nadia; Thépaut, Jean-Noël

    2003-07-01

    The Atmospheric Infrared Sounder (AIRS) on board the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Aqua satellite provides 2378 channels for each field of view of the instrument. As it is neither feasible nor efficient to assimilate all the channels in a numerical weather-prediction system, a policy of channel selection has to be designed in this context. This paper attempts to assess the optimality of the selection of the AIRS radiance channels that are made available to the scientific community in near real time (hereafter called AIRS NRT) by the National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite Data and Information Service. This assessment is done by comparing this channel selection with a method preserving the information content of the instrument, the so-called 'global' method. It turns out that although the selected channels are different and the information content as measured by the entropy reduction (ER) and the degrees of freedom for signal (DFS) is slightly smaller for the AIRS NRT channel set than for the 'global' set, both channel selections give similar results in terms of analysis error for temperature, humidity and ozone. The robustness of the results is then evaluated by varying the range of input parameters to the channel-selection scheme, in particular the atmospheric training dataset on which the channel selection is based, and the background-error covariance matrix. It is found that the performance of the 'global' channel selection is sensitive to the training dataset, while the AIRS NRT channel selection remains robust, even, to some extent, for the retrieval of key analysis-error structures. Altogether, the 'manually selected' AIRS NRT channels provide a good compromise between robustness and quality.

  20. Intraoperative Real-time Cochlear Response Telemetry Predicts Hearing Preservation in Cochlear Implantation.

    PubMed

    Campbell, Luke; Kaicer, Arielle; Sly, David; Iseli, Claire; Wei, Benjamin; Briggs, Robert; O'Leary, Stephen

    2016-04-01

    To monitor cochlear function during cochlear implantation and determine correlations with postoperative acoustic hearing. Cochlear response telemetry measures cochlear function directly from cochlear implant electrodes. We have adapted this system to provide real-time cochlear response telemetry (RT-CRT) monitoring of a patient's acoustic hearing as the cochlear implant electrode array is inserted. Eighteen subjects (1 child and 17 adults) with sloping high frequency hearing loss were implanted with Cochlear Ltd slim straight arrays (CI422/CI522). Tone bursts (500 Hz, 100-110 dB) were presented at 14 Hz continuously during the array insertion. RT-CRT amplitudes were correlated with surgical manoeuvres recorded on the video from the operating microscope and with postoperative pure tone audiograms. Despite an excellent overall rate of complete or partial hearing preservation (79%), RT-CRT identified that in 47% of these implantations there was transient or permanent reduction in the amplitude of the cochlear microphonic (CM). Patients with a preserved CM at the end of insertion had on average 15 dB better low-frequency hearing preservation. The CM amplitude was most vulnerable during the last few millimeters of insertion or when inadvertent movement of the array occurred after full insertion. Physical contact/elevation of the basilar membrane is hypothesized as a likely mechanism of hearing loss rather than overt physical trauma. RT-CRT can be used to predict early postoperative hearing loss and to potentially refine surgical technique. In the future, feedback of RT-CRT may prove to be a valuable tool for maximizing preservation of residual hearing or providing feedback on electrode contact with the basilar membrane.

  1. Prediction of the intelligibility for speech in real-life background noises for subjects with normal hearing.

    PubMed

    Rhebergen, Koenraad S; Versfeld, Niek J; Dreschler, Wouter A

    2008-04-01

    The speech reception threshold (SRT) traditionally is measured in stationary noise that has the long-term average speech spectrum of the target speech. However, in real life the instantaneous spectrum of the background noise is likely to be different from the stationary long-term average speech spectrum noise. To gain more insight into the effect of real-life background noises on speech intelligibility, the SRT of listeners with normal hearing was measured in a set of noises that varied in both the spectral and the temporal domain. This article investigates the ability of the extended speech intelligibility index (ESII), proposed by Rhebergen et al. to account for SRTs in these real-life background noises. SRTs in noise were measured in 12 subjects with normal hearing. Interfering noises consisted of a variety of real-life noises, selected from a database, and chosen on the basis of their spectrotemporal differences. Measured SRTs were converted to ESII values and compared. Ideally, at threshold, ESII values should be the same, because the ESII represents the amount of speech information available to the listener. SRTs ranged from -6 dB SNR (in stationary noise) to -21 dB SNR (in machine gun noise). Conversion to ESII values resulted in an average value of 0.34, with a standard deviation of 0.06. SRT predictions with the ESII model were better than those obtained with the conventional SII (ANSI 53.5-1997) model. In case of interfering speech, the ESII model predictions were poorer, because additional, nonenergetic (informational) masking is thought to occur. For the present set of masking noises, being representative for a variety of real-life noises, the ESII model of Rhebergen et al. is able to predict the SRTs of subjects with normal hearing with reasonable accuracy. It may be concluded that the ESII model can provide valuable predictions for the speech intelligibility in some everyday situations.

  2. Low T3 syndrome and long-term mortality in chronic hemodialysis patients

    PubMed Central

    Fragidis, Stylianos; Sombolos, Konstantinos; Thodis, Elias; Panagoutsos, Stylianos; Mourvati, Euthymia; Pikilidou, Maria; Papagianni, Aikaterini; Pasadakis, Ploumis; Vargemezis, Vasilios

    2015-01-01

    AIM: To investigate the predictive value of low freeT3 for long-term mortality in chronic hemodialysis (HD) patients and explore a possible causative role of chronic inflammation. METHODS: One hundred fourteen HD patients (84 males) consecutively entered the study and were assessed for thyroid function and two established markers of inflammation, high sensitivity C-reactive protein (hsCRP) and interleukin-6 (IL-6). Monthly blood samples were obtained from all patients for three consecutive months during the observation period for evaluation of thyroid function and measurement of inflammatory markers. The patients were then divided in two groups based on the cut-off value of 1.8 pg/mL for mean plasma freeT3, and were prospectively studied for a mean of 50.3 ± 30.8 mo regarding cumulative survival. The prognostic power of low serum fT3 levels for mortality was assessed using the Kaplan-Meier method and univariate and multivariate regression analysis. RESULTS: Kaplan-Meier survival curve showed a negative predictive power for low freeT3. In Cox regression analysis low freeT3 remained a significant predictor of mortality after adjustment for age, diabetes mellitus, hypertension, hsCRP, serum creatinine and albumin. Regarding the possible association with inflammation, freeT3 was correlated with hsCRP, but not IL-6, and only at the first month of the study. CONCLUSION: In chronic hemodialysis patients, low plasma freeT3 is a significant predictor of all-cause mortality. Further studies are required to identify the underlying mechanisms of this association. PMID:26167466

  3. Effect of T3 hormone on neural differentiation of human adipose derived stem cells.

    PubMed

    Razavi, Shahnaz; Mostafavi, Fatemeh Sadat; Mardani, Mohammad; Zarkesh Esfahani, Hamid; Kazemi, Mohammad; Esfandiari, Ebrahim

    2014-12-01

    Human adult stem cells, which are capable of self-renewal and differentiation into other cell types, can be isolated from various tissues. There are no ethical and rejection problems as in the case of embryonic stem cells, so they are a promising source for cell therapy. The human body contains a great amount of adipose tissue that contains high numbers of mesenchymal stem cells. Human adipose-derived stem cells (hADSCs) could be easily induced to form neuron-like cells, and because of its availability and abundance, we can use it for clinical cell therapy. On the other hand, T3 hormone as a known neurotropic factor has important impressions on the nervous system. The aim of this study was to explore the effects of T3 treatment on neural differentiation of hADSCs. ADSCs were harvested from human adipose tissue, after neurosphere formation, and during final differentiation, treatment with T3 was performed. Immunocytochemistry, real-time RT-PCR, Western blotting techniques were used for detection of nestin, MAP2, and GFAP markers in order to confirm the effects of T3 on neural differentiation of hADSCs. Our results showed an increase in the number of glial cells but reduction in neuronal cells number fallowing T3 treatment.

  4. [The effect of triiodothyronine (T3) and reverse triiodothyronine (rT3) on canine hemorrhagic shock].

    PubMed

    Shigematsu, H; Shatney, C H

    1988-10-01

    The euthyroid sick ("low T3") syndrome occurs in circulatory collapse and could influence survival. To evaluate the role of T3 and rT3 in shock, 36 mongrel dogs were subjected to hemorrhagic shock. In 13 dogs 15 micrograms/kg of T3 was given after 60 min of hypotension and 15 micrograms/kg of rT3 was administered IV 30 min before hemorrhage in 10 dogs. An equal volume of saline was injected in 13 dogs for control study. These dogs were bled rapidly into a reservoir to a mean arterial pressure (MAP) of 40 mmHg. After 60 min of hypotension the reservoir line was clamped for 30 min. The shed blood was then reinfused over 30 min. T3 administration caused significant increases during the clamped period in cardiac output, stroke volume, MAP, right and left ventricular stroke work and systemic vascular resistance, with a decrease in pulmonary vascular resistance (PVR). In the group receiving rT3 the only significant hemodynamic-metabolic differences were PVR and mean arterial pH. In the control group, 6 of 13 dogs died, whereas 9 of 10 dogs given rT3 died (p less than 0.03) and only one of 13 T3 dogs died (p less than 0.05). This study strongly suggests that T3 improves survival by acting on cardiovascular receptors or via the hypothalamic-pituitary-thyroid axis and that exogeneous rT3 is detrimental during the stress of shock and may play a biologically causative role in the sick euthyroid syndrome.

  5. Earthquake ground motion prediction for real sedimentary basins: which numerical schemes are applicable?

    NASA Astrophysics Data System (ADS)

    Moczo, P.; Kristek, J.; Galis, M.; Pazak, P.

    2009-12-01

    Numerical prediction of earthquake ground motion in sedimentary basins and valleys often has to account for P-wave to S-wave speed ratios (Vp/Vs) as large as 5 and even larger, mainly in sediments below groundwater level. The ratio can attain values larger than 10 in unconsolidated sediments (e.g. in Ciudad de México). In a process of developing 3D optimally-accurate finite-difference schemes we encountered a serious problem with accuracy in media with large Vp/Vs ratio. This led us to investigate the very fundamental reasons for the inaccuracy. In order to identify the very basic inherent aspects of the numerical schemes responsible for their behavior with varying Vp/Vs ratio, we restricted to the most basic 2nd-order 2D numerical schemes on a uniform grid in a homogeneous medium. Although basic in the specified sense, the schemes comprise the decisive features for accuracy of wide class of numerical schemes. We investigated 6 numerical schemes: finite-difference_displacement_conventional grid (FD_D_CG) finite-element_Lobatto integration (FE_L) finite-element_Gauss integration (FE_G) finite-difference_displacement-stress_partly-staggered grid (FD_DS_PSG) finite-difference_displacement-stress_staggered grid (FD_DS_SG) finite-difference_velocity-stress_staggered grid (FD_VS_SG) We defined and calculated local errors of the schemes in amplitude and polarization. Because different schemes use different time steps, they need different numbers of time levels to calculate solution for a desired time window. Therefore, we normalized errors for a unit time. The normalization allowed for a direct comparison of errors of different schemes. Extensive numerical calculations for wide ranges of values of the Vp/Vs ratio, spatial sampling ratio, stability ratio, and entire range of directions of propagation with respect to the spatial grid led to interesting and surprising findings. Accuracy of FD_D_CG, FE_L and FE_G strongly depends on Vp/Vs ratio. The schemes are not

  6. Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression.

    PubMed

    Bukhari, W; Hong, S-M

    2015-01-07

    Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR(+), implements a gating function without pre-specifying a particular region of the patient's breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR(+) algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR(+) implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR(+) in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR(+). The experimental results show that the EKF-GPR(+) algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR(+) reduces the patient-wise RMS error to 37%, 39% and

  7. Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression

    NASA Astrophysics Data System (ADS)

    Bukhari, W.; Hong, S.-M.

    2015-01-01

    Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR+, implements a gating function without pre-specifying a particular region of the patient’s breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR+ algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR+ implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR+ in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR+. The experimental results show that the EKF-GPR+ algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR+ reduces the patient-wise RMS error to 37%, 39% and 42% in

  8. Glucagon administration induces lowering of serum T3 and rise in reverse T3 in euthyroid healthy subjects.

    PubMed

    Kabadi, U M; Premachandra, B N

    1985-12-01

    Euthyroid sick syndrome is characterized by low serum T3 and raised reverse T3 (rT3). Most of the states with this syndrome are also documented to manifest hyperglucagonemia. Furthermore, several recent studies have suggested that glucagon may play a role in T4 monodeiodination in some of these states such as starvation and uncontrolled diabetes mellitus. Therefore, hyperglucagonemia was induced by intravenous glucagon administration in euthyroid healthy volunteers and thyroid hormone levels were determined at frequent intervals up to six hours. Plasma glucose and insulin rose promptly on glucagon administration, thus establishing the physiologic effect of glucagon. Serum T4, free T4, T3 resin uptake, and TSH concentrations remained unaltered throughout the study period. Serum T3 declined to a significantly low level (P less than 0.05) between 60-90 minutes. Serum rT3 rose significantly (P less than 0.05) by four hours and the rise was progressive till the end of the study period. Therefore, these results suggest that hyperglucagonemia may be one of the factors responsible for lowering of T3 and a rise in rT3 in euthyroid sick syndrome.

  9. Integrating Real-time and Manual Monitored Soil Moisture Data to Predict Hillslope Soil Moisture Variations with High Temporal Resolutions

    NASA Astrophysics Data System (ADS)

    Zhu, Qing; Lv, Ligang; Zhou, Zhiwen; Liao, Kaihua

    2016-04-01

    Spatial-temporal variability of soil moisture 15 has been remaining an challenge to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time soil moisture monitoring methods. This restricted the comprehensive and intensive examination of soil moisture dynamics. In this study, we aimed to integrate the manual and real-time monitored soil moisture to depict the hillslope dynamics of soil moisture with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear models (support vector machines-SVM) were used to predict soil moisture at 38 manual sites (collected 1-2 times per month) with soil moisture automatically collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each manual site, optimal soil moisture prediction model of this site was then determined. Results show that soil moisture at these 38 manual sites can be reliably predicted (root mean square errors<0.035 m3 m-3) using this approach. Absence or occurrence of subsurface flow can probably influence the choosing of SMLR or SVM in the prediction, respectively. Depth to bedrock, elevation, topographic wetness index, profile curvature, and relative difference of soil moisture and its standard deviation influenced the selection of prediction model since they related to the dynamics of soil water distribution and movement. By using this approach, hillslope soil moisture spatial distributions at un-sampled times and dates were predicted after a typical rainfall event. Missing information of hillslope soil moisture dynamics was then acquired successfully. This can be benefit for determining the hot spots and moments of soil water movement, as well as designing the proper soil moisture monitoring plan at the field scale.

  10. Real-time random delay compensation with prediction-based digital redesign.

    PubMed

    Zhang, Yongpeng; Cofie, Penrose; Ajuzie, Augustine N; Zhang, Jian; Akujuobi, Cajetan M

    2011-04-01

    Today's technological demands require challenging control solutions such as real-time applications of Networked Control System (NCS). However, due to communication protocol and shared data bus, NCS experiences uncertain and unpredictable time delays in both input and output channels. These delays cause asynchronization between the controller and the plant thereby degrading the performance of closed-loop control systems. To address this problem, this paper proposes to utilize digital redesign technique to provide real-time random delay compensation.

  11. Efficiency of a real time flood forecasting system in the Alps and in the Apennines: deterministic versus ensemble predictions

    NASA Astrophysics Data System (ADS)

    Grossi, G.

    2009-04-01

    Real time hydrological forecasting is still a challenging task for most of the Italian territory, especially in mountain areas where both the topography and the meteorological forcing are affected by a strong spatial variability. Nevertheless there is an increasing request to provide some clues for the development of efficient real time flood forecasting systems, for warning population as well as for water management purposes. In this perspective the efficiency of a real time forecasting system needs to be investigated, with particular care to the uncertainty of the provided prediction and to how this prediction will be handled by water resources managers and land protection services. To this aim a real time flood forecasting system using both deterministic and ensemble meteorological predictions has been implemented at University of Brescia and applied to an Alpine area (the Toce River - Piemonte Region) and to an Apennine area (the Taro River - Emilia Romagna Region). The Map D- Phase experiment (autumn 2007) was a good test for the implemented system: daily rainfall fields provided by high resolution deterministic limited area meteorological models and esemble rainfall predictions provided by coarser resolution meteorological models could be used to force a hydrological model and produce either a single deterministic or an esemble of flood forecats. Namely only minor flood events occurred in the Alpine area in autumn 2007, while one major flood event affected the Taro river at the end of November 2007. Focusing on this major event the potentials of the forecasting system was tested and evaluated with reference also to the geographical and climatic characteristics of the investigated area.

  12. Comparison of only T3 and T3-T4 sympathectomy for axillary hyperhidrosis regarding treatment effect and compensatory sweating.

    PubMed

    Yuncu, Gökhan; Turk, Figen; Ozturk, Gökhan; Atinkaya, Cansel

    2013-08-01

    Patients diagnosed with axillary hyperhidrosis can face psychosocial issues that can ultimately hinder their quality of life both privately and socially. The routine treatment for axillary hyperhidrosis is T3-T4 sympathectomy, but compensatory sweating is a serious side effect that is commonly seen with this approach. This study was designed to evaluate whether a T3 sympathectomy was effective for the treatment of axillary hyperhidrosis and whether this treatment led to less compensatory sweating than T3-T4 sympathectomies among our 60-patient population. One hundred and twenty endoscopic thoracic sympathectomies were performed on 60 patients who had axillary hyperhidrosis. The sympathectomies were accomplished by means of a single-lumen endotracheal tube and a single port. The axillary hyperhidrosis patients were randomly divided into two groups with 17 patients in Group 1 undergoing T3-T4 sympathectomies and 43 in Group 2 undergoing only T3 sympathectomies. We analysed the data associated with the resolution of axillary hyperhidrosis, the degree of patient satisfaction with the surgical outcome and the quality of life in parallel with compensatory sweating after the procedure as reported by the patient and confirmed by the examiner. Moreover, the results were compared statistically. No statistically significant difference was observed between the groups based on age (P=0.56), gender (P=0.81), duration of the surgery (P=0.35) or postoperative satisfaction levels (P=0.45). However, the incidence and degree of compensatory sweating were lower in the T3 group than the T3-T4 group at the 1-year follow-up (P=0.008). T3 sympathectomy was as effective as T3-T4 sympathectomy for the treatment of axillary hyperhidrosis based on the patients' reported postoperative satisfaction, and the T3 group demonstrated lower compensatory sweating at the 1-year follow-up.

  13. Low T3 syndrome is a strong predictor of poor outcomes in patients with community-acquired pneumonia

    PubMed Central

    Liu, Jinliang; Wu, Xuejie; Lu, Fang; Zhao, Lifang; Shi, Lingxian; Xu, Feng

    2016-01-01

    Low T3 syndrome was previously reported to be linked to poor clinical outcomes in critically ill patients. The aim of this study was to evaluate the predictive power of low T3 syndrome for clinical outcomes in patients with community-acquired pneumonia (CAP). Data for 503 patients were analyzed retrospectively, and the primary end point was 30-day mortality. The intensive care unit (ICU) admission rate and 30-day mortality were 8.3% and 6.4% respectively. The prevalence of low T3 syndrome differed significantly between survivors and nonsurvivors (29.1% vs 71.9%, P < 0.001), and low T3 syndrome was associated with a remarkable increased risk of 30-day mortality and ICU admission in patients with severe CAP. Multivariate logistic regression analysis produced an odds ratio of 2.96 (95% CI 1.14–7.76, P = 0.025) for 30-day mortality in CAP patients with low T3 syndrome. Survival analysis revealed that the survival rate among CAP patients with low T3 syndrome was lower than that in the control group (P < 0.01). Adding low T3 syndrome to the PSI and CURB-65 significantly increased the areas under the ROC curves for predicting ICU admission and 30-day mortality. In conclusion, low T3 syndrome is an independent risk factor for 30-day mortality in CAP patients. PMID:26928863

  14. Low T3 syndrome is a strong predictor of poor outcomes in patients with community-acquired pneumonia.

    PubMed

    Liu, Jinliang; Wu, Xuejie; Lu, Fang; Zhao, Lifang; Shi, Lingxian; Xu, Feng

    2016-03-01

    Low T3 syndrome was previously reported to be linked to poor clinical outcomes in critically ill patients. The aim of this study was to evaluate the predictive power of low T3 syndrome for clinical outcomes in patients with community-acquired pneumonia (CAP). Data for 503 patients were analyzed retrospectively, and the primary end point was 30-day mortality. The intensive care unit (ICU) admission rate and 30-day mortality were 8.3% and 6.4% respectively. The prevalence of low T3 syndrome differed significantly between survivors and nonsurvivors (29.1% vs 71.9%, P < 0.001), and low T3 syndrome was associated with a remarkable increased risk of 30-day mortality and ICU admission in patients with severe CAP. Multivariate logistic regression analysis produced an odds ratio of 2.96 (95% CI 1.14-7.76, P = 0.025) for 30-day mortality in CAP patients with low T3 syndrome. Survival analysis revealed that the survival rate among CAP patients with low T3 syndrome was lower than that in the control group (P < 0.01). Adding low T3 syndrome to the PSI and CURB-65 significantly increased the areas under the ROC curves for predicting ICU admission and 30-day mortality. In conclusion, low T3 syndrome is an independent risk factor for 30-day mortality in CAP patients.

  15. The effect of myostatin on proliferation and lipid accumulation in 3T3-L1 preadipocytes.

    PubMed

    Zhu, Hui Juan; Pan, Hui; Zhang, Xu Zhe; Li, Nai Shi; Wang, Lin Jie; Yang, Hong Bo; Gong, Feng Ying

    2015-06-01

    Myostatin is a critical negative regulator of skeletal muscle development, and has been reported to be involved in the progression of obesity and diabetes. In the present study, we explored the effects of myostatin on the proliferation and differentiation of 3T3-L1 preadipocytes by using 3-[4,5-dimethylthiazol-2-yl] 2,5-diphenyl tetrazolium bromide spectrophotometry, intracellular triglyceride (TG) assays, and real-time quantitative RT-PCR methods. The results indicated that recombinant myostatin significantly promoted the proliferation of 3T3-L1 preadipocytes and the expression of proliferation-related genes, including Cyclin B2, Cyclin D1, Cyclin E1, Pcna, and c-Myc, and IGF1 levels in the medium of 3T3-L1 were notably upregulated by 35.2, 30.5, 20.5, 33.4, 51.2, and 179% respectively (all P<0.01) in myostatin-treated 3T3-L1 cells. Meanwhile, the intracellular lipid content of myostatin-treated cells was notably reduced as compared with the non-treated cells. Additionally, the mRNA levels of Pparγ, Cebpα, Gpdh, Dgat, Acs1, Atgl, and Hsl were significantly downregulated by 22-76% in fully differentiated myostatin-treated adipocytes. Finally, myostatin regulated the mRNA levels and secretion of adipokines, including Adiponectin, Resistin, Visfatin, and plasminogen activator inhibitor-1 (PAI-1) in 3T3-L1 adipocytes (all P<0.001). Above all, myostatin promoted 3T3-L1 proliferation by increasing the expression of cell-proliferation-related genes and by stimulating IGF1 secretion. Myostatin inhibited 3T3-L1 adipocyte differentiation by suppressing Pparγ and Cebpα expression, which consequently deceased lipid accumulation in 3T3-L1 cells by inhibiting the expression of critical lipogenic enzymes and by promoting the expression of lipolytic enzymes. Finally, myostatin modulated the expression and secretion of adipokines in fully differentiated 3T3-L1 adipocytes. © 2015 Society for Endocrinology.

  16. Forecasting space weather: Using ACE data to provide real-time predictions of high-intensity energetic storm particle events

    NASA Astrophysics Data System (ADS)

    Wagstaff, K.; Ho, G. C.; Vandegriff, J.; Plauger, J.

    2003-04-01

    Geo-effective interplanetary (IP) shocks are often accompanied by Energetic Storm Particle (ESP) events, during which the intensity of charged particles can increase by several orders of magnitude. Such high intensities of incident ions present a radiation hazard to astronauts and electronics in Earth orbit. Observations by NASA's Advanced Composition Explorer (ACE) spacecraft indicate that these events are usually preceded by characteristic signatures in the ion intensities, thus providing an opportunity for predicting the events before they arrive. We have developed an algorithm that can forecast the arrival of ESP events. Using historical ion data from ACE, we trained an artificial neural network to detect the characteristic signals that warn of an impending event. The network predicts the time remaining until the maximum intensity is reached. We trained the network on 37 events, from 1997 to 2002, and tested it on a separate set of 18 events from the same time period. Initial performance of the network is very encouraging; the average uncertainty in predictions made 24 hours in advance is 9.4 hours, while the uncertainty improves to 4.9 hours when the event is 12 hours away. Recently, we have integrated our predictive algorithm in a system that uses real-time ACE data provided by the NOAA Space Environment Center. This system continually processes the latest ACE data and reports whether or not there is an impending ESP event. After detecting an event, our algorithm predicts the time remaining until the peak intensity occurs. For example, on November 25, 2002, our real-time system successfully detected an upcoming event and steadily produced predictions until the corresponding IP shock hit, at 9:45 p.m. on November 26, 2002. By providing a significant amount of lead-time, as well updated predictions every five minutes, this system can be a crucial source of information to mission planners, satellite operations controllers, and scientists.

  17. 6-gingerol inhibits rosiglitazone-induced adipogenesis in 3T3-L1 adipocytes.

    PubMed

    Tzeng, Thing-Fong; Chang, Chia Ju; Liu, I-Min

    2014-02-01

    We investigated the effects of 6-gingerol ((S)-5-hydroxy-1-(4-hydroxy-3-methoxyphenyl)-3-decanone) on the inhibition of rosiglitazone (RGZ)-induced adipogenesis in 3T3-L1 cells. The morphological changes were photographed based on staining lipid accumulation by Oil-Red O in RGZ (1 µmol/l)-treated 3T3-L1 cells without or with various concentrations of 6-gingerol on differentiation day 8. Quantitation of triglycerides content was performed in cells on day 8 after differentiation induction. Differentiated cells were lysed to detect mRNA and protein levels of adipocyte-specific transcription factors by real-time reverse transcription-polymerase chain reaction and Western blot analysis, respectively. 6-gingerol (50 µmol/l) effectively suppressed oil droplet accumulation and reduced the sizes of the droplets in RGZ-induced adipocyte differentiation in 3T3-L1 cells. The triglyceride accumulation induced by RGZ in differentiated 3T3-L1 cells was also reduced by 6-gingerol (50 µmol/l). Treatment of differentiated 3T3-L1 cells with 6-gingerol (50 µmol/l) antagonized RGZ-induced gene expression of peroxisome proliferator-activated receptor (PPAR)γ and CCAAT/enhancer-binding protein α. Additionally, the increased levels of mRNA and protein in adipocyte-specific fatty acid binding protein 4 and fatty acid synthase induced by RGZ in 3T3-L1 cells were decreased upon treatment with 6-gingerol. Our data suggests that 6-gingerol may be beneficial in obesity, by reducing adipogenesis partly through the down-regulating PPARγ activity. Copyright © 2013 John Wiley & Sons, Ltd.

  18. Improvement in cloud predictions using satellite data assimilation for real-time forecasting

    NASA Astrophysics Data System (ADS)

    Vellore, R.; Koracin, D.; Wetzel, M.

    2006-12-01

    The accuracy of quantitative forecasting of low-level operational cloud products such as the cloud top height, cloud top pressure and cloud thickness is rather low. Reliable forecasting of the low-level clouds (cloud top altitudes below 2-3 km) such as fog, stratus or stratocumulus is essential for aviation safety purposes. With the advent of an increased number of spectral channels and high-resolution imagers on the Geostationary Operational Environmental Satellite, cloud products can be diagnostically extracted and, furthermore, these cloud products can be used to modify the initial conditions for numerical weather prediction. Although operational methods are relatively successful in determining the cloud top altitudes for deep clouds and high clouds (usually above 5 km), there is no unique way of inferring the cloud top heights for low-level clouds due to their optical properties and low-level inversions. An algorithm has been developed in this study to classify the low-level cloud types using the brightness temperatures extracted from the GOES satellite visible and infrared channels. Cloud top temperatures above 8° C characterize low-level clouds. The brightness temperature differences between the window channel (11 ìm) and the shortwave infrared channel (4 ìm) are used to segregate the optically thin and thick clouds, and the relative humidity obtained from the surface stations is used to distinguish the fog or clouds formed by fog lifting. The infrared satellite imagery on 29 June 2006 is considered for this study with domain coverage of 400 x 400 km2 . The ground-truth observations were obtained from the surface weather station located at the Naval Air Station, Fallon (NASF), Nevada. Upon classification of low-level clouds in the satellite imagery, (a) the first step is to compute the cloud base temperature in the low-level cloudy pixels using the surface temperature and cloud base height obtained from the ceilometer measurements (at NASF) following a dry

  19. Prediction of the Recognition of Real Objects as a Function of Photometric and Geometric Characteristics

    DTIC Science & Technology

    1978-12-01

    54 10. Validity coefficients for Step 2 prediction models . 54 11. Validity coefficients for Step 3 prediction models . 55 12. Validity coefficients...for Step 4 prediction models . 55 13. Validity coefficients for Step 5 prediction models . 56 14. Analysis of variance of validity cuufficients ..... 58...S8 r 0 14a Tgt L . 55 0 15 Tgt W .60 0 16 Cross bqd -.41 38 17 Cross 25 .31 10 18 Cross tgt .25 13 19 Cross ov -.36 35 20a Rev bqd -.46 48 21a Rev 25

  20. The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope.

    PubMed

    Lin, Hsueh-Chun; Hong, Yao-Ming; Kan, Yao-Chiang

    2012-01-01

    The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.

  1. Defending plasma T3 is a biological priority

    PubMed Central

    Abdalla, Sherine M.; Bianco, Antonio C.

    2015-01-01

    Summary Triiodothyronine (T3), the active form of thyroid hormone is produced predominantly outside the thyroid parenchyma secondary to peripheral tissue deiodination of thyroxine (T4), with <20% being secreted directly from the thyroid. In healthy individuals, plasma T3 is regulated by the negative feedback loop of the hypothalamus–pituitary–thyroid axis and by homoeostatic changes in deiodinase expression. Therefore, with the exception of a minimal circadian rhythmicity, serum T3 levels are stable over long periods of time. Studies in rodents indicate that different levels of genetic disruption of the feedback mechanism and deiodinase system are met with increase in serum T4 and thyroid-stimulating hormone (TSH) levels, while serum T3 levels remain stable. These findings have focused attention on serum T3 levels in patients with thyroid disease, with important clinical implications affecting therapeutic goals and choice of therapy for patients with hypothyroidism. Although monotherapy with levothyroxine is the standard of care for hypothyroidism, not all patients normalize serum T3 levels with many advocating for combination therapy with levothyroxine and liothyronine. The latter could be relevant for a significant number of patients that remain symptomatic on monotherapy with levothyroxine, despite normalization of serum TSH levels. PMID:25040645

  2. Thyroid Hormone T3 Counteracts STZ Induced Diabetes in Mouse

    PubMed Central

    Madaro, Luca; Ranieri, Danilo; Lupoi, Lorenzo; Stigliano, Antonio; Torrisi, Maria Rosaria; Bouchè, Marina; Toscano, Vincenzo; Misiti, Silvia

    2011-01-01

    This study intended to demonstrate that the thyroid hormone T3 counteracts the onset of a Streptozotocin (STZ) induced diabetes in wild type mice. To test our hypothesis diabetes has been induced in Balb/c male mice by multiple low dose Streptozotocin injection; and a group of mice was contemporaneously injected with T3. After 48 h mice were tested for glucose tolerance test, insulin serum levels and then sacrified. Whole pancreata were utilized for morphological and biochemical analyses, while protein extracts and RNA were utilized for expression analyses of specific molecules. The results showed that islets from T3 treated mice were comparable to age- and sex-matched control, untreated mice in number, shape, dimension, consistency, ultrastructure, insulin and glucagon levels, Tunel positivity and caspases activation, while all the cited parameters and molecules were altered by STZ alone. The T3-induced pro survival effect was associated with a strong increase in phosphorylated Akt. Moreover, T3 administration prevented the STZ-dependent alterations in glucose blood level, both during fasting and after glucose challenge, as well as in insulin serum level. In conclusion we demonstrated that T3 could act as a protective factor against STZ induced diabetes. PMID:21637761

  3. Defending plasma T3 is a biological priority.

    PubMed

    Abdalla, Sherine M; Bianco, Antonio C

    2014-11-01

    Triiodothyronine (T3), the active form of thyroid hormone is produced predominantly outside the thyroid parenchyma secondary to peripheral tissue deiodination of thyroxine (T4), with <20% being secreted directly from the thyroid. In healthy individuals, plasma T3 is regulated by the negative feedback loop of the hypothalamus-pituitary-thyroid axis and by homoeostatic changes in deiodinase expression. Therefore, with the exception of a minimal circadian rhythmicity, serum T3 levels are stable over long periods of time. Studies in rodents indicate that different levels of genetic disruption of the feedback mechanism and deiodinase system are met with increase in serum T4 and thyroid-stimulating hormone (TSH) levels, while serum T3 levels remain stable. These findings have focused attention on serum T3 levels in patients with thyroid disease, with important clinical implications affecting therapeutic goals and choice of therapy for patients with hypothyroidism. Although monotherapy with levothyroxine is the standard of care for hypothyroidism, not all patients normalize serum T3 levels with many advocating for combination therapy with levothyroxine and liothyronine. The latter could be relevant for a significant number of patients that remain symptomatic on monotherapy with levothyroxine, despite normalization of serum TSH levels.

  4. Criminal Intent with Property: A Study of Real Estate Fraud Prediction and Detection

    ERIC Educational Resources Information Center

    Blackman, David H.

    2013-01-01

    The large number of real estate transactions across the United States, combined with closing process complexity, creates extremely large data sets that conceal anomalies indicative of fraud. The quantitative amount of damage due to fraud is immeasurable to the lives of individuals who are victims, not to mention the financial impact to…

  5. Criminal Intent with Property: A Study of Real Estate Fraud Prediction and Detection

    ERIC Educational Resources Information Center

    Blackman, David H.

    2013-01-01

    The large number of real estate transactions across the United States, combined with closing process complexity, creates extremely large data sets that conceal anomalies indicative of fraud. The quantitative amount of damage due to fraud is immeasurable to the lives of individuals who are victims, not to mention the financial impact to…

  6. Real-time EEG-based detection of fatigue driving danger for accident prediction.

    PubMed

    Wang, Hong; Zhang, Chi; Shi, Tianwei; Wang, Fuwang; Ma, Shujun

    2015-03-01

    This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of driver fatigue was analyzed. The functional brain networks were employed to track the fatigue impact on processing capacity of brain. The results show the overall functional connectivity of the subjects is weakened after long time driving tasks. The regularity is summarized as the fatigue convergence phenomenon. Based on the fatigue convergence phenomenon, we combined both the input and global synchronizations of brain together to calculate the residual amount of the information processing capacity of brain to obtain the dangerous points in real time. Finally, the danger detection system of the driver fatigue based on the neural mechanism was validated using accident EEG. The time distributions of the output danger points of the system have a good agreement with those of the real accident points.

  7. Predictability of Pilot Performance from Simulated to Real Flight in the UH-60 (Black Hawk) Helicopter

    DTIC Science & Technology

    2008-02-01

    the Federal Aviation Administration ( FAA ), which allows refractive surgery for civil aviators (Department of Transportation/Federal Aviation...vibration exposures, or true depth of field/ stereopsis , might only be meaningful in the real aircraft environment. Conclusions The use of operational...Administration. 2005. Guide for aviation medical examiners. Washington, DC: FAA Office of Aviation Medicine. Hasbrook, A. H. and Rasmussen, P. G. 1971

  8. CBFA2T3-ZNF651, like CBFA2T3-ZNF652, functions as a transcriptional corepressor complex.

    PubMed

    Kumar, Raman; Cheney, Kelly M; Neilsen, Paul M; Schulz, Renèe B; Callen, David F

    2010-03-05

    A significant proportion of the human genome codes for transcription factors. Balanced activity of transcriptional activators and repressors is essential for normal development and differentiation. Previously we reported that a classical C2H2 zinc finger DNA binding protein ZNF652 functionally interacts with CBFA2T3 to repress transcription of genes containing ZNF652 consensus DNA binding sequence within the promoters of these target genes. Here we show that ZNF651 is a ZNF652 paralogue that shares a common DNA binding sequence with ZNF652 and represses target gene expression through the formation of a CBFA2T3-ZNF651 corepressor complex. It is suggested that CBFA2T3-ZNF651 and CBFA2T3-ZNF652 repressor complexes perform functionally similar roles in a tissue-specific manner.

  9. Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table.

    PubMed

    Koseki, Shigenobu; Isobe, Seiichiro

    2005-10-25

    The growth of pathogenic bacteria Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes on iceberg lettuce under constant and fluctuating temperatures was modelled in order to estimate the microbial safety of this vegetable during distribution from the farm to the table. Firstly, we examined pathogen growth on lettuce at constant temperatures, ranging from 5 to 25 degrees C, and then we obtained the growth kinetic parameters (lag time, maximum growth rate (micro(max)), and maximum population density (MPD)) using the Baranyi primary growth model. The parameters were similar to those predicted by the pathogen modelling program (PMP), with the exception of MPD. The MPD of each pathogen on lettuce was 2-4 log(10) CFU/g lower than that predicted by PMP. Furthermore, the MPD of pathogens decreased with decreasing temperature. The relationship between mu(max) and temperature was linear in accordance with Ratkowsky secondary model as was the relationship between the MPD and temperature. Predictions of pathogen growth under fluctuating temperature used the Baranyi primary microbial growth model along with the Ratkowsky secondary model and MPD equation. The fluctuating temperature profile used in this study was the real temperature history measured during distribution from the field at harvesting to the retail store. Overall predictions for each pathogen agreed well with observed viable counts in most cases. The bias and root mean square error (RMSE) of the prediction were small. The prediction in which mu(max) was based on PMP showed a trend of overestimation relative to prediction based on lettuce. However, the prediction concerning E. coli O157:H7 and Salmonella spp. on lettuce greatly overestimated growth in the case of a temperature history starting relatively high, such as 25 degrees C for 5 h. In contrast, the overall prediction of L. monocytogenes under the same circumstances agreed with the observed data.

  10. Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions.

    PubMed

    Singh, Rakesh B; Huber, Alan H; Braddock, James N

    2003-10-01

    The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.

  11. The characteristics of the real-time land surface emissivity of the ATMS data for numerical weather prediction model

    NASA Astrophysics Data System (ADS)

    Kim, Jisoo; Ahn, Myoung-Hwan; Kim, Eunjin

    2017-04-01

    An accurate estimation of land surface emissivity in the microwave region is essential to expand the utilization of microwave satellite observations to the data assimilation process of numerical weather prediction (NWP) scheme. Several attempts have been made to derive real-time emissivities for this purpose. Here, we try to characterize the real-time land surface emissivity derived from the Advanced Technology Microwave Sounder (ATMS) data with auxiliary information obtained from the radiative simulation; RTTOV-11.2 with the Unified Model of the Korea Meteorological Administration's operational NWP model. Comparison of the real-time emissivities with a climatological emissivity atlas, TELSEM (A Tool to Estimate Land Surface Emissivities at Microwave frequencies), shows a significant improvement in the first guess departure; the reduced bias with the increased number of observations that pass the quality control along with the decreased diurnal variation of the first guess departure. Further, the uncertainty of the real-time emissivities has been estimated over the desert and dense forest areas where the physical variables related to the emissivity are relatively stable. With the 15 days of data at the selected target area, the estimated uncertainty varies about 0.5-5% (1.5-15 K) over both regions. The suspected error sources are the errors inherent in auxiliary data (e.g. surface temperature or temperature and humidity profiles) or the imperfect cloud screening which will be further analyzed.

