Application of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison with MM5/CMAQ

Science.gov (United States)

Zhang, Yang; Zhang, Xin; Wang, Litao; Zhang, Qiang; Duan, Fengkui; He, Kebin

2016-01-01

.g., secondary organic aerosol formation, gas/particle partitioning, dust emissions, dry and wet deposition), and inaccurate meteorological fields (e.g., overpredictions in WS10 and precipitation, but underpredictions in T2), as well as the large uncertainties in satellite retrievals (e.g., for column SO2). Comparing to MM5, WRF generally gives worse performance in meteorological predictions, in particular, T2, WS10, GSW, GLW, and cloud fraction in all months, as well as Q2 and precipitation in January and October, due to limitations in the above physics schemes or parameterizations. Comparing to CMAQ, WRF/Chem performs better for surface CO, O3, and PM10 concentrations at most sites in most months, column CO and SO2 abundances, and AOD. It, however, gives poorer performance for surface NOx concentrations at most sites in most months, surface SO2 concentrations at all sites in all months, and column NO2 abundances in January and April. WRF/Chem also gives lower concentrations of most secondary PM and black carbon. Those differences in results are attributed to differences in simulated meteorology, gas-phase chemistry, aerosol thermodynamic and dynamic treatments, dust and sea salt emissions, and wet and dry deposition treatments in both models.

Surface Energy Balance in Jakarta and Neighboring Regions As Simulated Using Fifth Mesoscale Model (MM5

Directory of Open Access Journals (Sweden)

Yopi Ilhamsyah

2014-04-01

Full Text Available The objective of the present research was to assess the surface energy balance particularly in terms of the computed surface energy and radiation balance and the development of boundary layer over Jakarta and Neighboring Regions (JNR by means of numerical model of fifth generation of Mesoscale Model (MM5. The MM5 with four domains of 9 kilometers in spatial resolution presenting the outermost and the innermost of JNR is utilized. The research focuses on the third and fourth domains covering the entire JNR. The description between radiation and energy balance at the surface is obtained from the model. The result showed that energy balance is higher in the city area during daytime. Meanwhile, energy components, e.g., surface sensible and latent heat flux showed that at the sea and in the city areas were higher than other areas. Moreover, ground flux showed eastern region was higher than others. In general, radiation and energy balance was higher in the daytime and lower in the nighttime for all regions. The calculation of Bowen Ratio, the ratio of surface sensible and latent heat fluxes, was also higher in the city area, reflecting the dominations of urban and built-up land in the region. Meanwhile, Bowen Ratio in the rural area dominated by irrigated cropland was lower. It is consistent with changes of land cover properties, e.g. albedo, soil moisture, and thermal characteristics. In addition, the boundary layer is also higher in the city. Meanwhile western region dominated by suburban showed higher boundary layer instead of eastern region.

New method for model coupling using Stampi. Application to the coupling of atmosphere model (MM5) and land-surface model (SOLVEG)

International Nuclear Information System (INIS)

Nagai, Haruyasu

2003-12-01

A new method to couple atmosphere and land-surface models using the message passing interface (MPI) was proposed to develop an atmosphere-land model for studies on heat, water, and material exchanges around the land surface. A non-hydrostatic atmospheric dynamic model of Pennsylvania State University and National Center for Atmospheric Research (PUS/NCAR-MM5) and a detailed land surface model (SOLVEG) including the surface-layer atmosphere, soil, and vegetation developed at Japan Atomic Energy Research Institute (JAERI) are used as the atmosphere and land-surface models, respectively. Concerning the MPI, a message passing library named Stampi developed at JAERI that can be used between different parallel computers is used. The models are coupled by exchanging calculation results by using MPI on their independent parallel calculations. The modifications for this model coupling are easy, simply adding some modules for data exchanges to each model code without changing each model's original structure. Moreover, this coupling method is flexible and allows the use of independent time step and grid interval for each model. (author)

Mathematical model of mechanical testing of bone-implant (4.5 mm LCP construct

Directory of Open Access Journals (Sweden)

Lucie Urbanová

2012-01-01

Full Text Available The study deals with the possibility of substituting time- and material-demanding mechanical testing of a bone defect fixation by mathematical modelling. Based on the mechanical model, a mathematical model of bone-implant construct stabilizing experimental segmental femoral bone defect (segmental ostectomy in a miniature pig ex vivo model using 4.5 mm titanium LCP was created. It was subsequently computer-loaded by forces acting parallel to the long axis of the construct. By the effect of the acting forces the displacement vector sum of individual construct points occurred. The greatest displacement was noted in the end segments of the bone in close proximity to ostectomy and in the area of the empty central plate hole (without screw at the level of the segmental bone defect. By studying the equivalent von Mises stress σEQV on LCP as part of the tested construct we found that the greatest changes of stress occur in the place of the empty central plate hole. The distribution of this strain was relatively symmetrical along both sides of the hole. The exceeding of the yield stress value and irreversible plastic deformations in this segment of LCP occurred at the acting of the force of 360 N. These findings are in line with the character of damage of the same construct loaded during its mechanic testing. We succeeded in creating a mathematical model of the bone-implant construct which may be further used for computer modelling of real loading of similar constructs chosen for fixation of bone defects in both experimental and clinical practice.

Narrow- (3.0 mm) Versus Standard-Diameter (4.0 and 4.5 mm) Implants for Splinted Partial Fixed Restoration of Posterior Mandibular and Maxillary Jaws: A 5-Year Retrospective Cohort Study.

Science.gov (United States)

Pieri, Francesco; Forlivesi, Caterina; Caselli, Ernesto; Corinaldesi, Giuseppe

2017-04-01

Evidence concerning predictability of narrow-diameter implants (NDIs) (3.0 mm) and standard-diameter implants (SDIs) (4.0 to 4.5 mm) supporting fixed partial dentures (FPDs) in posterior mandibular and maxillary jaws. All patients treated with at least two adjacent NDIs or SDIs according to available bone thickness and with a minimum follow-up of 5 years after placement were invited to undergo a clinical and radiologic examination. Outcome measures were implant and FPD failures, biologic and prosthetic complications, and marginal bone loss. A total of 107 out of 127 patients attended the examination: 49 (113 implants) of the NDI group, and 58 (126 implants) of the SDI group. Two NDIs failed in one patient versus four SDIs in four patients (P = 0.37). One FPD failed in the NDI group versus two FPDs in the SDI group (P >0.99). Nine biologic complications occurred in the NDI group and twelve in the SDI group (P = 0.81). Twelve prosthetic complications occurred in the NDI group and only two in the SDI group (P = 0.001). Peri-implant marginal bone loss at 5 years was 0.95 ± 0.84 mm for the NDI group and 1.2 ± 0.86 mm for the SDI group (P = 0.06). Five-year data indicate that FPD treatment in posterior mandibular and maxillary jaws with NDIs was as reliable as with SDIs, although NDIs showed a higher risk of prosthetic complications.

TU-F-17A-03: An Analytical Respiratory Perturbation Model for Lung Motion Prediction

International Nuclear Information System (INIS)

Li, G; Yuan, A; Wei, J

2014-01-01

Purpose: Breathing irregularity is common, causing unreliable prediction in tumor motion for correlation-based surrogates. Both tidal volume (TV) and breathing pattern (BP=ΔVthorax/TV, where TV=ΔVthorax+ΔVabdomen) affect lung motion in anterior-posterior and superior-inferior directions. We developed a novel respiratory motion perturbation (RMP) model in analytical form to account for changes in TV and BP in motion prediction from simulation to treatment. Methods: The RMP model is an analytical function of patient-specific anatomic and physiologic parameters. It contains a base-motion trajectory d(x,y,z) derived from a 4-dimensional computed tomography (4DCT) at simulation and a perturbation term Δd(ΔTV,ΔBP) accounting for deviation at treatment from simulation. The perturbation is dependent on tumor-specific location and patient-specific anatomy. Eleven patients with simulation and treatment 4DCT images were used to assess the RMP method in motion prediction from 4DCT1 to 4DCT2, and vice versa. For each patient, ten motion trajectories of corresponding points in the lower lobes were measured in both 4DCTs: one served as the base-motion trajectory and the other as the ground truth for comparison. In total, 220 motion trajectory predictions were assessed. The motion discrepancy between two 4DCTs for each patient served as a control. An established 5D motion model was used for comparison. Results: The average absolute error of RMP model prediction in superior-inferior direction is 1.6±1.8 mm, similar to 1.7±1.6 mm from the 5D model (p=0.98). Some uncertainty is associated with limited spatial resolution (2.5mm slice thickness) and temporal resolution (10-phases). Non-corrected motion discrepancy between two 4DCTs is 2.6±2.7mm, with the maximum of ±20mm, and correction is necessary (p=0.01). Conclusion: The analytical motion model predicts lung motion with accuracy similar to the 5D model. The analytical model is based on physical relationships, requires no

MM5 simulations for air quality modeling: An application to a coastal area with complex terrain

Science.gov (United States)

Lee, Sang-Mi; Princevac, Marko; Mitsutomi, Satoru; Cassmassi, Joe

A series of modifications were implemented in MM5 simulation in order to account for wind along the Santa Clarita valley, a north-south running valley located in the north of Los Angeles. Due to high range mountains in the north and the east of the Los Angeles Air Basin, sea breeze entering Los Angeles exits into two directions. One branch moves toward the eastern part of the basin and the other to the north toward the Santa Clarita valley. However, the northward flow has not been examined thoroughly nor simulated successfully in the previous studies. In the present study, we proposed four modifications to trigger the flow separation. They were (1) increasing drag over the ocean, (2) increasing soil moisture content, (3) selective observational nudging, and (4) one-way nesting for the innermost domain. The Control run overpredicted near-surface wind speed over the ocean and sensible heat flux, in an urbanized area, which justifies the above 1st and 2nd modification. The Modified run provided an improvement in near-surface temperature, sensible heat flux and wind fields including southeasterly flow along the Santa Clarita valley. The improved MM5 wind field triggered a transport to the Santa Clarita valley generating a plume elongated from an urban center to the north, which did not exist in MM5 Control run. In all, the modified MM5 fields yielded better agreement in both CO and O3 simulations especially in the Santa Clarita area.

Use of 5-mm Laparoscopic Stapler to Perform Open Small Bowel Anastomosis in a Neonatal Animal Model.

Science.gov (United States)

Glenn, Ian C; Bruns, Nicholas E; Ponsky, Todd A

2016-10-01

While adult bowel anastomoses are typically performed with staplers, neonatal small bowel anastomoses have traditionally been performed in a hand-sewn manner due to the large size of surgical staplers. The purpose of this study was to compare stapled anastomosis using a newly available, 5-mm laparoscopic stapler to a hand-sewn anastomosis in an open animal model. Twenty anastomoses were performed by two general surgery residents (10 stapled and 10 hand-sewn) in an adult New Zealand white rabbit. The small bowel was divided with a scalpel. Surgical technique was alternated between single-layer hand-sewn and stapled anastomoses. Each anastomosis was resected for ex vivo testing. Measurements collected were outer diameter of the bowel before division, time to perform the anastomosis, anastomosis inner diameter (ID), and leak test. IDs were measured by cutting the anastomosis in cross-section, taking a photograph, and measuring the diameter by computer software. In addition, the surgeons qualitatively evaluated the anastomoses for hemostasis and overall quality. Statistical significance was determined using the Student's t-test. There were statistically significant differences between stapled and hand-sewn anastomosis, respectively, for average operative time (4 minutes 2 seconds versus 16 minutes 6 seconds, P animal model, a 5-mm stapled anastomosis is an acceptable alternative to hand-sewn small bowel anastomosis. The stapler is faster and creates a larger diameter anastomosis, however, there was one leak when closing the enterotomy in the stapled group and overlapping staple lines should be avoided.

Machine-Learning-Based Future Received Signal Strength Prediction Using Depth Images for mmWave Communications

OpenAIRE

Okamoto, Hironao; Nishio, Takayuki; Nakashima, Kota; Koda, Yusuke; Yamamoto, Koji; Morikura, Masahiro; Asai, Yusuke; Miyatake, Ryo

2018-01-01

This paper discusses a machine-learning (ML)-based future received signal strength (RSS) prediction scheme using depth camera images for millimeter-wave (mmWave) networks. The scheme provides the future RSS prediction of any mmWave links within the camera's view, including links where nodes are not transmitting frames. This enables network controllers to conduct network operations before line-of-sight path blockages degrade the RSS. Using the ML techniques, the prediction scheme automatically...

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

International Nuclear Information System (INIS)

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

2008-01-01

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

Toward an individualized target motion management for IMRT of cervical cancer based on model-predicted cervix-uterus shape and position

International Nuclear Information System (INIS)

Bondar, Luiza; Hoogeman, Mischa; Mens, Jan Willem; Dhawtal, Glenn; Pree, Ilse de; Ahmad, Rozilawati; Quint, Sandra; Heijmen, Ben

2011-01-01

Background and Purpose: To design and evaluate a 3D patient-specific model to predict the cervix-uterus shape and position. Methods and Materials: For 13 patients lying in prone position, 10 variable bladder filling CT-scans were acquired, 5 at planning and 5 after 40 Gy. The delineated cervix-uterus volumes in 2-5 pre-treatment CT-scans were used to generate patient-specific models that predict the cervix-uterus geometry by bladder volume. Model predictions were compared to delineations, excluding those used for model construction. The prediction error was quantified by the margin required around the predicted volumes to accommodate 95% of the delineated volume and by the predicted-to-delineated surface distance. Results: The prediction margin was significantly smaller (average 50%) than the margin encompassing the cervix-uterus motion. The prediction margin could be decreased (from 7 to 5 mm at planning and from 10 to 8 mm after 40 Gy) by increasing (from 2 to 5) the number of CT-scans used for the model construction. Conclusion: For most patients, even with a model based on only two CT-scans, the prediction error was well below the margin encompassing the cervix-uterus motion. The described approach could be used to create prior to treatment, an individualized treatment strategy.

Evaluation of cloud prediction and determination of critical relative humidity for a mesoscale numerical weather prediction model

Energy Technology Data Exchange (ETDEWEB)

Seaman, N.L.; Guo, Z.; Ackerman, T.P. [Pennsylvania State Univ., University Park, PA (United States)

1996-04-01

Predictions of cloud occurrence and vertical location from the Pennsylvannia State University/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) were evaluated statistically using cloud observations obtained at Coffeyville, Kansas, as part of the Second International satellite Cloud Climatology Project Regional Experiment campaign. Seventeen cases were selected for simulation during a November-December 1991 field study. MM5 was used to produce two sets of 36-km simulations, one with and one without four-dimensional data assimilation (FDDA), and a set of 12-km simulations without FDDA, but nested within the 36-km FDDA runs.

A predictive model for dimensional errors in fused deposition modeling

DEFF Research Database (Denmark)

Stolfi, A.

2015-01-01

This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...... values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

Piezoelectric ultrasonic micromotor with 1.5 mm diameter.

Science.gov (United States)

Dong, Shuxiang; Lim, Siak P; Lee, Kwork H; Zhang, Jingdong; Lim, Leong C; Uchino, Kenji

2003-04-01

A piezoelectric ultrasonic micromotor has been developed using a lead zirconate titanate (PZT) ceramic/metal composite tube stator that was 1.5 mm in diameter and 7 mm in length. The micromotor was operated in its first bending vibration mode (approximately 70 kHz), producing speeds from hundreds to over 2000 rpm in both rotational directions. The maximum torque-output was 45 microN-m, which is far superior to previous PZT thin film-based micromotors. This micromotor showed good reliability and stability for more than 300 hours of continued operation.

Electrode characteristics of the (Mm)Ni 5-based hydrogen storage alloys

Energy Technology Data Exchange (ETDEWEB)

Han, Dong Soo; Choi, Seung Jun; Chang, Min Ho; Choi, Jeon; Park, Choong Nyun [Chonnam National University, Kwangju (Korea, Republic of)

1995-06-01

The MmNi-based alloy electrode was studied for use a negative electrode in Ni-MH battery. Alloys with MmNi{sub 5}-{sub x} M{sub x}(M=Co,Al,Mn) composition were synthesized, and their electrode characteristics of activation rate, temperature dependence, electrode capacity and cycle life were investigated. With increasing Al content and decreasing Mn content in the alloys, the discharge capacity increased while the cycle life decreased. As x in MmNi{sub 5}-{sub x} M{sub x} increased from 1.5 to 2.0, decreasing the Ni content, the discharge capacity, the low temperature property and the rate capability decreased. However its cycle life was improved. Increasing Co content resulted in a prolonged cycle life and decrease of high rate discharge capacity. It can be concluded that the most promising alloy in view of discharge capacity and cycle life is MmNi{sub 3}.5 Co{sub 0}.7 Al{sub 0}.5 Mn{sub 0}.3. (author). 9 refs., 9 figs., 1 tab.

Autoregressive spatially varying coefficients model for predicting daily PM2.5 using VIIRS satellite AOT

Science.gov (United States)

Schliep, E. M.; Gelfand, A. E.; Holland, D. M.

2015-12-01

There is considerable demand for accurate air quality information in human health analyses. The sparsity of ground monitoring stations across the United States motivates the need for advanced statistical models to predict air quality metrics, such as PM2.5, at unobserved sites. Remote sensing technologies have the potential to expand our knowledge of PM2.5 spatial patterns beyond what we can predict from current PM2.5 monitoring networks. Data from satellites have an additional advantage in not requiring extensive emission inventories necessary for most atmospheric models that have been used in earlier data fusion models for air pollution. Statistical models combining monitoring station data with satellite-obtained aerosol optical thickness (AOT), also referred to as aerosol optical depth (AOD), have been proposed in the literature with varying levels of success in predicting PM2.5. The benefit of using AOT is that satellites provide complete gridded spatial coverage. However, the challenges involved with using it in fusion models are (1) the correlation between the two data sources varies both in time and in space, (2) the data sources are temporally and spatially misaligned, and (3) there is extensive missingness in the monitoring data and also in the satellite data due to cloud cover. We propose a hierarchical autoregressive spatially varying coefficients model to jointly model the two data sources, which addresses the foregoing challenges. Additionally, we offer formal model comparison for competing models in terms of model fit and out of sample prediction of PM2.5. The models are applied to daily observations of PM2.5 and AOT in the summer months of 2013 across the conterminous United States. Most notably, during this time period, we find small in-sample improvement incorporating AOT into our autoregressive model but little out-of-sample predictive improvement.

Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

NARCIS (Netherlands)

Petersen, Japke F.; Stuiver, Martijn M.; Timmermans, Adriana J.; Chen, Amy; Zhang, Hongzhen; O'Neill, James P.; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T.; Koch, Wayne; van den Brekel, Michiel W. M.

2017-01-01

TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442

Statistical Modelling and Characterization of Experimental mm-Wave Indoor Channels for Future 5G Wireless Communication Networks.

Science.gov (United States)

Al-Samman, A M; Rahman, T A; Azmi, M H; Hindia, M N; Khan, I; Hanafi, E

This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios.

Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5

Science.gov (United States)

Ausati, Shadi; Amanollahi, Jamil

2016-10-01

Since Sanandaj is considered one of polluted cities of Iran, prediction of any type of pollution especially prediction of suspended particles of PM2.5, which are the cause of many diseases, could contribute to health of society by timely announcements and prior to increase of PM2.5. In order to predict PM2.5 concentration in the Sanandaj air the hybrid models consisting of an ensemble empirical mode decomposition and general regression neural network (EEMD-GRNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), principal component regression (PCR), and linear model such as multiple liner regression (MLR) model were used. In these models the data of suspended particles of PM2.5 were the dependent variable and the data related to air quality including PM2.5, PM10, SO2, NO2, CO, O3 and meteorological data including average minimum temperature (Min T), average maximum temperature (Max T), average atmospheric pressure (AP), daily total precipitation (TP), daily relative humidity level of the air (RH) and daily wind speed (WS) for the year 2014 in Sanandaj were the independent variables. Among the used models, EEMD-GRNN model with values of R2 = 0.90, root mean square error (RMSE) = 4.9218 and mean absolute error (MAE) = 3.4644 in the training phase and with values of R2 = 0.79, RMSE = 5.0324 and MAE = 3.2565 in the testing phase, exhibited the best function in predicting this phenomenon. It can be concluded that hybrid models have accurate results to predict PM2.5 concentration compared with linear model.

Mathematical Model for Prediction of Flexural Strength of Mound ...

African Journals Online (AJOL)

The mound soil-cement blended proportions were mathematically optimized by using scheffe's approach and the optimization model developed. A computer program predicting the mix proportion for the model was written. The optimal proportion by the program was used prepare beam samples measuring 150mm x 150mm ...

40 mm bore Nb-Ti model dipole magnet

International Nuclear Information System (INIS)

Taylor, C.; Gilbert, W.; Hassenzahl, W.; Meuser, R.; Peters, C.; Rechen, J.; Scanlan, R.

1984-01-01

Preliminary R and D has been started on magnets for a next-generation high-energy-physics accelerator, the 20 TeV Superconducting Supercollider (SSC). One design now being developed at LBL is described in this paper. The design is based on two layers of flattened Nb-Ti cable, a 40 mm ID winding with flared ends, and an operating field of 6.5 T. Experimental results are presented on several one-meter-long models tested at both He I and He II temperature. Measurement of field, residual magnetization, quench propagation velocity, and winding prestress are presented. (A 2-in-1 magnet based on this coil design is being jointly developed by LBL and Brookhaven National Laboratory, and 15 ft. long models are being constructed at BNL)

AGR-5/6/7 Irradiation Test Predictions using PARFUME

Energy Technology Data Exchange (ETDEWEB)

Skerjanc, William F. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2017-09-14

PARFUME, (PARticle FUel ModEl) a fuel performance modeling code used for high temperature gas-cooled reactors (HTGRs), was used to model the Advanced Gas Reactor (AGR)-5/6/7 irradiation test using predicted physics and thermal hydraulics data. The AGR-5/6/7 test consists of the combined fifth, sixth, and seventh planned irradiations of the AGR Fuel Development and Qualification Program. The AGR-5/6/7 test train is a multi-capsule, instrumented experiment that is designed for irradiation in the 133.4-mm diameter north east flux trap (NEFT) position of Advanced Test Reactor (ATR). Each capsule contains compacts filled with uranium oxycarbide (UCO) unaltered fuel particles. This report documents the calculations performed to predict the failure probability of tristructural isotropic (TRISO)-coated fuel particles during the AGR-5/6/7 experiment. In addition, this report documents the calculated source term from the driver fuel. The calculations include modeling of the AGR-5/6/7 irradiation that is scheduled to occur from October 2017 to April 2021 over a total of 13 ATR cycles, including nine normal cycles and four Power Axial Locator Mechanism (PALM) cycle for a total between 500 – 550 effective full power days (EFPD). The irradiation conditions and material properties of the AGR-5/6/7 test predicted zero fuel particle failures in Capsules 1, 2, and 4. Fuel particle failures were predicted in Capsule 3 due to internal particle pressure. These failures were predicted in the highest temperature compacts. Capsule 5 fuel particle failures were due to inner pyrolytic carbon (IPyC) cracking causing localized stresses concentrations in the SiC layer. This capsule predicted the highest particle failures due to the lower irradiation temperature. In addition, shrinkage of the buffer and IPyC layer during irradiation resulted in formation of a buffer-IPyC gap. The two capsules at the two ends of the test train, Capsules 1 and 5 experienced the smallest buffer-IPyC gap

Normal mediastinal and hilar lymph nodes evaluated by 5 mm slice bolus injection CT scan

International Nuclear Information System (INIS)

Yamamoto, Takako; Tsukada, Hiroshi; Koizumi, Naoya; Akita, Shinichi; Oda, Junichi; Sakai, Kunio

1995-01-01

We evaluated the number and size of normal mediastinal and hilar lymph nodes by 5 mm slice bolus injection CT (12 patients), compared with 10 mm slice CT (12 patients). More lymph nodes were clearly demonstrated by 5 mm slice CT than by 10 mm slice CT. Especially left-sided tracheobronchial (no.4), subaortic (no.5), subcarinal (no.7) and hilar lymph nodes were clearly visible. We concluded 5 mm slice bolus injection CT was useful to evaluate mediastinal and hilar lymph nodes. (author)

Massive MIMO 5G Cellular Networks:mm-Wave vs.μ-Wave Frequencies

Institute of Scientific and Technical Information of China (English)

Stefano Buzzi; Carmen D'Andrea

2017-01-01

Enhanced mobile broadband (eMBB) is one of the key use-cases for the development of the new standard 5G New Radio for the next generation of mobile wireless networks. Large-scale antenna arrays, a.k.a. massive multiple-input multiple-output (MIMO), the usage of carrier frequencies in the range 10-100 GHz, the so-called millimeter wave (mm-Wave) band, and the network densifica-tion with the introduction of small-sized cells are the three technologies that will permit implementing eMBB services and realiz-ing the Gbit/s mobile wireless experience. This paper is focused on the massive MIMO technology. Initially conceived for conven-tional cellular frequencies in the sub-6 GHz range (μ-Wave), the massive MIMO concept has been then progressively extended to the case in which mm-Wave frequencies are used. However, due to different propagation mechanisms in urban scenarios, the re-sulting MIMO channel models at μ-Wave and mm-Wave are radically different. Six key basic differences are pinpointed in this paper, along with the implications that they have on the architecture and algorithms of the communication transceivers and on the attainable performance in terms of reliability and multiplexing capabilities.

M5 model tree based predictive modeling of road accidents on non-urban sections of highways in India.

Science.gov (United States)

Singh, Gyanendra; Sachdeva, S N; Pal, Mahesh

2016-11-01

This work examines the application of M5 model tree and conventionally used fixed/random effect negative binomial (FENB/RENB) regression models for accident prediction on non-urban sections of highway in Haryana (India). Road accident data for a period of 2-6 years on different sections of 8 National and State Highways in Haryana was collected from police records. Data related to road geometry, traffic and road environment related variables was collected through field studies. Total two hundred and twenty two data points were gathered by dividing highways into sections with certain uniform geometric characteristics. For prediction of accident frequencies using fifteen input parameters, two modeling approaches: FENB/RENB regression and M5 model tree were used. Results suggest that both models perform comparably well in terms of correlation coefficient and root mean square error values. M5 model tree provides simple linear equations that are easy to interpret and provide better insight, indicating that this approach can effectively be used as an alternative to RENB approach if the sole purpose is to predict motor vehicle crashes. Sensitivity analysis using M5 model tree also suggests that its results reflect the physical conditions. Both models clearly indicate that to improve safety on Indian highways minor accesses to the highways need to be properly designed and controlled, the service roads to be made functional and dispersion of speeds is to be brought down. Copyright © 2016 Elsevier Ltd. All rights reserved.

Experimental Analysis and Full Prediction Model of a 5-DOF Motorized Spindle

Directory of Open Access Journals (Sweden)

Weiyu Zhang

2017-01-01

Full Text Available The cost and power consumption of DC power amplifiers are much greater than that of AC power converters. Compared to a motorized spindle supported with DC magnetic bearings, a motorized spindle supported with AC magnetic bearings is inexpensive and more efficient. This paper studies a five-degrees-of-freedom (5-DOF motorized spindle supported with AC hybrid magnetic bearings (HMBs. Most models of suspension forces, except a “switching model”, are quite accurate, but only in a particular operating area and not in regional coverage. If a “switching model” is applied to a 5-DOF motorized spindle, the real-time performance of the control system can be significantly decreased due to the large amount of data processing for both displacement and current. In order to solve this defect, experiments based on the “switching model” are performed, and the resulting data are analyzed. Using the data analysis results, a “full prediction model” based on the operating state is proposed to improve real-time performance and precision. Finally, comparative, verification and stiffness tests are conducted to verify the improvement of the proposed model. Results of the tests indicate that the rotor has excellent characteristics, such as good real-time performance, superior anti-interference performance with load and the accuracy of the model in full zone. The satisfactory experimental results demonstrate the effectiveness of the “full prediction model” applied to the control system under different operating stages. Therefore, the results of the experimental analysis and the proposed full prediction model can provide a control system of a 5-DOF motorized spindle with the most suitable mathematical models of the suspension force.

The predicting ultimate of joint withdrawal resistance constructed of plywood with regression models application according to diameter and penetrating depth

Directory of Open Access Journals (Sweden)

Sadegh Maleki

2013-11-01

Full Text Available The goal of this study was to present regression models for predicting resistance of joints made with screw and plywood members. Joint members were out of hardwood plywood that were 19 mm in thickness. Two types of screws including coarse and fine thread drywall screw with 3.5, 4 and 5mm in diameter and sheet metal screw with 4 and 5mm were used. Results have shown that withdrawal resistance of screw was increased by increasing of screws, diameter and penetrating depth. Joints fabricated with coarse thread drywall screws were higher than those of fine thread drywall screws. Finally, average joint withdrawal resistance of screwed could be predicted by means of the expressions Wc=2.127×D1.072×P0.520 for coarse thread drywall screws and Wf=1.377×D1.156×P0.581 for fine thread drywall screws by taking account the diameter and penetrating depth. The difference of the observed and predicted data showed that developed models have a good correlation with actual experimental measurements.

Development of Simple Drying Model for Performance Prediction of Solar Dryer: Theoretical Analysis

DEFF Research Database (Denmark)

Singh, Shobhana; Kumar, Subodh

2012-01-01

An analytical moisture diffusion model which considers the influence of external resistance to mass transfer is developed to predict thermal performance of dryer system. The moisture diffusion coefficient, Deff that is necessary to evaluate the prediction model has been determined in terms...... of experimental drying parameters. A laboratory model of mixed-mode solar dryer system is tested with cylindrical potato samples of thickness 5 and 18 mm under simulated indoor conditions. The potato samples were dried at a constant absorbed thermal energy of 750 W/m2 and air mass flow rate of 0.011 kg...

Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

Science.gov (United States)

Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

2018-05-01

TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks.

Science.gov (United States)

Kane, Michael J; Price, Natalie; Scotch, Matthew; Rabinowitz, Peter

2014-08-13

Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power. We applied ARIMA and Random Forest time series models to incidence data of outbreaks of highly pathogenic avian influenza (H5N1) in Egypt, available through the online EMPRES-I system. We found that the Random Forest model outperformed the ARIMA model in predictive ability. Furthermore, we found that the Random Forest model is effective for predicting outbreaks of H5N1 in Egypt. Random Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks. This result, along with those showing the concordance between bird and human outbreaks (Rabinowitz et al. 2012), provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data. Our analysis uncovers the time-series structure of outbreak severity for highly pathogenic avain influenza (H5N1) in Egypt.