  12. The real-time prediction and inhibition of linguistic outcomes: Effects of language and literacy skill.

    PubMed

    Kukona, Anuenue; Braze, David; Johns, Clinton L; Mencl, W Einar; Van Dyke, Julie A; Magnuson, James S; Pugh, Kenneth R; Shankweiler, Donald P; Tabor, Whitney

    2016-11-01

    Recent studies have found considerable individual variation in language comprehenders' predictive behaviors, as revealed by their anticipatory eye movements during language comprehension. The current study investigated the relationship between these predictive behaviors and the language and literacy skills of a diverse, community-based sample of young adults. We found that rapid automatized naming (RAN) was a key determinant of comprehenders' prediction ability (e.g., as reflected in predictive eye movements to a white cake on hearing "The boy will eat the white…"). Simultaneously, comprehension-based measures predicted participants' ability to inhibit eye movements to objects that shared features with predictable referents but were implausible completions (e.g., as reflected in eye movements to a white but inedible white car). These findings suggest that the excitatory and inhibitory mechanisms that support prediction during language processing are closely linked with specific cognitive abilities that support literacy. We show that a self-organizing cognitive architecture captures this pattern of results. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Mediator subunit MED1 is a T3-dependent and T3-independent coactivator on the thyrotropin β gene promoter

    SciTech Connect

    Matsui, Keiji; Oda, Kasumi; Mizuta, Shumpei; Ishino, Ruri; Urahama, Norinaga; Hasegawa, Natsumi; Roeder, Robert G.; Ito, Mitsuhiro

    2013-10-11

    Highlights: •MED1 is a bona fide T3-dependent coactivator on TSHB promoter. •Mice with LxxLL-mutant MED1 have attenuated TSHβ mRNA and thyroid hormone levels. •MED1 activates TSHB promoter T3-dependently in cultured cells. •T3-dependent MED1 action is enhanced when SRC1/SRC2 or HDAC2 is downregulated. •MED1 is also a T3-independent GATA2/Pit1 coactivator on TSHB promoter. -- Abstract: The MED1 subunit of the Mediator transcriptional coregulator complex is a nuclear receptor-specific coactivator. A negative feedback mechanism of thyroid-stimulating hormone (TSH, or thyrotropin) expression in the thyrotroph in the presence of triiodothyronine (T3) is employed by liganded thyroid hormone receptor β (TRβ) on the TSHβ gene promoter, where conventional histone-modifying coactivators act as corepressors. We now provide evidence that MED1 is a ligand-dependent positive cofactor on this promoter. TSHβ gene transcription was attenuated in MED1 mutant mice in which the nuclear receptor-binding ability of MED1 was specifically disrupted. MED1 stimulated GATA2- and Pit1-mediated TSHβ gene promoter activity in a ligand-independent manner in cultured cells. MED1 also stimulated transcription from the TSHβ gene promoter in a T3-dependent manner. The transcription was further enhanced when the T3-dependent corepressors SRC1, SRC2, and HDAC2 were downregulated. Hence, MED1 is a T3-dependent and -independent coactivator on the TSHβ gene promoter.

  14. Isobaric multiplet mass equation in the A =31 ,T =3 /2 quartets

    NASA Astrophysics Data System (ADS)

    Bennett, M. B.; Wrede, C.; Brown, B. A.; Liddick, S. N.; Pérez-Loureiro, D.; Bardayan, D. W.; Chen, A. A.; Chipps, K. A.; Fry, C.; Glassman, B. E.; Langer, C.; Larson, N. R.; McNeice, E. I.; Meisel, Z.; Ong, W.; O'Malley, P. D.; Pain, S. D.; Prokop, C. J.; Schwartz, S. B.; Suchyta, S.; Thompson, P.; Walters, M.; Xu, X.

    2016-06-01

    Background: The observed mass excesses of analog nuclear states with the same mass number A and isospin T can be used to test the isobaric multiplet mass equation (IMME), which has, in most cases, been validated to a high degree of precision. A recent measurement [Kankainen et al., Phys. Rev. C 93, 041304(R) (2016), 10.1103/PhysRevC.93.041304] of the ground-state mass of 31Cl led to a substantial breakdown of the IMME for the lowest A =31 ,T =3 /2 quartet. The second-lowest A =31 ,T =3 /2 quartet is not complete, due to uncertainties associated with the identity of the 31S member state. Purpose: Our goal is to populate the two lowest T =3 /2 states in 31S and use the data to investigate the influence of isospin mixing on tests of the IMME in the two lowest A =31 ,T =3 /2 quartets. Methods: Using a fast 31Cl beam implanted into a plastic scintillator and a high-purity Ge γ -ray detection array, γ rays from the 31Cl(β γ )31S sequence were measured. Shell-model calculations using USDB and the recently-developed USDE interactions were performed for comparison. Results: Isospin mixing between the 31S isobaric analog state (IAS) at 6279.0(6) keV and a nearby state at 6390.2(7) keV was observed. The second T =3 /2 state in 31S was observed at Ex=7050.0 (8 ) keV. Calculations using both USDB and USDE predict a triplet of isospin-mixed states, including the lowest T =3 /2 state in 31P, mirroring the observed mixing in 31S, and two isospin-mixed triplets including the second-lowest T =3 /2 states in both 31S and 31P. Conclusions: Isospin mixing in 31S does not by itself explain the IMME breakdown in the lowest quartet, but it likely points to similar isospin mixing in the mirror nucleus 31P, which would result in a perturbation of the 31P IAS energy. USDB and USDE calculations both predict candidate 31P states responsible for the mixing in the energy region slightly above Ex=6400 keV. The second quartet has been completed thanks to the identification of the second 31S T

  15. Predicting and Improving Recognition Memory Using Multiple Electrophysiological Signals in Real Time.

    PubMed

    Fukuda, Keisuke; Woodman, Geoffrey F

    2015-07-01

    Although people are capable of storing a virtually infinite amount of information in memory, their ability to encode new information is far from perfect. The quality of encoding varies from moment to moment and renders some memories more accessible than others. Here, we were able to forecast the likelihood that a given item will be later recognized by monitoring two dissociable fluctuations of the electroencephalogram during encoding. Next, we identified individual items that were poorly encoded, using our electrophysiological measures in real time, and we successfully improved the efficacy of learning by having participants restudy these items. Thus, our memory forecasts using multiple electrophysiological signals demonstrate the feasibility and the effectiveness of using real-time monitoring of the moment-to-moment fluctuations of the quality of memory encoding to improve learning. © The Author(s) 2015.

  16. Many Task Computing for Real-Time Uncertainty Prediction and Data Assimilation in the Ocean

    DTIC Science & Technology

    2010-01-01

    much like cell-phone charges usage of 1 hour 1 sec. counts as 2 hours. Moreover Amazon charges for data movement in and out of EC2. • The...enhancing this with runs on Amazon EC2 and the Teragrid and the I/O challenges faced. Keywords—MTC; assimilation; data-intensive; ensemble; F 1...application. In what follows, Section 2 describes the application area of ocean data assimilation and provides details about the timeline of real

  17. Predictive Analytics to Support Real-Time Management in Pathology Facilities.

    PubMed

    Lessard, Lysanne; Michalowski, Wojtek; Chen Li, Wei; Amyot, Daniel; Halwani, Fawaz; Banerjee, Diponkar

    2016-01-01

    Predictive analytics can provide valuable support to the effective management of pathology facilities. The introduction of new tests and technologies in anatomical pathology will increase the volume of specimens to be processed, as well as the complexity of pathology processes. In order for predictive analytics to address managerial challenges associated with the volume and complexity increases, it is important to pinpoint the areas where pathology managers would most benefit from predictive capabilities. We illustrate common issues in managing pathology facilities with an analysis of the surgical specimen process at the Department of Pathology and Laboratory Medicine (DPLM) at The Ottawa Hospital, which processes all surgical specimens for the Eastern Ontario Regional Laboratory Association. We then show how predictive analytics could be used to support management. Our proposed approach can be generalized beyond the DPLM, contributing to a more effective management of pathology facilities and in turn to quicker clinical diagnoses.

  18. Predictive Analytics to Support Real-Time Management in Pathology Facilities

    PubMed Central

    Lessard, Lysanne; Michalowski, Wojtek; Chen Li, Wei; Amyot, Daniel; Halwani, Fawaz; Banerjee, Diponkar

    2016-01-01

    Predictive analytics can provide valuable support to the effective management of pathology facilities. The introduction of new tests and technologies in anatomical pathology will increase the volume of specimens to be processed, as well as the complexity of pathology processes. In order for predictive analytics to address managerial challenges associated with the volume and complexity increases, it is important to pinpoint the areas where pathology managers would most benefit from predictive capabilities. We illustrate common issues in managing pathology facilities with an analysis of the surgical specimen process at the Department of Pathology and Laboratory Medicine (DPLM) at The Ottawa Hospital, which processes all surgical specimens for the Eastern Ontario Regional Laboratory Association. We then show how predictive analytics could be used to support management. Our proposed approach can be generalized beyond the DPLM, contributing to a more effective management of pathology facilities and in turn to quicker clinical diagnoses. PMID:28269873

  19. Virtual Diagnostics Interface: Real Time Comparison of Experimental Data and CFD Predictions for a NASA Ares I-Like Vehicle

    NASA Technical Reports Server (NTRS)

    Schwartz, Richard J.; Fleming, Gary A.

    2007-01-01

    Virtual Diagnostics Interface technology, or ViDI, is a suite of techniques utilizing image processing, data handling and three-dimensional computer graphics. These techniques aid in the design, implementation, and analysis of complex aerospace experiments. LiveView3D is a software application component of ViDI used to display experimental wind tunnel data in real-time within an interactive, three-dimensional virtual environment. The LiveView3D software application was under development at NASA Langley Research Center (LaRC) for nearly three years. LiveView3D recently was upgraded to perform real-time (as well as post-test) comparisons of experimental data with pre-computed Computational Fluid Dynamics (CFD) predictions. This capability was utilized to compare experimental measurements with CFD predictions of the surface pressure distribution of the NASA Ares I Crew Launch Vehicle (CLV) - like vehicle when tested in the NASA LaRC Unitary Plan Wind Tunnel (UPWT) in December 2006 - January 2007 timeframe. The wind tunnel tests were conducted to develop a database of experimentally-measured aerodynamic performance of the CLV-like configuration for validation of CFD predictive codes.

  20. Virtual Diagnostics Interface: Real Time Comparison of Experimental Data and CFD Predictions for a NASA Ares I-Like Vehicle

    NASA Technical Reports Server (NTRS)

    Schwartz, Richard J.; Fleming, Gary A.

    2007-01-01

    Virtual Diagnostics Interface technology, or ViDI, is a suite of techniques utilizing image processing, data handling and three-dimensional computer graphics. These techniques aid in the design, implementation, and analysis of complex aerospace experiments. LiveView3D is a software application component of ViDI used to display experimental wind tunnel data in real-time within an interactive, three-dimensional virtual environment. The LiveView3D software application was under development at NASA Langley Research Center (LaRC) for nearly three years. LiveView3D recently was upgraded to perform real-time (as well as post-test) comparisons of experimental data with pre-computed Computational Fluid Dynamics (CFD) predictions. This capability was utilized to compare experimental measurements with CFD predictions of the surface pressure distribution of the NASA Ares I Crew Launch Vehicle (CLV) - like vehicle when tested in the NASA LaRC Unitary Plan Wind Tunnel (UPWT) in December 2006 - January 2007 timeframe. The wind tunnel tests were conducted to develop a database of experimentally-measured aerodynamic performance of the CLV-like configuration for validation of CFD predictive codes.

  1. Automated system for near-real time modelling and prediction of altimeter-derived sea level anomalies

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz; Miziński, Bartłomiej

    2013-08-01

    This paper serves as a presentation of a novel geoinformation system and a dedicated service, jointly named as Prognocean and based at the University of Wrocław (Poland), that aim to predict Sea Level Anomaly (SLA) maps and publish them online. The system works in near-real time and is updated daily. The data are provided by the Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO), and the time series processed by Prognocean is delivered by various altimetric satellites. The emphasis is put on gridded SLA maps, also known as MSLA, which are provided as Delayed Time (DT) and Near-Real Time (NRT) daily products. The daily sampling interval, however, does not coincide with typical repeat cycles of altimetric satellites and is obtained through reprocessing produced by AVISO. The two-module infrastructure forms the system. The first module is responsible for the near-real time communication with AVISO to download the most recent MSLA data and acquire the corrected data when the geophysical corrections have been available. The second module forms the main engine which does data processing, modelling, forecasting, statistical quality control and finally generates products as maps. The online service, however, publishes the products online every day. The above-mentioned components and infrastructure are described in detail. The performance of the system was evaluated using at least 150 predicted MSLA maps, available after half year of computations carried out in near-real time. We identified a few regions of imperfect performance of our prognoses and found that they spatially correspond to the mouth of the Amazon River and locations of key mesoscale eddies, the vast majority of which being nonlinear and hence unmodelled in our experiment.

  2. Thyroid Hormones, T3 and T4, in the Brain

    PubMed Central

    Schroeder, Amy C.; Privalsky, Martin L.

    2014-01-01

    Thyroid hormones (THs) are essential for fetal and post-natal nervous system development and also play an important role in the maintenance of adult brain function. Of the two major THs, T4 (3,5,3′,5′-tetraiodo-l-thyronine) is classically viewed as an pro-hormone that must be converted to T3 (3,5,3′-tri-iodo-l-thyronine) via tissue-level deiodinases for biological activity. THs primarily mediate their effects by binding to thyroid hormone receptor (TR) isoforms, predominantly TRα1 and TRβ1, which are expressed in different tissues and exhibit distinctive roles in endocrinology. Notably, the ability to respond to T4 and to T3 differs for the two TR isoforms, with TRα1 generally more responsive to T4 than TRβ1. TRα1 is also the most abundantly expressed TR isoform in the brain, encompassing 70–80% of all TR expression in this tissue. Conversion of T4 into T3 via deiodinase 2 in astrocytes has been classically viewed as critical for generating local T3 for neurons. However, deiodinase-deficient mice do not exhibit obvious defectives in brain development or function. Considering that TRα1 is well-established as the predominant isoform in brain, and that TRα1 responds to both T3 and T4, we suggest T4 may play a more active role in brain physiology than has been previously accepted. PMID:24744751

  3. Thyroid hormones, t3 and t4, in the brain.

    PubMed

    Schroeder, Amy C; Privalsky, Martin L

    2014-01-01

    Thyroid hormones (THs) are essential for fetal and post-natal nervous system development and also play an important role in the maintenance of adult brain function. Of the two major THs, T4 (3,5,3',5'-tetraiodo-l-thyronine) is classically viewed as an pro-hormone that must be converted to T3 (3,5,3'-tri-iodo-l-thyronine) via tissue-level deiodinases for biological activity. THs primarily mediate their effects by binding to thyroid hormone receptor (TR) isoforms, predominantly TRα1 and TRβ1, which are expressed in different tissues and exhibit distinctive roles in endocrinology. Notably, the ability to respond to T4 and to T3 differs for the two TR isoforms, with TRα1 generally more responsive to T4 than TRβ1. TRα1 is also the most abundantly expressed TR isoform in the brain, encompassing 70-80% of all TR expression in this tissue. Conversion of T4 into T3 via deiodinase 2 in astrocytes has been classically viewed as critical for generating local T3 for neurons. However, deiodinase-deficient mice do not exhibit obvious defectives in brain development or function. Considering that TRα1 is well-established as the predominant isoform in brain, and that TRα1 responds to both T3 and T4, we suggest T4 may play a more active role in brain physiology than has been previously accepted.

  4. Demand response-enabled model predictive HVAC load control in buildings using real-time electricity pricing

    NASA Astrophysics Data System (ADS)

    Avci, Mesut

    A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy is built based on a proposed model that jointly minimizes the total energy consumption and hence, cost of electricity for the user, and the deviation of the inside temperature from the consumer's preference. An algorithm that assigns temperature set-points (reference temperatures) to price ranges based on the consumer's discomfort tolerance index is developed. A practical parameter prediction model is also designed for mapping between the HVAC load and the inside temperature. The prediction model and the produced temperature set-points are integrated as inputs into the MPC controller, which is then used to generate signal actions for the AC unit. To investigate and demonstrate the effectiveness of the proposed approach, a simulation based experimental analysis is presented using real-life pricing data. An actual prototype for the proposed HVAC load control strategy is then built and a series of prototype experiments are conducted similar to the simulation studies. The experiments reveal that the MPC strategy can lead to significant reductions in overall energy consumption and cost savings for the consumer. Results suggest that by providing an efficient response strategy for the consumers, the proposed MPC strategy can enable the utility providers to adopt efficient demand management policies using real-time pricing. Finally, a cost-benefit analysis is performed to display the economic feasibility of implementing such a controller as part of a building energy management system, and the payback period is identified considering cost of prototype build and cost savings to help the adoption of this controller in the building HVAC control industry.

  5. Real value prediction of protein folding rate change upon point mutation

    NASA Astrophysics Data System (ADS)

    Huang, Liang-Tsung; Gromiha, M. Michael

    2012-03-01

    Prediction of protein folding rate change upon amino acid substitution is an important and challenging problem in protein folding kinetics and design. In this work, we have analyzed the relationship between amino acid properties and folding rate change upon mutation. Our analysis showed that the correlation is not significant with any of the studied properties in a dataset of 476 mutants. Further, we have classified the mutants based on their locations in different secondary structures and solvent accessibility. For each category, we have selected a specific combination of amino acid properties using genetic algorithm and developed a prediction scheme based on quadratic regression models for predicting the folding rate change upon mutation. Our results showed a 10-fold cross validation correlation of 0.72 between experimental and predicted change in protein folding rates. The correlation is 0.73, 0.65 and 0.79, respectively in strand, helix and coil segments. The method has been further tested with an extended dataset of 621 mutants and a blind dataset of 62 mutants, and we observed a good agreement with experiments. We have developed a web server for predicting the folding rate change upon mutation and it is available at http://bioinformatics.myweb.hinet.net/fora.htm.

  6. Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

    NASA Astrophysics Data System (ADS)

    Hong, S.-M.; Jung, B.-H.; Ruan, D.

    2011-03-01

    Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

  7. A real-time prediction system for solar weather based on magnetic nonpotentiality (I)

    NASA Astrophysics Data System (ADS)

    Yang, Xiao; Lin, GangHua; Deng, YuanYong

    2016-07-01

    The Sun is the source of space weather. The characteristics and evolution of the solar active-region magnetic field closely relate to violent solar eruptions such as flares and coronal mass ejections. The Solar Magnetic Field Telescope in Huairou Solar Observing Station has accumulated numerous vector magnetogram data of solar photospheric active regions (AR) covering nearly 30 years. Utilizing these precious historical data to establish statistical prediction models for solar eruptive events, not only can provide a reference for the timely adjustment of observation mode to specific active regions, but also can offer valuable reference to the monitoring and forecasting departments of solar and space weather. In this part of work, we focus on the Yes/No and occurrence time predictions for AR-related solar flares, and the predictions independently rely on the vector magnetic-filed observation of the solar surface.

  8. Initial Study on the Predictability of Real Power on the Grid based on PMU Data

    SciTech Connect

    Ferryman, Thomas A.; Tuffner, Francis K.; Zhou, Ning; Lin, Guang

    2011-03-23

    Operations on the electric power grid provide highly reliable power to the end users. These operations involve hundreds of human operators and automated control schemes. However, the operations process can often take several minutes to complete. During these several minutes, the operations are often evaluated on a past state of the power system. Proper prediction methods could change this to make the operations evaluate the state of the power grid minutes in advance. Such information allows proactive, rather than reactive, actions on the power system and aids in improving the efficiency and reliability of the power grid as a whole. A successful demonstration of this prediction framework is necessary to evaluate the feasibility of utilizing such predicted states in grid operations.

  9. Real time prediction of marine vessel motions using Kalman filtering techniques

    NASA Technical Reports Server (NTRS)

    Triantafyllou, M. S.; Bodson, M.

    1982-01-01

    The present investigation is concerned with the prediction of the future behavior of a vessel within some confidence bounds at a specific instant of time, taking into account an interval of a few seconds. The ability to predict accurately the motions of a vessel can reduce significantly the probability of failure of operations in rough seas. The investigation was started as part of an effort to ensure safe landing of aircraft on relatively small vessels. However, the basic principles involved in the study are the same for any offshore operation, such as carbo transfer in the open sea, structure installation, and floating crane operation. The Kalman filter is a powerful tool for achieving the goals of the prediction procedure. Attention is given to a linear optimal predictor, the equations of motion of the vessel, the wave spectrum, rational approximation, the use of Kalman filter and predictor in an application for a ship, and the motions of a semisubmersible.

  10. Statistical analysis for understanding and predicting battery degradations in real-life electric vehicle use

    NASA Astrophysics Data System (ADS)

    Barré, Anthony; Suard, Frédéric; Gérard, Mathias; Montaru, Maxime; Riu, Delphine

    2014-01-01

    This paper describes the statistical analysis of recorded data parameters of electrical battery ageing during electric vehicle use. These data permit traditional battery ageing investigation based on the evolution of the capacity fade and resistance raise. The measured variables are examined in order to explain the correlation between battery ageing and operating conditions during experiments. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present the responsible factors on battery ageing phenomena. Predictive battery ageing models are built from this approach. Thereby results demonstrate and quantify a relationship between variables and battery ageing global observations, and also allow accurate battery ageing diagnosis through predictive models.

  11. Chlamydia trachomatis promotes 3T3 cell differentiation into adipocytes.

    PubMed

    Petyaev, Ivan M; Zigangirova, Nailya A; Kapotina, Lydia N; Fedina, Elena D; Kyle, Nigel H

    2014-01-01

    There is experimental and clinical evidence showing that some viral and bacterial pathogens are linked to the accumulation of excessive body fat and obesity. The aim of the study was to investigate the ability of C. trachomatis to propagate in the pre-adipocyte cell line and induce its differentiation into fat cells. 3T3 L1 pre-adipocytes or McCoy cells were plated and infected with C. trachomatis. The cell monolayers were further studied by immunofluorescent and quantitative RT-PCR methods. C. trachomatis can efficiently propagate in 3T3 L1 cells, a mouse pre-adipocyte cell line. The morphological characteristics of chlamydial growth revealed in 3T3 L1 cells with the monoclonal chlamydial MOMP-specific antibody resembled those seen in McCoy cells, a classic cell line used for chlamydial research. The number of chlamydial 16S rRNA copies detectable in the lysates of McCoy and 3T3 cells infected with C. trachomatis was almost identical, suggesting similar efficiency of pathogen propagation in both cell lines. Moreover, there was a significant increase in aP2 mRNA transcript levels as well as moderate induction of SCD-1 mRNA in the total RNA extracted from the infected 3T3 L1 cells 48 h following the pathogen inoculation. The increased expression of the adipogenic markers was also accompanied by lipid droplet accumulation in the C. trachomatis infected 3T3 L1 cells, suggesting their transformation into differentiated adipocytes. The direct effect of the pathogen on fat cell progenitors observed in this work may explain abnormal fat deposition at the sites of chronic inflammation caused by C. trachomatis.

  12. CLOCK promotes 3T3-L1 cell proliferation via Wnt signaling.

    PubMed

    Zhu, Zhu; Hua, Bingxuan; Xu, Lirong; Yuan, Gongsheng; Li, Ermin; Li, Xiaobo; Sun, Ning; Yan, Zuoqin; Lu, Chao; Qian, Ruizhe

    2016-07-01

    Circadian genes control most of the physiological functions including cell cycle. Cell proliferation is a critical factor in the differentiation of progenitor cells. However, the role of Clock gene in the regulation of cell cycle via wingless-type (Wnt) pathway and the relationship between Clock and adipogenesis are unclear. We found that the circadian locomotor output cycles kaput (Clock) regulated the proliferation and the adipogenesis of 3T3-L1 preadipocytes. We found that Clock attenuation inhibited the viability of 3T3-L1 preadipocytes in the cell counting kit 8. The expression of c-Myc and Cyclin D1 decreased dramatically in 3T3-L1 when Clock was silenced with short interfering RNA and was also decreased in fat tissue and adipose tissue-derived stem cells of Clock(Δ19) mice. Clock directly controls the expression of the components of Wnt signal transduction pathway, which was verified by serum shock, chromatin immunoprecipitation, Western blot, and quantitative real-time polymerase chain reaction (qRT-PCR). Furthermore, IWR-1, a Wnt signal pathway inhibitor, inhibited the cell cycle promotion by CLOCK, which was detected by cell viability assay, flow cytometry, and qRT-PCR. Therefore, CLOCK transcription control of Wnt signaling promotes cell cycle progression in 3T3-L1 preadipocytes. Clock inhibited the adipogenesis on day 2 in 3T3-L1 cells via Oil Red O staining and qRT-PCR detection and probably related to cellular differentiation. These data provide evidence that the circadian gene Clock regulates the proliferation of preadipocytes and affects adipogenesis. © 2016 IUBMB Life, 68(7):557-568, 2016. © 2016 International Union of Biochemistry and Molecular Biology.

  13. Real-time prediction of neuronal population spiking activity using FPGA.

    PubMed

    Li, Will X Y; Cheung, Ray C C; Chan, Rosa H M; Song, Dong; Berger, Theodore W

    2013-08-01

    A field-programmable gate array (FPGA)-based hardware architecture is proposed and utilized for prediction of neuronal population firing activity. The hardware system adopts the multi-input multi-output (MIMO) generalized Laguerre-Volterra model (GLVM) structure to describe the nonlinear dynamic neural process of mammalian brain and can switch between the two important functions: estimation of GLVM coefficients and prediction of neuronal population spiking activity (model outputs). The model coefficients are first estimated using the in-sample training data; then the output is predicted using the out-of-sample testing data and the field estimated coefficients. Test results show that compared with previous software implementation of the generalized Laguerre-Volterra algorithm running on an Intel Core i7-2620M CPU, the FPGA-based hardware system can achieve up to 2.66×10(3) speedup in doing model parameters estimation and 698.84 speedup in doing model output prediction. The proposed hardware platform will facilitate research on the highly nonlinear neural process of the mammal brain, and the cognitive neural prosthesis design.

  14. Model Predictive Control application for real time operation of controlled structures for the Water Authority Noorderzijlvest, The Netherlands

    NASA Astrophysics Data System (ADS)

    van Heeringen, Klaas-Jan; Gooijer, Jan; Knot, Floris; Talsma, Jan

    2015-04-01

    In the Netherlands, flood protection has always been a key issue to protect settlements against storm surges and riverine floods. Whereas flood protection traditionally focused on structural measures, nowadays the availability of meteorological and hydrological forecasts enable the application of more advanced real-time control techniques for operating the existing hydraulic infrastructure in an anticipatory and more efficient way. Model Predictive Control (MPC) is a powerful technique to derive optimal control variables with the help of model based predictions evaluated against a control objective. In a project for the regional water authority Noorderzijlvest in the north of the Netherlands, it has been shown that MPC can increase the safety level of the system during flood events by an anticipatory pre-release of water. Furthermore, energy costs of pumps can be reduced by making tactical use of the water storage and shifting pump activities during normal operating conditions to off-peak hours. In this way cheap energy is used in combination of gravity flow through gates during low tide periods. MPC has now been implemented for daily operational use of the whole water system of the water authority Noorderzijlvest. The system developed to a real time decision support system which not only supports the daily operation but is able to directly implement the optimal control settings at the structures. We explain how we set-up and calibrated a prediction model (RTC-Tools) that is accurate and fast enough for optimization purposes, and how we integrated it in the operational flood early warning system (Delft-FEWS). Beside the prediction model, the weights and the factors of the objective function are an important element of MPC, since they shape the control objective. We developed special features in Delft-FEWS to allow the operators to adjust the objective function in order to meet changing requirements and to evaluate different control strategies.

  15. Prediction of Real World Functional Disability in Chronic Mental Disorders: A Comparison of Schizophrenia and Bipolar Disorder

    PubMed Central

    Bowie, Christopher R.; Depp, Colin; McGrath, John A.; Wolyniec, Paula; Mausbach, Brent T.; Thornquist, Mary H.; Luke, James; Patterson, Thomas L.; Harvey, Philip D.; Pulver, Ann E.

    2013-01-01

    OBJECTIVE Schizophrenia (SZ) and Bipolar Disorder (BD) are associated with multidimensional disability. This study examined differential predictors of functional deficits between the disorders. METHODS Community dwelling individuals with SZ (N=161) or BD (N=130) were administered neuropsychological tests, symptom measures, performance-based social and adaptive (i.e., everyday-living skills) functional competence measures, and rated on domains of real-world functioning: 1) Community and Household activities, 2) Work skills, and 3) Interpersonal relationships. We used confirmatory path analysis to find the best fitting models to examine the direct and indirect (as mediated by competence) prediction of the three domains of real-world functioning. RESULTS In all models for both groups, neurocognition’s relationship with outcomes was largely mediated by competence. Symptoms were negatively associated with outcomes but unassociated with competence, with the exception of depression, which was a direct and mediated (through social competence) predictor in BD. In both groups, neurocognition was related to Activities directly and through a mediated relationship with adaptive competence. Work Skills were directly and indirectly (through mediation with social competence) predicted by neurocognition in SZ and entirely mediated by adaptive and social competence in BD. Neurocognition was associated with Interpersonal Relationships directly in the SZ group, and mediated by social competence in both groups. CONCLUSIONS Although there was greater disability in SZ, neurocognition predicted worse functioning in all outcome domains in both disorders. Our study supports the shared role of neurocognition in BD and SZ in producing disability, with predictive differences between disorders observed in domain-specific effects of symptoms and social and adaptive competence. PMID:20478878

  16. An integrated tool for real time prediction of hydrological response of steep-slopes in shallow pyroclastic deposits

    NASA Astrophysics Data System (ADS)

    Damiano, E.; Giorgio, M.; Greco, R.; Guida, A.; Netti, N.; Olivares, L.; Savastano, V.

    2012-04-01

    A large part of the mountains of Campania, in southern Italy, are interested by catastrophic flowslides triggered by heavy rainfalls. The slopes are covered by shallow deposits of loose pyroclastic soils in unsaturated conditions, which equilibrium is assured by the contribution of apparent cohesion due to soil suction. Hence, a key tool for the prediction of slope stability is the short-term forecasting of intense and persistent rainfall events and the subsequent analysis of the hydrological response of the shallow covers during such events. To this aim a numerical tool, is presented, consisting of a module for stochastic short-term rainfall prediction and 3D finite volumes model of infiltration and seepage through porous medium, provided with a geotechnical module for slope stability analysis. The presented predictor of rainfall evolution consists of an event based stochastic model, allowing formulating real time predictions of the future evolution of a storm, conditioned to the observed part of the storm. The 3D code (I-MOD3D) was calibrated through back-analysis of infiltration tests on slope model (Olivares et al. 2009) and of in situ suction measurements (Olivares and Damiano, 2007) collected in a instrumented site on a slope where recently a catastrophic flowslide occurred. The calibrated model has been applied to real time predictions of the slope response during some observed storms, showing the reliability of the results of the proposed model, which may represent a useful tool for decision making to implement early warning systems. Olivares L. and Damiano E. (2007). Post-failure mechanics of landslides: laboratory investigation of flowslides in pyroclastic soils. Journal of Geotechnical and Geoenvironmental Engineering ASCE, 133(1): 51-62 Olivares L., Damiano E, Greco R, Zeni L, Picarelli L, Minardo A, Guida A, Bernini R (2009). An Instrumented Flume to Investigate the Mechanics of Rainfall-Induced Landslides in Unsaturated Granular Soils. GEOTECHNICAL

  17. Can benthic community structure be used to predict the process of bioturbation in real ecosystems?

    NASA Astrophysics Data System (ADS)

    Queirós, Ana M.; Stephens, Nicholas; Cook, Richard; Ravaglioli, Chiara; Nunes, Joana; Dashfield, Sarah; Harris, Carolyn; Tilstone, Gavin H.; Fishwick, James; Braeckman, Ulrike; Somerfield, Paul J.; Widdicombe, Stephen

    2015-09-01

    Disentangling the roles of environmental change and natural environmental variability on biologically mediated ecosystem processes is paramount to predict future marine ecosystem functioning. Bioturbation, the biogenic mixing of sediments, has a regulating role in marine biogeochemical processes. However, our understanding of bioturbation as a community level process and of its environmental drivers is still limited by loose use of terminology, and a lack of consensus about what bioturbation is. To help resolve these challenges, this empirical study investigated the links between four different attributes of bioturbation (bioturbation depth, activity and distance, and biodiffusive transport); the ability of an index of bioturbation (BPc) to predict each of them; and their relation to seasonality, in a shallow coastal system - the Western Channel Observatory, UK. Bioturbation distance depended on changes in benthic community structure, while the other three attributes were more directly influenced by seasonality in food availability. In parallel, BPc successfully predicted bioturbation distance but not the other attributes of bioturbation. This study therefore highlights that community bioturbation results from this combination of processes responding to environmental variability at different time-scales. However, community level measurements of bioturbation across environmental variability are still scarce, and BPc is calculated using commonly available data on benthic community structure and the functional classification of invertebrates. Therefore, BPc could be used to support the growth of landscape scale bioturbation research, but future uses of the index need to consider which bioturbation attributes the index actually predicts. As BPc predicts bioturbation distance, estimated here using a random-walk model applicable to community settings, studies using either of the metrics should be directly comparable and contribute to a more integrated future for

  18. Predicting invasion in grassland ecosystems: is exotic dominance the real embarrassment of richness?

    PubMed

    Seabloom, Eric W; Borer, Elizabeth T; Buckley, Yvonne; Cleland, Elsa E; Davies, Kendi; Firn, Jennifer; Harpole, W Stanley; Hautier, Yann; Lind, Eric; MacDougall, Andrew; Orrock, John L; Prober, Suzanne M; Adler, Peter; Alberti, Juan; Anderson, T Michael; Bakker, Jonathan D; Biederman, Lori A; Blumenthal, Dana; Brown, Cynthia S; Brudvig, Lars A; Caldeira, Maria; Chu, Chengjin; Crawley, Michael J; Daleo, Pedro; Damschen, Ellen I; D'Antonio, Carla M; DeCrappeo, Nicole M; Dickman, Chris R; Du, Guozhen; Fay, Philip A; Frater, Paul; Gruner, Daniel S; Hagenah, Nicole; Hector, Andrew; Helm, Aveliina; Hillebrand, Helmut; Hofmockel, Kirsten S; Humphries, Hope C; Iribarne, Oscar; Jin, Virginia L; Kay, Adam; Kirkman, Kevin P; Klein, Julia A; Knops, Johannes M H; La Pierre, Kimberly J; Ladwig, Laura M; Lambrinos, John G; Leakey, Andrew D B; Li, Qi; Li, Wei; McCulley, Rebecca; Melbourne, Brett; Mitchell, Charles E; Moore, Joslin L; Morgan, John; Mortensen, Brent; O'Halloran, Lydia R; Pärtel, Meelis; Pascual, Jesús; Pyke, David A; Risch, Anita C; Salguero-Gómez, Roberto; Sankaran, Mahesh; Schuetz, Martin; Simonsen, Anna; Smith, Melinda; Stevens, Carly; Sullivan, Lauren; Wardle, Glenda M; Wolkovich, Elizabeth M; Wragg, Peter D; Wright, Justin; Yang, Louie

    2013-12-01

    Invasions have increased the size of regional species pools, but are typically assumed to reduce native diversity. However, global-scale tests of this assumption have been elusive because of the focus on exotic species richness, rather than relative abundance. This is problematic because low invader richness can indicate invasion resistance by the native community or, alternatively, dominance by a single exotic species. Here, we used a globally replicated study to quantify relationships between exotic richness and abundance in grass-dominated ecosystems in 13 countries on six continents, ranging from salt marshes to alpine tundra. We tested effects of human land use, native community diversity, herbivore pressure, and nutrient limitation on exotic plant dominance. Despite its widespread use, exotic richness was a poor proxy for exotic dominance at low exotic richness, because sites that contained few exotic species ranged from relatively pristine (low exotic richness and cover) to almost completely exotic-dominated ones (low exotic richness but high exotic cover). Both exotic cover and richness were predicted by native plant diversity (native grass richness) and land use (distance to cultivation). Although climate was important for predicting both exotic cover and richness, climatic factors predicting cover (precipitation variability) differed from those predicting richness (maximum temperature and mean temperature in the wettest quarter). Herbivory and nutrient limitation did not predict exotic richness or cover. Exotic dominance was greatest in areas with low native grass richness at the site- or regional-scale. Although this could reflect native grass displacement, a lack of biotic resistance is a more likely explanation, given that grasses comprise the most aggressive invaders. These findings underscore the need to move beyond richness as a surrogate for the extent of invasion, because this metric confounds monodominance with invasion resistance. Monitoring

  19. Predicting invasion in grassland ecosystems: Is exotic dominance the real embarrassment of richness?

    USGS Publications Warehouse

    Seabloom, Eric; Borer, Elizabeth; Buckley, Yvonne; Cleland, Elsa E.; Davies, Kendi; Firn, Jennifer; Harpole, W. Stanley; Hautier, Yann; Lind, Eric M.; MacDougall, Andrew; Orrock, John L.; Prober, Suzanne M.; Adler, Peter; Alberti, Juan; Anderson, T. Michael; Bakker, Jonathan D.; Biederman, Lori A.; Blumenthal, Dana; Brown, Cynthia S.; Brudvig, Lars A.; Caldeira, Maria; Chu, Cheng-Jin; Crawley, Michael J.; Daleo, Pedro; Damschen, Ellen Ingman; D'Antonio, Carla M.; DeCrappeo, Nicole M.; Dickman, Chris R.; Du, Guozhen; Fay, Philip A.; Frater, Paul; Gruner, Daniel S.; Hagenah, Nicole; Hector, Andrew; Helm, Aveliina; Hillebrand, Helmut; Hofmockel, Kirsten S.; Humphries, Hope C.; Iribarne, Oscar; Jin, Virginia L.; Kay, Adam; Kirkman, Kevin P.; Klein, Julia A.; Knops, Johannes M.H.; La Pierre, Kimberly J.; Ladwig, Laura M.; ,; John, G.; Leakey, Andrew D.B.; Li, Qi; Li, Wei; McCulley, Rebecca; Melbourne, Brett; ,; Charles, E.; Moore, Joslin L.; Morgan, John; Mortensen, Brent; O'Halloran, Lydia R.; Pärtel, Meelis; Pascual, Jesús; Pyke, David A.; Risch, Anita C.; Salguero-Gómez, Roberto; Sankaran, Mahesh; Schuetz, Martin; Simonsen, Anna; Smith, Melinda; Stevens, Carly; Sullivan, Lauren; Wardle, Glenda M.; Wolkovich, Elizabeth M.; Wragg, Peter D.; Wright, Justin; Yang, Louie

    2013-01-01

    Invasions have increased the size of regional species pools, but are typically assumed to reduce native diversity. However, global-scale tests of this assumption have been elusive because of the focus on exotic species richness, rather than relative abundance. This is problematic because low invader richness can indicate invasion resistance by the native community or, alternatively, dominance by a single exotic species. Here, we used a globally replicated study to quantify relationships between exotic richness and abundance in grass-dominated ecosystems in 13 countries on six continents, ranging from salt marshes to alpine tundra. We tested effects of human land use, native community diversity, herbivore pressure, and nutrient limitation on exotic plant dominance. Despite its widespread use, exotic richness was a poor proxy for exotic dominance at low exotic richness, because sites that contained few exotic species ranged from relatively pristine (low exotic richness and cover) to almost completely exotic-dominated ones (low exotic richness but high exotic cover). Both exotic cover and richness were predicted by native plant diversity (native grass richness) and land use (distance to cultivation). Although climate was important for predicting both exotic cover and richness, climatic factors predicting cover (precipitation variability) differed from those predicting richness (maximum temperature and mean temperature in the wettest quarter). Herbivory and nutrient limitation did not predict exotic richness or cover. Exotic dominance was greatest in areas with low native grass richness at the site- or regional-scale. Although this could reflect native grass displacement, a lack of biotic resistance is a more likely explanation, given that grasses comprise the most aggressive invaders. These findings underscore the need to move beyond richness as a surrogate for the extent of invasion, because this metric confounds monodominance with invasion resistance. Monitoring

  20. Predicting invasion in grassland ecosystems: is exotic dominance the real embarrassment of richness?

    USGS Publications Warehouse

    Seabloom, Eric; Borer, Elizabeth; Buckley, Yvonne; Cleland, Elsa E.; Davies, Kendi; Firn, Jennifer; Harpole, W. Stanley; Hautier, Yann; Lind, Eric M.; MacDougall, Andrew; Orrock, John L.; Prober, Suzanne M.; Adler, Peter; Alberti, Juan; Anderson, T. Michael; Bakker, Jonathan D.; Biederman, Lori A.; Blumenthal, Dana; Brown, Cynthia S.; Brudvig, Lars A.; Caldeira, Maria; Chu, Cheng-Jin; Crawley, Michael J.; Daleo, Pedro; Damschen, Ellen Ingman; D'Antonio, Carla M.; DeCrappeo, Nicole M.; Dickman, Chris R.; Du, Guozhen; Fay, Philip A.; Frater, Paul; Gruner, Daniel S.; Hagenah, Nicole; Hector, Andrew; Helm, Aveliina; Hillebrand, Helmut; Hofmockel, Kirsten S.; Humphries, Hope C.; Iribarne, Oscar; Jin, Virginia L.; Kay, Adam; Kirkman, Kevin P.; Klein, Julia A.; Knops, Johannes M.H.; La Pierre, Kimberly J.; Ladwig, Laura M.; ,; John, G.; Leakey, Andrew D.B.; Li, Qi; Li, Wei; McCulley, Rebecca; Melbourne, Brett; ,; Charles, E.; Moore, Joslin L.; Morgan, John; Mortensen, Brent; O'Halloran, Lydia R.; Pärtel, Meelis; Pascual, Jesús; Pyke, David A.; Risch, Anita C.; Salguero-Gómez, Roberto; Sankaran, Mahesh; Schuetz, Martin; Simonsen, Anna; Smith, Melinda; Stevens, Carly; Sullivan, Lauren; Wardle, Glenda M.; Wolkovich, Elizabeth M.; Wragg, Peter D.; Wright, Justin; Yang, Louie

    2013-01-01

    Invasions have increased the size of regional species pools, but are typically assumed to reduce native diversity. However, global-scale tests of this assumption have been elusive because of the focus on exotic species richness, rather than relative abundance. This is problematic because low invader richness can indicate invasion resistance by the native community or, alternatively, dominance by a single exotic species. Here, we used a globally replicated study to quantify relationships between exotic richness and abundance in grass-dominated ecosystems in 13 countries on six continents, ranging from salt marshes to alpine tundra. We tested effects of human land use, native community diversity, herbivore pressure, and nutrient limitation on exotic plant dominance. Despite its widespread use, exotic richness was a poor proxy for exotic dominance at low exotic richness, because sites that contained few exotic species ranged from relatively pristine (low exotic richness and cover) to almost completely exotic-dominated ones (low exotic richness but high exotic cover). Both exotic cover and richness were predicted by native plant diversity (native grass richness) and land use (distance to cultivation). Although climate was important for predicting both exotic cover and richness, climatic factors predicting cover (precipitation variability) differed from those predicting richness (maximum temperature and mean temperature in the wettest quarter). Herbivory and nutrient limitation did not predict exotic richness or cover. Exotic dominance was greatest in areas with low native grass richness at the site- or regional-scale. Although this could reflect native grass displacement, a lack of biotic resistance is a more likely explanation, given that grasses comprise the most aggressive invaders. These findings underscore the need to move beyond richness as a surrogate for the extent of invasion, because this metric confounds monodominance with invasion resistance. Monitoring

  1. Predicting invasion in grassland ecosystems: is exotic dominance the real embarrassment of richness?

    SciTech Connect

    Seabloom, Eric W.