Size distribution and concentrations of heavy metals in atmospheric aerosols originating from industrial emissions as predicted by the HYSPLIT model

Science.gov (United States)

Chen, Bing; Stein, Ariel F.; Maldonado, Pabla Guerrero; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Castell, Nuria; de la Rosa, Jesus D.

2013-06-01

This study presents a description of the emission, transport, dispersion, and deposition of heavy metals contained in atmospheric aerosols emitted from a large industrial complex in southern Spain using the HYSPLIT model coupled with high- (MM5) and low-resolution (GDAS) meteorological simulations. The dispersion model was configured to simulate eight size fractions (17 μm) of metals based on direct measurements taken at the industrial emission stacks. Twelve stacks in four plants were studied and the stacks showed considerable differences for both emission fluxes and size ranges of metals. We model the dispersion of six major metals; Cr, Co, Ni, La, Zn, and Mo, which represent 77% of the total mass of the 43 measured elements. The prediction shows that the modeled industrial emissions produce an enrichment of heavy metals by a factor of 2-5 for local receptor sites when compared to urban and rural background areas in Spain. The HYSPLIT predictions based on the meteorological fields from MM5 show reasonable consistence with the temporal evolution of concentrations of Cr, Co, and Ni observed at three sites downwind of the industrial area. The magnitude of concentrations of metals at two receptors was underestimated for both MM5 (by a factor of 2-3) and GDAS (by a factor of 4-5) meteorological runs. The model prediction shows that heavy metal pollution from industrial emissions in this area is dominated by the ultra-fine (<0.66 μm) and fine (<2.5 μm) size fractions.

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.

Science.gov (United States)

Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu

2018-01-19

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model

Directory of Open Access Journals (Sweden)

Jingzhou Xin

2018-01-01

Full Text Available Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA, and generalized autoregressive conditional heteroskedasticity (GARCH. Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS deformation monitoring system demonstrated that: (1 the Kalman filter is capable of denoising the bridge deformation monitoring data; (2 the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3 in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity; the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data

Tuned and Balanced Redistributed Charge Scheme for Combined Quantum Mechanical and Molecular Mechanical (QM/MM) Methods and Fragment Methods: Tuning Based on the CM5 Charge Model.

Science.gov (United States)

Wang, Bo; Truhlar, Donald G

2013-02-12

Tuned and balanced redistributed charge schemes have been developed for modeling the electrostatic fields of bonds that are cut by a quantum mechanical-molecular mechanical boundary in combined quantum mechanical and molecular mechanical (QM/MM) methods. First, the charge is balanced by adjusting the charge on the MM boundary atom to conserve the total charge of the entire QM/MM system. In the balanced smeared redistributed charge (BSRC) scheme, the adjusted MM boundary charge is smeared with a smearing width of 1.0 Å and is distributed in equal portions to the midpoints of the bonds between the MM boundary atom and the MM atoms bonded to it; in the balanced redistributed charge-2 (BRC2) scheme, the adjusted MM boundary charge is distributed as point charges in equal portions to the MM atoms that are bonded to the MM boundary atom. The QM subsystem is capped by a fluorine atom that is tuned to reproduce the sum of partial atomic charges of the uncapped portion of the QM subsystem. The new aspect of the present study is a new way to carry out the tuning process; in particular, the CM5 charge model, rather than the Mulliken population analysis applied in previous studies, is used for tuning the capping atom that terminates the dangling bond of the QM region. The mean unsigned error (MUE) of the QM/MM deprotonation energy for a 15-system test suite of deprotonation reactions is 2.3 kcal/mol for the tuned BSRC scheme (TBSRC) and 2.4 kcal/mol for the tuned BRC2 scheme (TBRC2). As was the case for the original tuning method based on Mulliken charges, the new tuning method performs much better than using conventional hydrogen link atoms, which have an MUE on this test set of about 7 kcal/mol. However, the new scheme eliminates the need to use small basis sets, which can be problematic, and it allows one to be more consistent by tuning the parameters with whatever basis set is appropriate for applications. (Alternatively, since the tuning parameters and partial charges

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

Science.gov (United States)

Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-06-07

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

Directory of Open Access Journals (Sweden)

Massaine Bandeira e Sousa

2017-06-01

Full Text Available Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1 single-environment, main genotypic effect model (SM; (2 multi-environment, main genotypic effects model (MM; (3 multi-environment, single variance G×E deviation model (MDs; and (4 multi-environment, environment-specific variance G×E deviation model (MDe. Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB, and a nonlinear kernel Gaussian kernel (GK. The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets, having different numbers of maize hybrids evaluated in different environments for grain yield (GY, plant height (PH, and ear height (EH. Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied.

Prediction of hourly PM2.5 using a space-time support vector regression model

Science.gov (United States)

Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang

2018-05-01

Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.

Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble

Science.gov (United States)

Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork

2016-01-01

Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819

Comprehensive fluence model for absolute portal dose image prediction

International Nuclear Information System (INIS)

Chytyk, K.; McCurdy, B. M. C.

2009-01-01

Amorphous silicon (a-Si) electronic portal imaging devices (EPIDs) continue to be investigated as treatment verification tools, with a particular focus on intensity modulated radiation therapy (IMRT). This verification could be accomplished through a comparison of measured portal images to predicted portal dose images. A general fluence determination tailored to portal dose image prediction would be a great asset in order to model the complex modulation of IMRT. A proposed physics-based parameter fluence model was commissioned by matching predicted EPID images to corresponding measured EPID images of multileaf collimator (MLC) defined fields. The two-source fluence model was composed of a focal Gaussian and an extrafocal Gaussian-like source. Specific aspects of the MLC and secondary collimators were also modeled (e.g., jaw and MLC transmission factors, MLC rounded leaf tips, tongue and groove effect, interleaf leakage, and leaf offsets). Several unique aspects of the model were developed based on the results of detailed Monte Carlo simulations of the linear accelerator including (1) use of a non-Gaussian extrafocal fluence source function, (2) separate energy spectra used for focal and extrafocal fluence, and (3) different off-axis energy spectra softening used for focal and extrafocal fluences. The predicted energy fluence was then convolved with Monte Carlo generated, EPID-specific dose kernels to convert incident fluence to dose delivered to the EPID. Measured EPID data were obtained with an a-Si EPID for various MLC-defined fields (from 1x1 to 20x20 cm 2 ) over a range of source-to-detector distances. These measured profiles were used to determine the fluence model parameters in a process analogous to the commissioning of a treatment planning system. The resulting model was tested on 20 clinical IMRT plans, including ten prostate and ten oropharyngeal cases. The model predicted the open-field profiles within 2%, 2 mm, while a mean of 96.6% of pixels over all

Simulation of boundary layer trajectory dispersion sensitivity to soil moisture conditions: MM5 and noah-based investigation

Science.gov (United States)

The sensitivity of trajectories from experiments in which volumetric values of soil moisture were changed with respect to control values were analyzed during three different synoptic episodes in June 2006. The MM5 and Noah land surface models were used to simulate the response of the planetary boun...

Evaluation of current prediction models for Lynch syndrome: updating the PREMM5 model to identify PMS2 mutation carriers

NARCIS (Netherlands)

A. Goverde (Anne); M.C.W. Spaander (Manon); D. Nieboer (Daan); A.M.W. van den Ouweland (Ans); W.N.M. Dinjens (Winand); H.J. Dubbink (Erik Jan); C. Tops (Cmj); S.W. Ten Broeke (Sanne W.); M.J. Bruno (Marco); R.M.W. Hofstra (Robert); E.W. Steyerberg (Ewout); A. Wagner (Anja)

2017-01-01

textabstractUntil recently, no prediction models for Lynch syndrome (LS) had been validated for PMS2 mutation carriers. We aimed to evaluate MMRpredict and PREMM5 in a clinical cohort and for PMS2 mutation carriers specifically. In a retrospective, clinic-based cohort we calculated predictions for

ICoNOs MM: The IT-enabled Collaborative Networked Organizations Maturity Model

NARCIS (Netherlands)

Santana Tapia, R.G.

2009-01-01

The focus of this paper is to introduce a comprehensive model for assessing and improving maturity of business-IT alignment (B-ITa) in collaborative networked organizations (CNOs): the ICoNOs MM. This two dimensional maturity model (MM) addresses five levels of maturity as well as four domains to

Ultrasonography-guided Fine-needle Aspiration for Solid Thyroid Nodules Less than 5 mm in the Largest Diameter: Comparison in Diagnostic Adequacy and Accuracy According to Nodule Size

Energy Technology Data Exchange (ETDEWEB)

Lee, Jang Hee; Kim, Dong Wook; Baek, Seung Hun [Busan Paik Hospital, Inje University College of Medicine, Busan (Korea, Republic of)

2012-03-15

This study assessed the adequacy and accuracy of ultrasonography (US)-guided fine-needle aspiration (US-FNA) of solid thyroid nodules, less than 5 mm in maximum diameter. From January to December 2009, US-FNA was performed for small solid thyroid nodules in 201 patients. Each thyroid nodule was classified into group A and B according to the largest diameter (1 mm {<=} group A < 3 mm and 3 mm {<=} group B < 5 mm). The adequacy and accuracy of US-FNA in two groups were compared using the histopathological results as a reference standard. Of the 227 thyroid nodules in 201 patients, the inadequacy of US-FNA in group A and B was 24.3% (18/74) and 13.1% (20/153), respectively, showing a statistically significant difference between the two groups (p = 0.0333, chi-square test). Eighty nodules were removed surgically in 72 patients, from which papillary thyroid carcinoma (n = 52), follicular thyroid carcinoma (n = 1), nodular hyperplasia (n = 26), and pseudonodule related to thyroiditis (n = 1) were confirmed. Based on the histopathological results of the 80 surgical nodules, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of US-FNA in group A and B were 55.0% and 79.4%, 81.8% and 100%, 84.6% and 100%, 50% and 68.2%, and 64.5% and 85.7%, respectively. The adequacy and accuracy of US-FNA for solid thyroid nodules, {>=} 3 mm in the largest diameter, were higher than those of US-FNA for very small nodules, < 3 mm in the largest diameter

SAAFEC: Predicting the Effect of Single Point Mutations on Protein Folding Free Energy Using a Knowledge-Modified MM/PBSA Approach.

Science.gov (United States)

Getov, Ivan; Petukh, Marharyta; Alexov, Emil

2016-04-07

Folding free energy is an important biophysical characteristic of proteins that reflects the overall stability of the 3D structure of macromolecules. Changes in the amino acid sequence, naturally occurring or made in vitro, may affect the stability of the corresponding protein and thus could be associated with disease. Several approaches that predict the changes of the folding free energy caused by mutations have been proposed, but there is no method that is clearly superior to the others. The optimal goal is not only to accurately predict the folding free energy changes, but also to characterize the structural changes induced by mutations and the physical nature of the predicted folding free energy changes. Here we report a new method to predict the Single Amino Acid Folding free Energy Changes (SAAFEC) based on a knowledge-modified Molecular Mechanics Poisson-Boltzmann (MM/PBSA) approach. The method is comprised of two main components: a MM/PBSA component and a set of knowledge based terms delivered from a statistical study of the biophysical characteristics of proteins. The predictor utilizes a multiple linear regression model with weighted coefficients of various terms optimized against a set of experimental data. The aforementioned approach yields a correlation coefficient of 0.65 when benchmarked against 983 cases from 42 proteins in the ProTherm database. the webserver can be accessed via http://compbio.clemson.edu/SAAFEC/.

Updating the model TREMOD - Mobile Machinery (TREMOD-MM); Aktualisierung des Modells TREMOD - Mobile Machinery (TREMOD-MM)

Energy Technology Data Exchange (ETDEWEB)

Helms, Hinrich; Lambrecht, Udo; Knoerr, Wolfram [ifeu - Institut fuer Energie- und Umweltforschung Heidelberg gGmbH, Heidelberg (Germany)

2010-05-15

In the context of the project ''Development of a model for the computation of the air pollutant emissions and the fuel consumption of combustion engines in mobile devices and machines'', the Institute for Energy and Environmental Research GmbH (Heidelberg, Federal Republic of Germany) has created the model TREMOD-MM (TREMOD Mobile Machinery). Thus a detailed computation of the emissions from mobile devices and machines in the agriculture, construction industry, forestry and gardening as well as the sport shipping and passenger shipping can be accomplished. Strongly differentiated data are considered to the age structure, engine performance, use and emission behaviour. Thus it is possible to compute the emissions for different scenarios in high degree of detail.

Predictors of Success after Extracorporeal Shock Wave Lithotripsy (ESWL for Renal Calculi Between 20—30 mm: A Multivariate Analysis Model

Directory of Open Access Journals (Sweden)

Ahmed El-Assmy

2006-01-01

Full Text Available The first-line management of renal stones between 20—30 mm remains controversial. The Extracorporeal Shock Wave Lithotripsy (ESWL stone-free rates for such patient groups vary widely. The purpose of this study was to define factors that have a significant impact on the stone-free rate after ESWL in such controversial groups. Between January 1990 and January 2004, 594 patients with renal stones 20—30 mm in length underwent ESWL monotherapy. Stone surface area was measured for all stones. The results of treatment were evaluated after 3 months of follow-up. The stone-free rate was correlated with stone and patient characteristics using the Chi-square test; factors found to be significant were further analyzed using multivariate analysis.Repeat ESWL was needed in 56.9% of cases. Post-ESWL complications occurred in 5% of cases and post-ESWL secondary procedures were required in 5.9%. At 3-month follow-up, the overall stone-free rate was 77.2%. Using the Chi-square test, stone surface area, location, number, radiological renal picture, and congenital renal anomalies had a significant impact on the stone-free rate. Multivariate analysis excluded radiological renal picture from the logistic regression model while other factors maintained their statistically significant effect on success rate, indicating that they were independent predictors. A regression analysis model was designed to estimate the probability of stone-free status after ESWL. The sensitivity of the model was 97.4%, the specificity 90%, and the overall accuracy 95.6%.Stone surface area, location, number, and congenital renal anomalies are prognostic predictors determining stone clearance after ESWL of renal calculi of 20—30 mm. High probability of stone clearance is obtained with single stone ≤400 mm2 located in renal pelvis with no congenital anomalies. Our regression model can predict the probability of the success of ESWL in such controversial groups and can define patients who

Evaluation of current prediction models for Lynch syndrome: updating the PREMM5 model to identify PMS2 mutation carriers.

Science.gov (United States)

Goverde, A; Spaander, M C W; Nieboer, D; van den Ouweland, A M W; Dinjens, W N M; Dubbink, H J; Tops, C J; Ten Broeke, S W; Bruno, M J; Hofstra, R M W; Steyerberg, E W; Wagner, A

2018-07-01

Until recently, no prediction models for Lynch syndrome (LS) had been validated for PMS2 mutation carriers. We aimed to evaluate MMRpredict and PREMM5 in a clinical cohort and for PMS2 mutation carriers specifically. In a retrospective, clinic-based cohort we calculated predictions for LS according to MMRpredict and PREMM5. The area under the operator receiving characteristic curve (AUC) was compared between MMRpredict and PREMM5 for LS patients in general and for different LS genes specifically. Of 734 index patients, 83 (11%) were diagnosed with LS; 23 MLH1, 17 MSH2, 31 MSH6 and 12 PMS2 mutation carriers. Both prediction models performed well for MLH1 and MSH2 (AUC 0.80 and 0.83 for PREMM5 and 0.79 for MMRpredict) and fair for MSH6 mutation carriers (0.69 for PREMM5 and 0.66 for MMRpredict). MMRpredict performed fair for PMS2 mutation carriers (AUC 0.72), while PREMM5 failed to discriminate PMS2 mutation carriers from non-mutation carriers (AUC 0.51). The only statistically significant difference between PMS2 mutation carriers and non-mutation carriers was proximal location of colorectal cancer (77 vs. 28%, p PMS2 mutation carriers (AUC 0.77) and overall (AUC 0.81 vs. 0.72). We validated these results in an external cohort of 376 colorectal cancer patients, including 158 LS patients. MMRpredict and PREMM5 cannot adequately identify PMS2 mutation carriers. Adding location of colorectal cancer to PREMM5 may improve the performance of this model, which should be validated in larger cohorts.

Where, When, and How mmWave is Used in 5G and Beyond

Science.gov (United States)

Sakaguchi, Kei; Haustein, Thomas; Barbarossa, Sergio; Strinati, Emilio Calvanese; Clemente, Antonio; Destino, Giuseppe; Pärssinen, Aarno; Kim, Ilgyu; Chung, Heesang; Kim, Junhyeong; Keusgen, Wilhelm; Weiler, Richard J.; Takinami, Koji; Ceci, Elena; Sadri, Ali; Xian, Liang; Maltsev, Alexander; Tran, Gia Khanh; Ogawa, Hiroaki; Mahler, Kim; Heath, Robert W., Jr.

Wireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but instead an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes. The paper starts with 28 GHz outdoor backhauling for fixed wireless access and moving hotspots, which will be demonstrated at the PyeongChang winter Olympic games in 2018. The second deployment example is a 60 GHz unlicensed indoor access system at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC) to enable ultra-high speed content download with low latency. The third example is mmWave mesh network to be used as a micro Radio Access Network ({\\mu}-RAN), for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and Vehicular-to-Everything (V2X) communications system, which enables automated driving by exchanging High Definition (HD) dynamic map information between cars and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play important roles for a diverse set of applications that require both ultra-high data rate and low latency communications.

Individual-Level Concentrations of Fine Particulate Matter Chemical Components and Subclinical Atherosclerosis: A Cross-Sectional Analysis Based on 2 Advanced Exposure Prediction Models in the Multi-Ethnic Study of Atherosclerosis

Science.gov (United States)

Kim, Sun-Young; Sheppard, Lianne; Kaufman, Joel D.; Bergen, Silas; Szpiro, Adam A.; Larson, Timothy V.; Adar, Sara D.; Diez Roux, Ana V.; Polak, Joseph F.; Vedal, Sverre

2014-01-01

Long-term exposure to outdoor particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) has been associated with cardiovascular morbidity and mortality. The chemical composition of PM2.5 that may be most responsible for producing these associations has not been identified. We assessed cross-sectional associations between long-term concentrations of PM2.5 and 4 of its chemical components (sulfur, silicon, elemental carbon, and organic carbon (OC)) and subclinical atherosclerosis, measured as carotid intima-media thickness (CIMT) and coronary artery calcium, between 2000 and 2002 among 5,488 Multi-Ethnic Study of Atherosclerosis participants residing in 6 US metropolitan areas. Long-term concentrations of PM2.5 components at participants' homes were predicted using both city-specific spatiotemporal models and a national spatial model. The estimated differences in CIMT associated with interquartile-range increases in sulfur, silicon, and OC predictions from the spatiotemporal model were 0.022 mm (95% confidence interval (CI): 0.014, 0.031), 0.006 mm (95% CI: 0.000, 0.012), and 0.026 mm (95% CI: 0.019, 0.034), respectively. Findings were generally similar using the national spatial model predictions but were often sensitive to adjustment for city. We did not find strong evidence of associations with coronary artery calcium. Long-term concentrations of sulfur and OC, and possibly silicon, were associated with CIMT using 2 distinct exposure prediction modeling approaches. PMID:25164422

Performance of six 4.5 m SSC [Superconducting Super Collider] dipole model magnets

International Nuclear Information System (INIS)

Willen, E.; Dahl, P.; Cottingham, J.

1986-01-01

Six 4.5 m long dipole models for the proposed Superconducting Super Collider have been successfully tested. The magnets are cold-iron (and cold bore) 1-in-1 dipoles, wound with current density-graded high homogeneity NbTi cable in a two-layer cos θ coil of 40 mm inner diameter. The coil is prestressed by 15 mm wide stainless steel collars, and mounted in a circular, split iron yoke of 267 mm outer diameter, supported in a cylindrical yoke containment vessel. At 4.5 K the magnets reached a field of about 6.6 T with little training, or the short sample limit of the conductor, and in subcooled (2.6 - 2.4 K) liquid, 8 T was achieved. The allowed harmonics were close to the predicted values, and the unallowed harmonics small. The sextupole trim coil operated well above the required current with little training

Improvement of Bragg peak shift estimation using dimensionality reduction techniques and predictive linear modeling

Science.gov (United States)

Xing, Yafei; Macq, Benoit

2017-11-01

With the emergence of clinical prototypes and first patient acquisitions for proton therapy, the research on prompt gamma imaging is aiming at making most use of the prompt gamma data for in vivo estimation of any shift from expected Bragg peak (BP). The simple problem of matching the measured prompt gamma profile of each pencil beam with a reference simulation from the treatment plan is actually made complex by uncertainties which can translate into distortions during treatment. We will illustrate this challenge and demonstrate the robustness of a predictive linear model we proposed for BP shift estimation based on principal component analysis (PCA) method. It considered the first clinical knife-edge slit camera design in use with anthropomorphic phantom CT data. Particularly, 4115 error scenarios were simulated for the learning model. PCA was applied to the training input randomly chosen from 500 scenarios for eliminating data collinearities. A total variance of 99.95% was used for representing the testing input from 3615 scenarios. This model improved the BP shift estimation by an average of 63+/-19% in a range between -2.5% and 86%, comparing to our previous profile shift (PS) method. The robustness of our method was demonstrated by a comparative study conducted by applying 1000 times Poisson noise to each profile. 67% cases obtained by the learning model had lower prediction errors than those obtained by PS method. The estimation accuracy ranged between 0.31 +/- 0.22 mm and 1.84 +/- 8.98 mm for the learning model, while for PS method it ranged between 0.3 +/- 0.25 mm and 20.71 +/- 8.38 mm.

PACE-90 water and solute transport calculations for 0.01, 0.1, and 0. 5 mm/yr infiltration into Yucca Mountain

International Nuclear Information System (INIS)

Dykhuizen, R.C.; Eaton, R.R.; Hopkins, P.L.; Martinez, M.J.

1991-12-01

Numerical results are presented for the Performance Assessment Calculational Exercise (PACE-90). One- and two-dimensional water and solute transport are presented for steady infiltration into Yucca Mountain. Evenly distributed infiltration rates of 0.01, 0.1, and 0.5 mm/yr were considered. The calculations of solute transport show that significant amounts of radionuclides can reach the water table over 100,000 yr at the 0.5 mm/yr rate. For time periods less than 10,000 yr or infiltrations less than 0.1 mm/yr very little solute reaches the water table. The numerical simulations clearly demonstrate that multi-dimensional effects can result in significant decreases in the travel time of solute through the modeled domain. Dual continuum effects are shown to be negligible for the low steady state fluxes considered. However, material heterogeneities may cause local amplification of the flux level in multi-dimensional flows. These higher flux levels may then require modeling of a dual continuum porous medium

A prediction model for 5-year cardiac mortality in patients with chronic heart failure using {sup 123}I-metaiodobenzylguanidine imaging

Energy Technology Data Exchange (ETDEWEB)

Nakajima, Kenichi; Matsuo, Shinro [Kanazawa University Hospital, Department of Nuclear Medicine, Kanazawa (Japan); Nakata, Tomoaki [Sapporo Medical University School of Medicine, Second Department of Internal Medicine (Cardiology), Sapporo (Japan); Hakodate-Goryoukaku Hospital, Department of Cardiology, Hakodate (Japan); Yamada, Takahisa [Osaka Prefectural General Medical Center, Department of Cardiology, Osaka (Japan); Yamashina, Shohei [Toho University Omori Medical Center, Department of Cardiovascular Medicine, Tokyo (Japan); Momose, Mitsuru [Tokyo Women' s Medical University, Department of Nuclear Medicine, Tokyo (Japan); Kasama, Shu [Cardiovascular Hospital of Central Japan, Department of Cardiology, Shibukawa (Japan); Matsui, Toshiki [Social Insurance Shiga General Hospital, Department of Cardiology, Otsu (Japan); Travin, Mark I. [Albert Einstein Medical College, Department of Cardiology and Nuclear Medicine, Montefiore Medical Center, Bronx, NY (United States); Jacobson, Arnold F. [GE Healthcare, Medical Diagnostics, Princeton, NJ (United States)

2014-09-15

Prediction of mortality risk is important in the management of chronic heart failure (CHF). The aim of this study was to create a prediction model for 5-year cardiac death including assessment of cardiac sympathetic innervation using data from a multicenter cohort study in Japan. The original pooled database consisted of cohort studies from six sites in Japan. A total of 933 CHF patients who underwent {sup 123}I-metaiodobenzylguanidine (MIBG) imaging and whose 5-year outcomes were known were selected from this database. The late MIBG heart-to-mediastinum ratio (HMR) was used for quantification of cardiac uptake. Cox proportional hazard and logistic regression analyses were used to select appropriate variables for predicting 5-year cardiac mortality. The formula for predicting 5-year mortality was created using a logistic regression model. During the 5-year follow-up, 205 patients (22 %) died of a cardiac event including heart failure death, sudden cardiac death and fatal acute myocardial infarction (64 %, 30 % and 6 %, respectively). Multivariate logistic analysis selected four parameters, including New York Heart Association (NYHA) functional class, age, gender and left ventricular ejection fraction, without HMR (model 1) and five parameters with the addition of HMR (model 2). The net reclassification improvement analysis for all subjects was 13.8 % (p < 0.0001) by including HMR and its inclusion was most effective in the downward reclassification of low-risk patients. Nomograms for predicting 5-year cardiac mortality were created from the five-parameter regression model. Cardiac MIBG imaging had a significant additive value for predicting cardiac mortality. The prediction formula and nomograms can be used for risk stratifying in patients with CHF. (orig.)

Iris-fixated phakic intraocular lens implantation to correct myopia and a predictive model of endothelial cell loss.

Science.gov (United States)

Bouheraoua, Nacim; Bonnet, Clemence; Labbé, Antoine; Sandali, Otman; Lecuen, Nicolas; Ameline, Barbara; Borderie, Vincent; Laroche, Laurent

2015-11-01

To report long-term results of Artisan phakic intraocular lens (pIOL) to correct myopia and to propose a model predicting endothelial cell loss after pIOL implantation. Quinze-Vingts National Ophthalmology Hospital, Paris, France. Retrospective, interventional case series. Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), and central endothelial cell count (ECC) were determined before and at yearly intervals up to 5 years after pIOL implantation. Linear model analysis was performed to present a model that describes endothelial cell loss as a linear decrease and an additional decrease depending on postoperative loss. A total of 49 patients (68 eyes) implanted with pIOLs from January 2000 to January 2009 were evaluated. The mean preoperative and final spherical equivalent (SE) were -13 ± 4.10 and -0.75 ± 0.74 diopters (D), respectively. The mean preoperative and final central ECC were 2629 ± 366 and 2250 ± 454 cells/mm(2), respectively. There were no intraoperative complications for any of the eyes. One eye required surgery for repositioning the pIOL, and 1 eye required pIOL exchange for postoperative refractive error. The model predicted that for patients with preoperative ECC of 3000, 2500, and 2000 cells/mm(2), a critical ECC of 1500 cells/mm(2) will be reached at 39, 28, and 15 years after implantation, respectively. Implantation of the pIOL was an effective and stable procedure after 5 years of follow-up. The presented model predicted EC loss after pIOL implantation, which can assist ophthalmologists in patient selection and follow-up. The authors report no conflict of interest. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Failed rib region prediction in a human body model during crash events with precrash braking.

Science.gov (United States)

Guleyupoglu, B; Koya, B; Barnard, R; Gayzik, F S

2018-02-28

The objective of this study is 2-fold. We used a validated human body finite element model to study the predicted chest injury (focusing on rib fracture as a function of element strain) based on varying levels of simulated precrash braking. Furthermore, we compare deterministic and probabilistic methods of rib injury prediction in the computational model. The Global Human Body Models Consortium (GHBMC) M50-O model was gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and airbag. Twelve cases were investigated with permutations for failure, precrash braking system, and crash severity. The severities used were median (17 kph), severe (34 kph), and New Car Assessment Program (NCAP; 56.4 kph). Cases with failure enabled removed rib cortical bone elements once 1.8% effective plastic strain was exceeded. Alternatively, a probabilistic framework found in the literature was used to predict rib failure. Both the probabilistic and deterministic methods take into consideration location (anterior, lateral, and posterior). The deterministic method is based on a rubric that defines failed rib regions dependent on a threshold for contiguous failed elements. The probabilistic method depends on age-based strain and failure functions. Kinematics between both methods were similar (peak max deviation: ΔX head = 17 mm; ΔZ head = 4 mm; ΔX thorax = 5 mm; ΔZ thorax = 1 mm). Seat belt forces at the time of probabilistic failed region initiation were lower than those at deterministic failed region initiation. The probabilistic method for rib fracture predicted more failed regions in the rib (an analog for fracture) than the deterministic method in all but 1 case where they were equal. The failed region patterns between models are similar; however, there are differences that arise due to stress reduced from element elimination that cause probabilistic failed regions to continue to rise after no deterministic failed region would be

A prospective randomized study comparing transnasal and peroral 5-mm ultrathin endoscopy

Directory of Open Access Journals (Sweden)

Lian-Feng Lin

2014-06-01

Conclusion: PO intubation seems an excellent alternative method when using a 5-mm ultrathin endoscopy because it achieves comparable patient tolerance, acceptance, and satisfaction as TN intubation, takes less time and causes lower intubation failure and epistaxis.

Prediction of bending moment resistance of screw connected joints in plywood members using regression models and compare with that commercial medium density fiberboard (MDF and particleboard

Directory of Open Access Journals (Sweden)

Sadegh Maleki

2014-11-01

Full Text Available The study aimed at predicting bending moment resistance plywood of screw (coarse and fine threads joints using regression models. Thickness of the member was 19mm and compared with medium density fiberboard (MDF and particleboard with 18mm thicknesses. Two types of screws including coarse and fine thread drywall screw with nominal diameters of 6, 8 and 10mm and 3.5, 4 and 5 cm length respectively and sheet metal screw with diameters of 8 and 10 and length of 4 cm were used. The results of the study have shown that bending moment resistance of screw was increased by increasing of screws diameter and penetrating depth. Screw Length was found to have a larger influence on bending moment resistance than screw diameter. Bending moment resistance with coarse thread drywall screws was higher than those of fine thread drywall screws. The highest bending moment resistance (71.76 N.m was observed in joints made with coarse screw which were 5 mm in diameter and 28 mm in depth of penetration. The lowest bending moment resistance (12.08 N.m was observed in joints having fine screw with 3.5 mm diameter and 9 mm penetrations. Furthermore, bending moment resistance in plywood was higher than those of medium density fiberboard (MDF and particleboard. Finally, it has been found that the ultimate bending moment resistance of plywood joint can be predicted following formula Wc = 0.189×D0.726×P0.577 for coarse thread drywall screws and Wf = 0.086×D0.942×P0.704 for fine ones according to diameter and penetrating depth. The analysis of variance of the experimental and predicted data showed that the developed models provide a fair approximation of actual experimental measurements.