    2013-08-14

    Invasions have increased the size of regional species pools, but are typically assumed to reduce native diversity. However, global-scale tests of this assumption have been elusive because of the focus on exotic species richness, rather than relative abundance. This is problematic because low invader richness can indicate invasion resistance by the native community or, alternatively, dominance by a single exotic species. Here, we used a globally replicated study to quantify relationships between exotic richness and abundance in grass-dominated ecosystems in 13 countries on six continents, ranging from salt marshes to alpine tundra. We tested effects of human land use, native community diversity, herbivore pressure, and nutrient limitation on exotic plant dominance. Despite its widespread use, exotic richness was a poor proxy for exotic dominance at low exotic richness, because sites that contained few exotic species ranged from relatively pristine (low exotic richness and cover) to almost completely exotic-dominated ones (low exotic richness but high exotic cover). Both exotic cover and richness were predicted by native plant diversity (native grass richness) and land use (distance to cultivation). Although climate was important for predicting both exotic cover and richness, climatic factors predicting cover (precipitation variability) differed from those predicting richness (maximum temperature and mean temperature in the wettest quarter). Herbivory and nutrient limitation did not predict exotic richness or cover. Exotic dominance was greatest in areas with low native grass richness at the site- or regional-scale. Although this could reflect native grass displacement, a lack of biotic resistance is a more likely explanation, given that grasses comprise the most aggressive invaders. These findings underscore the need to move beyond richness as a surrogate for the extent of invasion, because this metric confounds monodominance with invasion resistance. Monitoring

  2. Prediction in Real Time of the 2000 July 14 Heliospheric Shock Wave and its Companions During the `Bastille' Epoch*

    NASA Astrophysics Data System (ADS)

    Dryer, M.; Fry, C. D.; Sun, W.; Deehr, C.; Smith, Z.; Akasofu, S.-I.; Andrews, M. D.

    2001-12-01

    Prediction of solar-generated disturbances and their three-dimensional propagation through interplanetary space continues to present a vitally important operational space weather forecasting objective. This paper presents the first successful real-time prediction of a series of major heliospheric shock waves at Earth, including the one from the 14 July 2000 (`Bastille Day') flare. An ensemble of three models and their predictions were distributed to a world-wide group of interested scientists as part of an informal Internet space weather forecast research program. Two of the models, STOA (Shock Time of Arrival) and ISPM (Interplanetary Shock Propagation Model), presently in operation by the US Air Force Weather Agency, provided predictions of shock arrival time (SAT) that were, respectively, 0.5 hours after and 3.7 hours before the observed arrival. The third model, HAFv.2 (Hakamada Akasofu Fry version 2.0) predicted a time 0.3 hours after the observed shock arrival time (14:37 UT, 15 July 2000). Of primary interest to this study is the third model, firstly in terms of its capability of propagating shocks through non-uniform solar wind conditions, and secondly, in terms of its ability to integrate multiple solar events and display them graphically along with the background solar wind. This latter capability was brought to bear on ten real-time-reported flares, some with CMEs (coronal mass ejections) that took place as companions to the Bastille flare during the period 7 15 July 2000. Some limited statistics are given regarding the three models' shock arrival prediction capability at Earth, as an extension of our earlier studies with this three model ensemble in the prediction of SAT. HAFv.2, however, was able to describe not only the ten events and their interaction as measured at Earth, but also at the spacecraft NEAR (orbiting the asteroid, Eros, at 1.8 AU), and CASSINI (en route, at 4.0 AU, to Saturn). Several important points are noted: (1) this epoch

  3. Direct mapping rather than motor prediction subserves modulation of corticospinal excitability during observation of actions in real time.

    PubMed

    Gueugneau, Nicolas; Mc Cabe, Sofia I; Villalta, Jorge I; Grafton, Scott T; Della-Maggiore, Valeria

    2015-06-01

    Motor facilitation refers to the specific increment in corticospinal excitability (CSE) elicited by the observation of actions performed by others. To date, the precise nature of the mechanism at the basis of this phenomenon is unknown. One possibility is that motor facilitation is driven by a predictive process reminiscent of the role of forward models in motor control. Alternatively, motor facilitation may result from a model-free mechanism by which the basic elements of the observed action are directly mapped onto their cortical representations. Our study was designed to discern these alternatives. To this aim, we recorded the time course of CSE for the first dorsal interosseous (FDI) and the abductor digiti minimi (ADM) during observation of three grasping actions in real time, two of which strongly diverged in kinematics from their natural (invariant) form. Although artificially slow movements used in most action observation studies might enhance the observer's discrimination performance, the use of videos in real time is crucial to maintain the time course of CSE within the physiological range of daily actions. CSE was measured at 4 time points within a 240-ms window that best captured the kinematic divergence from the invariant form. Our results show that CSE of the FDI, not the ADM, closely follows the functional role of the muscle despite the mismatch between the natural and the divergent kinematics. We propose that motor facilitation during observation of actions performed in real time reflects the model-free coding of perceived movement following a direct mapping mechanism.

  4. Real-time Volcanic Cloud Products and Predictions for Aviation Alerts

    NASA Astrophysics Data System (ADS)

    Krotkov, N. A.; Hughes, E. J.; da Silva, A. M., Jr.; Seftor, C. J.; Brentzel, K. W.; Hassinen, S.; Heinrichs, T. A.; Schneider, D. J.; Hoffman, R.; Myers, T.; Flynn, L. E.; Niu, J.; Theys, N.; Brenot, H. H.

    2016-12-01

    We will discuss progress of the NASA ASP project, which promotes the use of satellite volcanic SO2 (VSO2) and Ash (VA) data, and forecasting tools that enhance VA Decision Support Systems (DSS) at the VA Advisory Centers (VAACs) for prompt aviation warnings. The goals are: (1) transition NASA algorithms to NOAA for global NRT processing and integration into DSS at Washington VAAC for operational users and public dissemination; (2) Utilize Direct Broadcast capability of the Aura and SNPP satellites to process Direct Readout (DR) data at two high latitude locations in Finland and Fairbanks, Alaska to enhance VA DSS in Europe and at USGS's Alaska Volcano Observatory (AVO) and Alaska-VAAC; (3) Improve global Eulerian model-based VA/VSO2 forecasting and risk/cost assessments with Metron Aviation. Our global NRT OMI and OMPS data have been fully integrated into European Support to Aviation Control Service and NOAA operational web sites. We are transitioning OMPS processing to our partners at NOAA/NESDIS to integrate into operational processing environment. NASA's Suomi NPP Ozone Science Team, in conjunction with GSFC's Direct Readout Laboratory (DRL), have implemented Version 2 of the OMPS real-time DR processing package to generate VSO2 and VA products at the Geographic Information Network of Alaska (GINA) and the Finnish Meteorological Institute (FMI). The system provides real-time coverage over some of the most congested airspace and over many of the most active volcanoes in the world. The OMPS real time capability is now publicly available via DRL's IPOPP package. We use satellite observations to define volcanic source term estimates in the NASA GOES-5 model, which was updated allowing for the simulation of VA and VSO2 clouds. Column SO2 observations from SNPP/OMPS provide an initial estimate of the total cloud SO2 mass, and are used with backward transport analysis to make an initial cloud height estimate. Later VSO2 observations are used to "nudge" the SO2 mass

  5. Real-time forecasting and predictability of catastrophic failure events: from rock failure to volcanoes and earthquakes

    NASA Astrophysics Data System (ADS)

    Main, I. G.; Bell, A. F.; Naylor, M.; Atkinson, M.; Filguera, R.; Meredith, P. G.; Brantut, N.

    2012-12-01

    Accurate prediction of catastrophic brittle failure in rocks and in the Earth presents a significant challenge on theoretical and practical grounds. The governing equations are not known precisely, but are known to produce highly non-linear behavior similar to those of near-critical dynamical systems, with a large and irreducible stochastic component due to material heterogeneity. In a laboratory setting mechanical, hydraulic and rock physical properties are known to change in systematic ways prior to catastrophic failure, often with significant non-Gaussian fluctuations about the mean signal at a given time, for example in the rate of remotely-sensed acoustic emissions. The effectiveness of such signals in real-time forecasting has never been tested before in a controlled laboratory setting, and previous work has often been qualitative in nature, and subject to retrospective selection bias, though it has often been invoked as a basis in forecasting natural hazard events such as volcanoes and earthquakes. Here we describe a collaborative experiment in real-time data assimilation to explore the limits of predictability of rock failure in a best-case scenario. Data are streamed from a remote rock deformation laboratory to a user-friendly portal, where several proposed physical/stochastic models can be analysed in parallel in real time, using a variety of statistical fitting techniques, including least squares regression, maximum likelihood fitting, Markov-chain Monte-Carlo and Bayesian analysis. The results are posted and regularly updated on the web site prior to catastrophic failure, to ensure a true and and verifiable prospective test of forecasting power. Preliminary tests on synthetic data with known non-Gaussian statistics shows how forecasting power is likely to evolve in the live experiments. In general the predicted failure time does converge on the real failure time, illustrating the bias associated with the 'benefit of hindsight' in retrospective analyses

  6. Evaluating the real-world predictive validity of the Body Image Quality of Life Inventory using Ecological Momentary Assessment.

    PubMed

    Heron, Kristin E; Mason, Tyler B; Sutton, Tiphanie G; Myers, Taryn A

    2015-09-01

    Perceptions of physical appearance, or body image, can affect psychosocial functioning and quality of life (QOL). The present study evaluated the real-world predictive validity of the Body Image Quality of Life Inventory (BIQLI) using Ecological Momentary Assessment (EMA). College women reporting subclinical disordered eating/body dissatisfaction (N=131) completed the BIQLI and related measures. For one week they then completed five daily EMA surveys of mood, social interactions, stress, and eating behaviors on palmtop computers. Results showed better body image QOL was associated with less negative affect, less overwhelming emotions, more positive affect, more pleasant social interactions, and higher self-efficacy for handling stress. Lower body image QOL was marginally related to less overeating and lower loss of control over eating in daily life. To our knowledge, this is the first study to support the real-world predictive validity of the BIQLI by identifying social, affective, and behavioral correlates in everyday life using EMA. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Enabling real time release testing by NIR prediction of dissolution of tablets made by continuous direct compression (CDC).

    PubMed

    Pawar, Pallavi; Wang, Yifan; Keyvan, Golshid; Callegari, Gerardo; Cuitino, Alberto; Muzzio, Fernando

    2016-10-15

    A method for predicting dissolution profiles of directly compressed tablets for a fixed sustained release formulation manufactured in a continuous direct compaction (CDC) system is presented. The methodology enables real-time release testing (RTRt). Tablets were made at a target drug concentration of 9% Acetaminophen, containing 90% lactose and 1% Magnesium Stearate, and at a target compression force of 24kN. A model for predicting dissolution profiles was developed using a 3(4-1) fractional factorial experimental design built around this targeted condition. Four variables were included: API concentration (low, medium, high), blender speed (150rpm, 200rpm, 250rpm), feed frame speed (20rpm, 25rpm, 30rpm), compaction force (8KN, 16KN, 24KN). The tablets thus obtained were scanned at-line in transmission mode using Near IR spectroscopy. The dissolution profiles were described using two approaches, a model-independent "shape and level" method, and a model-dependent approach based on Weibull's model. Multivariate regression was built between the NIR scores as the predictor variables and the dissolution profile parameters as the response. The model successfully predicted the dissolution profiles of the individual tablets (similarity factor, f2 ∼72) manufactured at the targeted set point. This is a first ever published manuscript addressing RTRt for dissolution prediction in continuous manufacturing, a novel and state of art technique for tablet manufacturing.

  8. Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.

    PubMed

    Basak, Chandramallika; Voss, Michelle W; Erickson, Kirk I; Boot, Walter R; Kramer, Arthur F

    2011-08-01

    Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 h to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes.

  9. Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study.

    PubMed

    Schilirò, Luca; Montrasio, Lorella; Scarascia Mugnozza, Gabriele

    2016-11-01

    In recent years, physically-based numerical models have frequently been used in the framework of early-warning systems devoted to rainfall-induced landslide hazard monitoring and mitigation. For this reason, in this work we describe the potential of SLIP (Shallow Landslides Instability Prediction), a simplified physically-based model for the analysis of shallow landslide occurrence. In order to test the reliability of this model, a back analysis of recent landslide events occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on October 1st, 2009 was performed. The simulation results have been compared with those obtained for the same event by using TRIGRS, another well-established model for shallow landslide prediction. Afterwards, a simulation over a 2-year span period has been performed for the same area, with the aim of evaluating the performance of SLIP as early warning tool. The results confirm the good predictive capability of the model, both in terms of spatial and temporal prediction of the instability phenomena. For this reason, we recommend an operating procedure for the real-time definition of shallow landslide triggering scenarios at the catchment scale, which is based on the use of SLIP calibrated through a specific multi-methodological approach.

  10. Optimal dose reduction in computed tomography methodologies predicted from real-time dosimetry

    NASA Astrophysics Data System (ADS)

    Tien, Christopher Jason

    Over the past two decades, computed tomography (CT) has become an increasingly common and useful medical imaging technique. CT is a noninvasive imaging modality with three-dimensional volumetric viewing abilities, all in sub-millimeter resolution. Recent national scrutiny on radiation dose from medical exams has spearheaded an initiative to reduce dose in CT. This work concentrates on dose reduction of individual exams through two recently-innovated dose reduction techniques: organ dose modulation (ODM) and tube current modulation (TCM). ODM and TCM tailor the phase and amplitude of x-ray current, respectively, used by the CT scanner during the scan. These techniques are unique because they can be used to achieve patient dose reduction without any appreciable loss in image quality. This work details the development of the tools and methods featuring real-time dosimetry which were used to provide pioneering measurements of ODM or TCM in dose reduction for CT.

  11. Real-time prediction of hydrocarbon emissions from liquid combustion systems

    SciTech Connect

    Barton, R.G.; Riale, M.; McCampbell, D.; VanDyne, M.

    1997-12-31

    A laboratory study was conducted to investigate the ability of heuristic computational techniques to predict hydrocarbon emissions using data from simple process and optical monitors. A mini-pilot scale combustion research facility located at Midwest Research Institute was used was used in the study. The facility`s operational and emissions characteristics have been well defined in previous studies. The facility was fired with fuel oil and operated at wide range of combustion conditions. All operating parameters including fuel feed rate, air feed rates and chamber temperature were monitored. In addition, a CCD-array video camera was used to monitor the flame. An array of conventional continuous emissions monitors for CO, CO{sub 2}, O{sub 2}, and THC sampled the exhaust gases. The operational data and the optical field data were combined with the emissions data to form a training data set for a neural network. The trained network was then used to predict the THC emissions.

  12. Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

    NASA Technical Reports Server (NTRS)

    Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

    2011-01-01

    A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

  13. Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues.

    PubMed

    Rapuano, Kristina M; Zieselman, Amanda L; Kelley, William M; Sargent, James D; Heatherton, Todd F; Gilbert-Diamond, Diane

    2017-01-03

    Obesity is a major public health concern that involves an interaction between genetic susceptibility and exposure to environmental cues (e.g., food marketing); however, the mechanisms that link these factors and contribute to unhealthy eating are unclear. Using a well-known obesity risk polymorphism (FTO rs9939609) in a sample of 78 children (ages 9-12 y), we observed that children at risk for obesity exhibited stronger responses to food commercials in the nucleus accumbens (NAcc) than children not at risk. Similarly, children at a higher genetic risk for obesity demonstrated larger NAcc volumes. Although a recessive model of this polymorphism best predicted body mass and adiposity, a dominant model was most predictive of NAcc size and responsivity to food cues. These findings suggest that children genetically at risk for obesity are predisposed to represent reward signals more strongly, which, in turn, may contribute to unhealthy eating behaviors later in life.

  14. Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues

    PubMed Central

    Rapuano, Kristina M.; Zieselman, Amanda L.; Kelley, William M.; Sargent, James D.; Heatherton, Todd F.

    2017-01-01

    Obesity is a major public health concern that involves an interaction between genetic susceptibility and exposure to environmental cues (e.g., food marketing); however, the mechanisms that link these factors and contribute to unhealthy eating are unclear. Using a well-known obesity risk polymorphism (FTO rs9939609) in a sample of 78 children (ages 9–12 y), we observed that children at risk for obesity exhibited stronger responses to food commercials in the nucleus accumbens (NAcc) than children not at risk. Similarly, children at a higher genetic risk for obesity demonstrated larger NAcc volumes. Although a recessive model of this polymorphism best predicted body mass and adiposity, a dominant model was most predictive of NAcc size and responsivity to food cues. These findings suggest that children genetically at risk for obesity are predisposed to represent reward signals more strongly, which, in turn, may contribute to unhealthy eating behaviors later in life. PMID:27994159

  15. Improved methods for computing drag corrected missile impact predictions in real time

    NASA Astrophysics Data System (ADS)

    Kuzanek, J. F.

    1980-06-01

    During missile flight tests at White Sands Missile Range (WSMR), position data on the current status of the missile is transmitted 20 times per second from radar sites to a Univac 1108 computer. Consecutive pairs of such data are averaged 10 times per second and computations for plotting displays such as current position, range verses altitude, or impact prediction are based upon this averaged data. In the event that a missile veers from its planned trajectory, it will be necessary to determine thrust to prevent the missile from impacting in a populated area. For this reason, the Range Safety Officer (RSO) requires that for each computational cycle (10 per second) an instantaneous impact prediction (IIP) of the missile be computed. This point is the intersection of the missile trajectory, should thrust be terminated, with the Clarke Spheroid (of 1866) model of the Earth at an altitude of 4000 feet.

  16. Real time estimation and prediction of ship motions using Kalman filtering techniques

    NASA Technical Reports Server (NTRS)

    Triantafyllou, M. A.; Bodson, M.; Athans, M.

    1982-01-01

    A landing scheme for landing V/STOL aircraft on rolling ships was sought using computerized simulations. The equations of motion as derived from hydrodynamics, their form and the physical mechanisms involved and the general form of the approximation are discussed. The modeling of the sea is discussed. The derivation of the state-space equations for the DD-963 destroyer is described. Kalman filter studies are presented and the influence of the various parameters is assessed. The effect of various modeling parameters on the rms error is assessed and simplifying conclusions are drawn. An upper bound for prediction time of about five seconds is established, with the exception of roll, which can be predicted up to ten seconds ahead.

  17. A prediction tool for real-time application in the disruption protection system at JET

    NASA Astrophysics Data System (ADS)

    Cannas, B.; Fanni, A.; Sonato, P.; Zedda, M. K.; contributors, JET-EFDA

    2007-11-01

    A disruption prediction system, based on neural networks, is presented in this paper. The system is ideally suitable for on-line application in the disruption avoidance and/or mitigation scheme at the JET tokamak. A multi-layer perceptron (MLP) predictor module has been trained on nine plasma diagnostic signals extracted from 86 disruptive pulses, selected from four years of JET experiments in the pulse range 47830-57346 (from 1999 to 2002). The disruption class of the disruptive pulses is available. In particular, the selected pulses belong to four classes (density limit/high radiated power, internal transport barrier, mode lock and h-mode/l-mode). A self-organizing map has been used to select the samples of the pulses to train the MLP predictor module and to determine its target, increasing the prediction capability of the system. The prediction performance has been tested over 86 disruptive and 102 non-disruptive pulses. The test has been performed presenting to the network all the samples of each pulse sampled every 20 ms. The missed alarm rate and the false alarm rate of the predictor, up to 100 ms prior to the disruption time, are 23% and 1%, respectively. Recent plasma configurations might present features different from those observed in the experiments used in the training set. This 'novelty' can lead to incorrect behaviour of the predictor. To improve the robustness and reliability of the system, a novelty detection module has been integrated in the prediction system, increasing the system performance and resulting in a missed alarm rate reduced to 7% and a false alarm rate reduced to 0%.

  18. Real Gas: CFD Prediction Methodology Flow Physics for Entry Capsule Mission Scenarios

    NASA Technical Reports Server (NTRS)

    Deiwert, George S.

    1997-01-01

    Mission and concept studies for space exploration are described for the purpose of identifying flow physics for entry capsule mission scenarios. These studies are a necessary precursor to the development and application of CFD prediction methodology for capsule aerothermodynamics. The scope of missions considered includes manned and unmanned cislunar missions, missions to the minor planets, and missions to the major planets and other celestial objects in the solar system.

  19. Real Gas: CFD Prediction Methodology Flow Physics for Entry Capsule Mission Scenarios

    NASA Technical Reports Server (NTRS)

    Deiwert, George S.

    1997-01-01

    Mission and concept studies for space exploration are described for the purpose of identifying flow physics for entry capsule mission scenarios. These studies are a necessary precursor to the development and application of CFD prediction methodology for capsule aerothermodynamics. The scope of missions considered includes manned and unmanned cislunar missions, missions to the minor planets, and missions to the major planets and other celestial objects in the solar system.

  20. Predicting Real Optimized Materials: Novel Nitrogen-Containing Fullerenes and Nanotubes

    SciTech Connect

    Manaa, M R

    2003-07-15

    We propose to investigate the possible configurations, electronic, conducting and energetic properties of nitrogen-containing carbon fullerenes and single-walled nanotubes with nitrogen contents up to 30% using first principle density functional theoretical calculations. The proposed research allows for a predictive method to control the electronic properties of fullerenes and nanotubes that could pave the way for controlled fabrication of molecular circuits and nanotube networks.

  1. OceanNOMADS: Real-time and retrospective access to operational U.S. ocean prediction products

    NASA Astrophysics Data System (ADS)

    Harding, J. M.; Cross, S. L.; Bub, F.; Ji, M.

    2011-12-01

    The National Oceanic and Atmospheric Administration (NOAA) National Operational Model Archive and Distribution System (NOMADS) provides both real-time and archived atmospheric model output from servers at the National Centers for Environmental Prediction (NCEP) and National Climatic Data Center (NCDC) respectively (http://nomads.ncep.noaa.gov/txt_descriptions/marRutledge-1.pdf). The NOAA National Ocean Data Center (NODC) with NCEP is developing a complementary capability called OceanNOMADS for operational ocean prediction models. An NCEP ftp server currently provides real-time ocean forecast output (http://www.opc.ncep.noaa.gov/newNCOM/NCOM_currents.shtml) with retrospective access through NODC. A joint effort between the Northern Gulf Institute (NGI; a NOAA Cooperative Institute) and the NOAA National Coastal Data Development Center (NCDDC; a division of NODC) created the developmental version of the retrospective OceanNOMADS capability (http://www.northerngulfinstitute.org/edac/ocean_nomads.php) under the NGI Ecosystem Data Assembly Center (EDAC) project (http://www.northerngulfinstitute.org/edac/). Complementary funding support for the developmental OceanNOMADS from U.S. Integrated Ocean Observing System (IOOS) through the Southeastern University Research Association (SURA) Model Testbed (http://testbed.sura.org/) this past year provided NODC the analogue that facilitated the creation of an NCDDC production version of OceanNOMADS (http://www.ncddc.noaa.gov/ocean-nomads/). Access tool development and storage of initial archival data sets occur on the NGI/NCDDC developmental servers with transition to NODC/NCCDC production servers as the model archives mature and operational space and distribution capability grow. Navy operational global ocean forecast subsets for U.S waters comprise the initial ocean prediction fields resident on the NCDDC production server. The NGI/NCDDC developmental server currently includes the Naval Research Laboratory Inter-America Seas

  2. Sub-seasonal Predictability of Heavy Precipitation Events: Implication for Real-time Flood Management in Iran

    NASA Astrophysics Data System (ADS)

    Najafi, H.; Shahbazi, A.; Zohrabi, N.; Robertson, A. W.; Mofidi, A.; Massah Bavani, A. R.

    2016-12-01

    Each year, a number of high impact weather events occur worldwide. Since any level of predictability at sub-seasonal to seasonal timescale is highly beneficial to society, international efforts is now on progress to promote reliable Ensemble Prediction Systems for monthly forecasts within the WWRP/WCRP initiative (S2S) project and North American Multi Model Ensemble (NMME). For water resources managers in the face of extreme events, not only can reliable forecasts of high impact weather events prevent catastrophic losses caused by floods but also contribute to benefits gained from hydropower generation and water markets. The aim of this paper is to analyze the predictability of recent severe weather events over Iran. Two recent heavy precipitations are considered as an illustration to examine whether S2S forecasts can be used for developing flood alert systems especially where large cascade of dams are in operation. Both events have caused major damages to cities and infrastructures. The first severe precipitation was is in the early November 2015 when heavy precipitation (more than 50 mm) occurred in 2 days. More recently, up to 300 mm of precipitation is observed within less than a week in April 2016 causing a consequent flash flood. Over some stations, the observed precipitation was even more than the total annual mean precipitation. To analyze the predictive capability, ensemble forecasts from several operational centers including (European Centre for Medium-Range Weather Forecasts (ECMWF) system, Climate Forecast System Version 2 (CFSv2) and Chinese Meteorological Center (CMA) are evaluated. It has been observed that significant changes in precipitation anomalies were likely to be predicted days in advance. The next step will be to conduct thorough analysis based on comparing multi-model outputs over the full hindcast dataset developing real-time high impact weather prediction systems.

  3. Teachers Teaching Teachers (T3). Volume 6, Number 2

    ERIC Educational Resources Information Center

    Armstrong, Anthony, Ed.

    2010-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Standing Up, Speaking Out: Teacher Voices Lift to Influence National Policy (Anthony Armstrong); (2) Tool: Develop a Relationship…

  4. Teachers Teaching Teachers (T3) [TM]. Vol. 2 No. 7

    ERIC Educational Resources Information Center

    Richardson, Joan, Ed.

    2007-01-01

    This issue of "Teachers Teaching Teachers" ("T3") focuses on coaches' role in the professional development of teachers. It contains the following articles: (1) An Excerpt from "Taking the Lead" (Joellen Killion and Cindy Harrison); (2) Be Like a Virus and Connect (Bill Ferriter); (3) No. 1 Resource Has a Human Face (Joellen Killion); (4) With This…

  5. T3 translational science in gastroenterology: getting to best outcomes.

    PubMed

    Crandall, Wallace

    2013-12-01

    Achieving the best possible outcomes requires the reliable implementation of best practices for every patient. Specifically, optimizing outcomes requires a spectrum of research spanning basic science, drug development, clinical efficacy and effectiveness, health services, quality improvement, and implementation research. However, our rapid increase in understanding the mechanisms of health and disease and their treatment has far outpaced our ability to reliably provide that care, resulting in poor reliability and enormous variation in care. T3 translational research studies attempt to answer questions surrounding reliable implementation of interventions, decreasing variations in care, and spreading effective therapies. To answer these questions, T3 research may use traditional research methodology such as randomized controlled trials (RCTs); however, various other approaches such as quasiexperimental designs (eg, time-series analysis) are often used. Although uncommon, T3 research has shown promise in not only improving process measures such as correct dosing of medications, but also outcome measures such as improved remission rates in patients with IBD. A more complete integration of T3 translational research into the more traditional research continuum is necessary if we are to achieve the best possible outcomes for our patients. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

  6. Teachers Teaching Teachers (T3)[TM]. Volume 4, Number 6

    ERIC Educational Resources Information Center

    von Frank, Valerie, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Values and Clarity Build Classroom Language (Valerie von Frank); (2) Tools: Identifying and Clarifying Beliefs about Learning; (3)…

  7. Teachers Teaching Teachers (T3) [TM]. Vol. 2 No. 7

    ERIC Educational Resources Information Center

    Richardson, Joan, Ed.

    2007-01-01

    This issue of "Teachers Teaching Teachers" ("T3") focuses on coaches' role in the professional development of teachers. It contains the following articles: (1) An Excerpt from "Taking the Lead" (Joellen Killion and Cindy Harrison); (2) Be Like a Virus and Connect (Bill Ferriter); (3) No. 1 Resource Has a Human Face (Joellen Killion); (4) With This…

  8. Teachers Teaching Teachers (T3)[TM]. Volume 5, Number 2

    ERIC Educational Resources Information Center

    Crow, Tracy, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Sharpening Skills for Our Century (Valerie von Frank); (2) Lessons from a Coach: First, I Assess How Teachers Learn (Julie…

  9. Teachers Teaching Teachers (T3)[TM]. Volume 5, Number 4

    ERIC Educational Resources Information Center

    Crow, Tracy, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Weekend Wisdom: Stimulus Funds Boost Professional Learning and Add Saturday Option (Valerie von Frank); (2) Lessons from a Coach:…

  10. Teachers Teaching Teachers (T3)[TM]. Volume 5, Number 1

    ERIC Educational Resources Information Center

    von Frank, Valerie, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Districts Harness the Expertise of Classroom Teachers (Valerie von Frank); (2) Tool: Measuring Collaborative…

  11. Teachers Teaching Teachers (T3). Volume 6, Number 2

    ERIC Educational Resources Information Center

    Armstrong, Anthony, Ed.

    2010-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Standing Up, Speaking Out: Teacher Voices Lift to Influence National Policy (Anthony Armstrong); (2) Tool: Develop a Relationship…

  12. Teachers Teaching Teachers (T3)[TM]. Volume 4, Number 8

    ERIC Educational Resources Information Center

    von Frank, Valerie, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Tackling Behavior from All Sides (Valerie von Frank); (2) Tools: Effective Behavior Support Self-Assessment Survey; (3) Lessons from…

  13. Teachers Teaching Teachers (T3)[TM]. Volume 4, Number 7

    ERIC Educational Resources Information Center

    von Frank, Valerie, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Learning Cycle Spins Individuals into a Team (Valerie von Frank); (2) NSDC Tool: The Professional Teaching and Learning Cycle; (3)…

  14. Teachers Teaching Teachers (T3)[TM]. Volume 4, Number 4

    ERIC Educational Resources Information Center

    von Frank, Valerie, Ed.

    2008-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' role in the professional development of teachers, exploring challenges and rewards that teacher leaders encounter. This issue includes: (1) Making a Serious Study of Classroom Scenes: High School Faculty Develops Away to Observe and Learn from Each Other (Valerie von Frank); (2) Tools for…

  15. Teachers Teaching Teachers (T3). Volume 6, Number 3

    ERIC Educational Resources Information Center

    Armstrong, Anthony, Ed.

    2010-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Teaching English Language Learners: Mainstream Teachers Make a Stellar Journey as a Team to Transform Classroom Practices (Elsa M.…

  16. Teachers Teaching Teachers (T3). Volume 6, Number 1

    ERIC Educational Resources Information Center

    Armstrong, Anthony, Ed.

    2010-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Collective Responsibility Makes All Teachers the Best (Stephanie Hirsh); (2) Tools: How Our School Measures up/Exploring Our…

  17. Teachers Teaching Teachers (T3)[TM]. Volume 5, Number 3

    ERIC Educational Resources Information Center

    Crow, Tracy, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' roles in the professional development of teachers. Each issue also explores the challenges and rewards that teacher leaders encounter. This issue includes: (1) Building Bridges: Data Help Instructional Coach Make Vital Connections with Teachers (Theresa Long); (2) NSDC Tool: Instructional…

  18. Teachers Teaching Teachers (T3)[TM]. Volume 4, Number 5

    ERIC Educational Resources Information Center

    von Frank, Valerie, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' role in the professional development of teachers, exploring challenges and rewards that teacher leaders encounter. This issue includes: (1) Call to Action: Landmark Study on Professional Learning Calls to Teacher Leaders (Joellen Killion); (2) Tools: Hone Your Understanding of Effective…

  19. Teachers Teaching Teachers (T3)[TM]. Volume 4, Number 5

    ERIC Educational Resources Information Center

    von Frank, Valerie, Ed.

    2009-01-01

    "Teachers Teaching Teachers" ("T3") focuses on coaches' role in the professional development of teachers, exploring challenges and rewards that teacher leaders encounter. This issue includes: (1) Call to Action: Landmark Study on Professional Learning Calls to Teacher Leaders (Joellen Killion); (2) Tools: Hone Your Understanding of Effective…

  20. Predicting complex syntactic structure in real time: Processing of negative sentences in Russian.

    PubMed

    Kazanina, Nina

    2016-09-19

    In Russian negative sentences the verb's direct object may appear either in the accusative case, which is licensed by the verb (as is common cross-linguistically), or in the genitive case, which is licensed by the negation (Russian-specific "genitive-of-negation" phenomenon). Such sentences were used to investigate whether case marking is employed for anticipating syntactic structure, and whether lexical heads other than the verb can be predicted on the basis of a case-marked noun phrase. Experiment 1, a completion task, confirmed that genitive-of-negation is part of Russian speakers' active grammatical repertoire. In Experiments 2 and 3, the genitive/accusative case manipulation on the preverbal object led to shorter reading times at the negation and verb in the genitive versus accusative condition. Furthermore, Experiment 3 manipulated linear order of the direct object and the negated verb in order to distinguish whether the abovementioned facilitatory effect was predictive or integrative in nature, and concluded that the parser actively predicts a verb and (otherwise optional) negation on the basis of a preceding genitive-marked object. Similarly to a head-final language, case-marking information on preverbal noun phrases (NPs) is used by the parser to enable incremental structure building in a free-word-order language such as Russian.

  1. Wireless Wearable Multisensory Suite and Real-Time Prediction of Obstructive Sleep Apnea Episodes.

    PubMed

    Le, Trung Q; Cheng, Changqing; Sangasoongsong, Akkarapol; Wongdhamma, Woranat; Bukkapatnam, Satish T S

    2013-01-01

    Obstructive sleep apnea (OSA) is a common sleep disorder found in 24% of adult men and 9% of adult women. Although continuous positive airway pressure (CPAP) has emerged as a standard therapy for OSA, a majority of patients are not tolerant to this treatment, largely because of the uncomfortable nasal air delivery during their sleep. Recent advances in wireless communication and advanced ("bigdata") preditive analytics technologies offer radically new point-of-care treatment approaches for OSA episodes with unprecedented comfort and afforadability. We introduce a Dirichlet process-based mixture Gaussian process (DPMG) model to predict the onset of sleep apnea episodes based on analyzing complex cardiorespiratory signals gathered from a custom-designed wireless wearable multisensory suite. Extensive testing with signals from the multisensory suite as well as PhysioNet's OSA database suggests that the accuracy of offline OSA classification is 88%, and accuracy for predicting an OSA episode 1-min ahead is 83% and 3-min ahead is 77%. Such accurate prediction of an impending OSA episode can be used to adaptively adjust CPAP airflow (toward improving the patient's adherence) or the torso posture (e.g., minor chin adjustments to maintain steady levels of the airflow).

  2. Wireless Wearable Multisensory Suite and Real-Time Prediction of Obstructive Sleep Apnea Episodes

    PubMed Central

    Cheng, Changqing; Sangasoongsong, Akkarapol; Wongdhamma, Woranat; Bukkapatnam, Satish T. S.

    2013-01-01

    Obstructive sleep apnea (OSA) is a common sleep disorder found in 24% of adult men and 9% of adult women. Although continuous positive airway pressure (CPAP) has emerged as a standard therapy for OSA, a majority of patients are not tolerant to this treatment, largely because of the uncomfortable nasal air delivery during their sleep. Recent advances in wireless communication and advanced (“bigdata”) preditive analytics technologies offer radically new point-of-care treatment approaches for OSA episodes with unprecedented comfort and afforadability. We introduce a Dirichlet process-based mixture Gaussian process (DPMG) model to predict the onset of sleep apnea episodes based on analyzing complex cardiorespiratory signals gathered from a custom-designed wireless wearable multisensory suite. Extensive testing with signals from the multisensory suite as well as PhysioNet's OSA database suggests that the accuracy of offline OSA classification is 88%, and accuracy for predicting an OSA episode 1-min ahead is 83% and 3-min ahead is 77%. Such accurate prediction of an impending OSA episode can be used to adaptively adjust CPAP airflow (toward improving the patient's adherence) or the torso posture (e.g., minor chin adjustments to maintain steady levels of the airflow). PMID:27170854

  3. A Real-time, Coupled, Refined Forecasting System for Coastal Prediction

    NASA Astrophysics Data System (ADS)

    Armstrong, B. N.; Warner, J. C.; Signell, R. P.

    2010-12-01

    In the coastal zone, storms are one of the primary environmental forces causing coastal change. These discrete events often produce large waves, storm surges, and flooding, resulting in coastal erosion. In addition, strong storm-generated currents may pose threats to life, property, and navigation. The ability to predict these events, their location, duration, and magnitude allows resource managers to better prepare for the storm impacts as well as guide post-storm survey assessments and recovery efforts. As a step towards increasing our capability for prediction of these events and to help us study the physical processes that occur we have developed an automated system to run components of the Coupled Ocean - Atmosphere - Wave - Sediment Transport (COAWST) Modeling System as a daily forecast. The current daily system couples Regional Ocean Model System (ROMS) and Simulation Waves Nearshore (SWAN) models to predict currents, salinity, temperature, wave height and direction, and sediment transport for the US East Coast and Gulf of Mexico on a 5 km scale. As part of the system a refined grid for the area of Cape Hatteras, NC at a resolution of 1 km is included. Management of the system is controlled by the Windows Scheduler to start Matlab® and run scripts and functions. Data required by the modeling system include daily modeled wave, wind, atmospheric surface inputs, and climatology fields. The Unidata Internet Data Distribution/Local Data Manager (http://www.unidata.ucar.edu/software/ldm/) is used to download National Centers for Environmental Prediction (NCEP) GFS global 5 degree data and NCEP NAM Conus 12km data to a local server. The Matlab “structs” tool and NJ-Toolbox (http://njtbx.sourceforge.net/njdocs/njtbxhelp/njtbxhelp.html) are used to access these large data sets on the local server as well as Wave Watch 3 (WW3) and NCEP model data sets available remotely on the Nomads http://nomads.ncep.noaa.gov site and Hybrid Coordinate Ocean Model (HYCOM) data

  4. Establishing a Real-Money Prediction Market for Climate on Decadal Horizons

    NASA Astrophysics Data System (ADS)

    Roulston, M. S.; Hand, D. J.; Harding, D. W.

    2016-12-01

    A plan to establish a not-for-profit prediction market that will allow participants to bet on the value of selected climate variables decades into the future will be presented. It is hoped that this market will provide an objective measure of the consensus view on climate change, including information concerning the uncertainty of climate projections. The proposed design of the market and the definition of the climate variables underlying the contracts will be discussed, as well as relevant regulatory and legal issues.

  5. Improving the effectiveness of real-time flood forecasting through Predictive Uncertainty estimation: the multi-temporal approach

    NASA Astrophysics Data System (ADS)

    Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Todini, Ezio

    2015-04-01

    The negative effects of severe flood events are usually contrasted through structural measures that, however, do not fully eliminate flood risk. Non-structural measures, such as real-time flood forecasting and warning, are also required. Accurate stage/discharge future predictions with appropriate forecast lead-time are sought by decision-makers for implementing strategies to mitigate the adverse effects of floods. Traditionally, flood forecasting has been approached by using rainfall-runoff and/or flood routing modelling. Indeed, both types of forecasts, cannot be considered perfectly representing future outcomes because of lacking of a complete knowledge of involved processes (Todini, 2004). Nonetheless, although aware that model forecasts are not perfectly representing future outcomes, decision makers are de facto implicitly assuming the forecast of water level/discharge/volume, etc. as "deterministic" and coinciding with what is going to occur. Recently the concept of Predictive Uncertainty (PU) was introduced in hydrology (Krzysztofowicz, 1999), and several uncertainty processors were developed (Todini, 2008). PU is defined as the probability of occurrence of the future realization of a predictand (water level/discharge/volume) conditional on: i) prior observations and knowledge, ii) the available information obtained on the future value, typically provided by one or more forecast models. Unfortunately, PU has been frequently interpreted as a measure of lack of accuracy rather than the appropriate tool allowing to take the most appropriate decisions, given a model or several models' forecasts. With the aim to shed light on the benefits for appropriately using PU, a multi-temporal approach based on the MCP approach (Todini, 2008; Coccia and Todini, 2011) is here applied to stage forecasts at sites along the Upper Tiber River. Specifically, the STAge Forecasting-Rating Curve Model Muskingum-based (STAFOM-RCM) (Barbetta et al., 2014) along with the Rating

  6. Utilizing the eigenvectors of freeway loop data spatiotemporal schematic for real time crash prediction.

    PubMed

    Fang, Shou'en; Xie, Wenjing; Wang, Junhua; Ragland, David R

    2016-09-01

    The concept of crash precursor identification is gaining more practicality due to the recent advancements in Advanced Transportation Management and Information Systems. Investigating the shortcomings of the existing models, this paper proposes a new method to model the real time crash likelihood based on loop data through schematic eigenvectors. Firstly, traffic volume, occupancy and density spatiotemporal schematics in certain duration before an accident occurrence were constructed to describe the traffic flow status. Secondly, eigenvectors and eigenvalues of the spatiotemporal schematics were extracted to represent traffic volume, occupancy and density situation before the crash occurrence. Thirdly, by setting the vectors in crash time as case and those at crash free time as control, a logistic model is constructed to identify the crash precursors. Results show that both the eigenvectors and eigenvalues can significantly impact the accident likelihood compared to the previous study, the proposed model has the advantage of avoiding multicollinearity, better reflection of the overall traffic flow status before the crash, and improving missing data problem of loop detectors.

  7. Prediction and real-time compensation of qubit decoherence via machine learning.

    PubMed

    Mavadia, Sandeep; Frey, Virginia; Sastrawan, Jarrah; Dona, Stephen; Biercuk, Michael J

    2017-01-16

    The wide-ranging adoption of quantum technologies requires practical, high-performance advances in our ability to maintain quantum coherence while facing the challenge of state collapse under measurement. Here we use techniques from control theory and machine learning to predict the future evolution of a qubit's state; we deploy this information to suppress stochastic, semiclassical decoherence, even when access to measurements is limited. First, we implement a time-division multiplexed approach, interleaving measurement periods with periods of unsupervised but stabilised operation during which qubits are available, for example, in quantum information experiments. Second, we employ predictive feedback during sequential but time delayed measurements to reduce the Dick effect as encountered in passive frequency standards. Both experiments demonstrate significant improvements in qubit-phase stability over 'traditional' measurement-based feedback approaches by exploiting time domain correlations in the noise processes. This technique requires no additional hardware and is applicable to all two-level quantum systems where projective measurements are possible.

  8. Prediction and real-time compensation of qubit decoherence via machine learning

    NASA Astrophysics Data System (ADS)

    Mavadia, Sandeep; Frey, Virginia; Sastrawan, Jarrah; Dona, Stephen; Biercuk, Michael J.

    2017-01-01

    The wide-ranging adoption of quantum technologies requires practical, high-performance advances in our ability to maintain quantum coherence while facing the challenge of state collapse under measurement. Here we use techniques from control theory and machine learning to predict the future evolution of a qubit's state; we deploy this information to suppress stochastic, semiclassical decoherence, even when access to measurements is limited. First, we implement a time-division multiplexed approach, interleaving measurement periods with periods of unsupervised but stabilised operation during which qubits are available, for example, in quantum information experiments. Second, we employ predictive feedback during sequential but time delayed measurements to reduce the Dick effect as encountered in passive frequency standards. Both experiments demonstrate significant improvements in qubit-phase stability over `traditional' measurement-based feedback approaches by exploiting time domain correlations in the noise processes. This technique requires no additional hardware and is applicable to all two-level quantum systems where projective measurements are possible.

  9. Prediction and real-time compensation of qubit decoherence via machine learning

    PubMed Central

    Mavadia, Sandeep; Frey, Virginia; Sastrawan, Jarrah; Dona, Stephen; Biercuk, Michael J.

    2017-01-01

    The wide-ranging adoption of quantum technologies requires practical, high-performance advances in our ability to maintain quantum coherence while facing the challenge of state collapse under measurement. Here we use techniques from control theory and machine learning to predict the future evolution of a qubit's state; we deploy this information to suppress stochastic, semiclassical decoherence, even when access to measurements is limited. First, we implement a time-division multiplexed approach, interleaving measurement periods with periods of unsupervised but stabilised operation during which qubits are available, for example, in quantum information experiments. Second, we employ predictive feedback during sequential but time delayed measurements to reduce the Dick effect as encountered in passive frequency standards. Both experiments demonstrate significant improvements in qubit-phase stability over ‘traditional' measurement-based feedback approaches by exploiting time domain correlations in the noise processes. This technique requires no additional hardware and is applicable to all two-level quantum systems where projective measurements are possible. PMID:28090085

  10. Mining big data to extract patterns and predict real-life outcomes.

    PubMed

    Kosinski, Michal; Wang, Yilun; Lakkaraju, Himabindu; Leskovec, Jure

    2016-12-01

    This article aims to introduce the reader to essential tools that can be used to obtain insights and build predictive models using large data sets. Recent user proliferation in the digital environment has led to the emergence of large samples containing a wealth of traces of human behaviors, communication, and social interactions. Such samples offer the opportunity to greatly improve our understanding of individuals, groups, and societies, but their analysis presents unique methodological challenges. In this tutorial, we discuss potential sources of such data and explain how to efficiently store them. Then, we introduce two methods that are often employed to extract patterns and reduce the dimensionality of large data sets: singular value decomposition and latent Dirichlet allocation. Finally, we demonstrate how to use dimensions or clusters extracted from data to build predictive models in a cross-validated way. The text is accompanied by examples of R code and a sample data set, allowing the reader to practice the methods discussed here. A companion website (http://dataminingtutorial.com) provides additional learning resources. (PsycINFO Database Record

  11. Becoming popular: interpersonal emotion regulation predicts relationship formation in real life social networks

    PubMed Central

    Niven, Karen; Garcia, David; van der Löwe, Ilmo; Holman, David; Mansell, Warren

    2015-01-01

    Building relationships is crucial for satisfaction and success, especially when entering new social contexts. In the present paper, we investigate whether attempting to improve others’ feelings helps people to make connections in new networks. In Study 1, a social network study following new networks of people for a 12-week period indicated that use of interpersonal emotion regulation (IER) strategies predicted growth in popularity, as indicated by other network members’ reports of spending time with the person, in work and non-work interactions. In Study 2, linguistic analysis of the tweets from over 8000 Twitter users from formation of their accounts revealed that use of IER predicted greater popularity in terms of the number of followers gained. However, not all types of IER had positive effects. Behavioral IER strategies (which use behavior to reassure or comfort in order to regulate affect) were associated with greater popularity, while cognitive strategies (which change a person’s thoughts about his or her situation or feelings in order to regulate affect) were negatively associated with popularity. Our findings have implications for our understanding of how new relationships are formed, highlighting the important the role played by intentional emotion regulatory processes. PMID:26483718

  12. Becoming popular: interpersonal emotion regulation predicts relationship formation in real life social networks.

    PubMed

    Niven, Karen; Garcia, David; van der Löwe, Ilmo; Holman, David; Mansell, Warren

    2015-01-01

    Building relationships is crucial for satisfaction and success, especially when entering new social contexts. In the present paper, we investigate whether attempting to improve others' feelings helps people to make connections in new networks. In Study 1, a social network study following new networks of people for a 12-week period indicated that use of interpersonal emotion regulation (IER) strategies predicted growth in popularity, as indicated by other network members' reports of spending time with the person, in work and non-work interactions. In Study 2, linguistic analysis of the tweets from over 8000 Twitter users from formation of their accounts revealed that use of IER predicted greater popularity in terms of the number of followers gained. However, not all types of IER had positive effects. Behavioral IER strategies (which use behavior to reassure or comfort in order to regulate affect) were associated with greater popularity, while cognitive strategies (which change a person's thoughts about his or her situation or feelings in order to regulate affect) were negatively associated with popularity. Our findings have implications for our understanding of how new relationships are formed, highlighting the important the role played by intentional emotion regulatory processes.

  13. 3D Markov Process for Traffic Flow Prediction in Real-Time

    PubMed Central

    Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi

    2016-01-01

    Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further. PMID:26821025

  14. The effects of COST on the differentiation of 3T3-L1 preadipocytes and the mechanism of action.

    PubMed

    Kong, Shang; Ding, Chen; Huang, Lanlan; Bai, Yan; Xiao, Tiancun; Guo, Jiao; Su, Zhengquan

    2017-02-01

    The objectives of this study were to explore the effect of COST (one thousand Da molecular weight chitosan oligosaccharide) on the differentiation of 3T3-L1 preadipocytes and to determine the mechanism of action. 3T3-L1 preadipocytes were used as the target cells, and the induction of the methods for the differentiation of 3T3-L1 preadipocytes was based on classic cocktails. The MTT assay was used to filtrate the concentration of COST. On the 6th day of induced-differentiation, the differentiation of 3T3-L1 cells was detected by Oil Red O staining. The expression of PPARγ and C/EBPα mRNA was determined using real-time fluorescence quantitative PCR (Q-PCR). COST inhibited 3T3-L1 preadipocyte differentiation in a dose-dependent manner and decreased lipid accumulation. At the molecular level, the expression of the transcription factors, PPARγ and C/EBPα, was reduced by COST during adipogenesis. These results indicate that COST effectively inhibited the differentiation of 3T3-L1 preadipocytes. The mechanism is related to the down-regulation expression of PPARγ and C/EBPα.

  15. Surface Temperature Variation Prediction Model Using Real-Time Weather Forecasts

    NASA Astrophysics Data System (ADS)

    Karimi, M.; Vant-Hull, B.; Nazari, R.; Khanbilvardi, R.

    2015-12-01

    Combination of climate change and urbanization are heating up cities and putting the lives of millions of people in danger. More than half of the world's total population resides in cities and urban centers. Cities are experiencing urban Heat Island (UHI) effect. Hotter days are associated with serious health impacts, heart attaches and respiratory and cardiovascular diseases. Densely populated cities like Manhattan, New York can be affected by UHI impact much more than less populated cities. Even though many studies have been focused on the impact of UHI and temperature changes between urban and rural air temperature, not many look at the temperature variations within a city. These studies mostly use remote sensing data or typical measurements collected by local meteorological station networks. Local meteorological measurements only have local coverage and cannot be used to study the impact of UHI in a city and remote sensing data such as MODIS, LANDSAT and ASTER have with very low resolution which cannot be used for the purpose of this study. Therefore, predicting surface temperature in urban cities using weather data can be useful.Three months of Field campaign in Manhattan were used to measure spatial and temporal temperature variations within an urban setting by placing 10 fixed sensors deployed to measure temperature, relative humidity and sunlight. Fixed instrument shelters containing relative humidity, temperature and illumination sensors were mounted on lampposts in ten different locations in Manhattan (Vant-Hull et al, 2014). The shelters were fixed 3-4 meters above the ground for the period of three months from June 23 to September 20th of 2013 making measurements with the interval of 3 minutes. These high resolution temperature measurements and three months of weather data were used to predict temperature variability from weather forecasts. This study shows that the amplitude of spatial and temporal variation in temperature for each day can be predicted

  16. Forecasting of Real Thunderstorms based on Electric Parameters Calculations in Numerical Weather Prediction Models

    NASA Astrophysics Data System (ADS)

    Dementyeva, Svetlana; Ilin, Nikolay; Shatalina, Maria; Mareev, Evgeny

    2016-04-01

    Now-casting and long-term forecasting of lightning flashes occurrence are urgent problems from different points of view. There are several approaches to predicting lightning activity using indirect non-electrical parameters based on the relationship of lightning flashes with vertical fluxes of solid-phased hydrometeors but for more explicit forecasting of the lightning flashes occurrence electric processes should be considered. In addition, a factor playing a key role for now-casting of lightning activity is the earliness. We have proposed an algorithm, which makes the process of thunderstorms prediction automatic (due to automatic start of the electric parameters calculation) and quick (due to the use of simplified methods). Our forecasting was based on the use of Weather Research and Forecasting (WRF) model, which does not include the electrification processes, but it was supplemented with two modules. The first is an algorithm, which allows us to select thunderstorm events indirectly. It is based on such characteristics of thunderclouds and thunderstorms as radar reflectivity, duration and area and provides us with information about an approximate beginning and duration of the thunderstorm. The second module is a method for electric parameters calculations, which we have proposed before. It was suggested that the non-inductive mechanism of charge generation and separation plays a key role in the thundercloud electrification processes. Also charge densities of solid-phased hydrometeors are assumed to be proportional to their mass in elementary air volume. According to the models by Saunders and Takahashi, particles change the sign of charge while getting into the lower part of thundercloud from the upper and vice versa. Electric neutrality in the vertical air column was supposed in the course of vertical charge separation due to collisions between falling graupels and carried upward ice crystals. Electric potential (and consequently electric field) can be found

  17. Flood Foresight: A near-real time flood monitoring and forecasting tool for rapid and predictive flood impact assessment

    NASA Astrophysics Data System (ADS)

    Revilla-Romero, Beatriz; Shelton, Kay; Wood, Elizabeth; Berry, Robert; Bevington, John; Hankin, Barry; Lewis, Gavin; Gubbin, Andrew; Griffiths, Samuel; Barnard, Paul; Pinnell, Marc; Huyck, Charles

    2017-04-01

    The hours and days immediately after a major flood event are often chaotic and confusing, with first responders rushing to mobilise emergency responders, provide alleviation assistance and assess loss to assets of interest (e.g., population, buildings or utilities). Preparations in advance of a forthcoming event are becoming increasingly important; early warning systems have been demonstrated to be useful tools for decision markers. The extent of damage, human casualties and economic loss estimates can vary greatly during an event, and the timely availability of an accurate flood extent allows emergency response and resources to be optimised, reduces impacts, and helps prioritise recovery. In the insurance sector, for example, insurers are under pressure to respond in a proactive manner to claims rather than waiting for policyholders to report losses. Even though there is a great demand for flood inundation extents and severity information in different sectors, generating flood footprints for large areas from hydraulic models in real time remains a challenge. While such footprints can be produced in real time using remote sensing, weather conditions and sensor availability limit their ability to capture every single flood event across the globe. In this session, we will present Flood Foresight (www.floodforesight.com), an operational tool developed to meet the universal requirement for rapid geographic information, before, during and after major riverine flood events. The tool provides spatial data with which users can measure their current or predicted impact from an event - at building, basin, national or continental scales. Within Flood Foresight, the Screening component uses global rainfall predictions to provide a regional- to continental-scale view of heavy rainfall events up to a week in advance, alerting the user to potentially hazardous situations relevant to them. The Forecasting component enhances the predictive suite of tools by providing a local

  18. Real-Time Ocean Prediction System for the East Coast of India

    NASA Astrophysics Data System (ADS)

    Warrior, H. V.

    2016-02-01

    The primary objective of the research work reported in this abstract was to develop a Realtime Environmental model for Ocean Dispersion and Impact (as part of an already in-place Decision Support System) for the purpose of radiological safety for the area along Kalpakkam (East Indian) coast. This system involves combining real-time ocean observations with numerical models of ocean processes to provide hindcasts, nowcasts and forecasts of currents, tides and waves. In this work we present the development of an Automated Coupled Atmospheric - Ocean Model (we call it IIT-CAOM) used to forecast the sea surface currents, sea surface temperature (SST) and salinity etc of the Bay of Bengal region under the influence of transient and unsteady atmospheric conditions. This method uses a coupling of Atmosphere and Ocean model. The models used here are the WRF for atmospheric simulations and POM for the ocean counterpart. It has a 3 km X 3 km resolution. This Coupled Model uses GFS (Global Forecast System) Data or FNL (Final Analyses) Data as initial conditions for jump-starting the atmospheric model. The Atmospheric model is run first thus extracting air temperature, wind speed and relative humidity. The heat flux subroutine computes the net heat flux, using above mentioned parameters data. The net heat flux feeds to the ocean model by simply adding net heat flux subroutine to the ocean model code without changing the model original structure. The online forecast of the IIT-CAOM is currently available in the web. The whole system has been automized and runs without any more manual support. The IIT-CAOM simulations have been carried out for Kalpakkam region, which is located on the East coast of India, about 70 km south of Chennai in Tamilnadu State and a three day forecast of sea surface currents, sea surface temperature (SST) and salinity, etc have been obtained.

  19. Obtaining Reliable Predictions of Terrestrial Energy Coupling From Real-Time Solar Wind Measurement

    NASA Technical Reports Server (NTRS)

    Weimer, Daniel R.

    2001-01-01

    The first draft of a manuscript titled "Variable time delays in the propagation of the interplanetary magnetic field" has been completed, for submission to the Journal of Geophysical Research. In the preparation of this manuscript all data and analysis programs had been updated to the highest temporal resolution possible, at 16 seconds or better. The program which computes the "measured" IMF propagation time delays from these data has also undergone another improvement. In another significant development, a technique has been developed in order to predict IMF phase plane orientations, and the resulting time delays, using only measurements from a single satellite at L1. The "minimum variance" method is used for this computation. Further work will be done on optimizing the choice of several parameters for the minimum variance calculation.

  20. Predicting thermal stability of organic solar cells through real-time capacitive techniques (Presentation Recording)

    NASA Astrophysics Data System (ADS)

    Tessarolo, Marta; Guerrero, Antonio; Seri, Mirko; Prosa, Mario; Bolognesi, Margherita; Garcia Belmonte, Germà

    2015-10-01

    Bulk Heterojunction (BHJ) solar cells have reached Power Conversion Efficiencies (PCE) over 10% but to be a competitive product long lifetimes are mandatory. In this view, guidelines for the prediction and optimization of the device stability are crucial to generate improved materials for efficient and stable BHJ devices. For encapsulated cells, degradation mechanisms can be mainly ascribed to external agents such as light and temperature. In particular, thermal degradation appears to be related not only to the BHJ morphology but also to the adjacent interfaces. Therefore, in order to have a complete description of the thermal stability of a BHJ cell, it is necessary to consider the entire stack degradation processes by using techniques enabling a direct investigation on working devices. Here, five different donor polymers were selected and the OPV performance of the corresponding BHJ devices were monitored during the thermal degradation at 85°C, showing an exponential decay of the corresponding PCEs. In parallel, we measured the geometrical capacitance of analogous OPV devices as a function of temperature and we observed that at a defined temperature (TMAX), typical for each polymer-based device, the capacitance starts to decrease. Combining all these results we found an evident and direct correlation between TMAX and the PCE decay parameters (obtained from capacitance-temperature an thermal measurements, respectively). This implies that the capacitance-method here presented is a fast, reliable and relatively simple method to predict the thermal stability of BHJ solar cells without the need to perform time-consuming thermal degradation tests.

  1. A geopotential model from satellite tracking, altimeter, and surface gravity data: GEM-T3

    NASA Technical Reports Server (NTRS)

    Lerch, F. J.; Nerem, R. S.; Putney, B. H.; Felsentreger, T. L.; Sanchez, B. V.; Marshall, J. A.; Klosko, S. M.; Patel, G. B.; Williamson, R. G.; Chinn, D. S.

    1994-01-01

    An improved model of Earth's gravitational field, Goddard Earth Model T-3 (GEM-T3), has been developed from a combination of satellite tracking, satellite altimeter, and surface gravimetric data. GEM-T3 provides a significant improvement in the modeling of the gravity field at half wavelengths of 400 km and longer. This model, complete to degree and order 50, yields more accurate satellite orbits and an improved geoid representation than previous Goddard Earth Models. GEM-T3 uses altimeter data from GEOS 3 (1975-1976), Seasat (1978) and Geosat (1986-1987). Tracking information used in the solution includes more than 1300 arcs of data encompassing 31 different satellites. The recovery of the long-wavelength components of the solution relies mostly on highly precise satellite laser ranging (SLR) data, but also includes Tracking Network (TRANET) Doppler, optical, and satellite-to-satellite tracking acquired between the ATS 6 and GEOS 3 satellites. The main advances over GEM-T2 (beyond the inclusion of altimeter and surface gravity information which is essential for the resolution of the shorter wavelength geoid) are some improved tracking data analysis approaches and additional SLR data. Although the use of altimeter data has greatly enhanced the modeling of the ocean geoid between 65 deg N and 60 deg S latitudes in GEM-T3, the lack of accurate detailed surface gravimetry leaves poor geoid resolution over many continental regions of great tectonic interest (e.g., Himalayas, Andes). Estimates of polar motion, tracking station coordinates, and long-wavelength ocean tidal terms were also made (accounting for 6330 parameters). GEM-T3 has undergone error calibration using a technique based on subset solutions to produce reliable error estimates. The calibration is based on the condition that the expected mean square deviation of a subset gravity solution from the full set values is predicted by the solutions' error covariances. Data weights are iteratively adjusted until

  2. Ginkgolide C Suppresses Adipogenesis in 3T3-L1 Adipocytes via the AMPK Signaling Pathway

    PubMed Central

    Liou, Chian-Jiun; Lai, Xuan-Yu; Chen, Ya-Ling; Wang, Chia-Ling; Wei, Ciao-Han; Huang, Wen-Chung

    2015-01-01

    Ginkgolide C, isolated from Ginkgo biloba leaves, is a flavone reported to have multiple biological functions, from decreased platelet aggregation to ameliorating Alzheimer disease. The study aim was to evaluate the antiadipogenic effect of ginkgolide C in 3T3-L1 adipocytes. Ginkgolide C was used to treat differentiated 3T3-L1 cells. Cell supernatant was collected to assay glycerol release, and cells were lysed to measure protein and gene expression related to adipogenesis and lipolysis by western blot and real-time PCR, respectively. Ginkgolide C significantly suppressed lipid accumulation in differentiated adipocytes. It also decreased adipogenesis-related transcription factor expression, including peroxisome proliferator-activated receptor and CCAAT/enhancer-binding protein. Furthermore, ginkgolide C enhanced adipose triglyceride lipase and hormone-sensitive lipase production for lipolysis and increased phosphorylation of AMP-activated protein kinase (AMPK), resulting in decreased activity of acetyl-CoA carboxylase for fatty acid synthesis. In coculture with an AMPK inhibitor (compound C), ginkgolide C also improved activation of sirtuin 1 and phosphorylation of AMPK in differentiated 3T3-L1 cells. The results suggest that ginkgolide C is an effective flavone for increasing lipolysis and inhibiting adipogenesis in adipocytes through the activated AMPK pathway. PMID:26413119

  3. Menaquinone-7 regulates gene expression in osteoblastic MC3T3E1 cells.

    PubMed

    Katsuyama, Hironobu; Saijoh, Kiyofumi; Otsuki, Takemi; Tomita, Masafumi; Fukunaga, Masao; Sunami, Shigeo

    2007-02-01

    Previous study has shown that the vitamin K2 analog menaquinone-7 (MK-7) induces expression of the osteoblast-specific genes osteocalcin, osteoprotegerin, receptor activator of NFkappaB, and its ligand. Since MK-7 may also regulate osteoblast cell function, we examined the expression of osteoblast genes regulated by MK-7 administration. Differences between gene expression in control and MK-7-administered MC3T3E1 cells were analyzed using the suppression subtractive hybridization method. After 24 h of MK-7 administration, genes upregulated by MK-7 included tenascin C and BMP2. Genes downregulated by MK-7 administration included biglycan and butyrophilin. Real-time PCR showed a marked increase in tenascin C. When the protein level was examined using Western blot analysis, tenascin C was higher in MK-7-administered cells than in control cells. These results indicated that MK-7 affected the cellular function of osteoblastic MC3T3E1 cells. Considering BMP2 mRNA expression was higher in MK-7-administered cells than in control cells, the effect of MK-7 administration on the signal transduction system was examined. Western blot analysis showed that cells administered MK-7 displayed a higher phosphorylated Smad1 level than control cells. Because MC3T3E1 cells have a nuclear binding receptor for MK-7, this result might indicate an indirect effect of MK-7 through BMP2 production.

  4. Prediction of RNA secondary structures: from theory to models and real molecules

    NASA Astrophysics Data System (ADS)

    Schuster, Peter

    2006-05-01

    RNA secondary structures are derived from RNA sequences, which are strings built form the natural four letter nucleotide alphabet, {AUGC}. These coarse-grained structures, in turn, are tantamount to constrained strings over a three letter alphabet. Hence, the secondary structures are discrete objects and the number of sequences always exceeds the number of structures. The sequences built from two letter alphabets form perfect structures when the nucleotides can form a base pair, as is the case with {GC} or {AU}, but the relation between the sequences and structures differs strongly from the four letter alphabet. A comprehensive theory of RNA structure is presented, which is based on the concepts of sequence space and shape space, being a space of structures. It sets the stage for modelling processes in ensembles of RNA molecules like evolutionary optimization or kinetic folding as dynamical phenomena guided by mappings between the two spaces. The number of minimum free energy (mfe) structures is always smaller than the number of sequences, even for two letter alphabets. Folding of RNA molecules into mfe energy structures constitutes a non-invertible mapping from sequence space onto shape space. The preimage of a structure in sequence space is defined as its neutral network. Similarly the set of suboptimal structures is the preimage of a sequence in shape space. This set represents the conformation space of a given sequence. The evolutionary optimization of structures in populations is a process taking place in sequence space, whereas kinetic folding occurs in molecular ensembles that optimize free energy in conformation space. Efficient folding algorithms based on dynamic programming are available for the prediction of secondary structures for given sequences. The inverse problem, the computation of sequences for predefined structures, is an important tool for the design of RNA molecules with tailored properties. Simultaneous folding or cofolding of two or more RNA

  5. Predictive Skill of Meteorological Drought Based on Multi-Model Ensemble Forecasts: A Real-Time Assessment

    NASA Astrophysics Data System (ADS)

    Chen, L. C.; Mo, K. C.; Zhang, Q.; Huang, J.

    2014-12-01

    Drought prediction from monthly to seasonal time scales is of critical importance to disaster mitigation, agricultural planning, and multi-purpose reservoir management. Starting in December 2012, NOAA Climate Prediction Center (CPC) has been providing operational Standardized Precipitation Index (SPI) Outlooks using the North American Multi-Model Ensemble (NMME) forecasts, to support CPC's monthly drought outlooks and briefing activities. The current NMME system consists of six model forecasts from U.S. and Canada modeling centers, including the CFSv2, CM2.1, GEOS-5, CCSM3.0, CanCM3, and CanCM4 models. In this study, we conduct an assessment of the predictive skill of meteorological drought using real-time NMME forecasts for the period from May 2012 to May 2014. The ensemble SPI forecasts are the equally weighted mean of the six model forecasts. Two performance measures, the anomaly correlation coefficient and root-mean-square errors against the observations, are used to evaluate forecast skill.Similar to the assessment based on NMME retrospective forecasts, predictive skill of monthly-mean precipitation (P) forecasts is generally low after the second month and errors vary among models. Although P forecast skill is not large, SPI predictive skill is high and the differences among models are small. The skill mainly comes from the P observations appended to the model forecasts. This factor also contributes to the similarity of SPI prediction among the six models. Still, NMME SPI ensemble forecasts have higher skill than those based on individual models or persistence, and the 6-month SPI forecasts are skillful out to four months. The three major drought events occurred during the 2012-2014 period, the 2012 Central Great Plains drought, the 2013 Upper Midwest flash drought, and 2013-2014 California drought, are used as examples to illustrate the system's strength and limitations. For precipitation-driven drought events, such as the 2012 Central Great Plains drought

  6. The SGI/CRAY T3E: Experiences and Insights

    NASA Technical Reports Server (NTRS)

    Bernard, Lisa Hamet

    1999-01-01

    The focus of the HPCC Earth and Space Sciences (ESS) Project is capability computing - pushing highly scalable computing testbeds to their performance limits. The drivers of this focus are the Grand Challenge problems in Earth and space science: those that could not be addressed in a capacity computing environment where large jobs must continually compete for resources. These Grand Challenge codes require a high degree of communication, large memory, and very large I/O (throughout the duration of the processing, not just in loading initial conditions and saving final results). This set of parameters led to the selection of an SGI/Cray T3E as the current ESS Computing Testbed. The T3E at the Goddard Space Flight Center is a unique computational resource within NASA. As such, it must be managed to effectively support the diverse research efforts across the NASA research community yet still enable the ESS Grand Challenge Investigator teams to achieve their performance milestones, for which the system was intended. To date, all Grand Challenge Investigator teams have achieved the 10 GFLOPS milestone, eight of nine have achieved the 50 GFLOPS milestone, and three have achieved the 100 GFLOPS milestone. In addition, many technical papers have been published highlighting results achieved on the NASA T3E, including some at this Workshop. The successes enabled by the NASA T3E computing environment are best illustrated by the 512 PE upgrade funded by the NASA Earth Science Enterprise earlier this year. Never before has an HPCC computing testbed been so well received by the general NASA science community that it was deemed critical to the success of a core NASA science effort. NASA looks forward to many more success stories before the conclusion of the NASA-SGI/Cray cooperative agreement in June 1999.

  7. Ames T-3 fire test facility - Aircraft crash fire simulation

    NASA Technical Reports Server (NTRS)

    Fish, R. H.

    1976-01-01

    There is a need to characterize the thermal response of materials exposed to aircraft fuel fires. Large scale open fire tests are costly and pollute the local environment. This paper describes the construction and operation of a subscale fire test that simulates the heat flux levels and thermochemistry of typical open pool fires. It has been termed the Ames T-3 Test and has been used extensively by NASA since 1969 to observe the behavior of materials exposed to JP-4 fuel fires.

  8. Prediction and Characterization of High-Activity Events in Social Media Triggered by Real-World News

    PubMed Central

    Kalyanam, Janani; Quezada, Mauricio; Poblete, Barbara; Lanckriet, Gert

    2016-01-01

    On-line social networks publish information on a high volume of real-world events almost instantly, becoming a primary source for breaking news. Some of these real-world events can end up having a very strong impact on on-line social networks. The effect of such events can be analyzed from several perspectives, one of them being the intensity and characteristics of the collective activity that it produces in the social platform. We research 5,234 real-world news events encompassing 43 million messages discussed on the Twitter microblogging service for approximately 1 year. We show empirically that exogenous news events naturally create collective patterns of bursty behavior in combination with long periods of inactivity in the network. This type of behavior agrees with other patterns previously observed in other types of natural collective phenomena, as well as in individual human communications. In addition, we propose a methodology to classify news events according to the different levels of intensity in activity that they produce. In particular, we analyze the most highly active events and observe a consistent and strikingly different collective reaction from users when they are exposed to such events. This reaction is independent of an event’s reach and scope. We further observe that extremely high-activity events have characteristics that are quite distinguishable at the beginning stages of their outbreak. This allows us to predict with high precision, the top 8% of events that will have the most impact in the social network by just using the first 5% of the information of an event’s lifetime evolution. This strongly implies that high-activity events are naturally prioritized collectively by the social network, engaging users early on, way before they are brought to the mainstream audience. PMID:27992437

  9. Prediction and Characterization of High-Activity Events in Social Media Triggered by Real-World News.

    PubMed

    Kalyanam, Janani; Quezada, Mauricio; Poblete, Barbara; Lanckriet, Gert

    2016-01-01

    On-line social networks publish information on a high volume of real-world events almost instantly, becoming a primary source for breaking news. Some of these real-world events can end up having a very strong impact on on-line social networks. The effect of such events can be analyzed from several perspectives, one of them being the intensity and characteristics of the collective activity that it produces in the social platform. We research 5,234 real-world news events encompassing 43 million messages discussed on the Twitter microblogging service for approximately 1 year. We show empirically that exogenous news events naturally create collective patterns of bursty behavior in combination with long periods of inactivity in the network. This type of behavior agrees with other patterns previously observed in other types of natural collective phenomena, as well as in individual human communications. In addition, we propose a methodology to classify news events according to the different levels of intensity in activity that they produce. In particular, we analyze the most highly active events and observe a consistent and strikingly different collective reaction from users when they are exposed to such events. This reaction is independent of an event's reach and scope. We further observe that extremely high-activity events have characteristics that are quite distinguishable at the beginning stages of their outbreak. This allows us to predict with high precision, the top 8% of events that will have the most impact in the social network by just using the first 5% of the information of an event's lifetime evolution. This strongly implies that high-activity events are naturally prioritized collectively by the social network, engaging users early on, way before they are brought to the mainstream audience.

  10. Predictive Methods for Real-Time Control of Flood Operation of a Multireservoir System: Methodology and Comparative Study

    NASA Astrophysics Data System (ADS)

    Niewiadomska-Szynkiewicz, Ewa; Malinowski, Krzysztof; Karbowski, Andrzej

    1996-04-01

    Predictive methods for real-time flood operation of water systems consisting of reservoirs located in parallel on tributaries to the main river are presented and discussed. The aspect of conflicting individual goals of the local decision units and other objectives important from an overall point of view is taken into account. The particular attention is focused on hierarchical control structure which provides framework for organization of an on-line reservoir management problem. The important factor involved in flood control the uncertainty with respect to future inflows is taken into consideration. A case study of the upper Vistula river basin system in the southern part of Poland is presented. Simulation results based on 11 historical floods are briefly described and discussed.

  11. A highly efficient semiphenomenological model of a half-sarcomere for real-time prediction of mechanical behavior.

    PubMed

    Chen, Xing; Yin, Yue Hong

    2014-12-01

    With existent biomechanical models of skeletal muscle, challenges still exist in implementing real-time predictions for contraction statuses that are particularly significant to biomechanical and biomedical engineering. Because of this difficulty, this paper proposed a decoupled scheme of the links involved in the working process of a sarcomere and established a semiphenomenological model integrating both linear and nonlinear frames of no higher than a second-order system. In order to facilitate engineering application and cybernetics, the proposed model contains a reduced number of parameters and no partial differential equation, making it highly concise and computationally efficient. Through the simulations of various contraction modes, including isometric, isotonic, successive stretch and release, and cyclic contractions, the correctness and efficiency of the model, are validated. Although this study targets half-sarcomeres, the proposed model can be easily extended to describe the larger-scale mechanical behavior of a muscle fiber or a whole muscle.

  12. Management of stage T3 and T4 glottic carcinomas

    SciTech Connect

    Yuen, A.; Medina, J.E.; Goepfert, H.; Fletcher, G.

    1984-10-01

    Between 1959 and 1979, 242 patients with T3 and T4 lesions of the vocal cords were treated at our institution. Treatment consisted of total laryngectomy in all patients. Different modalities of regional node dissections were performed on 187 patients. In addition, 50 patients received irradiation with cobalt-60 postoperatively for specific features of the disease. In the group of 192 patients whose treatment consisted of surgery alone, 28 (14 percent) had recurrence in the neck and 10 (5 percent) had stomal recurrence. Of the patients treated with combined therapy, three (6 percent) had ipsilateral neck recurrences and one (2 percent) had stomal recurrence. For lesions staged N0, failure rates above the clavicles were 16 percent and 31 percent for patients with T3 and T4 lesions, respectively, in the group treated by surgery alone, 9 percent and 6 percent for patients with T3 and T4 lesions, respectively, in the combined therapy group. The rate of failure above the clavicles for lesions staged N+ was 32 percent in the group treated with surgery alone and 8 percent in the combined therapy group. In this study, a correlation was made between the failure rates above the clavicles and different clinical and histologic characteristics of the tumor, surgical findings, and the different modalities of cervical node dissection used. From analysis of the data, recommendations have been made for the selective treatment of patients with advanced glottic carcinomas.

  13. Growth stimulation of 3T3 fibroblasts by Cystatin

    SciTech Connect

    Quan Sun Beijing Medical Univ. )

    1989-01-01

    Treatment of cultures of mouse 3T3 fibroblasts with Cystatin C, a thiol-proteinase inhibitor isolated from chicken egg white, resulted in an enhanced rate of cell proliferation. This stimulation was demonstrated using two independent assay systems: (a) assessment of total cell number and (b) measurement of ({sup 3}H)thymidine incorporated into acid-precipitable DNA. In both assays, the dose-response curves of Cystatin stimulation showed a rising function that plateaued at a concentration of {approximately}120 {mu}g/ml. The addition of Cystatin to cultures of Kirsten murine sarcoma virus-transformed 3T3 cells also enhanced DNA synthesis in these target cells. Control experiments showed that the presence of Cystatin did not alter the level of binding of radioactively labeled epidermal growth factor and platelet derived growth factor to 3T3 cells. These results argue against the possibility that the observed growth stimulation by Cystatin was due to growth factor contamination of the Cystatin preparation.

  14. Hormone (ACTH, T3) content of immunophenotyped lymphocyte subpopulations.

    PubMed

    Pállinger, Éva; Kiss, Gergely Attila; Csaba, György

    2016-12-01

    Cells of the immune system synthesize, store, and secrete polypeptide and amino acid type hormones, which also influence their functions, having receptors for different hormones. In the present experiment immunophenotyped immune cells isolated from bone marrow, thymus, and peritoneal fluid of mice were used for demonstrating the adrenocorticotropic hormone (ACTH) and triiodothyronine (T3) hormone production of differentiating immune cells. Both hormones were found in each cell type, and in each maturation state, which means that all cells are participating in the hormonal function of the immune system. The lineage-independent presence of ACTH and T3 in differentiating hematopoietic cells denotes that their expression ubiquitous during lymphocyte development. Higher ACTH and T3 content of B cells shows that these cells are the most hormonally active and suggests that the hormones may have an autocrine regulatory role in B cell development. Developing T cells showed heterogeneous hormone production which was associated with their maturation state. Differences in the hormone contents of immune cells isolated from different organs indicate that their hormone production is defined by their differentiation or maturation state, however, possibly also by the local microenvironment.

  15. Predictive modeling in Clostridium acetobutylicum fermentations employing Raman spectroscopy and multivariate data analysis for real-time culture monitoring

    NASA Astrophysics Data System (ADS)

    Zu, Theresah N. K.; Liu, Sanchao; Germane, Katherine L.; Servinsky, Matthew D.; Gerlach, Elliot S.; Mackie, David M.; Sund, Christian J.