Graft-free Ahmed tube insertion: a modified method at 5 mm from limbus

Directory of Open Access Journals (Sweden)

Juan Carlos Mesa-Gutiérrez

2010-04-01

Full Text Available Juan Carlos Mesa-Gutiérrez, Juan Lillo-Sopena, Anna Monés-Llivina, Silvia Sanz-Moreno, Jorge Arruga-GinebredaDepartment of Ophthalmology, Hospital Universitari de Bellvitge, L’Hospitalet de Llobregat, Barcelona, SpainObjective: To determine the medium-term outcome of Ahmed implants inserted through a needle tract at 5 mm from limbus that eliminates the need for a donor scleral graft.Methods: A retrospective case series of 19 patients undergoing Ahmed implant surgery for refractory glaucoma with a mean follow-up of 12 months. Primary outcome measures included control of intraocular pressure after surgery. Secondary outcome measure included the frequency of intraoperative and postoperative complications.Results: Intraocular pressure was maintained between 6 and 21 mmHg throughout the study. There was no postoperative hypotony. There were no complications related to this modified technique.Conclusion: Needle tract at 5 mm from limbus maintains implant’s ability to control intraocular pressure and eliminates the need for a donor scleral graft or heterologous material.Keywords: surgical technique, Ahmed implant, refractory glaucoma, donor scleral graft, tube shunt device

Video-assisted thoracoscopic thymectomy using 5-mm ports and carbon dioxide insufflation

DEFF Research Database (Denmark)

Petersen, René Horsleben

2016-01-01

complications overall with similar outcomes regarding survival, recurrence of thymoma and complete remission (CR) for myasthenia gravis patients. A variety of different approaches have been described previously. This is a detailed description of video-assisted thoracoscopic thymectomy using three 5 mm ports...

Prediction of N-nitrosodimethylamine (NDMA) formation as a disinfection by-product.

Science.gov (United States)

Kim, Jongo; Clevenger, Thomas E

2007-06-25

This study investigated the possibility of a statistical model application for the prediction of N-nitrosodimethylamine (NDMA) formation. The NDMA formation was studied as a function of monochloramine concentration (0.001-5mM) at fixed dimethylamine (DMA) concentrations of 0.01mM or 0.05mM. Excellent linear correlations were observed between the molar ratio of monochloramine to DMA and the NDMA formation on a log scale at pH 7 and 8. When a developed prediction equation was applied to a previously reported study, a good result was obtained. The statistical model appears to predict adequately NDMA concentrations if other NDMA precursors are excluded. Using the predictive tool, a simple and approximate calculation of NDMA formation can be obtained in drinking water systems.

Probabilistic Predictions of PM2.5 Using a Novel Ensemble Design for the NAQFC

Science.gov (United States)

Kumar, R.; Lee, J. A.; Delle Monache, L.; Alessandrini, S.; Lee, P.

2017-12-01

Poor air quality (AQ) in the U.S. is estimated to cause about 60,000 premature deaths with costs of 100B-150B annually. To reduce such losses, the National AQ Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) produces forecasts of ozone, particulate matter less than 2.5 mm in diameter (PM2.5), and other pollutants so that advance notice and warning can be issued to help individuals and communities limit the exposure and reduce air pollution-caused health problems. The current NAQFC, based on the U.S. Environmental Protection Agency Community Multi-scale AQ (CMAQ) modeling system, provides only deterministic AQ forecasts and does not quantify the uncertainty associated with the predictions, which could be large due to the chaotic nature of atmosphere and nonlinearity in atmospheric chemistry. This project aims to take NAQFC a step further in the direction of probabilistic AQ prediction by exploring and quantifying the potential value of ensemble predictions of PM2.5, and perturbing three key aspects of PM2.5 modeling: the meteorology, emissions, and CMAQ secondary organic aerosol formulation. This presentation focuses on the impact of meteorological variability, which is represented by three members of NOAA's Short-Range Ensemble Forecast (SREF) system that were down-selected by hierarchical cluster analysis. These three SREF members provide the physics configurations and initial/boundary conditions for the Weather Research and Forecasting (WRF) model runs that generate required output variables for driving CMAQ that are missing in operational SREF output. We conducted WRF runs for Jan, Apr, Jul, and Oct 2016 to capture seasonal changes in meteorology. Estimated emissions of trace gases and aerosols via the Sparse Matrix Operator Kernel (SMOKE) system were developed using the WRF output. WRF and SMOKE output drive a 3-member CMAQ mini-ensemble of once-daily, 48-h PM2.5 forecasts for the same four months. The CMAQ mini

A 2.5-mm diameter probe for photoacoustic and ultrasonic endoscopy.

Science.gov (United States)

Yang, Joon-Mo; Chen, Ruimin; Favazza, Christopher; Yao, Junjie; Li, Chiye; Hu, Zhilin; Zhou, Qifa; Shung, K Kirk; Wang, Lihong V

2012-10-08

We have created a 2.5-mm outer diameter integrated photo-acoustic and ultrasonic mini-probe which can be inserted into a standard video endoscope's instrument channel. A small-diameter focused ultrasonic transducer made of PMN-PT provides adequate signal sensitivity, and enables miniaturization of the probe. Additionally, this new endoscopic probe utilizes the same scanning mirror and micromotor-based built-in actuator described in our previous reports; however, the length of the rigid distal section of the new probe has been further reduced to ~35 mm. This paper describes the technical details of the mini-probe and presents experimental results that both quantify the imaging performance and demonstrate its in vivo imaging capability, which suggests that it could work as a mini-probe for certain clinical applications.

A 2.5-mm diameter probe for photoacoustic and ultrasonic endoscopy

Science.gov (United States)

Yang, Joon-Mo; Chen, Ruimin; Favazza, Christopher; Yao, Junjie; Li, Chiye; Hu, Zhilin; Zhou, Qifa; Shung, K. Kirk; Wang, Lihong V.

2012-01-01

We have created a 2.5-mm outer diameter integrated photo-acoustic and ultrasonic mini-probe which can be inserted into a standard video endoscope’s instrument channel. A small-diameter focused ultrasonic transducer made of PMN-PT provides adequate signal sensitivity, and enables miniaturization of the probe. Additionally, this new endoscopic probe utilizes the same scanning mirror and micromotor-based built-in actuator described in our previous reports; however, the length of the rigid distal section of the new probe has been further reduced to ~35 mm. This paper describes the technical details of the mini-probe and presents experimental results that both quantify the imaging performance and demonstrate its in vivo imaging capability, which suggests that it could work as a mini-probe for certain clinical applications. PMID:23188360

Invisalign® treatment in the anterior region: were the predicted tooth movements achieved?

Science.gov (United States)

Krieger, Elena; Seiferth, Jörg; Marinello, Ivana; Jung, Britta A; Wriedt, Susanne; Jacobs, Collin; Wehrbein, Heinrich

2012-09-01

Based on our previous pilot study, the objective of this extended study was to compare (a) casts to their corresponding digital ClinCheck® models at baseline and (b) the tooth movement achieved at the end of aligner therapy (Invisalign®) to the predicted movement in the anterior region. Pre- and post-treatment casts as well as initial and final ClinChecks® models of 50 patients (15-63 years of age) were analyzed. All patients were treated with Invisalign® (Align Technology, Santa Clara, CA, USA). Evaluated parameters were: upper/lower anterior arch length and intercanine distance, overjet, overbite, dental midline shift, and the irregularity index according to Little. The comparison achieved/predicted tooth movement was tested for equivalence [adjusted 98.57% confidence interval (- 1.00; + 1.00)]. Before treatment the anterior crowding, according to Little, was on average 5.39 mm (minimum 1.50 mm, maximum 14.50 mm) in the upper dentition and 5.96 mm (minimum 2.00 mm, maximum 11.50 mm) in the lower dentition. After treatment the values were reduced to 1.57 mm (minimum 0 mm, maximum 4.5 mm) in the maxilla and 0.82 mm (minimum 0 mm, maximum 2.50 mm) in the mandible. We found slight deviations between pretreatment casts and initialClinCheck® ranging on average from -0.08 mm (SD ± 0.29) for the overjet and up to -0.28 mm (SD ± 0.46) for the upper anterior arch length. The difference between achieved/predicted tooth movements ranged on average from 0.01 mm (SD ± 0.48) for the lower anterior arch length, up to 0.7 mm (SD ± 0.87) for the overbite. All parameters were significantly equivalent except for the overbite (-1.02; -0.39). Performed with aligners (Invisalign®), the resolvement of the partly severe anterior crowding was successfully accomplished. Resolving lower anterior crowding by protrusion of the anterior teeth (i.e., enlargement of the anterior arch length) seems well predictable. The initial ClinCheck® models provided high accuracy compared to the

Silicon Photonics Integrated Circuits for 5th Generation mm-Wave Wireless Communications

DEFF Research Database (Denmark)

Rommel, Simon; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso

Hybrid photonic-wireless transmission schemes in the mm-wave frequency are promising candidates to enable the multi-gigabit per second data communications required from wireless and mobile networks of the 5th and future generations. Photonic integration may pave the way to practical applicability...

Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients.

Science.gov (United States)

Kontodimopoulos, Nick; Bozios, Panagiotis; Yfantopoulos, John; Niakas, Dimitris

2013-04-01

The purpose of this methodological study was to to provide insight into the under-addressed issue of the longitudinal predictive ability of mapping models. Post-intervention predicted and reported utilities were compared, and the effect of disease severity on the observed differences was examined. A cohort of 120 rheumatoid arthritis (RA) patients (60.0% female, mean age 59.0) embarking on therapy with biological agents completed the Modified Health Assessment Questionnaire (MHAQ) and the EQ-5D at baseline, and at 3, 6 and 12 months post-intervention. OLS regression produced a mapping equation to estimate post-intervention EQ-5D utilities from baseline MHAQ data. Predicted and reported utilities were compared with t test, and the prediction error was modeled, using fixed effects, in terms of covariates such as age, gender, time, disease duration, treatment, RF, DAS28 score, predicted and reported EQ-5D. The OLS model (RMSE = 0.207, R(2) = 45.2%) consistently underestimated future utilities, with a mean prediction error of 6.5%. Mean absolute differences between reported and predicted EQ-5D utilities at 3, 6 and 12 months exceeded the typically reported MID of the EQ-5D (0.03). According to the fixed-effects model, time, lower predicted EQ-5D and higher DAS28 scores had a significant impact on prediction errors, which appeared increasingly negative for lower reported EQ-5D scores, i.e., predicted utilities tended to be lower than reported ones in more severe health states. This study builds upon existing research having demonstrated the potential usefulness of mapping disease-specific instruments onto utility measures. The specific issue of longitudinal validity is addressed, as mapping models derived from baseline patients need to be validated on post-therapy samples. The underestimation of post-treatment utilities in the present study, at least in more severe patients, warrants further research before it is prudent to conduct cost-utility analyses in the context

Wideband Channel Modeling for mm-Wave inside Trains for 5G-Related Applications

Directory of Open Access Journals (Sweden)

Juan Moreno García-Loygorri

2018-01-01

Full Text Available Passenger trains and especially metro trains have been identified as one of the key scenarios for 5G deployments. The wireless channel inside a train car is reported in the frequency range between 26.5 GHz and 40 GHz. These bands have received a lot of interest for high-density scenarios with a high-traffic demand, two of the most relevant aspects of a 5G network. In this paper we provide a full description of the wideband channel estimating Power-Delay Profiles (PDP, Saleh-Valenzuela model parameters, time-of-arrival (TOA ranging, and path-loss results. Moreover, the performance of an automatic clustering algorithm is evaluated. The results show a remarkable degree of coherence and general conclusions are obtained.

Simulation of heavy precipitation episode over eastern Peninsular Malaysia using MM5: sensitivity to cumulus parameterization schemes

Science.gov (United States)

Salimun, Ester; Tangang, Fredolin; Juneng, Liew

2010-06-01

A comparative study has been conducted to investigate the skill of four convection parameterization schemes, namely the Anthes-Kuo (AK), the Betts-Miller (BM), the Kain-Fritsch (KF), and the Grell (GR) schemes in the numerical simulation of an extreme precipitation episode over eastern Peninsular Malaysia using the Pennsylvania State University—National Center for Atmospheric Research Center (PSU-NCAR) Fifth Generation Mesoscale Model (MM5). The event is a commonly occurring westward propagating tropical depression weather system during a boreal winter resulting from an interaction between a cold surge and the quasi-stationary Borneo vortex. The model setup and other physical parameterizations are identical in all experiments and hence any difference in the simulation performance could be associated with the cumulus parameterization scheme used. From the predicted rainfall and structure of the storm, it is clear that the BM scheme has an edge over the other schemes. The rainfall intensity and spatial distribution were reasonably well simulated compared to observations. The BM scheme was also better in resolving the horizontal and vertical structures of the storm. Most of the rainfall simulated by the BM simulation was of the convective type. The failure of other schemes (AK, GR and KF) in simulating the event may be attributed to the trigger function, closure assumption, and precipitation scheme. On the other hand, the appropriateness of the BM scheme for this episode may not be generalized for other episodes or convective environments.

Site-specific strong ground motion prediction using 2.5-D modelling

Science.gov (United States)

Narayan, J. P.

2001-08-01

An algorithm was developed using the 2.5-D elastodynamic wave equation, based on the displacement-stress relation. One of the most significant advantages of the 2.5-D simulation is that the 3-D radiation pattern can be generated using double-couple point shear-dislocation sources in the 2-D numerical grid. A parsimonious staggered grid scheme was adopted instead of the standard staggered grid scheme, since this is the only scheme suitable for computing the dislocation. This new 2.5-D numerical modelling avoids the extensive computational cost of 3-D modelling. The significance of this exercise is that it makes it possible to simulate the strong ground motion (SGM), taking into account the energy released, 3-D radiation pattern, path effects and local site conditions at any location around the epicentre. The slowness vector (py) was used in the supersonic region for each layer, so that all the components of the inertia coefficient are positive. The double-couple point shear-dislocation source was implemented in the numerical grid using the moment tensor components as the body-force couples. The moment per unit volume was used in both the 3-D and 2.5-D modelling. A good agreement in the 3-D and 2.5-D responses for different grid sizes was obtained when the moment per unit volume was further reduced by a factor equal to the finite-difference grid size in the case of the 2.5-D modelling. The components of the radiation pattern were computed in the xz-plane using 3-D and 2.5-D algorithms for various focal mechanisms, and the results were in good agreement. A comparative study of the amplitude behaviour of the 3-D and 2.5-D wavefronts in a layered medium reveals the spatial and temporal damped nature of the 2.5-D elastodynamic wave equation. 3-D and 2.5-D simulated responses at a site using a different strike direction reveal that strong ground motion (SGM) can be predicted just by rotating the strike of the fault counter-clockwise by the same amount as the azimuth of

Using support vector regression to predict PM10 and PM2.5

International Nuclear Information System (INIS)

Weizhen, Hou; Zhengqiang, Li; Yuhuan, Zhang; Hua, Xu; Ying, Zhang; Kaitao, Li; Donghui, Li; Peng, Wei; Yan, Ma

2014-01-01

Support vector machine (SVM), as a novel and powerful machine learning tool, can be used for the prediction of PM 10 and PM 2.5 (particulate matter less or equal than 10 and 2.5 micrometer) in the atmosphere. This paper describes the development of a successive over relaxation support vector regress (SOR-SVR) model for the PM 10 and PM 2.5 prediction, based on the daily average aerosol optical depth (AOD) and meteorological parameters (atmospheric pressure, relative humidity, air temperature, wind speed), which were all measured in Beijing during the year of 2010–2012. The Gaussian kernel function, as well as the k-fold crosses validation and grid search method, are used in SVR model to obtain the optimal parameters to get a better generalization capability. The result shows that predicted values by the SOR-SVR model agree well with the actual data and have a good generalization ability to predict PM 10 and PM 2.5 . In addition, AOD plays an important role in predicting particulate matter with SVR model, which should be included in the prediction model. If only considering the meteorological parameters and eliminating AOD from the SVR model, the prediction results of predict particulate matter will be not satisfying

Long-term results using LigaSure™ 5 mm instrument for treatment of Zenker's diverticulum

DEFF Research Database (Denmark)

Andersen, Michelle Fog; Trolle, Waldemar; Anthonsen, Kristian

2017-01-01

The purpose of the present study was to evaluate the long-term results and patient's satisfaction of a new approach using the LigaSure™ 5 mm instrument for treatment of Zenker's diverticulum (ZD) and to compare with other long-term results using traditional treatment modalities. Between December ...... to traditional endoscopic techniques and is now the standard treatment method for ZD in our departments.......The purpose of the present study was to evaluate the long-term results and patient's satisfaction of a new approach using the LigaSure™ 5 mm instrument for treatment of Zenker's diverticulum (ZD) and to compare with other long-term results using traditional treatment modalities. Between December......%) reported no symptoms at all. Our results suggest that endoscopic management of ZD with the LigaSure™ 5 mm instrument is a minimally invasive, fast and safe method with solid long-term outcome with relief of symptoms and patient satisfaction. This new operative instrument was not found inferior...

Clinical prediction of 5-year survival in systemic sclerosis

DEFF Research Database (Denmark)

Fransen, Julie Munk; Popa-Diaconu, D; Hesselstrand, R

2011-01-01

Systemic sclerosis (SSc) is associated with a significant reduction in life expectancy. A simple prognostic model to predict 5-year survival in SSc was developed in 1999 in 280 patients, but it has not been validated in other patients. The predictions of a prognostic model are usually less accura...

Constraining models of postglacial rebound using space geodesy: a detailed assessment of model ICE-5G (VM2) and its relatives

Science.gov (United States)

Argus, Donald F.; Peltier, W. Richard

2010-05-01

Using global positioning system, very long baseline interferometry, satellite laser ranging and Doppler Orbitography and Radiopositioning Integrated by Satellite observations, including the Canadian Base Network and Fennoscandian BIFROST array, we constrain, in models of postglacial rebound, the thickness of the ice sheets as a function of position and time and the viscosity of the mantle as a function of depth. We test model ICE-5G VM2 T90 Rot, which well fits many hundred Holocene relative sea level histories in North America, Europe and worldwide. ICE-5G is the deglaciation history having more ice in western Canada than ICE-4G; VM2 is the mantle viscosity profile having a mean upper mantle viscosity of 0.5 × 1021Pas and a mean uppermost-lower mantle viscosity of 1.6 × 1021Pas T90 is an elastic lithosphere thickness of 90 km; and Rot designates that the model includes (rotational feedback) Earth's response to the wander of the North Pole of Earth's spin axis towards Canada at a speed of ~1° Myr-1. The vertical observations in North America show that, relative to ICE-5G, the Laurentide ice sheet at last glacial maximum (LGM) at ~26 ka was (1) much thinner in southern Manitoba, (2) thinner near Yellowknife (Northwest Territories), (3) thicker in eastern and southern Quebec and (4) thicker along the northern British Columbia-Alberta border, or that ice was unloaded from these areas later (thicker) or earlier (thinner) than in ICE-5G. The data indicate that the western Laurentide ice sheet was intermediate in mass between ICE-5G and ICE-4G. The vertical observations and GRACE gravity data together suggest that the western Laurentide ice sheet was nearly as massive as that in ICE-5G but distributed more broadly across northwestern Canada. VM2 poorly fits the horizontal observations in North America, predicting places along the margins of the Laurentide ice sheet to be moving laterally away from the ice centre at 2 mm yr-1 in ICE-4G and 3 mm yr-1 in ICE-5G, in

SDN Controlled mmWave Massive MIMO Hybrid Precoding for 5G Heterogeneous Mobile Systems

Directory of Open Access Journals (Sweden)

Na Chen

2016-01-01

Full Text Available In 5G mobile network, millimeter wave (mmWave and heterogeneous networks (Hetnets are significant techniques to sustain coverage and spectral efficiency. In this paper, we utilize the hybrid precoding to overcome hardware constraints on the analog-only beamforming in mmWave systems. Particularly, we identify the complicated antenna coordination and vast spatial domain information as the outstanding challenges in mmWave Hetnets. In our work, we employ software defined network (SDN to accomplish radio resource management (RRM and achieve flexible spacial coordination in mmWave Hetnets. In our proposed scheme, SDN controller is responsible for collecting the user channel state information (CSI and applying hybrid precoding based on the calculated null-space of victim users. Simulation results show that our design can effectively reduce the interference to victim users and support high quality of service.

MO-G-BRF-02: Enhancement of Texture-Based Metastasis Prediction Models Via the Optimization of PET/MRI Acquisition Protocols

Energy Technology Data Exchange (ETDEWEB)

Vallieres, M; Laberge, S; Levesque I, R; El Naqa, I [McGill University, Montreal, QC (Canada)

2014-06-15

Purpose: We have previously identified a prediction model of lung metastases at diagnosis of soft-tissue sarcomas (STS) that is composed of two textural features extracted from FDG-PET and T1-weighted (T1w) MRI scans. The goal of this study is to evaluate whether the optimization in FDGPET and MRI acquisition parameters would enhance the prediction performance of texture-based models. Methods: Ten FDG-PET and T1w- MRI digitized tumor models were generated from imaging data of STS patients who underwent pre-treatment clinical scans between 2005 and 2011. Five of ten patients eventually developed lung metastases. Numerically simulated MR images were produced using echo times (TE) of 2 and 4 times the nominal clinical parameter (TEc), and repetition times (TR) of 0.5, 0.67, 1.5 and 2 times the nominal clinical parameter (TRc) found in the DICOM headers (TEc range: 9–13 ms, TRc range: 410-667 ms). PET 2D images were simulated using Monte-Carlo and were reconstructed using an ordered-subsets expectation maximization (OSEM) algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. For all possible combinations of PET and MRI acquisition parameters, the prediction model was constructed using logistic regression with new coefficients, and its associated prediction performance for lung metastases was evaluated using the area under the ROC curve (AUC). Results: The prediction performance over all simulations yielded AUCs ranging from 0.7 to 1. Notably, TR values below or equal to TRc and higher PET post-reconstruction filter widths yielded higher prediction performance. The best results were obtained with a combination of 4*TEc, TRc, 30 OSEM iterations and 2mm filter width. Conclusion: This work indicates that texture-based metastasis prediction models could be improved using optimized choices of FDG-PET and MRI acquisition protocols. This principle could be generalized to other texture-based models.

Results from a partial lifetime test of a 40 mm-aperture 17 mm SSC model dipole

International Nuclear Information System (INIS)

Radusewicz, P.; Devred, A.; Bush, T.; Coombes, R.; DiMarco, J.; Goodzeit, C.; Kuzminski, J.; Ogitsu, T.; Potter, J.; Puglisi, M.; Sanger, P.; Schermer, R.; Tompkins, J.; Yu, Y.; Zhao, Y.; Zheng, H.; Anerella, M.; Cottingham, J.; Ganetis, G.; Garber, M.; Ghosh, A.; Greene, A.; Gupta, R.; Jain, A.; Kahn, S.; Kelly, E.; Morgan, G.; Muratore, J.; Prodell, A.; Rehak, M.; Roher, E.P.; Sampson, W.; Shutt, R.; Thomas, R.; Thompson, P.; Wanderer, P.; Willen, E.; Bleadon, M.; Hanft, R.; Kuchnir, M.; Mantsch, P.; Mazur, P.O.; Orris, D.; Peterson, T.; Strait, J.; Royett, J.; Scanlan, R.; Taylor, C.

1992-03-01

A 40-mm-aperture, 17-m-long Superconducting Super Collider (SSC) model dipole was assembled at Brookhaven National Laboratory (BNL) and tested initially at Fermi National Accelerator Lab (FNAL) and later at BNL. At BNL an extended cycle test was devised to examine the magnet's performance through numerous cold tests and thermal cycles. This paper discusses the magnet's mechanical and quench performance and magnet field measurements during the tests

Regional climate simulations over South America: sensitivity to model physics and to the treatment of lateral boundary conditions using the MM5 model

Energy Technology Data Exchange (ETDEWEB)

Solman, Silvina A. [CONICET-UBA, Centro de Investigaciones del Mar y la Atmosfera (CIMA), Buenos Aires (Argentina); Universidad de Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos. Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Pessacg, Natalia L. [CONICET-UBA, Centro de Investigaciones del Mar y la Atmosfera (CIMA), Buenos Aires (Argentina)

2012-01-15

In this study the capability of the MM5 model in simulating the main mode of intraseasonal variability during the warm season over South America is evaluated through a series of sensitivity experiments. Several 3-month simulations nested into ERA40 reanalysis were carried out using different cumulus schemes and planetary boundary layer schemes in an attempt to define the optimal combination of physical parameterizations for simulating alternating wet and dry conditions over La Plata Basin (LPB) and the South Atlantic Convergence Zone regions, respectively. The results were compared with different observational datasets and model evaluation was performed taking into account the spatial distribution of monthly precipitation and daily statistics of precipitation over the target regions. Though every experiment was able to capture the contrasting behavior of the precipitation during the simulated period, precipitation was largely underestimated particularly over the LPB region, mainly due to a misrepresentation in the moisture flux convergence. Experiments using grid nudging of the winds above the planetary boundary layer showed a better performance compared with those in which no constrains were imposed to the regional circulation within the model domain. Overall, no single experiment was found to perform the best over the entire domain and during the two contrasting months. The experiment that outperforms depends on the area of interest, being the simulation using the Grell (Kain-Fritsch) cumulus scheme in combination with the MRF planetary boundary layer scheme more adequate for subtropical (tropical) latitudes. The ensemble of the sensitivity experiments showed a better performance compared with any individual experiment. (orig.)

Postglacial Rebound and Current Ice Loss Estimates from Space Geodesy: The New ICE-6G (VM5a) Global Model

Science.gov (United States)

Peltier, W. R.; Argus, D.; Drummond, R.; Moore, A. W.

2012-12-01

We compare, on a global basis, estimates of site velocity against predictions of the newly constructed postglacial rebound model ICE-6G (VM5a). This model is fit to observations of North American postglacial rebound thereby demonstrating that the ice sheet at last glacial maximum must have been, relative to ICE-5G,thinner in southern Manitoba, thinner near Yellowknife (northwest Territories), thicker in eastern and southern Quebec, and thicker along the British Columbia-Alberta border. The GPS based estimates of site velocity that we employ are more accurate than were previously available because they are based on GPS estimates of position as a function of time determined by incorporating satellite phase center variations [Desai et al. 2011]. These GPS estimates are constraining postglacial rebound in North America and Europe more tightly than ever before. In particular, given the high density of GPS sites in North America, and the fact that the velocity of the mass center (CM) of Earth is also more tightly constrained, the new model much more strongly constrains both the lateral extent of the proglacial forebulge and the rate at which this peripheral bulge (that was emplaced peripheral to the late Pleistocence Laurentia ice sheet) is presently collapsing. This fact proves to be important to the more accurate inference of the current rate of ice loss from both Greenland and Alaska based upon the time dependent gravity observations being provided by the GRACE satellite system. In West Antarctica we have also been able to significantly revise the previously prevalent ICE-5G deglaciation history so as to enable its predictions to be optimally consistent with GPS site velocities determined by connecting campaign WAGN measurements to those provided by observations from the permanent ANET sites. Ellsworth Land (south of the Antarctic peninsula), is observed to be rising at 6 ±3 mm/yr according to our latest analyses; the Ellsworth mountains themselves are observed to be

A multisensor evaluation of the asymmetric convective model, version 2, in southeast Texas.

Science.gov (United States)

Kolling, Jenna S; Pleim, Jonathan E; Jeffries, Harvey E; Vizuete, William

2013-01-01

There currently exist a number of planetary boundary layer (PBL) schemes that can represent the effects of turbulence in daytime convective conditions, although these schemes remain a large source of uncertainty in meteorology and air quality model simulations. This study evaluates a recently developed combined local and nonlocal closure PBL scheme, the Asymmetric Convective Model, version 2 (ACM2), against PBL observations taken from radar wind profilers, a ground-based lidar, and multiple daytime radiosonde balloon launches. These observations were compared against predictions of PBLs from the Weather Research and Forecasting (WRF) model version 3.1 with the ACM2 PBL scheme option, and the Fifth-Generation Meteorological Model (MM5) version 3.7.3 with the Eta PBL scheme option that is currently being used to develop ozone control strategies in southeast Texas. MM5 and WRF predictions during the regulatory modeling episode were evaluated on their ability to predict the rise and fall of the PBL during daytime convective conditions across southeastern Texas. The MM5 predicted PBLs consistently underpredicted observations, and were also less than the WRF PBL predictions. The analysis reveals that the MM5 predicted a slower rising and shallower PBL not representative of the daytime urban boundary layer. Alternatively, the WRF model predicted a more accurate PBL evolution improving the root mean square error (RMSE), both temporally and spatially. The WRF model also more accurately predicted vertical profiles of temperature and moisture in the lowest 3 km of the atmosphere. Inspection of median surface temperature and moisture time-series plots revealed higher predicted surface temperatures in WRF and more surface moisture in MM5. These could not be attributed to surface heat fluxes, and thus the differences in performance of the WRF and MM5 models are likely due to the PBL schemes. An accurate depiction of the diurnal evolution of the planetary boundary layer (PBL) is

A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment

DEFF Research Database (Denmark)

Thomas, Timothy; Rybakowski, Marcin; Sun, Shu

2016-01-01

can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve-match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2.0 to 28 GHz and ray-tracing studies from 2.0 to 73.5 GHz, both in an urban-macro...... environment, to assess the prediction performance of the two PL modeling techniques. In other words we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where...

Prediction of subcooled flow boiling characteristics using two-fluid Eulerian CFD model

Energy Technology Data Exchange (ETDEWEB)

Braz Filho, Francisco A.; Ribeiro, Guilherme B., E-mail: gbribeiro@ieav.cta.br; Caldeira, Alexandre D.