    2016-05-01

    The coupling of optical fibers with Raman instrumentation has proven to be effective for real-time monitoring of chemical reactions and fermentations when combined with multivariate statistical data analysis. Raman spectroscopy is relatively fast, with little interference from the water peak present in fermentation media. Medical research has explored this technique for analysis of mammalian cultures for potential diagnosis of some cancers. Other organisms studied via this route include Escherichia coli, Saccharomyces cerevisiae, and some Bacillus sp., though very little work has been performed on Clostridium acetobutylicum cultures. C. acetobutylicum is a gram-positive anaerobic bacterium, which is highly sought after due to its ability to use a broad spectrum of substrates and produce useful byproducts through the well-known Acetone-Butanol-Ethanol (ABE) fermentation. In this work, real-time Raman data was acquired from C. acetobutylicum cultures grown on glucose. Samples were collected concurrently for comparative off-line product analysis. Partial-least squares (PLS) models were built both for agitated cultures and for static cultures from both datasets. Media components and metabolites monitored include glucose, butyric acid, acetic acid, and butanol. Models were cross-validated with independent datasets. Experiments with agitation were more favorable for modeling with goodness of fit (QY) values of 0.99 and goodness of prediction (Q2Y) values of 0.98. Static experiments did not model as well as agitated experiments. Raman results showed the static experiments were chaotic, especially during and shortly after manual sampling.

  16. Puget Sound Operational Forecast System - A Real-time Predictive Tool for Marine Resource Management and Emergency Responses

    SciTech Connect

    Yang, Zhaoqing; Khangaonkar, Tarang; Chase, Jared M.; Wang, Taiping

    2009-12-01

    To support marine ecological resource management and emergency response and to enhance scientific understanding of physical and biogeochemical processes in Puget Sound, a real-time Puget Sound Operational Forecast System (PS-OFS) was developed by the Coastal Ocean Dynamics & Ecosystem Modeling group (CODEM) of Pacific Northwest National Laboratory (PNNL). PS-OFS employs the state-of-the-art three-dimensional coastal ocean model and closely follows the standards and procedures established by National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). PS-OFS consists of four key components supporting the Puget Sound Circulation and Transport Model (PS-CTM): data acquisition, model execution and product archive, model skill assessment, and model results dissemination. This paper provides an overview of PS-OFS and its ability to provide vital real-time oceanographic information to the Puget Sound community. PS-OFS supports pacific northwest region’s growing need for a predictive tool to assist water quality management, fish stock recovery efforts, maritime emergency response, nearshore land-use planning, and the challenge of climate change and sea level rise impacts. The structure of PS-OFS and examples of the system inputs and outputs, forecast results are presented in details.

  17. Prediction of landslide activation at locations in Beskidy Mountains using standard and real-time monitoring methods

    NASA Astrophysics Data System (ADS)

    Bednarczyk, Z.

    2012-04-01

    The paper presents landslide monitoring methods used for prediction of landslide activity at locations in the Carpathian Mountains (SE Poland). Different types of monitoring methods included standard and real-time early warning measurement with use of hourly data transfer to the Internet were used. Project financed from the EU funds was carried out for the purpose of public road reconstruction. Landslides with low displacement rates (varying from few mm to over 5cm/year) had size of 0.4-2.2mln m3. Flysch layers involved in mass movements represented mixture of clayey soils and sandstones of high moisture content and plasticity. Core sampling and GPR scanning were used for recognition of landslide size and depths. Laboratory research included index, IL oedometer, triaxial and direct shear laboratory tests. GPS-RTK mapping was employed for actualization of landslide morphology. Instrumentation consisted of standard inclinometers, piezometers and pore pressure transducers. Measurements were carried 2006-2011, every month. In May 2010 the first in Poland real-time monitoring system was installed at landslide complex over the Szymark-Bystra public road. It included in-place uniaxial sensors and 3D continuous inclinometers installed to the depths of 12-16m with tilt sensors every 0.5m. Vibrating wire pore pressure and groundwater level transducers together with automatic meteorological station analyzed groundwater and weather conditions. Obtained monitoring and field investigations data provided parameters for LEM and FEM slope stability analysis. They enabled prediction and control of landslide behaviour before, during and after stabilization or partly stabilization works. In May 2010 after the maximum precipitation (100mm/3hours) the rates of observed displacements accelerated to over 11cm in a few days and damaged few standard inclinometer installations. However permanent control of the road area was possible by continuous inclinometer installations. Comprehensive

  18. Methicillin-resistant Staphylococcus aureus (MRSA) nasal real-time PCR: a predictive tool for contamination of the hospital environment.

    PubMed

    Livorsi, Daniel J; Livorsi, David J; Arif, Sana; Garry, Patricia; Kundu, Madan G; Satola, Sarah W; Davis, Thomas H; Batteiger, Byron; Kressel, Amy B

    2015-01-01

    OBJECTIVE We sought to determine whether the bacterial burden in the nares, as determined by the cycle threshold (CT) value from real-time MRSA PCR, is predictive of environmental contamination with MRSA. METHODS Patients identified as MRSA nasal carriers per hospital protocol were enrolled within 72 hours of room admission. Patients were excluded if (1) nasal mupirocin or chlorhexidine body wash was used within the past month or (2) an active MRSA infection was suspected. Four environmental sites, 6 body sites and a wound, if present, were cultured with premoistened swabs. All nasal swabs were submitted for both a quantitative culture and real-time PCR (Roche Lightcycler, Indianapolis, IN). RESULTS At study enrollment, 82 patients had a positive MRSA-PCR. A negative correlation of moderate strength was observed between the CT value and the number of MRSA colonies in the nares (r=-0.61; P<0.01). Current antibiotic use was associated with lower levels of MRSA nasal colonization (CT value, 30.2 vs 27.7; P<0.01). Patients with concomitant environmental contamination had a higher median log MRSA nares count (3.9 vs 2.5, P=0.01) and lower CT values (28.0 vs 30.2; P<0.01). However, a ROC curve was unable to identify a threshold MRSA nares count that reliably excluded environmental contamination. CONCLUSIONS Patients with a higher burden of MRSA in their nares, based on the CT value, were more likely to contaminate their environment with MRSA. However, contamination of the environment cannot be predicted solely by the degree of MRSA nasal colonization.

  19. Regulation of Vibrio parahaemolyticus T3SS2 gene expression and function of T3SS2 effectors that modulate actin cytoskeleton.

    PubMed

    Kodama, Toshio; Hiyoshi, Hirotaka; Okada, Ryu; Matsuda, Shigeaki; Gotoh, Kazuyoshi; Iida, Tetsuya

    2015-02-01

    Vibrio parahaemolyticus is a leading causative agent of seafood-borne gastroenteritis worldwide. Most clinical isolates from patients with diarrhoea possess two sets of genes for the type III secretion system (T3SS) on each chromosome (T3SS1 and T3SS2). T3SS is a protein secretion system that delivers effector proteins directly into eukaryotic cells. The injected effectors modify the normal cell functions by altering or disrupting the normal cell signalling pathways. Of the two sets of T3SS genes present in V. parahaemolyticus, T3SS2 is essential for enterotoxicity in several animal models. Recent studies have elucidated the biological activities of several T3SS2 effectors and their roles in virulence. This review focuses on the regulation of T3SS2 gene expression and T3SS2 effectors that specifically target the actin cytoskeleton. © 2014 John Wiley & Sons Ltd.

  20. Predicting primate local extinctions within "real-world" forest fragments: a pan-neotropical analysis.

    PubMed

    Benchimol, Maíra; Peres, Carlos A

    2014-03-01

    Understanding the main drivers of species extinction in human-modified landscapes has gained paramount importance in proposing sound conservation strategies. Primates play a crucial role in maintaining the integrity of forest ecosystem functions and represent the best studied order of tropical terrestrial vertebrates, yet primate species diverge widely in their responses to forest habitat disturbance and fragmentation. Here, we present a robust quantitative review on the synergistic effects of habitat fragmentation on Neotropical forest primates to pinpoint the drivers of species extinction across a wide range of forest patches from Mexico to Argentina. Presence-absence data on 19 primate functional groups were compiled from 705 forest patches and 55 adjacent continuous forest sites, which were nested within 61 landscapes investigated by 96 studies. Forest patches were defined in terms of their size, surrounding matrix and level of hunting pressure on primates, and each functional group was classified according to seven life-history traits. Generalized linear mixed models showed that patch size, forest cover, level of hunting pressure, home range size and trophic status were the main predictors of species persistence within forest isolates for all functional groups pooled together. However, patterns of local extinction varied greatly across taxa, with Alouatta and Callicebus moloch showing the highest occupancy rates even within tiny forest patches, whereas Brachyteles and Leontopithecus occupied fewer than 50% of sites, even in relatively large forest tracts. Our results uncover the main predictors of platyrrhine primate species extinction, highlighting the importance of considering the history of anthropogenic disturbances, the structure of landscapes, and species life-history attributes in predicting primate persistence in Neotropical forest patches. We suggest that large-scale conservation planning of fragmented forest landscapes should prioritize and set

  1. Vaspin promotes 3T3-L1 preadipocyte differentiation

    PubMed Central

    Liu, Ping; Wu, Jine; Zhou, Xin; Wang, Liping; Han, Wenqi; Lv, Ying; Sun, Chaofeng

    2015-01-01

    Vaspin, a novel adipocyte factor secreted from visceral adipose tissues, is associated with obesity and insulin resistance and can regulate glucose and lipid metabolism, increase insulin sensitivity, and suppress inflammation; however, the underlying mechanisms remain unknown. Proliferation and maladaptive differentiation are important pathological mechanisms underlying obesity. This study aimed to evaluate the effects of vaspin on the proliferation and differentiation of preadipocyte 3T3-L1 cells and to explore the likely mechanisms responsible for 3T3-L1 differentiation. Vaspin was added to cultured 3T3-L1 cells, and the differentiation of adipocytes was evaluated using Oil Red O staining. The AKT signaling pathway and specific differentiation factors related to the differentiation of preadipocyte 3T3-L1 cells, peroxisome proliferator-activated γ and the CCAAT/enhancer-binding protein (C/EBP) family, were evaluated using reverse transcription polymerase chain reaction (RT-PCR) and western blot analyses during the early phase of differentiation. Additionally, adiponectin mRNA, interleukin-6 mRNA (IL-6 mRNA), and glucose transporter-4 (GLUT4) protein levels were measured in the differentiated adipocytes. The results indicated that vaspin promotes the intracellular accumulation of lipids and increases differentiation-related factors, including peroxisome proliferator-activated receptor γ, C/EBPα, and free fatty acid-binding protein 4 (FABP4), in a dose-dependent manner. Additionally, vaspin (200 ng/mL) increased the mRNA and protein levels of C/EBPβ, peroxisome proliferator-activated γ, C/EBPα, and FABP4. Moreover, compared with the control, significantly smaller eight-day differentiated adipocytes were observed, and these cells exhibited decreased IL-6 mRNA and increased GLUT4 mRNA levels; these results also indicated the potential of vaspin to promote the insulin-mediated AKT signaling pathway during the early phase of differentiation. In conclusion

  2. Vaspin promotes 3T3-L1 preadipocyte differentiation.

    PubMed

    Liu, Ping; Li, Guoliang; Wu, Jine; Zhou, Xin; Wang, Liping; Han, Wenqi; Lv, Ying; Sun, Chaofeng

    2015-11-01

    Vaspin, a novel adipocyte factor secreted from visceral adipose tissues, is associated with obesity and insulin resistance and can regulate glucose and lipid metabolism, increase insulin sensitivity, and suppress inflammation; however, the underlying mechanisms remain unknown. Proliferation and maladaptive differentiation are important pathological mechanisms underlying obesity. This study aimed to evaluate the effects of vaspin on the proliferation and differentiation of preadipocyte 3T3-L1 cells and to explore the likely mechanisms responsible for 3T3-L1 differentiation. Vaspin was added to cultured 3T3-L1 cells, and the differentiation of adipocytes was evaluated using Oil Red O staining. The AKT signaling pathway and specific differentiation factors related to the differentiation of preadipocyte 3T3-L1 cells, peroxisome proliferator-activated γ and the CCAAT/enhancer-binding protein (C/EBP) family, were evaluated using reverse transcription polymerase chain reaction (RT-PCR) and western blot analyses during the early phase of differentiation. Additionally, adiponectin mRNA, interleukin-6 mRNA (IL-6 mRNA), and glucose transporter-4 (GLUT4) protein levels were measured in the differentiated adipocytes. The results indicated that vaspin promotes the intracellular accumulation of lipids and increases differentiation-related factors, including peroxisome proliferator-activated receptor γ, C/EBPα, and free fatty acid-binding protein 4 (FABP4), in a dose-dependent manner. Additionally, vaspin (200 ng/mL) increased the mRNA and protein levels of C/EBPβ, peroxisome proliferator-activated γ, C/EBPα, and FABP4. Moreover, compared with the control, significantly smaller eight-day differentiated adipocytes were observed, and these cells exhibited decreased IL-6 mRNA and increased GLUT4 mRNA levels; these results also indicated the potential of vaspin to promote the insulin-mediated AKT signaling pathway during the early phase of differentiation. In conclusion

  3. Deep redshift topological lensing: strategies for the T3 candidate

    NASA Astrophysics Data System (ADS)

    Roukema, Boudewijn F.; France, Martin J.; Kazimierczak, Tomasz A.; Buchert, Thomas

    2014-01-01

    The 3-torus (T3) Friedmann-Lemaître-Robertson-Walker model better fits the nearly zero large-scale two-point auto-correlation of the Wilkinson Microwave Anisotropy Probe (WMAP) cosmic microwave background sky maps than the infinite flat model. The T3 model's parameters, recently found using an optimal cross-correlation method on WMAP data, imply approximately equal-redshift topological lensing at redshifts z ˜ 6, the redshift range of the upcoming generation of new instruments and telescopes. We investigate observational strategies that can reject the T3 solution for a given region of parameter space of physical assumptions, or provide good candidate topologically lensed galaxy pairs for detailed spectroscopic followup. T3 holonomies are applied to (i) existing z ˜ 6 observations and (ii) simulated observations, creating multiply connected catalogues. Corresponding simply connected catalogues are generated. The simulated observational strategies are motivated by the matched discs principle. Each catalogue is analysed using a successive filter method and collecting matched quadruples. Quadruple statistics between the multiply and simply connected catalogues are compared. The expected rejection of the hypothesis, or detection of candidate topologically lensed galaxies, is possible at a significance of 5 per cent for a pair of T3 axis-centred northern and southern surveys if photometric redshift accuracy is σ(zphot) ≲ 0.01 for a pair of nearly complete 100 deg2 surveys with a total of ≳500 galaxies over 4.3 < z < 6.6, or for a pair of 196 deg2 surveys with ≳400 galaxies and σ(zphot) ≲ 0.02 over 4 < z < 7. Dropping the maximum time interval in a pair from Δt = 1 h-1 Gyr to Δt = 0.1 h-1 Gyr requires σ(zphot) ≲ 0.005 or σ(zphot) ≲ 0.01, respectively. Millions of z ˜ 6 galaxies will be observed over fields of these sizes during the coming decades, implying much stronger constraints. The question is not if the hypothesis will be rejected or confirmed

  4. Discriminating modes of toxic action in mice using toxicity in BALB/c mouse fibroblast (3T3) cells.

    PubMed

    Huang, Tao; Yan, Lichen; Zheng, Shanshan; Wang, Yue; Wang, Xiaohong; Fan, Lingyun; Li, Chao; Zhao, Yuanhui; Martyniuk, Christopher J

    2017-08-26

    The objective of this study was to determine whether toxicity in mouse fibroblast cells (3T3 cells) could predict toxicity in mice. Synthesized data on toxicity was subjected to regression analysis and it was observed that relationship of toxicities between mice and 3T3 cells was not strong (R(2) = 0.41). Inclusion of molecular descriptors (e.g. ionization, pKa) improved the regression to R(2) = 0.56, indicating that this relationship is influenced by kinetic processes of chemicals or specific toxic mechanisms associated to the compounds. However, to determine if we were able to discriminate modes of action (MOAs) in mice using the toxicities generated from 3T3 cells, compounds were first classified into "baseline" and "reactive" guided by the toxic ratio (TR) for each compound in mice. Sequence, binomial and recursive partitioning analyses provided strong predictions of MOAs in mice based upon toxicities in 3T3 cells. The correct classification of MOAs based on these methods was 86%. Nearly all the baseline compounds predicted from toxicities in 3T3 cells were identified as baseline compounds from the TR in mice. The incorrect assignment of MOAs for some compounds is hypothesized to be due to experimental uncertainty that exists in toxicity assays for both mice and 3T3 cells. Conversely, lack of assignment can also arise because some reactive compounds have MOAs that are different in mice compared to 3T3 cells. The methods developed here are novel and contribute to efforts to reduce animal numbers in toxicity tests that are used to evaluate risks associated with organic pollutants in the environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. The Inverse Contagion Problem (ICP) vs.. Predicting site contagion in real time, when network links are not observable

    NASA Astrophysics Data System (ADS)

    Mushkin, I.; Solomon, S.

    2017-10-01

    We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires ;only; the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types. The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the ;false link difficulty;. By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the ;false link difficulty; of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure. We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it

  6. The production of a monoclonal T3-antiidiotypic antibody (T3-MAAB) that mimics the effects of T3 on 2-deoxy-D-glucose uptake in chick embryo heart cells.

    PubMed

    Gordon, A; Schwartz, H; Gafny, M; Mizrachi, M; Swartz, H; Gross, J

    1994-01-01

    The Ig fraction of rabbit anti-T3 antibody was injected into the spleens of BALB/c mice. Four days later, the lymphocytes were recovered from their spleens and were fused with cells of the 653 myeloma cell line. Screening of the hybrid colonies was carried out in a T3 RIA system. Positive colonies were those whose supernatant displaced 125I-labeled T3 from its antibody. The positive cultures were recloned and one was injected ip into mice. The crude IgG fraction of the ascites fluid was affinity purified on an affigel-10 column containing a covalently bound rabbit anti-T3-IgG. In order to eliminate possible endogenous T3 contamination during the affinity purification, the column was stripped with a 40% solution of acetonitrile in 0.2 M acetic acid, neutralized, and then the purification proceeded as described. The affinity purified antibody was an IgG2a isotype. This monoclonal antibody (T3-MAAB) displaced labeled T3 from its antibody in an RIA system. It also mimicked T3 in the stimulation of [3H]2-deoxy-D-glucose (2-DOG) uptake in cultured chick embryo heart cells. After 6 h exposure, the dose-response curve of 2-DOG uptake to T3-MAAB was shifted to the left by at least one order of magnitude when compared to the dose-response curve obtained with T3. After 24 h exposure, T3 had the expected additional stimulatory effect that was dependent on neosynthesis of proteins, while T3-MAAB did not. Also at 24 h exposure, T3-MAAB did not stimulate the incorporation of labeled leucine and uridine into the heart cells while T3 at an equivalent concentration did. The MAAB activity could be abolished by boiling, while boiling did not affect the activity of an equivalent concentration of T3, thus excluding a T3 contamination-mediated effect. We conclude, therefore, that (a) a monoclonal hybridoma producing an antibody that mimics T3 was established; (b) this antibody competed with labeled T3 for anti-T3 antibody and, like T3, stimulated sugar uptake into cultured chick embryo

  7. Elevated serum levels of T3 without metabolic effect in nutritionally deficient rats, attributable to reduced cellular uptake of T3

    SciTech Connect

    Okamura, K.; Taurog, A.; DiStefano, J.J.

    1981-08-01

    Rats receiving a nutritionally deficient diet displayed markedly elevated serum free T3 levels but showed no increase in oxygen consumption. This was associated with greatly reduced ratios of hepatic cellular and nuclear /sub 125/I-T3 to serum /sub 125/I-T3. Kinetic data supported the conclusion that cellular uptake of T3 was decreased in the nutritionally deficient rats. The lack of metabolic effect, despite the elevated serum T3 levels, is attributable to reduced availability of serum T3 to tissue nuclear receptor sites.

  8. Predicting human decisions in socioeconomic interaction using real-time functional magnetic resonance imaging (rtfMRI)

    NASA Astrophysics Data System (ADS)

    Hollmann, Maurice; Mönch, Tobias; Müller, Charles; Bernarding, Johannes

    2009-02-01

    A major field in cognitive neuroscience investigates neuronal correlates of human decision-making processes [1, 2]. Is it possible to predict a decision before it is actually revealed by the volunteer? In the presented manuscript we use a standard paradigm from economic behavioral research that proved emotional influences on human decision making: the Ultimatum Game (UG). In the UG, two players have the opportunity to split a sum of money. One player is deemed the proposer and the other, the responder. The proposer makes an offer as to how this money should be split between the two. The second player can either accept or reject this offer. If it is accepted, the money is split as proposed. If rejected, then neither player receives anything. In the presented study a real-time fMRI system was used to derive the brain activation of the responder. Using a Relevance-Vector-Machine classifier it was possible to predict if the responder will accept or reject an offer. The classification result was presented to the operator 1-2 seconds before the volunteer pressed a button to convey his decision. The classification accuracy reached about 70% averaged over six subjects.

  9. Ensemble forecasting of short-term system scale irrigation demands using real-time flow data and numerical weather predictions

    NASA Astrophysics Data System (ADS)

    Perera, Kushan C.; Western, Andrew W.; Robertson, David E.; George, Biju; Nawarathna, Bandara

    2016-06-01

    Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real-time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short-term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash-Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.

  10. Analysis of the real estate market in Las Vegas: Bubble, seasonal patterns, and prediction of the CSW indices

    NASA Astrophysics Data System (ADS)

    Zhou, Wei-Xing; Sornette, Didier

    2008-01-01

    We analyze 27 house price indices of Las Vegas from June 1983 to March 2005, corresponding to 27 different zip codes. These analyses confirm the existence of a real estate bubble, defined as a price acceleration faster than exponential, which is found, however, to be confined to a rather limited time interval in the recent past from approximately 2003 to mid-2004 and has progressively transformed into a more normal growth rate comparable to pre-bubble levels in 2005. There has been no bubble till 2002 except for a medium-sized surge in 1990. In addition, we have identified a strong yearly periodicity which provides a good potential for fine-tuned prediction from month to month. A monthly monitoring using a model that we have developed could confirm, by testing the intra-year structure, if indeed the market has returned to “normal” or if more turbulence is expected ahead. We predict the evolution of the indices one year ahead, which is validated with new data up to September 2006. The present analysis demonstrates the existence of very significant variations at the local scale, in the sense that the bubble in Las Vegas seems to have preceded the more global USA bubble and has ended approximately two years earlier (mid-2004 for Las Vegas compared with mid-2006 for the whole of the USA).

  11. Judging a Book by Its Cover: Children's Facial Trustworthiness as Judged by Strangers Predicts Their Real-World Trustworthiness and Peer Relationships.

    PubMed

    Li, Qinggong; Heyman, Gail D; Mei, Jing; Lee, Kang

    2017-08-03

    This longitudinal research examined whether children's facial trustworthiness as judged by strangers can predict their real-world trustworthiness and peer acceptance. Adults (Study 1) and children (Study 2) judged the facial trustworthiness of 8- to 12-year-old children (N = 100) solely based on their photographs. The children's classmates were asked to report their real-world trustworthiness and peer acceptance. Children's facial trustworthiness reliably predicted these outcomes both initially when the photographs were taken, as well as 1 year later, and this effect was mediated by the initial ratings of real-world trustworthiness and peer acceptance. These results provide evidence for a long-lasting linkage between children's facial and real-world trustworthiness. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

  12. Ambulatory and Challenge-Associated Heart Rate Variability Measures Predict Cardiac Responses to “Real-World” Acute Emotional Stress

    PubMed Central

    Dikecligil, GN; Mujica-Parodi, LR

    2010-01-01

    Background Heart rate variability (HRV) measures homeostatic regulation of the autonomic nervous system in response to perturbation, and has been previously shown to quantify risk for cardiac events. In spite of known interactions between stress vulnerability, psychiatric illness, and cardiac health, however, to our knowledge this is the first study to directly compare the value of laboratory HRV in predicting autonomic modulation of “real-world” emotional stress. Methods We recorded ECG on 56 subjects: first, within the laboratory, and then during an acute emotional stressor: a first-time skydive. Laboratory sessions included two five-minute ECG recordings separated by one ambulatory 24-hour recording. To test the efficacy of introducing a mild emotional challenge, during each of the five-minute laboratory recordings subjects viewed either aversive or benign images. Following the laboratory session, subjects participated in the acute stressor wearing a holter ECG. Artifact-free ECGs (N=33) were analyzed for HRV, then statistically compared across laboratory and acute stress sessions. Results There were robust correlations (r=0.7-0.8) between the laboratory and acute stress HRV, indicating that the two most useful paradigms (long-term wake, followed by short-term challenge) also were most sensitive to distinct components of the acute stressor: the former correlated with the fine-tuned regulatory modulation occurring immediately prior and following the acute stressor, while the latter correlated with gross amplitude and recovery. Conclusions Our results confirmed the efficacy of laboratory-acquired HRV in predicting autonomic response to acute emotional stress, and suggest that ambulatory and challenge protocols enhance predictive value. PMID:20299007

  13. Preferential heating using transurethral thermoablation (T3) improves clinical results

    NASA Astrophysics Data System (ADS)

    Ramsey, Ernest W.; Miller, Paul D.; Parsons, Keith

    1997-05-01

    Transurethral microwave thermotherapy (TUMT) has been widely reported for the treatment of benign prostatic hyperplasia (BPH) but with variable results. This is likely due to the inability to develop and maintain high intraprostatic temperatures. The T3 device has a preferential heating pattern which prevents shutdowns as a result of rectal heating thus allowing continuous energy delivery throughout the therapy. High temperatures greater than 70 degrees Celsius are maintained resulting in extensive coagulative necrosis in the transitional zone. Treatment was performed in an outpatient clinic using topical anaesthesia with occasional low dose I.V. analgesia. One hundred and fifty-four patients have been treated in 3 centers using a similar protocol. Inclusion criteria required an AUA symptom score greater than or equal to 9 and a peak uroflow rate less than or equal to 12 ml/sec. Mean prostate size was 40.6 cc. One hundred and eighteen patients have been followed for at least 12 months, and 58 for 24 months. AUA symptom score decreased from a mean of 19.8 to 8.9 (12 M), and 7.6 (24 M). Improvement was seen in all 7 symptoms evaluated. Peak flow rates increased from a mean of 9.3 to 13.4 (12 M), and 13.1 (24 M). Improvement in symptom score and peak flow was observed across all prostate sizes. By 2 years, 15 patients had dropped out of the study, 8 for alternative treatment (6 TURP, 1 bladder neck incision, 1 urethrotomy) and 7 for administrative or other reasons. Treatment with the T3 device provides excellent improvement in symptoms, flow rates and patients satisfaction. T3 fulfills the criteria for an effective, minimally invasive, outpatient treatment for symptomatic BPH.

  14. Evaluation of the 1996 Predictions of the Run-Timing of Wild Migrant Spring/Summer Yearling Chinook in the Snake River Basin Using Program RealTime.

    SciTech Connect

    Townsend, Richard L.; Yasuda, Dean; Skalski, J.R.

    1997-03-01

    This report is a post-season analysis of the accuracy of the 1996 predictions from the program RealTime. Observed 1996 migration data collected at Lower Granite Dam were compared to the predictions made by RealTime for the spring outmigration of wild spring/summer chinook. Appendix A displays the graphical reports of the RealTime program that were interactively accessible via the World Wide Web during the 1996 migration season. Final reports are available at address http://www.cqs.washington.edu/crisprt/. The CRISP model incorporated the predictions of the run status to move the timing forecasts further down the Snake River to Little Goose, Lower Monumental and McNary Dams. An analysis of the dams below Lower Granite Dam is available separately.

  15. Prevalence and Clinical Significance of Low T3 Syndrome in Non-Dialysis Patients with Chronic Kidney Disease

    PubMed Central

    Fan, Jingxian; Yan, Peng; Wang, Yingdeng; Shen, Bo; Ding, Feng; Liu, Yingli

    2016-01-01

    Background There are few data on the prevalence of low T3 (triiodothyronine) syndrome in patients with non-dialysis chronic kidney disease (CKD) and it is unclear whether low T3 can be used to predict the progression of CKD. Material/Methods We retrospectively studied 279 patients who had been definitively diagnosed with CKD, without needing maintenance dialysis. Thyroid function was analyzed in all enrolled subjects and the incidence of thyroid dysfunction (low T3 syndrome, low T4 syndrome, and subclinical hypothyroidism) in patients at different stages of CKD was determined. Results Glomerular filtration rate (GFR) of CKD patients was estimated as follows: 145 subjects (52%) had GFR <60 ml/min per 1.73 m2; 47 subjects (16.8%) had GFR between 30 and 59 ml/min per 1.73 m2, and 98 subjects (35.1%) had GFR <30 ml/min per 1.73 m2. Among all enrolled subjects, 4.7% (n=13) had subclinical hypothyroidism, 5.4% (n=15) had low T4 syndrome, and 47% (n=131) had low T3 syndrome. In 114 CKD patients in stages 3–5, serum T3 was positively related to protein metabolism (STP, PA, and ALB) and anemia indicators (Hb and RBC), and negatively related to inflammatory status (CRP and IL-6). Conclusions A high prevalence of low T3 syndrome was observed in CKD patients without dialysis, even in early stages (1 and 2). The increasing prevalence of low T3 as CKD progresses indicates its value as a predictor of worsening CKD. Furthermore, low T3 syndrome is closely associated with both malnutrition-inflammation complex syndrome (MICS) and anemia. PMID:27056188

  16. Prevalence and Clinical Significance of Low T3 Syndrome in Non-Dialysis Patients with Chronic Kidney Disease.

    PubMed

    Fan, Jingxian; Yan, Peng; Wang, Yingdeng; Shen, Bo; Ding, Feng; Liu, Yingli

    2016-04-08

    BACKGROUND There are few data on the prevalence of low T3 (triiodothyronine) syndrome in patients with non-dialysis chronic kidney disease (CKD) and it is unclear whether low T3 can be used to predict the progression of CKD. MATERIAL AND METHODS We retrospectively studied 279 patients who had been definitively diagnosed with CKD, without needing maintenance dialysis. Thyroid function was analyzed in all enrolled subjects and the incidence of thyroid dysfunction (low T3 syndrome, low T4 syndrome, and subclinical hypothyroidism) in patients at different stages of CKD was determined. RESULTS Glomerular filtration rate (GFR) of CKD patients was estimated as follows: 145 subjects (52%) had GFR <60 ml/min per 1.73 m2; 47 subjects (16.8%) had GFR between 30 and 59 ml/min per 1.73 m2, and 98 subjects (35.1%) had GFR <30 ml/min per 1.73 m2. Among all enrolled subjects, 4.7% (n=13) had subclinical hypothyroidism, 5.4% (n=15) had low T4 syndrome, and 47% (n=131) had low T3 syndrome. In 114 CKD patients in stages 3-5, serum T3 was positively related to protein metabolism (STP, PA, and ALB) and anemia indicators (Hb and RBC), and negatively related to inflammatory status (CRP and IL-6). CONCLUSIONS A high prevalence of low T3 syndrome was observed in CKD patients without dialysis, even in early stages (1 and 2). The increasing prevalence of low T3 as CKD progresses indicates its value as a predictor of worsening CKD. Furthermore, low T3 syndrome is closely associated with both malnutrition-inflammation complex syndrome (MICS) and anemia.

  17. MiR-185 inhibits 3T3-L1 cell differentiation by targeting SREBP-1.

    PubMed

    Ning, Chunyou; Li, Guilin; You, Lu; Ma, Yao; Jin, Long; Ma, Jideng; Li, Xuewei; Li, Mingzhou; Liu, Haifeng

    2017-09-01

    Adipogenesis involves a highly orchestrated series of complex events in which microRNAs (miRNAs) may play an essential role. In this study, we found that the miR-185 expression increased gradually during 3T3-L1 cells differentiation. To explore the role of miR-185 in adipogenesis, miRNA agomirs and antagomirs were used to perform miR-185 overexpression and knockdown, respectively. Overexpression of miR-185 dramatically reduced the mRNA expression of the adipogenic markers, PPARγ, FABP4, FAS, and LPL, and the protein level of PPARγ and FAS. MiR-185 overexpression also led to a notable reduction in lipid accumulation. In contrast, miR-185 inhibition promoted differentiation of 3T3-L1 cells. By target gene prediction and luciferase reporter assay, we demonstrated that sterol regulatory element binding protein 1 (SREBP-1) may be the target of miR-185. These results indicate that miR-185 negatively regulates the differentiation of 3T3-L1 cells by targeting SREBP-1, further highlighting the importance of miRNAs in adipogenesis.

  18. Development of a real-time crash risk prediction model incorporating the various crash mechanisms across different traffic states.

    PubMed

    Xu, Chengcheng; Wang, Wei; Liu, Pan; Zhang, Fangwei

    2015-01-01

    This study aimed to identify the traffic flow variables contributing to crash risks under different traffic states and to develop a real-time crash risk model incorporating the varying crash mechanisms across different traffic states. The crash, traffic, and geometric data were collected on the I-880N freeway in California in 2008 and 2009. This study considered 4 different traffic states in Wu's 4-phase traffic theory. They are free fluid traffic, bunched fluid traffic, bunched congested traffic, and standing congested traffic. Several different statistical methods were used to accomplish the research objective. The preliminary analysis showed that traffic states significantly affected crash likelihood, collision type, and injury severity. Nonlinear canonical correlation analysis (NLCCA) was conducted to identify the underlying phenomena that made certain traffic states more hazardous than others. The results suggested that different traffic states were associated with various collision types and injury severities. The matching of traffic flow characteristics and crash characteristics in NLCCA revealed how traffic states affected traffic safety. The logistic regression analyses showed that the factors contributing to crash risks were quite different across various traffic states. To incorporate the varying crash mechanisms across different traffic states, random parameters logistic regression was used to develop a real-time crash risk model. Bayesian inference based on Markov chain Monte Carlo simulations was used for model estimation. The parameters of traffic flow variables in the model were allowed to vary across different traffic states. Compared with the standard logistic regression model, the proposed model significantly improved the goodness-of-fit and predictive performance. These results can promote a better understanding of the relationship between traffic flow characteristics and crash risks, which is valuable knowledge in the pursuit of improving

  19. An evaluation of the real-time tropical cyclone forecast skill of the Navy Operational Global Atmospheric Prediction System in the western North Pacific

    NASA Technical Reports Server (NTRS)

    Fiorino, Michael; Goerss, James S.; Jensen, Jack J.; Harrison, Edward J., Jr.

    1993-01-01

    The paper evaluates the meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones. It is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The meterological characteristics of the NOGAPS tropical cyclone predictions are evaluated by examining the formation of low-level cyclone systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones.

  20. Post-mastectomy Radiation Therapy for T3N0: A SEER Analysis

    PubMed Central

    Johnson, Matthew E.; Handorf, Elizabeth A.; Martin, Jeffrey M.; Hayes, Shelly B.

    2015-01-01

    Background There is conflicting evidence regarding the benefit of post-mastectomy radiation therapy (PMRT) for pathologic stage T3N0M0 breast cancers. We analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database to investigate the benefit of PMRT in these patients. Methods We queried the SEER database for T3N0M0 breast cancer patients diagnosed from 2000–2010 who underwent modified radical mastectomy. We excluded males, patients with unknown radiation timing/type, other primary tumors, or survival <6 months. 2525 patients were included in this analysis. We performed univariate and multivariate statistical analysis using Chi-squared tests, log rank test, and Cox proportional hazards regression. Primary endpoints were overall survival (OS) and breast cancer-specific survival (CSS). Results Of the 2525 patients identified, 1063 received PMRT. The median follow-up was 56 months (range: 6–131). On univariate analysis, PMRT improved OS (76.5% vs. 61.8%, p<0.01) and CSS (85.0% vs. 82.4%, p<0.01) at 8 years. The use of PMRT remained significant on multivariate analysis: PMRT improved OS (HR 0.63, p<0.001) and CSS (HR 0.77, p=0.045). Low tumor grade (p<0.01) and marital status "married" (p=0.01) also predicted for improved CSS on multivariate analysis. Conclusion(s) PMRT was associated with significant improvements in both CSS and OS in patients with T3N0M0 breast cancers treated with modified radical mastectomy from 2000 to 2010. PMRT should be strongly considered in T3N0M0 patients. PMID:24985911

  1. Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

    NASA Technical Reports Server (NTRS)

    Jules, Kenol; Lin, Paul P.

    2006-01-01

    their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

  2. Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

    NASA Technical Reports Server (NTRS)

    Jules, Kenol; Lin, Paul P.

    2006-01-01

    their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

  3. Cannabidiol promotes browning in 3T3-L1 adipocytes.

    PubMed

    Parray, Hilal Ahmad; Yun, Jong Won

    2016-05-01

    Recruitment of the brown-like phenotype in white adipocytes (browning) and activation of existing brown adipocytes are currently being investigated as a means to combat obesity. Thus, a wide variety of dietary agents that contribute to browning of white adipocytes have been identified. The present study was designed to investigate the effects of cannabidiol (CBD), a major nonpsychotropic phytocannabinoid of Cannabis sativa, on induction of browning in 3T3-L1 adipocytes. CBD enhanced expression of a core set of brown fat-specific marker genes (Ucp1, Cited1, Tmem26, Prdm16, Cidea, Tbx1, Fgf21, and Pgc-1α) and proteins (UCP1, PRDM16, and PGC-1α). Increased expression of UCP1 and other brown fat-specific markers contributed to the browning of 3T3-L1 adipocytes possibly via activation of PPARγ and PI3K. In addition, CBD increased protein expression levels of CPT1, ACSL, SIRT1, and PLIN while down-regulating JNK2, SREBP1, and LPL. These data suggest possible roles for CBD in browning of white adipocytes, augmentation of lipolysis, thermogenesis, and reduction of lipogenesis. In conclusion, the current data suggest that CBD plays dual modulatory roles in the form of inducing the brown-like phenotype as well as promoting lipid metabolism. Thus, CBD may be explored as a potentially promising therapeutic agent for the prevention of obesity.

  4. Aspartame downregulates 3T3-L1 differentiation.

    PubMed

    Pandurangan, Muthuraman; Park, Jeongeun; Kim, Eunjung

    2014-10-01

    Aspartame is an artificial sweetener used as an alternate for sugar in several foods and beverages. Since aspartame is 200 times sweeter than traditional sugar, it can give the same level of sweetness with less substance, which leads to lower-calorie food intake. There are reports that consumption of aspartame-containing products can help obese people lose weight. However, the potential role of aspartame in obesity is not clear. The present study investigated whether aspartame suppresses 3T3-L1 differentiation, by downregulating phosphorylated peroxisome proliferator-activated receptor γ (p-PPARγ), peroxisome proliferator-activated receptor γ (PPARγ), fatty acid-binding protein 4 (FABP4), CCAAT/enhancer-binding protein α (C/EBPα), and sterol regulatory element-binding protein 1 (SREBP1), which are critical for adipogenesis. The 3T3-L1 adipocytes were cultured and differentiated for 6 d in the absence and presence of 10 μg/ml of aspartame. Aspartame reduced lipid accumulation in differentiated adipocytes as evidenced by Oil Red O staining. qRT-PCR analysis showed that the PPARγ, FABP4, and C/EBPα mRNA expression was significantly reduced in the aspartame-treated adipocytes. Western blot analysis showed that the induction of p-PPARγ, PPARγ, SREBP1, and adipsin was markedly reduced in the aspartame-treated adipocytes. Taken together, these data suggest that aspartame may be a potent substance to alter adipocyte differentiation and control obesity.

  5. Characterization of hyaluronate binding proteins isolated from 3T3 and murine sarcoma virus transformed 3T3 cells

    SciTech Connect

    Turley, E.A.; Moore, D.; Hayden, L.J.