2016-11-15

Highlights: • CFD multiphase model is used to predict subcooled flow boiling characteristics. • Better agreement is achieved for higher saturation pressures. • Onset of nucleate boiling and saturated boiling are well predicted. • CFD multiphase model tends to underestimate the void fraction. • Factors were adjusted in order to improve the void fraction results. - Abstract: The present study concerns a detailed analysis of flow boiling phenomena under high pressure systems using a two-fluid Eulerian approach provided by a Computational Fluid Dynamics (CFD) solver. For this purpose, a vertical heated pipe made of stainless steel with an internal diameter of 15.4 mm was considered as the modeled domain. Two different uniform heat fluxes and three saturation pressures were applied to the channel wall, whereas water mass flux of 900 kg/m{sup 2} s was considered for all simulation cases. The model was validated against a set of experimental data and results have indicated a promising use of the CFD technique for estimation of the wall temperature, the liquid bulk temperature and the location of the departure of nucleate boiling. Changes in factors applied in the modeling of the interfacial heat transfer coefficient and bubble departure frequency were suggested, allowing a better prediction of the void fraction along the heated channel. The commercial CFD solver FLUENT 14.5 was used for the model implementation.

Prediction of subcooled flow boiling characteristics using two-fluid Eulerian CFD model

International Nuclear Information System (INIS)

Braz Filho, Francisco A.; Ribeiro, Guilherme B.; Caldeira, Alexandre D.

2016-01-01

Highlights: • CFD multiphase model is used to predict subcooled flow boiling characteristics. • Better agreement is achieved for higher saturation pressures. • Onset of nucleate boiling and saturated boiling are well predicted. • CFD multiphase model tends to underestimate the void fraction. • Factors were adjusted in order to improve the void fraction results. - Abstract: The present study concerns a detailed analysis of flow boiling phenomena under high pressure systems using a two-fluid Eulerian approach provided by a Computational Fluid Dynamics (CFD) solver. For this purpose, a vertical heated pipe made of stainless steel with an internal diameter of 15.4 mm was considered as the modeled domain. Two different uniform heat fluxes and three saturation pressures were applied to the channel wall, whereas water mass flux of 900 kg/m"2 s was considered for all simulation cases. The model was validated against a set of experimental data and results have indicated a promising use of the CFD technique for estimation of the wall temperature, the liquid bulk temperature and the location of the departure of nucleate boiling. Changes in factors applied in the modeling of the interfacial heat transfer coefficient and bubble departure frequency were suggested, allowing a better prediction of the void fraction along the heated channel. The commercial CFD solver FLUENT 14.5 was used for the model implementation.

Three-degree-of-freedom ultrasonic motor using a 5-mm-diameter piezoelectric ceramic tube.

Science.gov (United States)

Mingsen Guo; Junhui Hu; Hua Zhu; Chunsheng Zhao; Shuxiang Dong

2013-07-01

A small three-degree-of-freedom ultrasonic motor has been developed using a simple piezoelectric lead zirconate titanate (PZT)-tube stator (OD 5 mm, ID 3 mm, length 15 mm). The stator drives a ball-rotor into rotational motion around one of three orthogonal (x-, y-, and z-) axes by combing the first longitudinal and second bending vibration modes. A motor prototype was fabricated and characterized; its performance was superior to those of previous motors made with a PZT ceramic/metal composite stator of comparable size. The method for further improving the performance was discussed. The motor can be further miniaturized and it has potential to be applied to medical microrobots, endoscopes or micro laparoscopic devices, and cell manipulation devices.

Statistical Studies of Mesoscale Forecast Models MM5 and WRF

National Research Council Canada - National Science Library

Henmi, Teizi

2004-01-01

... models were carried out and the results were compared with surface observation data. Both models tended to overforecast temperature and dew-point temperature, although the correlation coefficients between forecast and observations were fairly high...

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

Science.gov (United States)

Fang, Xingang; Bagui, Sikha; Bagui, Subhash

2017-08-01

The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust Drones Formation Control in 5G Wireless Sensor Network Using mmWave

Directory of Open Access Journals (Sweden)

Shan Meng

2018-01-01

Full Text Available The drones formation control in 5G wireless sensor network is discussed. The base station (BS is used to receive backhaul position signals from the lead drone in formation and launches the beam to the lead one as the fronthaul flying signal enhancement. It is a promising approach to raise the formation strength of drones during flight control. The BS can transform the direction of the antennas and transmit energy to the lead drone that could widely enlarge the number of the receivers and increase the transmission speed of the data links. The millimeter-Wave (mmWave communication system offers new opportunities to meet this requirement owing to the tremendous amount of available spectrums. However, the massive non-line-of-sight (NLoS transmission and the site constraints in urban environment are severely challenging the conventional deploying terrestrial low power nodes (LPNs. Simulation experiments have been performed to verify the availability and effectiveness of mmWave in 5G wireless sensor network.

Predicting the water-drop energy required to breakdown dry soil aggregates

International Nuclear Information System (INIS)

Mbagwu, J.S.C.; Bazzoffi, P.

1995-04-01

The raindrop energy required to breakdown dry soil aggregates is an index of structural stability which has been found very useful in modelling soil erosion process and in evaluating the suitability of tillage implements for different soils. The aim of this research was to develop and validate a model for predicting the specific water-drop energy required to breakdown aggregates (D) as influenced by soil properties. Air-dry aggregates (2-4 mm in diameter), collected from 15 surface (0-20 cm) soils in north central Italy were used for this study. The actual and natural log-transformed D values were regressed on the soil properties. Clay content, wilting point moisture content (WP) and percent water-stable aggregates (WSA) > 2.0 mm were good predictors of D. Empirical models developed from either clay content or WP predicted D in 70% of the test soils whereas the model developed from WSA > 2.0 mm predicted D in 90% of the test soils. The correlation coefficients (r) between measured and predicted D were 0.961, 0.963 and 0.997 respectively, for models developed from clay, WP and WSA > 2.0 mm. The validity of these models need to be tested on other soils with a wider variation in properties than those used to developed the models. (author). 42 refs, 5 tabs

Performance of the first short model 150 mm aperture Nb$_3$Sn Quadrupole MQXFS for the High-Luminosity LHC upgrade

CERN Document Server

Chlachidze, G; Anerella, M; Bossert, R; Cavanna, E; Cheng, D; Dietderich, D; DiMarco, J; Felice, H; Ferracin, P; Ghosh, A; Grosclaude, P; Guinchard, M; Hafalia, A R; Holik, E; Izquierdo Bermudez, S; Krave, S; Marchevsky, M; Nobrega, F; Orris, D; Pan, H; Perez, J C; Prestemon, S; Ravaioli, E; Sabbi, G L; Salmi, T; Schmalzle, J; Stoynev, S; Strauss, T; Sylvester, C; Tartaglia, M; Todesco, E; Vallone, G; Velev, G; Wanderer, P; Wang, X; Yu, M

2017-01-01

The US LHC Accelerator Research Program (LARP) and CERN combined their efforts in developing Nb$_{3}$Sn magnets for the High-Luminosity LHC upgrade. The ultimate goal of this collaboration is to fabricate large aperture Nb$_{3}$Sn quadrupoles for the LHC interaction regions (IR). These magnets will replace the present 70 mm aperture NbTi quadrupole triplets for expected increase of the LHC peak luminosity by a factor of 5. Over the past decade LARP successfully fabricated and tested short and long models of 90 mm and 120 mm aperture Nb$_{3}$Sn quadrupoles. Recently the first short model of 150 mm diameter quadrupole MQXFS was built with coils fabricated both by the LARP and CERN. The magnet performance was tested at Fermilab’s vertical magnet test facility. This paper reports the test results, including the quench training at 1.9 K, ramp rate and temperature dependence studies.

Performance of the first short model 150 mm aperture Nb$_3$Sn Quadrupole MQXFS for the High- Luminosity LHC upgrade

Energy Technology Data Exchange (ETDEWEB)

Chlachidze, G.; et al.

2016-08-30

The US LHC Accelerator Research Program (LARP) and CERN combined their efforts in developing Nb3Sn magnets for the High-Luminosity LHC upgrade. The ultimate goal of this collaboration is to fabricate large aperture Nb3Sn quadrupoles for the LHC interaction regions (IR). These magnets will replace the present 70 mm aperture NbTi quadrupole triplets for expected increase of the LHC peak luminosity by a factor of 5. Over the past decade LARP successfully fabricated and tested short and long models of 90 mm and 120 mm aperture Nb3Sn quadrupoles. Recently the first short model of 150 mm diameter quadrupole MQXFS was built with coils fabricated both by the LARP and CERN. The magnet performance was tested at Fermilab’s vertical magnet test facility. This paper reports the test results, including the quench training at 1.9 K, ramp rate and temperature dependence studies.

Performance of Non-Orthogonal Multiple Access (NOMA) in mmWave wireless communications for 5G networks

DEFF Research Database (Denmark)

Marcano, Andrea; Christiansen, Henrik Lehrmann

2017-01-01

Among the key technologies that have been identified as capacity boosters for fifth generation - 5G - mobile networks, are millimeter wave (mmWave) transmissions and non-orthogonal multiple access (NOMA). The large amount of spectrum available at mmWave frequencies combined with a more effective...... use of available resources, helps improving the overall capacity. NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time, by implementing adaptive power allocation. In this paper we present a performance analysis of NOMA in mmWave cells...

An analysis of MM5 sensitivity to different parameterizations for high-resolution climate simulations

Science.gov (United States)

Argüeso, D.; Hidalgo-Muñoz, J. M.; Gámiz-Fortis, S. R.; Esteban-Parra, M. J.; Castro-Díez, Y.

2009-04-01

An evaluation of MM5 mesoscale model sensitivity to different parameterizations schemes is presented in terms of temperature and precipitation for high-resolution integrations over Andalusia (South of Spain). As initial and boundary conditions ERA-40 Reanalysis data are used. Two domains were used, a coarse one with dimensions of 55 by 60 grid points with spacing of 30 km and a nested domain of 48 by 72 grid points grid spaced 10 km. Coarse domain fully covers Iberian Peninsula and Andalusia fits loosely in the finer one. In addition to parameterization tests, two dynamical downscaling techniques have been applied in order to examine the influence of initial conditions on RCM long-term studies. Regional climate studies usually employ continuous integration for the period under survey, initializing atmospheric fields only at the starting point and feeding boundary conditions regularly. An alternative approach is based on frequent re-initialization of atmospheric fields; hence the simulation is divided in several independent integrations. Altogether, 20 simulations have been performed using varying physics options, of which 4 were fulfilled applying the re-initialization technique. Surface temperature and accumulated precipitation (daily and monthly scale) were analyzed for a 5-year period covering from 1990 to 1994. Results have been compared with daily observational data series from 110 stations for temperature and 95 for precipitation Both daily and monthly average temperatures are generally well represented by the model. Conversely, daily precipitation results present larger deviations from observational data. However, noticeable accuracy is gained when comparing with monthly precipitation observations. There are some especially conflictive subregions where precipitation is scarcely captured, such as the Southeast of the Iberian Peninsula, mainly due to its extremely convective nature. Regarding parameterization schemes performance, every set provides very

Heavy rain prediction using deterministic and probabilistic models - the flash flood cases of 11-13 October 2005 in Catalonia (NE Spain)

Science.gov (United States)

Barrera, A.; Altava-Ortiz, V.; Llasat, M. C.; Barnolas, M.

2007-09-01

Between the 11 and 13 October 2005 several flash floods were produced along the coast of Catalonia (NE Spain) due to a significant heavy rainfall event. Maximum rainfall achieved values up to 250 mm in 24 h. The total amount recorded during the event in some places was close to 350 mm. Barcelona city was also in the affected area where high rainfall intensities were registered, but just a few small floods occurred, thanks to the efficient urban drainage system of the city. Two forecasting methods have been applied in order to evaluate their capability of prediction regarding extreme events: the deterministic MM5 model and a probabilistic model based on the analogous method. The MM5 simulation allows analysing accurately the main meteorological features with a high spatial resolution (2 km), like the formation of some convergence lines over the region that partially explains the maximum precipitation location during the event. On the other hand, the analogous technique shows a good agreement among highest probability values and real affected areas, although a larger pluviometric rainfall database would be needed to improve the results. The comparison between the observed precipitation and from both QPF (quantitative precipitation forecast) methods shows that the analogous technique tends to underestimate the rainfall values and the MM5 simulation tends to overestimate them.

Influence of detector collimation on SNR in four different MDCT scanners using a reconstructed slice thickness of 5 mm

International Nuclear Information System (INIS)

Verdun, F.R.; Pachoud, M.; Monnin, P.; Valley, J.-F.; Noel, A.; Meuli, R.; Schnyder, P.; Denys, A.

2004-01-01

The purpose of this paper is to compare the influence of detector collimation on the signal-to-noise ratio (SNR) for a 5.0 mm reconstructed slice thickness for four multi-detector row CT (MDCT) units. SNRs were measured on Catphan test phantom images from four MDCT units: a GE LightSpeed QX/I, a Marconi MX 8000, a Toshiba Aquilion and a Siemens Volume Zoom. Five-millimetre-thick reconstructed slices were obtained from acquisitions performed using detector collimations of 2.0-2.5 mm and 5.0 mm, 120 kV, a 360 tube rotation time of 0.5 s, a wide range of mA and pitch values in the range of 0.75-0.85 and 1.25-1.5. For each set of acquisition parameters, a Wiener spectrum was also calculated. Statistical differences in SNR for the different acquisition parameters were evaluated using a Student's t-test (P<0.05). The influence of detector collimation on the SNR for a 5.0-mm reconstructed slice thickness is different for different MDCT scanners. At pitch values lower than unity, the use of a small detector collimation to produce 5.0-mm thick slices is beneficial for one unit and detrimental for another. At pitch values higher than unity, using a small detector collimation is beneficial for two units. One manufacturer uses different reconstruction filters when switching from a 2.5- to a 5.0-mm detector collimation. For a comparable reconstructed slice thickness, using a smaller detector collimation does not always reduce image noise. Thus, the impact of the detector collimation on image noise should be determined by standard deviation calculations, and also by assessing the power spectra of the noise. (orig.)

Is a 5 mm rat calvarium defect really critical? Um defeito de 5 mm em calota craniana de rato é realmente critico?

Directory of Open Access Journals (Sweden)

Gabriela Granja Porto

2012-11-01

Full Text Available PURPOSE: To evaluate bone regeneration in critical defects in the rats' calvarium. METHODS: Eighteen rats Wistar were divided into three groups of six animals each according to the time of evaluation (15, 30 and 60 days. One calvarium defect of 5mm was made in the parietal bone of each animal under general anesthesia. After the time of evaluation, the animals were killed, when the bone was histological studied and classified according to the type of tissue found: fibrosis or bone. RESULTS: The results showed that in the group of 15 days, in five animals there was only fibrosis. In the group of 30 days, the process of regeneration was growing and in four animals was found bone, in three with partial filling and in the other one with complete filling of the defect. In the group of 60 days, out of the three animals with bone, two had a complete filling of the defect. CONCLUSIONS: There was no bone regeneration in critical defects in 15 days. There was regeneration in the most part of the animals in 30 and 60 days.OBJETIVO: Avaliar a regeneração óssea de defeitos críticos em calota craniana de ratos. MÉTODOS: Foram utilizados 18 ratos Wistar que foram distribuídos em três grupos de acordo com o tempo de avaliação (15, 30 e 60 dias. Na calota craniana desses animais foi realizado defeito de 5mm, após anestesia geral prévia. Após o tempo de avaliação, os animais foram submetidos à eutanásia e a calota foi enviada para estudo histológico, quando foi classificada de acordo o tecido encontrado: fibroso ou ósseo. RESULTADOS: Diante dos achados deste estudo, pode-se observar que para o grupo de 15 dias na maioria dos animais, n=5, foi encontrado apenas fibrose. Com o passar do tempo de avaliação, no grupo de 30 dias, o processo de reparo foi evoluindo e em quatro animais já foi encontrado osso, sendo em três com preenchimento parcial e em um completo. No grupo de 60 dias, o processo praticamente permaneceu o mesmo, onde em tr

Size matters. The width and location of a ureteral stone accurately predict the chance of spontaneous passage

Energy Technology Data Exchange (ETDEWEB)

Jendeberg, Johan; Geijer, Haakan; Alshamari, Muhammed; Liden, Mats [Oerebro University Hospital, Department of Radiology, Faculty of Medicine and Health, Oerebro (Sweden); Cierzniak, Bartosz [Oerebro University, Department of Surgery, Faculty of Medicine and Health, Oerebro (Sweden)

2017-11-15

To determine how to most accurately predict the chance of spontaneous passage of a ureteral stone using information in the diagnostic non-enhanced computed tomography (NECT) and to create predictive models with smaller stone size intervals than previously possible. Retrospectively 392 consecutive patients with ureteric stone on NECT were included. Three radiologists independently measured the stone size. Stone location, side, hydronephrosis, CRP, medical expulsion therapy (MET) and all follow-up radiology until stone expulsion or 26 weeks were recorded. Logistic regressions were performed with spontaneous stone passage in 4 weeks and 20 weeks as the dependent variable. The spontaneous passage rate in 20 weeks was 312 out of 392 stones, 98% in 0-2 mm, 98% in 3 mm, 81% in 4 mm, 65% in 5 mm, 33% in 6 mm and 9% in ≥6.5 mm wide stones. The stone size and location predicted spontaneous ureteric stone passage. The side and the grade of hydronephrosis only predicted stone passage in specific subgroups. Spontaneous passage of a ureteral stone can be predicted with high accuracy with the information available in the NECT. We present a prediction method based on stone size and location. (orig.)

Simulation of atmospheric temperature inversions over greater cairo using the MM5 Meso-Scale atmospheric model

International Nuclear Information System (INIS)

Kandil, H.A.; Elhadidi, B.M.; Kader, A. A.; Moaty, A.A.; Sherif, A.O.

2006-01-01

Air pollution episodes have been recorded in Cairo, during the fall season, since 1999, as a result of specific meteorological conditions combined with large quantity of pollutants created by several ground-based sources. The main reason for the smog-like episodes (black clouds) is adverse weather conditions with low and variable winds, high humidity and strong temperature inversions in the few-hundred meters above the ground. The two important types of temperature inversion affecting the air pollution are surface or ground (radiation) inversion and subsidence (elevated) inversion. The surface temperature inversion is associated with a rapid decrease in the ground surface temperature with the simultaneous existence of warm air in the lower troposphere. The inversion develops at dusk and continues until the surface warms again the following day. Pollutants emitted during the night are caught under this i nversion lid. S ubsidence inversion forms when warm air masses move over colder air masses. The inversion develops with a stagnating high-pressure system (generally associated with fair weather). Under these conditions, the pressure gradient becomes progressively weaker so that winds become light. These light winds greatly reduce the horizontal transport and dispersion of pollutants. At the same time, the subsidence inversion acts as a barrier to the vertical dispersion of the pollutants. In this study, the Penn State/NCAR meso -scale model (MM5) is used to simulate the temperature inversion phenomenon over Greater Cairo region during the fall season of 2004. Accurate computations of the heat transfer at the surface are needed to capture this phenomenon. This can only be achieved by high-resolution simulations in both horizontal and vertical directions. Hence, for accurate simulation of the temperature inversion over Greater Cairo, four nested domains of resolutions of 27 km, 9 km, 3 km and 1 km, respectively, were used in the horizontal planes. Furthermore, 42

Improvement of snowpack simulations in a regional climate model

Energy Technology Data Exchange (ETDEWEB)

Jin, J.; Miller, N.L.

2011-01-10

To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth-generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land-surface model. One important cause for the underestimated SWE in Noah is its unrealistic land-surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow-season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near-surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over-predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5 CLM3 due to the lower evaporation resulting from the

Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model

Science.gov (United States)

Diaz-Rodriguez, Sebastian; Bozada, Samantha M.; Phifer, Jeremy R.; Paluch, Andrew S.

2016-11-01

We present blind predictions using the solubility parameter based method MOSCED submitted for the SAMPL5 challenge on calculating cyclohexane/water distribution coefficients at 298 K. Reference data to parameterize MOSCED was generated with knowledge only of chemical structure by performing solvation free energy calculations using electronic structure calculations in the SMD continuum solvent. To maintain simplicity and use only a single method, we approximate the distribution coefficient with the partition coefficient of the neutral species. Over the final SAMPL5 set of 53 compounds, we achieved an average unsigned error of 2.2± 0.2 log units (ranking 15 out of 62 entries), the correlation coefficient ( R) was 0.6± 0.1 (ranking 35), and 72± 6 % of the predictions had the correct sign (ranking 30). While used here to predict cyclohexane/water distribution coefficients at 298 K, MOSCED is broadly applicable, allowing one to predict temperature dependent infinite dilution activity coefficients in any solvent for which parameters exist, and provides a means by which an excess Gibbs free energy model may be parameterized to predict composition dependent phase-equilibrium.

Simulation of Thermal Processes in Metamaterial MM-to-IR Converter for MM-wave Imager

International Nuclear Information System (INIS)

Zagubisalo, Peter S; Paulish, Andrey G; Kuznetsov, Sergey A

2014-01-01

The main characteristics of MM-wave image detector were simulated by means of accurate numerical modelling of thermophysical processes in a metamaterial MM-to-IR converter. The converter represents a multilayer structure consisting of an ultra thin resonant metamaterial absorber and a perfect emissive layer. The absorber consists of a dielectric self-supporting film that is metallized from both sides. A micro-pattern is fabricated from one side. Resonant absorption of the MM waves induces the converter heating that yields enhancement of IR emission from the emissive layer. IR emission is detected by IR camera. In this contribution an accurate numerical model for simulation of the thermal processes in the converter structure was created by using COMSOL Multiphysics software. The simulation results are in a good agreement with experimental results that validates the model. The simulation shows that the real time operation is provided for the converter thickness less than 3 micrometers and time response can be improved by decreasing of the converter thickness. The energy conversion efficiency of MM waves into IR radiation is over 80%. The converter temperature increase is a linear function of a MM-wave radiation power within three orders of the dynamic range. The blooming effect and ways of its reducing are also discussed. The model allows us to choose the ways of converter structure optimization and improvement of image detector parameters

Modeling and numerical simulation of interior ballistic processes in a 120mm mortar system

Science.gov (United States)

Acharya, Ragini

Numerical Simulation of interior ballistic processes in gun and mortar systems is a very difficult and interesting problem. The mathematical model for the physical processes in the mortar systems consists of a system of non-linear coupled partial differential equations, which also contain non-homogeneity in form of the source terms. This work includes the development of a three-dimensional mortar interior ballistic (3D-MIB) code for a 120mm mortar system and its stage-wise validation with multiple sets of experimental data. The 120mm mortar system consists of a flash tube contained within an ignition cartridge, tail-boom, fin region, charge increments containing granular propellants, and a projectile payload. The ignition cartridge discharges hot gas-phase products and unburned granular propellants into the mortar tube through vent-holes on its surface. In view of the complexity of interior ballistic processes in the mortar propulsion system, the overall problem was solved in a modular fashion, i.e., simulating each physical component of the mortar propulsion system separately. These modules were coupled together with appropriate initial and boundary conditions. The ignition cartridge and mortar tube contain nitrocellulose-based ball propellants. Therefore, the gas dynamical processes in the 120mm mortar system are two-phase, which were simulated by considering both phases as an interpenetrating continuum. Mass and energy fluxes from the flash tube into the granular bed of ignition cartridge were determined from a semi-empirical technique. For the tail-boom section, a transient one-dimensional two-phase compressible flow solver based on method of characteristics was developed. The mathematical model for the interior ballistic processes in the mortar tube posed an initial value problem with discontinuous initial conditions with the characteristics of the Riemann problem due to the discontinuity of the initial conditions. Therefore, the mortar tube model was solved

Validation and uncertainty analysis of a pre-treatment 2D dose prediction model

Science.gov (United States)

Baeza, Jose A.; Wolfs, Cecile J. A.; Nijsten, Sebastiaan M. J. J. G.; Verhaegen, Frank

2018-02-01

Independent verification of complex treatment delivery with megavolt photon beam radiotherapy (RT) has been effectively used to detect and prevent errors. This work presents the validation and uncertainty analysis of a model that predicts 2D portal dose images (PDIs) without a patient or phantom in the beam. The prediction model is based on an exponential point dose model with separable primary and secondary photon fluence components. The model includes a scatter kernel, off-axis ratio map, transmission values and penumbra kernels for beam-delimiting components. These parameters were derived through a model fitting procedure supplied with point dose and dose profile measurements of radiation fields. The model was validated against a treatment planning system (TPS; Eclipse) and radiochromic film measurements for complex clinical scenarios, including volumetric modulated arc therapy (VMAT). Confidence limits on fitted model parameters were calculated based on simulated measurements. A sensitivity analysis was performed to evaluate the effect of the parameter uncertainties on the model output. For the maximum uncertainty, the maximum deviating measurement sets were propagated through the fitting procedure and the model. The overall uncertainty was assessed using all simulated measurements. The validation of the prediction model against the TPS and the film showed a good agreement, with on average 90.8% and 90.5% of pixels passing a (2%,2 mm) global gamma analysis respectively, with a low dose threshold of 10%. The maximum and overall uncertainty of the model is dependent on the type of clinical plan used as input. The results can be used to study the robustness of the model. A model for predicting accurate 2D pre-treatment PDIs in complex RT scenarios can be used clinically and its uncertainties can be taken into account.

A Review on Predicting Ground PM2.5 Concentration Using Satellite Aerosol Optical Depth

Directory of Open Access Journals (Sweden)

Yuanyuan Chu

2016-10-01

Full Text Available This study reviewed the prediction of fine particulate matter (PM2.5 from satellite aerosol optical depth (AOD and summarized the advantages and limitations of these predicting models. A total of 116 articles were included from 1436 records retrieved. The number of such studies has been increasing since 2003. Among these studies, four predicting models were widely used: Multiple Linear Regression (MLR (25 articles, Mixed-Effect Model (MEM (23 articles, Chemical Transport Model (CTM (16 articles and Geographically Weighted Regression (GWR (10 articles. We found that there is no so-called best model among them and each has both advantages and limitations. Regarding the prediction accuracy, MEM performs the best, while MLR performs worst. CTM predicts PM2.5 better on a global scale, while GWR tends to perform well on a regional level. Moreover, prediction performance can be significantly improved by combining meteorological variables with land use factors of each region, instead of only considering meteorological variables. In addition, MEM has advantages in dealing with the AOD data with missing values. We recommend that with the help of higher resolution AOD data, future works could be focused on developing satellite-based predicting models for the prediction of historical PM2.5 and other air pollutants.

Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

Science.gov (United States)

Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

2017-01-31

Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

Balancing Model Performance and Simplicity to Predict Postoperative Primary Care Blood Pressure Elevation.

Science.gov (United States)

Schonberger, Robert B; Dai, Feng; Brandt, Cynthia A; Burg, Matthew M

2015-09-01

Because of uncertainty regarding the reliability of perioperative blood pressures and traditional notions downplaying the role of anesthesiologists in longitudinal patient care, there is no consensus for anesthesiologists to recommend postoperative primary care blood pressure follow-up for patients presenting for surgery with an increased blood pressure. The decision of whom to refer should ideally be based on a predictive model that balances performance with ease-of-use. If an acceptable decision rule was developed, a new practice paradigm integrating the surgical encounter into broader public health efforts could be tested, with the goal of reducing long-term morbidity from hypertension among surgical patients. Using national data from US veterans receiving surgical care, we determined the prevalence of poorly controlled outpatient clinic blood pressures ≥140/90 mm Hg, based on the mean of up to 4 readings in the year after surgery. Four increasingly complex logistic regression models were assessed to predict this outcome. The first included the mean of 2 preoperative blood pressure readings; other models progressively added a broad array of demographic and clinical data. After internal validation, the C-statistics and the Net Reclassification Index between the simplest and most complex models were assessed. The performance characteristics of several simple blood pressure referral thresholds were then calculated. Among 215,621 patients, poorly controlled outpatient clinic blood pressure was present postoperatively in 25.7% (95% confidence interval [CI], 25.5%-25.9%) including 14.2% (95% CI, 13.9%-14.6%) of patients lacking a hypertension history. The most complex prediction model demonstrated statistically significant, but clinically marginal, improvement in discrimination over a model based on preoperative blood pressure alone (C-statistic, 0.736 [95% CI, 0.734-0.739] vs 0.721 [95% CI, 0.718-0.723]; P for difference 1 of 4 patients (95% CI, 25.5

5D Modelling: An Efficient Approach for Creating Spatiotemporal Predictive 3D Maps of Large-Scale Cultural Resources

Science.gov (United States)

Doulamis, A.; Doulamis, N.; Ioannidis, C.; Chrysouli, C.; Grammalidis, N.; Dimitropoulos, K.; Potsiou, C.; Stathopoulou, E.-K.; Ioannides, M.

2015-08-01

Outdoor large-scale cultural sites are mostly sensitive to environmental, natural and human made factors, implying an imminent need for a spatio-temporal assessment to identify regions of potential cultural interest (material degradation, structuring, conservation). On the other hand, in Cultural Heritage research quite different actors are involved (archaeologists, curators, conservators, simple users) each of diverse needs. All these statements advocate that a 5D modelling (3D geometry plus time plus levels of details) is ideally required for preservation and assessment of outdoor large scale cultural sites, which is currently implemented as a simple aggregation of 3D digital models at different time and levels of details. The main bottleneck of such an approach is its complexity, making 5D modelling impossible to be validated in real life conditions. In this paper, a cost effective and affordable framework for 5D modelling is proposed based on a spatial-temporal dependent aggregation of 3D digital models, by incorporating a predictive assessment procedure to indicate which regions (surfaces) of an object should be reconstructed at higher levels of details at next time instances and which at lower ones. In this way, dynamic change history maps are created, indicating spatial probabilities of regions needed further 3D modelling at forthcoming instances. Using these maps, predictive assessment can be made, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 5D Digital Cultural Heritage Model (5D-DCHM) is implemented using open interoperable standards based on the CityGML framework, which also allows the description of additional semantic metadata information. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 5D-DCHM geometry and the respective semantic information. The open source 3DCity

Application of XGBoost algorithm in hourly PM2.5 concentration prediction

Science.gov (United States)

Pan, Bingyue

2018-02-01

In view of prediction techniques of hourly PM2.5 concentration in China, this paper applied the XGBoost(Extreme Gradient Boosting) algorithm to predict hourly PM2.5 concentration. The monitoring data of air quality in Tianjin city was analyzed by using XGBoost algorithm. The prediction performance of the XGBoost method is evaluated by comparing observed and predicted PM2.5 concentration using three measures of forecast accuracy. The XGBoost method is also compared with the random forest algorithm, multiple linear regression, decision tree regression and support vector machines for regression models using computational results. The results demonstrate that the XGBoost algorithm outperforms other data mining methods.

Preprocedural Prediction Model for Contrast-Induced Nephropathy Patients.

Science.gov (United States)

Yin, Wen-Jun; Yi, Yi-Hu; Guan, Xiao-Feng; Zhou, Ling-Yun; Wang, Jiang-Lin; Li, Dai-Yang; Zuo, Xiao-Cong

2017-02-03

Several models have been developed for prediction of contrast-induced nephropathy (CIN); however, they only contain patients receiving intra-arterial contrast media for coronary angiographic procedures, which represent a small proportion of all contrast procedures. In addition, most of them evaluate radiological interventional procedure-related variables. So it is necessary for us to develop a model for prediction of CIN before radiological procedures among patients administered contrast media. A total of 8800 patients undergoing contrast administration were randomly assigned in a 4:1 ratio to development and validation data sets. CIN was defined as an increase of 25% and/or 0.5 mg/dL in serum creatinine within 72 hours above the baseline value. Preprocedural clinical variables were used to develop the prediction model from the training data set by the machine learning method of random forest, and 5-fold cross-validation was used to evaluate the prediction accuracies of the model. Finally we tested this model in the validation data set. The incidence of CIN was 13.38%. We built a prediction model with 13 preprocedural variables selected from 83 variables. The model obtained an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.907 and gave prediction accuracy of 80.8%, sensitivity of 82.7%, specificity of 78.8%, and Matthews correlation coefficient of 61.5%. For the first time, 3 new factors are included in the model: the decreased sodium concentration, the INR value, and the preprocedural glucose level. The newly established model shows excellent predictive ability of CIN development and thereby provides preventative measures for CIN. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Predictive sensor based x-ray calibration using a physical model

International Nuclear Information System (INIS)

Fuente, Matias de la; Lutz, Peter; Wirtz, Dieter C.; Radermacher, Klaus

2007-01-01

Many computer assisted surgery systems are based on intraoperative x-ray images. To achieve reliable and accurate results these images have to be calibrated concerning geometric distortions, which can be distinguished between constant distortions and distortions caused by magnetic fields. Instead of using an intraoperative calibration phantom that has to be visible within each image resulting in overlaying markers, the presented approach directly takes advantage of the physical background of the distortions. Based on a computed physical model of an image intensifier and a magnetic field sensor, an online compensation of distortions can be achieved without the need of an intraoperative calibration phantom. The model has to be adapted once to each specific image intensifier through calibration, which is based on an optimization algorithm systematically altering the physical model parameters, until a minimal error is reached. Once calibrated, the model is able to predict the distortions caused by the measured magnetic field vector and build an appropriate dewarping function. The time needed for model calibration is not yet optimized and takes up to 4 h on a 3 GHz CPU. In contrast, the time needed for distortion correction is less than 1 s and therefore absolutely acceptable for intraoperative use. First evaluations showed that by using the model based dewarping algorithm the distortions of an XRII with a 21 cm FOV could be significantly reduced. The model was able to predict and compensate distortions by approximately 80% to a remaining error of 0.45 mm (max) (0.19 mm rms)

A burnout prediction model based around char morphology

Energy Technology Data Exchange (ETDEWEB)

Tao Wu; Edward Lester; Michael Cloke [University of Nottingham, Nottingham (United Kingdom). School of Chemical, Environmental and Mining Engineering

2006-05-15

Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coal particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.

Improved Modeling and Prediction of Surface Wave Amplitudes

Science.gov (United States)

2017-05-31

AFRL-RV-PS- AFRL-RV-PS- TR-2017-0162 TR-2017-0162 IMPROVED MODELING AND PREDICTION OF SURFACE WAVE AMPLITUDES Jeffry L. Stevens, et al. Leidos...data does not license the holder or any other person or corporation; or convey any rights or permission to manufacture, use, or sell any patented...SUBTITLE Improved Modeling and Prediction of Surface Wave Amplitudes 5a. CONTRACT NUMBER FA9453-14-C-0225 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER

Predictions and measurements of residual stress in repair welds in plates

Energy Technology Data Exchange (ETDEWEB)

Brown, T.B. [Mitsui Babcock Energy Limited, Technology and Engineering, Porterfield Road, Renfrew, PA4 8DJ, Scotland (United Kingdom)]. E-mail: bbrown@mitsuibabcock.com; Dauda, T.A. [Mitsui Babcock Energy Limited, Technology and Engineering, Porterfield Road, Renfrew, PA4 8DJ, Scotland (United Kingdom); Truman, C.E. [Department of Mechanical Engineering, University of Bristol, Bristol BS8 1TR, England (United Kingdom); Smith, D.J. [Department of Mechanical Engineering, University of Bristol, Bristol BS8 1TR (United Kingdom); Memhard, D. [Fraunhofer-Institut fuer Werkstoffmechanik, Freiburg (Germany); Pfeiffer, W. [Fraunhofer-Institut fuer Werkstoffmechanik, Freiburg (Germany)

2006-11-15

This paper presents the work, from the European Union FP-5 project ELIXIR, on a series of rectangular repair welds in P275 and S690 steels to validate the numerical modelling techniques used in the determination of the residual stresses generated during the repair process. The plates were 1,000 mm by 800 mm with thicknesses of 50 and 100 mm. The repair welds were 50%, 75% and 100% through the plate thickness. The repair welds were modelled using the finite element method to make predictions of the as-welded residual stress distributions. These predictions were compared with surface-strain measurements made on the parent plates during welding and found to be in good agreement. Through-thickness residual stress measurements were obtained from the test plates through, and local to, the weld repairs using the deep hole drilling technique. Comparisons between the measurements and the finite element predictions generally showed good agreement, thus providing confidence in the method.

Predictions and measurements of residual stress in repair welds in plates

International Nuclear Information System (INIS)

Brown, T.B.; Dauda, T.A.; Truman, C.E.; Smith, D.J.; Memhard, D.; Pfeiffer, W.

2006-01-01

This paper presents the work, from the European Union FP-5 project ELIXIR, on a series of rectangular repair welds in P275 and S690 steels to validate the numerical modelling techniques used in the determination of the residual stresses generated during the repair process. The plates were 1,000 mm by 800 mm with thicknesses of 50 and 100 mm. The repair welds were 50%, 75% and 100% through the plate thickness. The repair welds were modelled using the finite element method to make predictions of the as-welded residual stress distributions. These predictions were compared with surface-strain measurements made on the parent plates during welding and found to be in good agreement. Through-thickness residual stress measurements were obtained from the test plates through, and local to, the weld repairs using the deep hole drilling technique. Comparisons between the measurements and the finite element predictions generally showed good agreement, thus providing confidence in the method

3-D dosimetric evaluation of 2.5 mm HD120 multileaf system for intensity modulated stereotactic radiosurgery using optical CT based polymer gel dosimetry

International Nuclear Information System (INIS)

Wuu, C-S; Kessel, Jack; Xu, Y

2009-01-01

A Trilogy TX equipped with a 2.5 mm HD120 multileaf collimator system is available for the treatment of radiosurgery and IMRT. In this study, we evaluated the 3-D dosimetric impact of leaf width on an IMRT radiosurgery plan by comparing the target coverage and the dose gradient around the target, produced from both a 2.5 mm HD120 high-definition MLC system and a 5mm-leaf-width millennium 120 MLC system, using an optical CT based polymer gel dosimetry system. The 2.5 mm MLC improves target conformity and surrounding tissue sparing when compared to that of 5 mm MLC.

Developing and validating a new precise risk-prediction model for new-onset hypertension: The Jichi Genki hypertension prediction model (JG model).

Science.gov (United States)

Kanegae, Hiroshi; Oikawa, Takamitsu; Suzuki, Kenji; Okawara, Yukie; Kario, Kazuomi

2018-03-31

No integrated risk assessment tools that include lifestyle factors and uric acid have been developed. In accordance with the Industrial Safety and Health Law in Japan, a follow-up examination of 63 495 normotensive individuals (mean age 42.8 years) who underwent a health checkup in 2010 was conducted every year for 5 years. The primary endpoint was new-onset hypertension (systolic blood pressure [SBP]/diastolic blood pressure [DBP] ≥ 140/90 mm Hg and/or the initiation of antihypertensive medications with self-reported hypertension). During the mean 3.4 years of follow-up, 7402 participants (11.7%) developed hypertension. The prediction model included age, sex, body mass index (BMI), SBP, DBP, low-density lipoprotein cholesterol, uric acid, proteinuria, current smoking, alcohol intake, eating rate, DBP by age, and BMI by age at baseline and was created by using Cox proportional hazards models to calculate 3-year absolute risks. The derivation analysis confirmed that the model performed well both with respect to discrimination and calibration (n = 63 495; C-statistic = 0.885, 95% confidence interval [CI], 0.865-0.903; χ 2 statistic = 13.6, degree of freedom [df] = 7). In the external validation analysis, moreover, the model performed well both in its discrimination and calibration characteristics (n = 14 168; C-statistic = 0.846; 95%CI, 0.775-0.905; χ 2 statistic = 8.7, df = 7). Adding LDL cholesterol, uric acid, proteinuria, alcohol intake, eating rate, and BMI by age to the base model yielded a significantly higher C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement, especially NRI non-event (NRI = 0.127, 95%CI = 0.100-0.152; NRI non-event  = 0.108, 95%CI = 0.102-0.117). In conclusion, a highly precise model with good performance was developed for predicting incident hypertension using the new parameters of eating rate, uric acid, proteinuria, and BMI by age. ©2018 Wiley Periodicals, Inc.

Passive Stretch Induces Structural and Functional Maturation of Engineered Heart Muscle as Predicted by Computational Modeling.

Science.gov (United States)

Abilez, Oscar J; Tzatzalos, Evangeline; Yang, Huaxiao; Zhao, Ming-Tao; Jung, Gwanghyun; Zöllner, Alexander M; Tiburcy, Malte; Riegler, Johannes; Matsa, Elena; Shukla, Praveen; Zhuge, Yan; Chour, Tony; Chen, Vincent C; Burridge, Paul W; Karakikes, Ioannis; Kuhl, Ellen; Bernstein, Daniel; Couture, Larry A; Gold, Joseph D; Zimmermann, Wolfram H; Wu, Joseph C

2018-02-01

The ability to differentiate human pluripotent stem cells (hPSCs) into cardiomyocytes (CMs) makes them an attractive source for repairing injured myocardium, disease modeling, and drug testing. Although current differentiation protocols yield hPSC-CMs to >90% efficiency, hPSC-CMs exhibit immature characteristics. With the goal of overcoming this limitation, we tested the effects of varying passive stretch on engineered heart muscle (EHM) structural and functional maturation, guided by computational modeling. Human embryonic stem cells (hESCs, H7 line) or human induced pluripotent stem cells (IMR-90 line) were differentiated to hPSC-derived cardiomyocytes (hPSC-CMs) in vitro using a small molecule based protocol. hPSC-CMs were characterized by troponin + flow cytometry as well as electrophysiological measurements. Afterwards, 1.2 × 10 6 hPSC-CMs were mixed with 0.4 × 10 6 human fibroblasts (IMR-90 line) (3:1 ratio) and type-I collagen. The blend was cast into custom-made 12-mm long polydimethylsiloxane reservoirs to vary nominal passive stretch of EHMs to 5, 7, or 9 mm. EHM characteristics were monitored for up to 50 days, with EHMs having a passive stretch of 7 mm giving the most consistent formation. Based on our initial macroscopic observations of EHM formation, we created a computational model that predicts the stress distribution throughout EHMs, which is a function of cellular composition, cellular ratio, and geometry. Based on this predictive modeling, we show cell alignment by immunohistochemistry and coordinated calcium waves by calcium imaging. Furthermore, coordinated calcium waves and mechanical contractions were apparent throughout entire EHMs. The stiffness and active forces of hPSC-derived EHMs are comparable with rat neonatal cardiomyocyte-derived EHMs. Three-dimensional EHMs display increased expression of mature cardiomyocyte genes including sarcomeric protein troponin-T, calcium and potassium ion channels, β-adrenergic receptors, and t

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

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Jenessa Lancaster

2018-02-01

Full Text Available Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years we trained support vector machines to (i distinguish between young (<22 years and old (>50 years brains (classification and (ii predict chronological age (regression. We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years. Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm. For predicting chronological age, a mean absolute error (MAE of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm. This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian

Bootstrap prediction and Bayesian prediction under misspecified models

OpenAIRE

Fushiki, Tadayoshi

2005-01-01

We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

Predictable topography simulation of SiO2 etching by C5F8 gas combined with a plasma simulation, sheath model and chemical reaction model

International Nuclear Information System (INIS)

Takagi, S; Onoue, S; Iyanagi, K; Nishitani, K; Shinmura, T; Kanoh, M; Itoh, H; Shioyama, Y; Akiyama, T; Kishigami, D

2003-01-01

We have developed a simulation for predicting reactive ion etching (RIE) topography, which is a combination of plasma simulation, the gas reaction model, the sheath model and the surface reaction model. The simulation is applied to the SiO 2 etching process of a high-aspect-ratio contact hole using C 5 F 8 gas. A capacitively coupled plasma (CCP) reactor of an 8-in. wafer was used in the etching experiments. The baseline conditions are RF power of 1500 W and gas pressure of 4.0 Pa in a gas mixture of Ar, O 2 and C 5 F 8 . The plasma simulation reproduces the tendency that CF 2 radical density increases rapidly and the electron density decreases gradually with increasing gas flow rate of C 5 F 8 . In the RIE topography simulation, the etching profiles such as bowing and taper shape at the bottom are reproduced in deep holes with aspect ratios greater than 19. Moreover, the etching profile, the dependence of the etch depth on the etching time, and the bottom diameter can be predicted by this simulation

An improved model to predict nonuniform deformation of Zr-2.5 Nb pressure tubes

International Nuclear Information System (INIS)

Lei, Q.M.; Fan, H.Z.

1997-01-01

Present circular pressure-tube ballooning models in most fuel channel codes assume that the pressure tube remains circular during ballooning. This model provides adequate predictions of pressure-tube ballooning behaviour when the pressure tube (PT) and the calandria tube (CT) are concentric and when a small (<100 degrees C) top-to-bottom circumferential temperature gradient is present on the pressure tube. However, nonconcentric ballooning is expected to occur under certain postulated CANDU (CANada Deuterium Uranium) accident conditions. This circular geometry assumption prevents the model from accurately predicting nonuniform pressure-tube straining and local PT/CT contact when the pressure tube is subjected to a large circumferential temperature gradient and consequently deforms in a noncircular pattern. This paper describes an improved model that predicts noncircular pressure-tube deformation. Use of this model (once fully validated) will reduce uncertainties in the prediction of pressure-tube ballooning during a postulated loss-of-coolant accident (LOCA) in a CANDU reactor. The noncircular deformation model considers a ring or cross-section of a pressure tube with unit axial length to calculate deformation in the radial and circumferential directions. The model keeps track of the thinning of the pressure-tube wall as well as the shape deviation from a reference circle. Such deviation is expressed in a cosine Fourier series for the lateral symmetry case. The coefficients of the series for the first m terms are calculated by solving a set of algebraic equations at each time step. The model also takes into account the effects of pressure-tube sag or bow on ballooning, using an input value of the offset distance between the centre of the calandria tube and the initial centre of the pressure tube for determining the position radius of the pressure tube. One significant improvement realized in using the noncircular deformation model is a more accurate prediction in

Persistent pulmonary subsolid nodules with solid portions of 5 mm or smaller: Their natural course and predictors of interval growth

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Hyuk [Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Department of Radiology, Seoul (Korea, Republic of); Park, Chang Min [Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Department of Radiology, Seoul (Korea, Republic of); Seoul National University, Cancer Research Institute, Seoul (Korea, Republic of); Duke University Medical Center, Department of Radiology, Durham, NC (United States); Lee, Sang Min [University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology, Seoul (Korea, Republic of); Kim, Hyungjin [Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Department of Radiology, Seoul (Korea, Republic of); Air Force Education and Training Command, Aerospace Medical Group, Jinju (Korea, Republic of); McAdams, H.P. [Duke University Medical Center, Department of Radiology, Durham, NC (United States); Goo, Jin Mo [Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Department of Radiology, Seoul (Korea, Republic of); Seoul National University, Cancer Research Institute, Seoul (Korea, Republic of)

2016-06-15

To investigate the natural course of persistent pulmonary subsolid nodules (SSNs) with solid portions ≤5 mm and the clinico-radiological features that influence interval growth over follow-ups. From 2005 to 2013, the natural courses of 213 persistent SSNs in 213 patients were evaluated. To identify significant predictors of interval growth, Kaplan-Meier analysis and Cox proportional hazard regression analysis were performed. Among the 213 nodules, 136 were pure ground-glass nodules (GGNs; growth, 18; stable, 118) and 77 were part-solid GGNs with solid portions ≤5 mm (growth, 24; stable, 53). For all SSNs, lung cancer history (p = 0.001), part-solid GGNs (p < 0.001), and nodule diameter (p < 0.001) were significant predictors for interval growth. On subgroup analysis, nodule diameter was an independent predictor for the interval growth of both pure GGNs (p < 0.001), and part-solid GGNs (p = 0.037). For part-solid GGNs, lung cancer history (p = 0.002) was another significant predictor of the interval growth. Interval growth of pure GGNs ≥10 mm and part-solid GGNs ≥8 mm were significantly more frequent than in pure GGNs <10 mm (p < 0.001) and part-solid GGNs <8 mm (p = 0.003), respectively. The natural course of SSNs with solid portions ≤5 mm differed significantly according to their nodule type and nodule diameters, with which their management can be subdivided. (orig.)

Predicting problematic alcohol use with the DSM-5 alternative model of personality pathology.

Science.gov (United States)

Creswell, Kasey G; Bachrach, Rachel L; Wright, Aidan G C; Pinto, Anthony; Ansell, Emily

2016-01-01

High comorbidity between personality disorders and alcohol use disorders appears related to individual differences in underlying personality dimensions of behavioral undercontrol and affective dysregulation. However, very little is known about how the Diagnostic and Statistical Manual of Mental Disorders (5th edition; DSM-5) Section III trait model of personality pathology relates to alcohol problems or how the strength of the relationship between personality pathology and alcohol problems changes with age and across gender. The current study examined these questions in a sample of 877 participants using the General Assessment of Personality Disorder to assess general personality dysfunction, the Personality Inventory for DSM-5 to measure specific traits, and the Alcohol Use Disorder Identification Test (AUDIT) to assess problematic alcohol use. Results demonstrated that general personality pathology (Criterion A) was significantly related to problematic alcohol use after controlling for age and gender effects. Furthermore, 2 of the 5 higher-order personality trait domains (Criterion B), Antagonism and Disinhibition, remained significant predictors of problematic alcohol use after accounting for the influence of general personality pathology; however, general personality pathology no longer predicted hazardous alcohol use once Antagonism and Disinhibition were added into the model. Finally, these 2 specific traits interacted with age, such that Antagonism was a stronger predictor of AUDIT scores among older individuals and Disinhibition was a stronger predictor of alcohol problems among younger individuals. Findings support the general validity of this new personality disorder diagnostic system and suggest important age effects in the relationship between traits and problematic alcohol use. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Predictive ability of severe rainfall events over Catalonia for the year 2008

Science.gov (United States)

Comellas, A.; Molini, L.; Parodi, A.; Sairouni, A.; Llasat, M. C.; Siccardi, F.

2011-07-01

This paper analyses the predictive ability of quantitative precipitation forecasts (QPF) and the so-called "poor-man" rainfall probabilistic forecasts (RPF). With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC) for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain), managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9-10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF) issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h) MM5 tends to overestimate total precipitation, whereas for short events (≤24 h) the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale. Throughout this study, we have only dealt with (SMC-issued) warning episodes in order to analyse deterministic (MM5 and COSMO-I7) and probabilistic (SMC

Hybrid Single-Incision Laparoscopic Colon Cancer Surgery Using One Additional 5 mm Trocar.

Science.gov (United States)

Kim, Hyung Ook; Choi, Dae Jin; Lee, Donghyoun; Lee, Sung Ryol; Jung, Kyung Uk; Kim, Hungdai; Chun, Ho-Kyung

2018-02-01

Single-incision laparoscopic surgery (SILS) is a feasible and safe procedure for colorectal cancer. However, SILS has some technical limitations such as collision between instruments and inadequate countertraction. We present a hybrid single-incision laparoscopic surgery (hybrid SILS) technique for colon cancer that involves use of one additional 5 mm trocar. Hybrid SILS for colon cancer was attempted in 70 consecutive patients by a single surgeon between August 2014 and July 2016 at Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine. Using prospectively collected data, an observational study was performed on an intention-to-treat basis. Hybrid SILS was technically completed in 66 patients, with a failure rate of 5.7% (4/70). One patient was converted to open surgery for para-aortic lymph node dissection. Another was converted to open surgery due to severe peritoneal adhesion. An additional trocar was inserted for adhesiolysis in the other two cases. Median lengths of proximal and distal margins were 12.8 cm (interquartile range [IQR], 10.0-18.6), and 8.2 cm (IQR, 5.5-18.3), respectively. Median total number of lymph nodes harvested was 24 (IQR, 18-33). Overall rate of postoperative morbidity was 12.9%, but there were no Clavien-Dindo grade III or IV complications. There was no postoperative mortality or reoperation. Median postoperative hospital stay was 6 days (IQR, 5-7). Hybrid SILS using one additional 5 mm trocar is a safe and effective minimally invasive surgical technique for colon cancer. Experienced laparoscopic surgeons can perform hybrid SILS without a learning curve based on the formulaic surgical techniques presented in this article.

Scanning slit for HIE-ISOLDE: vibrational test (linear motion actuator from UHV design, speed = 2.5 mm/s)

CERN Document Server

Bravin, E; Sosa, A

2014-01-01

This report summarizes the results of a series of tests performed on the prototype HIE-ISOLDE diagnostic box (HIE-DB) regarding the vibrations and drifts in the transverse position of the scanning blade while moving inside or outside the box. To monitor the transverse position of the blade, a series of 0.1 mm diameter holes were drilled on it and their positions were tracked with an optical system. The linear motion actuator was acquired from UHV design (model LSM38-150-SS), is driven by a stepper motor and has all the guiding mechanisms outside vacuum. The maximum speed of the scanning blade during the tests was 2.5 mm/s. The transverse movement of the slit in the direction perpendicular to the movement was lower than 50 m, and is dominated by the displacement of the contact point of the applied force on the lead-screw. An offset on the slit position was observed while changing the direction of movement of the blade, its amplitude being of the order of 30 m. The amplitudes of the displacements of the transve...

Survival prediction model for postoperative hepatocellular carcinoma patients.

Science.gov (United States)

Ren, Zhihui; He, Shasha; Fan, Xiaotang; He, Fangping; Sang, Wei; Bao, Yongxing; Ren, Weixin; Zhao, Jinming; Ji, Xuewen; Wen, Hao

2017-09-01

This study is to establish a predictive index (PI) model of 5-year survival rate for patients with hepatocellular carcinoma (HCC) after radical resection and to evaluate its prediction sensitivity, specificity, and accuracy.Patients underwent HCC surgical resection were enrolled and randomly divided into prediction model group (101 patients) and model evaluation group (100 patients). Cox regression model was used for univariate and multivariate survival analysis. A PI model was established based on multivariate analysis and receiver operating characteristic (ROC) curve was drawn accordingly. The area under ROC (AUROC) and PI cutoff value was identified.Multiple Cox regression analysis of prediction model group showed that neutrophil to lymphocyte ratio, histological grade, microvascular invasion, positive resection margin, number of tumor, and postoperative transcatheter arterial chemoembolization treatment were the independent predictors for the 5-year survival rate for HCC patients. The model was PI = 0.377 × NLR + 0.554 × HG + 0.927 × PRM + 0.778 × MVI + 0.740 × NT - 0.831 × transcatheter arterial chemoembolization (TACE). In the prediction model group, AUROC was 0.832 and the PI cutoff value was 3.38. The sensitivity, specificity, and accuracy were 78.0%, 80%, and 79.2%, respectively. In model evaluation group, AUROC was 0.822, and the PI cutoff value was well corresponded to the prediction model group with sensitivity, specificity, and accuracy of 85.0%, 83.3%, and 84.0%, respectively.The PI model can quantify the mortality risk of hepatitis B related HCC with high sensitivity, specificity, and accuracy.

Perbedaan hasil belajar fisika siswa antara model pembelajaran Problem Based Learning (PBL dengan model pembelajaran Prediction, Observation, and Explanation (POE di kelas X SMA Negeri 5 Lubuklinggau

Directory of Open Access Journals (Sweden)

Tri Ariani

2016-11-01

Full Text Available Penelitian ini bertujuan untuk mengetahui Perbedaan Hasil Belajar Fisika Siswa antara Model Pembelajaran Problem Based Learning (PBL dengan Model Pembelajaran Prediction, Observation, And Explanation (POE di Kelas X SMA Negeri 5 Lubuklinggau Tahun Pelajaran 2015/2016. Jenis penelitian ini adalah penelitian kuantitatif dengan metode penelitian eksperimen semu yang dilaksanakan dengan membandingkan kelompok eksperimen I dan kelompok eksperimen II desain penelitian  ini pre-test post-test group design. Populasi penelitian ini adalah seluruh siswa kelas X SMA Negeri 5 Lubuklinggau Tahun Pelajaran 2015/2016, yang terdiri dari 314 siswa dari 9 kelas. Pengambilan sampel dilakukan secara acak (Simple Random Sampling dengan cara pengundian nomor kelas populasi. Pengumpulan data berupa tes, data tes yang sudah dianalisis dengan uji-t, pada taraf  a= 0,05, diperoleh thitung > ttabel (2,17 > 2,00. Rata-rata akhir hasil belajar fisika kelas eksperimen I sebesar 73,4 sedangkan pada kelas kelas eksperimen II  sebesar 69,14. Sehingga dapat disimpulkan ada Perbedaan Hasil Belajar Fisika Siswa antara Model Pembelajaran Problem Based Learning (PBL Dengan Model Pembelajaran Prediction, Observation, And Explanation (POE Di Kelas X SMA Negeri 5 Lubuklinggau Tahun Pelajaran 2015/2016. The aim of this research was to find out the Comparative Results Between Students Studying Physics Learning Model Problem Based Learning (PBL with Learning Model Prediction, Observation, And Explanation (POE in the Class X SMAN 5 Lubuklinggau 2015/2016 Academic Year . This research was a quantitative research methods of experimental research conducted by comparing the experimental group I and group II experimental research design was a pre-test post-test group design. As the population in this research were all students of class X SMA Negeri 5 Lubuklinggau Academic Year 2015/2016, consisting of 314 students from the ninth grade. Sampling is done randomly (Simple Random Sampling by

Avaliação de modelos de predição da energia metabolizável do milho para suínos Evaluating models to predict the metabolizable energy of maize for swine

Directory of Open Access Journals (Sweden)

R.N. Pelizzeri

2013-04-01

Full Text Available Os objetivos propostos no presente trabalho foram a validação da predição de modelos de regressão linear de 1º grau, dos valores estimados de energia metabolizável (EM em função dos valores observados de EM do milho, obtidos em ensaios biológicos com suínos. Setenta e quatro registros de composição química e energética do milho foram obtidos na literatura e utilizados para estimar a EM de 41 modelos de predição em função da composição química. A significância dos parâmetros (β0 e β1 da regressão foi avaliada pelo teste t parcial, e a validação da predição dos modelos de 1º grau foi obtida pela aceitação da hipótese de nulidade conjunta β0=0 e β1=1. Os modelos EM7 = 1,099 + 0,740EB - 5,5MM - 3,7FDN; EM9 = 16,13 - 9,5FDN + 16EE + 23PB*FDN - 138MM*FDN e EM13 = 5,42 - 17,2FDN - 19,4MM + 0,709EB são os mais adequados para estimar os valores de EM do milho e podem ser utilizados como ferramenta para formulação de rações para suínos.The proposed objective of this study was to validate the prediction of linear regression models of the first degree, the estimated values of metabolizable energy (ME regarding the observed ME values of maize obtained in biological assays with swine. Seventy four records of chemical and energetic composition of maize were obtained from literature and used to estimate the ME of 41 prediction models depending on the chemical composition. The significance of the regression parameters (β0and β1was evaluated by partial t test and the prediction validation of first degree models was obtained by accepting the null hypothesis β0=0 and β1=1. The ME7= 1.099 + 0.740GE - 5.5MM - 3.7NDF; ME9= 16.13 - 9.5NDF + 16EE + 23CP*NDF - 138MM* NDF and ME13= 5.42 - 17.2 NDF - 19.4MM + 0.709GE models are the most adequate to estimate the metabolizable energy of maize and can be used as a tool to formulate diets for swine.

Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy

International Nuclear Information System (INIS)

Shiraishi, Satomi; Moore, Kevin L.

2016-01-01

Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrix and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D clin − D pred . The mean (〈δD r 〉), standard deviation (σ δD r ), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r PTV ) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r PTV ∈ [ − 6, 30] mm. The average prediction error was less

MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

Science.gov (United States)

Son, S. W.; Lim, Y.; Kim, D.

2017-12-01

The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

OpenAIRE

David Ebert

2006-01-01

One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

Evaluation of two MM5-PBL parameterization for solar radiation and temperature estimation in the South-Eastern area of the Iberian Peninsula

International Nuclear Information System (INIS)

Ruiz-Arias, J.A.; Pozo-Vasquez, D.; Sanchez-Sanchez, N.; Hayas-Barru, A.; Tovar-Pescador, J.; Montavez, J.P.