    1987-06-02

    A hyaluronic acid binding fraction was purified from the supernatant media of both 3T3 and murine sarcoma virus (MSV) transformed 3T3 cultures by hyaluronate and immunoaffinity chromatography. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis resolved the hyaluronate affinity-purified fraction into three major protein bands of estimated molecular weight (M/sub r,e/) 70K, 66K, and 56K which contained hyaluronate binding activity and which were termed hyaluronate binding proteins (HABP). Hyaluronate affinity chromatography combined with immunoaffinity chromatography, using antibody directed against the larger HABP, allowed a 20-fold purification of HABP. Fractions isolated from 3T3 supernatant medium also contained additional binding molecules in the molecular weight range of 20K. This material was present in vanishingly small amounts and was not detected with a silver stain or with (/sup 35/S)methionine label. The three protein species isolated by hyaluronate affinity chromatography (M/sub r,e/ 70K, 66K, and 56K) were related to one another since they shared antigenic determinants and exhibited similar pI values. In isocratic conditions, HABP occurred as aggregates of up to 580 kilodaltons. Their glycoprotein nature was indicated by their incorporation of /sup 3/H-sugars. Enzyme-linked immunoadsorbent assay showed they were antigenically distinct from other hyaluronate binding proteins such as fibronectin, cartilage link protein, and the hyaluronate binding region of chondroitin sulfate proteoglycan. The results are discussed with regard both to the functional significance of hyaluronate-cell surface interactions in transformed as well as normal cells and to the relationship of HABP to other reported hyaluronate binding proteins.

  6. A Real-Time Tool to Display the Predicted Disease Course and Treatment Response for Children with Crohn's Disease

    PubMed Central

    Siegel, Corey A.; Siegel, Lori S.; Hyams, Jeffrey S.; Kugathasan, Subra; Markowitz, James; Rosh, Joel R.; Leleiko, Neal; Mack, David R.; Crandall, Wallace; Evans, Jonathan; Keljo, David J.; Otley, Anthony R.; Oliva-Hemker, Maria; Farrior, Sharmayne; Langton, Christine R.; Wrobel, Iwona T.; Wahbeh, Ghassan; Quiros, J. Antonio; Silber, Gary; Bahar, Ron J.; Sands, Bruce E.; Dubinsky, Marla C.

    2010-01-01

    BACKGROUND Immunomodulators and biologics are effective treatments for children with Crohn’s disease (CD). The challenge of communicating the anticipated disease course with and without therapy to patients and parents is a barrier to the timely use of these agents. The aim of this project was to develop a tool to graphically display the predicted risks of CD and expected benefits of therapy. METHODS Using prospectively collected data from 796 pediatric CD patients we developed a model using system dynamics analysis (SDA). The primary model outcome is the probability of developing a CD related complication. Input variables include patient and disease characteristics, magnitude of serologic immune responses expressed as the quartile sum score (QSS), and exposure to medical treatments. RESULTS Multivariate Cox proportional analyses show variables contributing a significant increase in the hazard ratio (HR) for a disease complication include female gender, older age at diagnosis, small bowel or perianal disease, and a higher QSS. As QSS increases, the HR for early use of corticosteroids increases, in contrast to a decreasing HR with early use of immunomodulators, early or late biologics, and early combination therapy. The concordance index for the model is 0.81. Using SDA, results of the Cox analyses are transformed into a simple graph displaying a real-time individualized probability of disease complication and treatment response. CONCLUSIONS We have developed a tool to predict and communicate individualized risks of CD complications and how this is modified by treatment. Once validated, it can be used at the bedside to facilitate patient decision making. PMID:20812335

  7. Simulation of real-gas effects on pressure distributions for aeroassist flight experiment vehicle and comparison with prediction

    NASA Technical Reports Server (NTRS)

    Micol, John R.

    1992-01-01

    Pressure distributions measured on a 60 degree half-angle elliptic cone, raked off at an angle of 73 degrees from the cone centerline and having an ellipsoid nose (ellipticity equal to 2.0 in the symmetry plane) are presented for angles of attack from -10 degrees to 10 degrees. The high normal shock density ratio aspect of a real gas was simulated by testing in Mach 6 air and CF sub 4 (density ratio equal to 5.25 and 12.0, respectively). The effects of Reynolds number, angle of attack, and normal shock density ratio on these measurements are examined, and comparisons with a three dimensional Euler code known as HALIS are made. A significant effect of density ratio on pressure distributions on the cone section of the configuration was observed; the magnitude of this effect decreased with increasing angle of attack. The effect of Reynolds number on pressure distributions was negligible for forebody pressure distributions, but a measurable effect was noted on base pressures. In general, the HALIS code accurately predicted the measured pressure distributions in air and CF sub 4.

  8. The Dark Side of Authenticity: Feeling "Real" While Gambling Interacts with Enhancement Motives to Predict Problematic Gambling Behavior.

    PubMed

    Lister, Jamey J; Wohl, Michael J A; Davis, Christopher G

    2015-09-01

    Engaging in activities that make people feel authentic or real is typically associated with a host of positive psychological and physiological outcomes (i.e., being authentic serves to increase well-being). In the current study, we tested the idea that authenticity might have a dark side among people engaged in an addictive or risky behavior (gambling). To test this possibility, we assessed gamblers (N = 61) who were betting on the National Hockey League playoff games at a sports bar. As predicted, people who felt authentic when gambling reported behavior associated with problem gambling (high frequency of betting) as well as problematic play (a big monetary loss and a big monetary win). Moreover, such behavior and gambling outcomes were particularly high among people who were motivated to gamble for the purpose of enhancement. The interaction of feeling authentic when betting and gambling for purposes of enhancing positive emotions proved especially troublesome for problematic forms of play. Implications of authenticity as a potential vulnerability factor for sports betting and other types of gambling are discussed.

  9. Klein tunneling in the α -T3 model

    NASA Astrophysics Data System (ADS)

    Illes, E.; Nicol, E. J.

    2017-06-01

    We investigate Klein tunneling for the α -T3 model, which interpolates between graphene and the dice lattice via parameter α . We study transmission across two types of electrostatic interfaces: sharp potential steps and sharp potential barriers. We find both interfaces to be perfectly transparent for normal incidence for the full range of the parameter α for both interfaces. For other angles of incidence, we find that transmission is enhanced with increasing α . For the dice lattice, we find perfect, all-angle transmission across a potential step for incoming electrons with energy equal to half of the height of the potential step. This is analogous to the "super", all-angle transmission reported for the dice lattice for Klein tunneling across a potential barrier.

  10. Shelf-life prediction models for ready-to-eat fresh cut salads: Testing in real cold chain.

    PubMed

    Tsironi, Theofania; Dermesonlouoglou, Efimia; Giannoglou, Marianna; Gogou, Eleni; Katsaros, George; Taoukis, Petros

    2017-01-02

    The aim of the study was to develop and test the applicability of predictive models for shelf-life estimation of ready-to-eat (RTE) fresh cut salads in realistic distribution temperature conditions in the food supply chain. A systematic kinetic study of quality loss of RTE mixed salad (lollo rosso lettuce-40%, lollo verde lettuce-45%, rocket-15%) packed under modified atmospheres (3% O2, 10% CO2, 87% N2) was conducted. Microbial population (total viable count, Pseudomonas spp., lactic acid bacteria), vitamin C, colour and texture were the measured quality parameters. Kinetic models for these indices were developed to determine the quality loss and calculate product remaining shelf-life (SLR). Storage experiments were conducted at isothermal (2.5-15°C) and non-isothermal temperature conditions (Teff=7.8°C defined as the constant temperature that results in the same quality value as the variable temperature distribution) for validation purposes. Pseudomonas dominated spoilage, followed by browning and chemical changes. The end of shelf-life correlated with a Pseudomonas spp. level of 8 log(cfu/g), and 20% loss of the initial vitamin C content. The effect of temperature on these quality parameters was expressed by the Arrhenius equation; activation energy (Ea) value was 69.1 and 122.6kJ/mol for Pseudomonas spp. growth and vitamin C loss rates, respectively. Shelf-life prediction models were also validated in real cold chain conditions (including the stages of transport to and storage at retail distribution center, transport to and display at 7 retail stores, transport to and storage in domestic refrigerators). The quality level and SLR estimated after 2-3days of domestic storage (time of consumption) ranged between 1 and 8days at 4°C and was predicted within satisfactory statistical error by the kinetic models. Teff in the cold chain ranged between 3.7 and 8.3°C. Using the validated models, SLR of RTE fresh cut salad can be estimated at any point of the cold chain

  11. The 3T3-L1 adipocyte glycogen proteome

    PubMed Central

    2013-01-01

    Background Glycogen is a branched polysaccharide of glucose residues, consisting of α-1-4 glycosidic linkages with α-1-6 branches that together form multi-layered particles ranging in size from 30 nm to 300 nm. Glycogen spatial conformation and intracellular organization are highly regulated processes. Glycogen particles interact with their metabolizing enzymes and are associated with a variety of proteins that intervene in its biology, controlling its structure, particle size and sub-cellular distribution. The function of glycogen in adipose tissue is not well understood but appears to have a pivotal role as a regulatory mechanism informing the cells on substrate availability for triacylglycerol synthesis. To provide new molecular insights into the role of adipocyte glycogen we analyzed the glycogen-associated proteome from differentiated 3T3-L1-adipocytes. Results Glycogen particles from 3T3-L1-adipocytes were purified using a series of centrifugation steps followed by specific elution of glycogen bound proteins using α-1,4 glucose oligosaccharides, or maltodextrins, and tandem mass spectrometry. We identified regulatory proteins, 14-3-3 proteins, RACK1 and protein phosphatase 1 glycogen targeting subunit 3D. Evidence was also obtained for a regulated subcellular distribution of the glycogen particle: metabolic and mitochondrial proteins were abundant. Unlike the recently analyzed hepatic glycogen proteome, no endoplasmic proteins were detected, along with the recently described starch-binding domain protein 1. Other regulatory proteins which have previously been described as glycogen-associated proteins were not detected, including laforin, the AMPK beta-subunit and protein targeting to glycogen (PTG). Conclusions These data provide new molecular insights into the regulation of glycogen-bound proteins that are associated with the maintenance, organization and localization of the adipocyte glycogen particle. PMID:23521774

  12. The real-time HF frequency prediction service based on the development of an assimilative IRI model using the Digisonde observation in Korea.

    NASA Astrophysics Data System (ADS)

    Oh, Seung Jun; Chung, Jong-Kyun; Lee, Sungho; Lee, Jeong-Deok; Moon, Joon-Cheol

    The IRI(International Reference Ionosphere) is an international project sponsored by the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI), and it has produced an empirical standard model of the ionosphere based on all available data sources from the worldwide network of ionosonde. The model is now widely used to provide HF prediction services to HF users by the radio science-related organizations in the world. However, the accurate representation of the regional ionosphere, especially the effect of space weather, for a real-time HF prediction by using lRI, is hampered by the limitation of its performance since the model is designed as a climatological model. We have developed an assimilative IRI model using the real-time Digisonde data from two stations (Icheon and Jeju) in Korea. The data stream from the stations is ingested by the model every 30 minute to create the real-time updated CCIR/URSI maps of coefficients that are applied for the real-time usable HF frequency prediction service. Test results for the model output comparing with observed data are presented and we briefly introduce the HF prediction service operated by Korean Space Weather Center, Radio Research Agency (KSWC, RRA), Korea.

  13. [The relation between the low T3 syndrome in the clinical course of myocardial infarction and heart failure].

    PubMed

    Frączek, Magdalena Maria; Gackowski, Andrzej; Przybylik-Mazurek, Elwira; Nessler, Jadwiga

    2016-06-01

    It has been proven that either excess or deficiency of thyroid hormones has harmful influence on the cardiovascular system function. On the other hand, severe systemic conditions like myocardial infarction or severe heart failure may affect thyroid hormones secretion and their peripheral conversion, leading to low T3 syndrome. Amongst many mechanisms causing T4 to T3 conversion disturbances, important role plays decreased activity of D1 deiodinase and increased activity of D3 deiodinase. The animal research confirmed that thyroid hormones influence cardiomiocytes phenotype and morphology. They inhibit inflammation, apoptosis and cardiac remodelling after myocardial infarction. It was also proven that free triiodothyronine similarly to brain natriuretic peptide predict long-term prognosis in chronic and acute heart failure patients. Potential influence of low T3 syndrome on the course of myocardial infarction and heart failure may have significant impact on the future research on individualization of myocardial infarction and heart failure treatment depending on patient's thyroid status.

  14. Folate receptor {alpha} regulates cell proliferation in mouse gonadotroph {alpha}T3-1 cells

    SciTech Connect

    Yao, Congjun; Evans, Chheng-Orn; Stevens, Victoria L.; Owens, Timothy R.; Oyesiku, Nelson M.

    2009-11-01

    We have previously found that the mRNA and protein levels of the folate receptor alpha (FR{alpha}) are uniquely over-expressed in clinically human nonfunctional (NF) pituitary adenomas, but the mechanistic role of FR{alpha} has not fully been determined. We investigated the effect of FR{alpha} over-expression in the mouse gonadotroph {alpha}T3-1 cell line as a model for NF pituitary adenomas. We found that the expression and function of FR{alpha} were strongly up-regulated, by Western blotting and folic acid binding assay. Furthermore, we found a higher cell growth rate, an enhanced percentage of cells in S-phase by BrdU assay, and a higher PCNA staining. These observations indicate that over-expression of FR{alpha} promotes cell proliferation. These effects were abrogated in the same {alpha}T3-1 cells when transfected with a mutant FR{alpha} cDNA that confers a dominant-negative phenotype by inhibiting folic acid binding. Finally, by real-time quantitative PCR, we found that mRNA expression of NOTCH3 was up-regulated in FR{alpha} over-expressing cells. In summary, our data suggests that FR{alpha} regulates pituitary tumor cell proliferation and mechanistically may involve the NOTCH pathway. Potentially, this finding could be exploited to develop new, innovative molecular targeted treatment for human NF pituitary adenomas.

  15. Berberine inhibits 3T3-L1 adipocyte differentiation through the PPARgamma pathway.

    PubMed

    Huang, Cheng; Zhang, Yuebo; Gong, Zhenwei; Sheng, Xiaoyan; Li, Zongmeng; Zhang, Wei; Qin, Ying

    2006-09-22

    Berberine (BBR), a compound purified from Cortidis rhizoma, reduces serum cholesterol, triglycerides, and LDL-cholesterol of hypercholesterolemic patients and high fat diet fed animals, and increases hepatic LDLR mRNA and protein levels through a post-transcriptional mechanism. BBR also enhances the hypoglycemic action of insulin in diabetic animal models. Here, we show that BBR inhibits the differentiation of 3T3-L1 preadipocytes induced by DM and suppresses the mitotic clonal expansion of 3T3-L1 preadipocytes in a time- and dose-dependent manner. Gene expression analysis and Western blot analysis reveal that the BBR inhibits the mRNA and protein levels of adipogenesis related transcription factors PPARgamma and C/EBPalpha and their upstream regulator, C/EBPbeta. Reporter gene assays demonstrate that the full-length PPARgamma and alpha transcription activities are inhibited by BBR. Using real-time PCR, we have also found that the PPAR target genes that are involved in adipocyte differentiation, such as aP2, CD36, ACO, LPL, and other adipocyte markers, are suppressed by BBR. These studies suggest that BBR works on multiple molecular targets as an inhibitor of PPARgamma and alpha, and is a potential weight reducing, hypolipidemic, and hypoglycemic drug.

  16. Berberine increases adipose triglyceride lipase in 3T3-L1 adipocytes through the AMPK pathway.

    PubMed

    Jiang, Dongqing; Wang, Dianhui; Zhuang, Xianghua; Wang, Zhanqing; Ni, Yihong; Chen, Shihong; Sun, Fudun

    2016-12-09

    Obesity is closely related to the metabolism of triacylglycerol (TG) in adipocytes. Adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL) are rate-limiting enzymes that control the hydrolysis of TG. Effects on ATGL and HSL to increase lipolysis may counteract obesity. Berberine (BBR) is a compound derived from the Chinese medicine plant Coptis chinensis. In the present study we show the effects of BBR on ATGL and HSL and explore the potential underlying mechanisms of these effects. The TG content in cells was measured using a colorimetric assay. The expressions of HSL, ATGL and GPAT3 were evaluated by Western-blotting. The expression of ATGL was also evaluated by real-time PCR and radioimmunoassay. Compound C, an inhibitor of AMP-activated protein kinase (AMPK), was used to explore the possible pathway that involved in the effect of BBR on ATGL. TG content of differentiated 3T3-L1 cells was significantly decreased by more than 10% after treated with BBR. In differentiated 3T3-L1 adipocytes, BBR increased the expression of p-HSL and ATGL, and these effects were time-depended (p <0.01). The effect of BBR on ATGL expression could be abolished by Compound C which suggested that AMPK pathway was involved in the effects of BBR on p-HSL and ATGL. BBR could increase the expression of ATGL and therefore stimulate basal lipolysis in mature adipocytes through the associated mechanisms related to the AMPK pathway.

  17. Updating long-range transport model predictions using real-time monitoring data in case of nuclear accidents with release to the atmosphere

    NASA Astrophysics Data System (ADS)

    Raes, Frank; Tassone, Caterina; Grippa, Gianni; Zarimpas, Nicolas; Graziani, Giovanni

    A procedure is developed to reduce the uncertainties of long-range transport model predictions, in case of a large scale nuclear accident. It is based on the availability in 'real time' of the concentrations of airborne radioactive aerosols from automatic on-line monitors, which are presently being installed throughout Europe. Essentially, the procedure consists of: (1) constructing new (area) source terms from the measured field data as they become available; and (2) restart the prediction with these sources, rather than with the original (point) source. The procedure is applied to the Chernobyl accident. It is shown that the procedure is feasible and might result in an improvement of the prediction of the location of the cloud by several hundreds of kilometers and the actual levels with an order of magnitude. The weak point is the treatment of the vertical structure and transport of the cloud, which can only be solved when 'real-time' upper air observations are also available.

  18. GNSS tropospheric tomography in Near-Real Time mode as a valuable data source for Numerical Weather Prediction models

    NASA Astrophysics Data System (ADS)

    Trzcina, Estera; Rohm, Witold; Dymarska, Natalia

    2017-04-01

    GNSS tropospheric tomography is a technique that aims to obtain spatial distribution of wet refractivity in the lower atmosphere based on satellite signal delay. These estimates, strictly related to the water vapor amount in atmosphere, can be assimilated in Numerical Weather Prediction (NWP) models. These observations are very valuable for the weather prediction process. Water vapor amount in the troposphere is one of the most important factors forming weather conditions. Moreover it is highly variable in time and space, thus should be monitored with high spatio-temporal resolution. Vertical distribution of the water vapor in the atmosphere is usually obtained by balloon-based radiosonde sounding. This approach is very common, but also expensive. Spatial and temporal resolutions of these measurements are rather poor in comparison to the NWP models. In contrast, resolution of the GNSS tomography can be similar to the NWP models with no additional costs, especially on the areas equipped with well-developed GNSS stations networks. Previous studies on GNSS tomography indicates that the accuracy of the results is satisfactory and might be applied in meteorology. Tropospheric tomography is a very promising technique for the weather prediction because of the slant satellite observations utilization - Slant Wet Delays (SWD) or Slant Integrated Water Vapor (SIWV). Due to the slant trajectories of the GNSS signals crossing atmosphere and tomography inverse processing the vertical profiles of humidity can be estimated. In this study an effort was made to meet two major preconditions for tomographic data assimilation in NWP: 1) adjusting tomography model to near-real time (NRT) observation and 2) reaching required accuracy of the solution. Moreover the first attempt of assimilation tomographic data in NWP model was made using refractivity profile operator (GPS_REF). GNSS tomography model TOMO2 was adjusted to use NRT troposphere observation by using predicted orbits, ZTDs and

  19. Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory.

    PubMed

    Kazerounian, Sohrob; Grossberg, Stephen

    2014-01-01

    How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list ABADBD. Comparisons

  20. Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory

    PubMed Central

    Kazerounian, Sohrob; Grossberg, Stephen

    2014-01-01

    How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list ABADBD. Comparisons

  1. A model and simulation to predict 3D imaging LADAR sensor systems performance in real-world type environments

    NASA Astrophysics Data System (ADS)

    Grasso, Robert J.; Dippel, George F.; Russo, Leonard E.

    2006-08-01

    BAE SYSTEMS reports on a program to develop a high-fidelity model and simulation to predict the performance of angle-angle-range 3D flash LADAR Imaging Sensor systems. Accurate methods to model and simulate performance from 3D LADAR systems have been lacking, relying upon either single pixel LADAR performance or extrapolating from passive detection FPA performance. The model and simulation here is developed expressly for 3D angle-angle-range imaging LADAR systems. To represent an accurate "real world" type environment this model and simulation accounts for: 1) laser pulse shape; 2) detector array size; 3) detector noise figure; 4) detector gain; 5) target attributes; 6) atmospheric transmission; 7) atmospheric backscatter; 8) atmospheric turbulence; 9) obscurants; 10) obscurant path length, and; 11) platform motion. The angle-angle-range 3D flash LADAR model and simulation accounts for all pixels in the detector array by modeling and accounting for the non-uniformity of each individual pixel. Here, noise sources and gain are modeled based upon their pixel-to-pixel statistical variation. A cumulative probability function is determined by integrating the normal distribution with respect to detector gain, and, for each pixel, a random number is compared with the cumulative probability function resulting in a different gain for each pixel within the array. In this manner very accurate performance is determined pixel-by-pixel for the entire array. Model outputs are 3D images of the far-field distribution across the array as intercepted by the target, gain distribution, power distribution, average signal-to-noise, and probability of detection across the array.

  2. Methods Developed by the Tools for Engine Diagnostics Task to Monitor and Predict Rotor Damage in Real Time

    NASA Technical Reports Server (NTRS)

    Baaklini, George Y.; Smith, Kevin; Raulerson, David; Gyekenyesi, Andrew L.; Sawicki, Jerzy T.; Brasche, Lisa

    2003-01-01

    Tools for Engine Diagnostics is a major task in the Propulsion System Health Management area of the Single Aircraft Accident Prevention project under NASA s Aviation Safety Program. The major goal of the Aviation Safety Program is to reduce fatal aircraft accidents by 80 percent within 10 years and by 90 percent within 25 years. The goal of the Propulsion System Health Management area is to eliminate propulsion system malfunctions as a primary or contributing factor to the cause of aircraft accidents. The purpose of Tools for Engine Diagnostics, a 2-yr-old task, is to establish and improve tools for engine diagnostics and prognostics that measure the deformation and damage of rotating engine components at the ground level and that perform intermittent or continuous monitoring on the engine wing. In this work, nondestructive-evaluation- (NDE-) based technology is combined with model-dependent disk spin experimental simulation systems, like finite element modeling (FEM) and modal norms, to monitor and predict rotor damage in real time. Fracture mechanics time-dependent fatigue crack growth and damage-mechanics-based life estimation are being developed, and their potential use investigated. In addition, wireless eddy current and advanced acoustics are being developed for on-wing and just-in-time NDE engine inspection to provide deeper access and higher sensitivity to extend on-wing capabilities and improve inspection readiness. In the long run, these methods could establish a base for prognostic sensing while an engine is running, without any overt actions, like inspections. This damage-detection strategy includes experimentally acquired vibration-, eddy-current- and capacitance-based displacement measurements and analytically computed FEM-, modal norms-, and conventional rotordynamics-based models of well-defined damages and critical mass imbalances in rotating disks and rotors.

  3. Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

    NASA Astrophysics Data System (ADS)

    Zhu, Qing; Zhou, Zhiwen; Duncan, Emily W.; Lv, Ligang; Liao, Kaihua; Feng, Huihui

    2017-02-01

    Spatio-temporal variability of soil moisture (θ) is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time θ monitoring methods. This restricted the comprehensive and intensive examination of θ dynamics. In this study, we integrated the manual and real-time monitored data to depict the hillslope θ dynamics with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear (support vector machines-SVM) models were used to predict θ at 39 manual sites (collected 1-2 times per month) with θ collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each depth and manual site, an optimal prediction model was then determined at this depth of this site. Results showed that θ at the 39 manual sites can be reliably predicted (root mean square errors <0.028 m3 m-3) using both SMLR and SVM. The linear or non-linear relationship between θ at each manual site and at the three real-time monitoring sites was the main reason for choosing SMLR or SVM as the optimal prediction model. The subsurface flow dynamics was an important factor that determined whether the relationship was linear or non-linear. Depth to bedrock, elevation, topographic wetness index, profile curvature, and θ temporal stability influenced the selection of prediction model since they were related to the subsurface soil water distribution and movement. Using this approach, hillslope θ spatial distributions at un-sampled times and dates can be predicted. Missing information of hillslope θ dynamics can be acquired successfully.

  4. Multitasking capacities in persons diagnosed with schizophrenia: a preliminary examination of their neurocognitive underpinnings and ability to predict real world functioning.

    PubMed

    Laloyaux, Julien; Van der Linden, Martial; Levaux, Marie-Noëlle; Mourad, Haitham; Pirri, Anthony; Bertrand, Hervé; Domken, Marc-André; Adam, Stéphane; Larøi, Frank

    2014-07-30

    Difficulties in everyday life activities are core features of persons diagnosed with schizophrenia and in particular during multitasking activities. However, at present, patients׳ multitasking capacities have not been adequately examined in the literature due to the absence of suitable assessment strategies. We thus recently developed a computerized real-life activity task designed to take into account the complex and multitasking nature of certain everyday life activities where participants are required to prepare a room for a meeting. Twenty-one individuals diagnosed with schizophrenia and 20 matched healthy controls completed the computerized task. Patients were also evaluated with a cognitive battery, measures of symptomatology and real world functioning. To examine the ecological validity, 14 other patients were recruited and were given the computerized version and a real version of the meeting preparation task. Results showed that performance on the computerized task was significantly correlated with executive functioning, pointing to the major implication of these cognitive processes in multitasking situations. Performance on the computerized task also significantly predicted up to 50% of real world functioning. Moreover, the computerized task demonstrated good ecological validity. These findings suggest the importance of evaluating multitasking capacities in patients diagnosed with schizophrenia in order to predict real world functioning.

  5. T3 and cardiac myocyte cell: a theoretical model.

    PubMed

    Athanasios, Tsatsaris; Antonios, Baldoukas; Antonios, Loumousiotis; Eustathios, Koukounaris; Maria, Giota; Despina, Perrea

    2013-08-01

    In the last decades, the outstanding role of Thyroid gland in regulating both physiological and pathological operation of cardiovascular system has been acknowledged worldwide. Three main domains of Thyroid function, that is to say, euthyroidism -hyperthyroidism-hypothyroidism, have a direct impact on cardiac response through a variety of mechanisms. Cellular pathways mediate in cardiac contractility, cardiac output, cardiac rhythm, arterial blood pressure and peripheral vessel resistance. Particular biochemical algorithms exist not only between Thyroid hormones' serum concentration and thyroid gland but also between the hormones' serum level and heart muscle genes. These biochemical pathways primarily regulate the appropriate secretion of levothyroxine (T4) and triiodothyronine(T3) via Thyroid- Stimulating-Hormone(TSH) pituitary system, and secondly adjust the cardiac function. In this study, a mathematic model has been developed describing significant aspects of positive or negative feedback mechanisms of THYRO-CARDIAC (THY-CAR) system along with potential applications of novel up-to-date patents in this area of research.

  6. Magnetotransport properties of the α-T 3 model

    NASA Astrophysics Data System (ADS)

    Biswas, Tutul; Kanti Ghosh, Tarun

    2016-12-01

    Using the well-known Kubo formula, we evaluate magnetotransport quantities, such as the collisional and Hall conductivities of the α-T 3 model. The collisional conductivity exhibits a series of peaks at a strong magnetic field. Each of the conductivity peaks for α =0 (graphene) splits into two in the presence of a finite α. This splitting occurs due to a finite phase difference between the contributions coming from the two valleys. The density of states is also calculated to explore the origin of the splitting of conductivity peaks. As α approaches 1, the right split part of a conductivity peak comes closer to the left split part of the next conductivity peak. At α =1 , they merge with each other to produce a new series of the conductivity peaks. On the other hand, the Hall conductivity undergoes a smooth transition from {σyx}=2(2n+1){{e}2}/h to {σyx}=4n{{e}2}/h with n  =  0,1,2,... as we tune α from 0-1. For intermediate α, we obtain the Hall plateaus at values 0,2,4,6,8,... in units of e 2/h.

  7. miR-26b Promotes 3T3-L1 Adipocyte Differentiation Through Targeting PTEN.

    PubMed

    Li, Guilin; Ning, Chunyou; Ma, Yao; Jin, Long; Tang, Qianzi; Li, Xuewei; Li, Mingzhou; Liu, Haifeng

    2017-08-01

    microRNAs (miRNAs) play important roles in adipogenesis that is closely linked to obesity and energy homeostasis. Thus far, only a few miRNAs have been identified to regulate adipocyte development, arousing interest in the detailed function of miRNAs during adipogenesis. In this study, we found that the miR-26b expression showed an increasing trend during 3T3-L1 cells differentiation. To investigate the role of miR-26b in adipogenesis, the synthetic miR-26b agomirs and antagomirs were used to perform overexpression and knockdown experiment, respectively. Our data revealed that overexpression of miR-26b significantly accelerated the mRNA expression of the adipogenic markers, peroxisome proliferator-activated receptor gamma (PPARγ), fatty acid synthase (FAS), CCAAT/enhancer binding protein alpha (C/EBPα), and lipoprotein lipase, and the protein level of PPARγ and FAS. miR-26b overexpression also resulted in a significant increase in lipid accumulation. In contrast, inhibition of miR-26b expression decreased differentiation of 3T3-L1 cells. By target gene prediction and luciferase reporter assay, we demonstrated that miR-26b may directly bind to the 3' UTR of phosphatase and tensin homolog (PTEN). Taken together, these results demonstrate that miR-26b might participate in regulating adipogenic differentiation in 3T3-L1 cells by inhibiting the PTEN expression, further highlighting the importance of miRNA in adipogenesis.

  8. Enhanced osteogenic differentiation of MC3T3-E1 on rhBMP-2-immobilized titanium via click reaction.

    PubMed

    Kim, Eun-Cheol; Kim, Tae-Hee; Jung, Jae-Hoon; Hong, Sung Ok; Lee, Deok-Won

    2014-03-15

    In the present study, we report about the efficacy of titanium surface-immobilized with bone morphogenetic protein-2 (BMP-2) via click reaction on enhanced osteogenic differentiation of MC3T3-E1 cells. The surface was characterized by static contact angles and XPS measurements, which indicated that pristine titanium (Ti-1) was successfully surface-modified via click chemistry (aminated titanium, Ti-4). By quantitative analysis of heparin immobilized on aminated titanium (Ti-4), we found that the Ti-4 can be used as a good candidate to immobilize biomolecules such as heparin. BMP-2 from titanium immobilized with BMP-2 (Ti-6) was released for a period of 28 days in a sustained manner. The highest proliferation rate of MC3T3-E1 cells was observed on Ti-6. Through in vitro tests including alkaline phosphatase (ALP) activity, calcium deposition and real-time polymerase chain reaction (real-time PCR), we found that Ti-6 can be used as a good implant to enhance the osteogenic differentiation of MC3T3-E1 cells.

  9. Real-Time Predictions of Reservoir Size and Rebound Time during Antiretroviral Therapy Interruption Trials for HIV

    PubMed Central

    Rosenbloom, Daniel I. S.; Goldstein, Edward; Hanhauser, Emily; Kuritzkes, Daniel R.

    2016-01-01

    Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART) interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients—between 40 and 150—will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two “Boston patients”, recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV+ cells in the recipient versus newly infected cells from the donor made to the residual reservoir

  10. Real-Time Predictions of Reservoir Size and Rebound Time during Antiretroviral Therapy Interruption Trials for HIV.

    PubMed

    Hill, Alison L; Rosenbloom, Daniel I S; Goldstein, Edward; Hanhauser, Emily; Kuritzkes, Daniel R; Siliciano, Robert F; Henrich, Timothy J

    2016-04-01

    Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART) interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients-between 40 and 150-will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two "Boston patients", recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV+ cells in the recipient versus newly infected cells from the donor made to the residual reservoir that

  11. International journal of computational fluid dynamics real-time prediction of unsteady flow based on POD reduced-order model and particle filter

    NASA Astrophysics Data System (ADS)

    Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru

    2016-04-01

    An integrated method consisting of a proper orthogonal decomposition (POD)-based reduced-order model (ROM) and a particle filter (PF) is proposed for real-time prediction of an unsteady flow field. The proposed method is validated using identical twin experiments of an unsteady flow field around a circular cylinder for Reynolds numbers of 100 and 1000. In this study, a PF is employed (ROM-PF) to modify the temporal coefficient of the ROM based on observation data because the prediction capability of the ROM alone is limited due to the stability issue. The proposed method reproduces the unsteady flow field several orders faster than a reference numerical simulation based on Navier-Stokes equations. Furthermore, the effects of parameters, related to observation and simulation, on the prediction accuracy are studied. Most of the energy modes of the unsteady flow field are captured, and it is possible to stably predict the long-term evolution with ROM-PF.

  12. Diffusion algorithms and data reduction routine for onsite real-time launch predictions for the transport of Delta-Thor exhaust effluents

    NASA Technical Reports Server (NTRS)

    Stephens, J. B.

    1976-01-01

    The National Aeronautics and Space Administration/Marshall Space Flight Center multilayer diffusion algorithms have been specialized for the prediction of the surface impact for the dispersive transport of the exhaust effluents from the launch of a Delta-Thor vehicle. This specialization permits these transport predictions to be made at the launch range in real time so that the effluent monitoring teams can optimize their monitoring grids. Basically, the data reduction routine requires only the meteorology profiles for the thermodynamics and kinematics of the atmosphere as an input. These profiles are graphed along with the resulting exhaust cloud rise history, the centerline concentrations and dosages, and the hydrogen chloride isopleths.

  13. Investigation of the Compressive Strength and Creep Lifetime of 2024-T3 Aluminum-Alloy Plates at Elevated Temperatures

    NASA Technical Reports Server (NTRS)

    Mathauser, Eldon E; Deveikis, William D

    1957-01-01

    The results of elevated-temperature compressive strength and creep tests of 2024-t3 (formerly 24s-t3) aluminum alloy plates supported in v-grooves are presented. The strength-test results indicate that a relation previously developed for predicting plate compressive strength for plates of all materials at room temperature is also satisfactory for determining elevated-temperature strength. Creep-lifetime results are presented for plates in the form of master creep-lifetime curves by using a time-temperature parameter that is convenient for summarizing tensile creep-rupture data. A comparison is made between tensile and compressive creep lifetime for the plates and a method that made use of isochronous stress-strain curves for predicting plate-creep failure stresses is investigated.

  14. An assessment of the small-crack effect for 2024-T3 aluminum alloy

    NASA Technical Reports Server (NTRS)

    Newman, J. C., Jr.; Swain, M. H.; Phillips, E. P.

    1986-01-01

    Data on small-crack behavior were obtained for a single-edge-notched tensile specimen made of 2024-T3 Al alloy and used to evaluate the capability of a semiempirical crack-growth and closure model to predict the fatigue life of notched specimens. Fatigue tests were conducted under either constant-amplitude loading (with stress ratios of 0.5, 0, -1, and -2) or spectrum loading, using a replication technique to record growth. It was found that small cracks exhibited the 'small-crack' effect in that they grew faster than large cracks when subjected to the same stress intensity factor range. Experimental small-crack growth rates agreed well with the model predictions. For making predictions of fatigue life, an initial surface defect void size of 3 x 12 x 0.4 microns was used in all calculations; predicted fatigue lives agreed well with experimentally determined values obtained in all tests. The crack-closure model indicated that the 'small-crack' effect on fatigue life was greatest in tests involving significant compressive loads.

  15. Bovine Collagen Peptides Compounds Promote the Proliferation and Differentiation of MC3T3-E1 Pre-Osteoblasts

    PubMed Central

    Liu, JunLi; Zhang, Bing; Song, ShuJun; Ma, Ming; Si, ShaoYan; Wang, YiHu; Xu, BingXin; Feng, Kai; Wu, JiGong; Guo, YanChuan

    2014-01-01

    Objective Collagen peptides (CP) compounds, as bone health supplements, are known to play a role in the treatment of osteoporosis. However, the molecular mechanisms of this process remain unclear. This study aimed to investigate the effects of bovine CP compounds on the proliferation and differentiation of MC3T3-E1 cells. Methods Mouse pre-osteoblast cell line MC3T3-E1 subclone 4 cells were treated with bovine CP compounds. Cell proliferation was analyzed by MTT assays and the cell cycle was evaluated by flow cytometry scanning. Furthermore, MC3T3-E1 cell differentiation was analyzed at the RNA level by real-time PCR and at the protein level by western blot analysis for runt-related transcription factor 2 (Runx2), a colorimetric p-nitrophenyl phosphate assay for alkaline phosphatase (ALP), and ELISA for osteocalcin (OC). Finally, alizarin red staining for mineralization was measured using Image Software Pro Plus 6.0. Results Cell proliferation was very efficient after treatment with different concentrations of bovine CP compounds, and the best concentration was 3 mg/mL. Bovine CP compounds significantly increased the percentage of MC3T3-E1 cells in G2/S phase. Runx2 expression, ALP activity, and OC production were significantly increased after treatment with bovine CP compounds for 7 or 14 days. Quantitative analyses with alizarin red staining showed significantly increased mineralization of MC3T3-E1 cells after treatment with bovine CP compounds for 14 or 21 days. Conclusions Bovine CP compounds increased osteoblast proliferation, and played positive roles in osteoblast differentiation and mineralized bone matrix formation. Taking all the experiments together, our study indicates a molecular mechanism for the potential treatment of osteoarthritis and osteoporosis. PMID:24926875

  16. Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network.

    PubMed

    Faraggi, Eshel; Xue, Bin; Zhou, Yaoqi

    2009-03-01

    This article attempts to increase the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins through improved learning. Most methods developed for improving the backpropagation algorithm of artificial neural networks are limited to small neural networks. Here, we introduce a guided-learning method suitable for networks of any size. The method employs a part of the weights for guiding and the other part for training and optimization. We demonstrate this technique by predicting residue solvent accessibility and real-value backbone torsion angles of proteins. In this application, the guiding factor is designed to satisfy the intuitive condition that for most residues, the contribution of a residue to the structural properties of another residue is smaller for greater separation in the protein-sequence distance between the two residues. We show that the guided-learning method makes a 2-4% reduction in 10-fold cross-validated mean absolute errors (MAE) for predicting residue solvent accessibility and backbone torsion angles, regardless of the size of database, the number of hidden layers and the size of input windows. This together with introduction of two-layer neural network with a bipolar activation function leads to a new method that has a MAE of 0.11 for residue solvent accessibility, 36 degrees for psi, and 22 degrees for phi. The method is available as a Real-SPINE 3.0 server in http://sparks.informatics.iupui.edu.

  17. Evaluation of the 1998 Predictions of the Run-Timing of Wild Migrant Yearling Chinook and Water Quality at Multiple Locations on the Snake and Columbia Rivers using CRiSP/RealTime, 1998 Technical Report.

    SciTech Connect

    Beer, W. Nicholas; Hayes, Joshua A.; Shaw, Pamela

    1999-07-21

    Since 1988, wild salmon have been PIT-tagged through monitoring and research programs conducted by the Columbia River fisheries agencies and Tribes. Workers at the University of Washington have used detection data at Lower Granite Dam to generate predictions of arrival distributions for various stocks at the dam. The prediction tool is known as RealTime. In 1996, RealTime predictions were linked to a downstream migration model, CRiSP.1. The composite model, known as CRiSP/RealTime, predicts the arrival distribution and fraction transported at downriver locations.

  18. Comparison of only T3 and T3–T4 sympathectomy for axillary hyperhidrosis regarding treatment effect and compensatory sweating

    PubMed Central

    Yuncu, Gökhan; Turk, Figen; Ozturk, Gökhan; Atinkaya, Cansel

    2013-01-01

    OBJECTIVES Patients diagnosed with axillary hyperhidrosis can face psychosocial issues that can ultimately hinder their quality of life both privately and socially. The routine treatment for axillary hyperhidrosis is T3–T4 sympathectomy, but compensatory sweating is a serious side effect that is commonly seen with this approach. This study was designed to evaluate whether a T3 sympathectomy was effective for the treatment of axillary hyperhidrosis and whether this treatment led to less compensatory sweating than T3–T4 sympathectomies among our 60-patient population. METHODS One hundred and twenty endoscopic thoracic sympathectomies were performed on 60 patients who had axillary hyperhidrosis. The sympathectomies were accomplished by means of a single-lumen endotracheal tube and a single port. The axillary hyperhidrosis patients were randomly divided into two groups with 17 patients in Group 1 undergoing T3–T4 sympathectomies and 43 in Group 2 undergoing only T3 sympathectomies. We analysed the data associated with the resolution of axillary hyperhidrosis, the degree of patient satisfaction with the surgical outcome and the quality of life in parallel with compensatory sweating after the procedure as reported by the patient and confirmed by the examiner. Moreover, the results were compared statistically. RESULTS No statistically significant difference was observed between the groups based on age (P = 0.56), gender (P = 0.81), duration of the surgery (P = 0.35) or postoperative satisfaction levels (P = 0.45). However, the incidence and degree of compensatory sweating were lower in the T3 group than the T3–T4 group at the 1-year follow-up (P = 0.008). CONCLUSIONS T3 sympathectomy was as effective as T3–T4 sympathectomy for the treatment of axillary hyperhidrosis based on the patients’ reported postoperative satisfaction, and the T3 group demonstrated lower compensatory sweating at the 1-year follow-up. PMID:23644731

  19. Proof test and fatigue crack growth modeling on 2024-T3 aluminum alloy

    NASA Technical Reports Server (NTRS)

    Newman, J. C., Jr.; Poe, C. C., Jr.; Dawicke, D. S.