2008-01-01

We study the relative performance of two different MM5-PBL parametrizations (Blackadar and MRF) simulating hourly values of solar irradiance and temperature in the south-eastern part of the Iberian Peninsula. The evaluation was carried out throughout the different season of the year 2005 and for three different sky conditions: clear-sky, broken-clouds and overcast conditions. Two integrations, one per PBL parameterization, were carried out for every sky condition and season of the year and results were compared with observational data. Overall, the MM5 model, both using the Blackadar or MRF PBL parameterization, revealed to be a valid tool to estimate hourly values of solar radiation and temperature over the study area. The influence of the PBL parameterization on the model estimates was found to be more important for the solar radiation than for the temperature and highly dependent on the season and sky conditions. Particularly, a detailed analysis revealed that, during broken-clouds conditions, the ability of the model to reproduce hourly changes in the solar radiation strongly depends upon the selected PBL parameterization. Additionally, it was found that solar radiation RMSE values are about one order of magnitude higher during broken-clouds and overcast conditions compared to clear-sky conditions. For the temperature, the two PBL parameterizations provide very similar estimates. Only under overcast conditions and during the autumn, the MRF provides significantly better estimates.

Microhardness of light- and dual-polymerizable luting resins polymerized through 7.5-mm-thick endocrowns.

Science.gov (United States)

Gregor, Ladislav; Bouillaguet, Serge; Onisor, Ioana; Ardu, Stefano; Krejci, Ivo; Rocca, Giovanni Tommaso

2014-10-01

The complete polymerization of luting resins through thick indirect restorations is still questioned. The purpose of this study was to evaluate the degree of polymerization of light- and dual-polymerizable luting resins under thick indirect composite resin and ceramic endocrowns by means of Vickers microhardness measurements. The Vickers microhardness measurements of a light-polymerizable microhybrid composite resin and a dual-polymerizable luting cement directly polymerized in a natural tooth mold for 40 seconds with a high-power light-emitting diode lamp (control) were compared with measurements after indirect irradiation through 7.5-mm-thick composite resin and ceramic endocrowns for 3 × 90 seconds. A test-to-control microhardness values ratio of 0.80 at a depth of 0.5 mm below the surface was assumed as the criterion for adequate conversion. For the Vickers microhardness measurements of a dual-polymerizable luting cement, no differences (P>.05) were found between Vickers microhardness control values and values reported after polymerization through composite resin and ceramic endocrowns. For The Vickers microhardness measurements (±SD) of a light-polymerizable microhybrid composite resin, control values were significantly (P.05). Under the conditions of this in vitro study, Vickers microhardness values of the dual-polymerizable resin cement and the light-polymerizable restorative composite resin irradiated for 3 × 90 seconds with a high irradiance light-emitting diode lamp through 7.5-mm-thick endocrowns reached at least 80% of the control Vickers microhardness values, which means that both materials can be adequately polymerized when they are used for luting thick indirect restorations. Copyright © 2014 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Decadal Prediction Skill in the GEOS-5 Forecast System

Science.gov (United States)

Ham, Yoo-Geun; Rienecker, Michele M.; Suarez, Max J.; Vikhliaev, Yury; Zhao, Bin; Marshak, Jelena; Vernieres, Guillaume; Schubert, Siegfried D.

2013-01-01

A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office's (GMAO's) GEOS-5 Atmosphere-Ocean general circulation model. The hind casts are initialized every December 1st from 1959 to 2010, following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multivariate ensemble optimal interpolation ocean and sea-ice reanalysis, and from GMAO's atmospheric reanalysis, the modern-era retrospective analysis for research and applications. The mean forecast skill of a three-member-ensemble is compared to that of an experiment without initialization but also forced with observed greenhouse gases. The results show that initialization increases the forecast skill of North Atlantic sea surface temperature compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. On the other hand, the initialization reduces the skill in predicting the warming trend over some regions outside the Atlantic. The annual-mean Atlantic meridional overturning circulation index, which is defined here as the maximum of the zonally-integrated overturning stream function at mid-latitude, is predictable up to a 4-year lead time, consistent with the predictable signal in upper ocean heat content over the North Atlantic. While the 6- to 9-year forecast skill measured by mean squared skill score shows 50 percent improvement in the upper ocean heat content over the subtropical and mid-latitude Atlantic, prediction skill is relatively low in the sub-polar gyre. This low skill is due in part to features in the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region that differ from observations. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.

Finding Furfural Hydrogenation Catalysts via Predictive Modelling.

Science.gov (United States)

Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

2010-09-10

We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (k(H):k(D)=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R(2)=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model's predictions, demonstrating the validity and value of predictive modelling in catalyst optimization.

Systematic review and meta-analysis of randomized controlled trials for the management of limited vertical height in the posterior region: short implants (5 to 8 mm) vs longer implants (> 8 mm) in vertically augmented sites.

Science.gov (United States)

Lee, Sung-Ah; Lee, Chun-Teh; Fu, Martin M; Elmisalati, Waiel; Chuang, Sung-Kiang

2014-01-01

The aim of this study was to undertake a systematic review with meta-analysis on randomized controlled trials (RCTs) to compare the rates of survival, success, and complications of short implants to those of longer implants in the posterior regions. Electronic literature searches were conducted through the MEDLINE (PubMed) and EMBASE databases to locate all relevant articles published between January 1, 1990, and April 30, 2013. Eligible studies were selected based on inclusion criteria, and quality assessments were conducted. After data extraction, meta-analyses were performed. In total, 539 dental implants (265 short implants [length 5 to 8 mm] and 274 control implants [length > 8 mm]) from four RCTs were included. The fixed prostheses of multiple short and control implants were all splinted. The mean follow-up period was 2.1 years. The 1-year and 5-year cumulative survival rates (CSR) were 98.7% (95% confidence interval [CI], 97.8% to 99.5%) and 93.6% (95% CI, 89.8% to 97.5%), respectively, for the short implant group and 98.0% (95% CI, 96.9% to 99.1%) and 90.3% (95% CI, 85.2% to 95.4%), respectively, for the control implant group. The CSRs of the two groups did not demonstrate a statistically significant difference. There were also no statistically significant differences in success rates, failure rates, or complications between the two groups. Placement of short dental implants could be a predictable alternative to longer implants to reduce surgical complications and patient morbidity in situations where vertical augmentation procedures are needed. However, only four studies with potential risk of bias were selected in this meta-analysis. Within the limitations of this meta-analysis, these results should be confirmed with robust methodology and RCTs with longer follow-up duration.

Wind field near complex terrain using numerical weather prediction model

Science.gov (United States)

Chim, Kin-Sang

The PennState/NCAR MM5 model was modified to simulate an idealized flow pass through a 3D obstacle in the Micro- Alpha Scale domain. The obstacle used were the idealized Gaussian obstacle and the real topography of Lantau Island of Hong Kong. The Froude number under study is ranged from 0.22 to 1.5. Regime diagrams for both the idealized Gaussian obstacle and Lantau island were constructed. This work is divided into five parts. The first part is the problem definition and the literature review of the related publications. The second part briefly discuss as the PennState/NCAR MM5 model and a case study of long- range transport is included. The third part is devoted to the modification and the verification of the PennState/NCAR MM5 model on the Micro-Alpha Scale domain. The implementation of the Orlanski (1976) open boundary condition is included with the method of single sounding initialization of the model. Moreover, an upper dissipative layer, Klemp and Lilly (1978), is implemented on the model. The simulated result is verified by the Automatic Weather Station (AWS) data and the Wind Profiler data. Four different types of Planetary Boundary Layer (PBL) parameterization schemes have been investigated in order to find out the most suitable one for Micro-Alpha Scale domain in terms of both accuracy and efficiency. Bulk Aerodynamic type of PBL parameterization scheme is found to be the most suitable PBL parameterization scheme. Investigation of the free- slip lower boundary condition is performed and the simulated result is compared with that with friction. The fourth part is the use of the modified PennState/NCAR MM5 model for an idealized flow simulation. The idealized uniform flow used is nonhydrostatic and has constant Froude number. Sensitivity test is performed by varying the Froude number and the regime diagram is constructed. Moreover, nondimensional drag is found to be useful for regime identification. The model result is also compared with the analytic

Assessment of Arctic and Antarctic sea ice predictability in CMIP5 decadal hindcasts

Directory of Open Access Journals (Sweden)

C.-Y. Yang

2016-10-01

Full Text Available This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5 models. Decadal hindcasts exhibit a large multi-model spread in the simulated sea ice extent, with some models deviating significantly from the observations as the predicted ice extent quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3–7 years, but there is a re-emerging predictive skill in the North Atlantic at a lead time of 6–8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.

Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth.

Science.gov (United States)

Zhang, Xueying; Chu, Yiyi; Wang, Yuxuan; Zhang, Kai

2018-08-01

The regulatory monitoring data of particulate matter with an aerodynamic diameter images retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. We then developed mixed-effects models based on AODs, land use features, geographic characteristics, and weather conditions, and the day-specific as well as site-specific random effects to estimate the PM 2.5 concentrations (μg/m 3 ) in the state of Texas during the period 2008-2013. The mixed-effects models' performance was evaluated using the coefficient of determination (R 2 ) and square root of the mean squared prediction error (RMSPE) from ten-fold cross-validation, which randomly selected 90% of the observations for training purpose and 10% of the observations for assessing the models' true prediction ability. Mixed-effects regression models showed good prediction performance (R 2 values from 10-fold cross validation: 0.63-0.69). The model performance varied by regions and study years, and the East region of Texas, and year of 2009 presented relatively higher prediction precision (R 2 : 0.62 for the East region; R 2 : 0.69 for the year of 2009). The PM 2.5 concentrations generated through our developed models at 1-km grid cells in the state of Texas showed a decreasing trend from 2008 to 2013 and a higher reduction of predicted PM 2.5 in more polluted areas. Our findings suggest that mixed-effects regression models developed based on MAIAC AOD are a feasible approach to predict ground-level PM 2.5 in Texas. Predicted PM 2.5 concentrations at the 1-km resolution on a daily basis can be used for epidemiological studies to investigate short- and long-term health impact of PM 2.5 in Texas. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study.

Science.gov (United States)

King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin

2011-01-01

Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study.

Directory of Open Access Journals (Sweden)

Michael King

Full Text Available Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL for the development of hazardous drinking in safe drinkers.A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women.69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873. The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51. External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846 and Hedge's g of 0.68 (95% CI 0.57, 0.78.The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

A comparative study of shadow shield whole body monitor incorporated with 203 mm dia. x 102 mm thick and 102 mm dia. x 76 mm thick NaI(TI) detectors

International Nuclear Information System (INIS)

Sankhla, Rajesh; Singh, I.S.; Rao, D.D.

2016-01-01

The whole body counting using Shadow Shield Whole Body Monitor (SSWBM) proved to be a popular method for assessment of internal contamination due to high energy gamma (E>200 keV) emitting radio nuclides that got inadvertently incorporated in the occupational workers. Currently ∼ 5 SSWBMs are operational at various DAE nuclear facilities throughout the country. The shielding of SSWBMs are said to be designed for 102 mm x 76 mm NaI(Tl) detector and over a period of time, the same concept is being followed. At present, the number of subjects monitored per annum has increased significantly compared to earlier years due to the increase in nuclear facilities at different sites and also increase in number of contract personnel. Aim of this study is to develop/upgrade the existing SSWBMs to increase their capabilities in terms of throughput without compromising on sensitivity. This work includes response studies of individual detectors of sizes 102 mm x 76 mm and 203 mm x 102 mm housed in SSWBM in terms of background, efficiency and Minimum Detection Activity (MDA) for different gamma emitting radio nuclides using Bhabha Atomic Research Centre reference Bottle Mannequin ABsorption (BOMAB) phantom

Design of Vibration Absorber using Spring and Rubber for Armored Vehicle 5.56 mm Caliber Rifle

Directory of Open Access Journals (Sweden)

Aditya Sukma Nugraha

2014-12-01

Full Text Available This paper presents a design of vibration absorber using spring and rubber for 5.56 mm caliber rifle armored vehicle. Such a rifle is used in a Remote-Controlled Weapon System (RCWS or a turret where it is fixed using a two degree of freedom pan-tilt mechanism. A half car lumped mass dynamic model of armored vehicles was derived. Numerical simulation was conducted using fourth order Runge Kutta method. Various types of vibration absorbers using spring and rubber with different configurations are installed in the elevation element. Vibration effects on horizontal direction, vertical direction and angular deviation of the elevation element was investigated. Three modes of fire were applied i.e. single fire, semi-automatic fire and automatic fire. From simulation results, it was concluded that the parallel configuration of damping rubber type 3, which has stiffness of 980,356.04 (N/m2 and damping coefficient of 107.37 (N.s/m, and Carbon steel spring whose stiffness coefficient is 5.547 x 106 (N/m2 provides the best vibration absorption. 

Growth-Prediction Model for Blue Mussels (Mytilus edulis on Future Optimally Thinned Farm-Ropes in Great Belt (Denmark

Directory of Open Access Journals (Sweden)

Poul S. Larsen

2016-07-01

Full Text Available A recently developed BioEnergetic Growth (BEG model for blue mussels (Mytilus edulis, valid for juvenile mussels, has been further developed to an ‘extended model’ and an alternative ‘ad hoc BEG model’ valid for post-metamorphic mussels, where the latter accounts for changing ambient chl a concentration. It was used to predict the growth of M. edulis on optimally thinned farm-ropes in Great Belt (Denmark, from newly settled post-metamorphic mussels of an initial shell size of 0.8 mm to marketable juvenile 30–35 mm ‘mini-mussels’. Such mussels will presumably in the near future be introduced as a new Danish, smaller-sized consumer product. Field data for actual growth (from Day 0 = 14 June 2011 showed that size of ‘mini-mussel’ was reached on Day 109 (Oct 1 and length 38 mm on Day 178 (Dec 9 while the corresponding predictions using the extended model were Day 121 (Oct 13 and Day 159 (Nov 20. Similar results were obtained by use of the ad hoc BEG model which also demonstrated the sensitivity of growth prediction to levels of chl a concentration, but less to temperature. The results suggest that it is possible (when the conditions are optimal, i.e., no intraspecific competition ensured by sufficient thinning to produce ‘mini-mussels’ in Great Belt during one season, but not the usual marketable 45-mm mussels. We suggest that the prediction model may be used as a practical instrument to evaluate to what degree the actual growth of mussels on farm ropes due to intraspecific competition may deviate from the potential (optimal growth under specified chl a and temperature conditions, and this implies that the effect of thinning to optimize the individual growth by eliminating intraspecific competition can be rationally evaluated.

Decadal prediction skill in the ocean with surface nudging in the IPSL-CM5A-LR climate model

OpenAIRE

Mignot , Juliette; García-Serrano , Javier; Swingedouw , Didier; Germe , Agathe; Nguyen , Sébastien; Ortega , Pablo; Guilyardi , Éric; Ray , Sulagna

2016-01-01

International audience; Two decadal prediction ensembles, based on the same climate model (IPSL-CM5A-LR) and the same surface nudging initialization strategy are analyzed and compared with a focus on upper-ocean variables in different regions of the globe. One ensemble consists of 3-member hindcasts launched every year since 1961 while the other ensemble benefits from 9 members but with start dates only every 5 years. Analysis includes anomaly correlation coefficients and root mean square err...

Decadal prediction skill in the ocean with surface nudging in the IPSL-CM5A-LR climate model

Science.gov (United States)

Mignot, Juliette; García-Serrano, Javier; Swingedouw, Didier; Germe, Agathe; Nguyen, Sébastien; Ortega, Pablo; Guilyardi, Eric; Ray, Sulagna

2016-08-01

Two decadal prediction ensembles, based on the same climate model (IPSL-CM5A-LR) and the same surface nudging initialization strategy are analyzed and compared with a focus on upper-ocean variables in different regions of the globe. One ensemble consists of 3-member hindcasts launched every year since 1961 while the other ensemble benefits from 9 members but with start dates only every 5 years. Analysis includes anomaly correlation coefficients and root mean square errors computed against several reanalysis and gridded observational fields, as well as against the nudged simulation used to produce the hindcasts initial conditions. The last skill measure gives an upper limit of the predictability horizon one can expect in the forecast system, while the comparison with different datasets highlights uncertainty when assessing the actual skill. Results provide a potential prediction skill (verification against the nudged simulation) beyond the linear trend of the order of 10 years ahead at the global scale, but essentially associated with non-linear radiative forcings, in particular from volcanoes. At regional scale, we obtain 1 year in the tropical band, 10 years at midlatitudes in the North Atlantic and North Pacific, and 5 years at tropical latitudes in the North Atlantic, for both sea surface temperature (SST) and upper-ocean heat content. Actual prediction skill (verified against observational or reanalysis data) is overall more limited and less robust. Even so, large actual skill is found in the extratropical North Atlantic for SST and in the tropical to subtropical North Pacific for upper-ocean heat content. Results are analyzed with respect to the specific dynamics of the model and the way it is influenced by the nudging. The interplay between initialization and internal modes of variability is also analyzed for sea surface salinity. The study illustrates the importance of two key ingredients both necessary for the success of future coordinated decadal

Mental models accurately predict emotion transitions.

Science.gov (United States)

Thornton, Mark A; Tamir, Diana I

2017-06-06

Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

Mental models accurately predict emotion transitions

Science.gov (United States)

Thornton, Mark A.; Tamir, Diana I.

2017-01-01

Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

Thermochemical Erosion Modeling of the 25-MM M242/M791 Gun System

National Research Council Canada - National Science Library

Sopok, Samuel

1997-01-01

The MACE gun barrel thermochemical erosion modeling code addresses wall degradations due to transformations, chemical reactions, and cracking coupled with pure mechanical erosion for the 25-mm M242/M791 gun system...

Use of mathematic modeling to compare and predict hemodynamic effects of the modified Blalock-Taussig and right ventricle-pulmonary artery shunts for hypoplastic left heart syndrome.

Science.gov (United States)

Bove, Edward L; Migliavacca, Francesco; de Leval, Marc R; Balossino, Rossella; Pennati, Giancarlo; Lloyd, Thomas R; Khambadkone, Sachin; Hsia, Tain-Yen; Dubini, Gabriele

2008-08-01

Stage one reconstruction (Norwood operation) for hypoplastic left heart syndrome can be performed with either a modified Blalock-Taussig shunt or a right ventricle-pulmonary artery shunt. Both methods have certain inherent characteristics. It is postulated that mathematic modeling could help elucidate these differences. Three-dimensional computer models of the Blalock-Taussig shunt and right ventricle-pulmonary artery shunt modifications of the Norwood operation were developed by using the finite volume method. Conduits of 3, 3.5, and 4 mm were used in the Blalock-Taussig shunt model, whereas conduits of 4, 5, and 6 mm were used in the right ventricle-pulmonary artery shunt model. The hydraulic nets (lumped resistances, compliances, inertances, and elastances) were identical in the 2 models. A multiscale approach was adopted to couple the 3-dimensional models with the circulation net. Computer simulations were compared with postoperative catheterization data. Good correlation was found between predicted and observed data. For the right ventricle-pulmonary artery shunt modification, there was higher aortic diastolic pressure, decreased pulmonary artery pressure, lower Qp/Qs ratio, and higher coronary perfusion pressure. Mathematic modeling predicted minimal regurgitant flow in the right ventricle-pulmonary artery shunt model, which correlated with postoperative Doppler measurements. The right ventricle-pulmonary artery shunt demonstrated lower stroke work and a higher mechanical efficiency (stroke work/total mechanical energy). The close correlation between predicted and observed data supports the use of mathematic modeling in the design and assessment of surgical procedures. The potentially damaging effects of a systemic ventriculotomy in the right ventricle-pulmonary artery shunt modification of the Norwood operation have not been analyzed.

A novel very wideband integrated antenna system for 4G and 5G mm-wave applications

KAUST Repository

Ikram, M.

2017-09-22

In this work, a novel very wideband 4-element monopole based multiple-input multiple-output (MIMO) antenna system with single connected antenna array (CAA) is presented. The CAA is based on a single slot which is etched on the ground plane. A 2 × 1 power divider/combiner is used to excite the slot to act as a CAA. The proposed design covers the 4G bands between 1850 and 3700, and the 28 GHz 5G band. The covered bandwidths are 1462 and 240 MHz from 1843 to 3305 MHz and 3500 to 3740 MHz, respectively, for 4G applications. A bandwidth of 1.22 GHz from 27.5 to 28.72 GHz is obtained for 5G applications. The proposed antenna system is designed on a double layer RO4350B substrate with height of 0.76 mm and dielectric constant of 3.5. The total size of the design is 115 × 65 × 0.76 mm. It is compact, low profile and suitable for wireless handheld devices. The MIMO performance metrics such as isolation and ECC are evaluated and good agreement between simulations and measurements is achieved.

Alcator C-Mod predictive modeling

International Nuclear Information System (INIS)

Pankin, Alexei; Bateman, Glenn; Kritz, Arnold; Greenwald, Martin; Snipes, Joseph; Fredian, Thomas

2001-01-01

Predictive simulations for the Alcator C-mod tokamak [I. Hutchinson et al., Phys. Plasmas 1, 1511 (1994)] are carried out using the BALDUR integrated modeling code [C. E. Singer et al., Comput. Phys. Commun. 49, 275 (1988)]. The results are obtained for temperature and density profiles using the Multi-Mode transport model [G. Bateman et al., Phys. Plasmas 5, 1793 (1998)] as well as the mixed-Bohm/gyro-Bohm transport model [M. Erba et al., Plasma Phys. Controlled Fusion 39, 261 (1997)]. The simulated discharges are characterized by very high plasma density in both low and high modes of confinement. The predicted profiles for each of the transport models match the experimental data about equally well in spite of the fact that the two models have different dimensionless scalings. Average relative rms deviations are less than 8% for the electron density profiles and 16% for the electron and ion temperature profiles

Analysis on MM5 predictions at Sriharikota during northeast ...

Indian Academy of Sciences (India)

of objective analysis system using radiosonde observations, surface observations and Kalpana-1 satellite derived Atmospheric ... to take go/no-go decision for the planned activities. For this ... Methodology and data used ... tors, i.e., water vapour winds and cloud motion ..... discussed in earlier sections is supported by a sta-.

Validation of the STAFF-5 computer model

International Nuclear Information System (INIS)

Fletcher, J.F.; Fields, S.R.

1981-04-01

STAFF-5 is a dynamic heat-transfer-fluid-flow stress model designed for computerized prediction of the temperature-stress performance of spent LWR fuel assemblies under storage/disposal conditions. Validation of the temperature calculating abilities of this model was performed by comparing temperature calculations under specified conditions to experimental data from the Engine Maintenance and Dissassembly (EMAD) Fuel Temperature Test Facility and to calculations performed by Battelle Pacific Northwest Laboratory (PNL) using the HYDRA-1 model. The comparisons confirmed the ability of STAFF-5 to calculate representative fuel temperatures over a considerable range of conditions, as a first step in the evaluation and prediction of fuel temperature-stress performance

Selecting the minimum prediction base of historical data to perform 5-year predictions of the cancer burden: The GoF-optimal method.

Science.gov (United States)

Valls, Joan; Castellà, Gerard; Dyba, Tadeusz; Clèries, Ramon

2015-06-01

Predicting the future burden of cancer is a key issue for health services planning, where a method for selecting the predictive model and the prediction base is a challenge. A method, named here Goodness-of-Fit optimal (GoF-optimal), is presented to determine the minimum prediction base of historical data to perform 5-year predictions of the number of new cancer cases or deaths. An empirical ex-post evaluation exercise for cancer mortality data in Spain and cancer incidence in Finland using simple linear and log-linear Poisson models was performed. Prediction bases were considered within the time periods 1951-2006 in Spain and 1975-2007 in Finland, and then predictions were made for 37 and 33 single years in these periods, respectively. The performance of three fixed different prediction bases (last 5, 10, and 20 years of historical data) was compared to that of the prediction base determined by the GoF-optimal method. The coverage (COV) of the 95% prediction interval and the discrepancy ratio (DR) were calculated to assess the success of the prediction. The results showed that (i) models using the prediction base selected through GoF-optimal method reached the highest COV and the lowest DR and (ii) the best alternative strategy to GoF-optimal was the one using the base of prediction of 5-years. The GoF-optimal approach can be used as a selection criterion in order to find an adequate base of prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method.

Directory of Open Access Journals (Sweden)

Marharyta Petukh

2015-07-01

Full Text Available A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624 while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation.

A national prediction model for PM2.5 component exposures and measurement error-corrected health effect inference.

Science.gov (United States)

Bergen, Silas; Sheppard, Lianne; Sampson, Paul D; Kim, Sun-Young; Richards, Mark; Vedal, Sverre; Kaufman, Joel D; Szpiro, Adam A

2013-09-01

Studies estimating health effects of long-term air pollution exposure often use a two-stage approach: building exposure models to assign individual-level exposures, which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. To illustrate the importance of accounting for exposure model characteristics in two-stage air pollution studies, we considered a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). We built national spatial exposure models that used partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), silicon (Si), and sulfur (S). We predicted PM2.5 component exposures for the MESA cohort and estimated cross-sectional associations with carotid intima-media thickness (CIMT), adjusting for subject-specific covariates. We corrected for measurement error using recently developed methods that account for the spatial structure of predicted exposures. Our models performed well, with cross-validated R2 values ranging from 0.62 to 0.95. Naïve analyses that did not account for measurement error indicated statistically significant associations between CIMT and exposure to OC, Si, and S. EC and OC exhibited little spatial correlation, and the corrected inference was unchanged from the naïve analysis. The Si and S exposure surfaces displayed notable spatial correlation, resulting in corrected confidence intervals (CIs) that were 50% wider than the naïve CIs, but that were still statistically significant. The impact of correcting for measurement error on health effect inference is concordant with the degree of spatial correlation in the exposure surfaces. Exposure model characteristics must be considered when performing two-stage air pollution epidemiologic analyses because naïve health effect inference may be inappropriate.

Risk terrain modeling predicts child maltreatment.

Science.gov (United States)

Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

2016-12-01

As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Comparative Study of Bancruptcy Prediction Models

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Isye Arieshanti

2013-09-01

Full Text Available Early indication of bancruptcy is important for a company. If companies aware of  potency of their bancruptcy, they can take a preventive action to anticipate the bancruptcy. In order to detect the potency of a bancruptcy, a company can utilize a a model of bancruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully. Because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for bancruptcy prediction. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP, Hybrid of MLP + Multiple Linear Regression, it can be showed that fuzzy k-NN method achieve the best performance with accuracy 77.5%

Predictive ability of severe rainfall events over Catalonia for the year 2008

Directory of Open Access Journals (Sweden)

A. Comellas

2011-07-01

Full Text Available This paper analyses the predictive ability of quantitative precipitation forecasts (QPF and the so-called "poor-man" rainfall probabilistic forecasts (RPF. With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain, managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9–10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h MM5 tends to overestimate total precipitation, whereas for short events (≤24 h the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale.

Throughout this study, we have only dealt with (SMC-issued warning episodes in order to analyse deterministic (MM5 and COSMO-I7

Regional calibration models for predicting loblolly pine tracheid properties using near-infrared spectroscopy

Science.gov (United States)

Mohamad Nabavi; Joseph Dahlen; Laurence Schimleck; Thomas L. Eberhardt; Cristian Montes

2018-01-01

This study developed regional calibration models for the prediction of loblolly pine (Pinus taeda) tracheid properties using near-infrared (NIR) spectroscopy. A total of 1842 pith-to-bark radial strips, aged 19–31 years, were acquired from 268 trees from 109 stands across the southeastern USA. Diffuse reflectance NIR spectra were collected at 10-mm...

Finding Furfural Hydrogenation Catalysts via Predictive Modelling

Science.gov (United States)

Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

2010-01-01

Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Shiraishi, Satomi; Moore, Kevin L., E-mail: kevinmoore@ucsd.edu [Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California 92093 (United States)

2016-01-15

Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrix and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D{sub clin} − D{sub pred}. The mean (〈δD{sub r}〉), standard deviation (σ{sub δD{sub r}}), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r{sub PTV}) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r{sub PTV} ∈ [ − 6, 30] mm. The

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

Science.gov (United States)

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

Development of estrogen receptor beta binding prediction model using large sets of chemicals.

Science.gov (United States)

Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

2017-11-03

We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .

Binding Mode Prediction of 5-Hydroxytryptamine 2C Receptor Ligands by Homology Modeling and Molecular Docking Analysis

Energy Technology Data Exchange (ETDEWEB)

Ahmed, Asif; Nagarajan, Shanthi; Doddareddy, Munikumar Reddy; Cho, Yong Seo; Pae, Ae Nim [Korea Institute of Science and Technology, Seoul (Korea, Republic of)

2011-06-15

Serotonin or 5-hydroxytryptamine subtype 2C (5-HT{sub 2C}) receptor belongs to class A amine subfamily of Gprotein- coupled receptor (GPCR) super family and its ligands has therapeutic promise as anti-depressant and -obesity agents. So far, bovine rhodopsin from class A opsin subfamily was the mostly used X-ray crystal template to model this receptor. Here, we explained homology model using beta 2 adrenergic receptor (β2AR), the model was energetically minimized and validated by flexible ligand docking with known agonists and antagonists. In the active site Asp134, Ser138 of transmembrane 3 (TM3), Arg195 of extracellular loop 2 (ECL2) and Tyr358 of TM7 were found as important residues to interact with agonists. In addition to these, V208 of ECL2 and N351 of TM7 was found to interact with antagonists. Several conserved residues including Trp324, Phe327 and Phe328 were also found to contribute hydrophobic interaction. The predicted ligand binding mode is in good agreement with published mutagenesis and homology model data. This new template derived homology model can be useful for further virtual screening based lead identification.

An "all 5 mm ports" technique for laparoscopic day-case anti-reflux surgery: A consecutive case series of 205 patients.

Science.gov (United States)

Almond, L M; Charalampakis, V; Mistry, P; Naqvi, M; Hodson, J; Lafaurie, G; Matthews, J; Singhal, R; Super, P

2016-11-01

Laparoscopic anti-reflux surgery is conventionally performed using two 10/12 mm ports. While laparoscopic procedures reduce post-operative pain, the use of larger ports invariably increases discomfort and affects cosmesis. We describe a new all 5 mm ports technique for laparoscopic anti-reflux surgery and present a review of our initial experience with this approach. All patients undergoing laparoscopic fundoplication over a 35 month period from February 2013 under the care of a single surgeon were included. A Lind laparoscopic fundoplication was performed using an all 5 mm port technique. Data was recorded prospectively on patient demographics, operating surgeon, surgical time, date of discharge, readmissions, complications, need for re-intervention, and reasons for admission. Two hundred and five consecutive patients underwent laparoscopic fundoplication over the study period. The all 5 mm port technique was used in all cases, with conversion to a 12 mm port only once (0.49%). Median operating time was 52 min 185 (90.2%) patients were discharged as day cases. Increasing ASA grade and the presence of a hiatus hernia were associated with the need for overnight stay with admission required in 33% of patients with ASA 3, compared to 4% with ASA 1 (p = 0.001), and 29% of those with a hiatus hernia vs. 5% without (p management. This would improve the service for these patients and culminate in cost savings for the NHS. Copyright © 2016. Published by Elsevier Ltd.

Visualization of Lamb Wave Interaction with a 5 mm Fatigue Crack using 1D Ultra High Frequency Laser Doppler Vibrometry

Science.gov (United States)

2011-09-01

detection of a fatigue crack via 3D LDV measurements, both in aluminum plates. All the referenced LDV/guided wave studies made use of PZT or similar...Figure 1a). (b) (a) (c) Figure 1: (a) Test specimen in MTS fatigue test machine, (b) hole with 5 mm crack, (c) PZT placement with...mm thick aluminum plates with a small (1.59 mm) center hole added to facilitate growth of a fatigue crack. One plate was left undamaged while the

Can the possibility of transverse iliosacral screw fixation for first sacral segment be predicted preoperatively? Results of a computational cadaveric study.

Science.gov (United States)

Jeong, Jin-Hoon; Jin, Jin Woo; Kang, Byoung Youl; Jung, Gu-Hee

2017-10-01

The purpose of this study was to predict the possibility of transverse iliosacral (TIS) screw fixation into the first sacral segment (S 1 ) and introduce practical anatomical variables using conventional computed tomography (CT) scans. A total of 82 cadaveric sacra (42 males and 40 females) were used for continuous 1.0-mm slice CT scans, which were imported into Mimics ® software to produce a three-dimensional pelvis model. The anterior height (BH) and superior width (BW) of the elevated sacral segment was measured, followed by verification of the safe zone (SZ S1 and SZ S2 ) in a true lateral view. Their vertical (VD S1 and VD S2 ) and horizontal (HD S1 and HD S2 ) distances were measured. VD S1 less than 7mm was classified as impossible sacrum, since the transverse fixation of 7.0 mm-sized IS screw could not be done safely. Fourteen models (16.7%; six females, eight males) were assigned as the impossible sacrum. There was no statistical significance regarding gender (p=0.626) and height (p=0.419). The average values were as follows: BW, 31.4mm (SD 2.9); BH, 16.7mm (SD 6.8); VD S1 , 13.4mm (SD 6.1); HD S1 , 22.5mm (SD 4.5); SZ S1 , 239.5mm 2 (SD 137.1); VD S2 , 15.5mm (SD 3.0); HD S2 , 18.3mm (SD 2.9); and SZ S2 , 221.1mm 2 (SD 68.5). Logistic regression analysis identified BH (p=0.001) and HD S1 (p=0.02) as the only statistically significant variables to predict the possibility. Receiver operating characteristic curve analysis established a cut-off value for BH and HD S1 of impossible sacrum of 20.6mm and 18.6mm, respectively. BH and HD S1 could be used to predict the possibility of TIS screw fixation. If the BH exceeds 20.6mm or HD S1 is less than 18.6mm, TIS screw fixation for S 1 should not be undertaken because of narrowed SZ. Copyright © 2017 Elsevier Ltd. All rights reserved.

FINE-SCALE STRUCTURE OF THE QUASAR 3C 279 MEASURED WITH 1.3 mm VERY LONG BASELINE INTERFEROMETRY

Energy Technology Data Exchange (ETDEWEB)

Lu Rusen; Fish, Vincent L.; Doeleman, Sheperd S.; Crew, Geoffrey; Cappallo, Roger J. [Massachusetts Institute of Technology, Haystack Observatory, Route 40, Westford, MA 01886 (United States); Akiyama, Kazunori; Honma, Mareki [National Astronomical Observatory of Japan, Osawa 2-21-1, Mitaka, Tokyo 181-8588 (Japan); Algaba, Juan C.; Ho, Paul T. P.; Inoue, Makoto [Institute of Astronomy and Astrophysics, Academia Sinica, P.O. Box 23-141, Taipei 10617, Taiwan, R.O.C. (China); Bower, Geoffrey C.; Dexter, Matt [Department of Astronomy, Radio Astronomy Laboratory, University of California Berkeley, 601 Campbell, Berkeley, CA 94720-3411 (United States); Brinkerink, Christiaan [Department of Astrophysics, IMAPP, Radboud University Nijmegen, P.O. Box 9010, 6500-GL Nijmegen (Netherlands); Chamberlin, Richard [Caltech Submillimeter Observatory, 111 Nowelo Street, Hilo, HI 96720 (United States); Freund, Robert [Arizona Radio Observatory, Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721-0065 (United States); Friberg, Per [James Clerk Maxwell Telescope, Joint Astronomy Centre, 660 North A' ohoku Place, University Park, Hilo, HI 96720 (United States); Gurwell, Mark A. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Jorstad, Svetlana G. [Institute for Astrophysical Research, Boston University, Boston, MA 02215 (United States); Krichbaum, Thomas P. [Max-Planck-Institut fuer Radioastronomie, Auf dem Huegel 69, D-53121 Bonn (Germany); Loinard, Laurent, E-mail: rslu@haystack.mit.edu [Centro de Radiostronomia y Astrofisica, Universidad Nacional Autonoma de Mexico, 58089 Morelia, Michoacan (Mexico); and others

2013-07-20

We report results from five day very long baseline interferometry observations of the well-known quasar 3C 279 at 1.3 mm (230 GHz) in 2011. The measured nonzero closure phases on triangles including stations in Arizona, California, and Hawaii indicate that the source structure is spatially resolved. We find an unusual inner jet direction at scales of {approx}1 pc extending along the northwest-southeast direction (P.A. = 127 Degree-Sign {+-} 3 Degree-Sign ), as opposed to other (previously) reported measurements on scales of a few parsecs showing inner jet direction extending to the southwest. The 1.3 mm structure corresponds closely with that observed in the central region of quasi-simultaneous super-resolution Very Long Baseline Array images at 7 mm. The closure phase changed significantly on the last day when compared with the rest of observations, indicating that the inner jet structure may be variable on daily timescales. The observed new direction of the inner jet shows inconsistency with the prediction of a class of jet precession models. Our observations indicate a brightness temperature of {approx}8 Multiplication-Sign 10{sup 10} K in the 1.3 mm core, much lower than that at centimeter wavelengths. Observations with better uv coverage and sensitivity in the coming years will allow the discrimination between different structure models and will provide direct images of the inner regions of the jet with 20-30 {mu}as (5-7 light months) resolution.

FINE-SCALE STRUCTURE OF THE QUASAR 3C 279 MEASURED WITH 1.3 mm VERY LONG BASELINE INTERFEROMETRY

International Nuclear Information System (INIS)

Lu Rusen; Fish, Vincent L.; Doeleman, Sheperd S.; Crew, Geoffrey; Cappallo, Roger J.; Akiyama, Kazunori; Honma, Mareki; Algaba, Juan C.; Ho, Paul T. P.; Inoue, Makoto; Bower, Geoffrey C.; Dexter, Matt; Brinkerink, Christiaan; Chamberlin, Richard; Freund, Robert; Friberg, Per; Gurwell, Mark A.; Jorstad, Svetlana G.; Krichbaum, Thomas P.; Loinard, Laurent

2013-01-01

We report results from five day very long baseline interferometry observations of the well-known quasar 3C 279 at 1.3 mm (230 GHz) in 2011. The measured nonzero closure phases on triangles including stations in Arizona, California, and Hawaii indicate that the source structure is spatially resolved. We find an unusual inner jet direction at scales of ∼1 pc extending along the northwest-southeast direction (P.A. = 127° ± 3°), as opposed to other (previously) reported measurements on scales of a few parsecs showing inner jet direction extending to the southwest. The 1.3 mm structure corresponds closely with that observed in the central region of quasi-simultaneous super-resolution Very Long Baseline Array images at 7 mm. The closure phase changed significantly on the last day when compared with the rest of observations, indicating that the inner jet structure may be variable on daily timescales. The observed new direction of the inner jet shows inconsistency with the prediction of a class of jet precession models. Our observations indicate a brightness temperature of ∼8 × 10 10 K in the 1.3 mm core, much lower than that at centimeter wavelengths. Observations with better uv coverage and sensitivity in the coming years will allow the discrimination between different structure models and will provide direct images of the inner regions of the jet with 20-30 μas (5-7 light months) resolution.

Preclinical evaluation of invariant natural killer T cells in the 5T33 multiple myeloma model.

Directory of Open Access Journals (Sweden)

Haneen Nur

Full Text Available Immunomodulators have been used in recent years to reactivate host anti-tumor immunity in several hematological malignancies. This report describes the effect of activating natural killer T (NKT cells by α-Galactosylceramide (α-GalCer in the 5T33MM model of multiple myeloma (MM. NKT cells are T lymphocytes, co-expressing T and NK receptors, while invariant NKT cells (iNKTs also express a unique semi-invariant TCR α-chain. We followed iNKT numbers during the development of the disease in both 5T33MM mice and MM patients and found that their numbers dropped dramatically at the end stage of the disease, leading to a loss of total IFN-γ secretion. We furthermore observed that α-GalCer treatment significantly increased the survival of 5T33MM diseased mice. Taken together, our data demonstrate for the first time the possibility of using a preclinical murine MM model to study the effects of α-GalCer and show promising results of α-GalCer treatment in a low tumor burden setting.

Modeling Chemical Reactions by QM/MM Calculations: The Case of the Tautomerization in Fireflies Bioluminescent Systems.

Science.gov (United States)

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-01-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modeling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Modelling chemical reactions by QM/MM calculations: the case of the tautomerization in fireflies bioluminescent systems

Science.gov (United States)

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-04-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modelling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Prediction skill of rainstorm events over India in the TIGGE weather prediction models

Science.gov (United States)

Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

2017-12-01

Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

Modelling bankruptcy prediction models in Slovak companies

Directory of Open Access Journals (Sweden)

Kovacova Maria

2017-01-01

Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models.

Science.gov (United States)

de Jesus, Karla; Ayala, Helon V H; de Jesus, Kelly; Coelho, Leandro Dos S; Medeiros, Alexandre I A; Abraldes, José A; Vaz, Mário A P; Fernandes, Ricardo J; Vilas-Boas, João Paulo

2018-03-01

Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.

Correlation of clinical predictions and surgical results in maxillary superior repositioning.

Science.gov (United States)

Tabrizi, Reza; Zamiri, Barbad; Kazemi, Hamidreza

2014-05-01

This is a prospective study to evaluate the accuracy of clinical predictions related to surgical results in subjects who underwent maxillary superior repositioning without anterior-posterior movement. Surgeons' predictions according to clinical (tooth show at rest and at the maximum smile) and cephalometric evaluation were documented for the amount of maxillary superior repositioning. Overcorrection or undercorrection was documented for every subject 1 year after the operations. Receiver operating characteristic curve test was used to find a cutoff point in prediction errors and to determine positive predictive value (PPV) and negative predictive value. Forty subjects (14 males and 26 females) were studied. Results showed a significant difference between changes in the tooth show at rest and at the maximum smile line before and after surgery. Analysis of the data demonstrated no correlation between the predictive data and the surgical results. The incidence of undercorrection (25%) was more common than overcorrection (7.5%). The cutoff point for errors in predictions was 5 mm for tooth show at rest and 15 mm at the maximum smile. When the amount of the presurgical tooth show at rest was more than 5 mm, 50.5% of clinical predictions did not match the clinical results (PPV), and 75% of clinical predictions showed the same results when the tooth show was less than 5 mm (negative predictive value). When the amount of presurgical tooth shown in the maximum smile line was more than 15 mm, 75% of clinical predictions did not match with clinical results (PPV), and 25% of the predictions had the same results because the tooth show at the maximum smile was lower than 15 mm. Clinical predictions according to the tooth show at rest and at the maximum smile have a poor correlation with clinical results in maxillary superior repositioning for vertical maxillary excess. The risk of errors in predictions increased when the amount of superior repositioning of the maxilla increased

A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

Directory of Open Access Journals (Sweden)

M Irfan Ashraf

Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

[The value of 5-HTT gene polymorphism for the assessment and prediction of male adolescence violence].

Science.gov (United States)

Yu, Yue; Liu, Xiang; Yang, Zhen-xing; Qiu, Chang-jian; Ma, Xiao-hong

2012-08-01

To establish an adolescent violence crime prediction model, and to assess the value of serotonin transporter (5-HTT) gene polymorphism for the assessment and prediction of violent crime. Investigative tools were used to analyze the difference in personality dimensions, social support, coping styles, aggressiveness, impulsivity, and family condition scale between 223 adolescents with violence behavior and 148 adolescents without violence behavior. The distribution of 5-HTT gene polymorphisms (5-HTTLPR and 5-HTTVNTR) was compared between the two groups. The role of 5-HTT gene polymorphism on adolescent personality, impulsion and aggression scale also was also analyzed. Stepwise logistic regression was used to establish a predictive model for adolescent violent crime. Significant difference was found between the violence group and the control group on multiple dimensions of psychology and environment scales. However, no statistical difference was found with regard to the 5-HTT genotypes and alleles between adolescents with violent behaviors and normal controls. The rate of prediction accuracy was not significantly improved when 5-HTT gene polymorphism was taken into the model. The violent crime of adolescents was closely related with social and environmental factors. No association was found between 5-HTT polymorphisms and adolescent violence criminal behavior.

Predictors of success after extracorporeal shock wave lithotripsy (ESWL) for renal calculi between 20-30 mm: a multivariate analysis model.

Science.gov (United States)

El-Assmy, Ahmed; El-Nahas, Ahmed R; Abo-Elghar, Mohamed E; Eraky, Ibrahim; El-Kenawy, Mahmoud R; Sheir, Khaled Z

2006-03-23

The first-line management of renal stones between 20-30 mm remains controversial. The Extracorporeal Shock Wave Lithotripsy (ESWL) stone-free rates for such patient groups vary widely. The purpose of this study was to define factors that have a significant impact on the stone-free rate after ESWL in such controversial groups. Between January 1990 and January 2004, 594 patients with renal stones 20-30 mm in length underwent ESWL monotherapy. Stone surface area was measured for all stones. The results of treatment were evaluated after 3 months of follow-up. The stone-free rate was correlated with stone and patient characteristics using the Chi-square test; factors found to be significant were further analyzed using multivariate analysis. Repeat ESWL was needed in 56.9% of cases. Post-ESWL complications occurred in 5% of cases and post-ESWL secondary procedures were required in 5.9%. At 3-month follow-up, the overall stone-free rate was 77.2%. Using the Chi-square test, stone surface area, location, number, radiological renal picture, and congenital renal anomalies had a significant impact on the stone-free rate. Multivariate analysis excluded radiological renal picture from the logistic regression model while other factors maintained their statistically significant effect on success rate, indicating that they were independent predictors. A regression analysis model was designed to estimate the probability of stone-free status after ESWL. The sensitivity of the model was 97.4%, the specificity 90%, and the overall accuracy 95.6%. Stone surface area, location, number, and congenital renal anomalies are prognostic predictors determining stone clearance after ESWL of renal calculi of 20-30 mm. High probability of stone clearance is obtained with single stone ESWL in such controversial groups and can define patients who would need other treatment modality.

Operational mesoscale atmospheric dispersion prediction using high performance parallel computing cluster for emergency response

International Nuclear Information System (INIS)

Srinivas, C.V.; Venkatesan, R.; Muralidharan, N.V.; Das, Someshwar; Dass, Hari; Eswara Kumar, P.

2005-08-01

An operational atmospheric dispersion prediction system is implemented on a cluster super computer for 'Online Emergency Response' for Kalpakkam nuclear site. The numerical system constitutes a parallel version of a nested grid meso-scale meteorological model MM5 coupled to a random walk particle dispersion model FLEXPART. The system provides 48 hour forecast of the local weather and radioactive plume dispersion due to hypothetical air borne releases in a range of 100 km around the site. The parallel code was implemented on different cluster configurations like distributed and shared memory systems. Results of MM5 run time performance for 1-day prediction are reported on all the machines available for testing. A reduction of 5 times in runtime is achieved using 9 dual Xeon nodes (18 physical/36 logical processors) compared to a single node sequential run. Based on the above run time results a cluster computer facility with 9-node Dual Xeon is commissioned at IGCAR for model operation. The run time of a triple nested domain MM5 is about 4 h for 24 h forecast. The system has been operated continuously for a few months and results were ported on the IMSc home page. Initial and periodic boundary condition data for MM5 are provided by NCMRWF, New Delhi. An alternative source is found to be NCEP, USA. These two sources provide the input data to the operational models at different spatial and temporal resolutions and using different assimilation methods. A comparative study on the results of forecast is presented using these two data sources for present operational use. Slight improvement is noticed in rainfall, winds, geopotential heights and the vertical atmospheric structure while using NCEP data probably because of its high spatial and temporal resolution. (author)

A burnout prediction model based around char morphology

Energy Technology Data Exchange (ETDEWEB)

T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre

2005-07-01

Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.

Density-Dependent Formulation of Dispersion-Repulsion Interactions in Hybrid Multiscale Quantum/Molecular Mechanics (QM/MM) Models.

Science.gov (United States)

Curutchet, Carles; Cupellini, Lorenzo; Kongsted, Jacob; Corni, Stefano; Frediani, Luca; Steindal, Arnfinn Hykkerud; Guido, Ciro A; Scalmani, Giovanni; Mennucci, Benedetta

2018-03-13

Mixed multiscale quantum/molecular mechanics (QM/MM) models are widely used to explore the structure, reactivity, and electronic properties of complex chemical systems. Whereas such models typically include electrostatics and potentially polarization in so-called electrostatic and polarizable embedding approaches, respectively, nonelectrostatic dispersion and repulsion interactions are instead commonly described through classical potentials despite their quantum mechanical origin. Here we present an extension of the Tkatchenko-Scheffler semiempirical van der Waals (vdW TS ) scheme aimed at describing dispersion and repulsion interactions between quantum and classical regions within a QM/MM polarizable embedding framework. Starting from the vdW TS expression, we define a dispersion and a repulsion term, both of them density-dependent and consistently based on a Lennard-Jones-like potential. We explore transferable atom type-based parametrization strategies for the MM parameters, based on either vdW TS calculations performed on isolated fragments or on a direct estimation of the parameters from atomic polarizabilities taken from a polarizable force field. We investigate the performance of the implementation by computing self-consistent interaction energies for the S22 benchmark set, designed to represent typical noncovalent interactions in biological systems, in both equilibrium and out-of-equilibrium geometries. Overall, our results suggest that the present implementation is a promising strategy to include dispersion and repulsion in multiscale QM/MM models incorporating their explicit dependence on the electronic density.

Linear sign in cystic brain lesions ≥5 mm. A suggestive feature of perivascular space

Energy Technology Data Exchange (ETDEWEB)

Sung, Jinkyeong [The Catholic University of Korea, Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, Seoul (Korea, Republic of); The Catholic University of Korea, Department of Radiology, St. Vincent' s Hospital, College of Medicine, Seoul (Korea, Republic of); Jang, Jinhee; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-soo [The Catholic University of Korea, Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, Seoul (Korea, Republic of)

2017-11-15

To determine the prevalence of a linear sign within enlarged perivascular space (EPVS) and chronic lacunar infarction (CLI) ≥ 5 mm on T2-weighted imaging (T2WI) and time-of-flight (TOF) magnetic resonance angiography (MRA), and to evaluate the diagnostic value of the linear signs for EPVS over CLI. This study included 101 patients with cystic lesions ≥ 5 mm on brain MRI including TOF MRA. After classification of cystic lesions into EPVS or CLI, two readers assessed linear signs on T2WI and TOF MRA. We compared the prevalence and the diagnostic performance of linear signs. Among 46 EPVS and 51 CLI, 84 lesions (86.6%) were in basal ganglia. The prevalence of T2 and TOF linear signs was significantly higher in the EPVS than in the CLI (P <.001). For the diagnosis of EPVS, T2 and TOF linear signs showed high sensitivity (> 80%). TOF linear sign showed significantly higher specificity (100%) and accuracy (92.8% and 90.7%) than T2 linear sign (P <.001). T2 and TOF linear signs were more frequently observed in EPVS than CLI. They showed high sensitivity in differentiation of them, especially for basal ganglia. TOF sign showed higher specificity and accuracy than T2 sign. (orig.)

Break model comparison in different RELAP5 versions

International Nuclear Information System (INIS)

Parzer, I.

2003-01-01

The presented work focuses on the break flow prediction in RELAP5/MOD3 code, which is crucial to predict core uncovering and heatup during the Small Break Loss-of-Coolant Accidents (SB LOCA). The code prediction has been compared to the IAEA-SPE-4 experiments conducted on the PMK-2 integral test facilities in Hungary. The simulations have been performed with MOD3.2.2 Beta, MOD3.2.2 Gamma, MOD3.3 Beta and MOD3.3 frozen code version. In the present work we have compared the Ransom-Trapp and Henry-Fauske break model predictions. Additionally, both model predictions have been compared to itself, when used as the main modeling tool or when used as another code option, as so-called 'secret developmental options' on input card no.1. (author)

Mirrors design, analysis and manufacturing of the 550mm Korsch telescope experimental model

Science.gov (United States)

Huang, Po-Hsuan; Huang, Yi-Kai; Ling, Jer

2017-08-01

In 2015, NSPO (National Space Organization) began to develop the sub-meter resolution optical remote sensing instrument of the next generation optical remote sensing satellite which follow-on to FORMOSAT-5. Upgraded from the Ritchey-Chrétien Cassegrain telescope optical system of FORMOSAT-5, the experimental optical system of the advanced optical remote sensing instrument was enhanced to an off-axis Korsch telescope optical system which consists of five mirrors. It contains: (1) M1: 550mm diameter aperture primary mirror, (2) M2: secondary mirror, (3) M3: off-axis tertiary mirror, (4) FM1 and FM2: two folding flat mirrors, for purpose of limiting the overall volume, reducing the mass, and providing a long focal length and excellent optical performance. By the end of 2015, we implemented several important techniques including optical system design, opto-mechanical design, FEM and multi-physics analysis and optimization system in order to do a preliminary study and begin to develop and design these large-size lightweight aspheric mirrors and flat mirrors. The lightweight mirror design and opto-mechanical interface design were completed in August 2016. We then manufactured and polished these experimental model mirrors in Taiwan; all five mirrors ware completed as spherical surfaces by the end of 2016. Aspheric figuring, assembling tests and optical alignment verification of these mirrors will be done with a Korsch telescope experimental structure model in 2018.

A model for predicting lung cancer response to therapy

International Nuclear Information System (INIS)

Seibert, Rebecca M.; Ramsey, Chester R.; Hines, J. Wesley; Kupelian, Patrick A.; Langen, Katja M.; Meeks, Sanford L.; Scaperoth, Daniel D.

2007-01-01

Purpose: Volumetric computed tomography (CT) images acquired by image-guided radiation therapy (IGRT) systems can be used to measure tumor response over the course of treatment. Predictive adaptive therapy is a novel treatment technique that uses volumetric IGRT data to actively predict the future tumor response to therapy during the first few weeks of IGRT treatment. The goal of this study was to develop and test a model for predicting lung tumor response during IGRT treatment using serial megavoltage CT (MVCT). Methods and Materials: Tumor responses were measured for 20 lung cancer lesions in 17 patients that were imaged and treated with helical tomotherapy with doses ranging from 2.0 to 2.5 Gy per fraction. Five patients were treated with concurrent chemotherapy, and 1 patient was treated with neoadjuvant chemotherapy. Tumor response to treatment was retrospectively measured by contouring 480 serial MVCT images acquired before treatment. A nonparametric, memory-based locally weight regression (LWR) model was developed for predicting tumor response using the retrospective tumor response data. This model predicts future tumor volumes and the associated confidence intervals based on limited observations during the first 2 weeks of treatment. The predictive accuracy of the model was tested using a leave-one-out cross-validation technique with the measured tumor responses. Results: The predictive algorithm was used to compare predicted verse-measured tumor volume response for all 20 lesions. The average error for the predictions of the final tumor volume was 12%, with the true volumes always bounded by the 95% confidence interval. The greatest model uncertainty occurred near the middle of the course of treatment, in which the tumor response relationships were more complex, the model has less information, and the predictors were more varied. The optimal days for measuring the tumor response on the MVCT images were on elapsed Days 1, 2, 5, 9, 11, 12, 17, and 18 during

Fatigue life prediction of Ni-base thermal solar receiver tubes

Energy Technology Data Exchange (ETDEWEB)

Hartrott, Philipp von; Schlesinger, Michael [Fraunhofer-Institut fuer Werkstoffmechanik (IWM), Freiburg im Breisgau (Germany); Uhlig, Ralf; Jedamski, Jens [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Stuttgart (Germany)

2010-07-01

Solar receivers for tower type Solar Thermal Power Plants are subjected to complex thermo-mechanical loads including fast and severe thermo-mechanical cycles. The material temperatures can reach more than 800 C and fall to room temperature very quickly. In order to predict the fatigue life of a receiver design, receiver tubes made of Alloy 625 with a wall thickness of 0.5 mm were tested in isothermal and thermo-cyclic experiments. The number of cycles to failure was in the range of 100 to 100,000. A thermo-mechanical fatigue life prediction model was set up. The model is based on the cyclic deformation of the material and the damage caused by the growth of fatigue micro cracks. The model reasonably predicts the experimental results. (orig.)

Sub-mm emission line deep fields: CO and [C II] luminosity functions out to z = 6

NARCIS (Netherlands)

Popping, Gergö; van Kampen, Eelco; Decarli, Roberto; Spaans, Marco; Somerville, Rachel S.; Trager, Scott C.

2016-01-01

Now that Atacama Large (Sub)Millimeter Array is reaching its full capabilities, observations of sub-mm emission line deep fields become feasible. We couple a semi-analytic model of galaxy formation with a radiative transfer code to make predictions for the luminosity function of CO J =1-0 out to CO

Modelling 137Cs uptake in plants from undisturbed soil monoliths

International Nuclear Information System (INIS)

Waegeneers, Nadia; Smolders, Erik; Merckx, Roel

2005-01-01

A model predicting 137 Cs uptake in plants was applied on data from artificially contaminated lysimeters. The lysimeter data involve three different crops (beans, ryegrass and lettuce) grown on five different soils between 3 and 5 years after contamination and where soil solution composition was monitored. The mechanistic model predicts plant uptake of 137 Cs from soil solution composition. Predicted K concentrations in the rhizosphere were up to 50-fold below that in the bulk soil solution whereas corresponding 137 Cs concentration gradients were always less pronounced. Predictions of crop 137 Cs content based on rhizosphere soil solution compositions were generally closer to observations than those based on bulk soil solution composition. The model explained 17% (beans) to 91% (lettuce) of the variation in 137 Cs activity concentrations in the plants. The model failed to predict the 137 Cs activity concentration in ryegrass where uptake of the 5-year-old 137 Cs from 3 soils was about 40-fold larger than predicted. The model generally underpredicted crop 137 Cs concentrations at soil solution K concentration below about 1.0 mM. It is concluded that 137 Cs uptake can be predicted from the soil solution composition at adequate K nutrition but that significant uncertainties remain when soil solution K is below 1 mM

SU-E-J-234: Application of a Breathing Motion Model to ViewRay Cine MR Images

International Nuclear Information System (INIS)

O’Connell, D. P.; Thomas, D. H.; Dou, T. H.; Lamb, J. M.; Yang, L.; Low, D. A.

2015-01-01

Purpose: A respiratory motion model previously used to generate breathing-gated CT images was used with cine MR images. Accuracy and predictive ability of the in-plane models were evaluated. Methods: Sagittalplane cine MR images of a patient undergoing treatment on a ViewRay MRI/radiotherapy system were acquired before and during treatment. Images were acquired at 4 frames/second with 3.5 × 3.5 mm resolution and a slice thickness of 5 mm. The first cine frame was deformably registered to following frames. Superior/inferior component of the tumor centroid position was used as a breathing surrogate. Deformation vectors and surrogate measurements were used to determine motion model parameters. Model error was evaluated and subsequent treatment cines were predicted from breathing surrogate data. A simulated CT cine was created by generating breathing-gated volumetric images at 0.25 second intervals along the measured breathing trace, selecting a sagittal slice and downsampling to the resolution of the MR cines. A motion model was built using the first half of the simulated cine data. Model accuracy and error in predicting the remaining frames of the cine were evaluated. Results: Mean difference between model predicted and deformably registered lung tissue positions for the 28 second preview MR cine acquired before treatment was 0.81 +/− 0.30 mm. The model was used to predict two minutes of the subsequent treatment cine with a mean accuracy of 1.59 +/− 0.63 mm. Conclusion: Inplane motion models were built using MR cine images and evaluated for accuracy and ability to predict future respiratory motion from breathing surrogate measurements. Examination of long term predictive ability is ongoing. The technique was applied to simulated CT cines for further validation, and the authors are currently investigating use of in-plane models to update pre-existing volumetric motion models used for generation of breathing-gated CT planning images

Microeconomics of 300-mm process module control

Science.gov (United States)

Monahan, Kevin M.; Chatterjee, Arun K.; Falessi, Georges; Levy, Ady; Stoller, Meryl D.

2001-08-01

Simple microeconomic models that directly link metrology, yield, and profitability are rare or non-existent. In this work, we validate and apply such a model. Using a small number of input parameters, we explain current yield management practices in 200 mm factories. The model is then used to extrapolate requirements for 300 mm factories, including the impact of simultaneous technology transitions to 130nm lithography and integrated metrology. To support our conclusions, we use examples relevant to factory-wide photo module control.

Cross-Validation of Aerobic Capacity Prediction Models in Adolescents.