    1990-01-01

    Pressure proof testing of aircraft fuselage structures has been suggested as a means of screening critical crack sizes and of extending their useful life. The objective of this paper is to study the proof-test concept and to model the crack-growth process on a ductile material. Simulated proof and operational fatigue life tests have been conducted on cracked panels made of 2024-T3 aluminum alloy sheet material. A fatigue crack-closure model was modified to simulate the proof test and operational fatigue cycling. Using crack-growth rate and resistance-curve data, the model was able to predict crack growth during and after the proof load. These tests and analyses indicate that the proof test increases fatigue life; but the beneficial life, after a 1.33 or 1.5 proof, was less than a few hundred cycles.

  20. Digital holography particle image velocimetry for the measurement of 3D t-3c flows

    NASA Astrophysics Data System (ADS)

    Shen, Gongxin; Wei, Runjie

    2005-10-01

    In this paper a digital in-line holographic recording and reconstruction system was set up and used in the particle image velocimetry for the 3D t-3c (the three-component (3c), velocity vector field measurements in a three-dimensional (3D), space field with time history ( t)) flow measurements that made up of the new full-flow field experimental technique—digital holographic particle image velocimetry (DHPIV). The traditional holographic film was replaced by a CCD chip that records instantaneously the interference fringes directly without the darkroom processing, and the virtual image slices in different positions were reconstructed by computation using Fresnel-Kirchhoff integral method from the digital holographic image. Also a complex field signal filter (analyzing image calculated by its intensity and phase from real and image parts in fast fourier transform (FFT)) was applied in image reconstruction to achieve the thin focus depth of image field that has a strong effect with the vertical velocity component resolution. Using the frame-straddle CCD device techniques, the 3c velocity vector was computed by 3D cross-correlation through space interrogation block matching through the reconstructed image slices with the digital complex field signal filter. Then the 3D-3c-velocity field (about 20 000 vectors), 3D-streamline and 3D-vorticiry fields, and the time evolution movies (30 field/s) for the 3D t-3c flows were displayed by the experimental measurement using this DHPIV method and techniques.

  1. Monoterpene limonene induces brown fat-like phenotype in 3T3-L1 white adipocytes.

    PubMed

    Lone, Jameel; Yun, Jong Won

    2016-05-15

    Several dietary compounds that are able to induce the brown fat-like phenotype in white adipocytes have been considered for treatment of obesity due to their ability to increase energy expenditure. Here, we report that limonene induces the brown fat-like phenotype in 3T3-L1 adipocytes by increasing expression of brown adipocyte-specific genes and proteins. Limonene-induced browning in white adipocytes was investigated by determining expression levels of brown fat-specific genes and proteins by real-time RT-PCR, immunoblot analysis, and immunocytochemical staining. Limonene enhanced mitochondrial biogenesis, as evidenced by increased mitochondrial content and immunofluorescent intensity. Limonene also significantly elevated protein levels of HSL, PLIN, p-AMPK, p-ACC, ACO, COX4, CPT1, and CYT C, suggesting its possible role in enhancement of lipolysis and lipid catabolism. Increased expression of PRDM16, UCP1, C/EBPβ, and other brown fat-specific markers by limonene was possibly mediated by activation of β3-adnergenic receptor (β3-AR), as inhibition of β3-AR inhibited up-regulation of brown fat-specific markers. Similarly, limonene-mediated activation of ERK and up-regulation of key brown adipocyte specific markers were eliminated by treatment with ERK antagonist. Taken together, these results suggest that limonene induces browning of 3T3-L1 adipocytes via activation of β3-AR and the ERK signaling pathway. In conclusion, our findings suggest that limonene plays a dual modulatory role in induction of the brown adipocyte-like phenotype as well as promotion of lipid metabolism and thus may have potential therapeutic implications for treatment of obesity. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Suppression of adipocyte differentiation and lipid accumulation by stearidonic acid (SDA) in 3T3-L1 cells.

    PubMed

    Li, Yueru; Rong, Yinghui; Bao, Lisui; Nie, Ben; Ren, Guang; Zheng, Chen; Amin, Rajesh; Arnold, Robert D; Jeganathan, Ramesh B; Huggins, Kevin W

    2017-09-25

    Increased consumption of omega-3 (ω-3) fatty acids found in cold-water fish and fish oil has been reported to protect against obesity. A potential mechanism may be through reduction in adipocyte differentiation. Stearidonic acid (SDA), a plant-based ω-3 fatty acid, has been targeted as a potential surrogate for fish-based fatty acids; however, its role in adipocyte differentiation is unknown. This study was designed to evaluate the effects of SDA on adipocyte differentiation in 3T3-L1 cells. 3T3-L1 preadipocytes were differentiated in the presence of SDA or vehicle-control. Cell viability assay was conducted to determine potential toxicity of SDA. Lipid accumulation was measured by Oil Red O staining and triglyceride (TG) quantification in differentiated 3T3-L1 adipocytes. Adipocyte differentiation was evaluated by adipogenic transcription factors and lipid accumulation gene expression by quantitative real-time polymerase chain reaction (qRT-PCR). Fatty acid analysis was conducted by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS). 3T3-L1 cells treated with SDA were viable at concentrations used for all studies. SDA treatment reduced lipid accumulation in 3T3-L1 adipocytes. This anti-adipogenic effect by SDA was a result of down-regulation of mRNA levels of the adipogenic transcription factors CCAAT/enhancer-binding proteins alpha and beta (C/EBPα, C/EBPβ), peroxisome proliferator-activated receptor gamma (PPARγ), and sterol-regulatory element binding protein-1c (SREBP-1c). SDA treatment resulted in decreased expression of the lipid accumulation genes adipocyte fatty-acid binding protein (AP2), fatty acid synthase (FAS), stearoyl-CoA desaturase (SCD-1), lipoprotein lipase (LPL), glucose transporter 4 (GLUT4) and phosphoenolpyruvate carboxykinase (PEPCK). The transcriptional activity of PPARγ was found to be decreased with SDA treatment. SDA treatment led to significant EPA enrichment in 3T3-L1 adipocytes compared to vehicle-control. These

  3. The role and possible mechanism of lncRNA U90926 in modulating 3T3-L1 preadipocyte differentiation.

    PubMed

    Chen, J; Liu, Y; Lu, S; Yin, L; Zong, C; Cui, S; Qin, D; Yang, Y; Guan, Q; Li, X; Wang, X

    2017-02-01

    Obesity is a risk factor for metabolic diseases, while preadipocyte differentiation or adipogenesis is closely related to obesity occurrence. Long noncoding RNAs (lncRNAs) are a unique class of transcripts in regulation of a variety of biological processes. Using cDNA microarray, we found lncRNA U90926 is negatively correlated with 3T3-L1 preadipocyte differentiation. The aim of this study was to explore the role of lncRNA U90926 (lnc-U90926) in adipogenesis and the underlying mechanisms. Quantitative real-time PCR (qPCR) was performed to determine lnc-U90926 expression in 3T3-L1 preadipocytes, differentiated adipocytes, and in adipose tissues form mice. RNA fluorescent in situ hybridization (FISH) was performed to determine the localization of lnc-U90926 in 3T3-L1 preadipocytes. The effects of lnc-U90926 on 3T3-L1 adipogenesis were analyzed with lentivirus-mediated gain- and loss-of-function experiments. Lipid accumulation was evaluated by oil red O staining; several adipogenesis makers were analyzed by qPCR and western blotting. Dual luciferase assay was applied to explore the transactivation of target genes modulated by lnc-U90926. All measurements were performed at least for three times. Lnc-U90926 expression decreased along the differentiation of 3T3-L1 preadipocytes. In mice, lnc-U90926 is predominantly expressed in adipose tissue. Obese mice have lower lnc-U90926 expression in subcutaneous and visceral adipose tissue than non-obese mice. FISH results showed that lnc-U90926 was mainly located in the cytoplasm. Overexpression lnc-U90926 attenuated 3T3-L1 adipocyte differentiation as evidenced by its ability to inhibit lipid accumulation, to decrease the mRNA levels of peroxisome proliferator-activated receptor gamma 2 (PPARγ2), fatty acid binding protein 4 (FABP4) and adiponectin (AdipoQ) as well as to reduce the protein levels of PPARγ and FABP4 (P<0.05). Knockdown of lnc-U90926 showed opposite effects, which increased mRNA expression of PPARγ2, FABP4

  4. The role and possible mechanism of lncRNA U90926 in modulating 3T3-L1 preadipocyte differentiation

    PubMed Central

    Chen, J; Liu, Y; Lu, S; Yin, L; Zong, C; Cui, S; Qin, D; Yang, Y; Guan, Q; Li, X; Wang, X

    2017-01-01

    Background: Obesity is a risk factor for metabolic diseases, while preadipocyte differentiation or adipogenesis is closely related to obesity occurrence. Long noncoding RNAs (lncRNAs) are a unique class of transcripts in regulation of a variety of biological processes. Using cDNA microarray, we found lncRNA U90926 is negatively correlated with 3T3-L1 preadipocyte differentiation. Objective: The aim of this study was to explore the role of lncRNA U90926 (lnc-U90926) in adipogenesis and the underlying mechanisms. Methods: Quantitative real-time PCR (qPCR) was performed to determine lnc-U90926 expression in 3T3-L1 preadipocytes, differentiated adipocytes, and in adipose tissues form mice. RNA fluorescent in situ hybridization (FISH) was performed to determine the localization of lnc-U90926 in 3T3-L1 preadipocytes. The effects of lnc-U90926 on 3T3-L1 adipogenesis were analyzed with lentivirus-mediated gain- and loss-of-function experiments. Lipid accumulation was evaluated by oil red O staining; several adipogenesis makers were analyzed by qPCR and western blotting. Dual luciferase assay was applied to explore the transactivation of target genes modulated by lnc-U90926. All measurements were performed at least for three times. Results: Lnc-U90926 expression decreased along the differentiation of 3T3-L1 preadipocytes. In mice, lnc-U90926 is predominantly expressed in adipose tissue. Obese mice have lower lnc-U90926 expression in subcutaneous and visceral adipose tissue than non-obese mice. FISH results showed that lnc-U90926 was mainly located in the cytoplasm. Overexpression lnc-U90926 attenuated 3T3-L1 adipocyte differentiation as evidenced by its ability to inhibit lipid accumulation, to decrease the mRNA levels of peroxisome proliferator-activated receptor gamma 2 (PPARγ2), fatty acid binding protein 4 (FABP4) and adiponectin (AdipoQ) as well as to reduce the protein levels of PPARγ and FABP4 (P<0.05). Knockdown of lnc-U90926 showed opposite effects, which

  5. Performance on a computerized shopping task significantly predicts real world functioning in persons diagnosed with bipolar disorder.

    PubMed

    Laloyaux, Julien; Pellegrini, Nadia; Mourad, Haitham; Bertrand, Hervé; Domken, Marc-André; Van der Linden, Martial; Larøi, Frank

    2013-12-15

    Persons diagnosed with bipolar disorder often suffer from cognitive impairments. However, little is known concerning how these cognitive deficits impact their real world functioning. We developed a computerized real-life activity task, where participants are required to shop for a list of grocery store items. Twenty one individuals diagnosed with bipolar disorder and 21 matched healthy controls were administered the computerized shopping task. Moreover, the patient group was assessed with a battery of cognitive tests and clinical scales. Performance on the shopping task significantly differentiated patients and healthy controls for two variables: Total time to complete the shopping task and Mean time spent to consult the shopping list. Moreover, in the patient group, performance on these variables from the shopping task correlated significantly with cognitive functioning (i.e. processing speed, verbal episodic memory, planning, cognitive flexibility, and inhibition) and with clinical variables including duration of illness and real world functioning. Finally, variables from the shopping task were found to significantly explain 41% of real world functioning of patients diagnosed with bipolar disorder. These findings suggest that the shopping task provides a good indication of real world functioning and cognitive functioning of persons diagnosed with bipolar disorder. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. Effects of thyroid hormone transporters MCT8 and MCT10 on nuclear activity of T3.

    PubMed

    van Mullem, Alies A; van Gucht, Anja L M; Visser, W Edward; Meima, Marcel E; Peeters, Robin P; Visser, Theo J

    2016-12-05

    Transport of thyroid hormone (TH) across the plasma membrane is necessary for the genomic action of T3 mediated by its nuclear T3 receptor. MCT8 and MCT10 have been identified as important TH transporters. Mutations in MCT8 result in severe psychomotor retardation. In addition to TH transport into the cell, MCT8 and MCT10 also facilitate TH efflux from cells. Therefore, the aim of this study was to examine if MCT8 and MCT10 increase the availability of T3 for its nuclear receptor rather than generate a rapid equilibrium between cellular and serum T3. T3 action was investigated in JEG3 cells co-transfected with TRβ1 and a T3 response element-driven luciferase construct, and T3 metabolism was analyzed in cells transfected with type 3 deiodinase (D3). In addition, cells were transfected with MCT8 or MCT10 and/or the cytoplasmic T3-binding protein mu-crystallin (CRYM). Luciferase signal was markedly stimulated by incubating cells for 24 h with 1 nM T3, but this response was not augmented by MCT8 or MCT10 expression. Limiting the time of T3 exposure to 1-6 h and co-transfection with CRYM allowed for a modest increase in luciferase response to T3. In contrast, T3 metabolism by D3 was potently stimulated by MCT8 or MCT10 expression, but it was not affected by expression of CRYM. These results suggest that MCT8 and MCT10 by virtue of their bidirectional T3 transport have less effect on steady-state nuclear T3 levels than on T3 levels at the cell periphery where D3 is located. CRYM alters the dynamics of cellular TH transport but its exact function in the cellular distribution of TH remains to be determined.

  7. Predicting three-month and 12-month post-fitting real-world hearing-aid outcome using pre-fitting acceptable noise level (ANL).

    PubMed

    Wu, Yu-Hsiang; Ho, Hsu-Chueh; Hsiao, Shih-Hsuan; Brummet, Ryan B; Chipara, Octav

    2016-01-01

    Determine the extent to which pre-fitting acceptable noise level (ANL), with or without other predictors such as hearing-aid experience, can predict real-world hearing-aid outcomes at three and 12 months post-fitting. ANLs were measured before hearing-aid fitting. Post-fitting outcome was assessed using the international outcome inventory for hearing aids (IOI-HA) and a hearing-aid use questionnaire. Models that predicted outcomes (successful vs. unsuccessful) were built using logistic regression and several machine learning algorithms, and were evaluated using the cross-validation technique. A total of 132 adults with hearing impairment. The prediction accuracy of the models ranged from 61% to 68% (IOI-HA) and from 55% to 61% (hearing-aid use questionnaire). The models performed more poorly in predicting 12-month than three-month outcomes. The ANL cutoff between successful and unsuccessful users was higher for experienced (∼18 dB) than first-time hearing-aid users (∼10 dB), indicating that most experienced users will be predicted as successful users regardless of their ANLs. Pre-fitting ANL is more useful in predicting short-term (three months) hearing-aid outcomes for first-time users, as measured by the IOI-HA. The prediction accuracy was lower than the accuracy reported by some previous research that used a cross-sectional design.

  8. Predicting 3-month and 12-month Post-Fitting Real-World Hearing Aid Outcome using Pre-fitting Acceptable Noise Level (ANL)

    PubMed Central

    Wu, Yu-Hsiang; Ho, Hsu-Chueh; Hsiao, Shih-Hsuan; Brummet, Ryan B.; Chipara, Octav

    2016-01-01

    Objective Determine the extent to which pre-fitting acceptable noise level (ANL), with or without other predictors such as hearing aid experience, can predict real-world hearing aid outcomes at 3 and 12 months post-fitting. Design ANLs were measured before hearing aid fitting. Post-fitting outcome was assessed using the International Outcome Inventory for Hearing Aids (IOI-HA) and a hearing aid use questionnaire. Models that predicted outcomes (successful vs. unsuccessful) were built using logistic regression and several machine learning algorithms, and were evaluated using the cross-validation technique. Study sample 132 adults with hearing impairment. Results The prediction accuracy of the models ranged from 61% to 68% (IOI-HA) and from 55% to 61% (hearing aid use questionnaire). The models performed more poorly in predicting 12-month than 3-month outcomes. The ANL cutoff between successful and unsuccessful users was higher for experienced (~18 dB) than first-time hearing aid users (~10 dB), indicating that most experienced users will be predicted as successful users regardless of their ANLs. Conclusions Pre-fitting ANL is more useful in predicting short-term (3 months) hearing aid outcomes for first-time users, as measured by the IOI-HA. The prediction accuracy was lower than the accuracy reported by some previous research that used a cross-sectional design. PMID:26878163

  9. Real-time prediction and gating of respiratory motion in 3D space using extended Kalman filters and Gaussian process regression network.

    PubMed

    Bukhari, W; Hong, S-M

    2016-03-07

    The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the radiation treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting respiratory motion in 3D space and realizing a gating function without pre-specifying a particular phase of the patient's breathing cycle. The algorithm, named EKF-GPRN(+) , first employs an extended Kalman filter (EKF) independently along each coordinate to predict the respiratory motion and then uses a Gaussian process regression network (GPRN) to correct the prediction error of the EKF in 3D space. The GPRN is a nonparametric Bayesian algorithm for modeling input-dependent correlations between the output variables in multi-output regression. Inference in GPRN is intractable and we employ variational inference with mean field approximation to compute an approximate predictive mean and predictive covariance matrix. The approximate predictive mean is used to correct the prediction error of the EKF. The trace of the approximate predictive covariance matrix is utilized to capture the uncertainty in EKF-GPRN(+) prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification enables us to pause the treatment beam over such instances. EKF-GPRN(+) implements a gating function by using simple calculations based on the trace of the predictive covariance matrix. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPRN(+) . The experimental results show that the EKF-GPRN(+) algorithm reduces the patient-wise prediction error to 38%, 40% and 40% in root-mean-square, compared to no prediction, at lookahead lengths of 192 ms, 384 ms and 576 ms, respectively. The EKF-GPRN(+) algorithm can further reduce the prediction error by employing the gating

  10. Real-time prediction and gating of respiratory motion in 3D space using extended Kalman filters and Gaussian process regression network

    NASA Astrophysics Data System (ADS)

    Bukhari, W.; Hong, S.-M.

    2016-03-01

    The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the radiation treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting respiratory motion in 3D space and realizing a gating function without pre-specifying a particular phase of the patient’s breathing cycle. The algorithm, named EKF-GPRN+ , first employs an extended Kalman filter (EKF) independently along each coordinate to predict the respiratory motion and then uses a Gaussian process regression network (GPRN) to correct the prediction error of the EKF in 3D space. The GPRN is a nonparametric Bayesian algorithm for modeling input-dependent correlations between the output variables in multi-output regression. Inference in GPRN is intractable and we employ variational inference with mean field approximation to compute an approximate predictive mean and predictive covariance matrix. The approximate predictive mean is used to correct the prediction error of the EKF. The trace of the approximate predictive covariance matrix is utilized to capture the uncertainty in EKF-GPRN+ prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification enables us to pause the treatment beam over such instances. EKF-GPRN+ implements a gating function by using simple calculations based on the trace of the predictive covariance matrix. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPRN+ . The experimental results show that the EKF-GPRN+ algorithm reduces the patient-wise prediction error to 38%, 40% and 40% in root-mean-square, compared to no prediction, at lookahead lengths of 192 ms, 384 ms and 576 ms, respectively. The EKF-GPRN+ algorithm can further reduce the prediction error by employing the gating function, albeit

  11. Continuous real-time in vivo measurement of cerebral nitric oxide supports theoretical predictions of an irreversible switching in cerebral ROS after sufficient exposure to external toxins.

    PubMed

    Finnerty, Niall J; O'Riordan, Saidhbhe L; Lowry, John P; Cloutier, Mathieu; Wellstead, Peter

    2013-01-01

    Mathematical models of the interactions between alphasynuclein (αS) and reactive oxygen species (ROS) predict a systematic and irreversible switching to damagingly high levels of ROS after sufficient exposure to risk factors associated with Parkinson's disease (PD). We tested this prediction by continuously monitoring real-time changes in neurochemical levels over periods of several days in animals exposed to a toxin known to cause Parkinsonian symptoms. Nitric oxide (NO) sensors were implanted in the brains of freely moving rats and the NO levels continuously recorded while the animals were exposed to paraquat (PQ) injections of various amounts and frequencies. Long-term, real-time measurement of NO in a cohort of animals showed systematic switching in levels when PQ injections of sufficient size and frequency were administered. The experimental observations of changes in NO imply a corresponding switching in endogenous ROS levels and support theoretical predictions of an irreversible change to damagingly high levels of endogenous ROS when PD risks are sufficiently large. Our current results only consider one form of PD risk, however, we are sufficiently confident in them to conclude that: (i) continuous long-term measurement of neurochemical dynamics provide a novel way to measure the temporal change and system dynamics which determine Parkinsonian damage, and (ii) the bistable feedback switching predicted by mathematical modelling seems to exist and that a deeper analysis of its characteristics would provide a way of understanding the pathogenic mechanisms that initiate Parkinsonian cell damage.

  12. A T3 and T7 Recombinant Phage Acquires Efficient Adsorption and a Broader Host Range

    PubMed Central

    Lin, Tiao-Yin; Lo, Yi-Haw; Tseng, Pin-Wei; Chang, Shun-Fu; Lin, Yann-Tsyr; Chen, Ton-Seng

    2012-01-01

    It is usually thought that bacteriophage T7 is female specific, while phage T3 can propagate on male and female Escherichia coli. We found that the growth patterns of phages T7M and T3 do not match the above characteristics, instead showing strain dependent male exclusion. Furthermore, a T3/7 hybrid phage exhibits a broader host range relative to that of T3, T7, as well as T7M, and is able to overcome the male exclusion. The T7M sequence closely resembles that of T3. T3/7 is essentially T3 based, but a DNA fragment containing part of the tail fiber gene 17 is replaced by the T7 sequence. T3 displays inferior adsorption to strains tested herein compared to T7. The T3 and T7 recombinant phage carries altered tail fibers and acquires better adsorption efficiency than T3. How phages T3 and T7 recombine was previously unclear. This study is the first to show that recombination can occur accurately within only 8 base-pair homology, where four-way junction structures are identified. Genomic recombination models based on endonuclease I cleavages at equivalent and nonequivalent sites followed by strand annealing are proposed. Retention of pseudo-palindromes can increase recombination frequency for reviving under stress. PMID:22347414

  13. A T3 and T7 recombinant phage acquires efficient adsorption and a broader host range.

    PubMed

    Lin, Tiao-Yin; Lo, Yi-Haw; Tseng, Pin-Wei; Chang, Shun-Fu; Lin, Yann-Tsyr; Chen, Ton-Seng

    2012-01-01

    It is usually thought that bacteriophage T7 is female specific, while phage T3 can propagate on male and female Escherichia coli. We found that the growth patterns of phages T7M and T3 do not match the above characteristics, instead showing strain dependent male exclusion. Furthermore, a T3/7 hybrid phage exhibits a broader host range relative to that of T3, T7, as well as T7M, and is able to overcome the male exclusion. The T7M sequence closely resembles that of T3. T3/7 is essentially T3 based, but a DNA fragment containing part of the tail fiber gene 17 is replaced by the T7 sequence. T3 displays inferior adsorption to strains tested herein compared to T7. The T3 and T7 recombinant phage carries altered tail fibers and acquires better adsorption efficiency than T3. How phages T3 and T7 recombine was previously unclear. This study is the first to show that recombination can occur accurately within only 8 base-pair homology, where four-way junction structures are identified. Genomic recombination models based on endonuclease I cleavages at equivalent and nonequivalent sites followed by strand annealing are proposed. Retention of pseudo-palindromes can increase recombination frequency for reviving under stress.

  14. Challenges in Seeing Data as Useful Evidence in Making Predictions of the Probability of a Real-World Phenomenon

    ERIC Educational Resources Information Center

    Nilsson, Per

    2013-01-01

    This study investigates the relationship between deterministic and probabilistic reasoning when students experiment on a real-world situation involving uncertainty. Twelve students, aged eight to nine years, participated in an outdoor teaching activity that called for reflection on the growth of sunflowers within the frame of a sunflower lottery,…

  15. Engaging Middle School Students with Technology: Using Real-Time Data to Test Predictions in Aquatic Ecosystems

    ERIC Educational Resources Information Center

    Adams, Lisa G.

    2011-01-01

    Take advantage of teen internet savvy and redirect students' online travels toward exploration of our environment through streaming real-time data (RTD). Studies have shown that using RTD adds relevancy to students' learning experiences and engages them in scientific investigations. (Contains 14 online resources and 5 figures.)

  16. Engaging Middle School Students with Technology: Using Real-Time Data to Test Predictions in Aquatic Ecosystems

    ERIC Educational Resources Information Center

    Adams, Lisa G.

    2011-01-01

    Take advantage of teen internet savvy and redirect students' online travels toward exploration of our environment through streaming real-time data (RTD). Studies have shown that using RTD adds relevancy to students' learning experiences and engages them in scientific investigations. (Contains 14 online resources and 5 figures.)

  17. Challenges in Seeing Data as Useful Evidence in Making Predictions of the Probability of a Real-World Phenomenon

    ERIC Educational Resources Information Center

    Nilsson, Per

    2013-01-01

    This study investigates the relationship between deterministic and probabilistic reasoning when students experiment on a real-world situation involving uncertainty. Twelve students, aged eight to nine years, participated in an outdoor teaching activity that called for reflection on the growth of sunflowers within the frame of a sunflower lottery,…

  18. Appraising bacterial strains for rapid BOD sensing--an empirical test to identify bacterial strains capable of reliably predicting real effluent BODs.

    PubMed

    Webber, Judith B; Noonan, Mike; Pasco, Neil F; Hay, Joanne M

    2011-01-01

    The measured response of rapid biochemical oxygen demand (BOD) biosensors is often not identical to those measured using the conventional 5-day BOD assay. This paper highlights the efficacy of using both glucose-glutamic acid (GGA) and Organisation for Economic Cooperation and Development (OECD) BOD standards as a rapid screen for microorganisms most likely to reliably predict real effluent BODs when used in rapid BOD devices. Using these two synthetic BOD standards, a microorganism was identified that produced comparable BOD response profiles for two assays, the MICREDOX® assay and the conventional 5-day BOD(5) test. A factorial experimental design systematically evaluated the impact of four factors (microbial strain, growth media composition, media strength, and microbial growth phase) on the BOD response profiles using GGA and OECD synthetic standard substrates. An outlier was identified that showed an improved correlation between the MICREDOX® BOD (BOD(sens)) and BOD(5) assays for both the synthetic standards and for real wastewater samples. Microbial strain was the dominant factor influencing BOD(sens) values, with Arthrobacter globiformis single cultures clearly demonstrating superior rapid BOD(sens) response profiles for both synthetic and real waste samples. It was the only microorganism to approach the BOD(5) response for the OECD substrate (171 mg O(2)L(-1)), and also reported BOD values for real waste samples that were comparable to those produced by the BOD(5) test, including discriminating between filtered and unfiltered samples.

  19. Multimodel hydrologic ensemble predictions of peak flows: lessons learned from the real-time experiment in the upper Nysa Klodzka basin (SW Poland)

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz; Mizinski, Bartlomiej

    2015-04-01

    The novel system for issuing the real-time warnings against hydrologic hazards, known as HydroProg (research project no. 2011/01/D/ST10/04171 of the National Science Centre of Poland), has been implemented in the upper Nysa Klodzka basin (SW Poland). The system itself works like a bridge between automatic hydrometeorological observational networks and numerous hydrologic models. Its main objective is to automatically produce and publish flood warnings on a basis of prognoses of river stages calculated from dissimilar models and - most importantly - their multimodel ensembles which are computed in real time within HydroProg. The implementation in question for the upper Nysa Klodzka basin is abbreviated as HydroProg-Klodzko, and is feasible due to the partnership with Klodzko County which maintains the Local System for Flood Monitoring (Lokalny System Oslony Przeciwpowodziowej - LSOP). The HydroProg-Klodzko prototype is continuously, i.e. with 15-minute update, calculating multimodel hydrologic ensemble predictions and publishing them along with prognoses corresponding to individual ensemble members (www.klodzko.hydroprog.uni.wroc.pl). The real-time HydroProg-Klodzko experiment provided us with a valuable database of predictions as well as their errors and performance characteristics. At present, six hydrologic models participate in the experiment, however two of them (multi- and univariate autoregressive time series models) work uninterruptedly since the launch of the system in August 2013. The present study focuses on the detailed characterization of the real-time performance of the two models in predicting a few significant peak flows that occurred over the entire year of the experiment. In particular, we show how the two models can be weighted to produce skilful multimodel ensemble prognoses of river stages during peak flows. We identify phases of a peak flow in which, in order to improve the predictive skills, one should switch between individual models and

  20. Metamorphic T3-response genes have specific co-regulator requirements

    PubMed Central

    Havis, Emmanuelle; Sachs, Laurent M.; Demeneix, Barbara A.

    2003-01-01

    Thyroid hormone receptors (TRs) have several regulatory functions in vertebrates. In the absence of thyroid hormone (T3; triiodothyronine), apo-TRs associate with co-repressors to repress transcription, whereas in the presence of T3, holo-TRs engage transcriptional coactivators. Although many studies have addressed the molecular mechanisms of T3 action, it is not known how specific physiological responses arise. We used T3-dependent amphibian metamorphosis to analyse how TRs interact with particular co-regulators to differentially regulate gene expression during development. Using chromatin immunoprecipitation to study tissue from pre-metamorphic tad-poles, we found that TRs are physically associated with T3-responsive promoters, whether or not T3 is present. Addition of T3 results in histone H4 acetylation specifically on T3-response genes. Most importantly, we show that individual T3-response genes have distinct co-regulator requirements, the T3-dependent co-repressor-to-coactivator switch being gene-specific for both co-regulator categories. PMID:12947412

  1. Inhibitory effects of green tea catechin on the lipid accumulation in 3T3-L1 adipocytes.

    PubMed

    Lee, Mak-Soon; Kim, Chong-Tai; Kim, In-Hwan; Kim, Yangha

    2009-08-01

    The aim of the present study was to evaluate the effects of green tea (-)-epigallocatechin-3-gallate (EGCG) on the depletion of accumulated fat in differentiated 3T3-L1 adipocytes. Intracellular lipid accumulation was decreased significantly after 24 h of incubation with 10 microm EGCG, while the viability of adipocytes was reported to be unaffected. Under the same experimental conditions, the amount of glycerol released from cells into the medium was increased by 10 microm EGCG. The level of mRNA in the 3T3-L1 adipocytes was analysed by quantitative real-time RT-PCR. EGCG notably increased the mRNA level of hormone sensitive lipase (HSL), which catalyses the rate-limiting stage in hydrolysis of stored triacylglycerol to monoacylglycerol and free fatty acids. In conclusion, the experiment produced results which showed that green tea EGCG effectively depleted fat accumulation via the stimulation of lipolysis and increased HSL gene expression in 3T3-L1 adipocytes. These results may relate to the mechanism by which EGCG modulates lipolysis in adipocytes. Copyright 2009 John Wiley & Sons, Ltd.

  2. Aculeatin, a coumarin derived from Toddalia asiatica (L.) Lam., enhances differentiation and lipolysis of 3T3-L1 adipocytes.

    PubMed

    Watanabe, Akio; Kato, Tsuyoshi; Ito, Yusuke; Yoshida, Izumi; Harada, Teppei; Mishima, Takashi; Fujita, Kazuhiro; Watai, Masatoshi; Nakagawa, Kiyotaka; Miyazawa, Teruo

    2014-10-31

    Toddalia asiatica (L.) Lam. (T. asiatica) has been utilized traditionally for medicinal purposes such as the treatment of diabetes. Currently, the extract is considered to be a good source of anti-diabetic agents, but the active compounds have yet to be identified. In this study, we investigated the effects of fractionated T. asiatica extracts on the differentiation of 3T3-L1 preadipocytes and identified aculeatin as a potential active agent. When 3T3-L1 preadipocytes were treated with aculeatin isolated from T. asiatica in the presence of insulin, aculeatin increased cellular triglyceride levels and glycerol-3-phosphate dehydrogenase activity. This indicated that aculeatin could enhance the differentiation of preadipocytes into adipocytes. Further analyses using a DNA microarray and real-time quantitative reverse-transcription PCR showed an increase in the expression of peroxisome proliferator-activated receptor-γ target genes (Pparg, Ap2, Cd36, Glut4 and Adipoq) by aculeatin, suggesting that aculeatin enhances the differentiation of 3T3-L1 cells by modulating the expression of genes critical for adipogenesis. Interestingly, after treatment of differentiated adipocytes with aculeatin, glucose uptake and lipolysis were enhanced. Overall, our results suggested that aculeatin is an active compound in T. asiatica for enhancing both differentiation and lipolysis of adipocytes, which are useful for the treatment of lipid abnormalities as well as diabetes. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Effects of PEMF exposure at different pulses on osteogenesis of MC3T3-E1 cells.

    PubMed

    Li, Kangchu; Ma, Shirong; Li, Yurong; Ding, Guirong; Teng, Zenghui; Liu, Junye; Ren, Dongqing; Guo, Yao; Ma, Lei; Guo, Guozhen

    2014-09-01

    Pulsed electromagnetic fields (PEMFs) were considered to be a factor which may affect osteogenesis of osteoblasts, but the effects were diverse with different PEMF parameters. The aim of the current study is to explore the effects of exposure to PEMFs at different pulse number on osteogenesis of osteoblasts. The mouse osteoblast-like MC3T3-E1 cells were exposed to 0, 400 or 2800 pulses 400kV/m PEMF and the proliferation, differentiation and mineralization of cells were observed after PEMF exposure by the methods of MTT, biochemical measurement, real-time PCR and Alizarin Red assay. Compared with 0 pulses groups, the growth curve, alkaline phosphatase (ALP) activity, mRNA level of osteocalcin (OCN) and mineralized nodule formation of MC3T3-E1 cells did not change after 400 pulses PEMF exposure, but decreased after 2800 pulses PEMF exposure. It suggested that under our experimental conditions, only 2800 pulses 400kV/m PEMF exposure can suppress the proliferation, differentiation and mineralization of MC3T3-E1 cells, but 400 pulses 400kV/m PEMF exposure cannot. Pulse number is another involved parameter which may influence the effects of PEMF on osteogenesis of osteoblasts. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Aculeatin, a coumarin derived from Toddalia asiatica (L.) Lam., enhances differentiation and lipolysis of 3T3-L1 adipocytes

    SciTech Connect

    Watanabe, Akio; Kato, Tsuyoshi; Ito, Yusuke; Yoshida, Izumi; Harada, Teppei; Mishima, Takashi; Fujita, Kazuhiro; Watai, Masatoshi; Nakagawa, Kiyotaka; Miyazawa, Teruo

    2014-10-31

    Highlights: • Aculeatin promoted adipocyte differentiation. • Aculeatin improved glucose uptake. • Aculeatin enhanced adipocyte lipolysis. - Abstract: Toddalia asiatica (L.) Lam. (T. asiatica) has been utilized traditionally for medicinal purposes such as the treatment of diabetes. Currently, the extract is considered to be a good source of anti-diabetic agents, but the active compounds have yet to be identified. In this study, we investigated the effects of fractionated T. asiatica extracts on the differentiation of 3T3-L1 preadipocytes and identified aculeatin as a potential active agent. When 3T3-L1 preadipocytes were treated with aculeatin isolated from T. asiatica in the presence of insulin, aculeatin increased cellular triglyceride levels and glycerol-3-phosphate dehydrogenase activity. This indicated that aculeatin could enhance the differentiation of preadipocytes into adipocytes. Further analyses using a DNA microarray and real-time quantitative reverse-transcription PCR showed an increase in the expression of peroxisome proliferator-activated receptor-γ target genes (Pparg, Ap2, Cd36, Glut4 and Adipoq) by aculeatin, suggesting that aculeatin enhances the differentiation of 3T3-L1 cells by modulating the expression of genes critical for adipogenesis. Interestingly, after treatment of differentiated adipocytes with aculeatin, glucose uptake and lipolysis were enhanced. Overall, our results suggested that aculeatin is an active compound in T. asiatica for enhancing both differentiation and lipolysis of adipocytes, which are useful for the treatment of lipid abnormalities as well as diabetes.

  5. Behavior of a fluorescent analogue of calmodulin in living 3T3 cells

    PubMed Central

    1985-01-01

    interacts with intracellular components with a range of affinities. The mobility of LRB-CM in the cytoplasm was sensitive to treatment of the cells with trifluoperazine, which suggests that at least some of the intracellular binding sites are specific for calmodulin in the calcium-bound form. FRAP of LRB-CM in the nuclei of living 3T3 cells indicated that the analogue was highly mobile within the nucleus but entered the nucleus from the cytoplasm much more slowly than fluorescein isothiocyanate-dextran of comparable molecular size and much more slowly than predicted from its mobility in cytoplasm. PMID:4044638

  6. Real-time seizure prediction using RLS filtering and interpolated histogram feature based on hybrid optimization algorithm of Bayesian classifier and Hunting search.

    PubMed

    Behnam, Morteza; Pourghassem, Hossein

    2016-08-01

    Epileptic seizure prediction using EEG signal analysis is an important application for drug therapy and pediatric patient monitoring. Time series estimation to obtain the future samples of EEG signal has vital role for detecting seizure attack. In this paper, a novel density-based real-time seizure prediction algorithm based on a trained offline seizure detection algorithm is proposed. In the offline seizure detection procedure, after signal preprocessing, histogram-based statistical features are extracted from signal probability distribution. By defining a deterministic polynomial model on the normalized histogram, a novel syntactic feature that is named Interpolated Histogram Feature (IHF) is proposed. Moreover, with this feature, Seizure Distribution Model (SDM) as a descriptor of the seizure and non-seizure signals is presented. By using a novel hybrid optimization algorithm based on Bayesian classifier and Hunting Search (HuS) algorithm, the optimal features are selected. To detect the seizure attacks in the online mode, a Multi-Layer Perceptron (MLP) classifier is trained with the optimal features in the offline procedure. For online prediction, the enhanced Recursive Least Square (RLS) filter is applied to estimate sample-by-sample of the EEG signal. Also, a density-based signal tracking scenario is introduced to update and tune the parameters of RLS filtering algorithm. Our prediction algorithm is evaluated on 104 hours of EEG signals recorded from 23 pediatric patients. Our online signal prediction algorithm provides the accuracy rate of 86.56% and precision rate of 86.53% simultaneously using the trained MLP classifier from the offline mode. The recall rate of seizure prediction is 97.27% and the false prediction rate of 0.00215 per hour is achieved as well. Ultimately, the future samples of EEG signal are estimated, and the time of seizure signal prediction is also converged to 6.64 seconds. In our proposed real-time algorithm, by implementing a density

  7. Predicting cardiovascular disease from real-time electrocardiographic monitoring: An adaptive machine learning approach on a cell phone.

    PubMed

    Jin, Zhanpeng; Sun, Yuwen; Cheng, Allen C

    2009-01-01

    To date, cardiovascular disease (CVD) is the leading cause of global death. The Electrocardiogram (ECG) is the most widely adopted clinical tool that measures the electrical activities of the heart from the body surface. However, heart rhythm irregularities cannot always be detected on a standard resting ECG machine, since they may not occur during an individual's recording session. Common Holter-based portable solutions that record ECG for up to 24 to 48 hours lack the capability to provide real-time feedback. In this research, we seek to establish a cell phone-based real-time monitoring technology for CVD, capable of performing continuous on-line ECG processing, generating a personalized cardiac health summary report in layman's language, automatically detecting and classifying abnormal CVD conditions, all in real time. Specifically, we developed an adaptive artificial neural network (ANN)-based machine learning technique, combining both an individual's cardiac characteristics and information from clinical ECG databases, to train the cell phone to learn to adapt to its user's physiological conditions to achieve better ECG feature extraction and more accurate CVD classification on cell phones.

  8. Is principal component analysis an effective tool to predict face attractiveness? A contribution based on real 3D faces of highly selected attractive women, scanned with stereophotogrammetry.

    PubMed

    Galantucci, Luigi Maria; Di Gioia, Eliana; Lavecchia, Fulvio; Percoco, Gianluca

    2014-05-01

    In the literature, several papers report studies on mathematical models used to describe facial features and to predict female facial beauty based on 3D human face data. Many authors have proposed the principal component analysis (PCA) method that permits modeling of the entire human face using a limited number of parameters. In some cases, these models have been correlated with beauty classifications, obtaining good attractiveness predictability using wrapped 2D or 3D models. To verify these results, in this paper, the authors conducted a three-dimensional digitization study of 66 very attractive female subjects using a computerized noninvasive tool known as 3D digital photogrammetry. The sample consisted of the 64 contestants of the final phase of the Miss Italy 2010 beauty contest, plus the two highest ranked contestants in the 2009 competition. PCA was conducted on this real faces sample to verify if there is a correlation between ranking and the principal components of the face models. There was no correlation and therefore, this hypothesis is not confirmed for our sample. Considering that the results of the contest are not only solely a function of facial attractiveness, but undoubtedly are significantly impacted by it, the authors based on their experience and real faces conclude that PCA analysis is not a valid prediction tool for attractiveness. The database of the features belonging to the sample analyzed are downloadable online and further contributions are welcome.

  9. Space weather and the safety of ground infrastructures. Numerical simulation and prediction of electromagnetic effects induced by real magnetospheric substorms in the Earth's models with real three-dimensional distribution of electrical conductivity

    NASA Astrophysics Data System (ADS)

    Kuvshinov, Alexey; Filippov, Sergey; Kalegaev, Vladimir; Sidorova, Larisa; Mukhametdinova, Ludmila; Pankratov, Oleg; Alexeev, Dmitry

    Strong eruptions at Sun’s surface produce large release of matter (plasma), which, with a speed of 800-1000 km/s (the solar wind), flows into interplanetary space. If the Earth appears to be on the way of the solar wind the interaction of the wind with the Earth's magnetosphere and the ionosphere leads to abnormal disturbance of fluctuating geomagnetic field. In the middle latitudes, the disturbances (geomagnetic storms) last a few days and have amplitudes up to 400 nT. At high latitudes, these perturbations (magnetospheric substorms) last a few hours and have amplitudes up to 3000 nT. According to Faraday’s law of induction, the fluctuating magnetic field in turn generates a electric field. The electric field for intense substorms can reach hundreds of volts/km in the polar region and generate very high, the so-called geomagnetic induced currents in the ground-based systems, such as power grids and pipelines. These currents are one of the most dangerous factors affecting the operation of the above systems. Thus extremely topical task in the field of "space weather" is the quantification and prediction of spatio-temporal distribution of the electric field during substorm activity. Despite the abundance of works carried out in this direction, the problem is still far from a satisfactory solution. In the field of modeling, researchers are still working with highly simplified models of both the source and the conducting Earth. As for prediction the situation is even worse. In this presentation we discuss a general formalism which allows for simulating the electric fields induced by real magnetospheric substorms in the spherical model of the Earth with real three-dimensional distribution of conductivity. We show the first results of such simulations. We also discuss a concept to predict substorm spatio-temporal pattern of the electric field.

  10. Lysophosphatidic acid receptor-5 negatively regulates cellular responses in mouse fibroblast 3T3 cells

    SciTech Connect

    Dong, Yan; Hirane, Miku; Araki, Mutsumi; Fukushima, Nobuyuki; Tsujiuchi, Toshifumi

    2014-04-04

    Highlights: • LPA{sub 5} inhibits the cell growth and motile activities of 3T3 cells. • LPA{sub 5} suppresses the cell motile activities stimulated by hydrogen peroxide in 3T3 cells. • Enhancement of LPA{sub 5} on the cell motile activities inhibited by LPA{sub 1} in 3T3 cells. • The expression and activation of Mmp-9 were inhibited by LPA{sub 5} in 3T3 cells. • LPA signaling via LPA{sub 5} acts as a negative regulator of cellular responses in 3T3 cells. - Abstract: Lysophosphatidic acid (LPA) signaling via G protein-coupled LPA receptors (LPA{sub 1}–LPA{sub 6}) mediates a variety of biological functions, including cell migration. Recently, we have reported that LPA{sub 1} inhibited the cell motile activities of mouse fibroblast 3T3 cells. In the present study, to evaluate a role of LPA{sub 5} in cellular responses, Lpar5 knockdown (3T3-L5) cells were generated from 3T3 cells. In cell proliferation assays, LPA markedly stimulated the cell proliferation activities of 3T3-L5 cells, compared with control cells. In cell motility assays with Cell Culture Inserts, the cell motile activities of 3T3-L5 cells were significantly higher than those of control cells. The activity levels of matrix metalloproteinases (MMPs) were measured by gelatin zymography. 3T3-L5 cells stimulated the activation of Mmp-2, correlating with the expression levels of Mmp-2 gene. Moreover, to assess the co-effects of LPA{sub 1} and LPA{sub 5} on cell motile activities, Lpar5 knockdown (3T3a1-L5) cells were also established from Lpar1 over-expressing (3T3a1) cells. 3T3a1-L5 cells increased the cell motile activities of 3T3a1 cells, while the cell motile activities of 3T3a1 cells were significantly lower than those of control cells. These results suggest that LPA{sub 5} may act as a negative regulator of cellular responses in mouse fibroblast 3T3 cells, similar to the case for LPA{sub 1}.

  11. Hormone and pharmaceutical regulation of ASP production in 3T3-L1 adipocytes.

    PubMed

    Gao, Ying; Gauvreau, Danny; Cianflone, Katherine

    2010-04-01

    Several studies have demonstrated increases in acylation stimulating protein (ASP), and precursor protein C3 in obesity, diabetes and dyslipidemia, however the nature of the regulation is unknown. To evaluate chronic hormonal and pharmaceutical mediated changes in ASP and potential mechanisms, 3T3-L1 adipocytes were treated with physiological concentrations of relevant hormones and drugs currently used in treatment of metabolic diseases for 48 h. Medium ASP production and C3 secretion were evaluated in relation to changes in adipocyte lipid metabolism (cellular triglyceride (TG) mass, non-esterified fatty acid (NEFA) release and real-time FA uptake). Chylomicrons increased ASP production (up to 411 +/- 133% P < 0.05), while leptin, triiodothyronine, and beta-blockers atenolol and propranolol had no effect. Dexamethasone, lovastatin, rosiglitazone and rimonabant decreased ASP production (-53 to -85%, P < 0.05), associated with a decrease in the precursor protein C3 (-37% to -65%, P < 0.01). By contrast, epinephrine, progesterone, testosterone, angiotensin II and metformin also decreased ASP (-54% to -100%, P < 0.05), but without change in precursor protein C3, suggesting a direct effect on convertase activity, possibly mediated by interference (except metformin) due to marked increases in NEFA (5.6-31-fold, increased P < 0.05). Both lovastatin and metformin induced decreases in ASP were also associated with decreased TG mass (maximal -60%, P < 0.05) and real-time FA uptake (maximum -75%, P < 0.05), suggesting a change in adipocyte differentiation status. These in vitro results are consistent with in vivo ASP profiles in subjects, and suggest that ASP may be regulated through precursor C3 availability, convertase activity and differentiation status.

  12. Does Playing Sports Video Games Predict Increased Involvement in Real-Life Sports Over Several Years Among Older Adolescents and Emerging Adults?

    PubMed

    Adachi, Paul J C; Willoughby, Teena

    2016-02-01

    Given the extreme popularity of video games among older adolescents and emerging adults, the investigation of positive outcomes of video game play during these developmental periods is crucial. An important direction for research in this area is the investigation of a link between sports video game play and involvement in real-life sports among youth. Yet, this association has not been examined in the long-term among older adolescents and emerging adults, and thus represents an exciting new area for discovery. The primary goal of the current study, therefore, was to examine the long-term association between sports video game play and involvement in real-life sports clubs among older adolescents and emerging adults. In addition, we examined whether self-esteem was an underlying mechanism of this longitudinal association. We surveyed older adolescents and emerging adults (N = 1132; 70.6 % female; M age = 19.06 years, range of 17-25 years at the first assessment) annually over 3 years about their video game play, self-esteem, and involvement in real-life sports. We found a long-term predictive effect of sports video game play on increased involvement in real-life sports over the 3 years. Furthermore, we demonstrated that self-esteem was an underlying mechanism of this long-term association. Our findings make an important contribution to an emerging body of literature on the positive outcomes of video game play, as they suggest that sports video game play may be an effective tool to promote real-life sports participation and physical activity among older adolescents and emerging adults.

  13. Elements of a predictive model for determining beach closures on a real time basis: the case of 63rd Street Beach Chicago.

    PubMed

    Olyphant, Greg A; Whitman, Richard L

    2004-11-01

    Data on hydrometeorological conditions and E. coli concentration were simultaneously collected on 57 occasions during the summer of 2000 at 63rd Street Beach, Chicago, Illinois. The data were used to identify and calibrate a statistical regression model aimed at predicting when the bacterial concentration of the beach water was above or below the level considered safe for full body contact. A wide range of hydrological, meteorological, and water quality variables were evaluated as possible predictive variables. These included wind speed and direction, incoming solar radiation (insolation), various time frames of rainfall, air temperature, lake stage and wave height, and water temperature, specific conductance, dissolved oxygen, pH, and turbidity. The best-fit model combined real-time measurements of wind direction and speed (onshore component of resultant wind vector), rainfall, insolation, lake stage, water temperature and turbidity to predict the geometric mean E. coli concentration in the swimming zone of the beach. The model, which contained both additive and multiplicative (interaction) terms, accounted for 71% of the observed variability in the log E. coli concentrations. A comparison between model predictions of when the beach should be closed and when the actual bacterial concentrations were above or below the 235 cfu 100 ml(-1) threshold value, indicated that the model accurately predicted openings versus closures 88% of the time.

  14. Elements of a predictive model for determining beach closures on a real time basis: the case of 63rd Street Beach Chicago

    USGS Publications Warehouse

    Olyphant, Greg A.; Whitman, Richard L.

    2004-01-01

    Data on hydrometeorological conditions and E. coli concentration were simultaneously collected on 57 occasions during the summer of 2000 at 63rd Street Beach, Chicago, Illinois. The data were used to identify and calibrate a statistical regression model aimed at predicting when the bacterial concentration of the beach water was above or below the level considered safe for full body contact. A wide range of hydrological, meteorological, and water quality variables were evaluated as possible predictive variables. These included wind speed and direction, incoming solar radiation (insolation), various time frames of rainfall, air temperature, lake stage and wave height, and water temperature, specific conductance, dissolved oxygen, pH, and turbidity. The best-fit model combined real-time measurements of wind direction and speed (onshore component of resultant wind vector), rainfall, insolation, lake stage, water temperature and turbidity to predict the geometric mean E.coliconcentration in the swimming zone of the beach. The model, which contained both additive and multiplicative (interaction) terms, accounted for 71% of the observed variability in the log E. coliconcentrations. A comparison between model predictions of when the beach should be closed and when the actualbacterial concentrations were above or below the 235 cfu 100 ml-1 threshold value, indicated that the model accurately predicted openingsversus closures 88% of the time.

  15. Performance and Verification of a Real-Time PCR Assay Targeting the gyrA Gene for Prediction of Ciprofloxacin Resistance in Neisseria gonorrhoeae

    PubMed Central

    Hemarajata, P.; Yang, S.; Soge, O. O.; Klausner, J. D.

    2016-01-01

    In the United States, 19.2% of Neisseria gonorrhoeae isolates are resistant to ciprofloxacin. We evaluated a real-time PCR assay to predict ciprofloxacin susceptibility using residual DNA from the Roche Cobas 4800 CT/NG assay. The results of the assay were 100% concordant with agar dilution susceptibility test results for 100 clinical isolates. Among 76 clinical urine and swab specimens positive for N. gonorrhoeae by the Cobas assay, 71% could be genotyped. The test took 1.5 h to perform, allowing the physician to receive results in time to make informed clinical decisions. PMID:26739156

  16. Lysophosphatidic acid receptor-5 negatively regulates cellular responses in mouse fibroblast 3T3 cells.

    PubMed

    Dong, Yan; Hirane, Miku; Araki, Mutsumi; Fukushima, Nobuyuki; Tsujiuchi, Toshifumi

    2014-04-04

    Lysophosphatidic acid (LPA) signaling via G protein-coupled LPA receptors (LPA1-LPA6) mediates a variety of biological functions, including cell migration. Recently, we have reported that LPA1 inhibited the cell motile activities of mouse fibroblast 3T3 cells. In the present study, to evaluate a role of LPA5 in cellular responses, Lpar5 knockdown (3T3-L5) cells were generated from 3T3 cells. In cell proliferation assays, LPA markedly stimulated the cell proliferation activities of 3T3-L5 cells, compared with control cells. In cell motility assays with Cell Culture Inserts, the cell motile activities of 3T3-L5 cells were significantly higher than those of control cells. The activity levels of matrix metalloproteinases (MMPs) were measured by gelatin zymography. 3T3-L5 cells stimulated the activation of Mmp-2, correlating with the expression levels of Mmp-2 gene. Moreover, to assess the co-effects of LPA1 and LPA5 on cell motile activities, Lpar5 knockdown (3T3a1-L5) cells were also established from Lpar1 over-expressing (3T3a1) cells. 3T3a1-L5 cells increased the cell motile activities of 3T3a1 cells, while the cell motile activities of 3T3a1 cells were significantly lower than those of control cells. These results suggest that LPA5 may act as a negative regulator of cellular responses in mouse fibroblast 3T3 cells, similar to the case for LPA1.

  17. The thyroid gland is a major source of circulating T3 in the rat.

    PubMed Central

    Chanoine, J P; Braverman, L E; Farwell, A P; Safran, M; Alex, S; Dubord, S; Leonard, J L

    1993-01-01

    In rats, the respective contribution of the thyroid and peripheral tissues to the pool of T3 remains unclear. Most, if not all, of the circulating T3 produced by extrathyroidal sources is generated by 5'-deiodination of T4, catalyzed by the selenoenzyme, type I iodothyronine 5'-deiodinase (5'D-I). 5'D-I in the liver and kidney is almost completely lost in selenium deficiency, resulting in a marked decrease in T4 deiodination and an increase in circulating T4 levels. Surprisingly, circulating T3 levels are only marginally decreased by selenium deficiency. In this study, we used selenium deficiency and thyroidectomy to determine the relative contribution of thyroidal and extrathyroidal sources to the total body pool of T3. Despite maintaining normal serum T4 concentrations in thyroidectomized rats by T4 replacement, serum T3 concentrations remained 55% lower than those seen in intact rats. In intact rats, restricting selenium intake had no effect on circulating T3 concentrations. Decreasing 5'D-I activity in the liver and kidney by > 90% by restricting selenium intake resulted in a further 20% decrease in serum T3 concentrations in the thyroidectomized, T4 replaced rats, suggesting that peripheral T4 to T3 conversion in these tissues generates approximately 20% of the circulating T3 concentrations. While dietary selenium restriction markedly decreased intrahepatic selenium content (> 95%), intrathyroidal selenium content decreased by only 27%. Further, thyroid 5'D-I activity actually increased 25% in the selenium deficient rats, suggesting the continued synthesis of this selenoenzyme over selenoproteins in other tissues in selenium deficiency. These data demonstrate that the thyroid is the major source of T3 in the rat and suggest that intrathyroidal T4 to T3 conversion may account for most of the T3 released by the thyroid. PMID:8514878

  18. Triiodothyronine (T3) inhibits hyaluronate synthesis in a human dermal equivalent by downregulation of HAS2.

    PubMed

    Pouyani, Tara; Sadaka, Basma H; Papp, Suzanne; Schaffer, Lana

    2013-03-01

    Triiodothyronine (T3) is a thyroid hormone that can have varying effects on skin. In order to assess the effects of T3 on the human dermis, we prepared dermal equivalents using neonatal dermal cells via the process of self-assembly in the presence of differing concentrations of T3. These dermal equivalents were prepared in the absence of serum and a three dimensional matrix allowing for the direct assessment of different concentrations of T3 on dermal extracellular matrix formation. Three different concentrations of T3 were chosen, 20 pM, which is part of the base medium, 0.2 nM T3 and 2 nM T3. We find that self-assembled dermal equivalents formed under these conditions show a progressive "thinning" with increasing T3 concentrations. While we observed no change in total collagen content, inhibition of hyaluronate (HA) synthesis was observed in the 0.2- and 2-nM T3 constructs as compared to the 20-pM construct. Other glycosaminoglycan synthesis was not affected by increasing T3 concentrations. In order to identify the gene(s) responsible for inhibition of HA synthesis in the 2-nM T3 dermal equivalent, we conducted a differential gene array analysis. The results of these experiments demonstrate the differential expression of 40 genes, of these, 34 were upregulated and 6 genes were downregulated. The results from these experiments suggest that downregulation of HAS2 may be responsible for inhibition of hyaluronate synthesis in the self-assembled 2-nM T3 human dermal matrix.

  19. Feasibility of real-time MR thermal dose mapping for predicting radiofrequency ablation outcome in the myocardium in vivo.

    PubMed

    Toupin, Solenn; Bour, Pierre; Lepetit-Coiffé, Matthieu; Ozenne, Valéry; Denis de Senneville, Baudouin; Schneider, Rainer; Vaussy, Alexis; Chaumeil, Arnaud; Cochet, Hubert; Sacher, Frédéric; Jaïs, Pierre; Quesson, Bruno

    2017-01-25

    Clinical treatment of cardiac arrhythmia by radiofrequency ablation (RFA) currently lacks quantitative and precise visualization of lesion formation in the myocardium during the procedure. This study aims at evaluating thermal dose (TD) imaging obtained from real-time magnetic resonance (MR) thermometry on the heart as a relevant indicator of the thermal lesion extent. MR temperature mapping based on the Proton Resonance Frequency Shift (PRFS) method was performed at 1.5 T on the heart, with 4 to 5 slices acquired per heartbeat. Respiratory motion was compensated using navigator-based slice tracking. Residual in-plane motion and related magnetic susceptibility artifacts were corrected online. The standard deviation of temperature was measured on healthy volunteers (N = 5) in both ventricles. On animals, the MR-compatible catheter was positioned and visualized in the left ventricle (LV) using a bSSFP pulse sequence with active catheter tracking. Twelve MR-guided RFA were performed on three sheep in vivo at various locations in left ventricle (LV). The dimensions of the thermal lesions measured on thermal dose images, on 3D T1-weighted (T1-w) images acquired immediately after the ablation and at gross pathology were correlated. MR thermometry uncertainty was 1.5 °C on average over more than 96% of the pixels covering the left and right ventricles, on each volunteer. On animals, catheter repositioning in the LV with active slice tracking was successfully performed and each ablation could be monitored in real-time by MR thermometry and thermal dosimetry. Thermal lesion dimensions on TD maps were found to be highly correlated with those observed on post-ablation T1-w images (R = 0.87) that also correlated (R = 0.89) with measurements at gross pathology. Quantitative TD mapping from real-time rapid CMR thermometry during catheter-based RFA is feasible. It provides a direct assessment of the lesion extent in the myocardium with precision in the range of one

  20. High Performance Programming Using Explicit Shared Memory Model on the Cray T3D

    NASA Technical Reports Server (NTRS)

    Saini, Subhash; Simon, Horst D.; Lasinski, T. A. (Technical Monitor)

    1994-01-01

    The Cray T3D is the first-phase system in Cray Research Inc.'s (CRI) three-phase massively parallel processing program. In this report we describe the architecture of the T3D, as well as the CRAFT (Cray Research Adaptive Fortran) programming model, and contrast it with PVM, which is also supported on the T3D We present some performance data based on the NAS Parallel Benchmarks to illustrate both architectural and software features of the T3D.

  1. Impact of stress hormone on adipogenesis in the 3T3-L1 adipocytes.

    PubMed

    Pandurangan, Muthuraman; Ravikumar, Sambandam

    2014-08-01

    Stress hormone is known to play a vital role in lipolysis and adipogenesis in fat cells. The present study was carried out to evaluate the effect of epinephrine on adipogenesis in the 3T3-L1 cells. The investigation on adipogenesis was done in both mono and co-cultured 3T3-L1 cells. 3T3-L1 preadipocytes and C2C12 cells were grown independently on transwell plates and transferred to differentiation medium. Following differentiation, C2C12 cells transferred to 3T3-L1 plate and treated with medium containing 10 μg/ml of epinephrine. Adipogenic markers such as fatty acid binding protein 4, peroxisome proliferator activating receptor, CCAAT/enhancer-binding protein, adiponectin, lipoprotein lipase and fatty acid synthase mRNA expressions were evaluated in the 3T3-L1 cells. Epinephrine treatment reduced adipogenesis, evidenced by reducing adipogenic marker mRNA expression in the 3T3-L1 cells. In addition, glycerol accumulation and oil red-O staining supported the reduced rate of adipogenesis. Taking all together, it is concluded that the stress hormone, epinephrine reduces the rate of adipogenesis in the mono and co-cultured 3T3-L1 cells. In addition, the rate of adipogenesis is much reduced in the co-cultured 3T3-L1 cells compared monocultured 3T3-L1 cells.

  2. Differentiation of human mature thymocytes: existence of a T3+4-8- intermediate stage.

    PubMed

    De la Hera, A; Toribio, M L; Marquez, C; Marcos, M A; Cabrero, E; Martinez-A, C

    1986-06-01

    A T3 complex-bearing subpopulation was characterized within an in vivo cycling T4-8- early thymocyte compartment which contains cells constitutively expressing interleukin 2 and transferrin receptors. We show differentiation in vitro of both mature subsets of thymocytes (T3+4+8- and T3+4-8+) from the above T4-8- compartment, their appearance being preceded by cells in a T3+4-8- intermediate stage. Furthermore, those mature thymocytes generated in vitro contain functionally competent cells which use T3, T4 and T8 structures for their cytolytic activity. The finding of T3+4-8- thymocytes in vivo, together with the observation that T3 antigen expression precedes that of T4 or T8 molecules in vitro, shows that T3 (and presumably Ti) is present early in ontogeny, and suggests that T3+4-8- cells constitute an "intermediate" stage relevant to the connection between early precursors and mature thymocytes during T lymphocyte ontogeny.

  3. Effects of Maillard reaction on allergenicity of buckwheat allergen Fag t 3 during thermal processing.

    PubMed

    Yang, Zhen-Huang; Li, Chen; Li, Yu-Ying; Wang, Zhuan-Hua

    2013-04-01

    Fag t 3 is a major allergenic protein in tartary buckwheat. The Maillard reaction commonly occurs in food processing, but few studies have been conducted on the influence of thermal processing on the allergenic potential of buckwheat allergen. The aim of the present study was to investigate the effects of autologous plant polysaccharides on the immunoreactivity of buckwheat Fag t 3 (11S globulin) following the Maillard reaction. Fag t 3 and crude polysaccharides were prepared from tartary buckwheat (Fagopyrum tataricum) flour. After heating, the polysaccharides were covalently linked to Fag t 3 via a Maillard reaction, and the IgE/IgG-binding properties of Fag t 3 decreased dramatically, with significant changes also being observed in the electrophoretic mobility, secondary structure and solubility of the glycated Fag t 3. The great influence of glycation on IgE/IgG binding to Fag t 3 was correlated with a significant change in the structure and epitopes of the allergenic protein. These data indicated that conjugation of polysaccharides to Fag t 3 markedly reduced the allergen's immunoreactivity. Glycation that occurs via the Maillard reaction during the processing of buckwheat food may be an efficient method to reduce Fag t 3 allergenicity. © 2012 Society of Chemical Industry.

  4. Maturational changes in T4 to T3 conversion in domestic fowl.

    PubMed

    Klandorf, H; Harvey, S

    1985-01-01

    The in vivo conversion of thyroxine (T4) to triiodothyronine (T3) has been determined in fed and 24 hr-fasted thyroidectomized cockerels at 4, 7, 13 and 23 weeks of age. The conversion of T4 to T3 in pubertal (13-week-old) and adult (22-week-old) cockerels was greater than that in immature (less than 7-week-old) chicks. The deprivation of food for 24 hr markedly reduced the rate of T4 to T3 conversion, especially in immature chicks. These maturational changes in T4 to T3 conversion may be related to differences in metabolic rate.

  5. T3 Regulates a Human Macrophage-Derived TSH-β Splice Variant: Implications for Human Bone Biology.

    PubMed

    Baliram, R; Latif, R; Morshed, S A; Zaidi, M; Davies, T F

    2016-09-01

    TSH and thyroid hormones (T3 and T4) are intimately involved in bone biology. We have previously reported the presence of a murine TSH-β splice variant (TSH-βv) expressed specifically in bone marrow-derived macrophages and that exerted an osteoprotective effect by inducing osteoblastogenesis. To extend this observation and its relevance to human bone biology, we set out to identify and characterize a TSH-β variant in human macrophages. Real-time PCR analyses using human TSH-β-specific primers identified a 364-bp product in macrophages, bone marrow, and peripheral blood mononuclear cells that was sequence verified and was homologous to a human TSH-βv previously reported. We then examined TSH-βv regulation using the THP-1 human monocyte cell line matured into macrophages. After 4 days, 46.1% of the THP-1 cells expressed the macrophage markers CD-14 and macrophage colony-stimulating factor and exhibited typical morphological characteristics of macrophages. Real-time PCR analyses of these cells treated in a dose-dependent manner with T3 showed a 14-fold induction of human TSH-βv mRNA and variant protein. Furthermore, these human TSH-βv-positive cells, induced by T3 exposure, had categorized into both M1 and M2 macrophage phenotypes as evidenced by the expression of macrophage colony-stimulating factor for M1 and CCL-22 for M2. These data indicate that in hyperthyroidism, bone marrow resident macrophages have the potential to exert enhanced osteoprotective effects by oversecreting human TSH-βv, which may exert its local osteoprotective role via osteoblast and osteoclast TSH receptors.

  6. Comparison of predicted and experimental real-gas pressure distributions on space shuttle orbiter nose for shuttle entry air data system

    NASA Technical Reports Server (NTRS)

    Shinn, J. L.

    1980-01-01

    An experimental investigation of inviscid real-gas effects on the pressure distribution along the Space Shuttle Orbiter nose center line up to an angle of attack of 32 deg was performed in support of the Shuttle Entry Air Data System (SEADS). Free-stream velocities from 4.8 to 6.6 kn/s were generated at hypersonic conditions with helium, air, and CO2, resulting in normal-shock density ratios from 3.7 to 18.4. The experimental results for pressure distribution agreed closely with numerical results. Modified Newtonian theory deviates from both experiment and the numerical results as angle of attack increases or shock density ratio decreases. An evaluation of the use of modified Newtonian theory for predicting SEADS pressure distributions in actual flight conditions was made through comparison with numerical predictions.

  7. Ocean Model Analysis and Prediction System (Ocean Maps): Operational Ocean Forecasting Base on Near Real-Time Satellite Altimetry

    NASA Astrophysics Data System (ADS)

    Brassington, G. B.

    2006-07-01

    BLU Elink> is a join t Australian governmen t initiative to develop Austr alia's f irst operational ocean forecasting system called O cean MAPS. The project has transitioned to th e implemen tation and trial phase using the infrastructure of the Bureau of Meteorology. OceanMAPS has a g lobal grid with 1/10° by 1/10° resolution in the Australian region (90E-180E, 70S- 16N) and uses the Modular Ocean Model version 4 optimised for the NEC SX6. The analysis uses an ensemb le based multi-variate optimal interpolation scheme wh ere model error cov ariances ar e der ived from a 72-member ensemble of in tra-seasonal anomalies based on a 12-year ocean only model integration. The scheme has been formulated to assimilate near real- time sea level heigh t anomalies processed from Jason-1, ENVISAT and Geosat Follow-On and profile observations including Argo, X BT and the TAO array. The operation al configuration including the data manag emen t of the near real- time observ ations is review ed.

  8. Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

    ERIC Educational Resources Information Center

    Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

    2011-01-01

    Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also…

  9. Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

    ERIC Educational Resources Information Center

    Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

    2011-01-01

    Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also…

  10. Real-time implementation of model predictive control on Maricopa-Stanfield irrigation and drainage district's WM canal

    USDA-ARS?s Scientific Manuscript database

    Water resources are limited in many agricultural areas. One method to improve the effective use of water is to improve delivery service from irrigation canals. This can be done by applying automatic control methods that control the gates in an irrigation canal. The model predictive control MPC is ...

  11. Dynamic neural networks for real-time water level predictions of sewerage systems - covering gauged and ungauged sites

    NASA Astrophysics Data System (ADS)

    Chiang, Y.-M.; Chang, L.-C.; Tsai, M.-J.; Wang, Y.-F.; Chang, F.-J.

    2010-04-01

    In this research, we propose recurrent neural networks (RNNs) to build a relationship between rainfalls and water level patterns of an urban sewerage system based on historical torrential rain/storm events. The RNN allows a signal to propagate in backward direction which gives this network a dynamic memory to effectively deal with time-varying systems. The RNN is implemented at both gauged and ungauged sites for 5-, 10-, 15-, and 20-min-ahead water level predictions. The results show that the RNN is capable of learning the nonlinear sewerage system and producing satisfactory predictions at the gauged sites. Concerning the ungauged sites, there are no historical data of water level to support prediction. In order to overcome such problem, a set of synthetic data, generated from a storm water management model (SWMM) under cautious verification process of applicability based on the data from nearby gauging stations, are introduced as the learning target to the training procedure of the RNN and moreover evaluating the performance of the RNN at the ungauged sites. The results demonstrate that the potential role of the SWMM coupled with nearby rainfall and water level information can be of great use in enhancing the capability of the RNN at the ungauged sites. Hence we can conclude that the RNN is an effective and suitable model for successfully predicting the water levels at both gauged and ungauged sites in urban sewerage systems.

  12. Accuracy of pregnancy diagnosis and prediction of calving date in red deer using real-time ultrasound scanning.

    PubMed

    Wilson, P R; Bingham, C M

    1990-02-10

    One hundred and sixty-two 18-month-old farmed red deer were used to test the accuracy of pregnancy detection and equations for predicting gestational age. Deer ranging from 30 to 110 days gestation were examined by rectal ultrasonography using a 5 MHz transducer while they were standing. Each scan was recorded on video tape for measurements of uterine diameter, amniotic sac diameters, crown-rump length, head length, head diameter, nose length, chest depth, chest width and placentome base-apex length and width. Fetal age was calculated from the mean of the age predictions derived from each dimension measured on individual deer, for 132 deer between 44 and 110 days gestation. All the hinds diagnosed as pregnant produced offspring, and all the hinds diagnosed as not pregnant failed to produce offspring. Between one and six fetal and uterine dimensions were measurable and the number measurable increased with fetal age. The mean error of calving date prediction in 132 deer was 0.97 days. The error of prediction when measurements were made between 44 and 60 days was 0.44 days, whereas between 61 and 80 days and between 81 and 110 days the errors were +0.95 and +4.72 days, respectively. The estimates of calving date were all within 13 days of the calving date.

  13. Elements of a pragmatic approach for dealing with bias and uncertainty in experiments through predictions : experiment design and data conditioning; %22real space%22 model validation and conditioning; hierarchical modeling and extrapolative prediction.

    SciTech Connect

    Romero, Vicente Jose

    2011-11-01

    This report explores some important considerations in devising a practical and consistent framework and methodology for utilizing experiments and experimental data to support modeling and prediction. A pragmatic and versatile 'Real Space' approach is outlined for confronting experimental and modeling bias and uncertainty to mitigate risk in modeling and prediction. The elements of experiment design and data analysis, data conditioning, model conditioning, model validation, hierarchical modeling, and extrapolative prediction under uncertainty are examined. An appreciation can be gained for the constraints and difficulties at play in devising a viable end-to-end methodology. Rationale is given for the various choices underlying the Real Space end-to-end approach. The approach adopts and refines some elements and constructs from the literature and adds pivotal new elements and constructs. Crucially, the approach reflects a pragmatism and versatility derived from working many industrial-scale problems involving complex physics and constitutive models, steady-state and time-varying nonlinear behavior and boundary conditions, and various types of uncertainty in experiments and models. The framework benefits from a broad exposure to integrated experimental and modeling activities in the areas of heat transfer, solid and structural mechanics, irradiated electronics, and combustion in fluids and solids.

  14. Evaluation of stream mining classifiers for real-time clinical decision support system: a case study of blood glucose prediction in diabetes therapy.

    PubMed

    Fong, Simon; Zhang, Yang; Fiaidhi, Jinan; Mohammed, Osama; Mohammed, Sabah

    2013-01-01

    Earlier on, a conceptual design on the real-time clinical decision support system (rt-CDSS) with data stream mining was proposed and published. The new system is introduced that can analyze medical data streams and can make real-time prediction. This system is based on a stream mining algorithm called VFDT. The VFDT is extended with the capability of using pointers to allow the decision tree to remember the mapping relationship between leaf nodes and the history records. In this paper, which is a sequel to the rt-CDSS design, several popular machine learning algorithms are investigated for their suitability to be a candidate in the implementation of classifier at the rt-CDSS. A classifier essentially needs to accurately map the events inputted to the system into one of the several predefined classes of assessments, such that the rt-CDSS can follow up with the prescribed remedies being recommended to the clinicians. For a real-time system like rt-CDSS, the major technological challenges lie in the capability of the classifier to process, analyze and classify the dynamic input data, quickly and upmost reliably. An experimental comparison is conducted. This paper contributes to the insight of choosing and embedding a stream mining classifier into rt-CDSS with a case study of diabetes therapy.

  15. Effect of microsomal enzyme inducers on the biliary excretion of triiodothyronine (T(3)) and its metabolites.

    PubMed

    Vansell, Nichole R; Klaassen, Curtis D

    2002-02-01

    It has been postulated that inducers of UDP-glucuronosyltransferase (UGT) decrease circulating thyroid hormone concentrations by increasing their biliary excretion. The inducers pregnenolone-16 alpha-carbonitrile (PCN), 3-methylcholanthrene (3MC), and Aroclor 1254 (PCB) are each effective at reducing serum thyroxine concentrations. However, only PCN treatment produces a marked increase in serum levels of thyroid-stimulating hormone (TSH), whereas 3MC and PCB cause little to no increase in TSH. Excessive TSH elevation is considered the primary stimulus for thyroid tumor development in rats, yet the mechanism by which enzyme induction leads to TSH elevation is not fully understood. Whereas PCN, 3MC, and PCB all increase microsomal UGT activity toward T(4), only PCN causes an increase in T(3)-UGT activity in vitro. The purpose of this study was to determine whether PCN, which increases serum TSH, causes an increase in the glucuronidation and biliary excretion of T(3) in vivo. Male rats were fed control diet or diet containing PCN (1000 ppm), 3MC (250 ppm), or PCB (100 ppm) for 7 days. Animals were then given [(125)I]-T(3), i.v., and bile was collected for 2 h. Radiolabeled metabolites in bile were analyzed by reverse-phase HPLC with gamma-detection. The biliary excretion of total radioactivity was increased up to 75% by PCN, but not by 3MC or PCB. Of the T(3) excreted into bile, approximately 75% was recovered as T(3)-glucuronide, with remaining amounts represented as T(3)-sulfate, T(2)-sulfate, T(3), and T(2). Biliary excretion of T(3)-glucuronide was increased up to 66% by PCN, while neither 3MC nor PCB altered T(3)-glucuronide excretion. These findings indicate that PCN increases the glucuronidation and biliary excretion of T(3) in vivo, and suggest that enhanced elimination of T(3) may be the mechanism responsible for the increases in serum TSH caused by PCN.

  16. Characterizing the Severe Turbulence Environments Associated With Commercial Aviation Accidents: A Real-Time Turbulence Model (RTTM) Designed for the Operational Prediction of Hazardous Aviation Turbulence Environments

    NASA Technical Reports Server (NTRS)

    Kaplan, Michael L.; Lux, Kevin M.; Cetola, Jeffrey D.; Huffman, Allan W.; Riordan, Allen J.; Slusser, Sarah W.; Lin, Yuh-Lang; Charney, Joseph J.; Waight, Kenneth T.

    2004-01-01

    Real-time prediction of environments predisposed to producing moderate-severe aviation turbulence is studied. We describe the numerical model and its postprocessing system designed for said prediction of environments predisposed to severe aviation turbulence as well as presenting numerous examples of its utility. The numerical model is MASS version 5.13, which is integrated over three different grid matrices in real time on a university work station in support of NASA Langley Research Center s B-757 turbulence research flight missions. The postprocessing system includes several turbulence-related products, including four turbulence forecasting indices, winds, streamlines, turbulence kinetic energy, and Richardson numbers. Additionally, there are convective products including precipitation, cloud height, cloud mass fluxes, lifted index, and K-index. Furthermore, soundings, sounding parameters, and Froude number plots are also provided. The horizontal cross-section plot products are provided from 16 000 to 46 000 ft in 2000-ft intervals. Products are available every 3 hours at the 60- and 30-km grid interval and every 1.5 hours at the 15-km grid interval. The model is initialized from the NWS ETA analyses and integrated two times a day.

  17. Researches on the Nankai trough mega thrust earthquake seismogenic zones using real time observing systems for advanced early warning systems and predictions

    NASA Astrophysics Data System (ADS)

    Kaneda, Yoshiyuki

    2015-04-01

    We recognized the importance of real time monitoring on Earthquakes and Tsunamis Based on lessons learned from 2004 Sumatra Earthquake/Tsunamis and 2011 East Japan Earthquake. We deployed DONET1 and are developing DONET2 as real time monitoring systems which are dense ocean floor networks around the Nankai trough seismogenic zone Southwestern Japan. Total observatories of DONE1 and DONET2 are 51 observatories equipped with multi kinds of sensors such as the accelerometer, broadband seismometer, pressure gauge, difference pressure gauge, hydrophone and thermometer in each observatory. These systems are indispensable for not only early warning of Earthquakes/ Tsunamis, but also researches on broadband crustal activities around the Nankai trough seismogenic zone for predictions. DONET1 detected offshore tsunamis 15 minutes earlier than onshore stations at the 2011 East Japan earthquake/tsunami. Furthermore, DONET1/DONET2 will be expected to monitor slow events such as low frequency tremors and slow earthquakes for the prediction researches. Finally, the integration of observations and simulation researches will contribute to estimate of seismic stage changes from the inter-seismic to pre seismic stage. I will introduce applications of DONET1/DONET2 data and advanced simulation researches.

  18. A Perceptual Pathway to Bias: Interracial Exposure Reduces Abrupt Shifts in Real-Time Race Perception That Predict Mixed-Race Bias.

    PubMed

    Freeman, Jonathan B; Pauker, Kristin; Sanchez, Diana T

    2016-04-01

    In two national samples, we examined the influence of interracial exposure in one's local environment on the dynamic process underlying race perception and its evaluative consequences. Using a mouse-tracking paradigm, we found in Study 1 that White individuals with low interracial exposure exhibited a unique effect of abrupt, unstable White-Black category shifting during real-time perception of mixed-race faces, consistent with predictions from a neural-dynamic model of social categorization and computational simulations. In Study 2, this shifting effect was replicated and shown to predict a trust bias against mixed-race individuals and to mediate the effect of low interracial exposure on that trust bias. Taken together, the findings demonstrate that interracial exposure shapes the dynamics through which racial categories activate and resolve during real-time perceptions, and these initial perceptual dynamics, in turn, may help drive evaluative biases against mixed-race individuals. Thus, lower-level perceptual aspects of encounters with racial ambiguity may serve as a foundation for mixed-race prejudice. © The Author(s) 2016.

  19. Prediction of carcase and breast weights and yields in broiler chickens using breast volume determined in vivo by real-time