Science.gov (United States)

Burns, Ryan Donald; Hannon, James C; Brusseau, Timothy A; Eisenman, Patricia A; Saint-Maurice, Pedro F; Welk, Greg J; Mahar, Matthew T

2015-08-01

Cardiorespiratory endurance is a component of health-related fitness. FITNESSGRAM recommends the Progressive Aerobic Cardiovascular Endurance Run (PACER) or One mile Run/Walk (1MRW) to assess cardiorespiratory endurance by estimating VO2 Peak. No research has cross-validated prediction models from both PACER and 1MRW, including the New PACER Model and PACER-Mile Equivalent (PACER-MEQ) using current standards. The purpose of this study was to cross-validate prediction models from PACER and 1MRW against measured VO2 Peak in adolescents. Cardiorespiratory endurance data were collected on 90 adolescents aged 13-16 years (Mean = 14.7 ± 1.3 years; 32 girls, 52 boys) who completed the PACER and 1MRW in addition to a laboratory maximal treadmill test to measure VO2 Peak. Multiple correlations among various models with measured VO2 Peak were considered moderately strong (R = .74-0.78), and prediction error (RMSE) ranged from 5.95 ml·kg⁻¹,min⁻¹ to 8.27 ml·kg⁻¹.min⁻¹. Criterion-referenced agreement into FITNESSGRAM's Healthy Fitness Zones was considered fair-to-good among models (Kappa = 0.31-0.62; Agreement = 75.5-89.9%; F = 0.08-0.65). In conclusion, prediction models demonstrated moderately strong linear relationships with measured VO2 Peak, fair prediction error, and fair-to-good criterion referenced agreement with measured VO2 Peak into FITNESSGRAM's Healthy Fitness Zones.

A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities

Energy Technology Data Exchange (ETDEWEB)

Yuan, Amy [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York (United States); Wei, Jie [Department of Computer Science, City College of New York, New York, New York (United States); Gaebler, Carl P.; Huang, Hailiang; Olek, Devin [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York (United States); Li, Guang, E-mail: lig2@mskcc.org [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York (United States)

2016-12-01

Purpose: To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. Methods and Materials: A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. Results: The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm{sup 3} (−26% to 61%), and the ΔBP ranged from 0 to 0.2 (−71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model. Conclusions: A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for

Predictive Modeling of Structural Sensing for Aerospace Applications

Science.gov (United States)

2015-08-03

wave speed, which equals 3129 m s−1 for our case study aluminium 2024-T3 alloy . The Figure 7.Modeshapes of vibrations of 1 mm thick aluminium beam with...experiments was a proof of concept that was performed on 3.4 mm thick aluminium 7075 T6 alloy plate (figure 11). The SH-PWAS was 15 mm× 15mm×1mm, and...0.2 mm. The mesh size of SH-PWAS elements was 0.5 mm and 4 elements, per the 1 mm thickness. A 1 mm aluminium 2024 alloy plate was used in our simu

A single CD4 test with 250 cells/mm3 threshold predicts viral suppression in HIV-infected adults failing first-line therapy by clinical criteria.

Directory of Open Access Journals (Sweden)

Charles F Gilks

Full Text Available In low-income countries, viral load (VL monitoring of antiretroviral therapy (ART is rarely available in the public sector for HIV-infected adults or children. Using clinical failure alone to identify first-line ART failure and trigger regimen switch may result in unnecessary use of costly second-line therapy. Our objective was to identify CD4 threshold values to confirm clinically-determined ART failure when VL is unavailable.3316 HIV-infected Ugandan/Zimbabwean adults were randomised to first-line ART with Clinically-Driven (CDM, CD4s measured but blinded or routine Laboratory and Clinical Monitoring (LCM, 12-weekly CD4s in the DART trial. CD4 at switch and ART failure criteria (new/recurrent WHO 4, single/multiple WHO 3 event; LCM: CD4<100 cells/mm(3 were reviewed in 361 LCM, 314 CDM participants who switched over median 5 years follow-up. Retrospective VLs were available in 368 (55% participants.Overall, 265/361 (73% LCM participants failed with CD4<100 cells/mm(3; only 7 (2% switched with CD4≥250 cells/mm(3, four switches triggered by WHO events. Without CD4 monitoring, 207/314 (66% CDM participants failed with WHO 4 events, and 77(25%/30(10% with single/multiple WHO 3 events. Failure/switching with single WHO 3 events was more likely with CD4≥250 cells/mm(3 (28/77; 36% (p = 0.0002. CD4 monitoring reduced switching with viral suppression: 23/187 (12% LCM versus 49/181 (27% CDM had VL<400 copies/ml at failure/switch (p<0.0001. Amongst CDM participants with CD4<250 cells/mm(3 only 11/133 (8% had VL<400 copies/ml, compared with 38/48 (79% with CD4≥250 cells/mm(3 (p<0.0001.Multiple, but not single, WHO 3 events predicted first-line ART failure. A CD4 threshold 'tiebreaker' of ≥250 cells/mm(3 for clinically-monitored patients failing first-line could identify ∼80% with VL<400 copies/ml, who are unlikely to benefit from second-line. Targeting CD4s to single WHO stage 3 'clinical failures' would particularly avoid premature, costly

A risk prediction score model for predicting occurrence of post-PCI vasovagal reflex syndrome: a single center study in Chinese population.

Science.gov (United States)

Li, Hai-Yan; Guo, Yu-Tao; Tian, Cui; Song, Chao-Qun; Mu, Yang; Li, Yang; Chen, Yun-Dai

2017-08-01

The vasovagal reflex syndrome (VVRS) is common in the patients undergoing percutaneous coronary intervention (PCI). However, prediction and prevention of the risk for the VVRS have not been completely fulfilled. This study was conducted to develop a Risk Prediction Score Model to identify the determinants of VVRS in a large Chinese population cohort receiving PCI. From the hospital electronic medical database, we identified 3550 patients who received PCI (78.0% males, mean age 60 years) in Chinese PLA General Hospital from January 1, 2000 to August 30, 2016. The multivariate analysis and receiver operating characteristic (ROC) analysis were performed. The adverse events of VVRS in the patients were significantly increased after PCI procedure than before the operation (all P PCI was 4.5% (4.1%-5.6%). Compared to the patients suffering no VVRS, incidence of VVRS involved the following factors, namely female gender, primary PCI, hypertension, over two stents implantation in the left anterior descending (LAD), and the femoral puncture site. The multivariate analysis suggested that they were independent risk factors for predicting the incidence of VVRS (all P PCI (c-statistic 0.76, 95% CI: 0.72-0.79, P PCI whose diastolic blood pressure dropped by more than 30 mmHg and heart rate reduced by 10 times per minute (AUC: 0.84, 95% CI: 0.81-0.87, P PCI. In which, the following factors may be involved, the femoral puncture site, female gender, hypertension, primary PCI, and over 2 stents implanted in LAD.

Predictive value of diminutive colonic adenoma trial: the PREDICT trial.

Science.gov (United States)

Schoenfeld, Philip; Shad, Javaid; Ormseth, Eric; Coyle, Walter; Cash, Brooks; Butler, James; Schindler, William; Kikendall, Walter J; Furlong, Christopher; Sobin, Leslie H; Hobbs, Christine M; Cruess, David; Rex, Douglas

2003-05-01

Diminutive adenomas (1-9 mm in diameter) are frequently found during colon cancer screening with flexible sigmoidoscopy (FS). This trial assessed the predictive value of these diminutive adenomas for advanced adenomas in the proximal colon. In a multicenter, prospective cohort trial, we matched 200 patients with normal FS and 200 patients with diminutive adenomas on FS for age and gender. All patients underwent colonoscopy. The presence of advanced adenomas (adenoma >or= 10 mm in diameter, villous adenoma, adenoma with high grade dysplasia, and colon cancer) and adenomas (any size) was recorded. Before colonoscopy, patients completed questionnaires about risk factors for adenomas. The prevalence of advanced adenomas in the proximal colon was similar in patients with diminutive adenomas and patients with normal FS (6% vs. 5.5%, respectively) (relative risk, 1.1; 95% confidence interval [CI], 0.5-2.6). Diminutive adenomas on FS did not accurately predict advanced adenomas in the proximal colon: sensitivity, 52% (95% CI, 32%-72%); specificity, 50% (95% CI, 49%-51%); positive predictive value, 6% (95% CI, 4%-8%); and negative predictive value, 95% (95% CI, 92%-97%). Male gender (odds ratio, 1.63; 95% CI, 1.01-2.61) was associated with an increased risk of proximal colon adenomas. Diminutive adenomas on sigmoidoscopy may not accurately predict advanced adenomas in the proximal colon.

Predictive modeling of complications.

Science.gov (United States)

Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

2016-09-01

Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

An assessment of historical Antarctic precipitation and temperature trend using CMIP5 models and reanalysis datasets

Science.gov (United States)

Tang, Malcolm S. Y.; Chenoli, Sheeba Nettukandy; Samah, Azizan Abu; Hai, Ooi See

2018-03-01

The study of Antarctic precipitation has attracted a lot of attention recently. The reliability of climate models in simulating Antarctic precipitation, however, is still debatable. This work assess the precipitation and surface air temperature (SAT) of Antarctica (90 oS to 60 oS) using 49 Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models and the European Centre for Medium-range Weather Forecasts "Interim" reanalysis (ERA-Interim); the National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR); the Japan Meteorological Agency 55-year Reanalysis (JRA-55); and the Modern Era Retrospective-analysis for Research and Applications (MERRA) datasets for 1979-2005 (27 years). For precipitation, the time series show that the MERRA and JRA-55 have significantly increased from 1979 to 2005, while the ERA-Int and CFSR have insignificant changes. The reanalyses also have low correlation with one another (generally less than +0.69). 37 CMIP5 models show increasing trend, 18 of which are significant. The resulting CMIP5 MMM also has a significant increasing trend of 0.29 ± 0.06 mm year-1. For SAT, the reanalyses show insignificant changes and have high correlation with one another, while the CMIP5 MMM shows a significant increasing trend. Nonetheless, the variability of precipitation and SAT of MMM could affect the significance of its trend. One of the many reasons for the large differences of precipitation is the CMIP5 models' resolution.

Predictive Capability Maturity Model for computational modeling and simulation.

Energy Technology Data Exchange (ETDEWEB)

Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

2007-10-01

The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

Efficacy of aprons equivalent to 0.5 mm of lead in PET procedures using the Monte Carlo method

International Nuclear Information System (INIS)

Fonseca, R.B.; Amaral, A.; Campos, L.

2012-01-01

In positron emission tomography (PET), health staff is exposed to 511-keV photons, which is a result of the positron annihilation process. This energy is about four times greater than the 140 keV commonly found in studies based on single photon emission computed tomography (SPECT). Besides this different level of energy, 0.5 mm lead-equivalent aprons have being used either in SPECT or PET procedures. In this context, this work was designed for evaluating the effectiveness of such aprons in individual radioprotection of health professionals involved in positron emission tomography. For this, by using MCNP4C-based Monte Carlo simulations, the average energy delivered per particle to the regions corresponding to operational quantities Hp(10) and Hp(0.07) were calculated for two conditions of individual exposures: wearing and not wearing a 0.05 mm lead-equivalent apron. The results obtained pointed out that Hp(10) has similar value in both situations. On the other hand, for the region corresponding to Hp(0.07), wearing this lead apron will improve this dose in about 26%. On the basis of this work, 0.5 mm lead equivalent aprons do not offer adequate protection for medical staff working on positron emission tomography. (author)

Tumor motion prediction with the diaphragm as a surrogate: a feasibility study

International Nuclear Information System (INIS)

Cervino, Laura I; Jiang Yan; Sandhu, Ajay; Jiang, Steve B

2010-01-01

We have previously assessed the use of the diaphragm as a surrogate for predicting real-time tumor position with linear models built with training data extracted from the same treatment fraction (Cervino et al 2009 Phys. Med. Biol. 54 3529-41). However, practical use in the clinical setting requires the capability of predicting tumor position throughout the treatment course using a model built at the beginning of the course. We evaluate the inter-fraction applicability of linear models to predict superior-inferior tumor position based on diaphragm position using 21 fluoroscopic sequences from five lung cancer patients. Tumor position is predicted with models built during the first fluoroscopic sequence of each patient. Other fluoroscopic sets are registered to the first set with five different methods. The mean localization prediction error and maximum error at a 95% confidence level averaged over all patients are found to be 1.2 mm and 2.9 mm, respectively, for bony registration and 1.2 mm and 2.8 mm, respectively, for registration based on the mean position of the tumor in the first two breathing cycles. Other registration methods produce larger prediction errors. In the clinical setting, this prediction error could be added as a margin to the target volume. We therefore conclude that it is feasible to predict lung tumor motion with diaphragm with sufficient accuracy in the clinical setting. (note)

Assessment and improvement of condensation models in RELAP5/MOD3.2

Energy Technology Data Exchange (ETDEWEB)

Choi, Ki Yong; Park, Hyun Sik; Kim, Sang Jae; No, Hee Chen [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1998-12-31

The condensation models in the standard RELAP5/MOD3.2 code are assessed and improved based on the database, which is constructed from the previous experimental data on various condensation phenomena. The default model of the laminar film condensation in RELAP5/MOD3.2 does not give any reliable predictions, and its alternative model always predicts higher values than the experimental data. Therefore, it is needed to develop a new correlation based on the experimental data of various operating ranges in the constructed database. The Shah correlation, which is used to calculate the turbulent film condensation heat transfer coefficients in the standard RELAP5/MOD3.2, well predicts the experimental data in the database. The horizontally stratified condensation model of RELAP5/MOD3.2 overpredicts both cocurrent and countercurrent experimental data. The correlation proposed by H.J.Kim predicts the database relatively well compared with that of RELAP6/MOD3.2. The RELAP5/MOD3.2 model should use the liquid velocity for the calculation of the liquid Reynolds number and be modified to consider the effects of the gas velocity and the film thickness. 2 refs., 5 figs., 1 tab. (Author)

Assessment and improvement of condensation models in RELAP5/MOD3.2

Energy Technology Data Exchange (ETDEWEB)

Choi, Ki Yong; Park, Hyun Sik; Kim, Sang Jae; No, Hee Chen [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1997-12-31

The condensation models in the standard RELAP5/MOD3.2 code are assessed and improved based on the database, which is constructed from the previous experimental data on various condensation phenomena. The default model of the laminar film condensation in RELAP5/MOD3.2 does not give any reliable predictions, and its alternative model always predicts higher values than the experimental data. Therefore, it is needed to develop a new correlation based on the experimental data of various operating ranges in the constructed database. The Shah correlation, which is used to calculate the turbulent film condensation heat transfer coefficients in the standard RELAP5/MOD3.2, well predicts the experimental data in the database. The horizontally stratified condensation model of RELAP5/MOD3.2 overpredicts both cocurrent and countercurrent experimental data. The correlation proposed by H.J.Kim predicts the database relatively well compared with that of RELAP6/MOD3.2. The RELAP5/MOD3.2 model should use the liquid velocity for the calculation of the liquid Reynolds number and be modified to consider the effects of the gas velocity and the film thickness. 2 refs., 5 figs., 1 tab. (Author)

Improvement of the RELAP5 subcooled boiling model for low pressure conditions

International Nuclear Information System (INIS)

Koncar, B.; Mavko, B.

2000-01-01

The RELAP5/MOD3.2.2 Gamma code was assessed against low pressure subcooled boiling experiments performed by Zeitoun and Shoukri [1] in a vertical annulus. The predictions of subcooled boiling bubbly flow showed that the present version of the RELAP5 code underestimates the void fraction growth along the tube. To improve the void fraction prediction at low pressure conditions a set of model changes is proposed, which includes modifications of bubbly-slug transition criterion, drift-flux model, interphase heat transfer coefficient and wall evaporation modeling. The improved experiment predictions with the modified RELAP5 code are presented and analysed. (author)

Experimental characteristics of a high-gain free-electron laser amplifier operating at 8-mm and 2-mm wavelengths

International Nuclear Information System (INIS)

Throop, A.L.; Orzechowski, T.J.; Anderson, B.R.

1987-01-01

The Electron Laser Facility (ELF) at the Lawrence Livermore National Laboratory (LLNL) uses a high-current induction linac (3.5 MeV, 1000 A), in conjunction with a pulsed electromagnetic wiggler (4.0 M, 4000 G), to operate a free electron laser (FEL) that produces intense radiation in the microwave regime (2 to 8 mm). ELF is a high-gain, single-pass amplifier, using a commercial microwave source as an oscillator input (200 W-50 kW). Previous experiments at 35 GHz produced exponential gains of 40 dB/m, peak powers exceeding 1 GW, and beam-to-rf conversion efficiencies of 34%. Recent experiments at 140 GHz have demonstrated exponential gains of 22 dB/m, peak powers exceeding 50 MW, and total gains of 65 dB. In this paper, we describe the experimental results at these two frequencies and compare then with the predictions of simulation codes

Babcock and Wilcox model for predicting in-reactor densification

International Nuclear Information System (INIS)

Buescher, B.J.; Pegram, J.W.

1975-06-01

The B and W fuel densification model is used to describe the extent and kinetics of in-reactor densification in B and W production fuel. The model and approach are qualified against an extensive data base available through B and W's participation in the EEI Fuel Densification Program. Out-of-reactor resintering tests on representative pellets from each batch of fuel are used to provide input parameters to the B and W densification model. The B and W densification model predicts in-reactor densification very accurately for pellets operated at heat rates above 5 kW/ft and with considerable conservation for pellets operated at heat rates less than 5 kW/ft. This model represents a technically rigorous and conservative basis for predicting the extent and kinetics of in-reactor densification. 9 references. (U.S.)

Flipped SU(5) predicts {delta}T/T

Energy Technology Data Exchange (ETDEWEB)

Kyae, Bumseok [School of Physics, Korea Institute for Advanced Study, 207-43, Cheongnyangni-Dong, Dongdaemun-Gu, Seoul 130-722 (Korea, Republic of)]. E-mail: bkyae@kias.re.kr; Shafi, Qaisar [Bartol Research Institute, Department of Physics and Astronomy, University of Delaware, Newark, DE 19716 (United States)]. E-mail: shafi@bartol.udel.edu

2006-04-20

We discuss hybrid inflation in supersymmetric flipped SU(5) model such that the cosmic microwave anisotropy {delta}T/T is essentially proportional to (M/M{sub P}){sup 2}, where M denotes the symmetry breaking scale and M{sub P} (=2.4x10{sup 18} GeV) is the reduced Planck mass. The magnitude of M determined from {delta}T/T measurements can be consistent with the value inferred from the evolution of SU(3) and SU(2) gauge couplings. In other words, one could state that flipped SU(5) predicts (more precisely 'postdicts') {delta}T/T. The scalar spectral index n{sub s}=0.993+/-0.007, the scalar to tensor ratio satisfies r-bar 10{sup -6}, while dn{sub s}/dlnk-bar 4x10{sup -4}.

Comparison of 2D and 3D modeled tumor motion estimation/prediction for dynamic tumor tracking during arc radiotherapy

Science.gov (United States)

Liu, Wu; Ma, Xiangyu; Yan, Huagang; Chen, Zhe; Nath, Ravinder; Li, Haiyun

2017-05-01

Many real-time imaging techniques have been developed to localize a target in 3D space or in a 2D beam’s eye view (BEV) plane for intrafraction motion tracking in radiation therapy. With tracking system latency, the 3D-modeled method is expected to be more accurate even in terms of 2D BEV tracking error. No quantitative analysis, however, has been reported. In this study, we simulated co-planar arc deliveries using respiratory motion data acquired from 42 patients to quantitatively compare the accuracy between 2D BEV and 3D-modeled tracking in arc therapy and to determine whether 3D information is needed for motion tracking. We used our previously developed low kV dose adaptive MV-kV imaging and motion compensation framework as a representative of 3D-modeled methods. It optimizes the balance between additional kV imaging dose and 3D tracking accuracy and solves the MLC blockage issue. With simulated Gaussian marker detection errors (zero mean and 0.39 mm standard deviation) and ~155/310/460 ms tracking system latencies, the mean percentage of time that the target moved  >2 mm from the predicted 2D BEV position are 1.1%/4.0%/7.8% and 1.3%/5.8%/11.6% for the 3D-modeled and 2D-only tracking, respectively. The corresponding average BEV RMS errors are 0.67/0.90/1.13 mm and 0.79/1.10/1.37 mm. Compared to the 2D method, the 3D method reduced the average RMS unresolved motion along the beam direction from ~3 mm to ~1 mm, resulting in on average only  <1% dosimetric advantage in the depth direction. Only for a small fraction of the patients, when tracking latency is long, the 3D-modeled method showed significant improvement of BEV tracking accuracy, indicating potential dosimetric advantage. However, if the tracking latency is short (~150 ms or less), those improvements are limited. Therefore, 2D BEV tracking has sufficient targeting accuracy for most clinical cases. The 3D technique is, however, still important in solving the MLC blockage problem

Assessment of delta ferrite in multipass TIG welds of 40 mm thick SS 316L: A comparative study of ferrite number (FN) prediction and measurements

Science.gov (United States)

Buddu, Ramesh Kumar; Raole, P. M.; Sarkar, B.

2017-04-01

Austenitic stainless steels are widely used in the fabrication of fusion reactor major systems like vacuum vessel, divertor, cryostat and other structural components development. Multipass welding is used for the development of thick plates for the structural components fabrication. Due to the repeated weld thermal cycles, the microstructure adversely alters owing to the presence of complex phases like austenite, ferrite and delta ferrite and subsequently influences the mechanical properties like tensile and impact toughness of joints. The present paper reports the detail analysis of delta ferrite phase in welded region of 40 mm thick SS316L plates welded by special design multipass narrow groove TIG welding process under three different heat input conditions. The correlation of delta ferrite microstructure of different type structures acicular and vermicular is observed. The chemical composition of weld samples was used to predict the Ferrite Number (FN), which is representative form of delta ferrite in welds, with Schaeffler’s, WRC-1992 diagram and DeLong techniques by calculating the Creq and Nieq ratios and compared with experimental data of FN from Feritescope measurements. The low heat input conditions (1.67 kJ/mm) have produced higher FN (7.28), medium heat input (1.72 kJ/mm) shown FN (7.04) where as high heat input (1.87 kJ/mm) conditions has shown FN (6.68) decreasing trend and FN data is compared with the prediction methods.

Prediction of the mechanical properties of zeolite pellets for aerospace molecular decontamination applications

Directory of Open Access Journals (Sweden)

Guillaume Rioland

2016-11-01

Full Text Available Zeolite pellets containing 5 wt % of binder (methylcellulose or sodium metasilicate were formed with a hydraulic press. This paper describes a mathematical model to predict the mechanical properties (uniaxial and diametric compression of these pellets for arbitrary dimensions (height and diameter using a design of experiments (DOE methodology. A second-degree polynomial equation including interactions was used to approximate the experimental results. This leads to an empirical model for the estimation of the mechanical properties of zeolite pellets with 5 wt % of binder. The model was verified by additional experimental tests including pellets of different dimensions created with different applied pressures. The optimum dimensions were found to be a diameter of 10–23 mm, a height of 1–3.5 mm and an applied pressure higher than 200 MPa. These pellets are promising for technological uses in molecular decontamination for aerospace-based applications.

Simulation of 1.5-mm-thick and 15-cm-diameter gated silicon drift X-ray detector operated with a single high-voltage source

Science.gov (United States)

Matsuura, Hideharu

2015-04-01

High-resolution silicon X-ray detectors with a large active area are required for effectively detecting traces of hazardous elements in food and soil through the measurement of the energies and counts of X-ray fluorescence photons radially emitted from these elements. The thicknesses and areas of commercial silicon drift detectors (SDDs) are up to 0.5 mm and 1.5 cm2, respectively. We describe 1.5-mm-thick gated SDDs (GSDDs) that can detect photons with energies up to 50 keV. We simulated the electric potential distributions in GSDDs with a Si thickness of 1.5 mm and areas from 0.18 to 168 cm2 at a single high reverse bias. The area of a GSDD could be enlarged simply by increasing all the gate widths by the same multiple, and the capacitance of the GSDD remained small and its X-ray count rate remained high.

Non-isothermal kinetics model to predict accurate phase transformation and hardness of 22MnB5 boron steel

Energy Technology Data Exchange (ETDEWEB)

Bok, H.-H.; Kim, S.N.; Suh, D.W. [Graduate Institute of Ferrous Technology, POSTECH, San 31, Hyoja-dong, Nam-gu, Pohang, Gyeongsangbuk-do (Korea, Republic of); Barlat, F., E-mail: f.barlat@postech.ac.kr [Graduate Institute of Ferrous Technology, POSTECH, San 31, Hyoja-dong, Nam-gu, Pohang, Gyeongsangbuk-do (Korea, Republic of); Lee, M.-G., E-mail: myounglee@korea.ac.kr [Department of Materials Science and Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul (Korea, Republic of)

2015-02-25

A non-isothermal phase transformation kinetics model obtained by modifying the well-known JMAK approach is proposed for application to a low carbon boron steel (22MnB5) sheet. In the modified kinetics model, the parameters are functions of both temperature and cooling rate, and can be identified by a numerical optimization method. Moreover, in this approach the transformation start and finish temperatures are variable instead of the constants that depend on chemical composition. These variable reference temperatures are determined from the measured CCT diagram using dilatation experiments. The kinetics model developed in this work captures the complex transformation behavior of the boron steel sheet sample accurately. In particular, the predicted hardness and phase fractions in the specimens subjected to a wide range of cooling rates were validated by experiments.

A simple model for the prediction of thermal conductivity of Ge2Sb2Te5 thin film

International Nuclear Information System (INIS)

Jin, Jae Sik

2013-01-01

A modified version of the Mayadas-Shatzkes (MS) model is proposed for the prediction of the thermal conductivity of both amorphous and crystalline of Ge 2 Sb 2 Te 5 (GST) phase-change materials at room temperature. The structural parameters of the original MS model are extended to describe the additional disorder scattering effects caused by the ternary components of the GST. The effect of disorder due to the alloy composition on the grain boundary scattering can be interpreted with the aid of thermal models. It is also found that for all phases of GST, the contribution of disorder scattering to the thermal resistance is nearly uniform. This is consistent with the fact that the GST phase changes without any destruction of the structural basis such as the building blocks.

Candidate Prediction Models and Methods

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

2005-01-01

This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

The association of LUR modeled PM2.5 elemental composition with personal exposure

International Nuclear Information System (INIS)

Montagne, Denise; Hoek, Gerard; Nieuwenhuijsen, Mark; Lanki, Timo; Pennanen, Arto; Portella, Meritxell; Meliefste, Kees; Wang, Meng; Eeftens, Marloes; Yli-Tuomi, Tarja; Cirach, Marta; Brunekreef, Bert

2014-01-01

Background and aims: Land use regression (LUR) models predict spatial variation of ambient concentrations, but little is known about the validity in predicting personal exposures. In this study, the association of LUR modeled concentrations of PM 2.5 components with measured personal concentrations was determined. The elements of interest were copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn). Methods: In Helsinki (Finland), Utrecht (the Netherlands) and Barcelona (Spain) five participants from urban background, five from suburban background and five from busy street sites were selected in each city (15 participants per city). Outdoor, indoor and personal 96-hour PM 2.5 samples were collected by the participants over periods of two weeks in three different seasons (winter, summer and spring/autumn) and the overall average was calculated. Elemental composition was measured by ED-XRF spectrometry. The LUR models for the average ambient concentrations of each element were developed by the ESCAPE project. Results: LUR models predicted the within-city variation of average outdoor Cu and Fe concentrations moderately well (range in R 2 27–67% for Cu and 24–54% for Fe). The outdoor concentrations of the other elements were not well predicted. The LUR modeled concentration only significantly correlated with measured personal Fe exposure in Utrecht and Ni and V in Helsinki. The LUR model predictions did not correlate with measured personal Cu exposure. After excluding observations with an indoor/outdoor ratio of > 1.5, modeled Cu outdoor concentrations correlated with indoor concentrations in Helsinki and Utrecht and personal concentrations in Utrecht. The LUR model predictions were associated with measured outdoor, indoor and personal concentrations for all elements when the data for the three cities was pooled. Conclusions: Within-city modeled variation of elemental composition of PM 2.5 did not predict measured

Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

Directory of Open Access Journals (Sweden)

Okokpujie Imhade Princess

2017-12-01

Full Text Available In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N, feed rate (f, axial depth of cut (a and radial depth of cut (r. The experiment was designed using central composite design (CCD in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM. The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

Science.gov (United States)

Okokpujie, Imhade Princess; Ikumapayi, Omolayo M.; Okonkwo, Ugochukwu C.; Salawu, Enesi Y.; Afolalu, Sunday A.; Dirisu, Joseph O.; Nwoke, Obinna N.; Ajayi, Oluseyi O.

2017-12-01

In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

Wind power prediction models

Science.gov (United States)

Levy, R.; Mcginness, H.

1976-01-01

Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

Hafnium Films and Magnetic Shielding for TIME, A mm-Wavelength Spectrometer Array

Science.gov (United States)

Hunacek, J.; Bock, J.; Bradford, C. M.; Butler, V.; Chang, T.-C.; Cheng, Y.-T.; Cooray, A.; Crites, A.; Frez, C.; Hailey-Dunsheath, S.; Hoscheit, B.; Kim, D. W.; Li, C.-T.; Marrone, D.; Moncelsi, L.; Shirokoff, E.; Steinbach, B.; Sun, G.; Trumper, I.; Turner, A.; Uzgil, B.; Weber, A.; Zemcov, M.

2018-04-01

TIME is a mm-wavelength grating spectrometer array that will map fluctuations of the 157.7-μm emission line of singly ionized carbon ([CII]) during the epoch of reionization (redshift z ˜ 5-9). Sixty transition-edge sensor (TES) bolometers populate the output arc of each of the 32 spectrometers, for a total of 1920 detectors. Each bolometer consists of gold absorber on a ˜ 3 × 3 mm silicon nitride micro-mesh suspended near the corners by 1 × 1 × 500 μm silicon nitride legs targeting a photon-noise-dominated NEP ˜ 1 × 10^{-17} W/√{Hz} . Hafnium films are explored as a lower-T_c alternative to Ti (500 mK) for TIME TESs, allowing thicker support legs for improved yield. Hf T_c is shown to vary between 250 and 450 mK when varying the resident Ar pressure during deposition. Magnetic shielding designs and simulations are presented for the TIME first-stage SQUIDs. Total axial field suppression is predicted to be 5 × 10^7.

Genomic prediction in a nuclear population of layers using single-step models.

Science.gov (United States)

Yan, Yiyuan; Wu, Guiqin; Liu, Aiqiao; Sun, Congjiao; Han, Wenpeng; Li, Guangqi; Yang, Ning

2018-02-01

Single-step genomic prediction method has been proposed to improve the accuracy of genomic prediction by incorporating information of both genotyped and ungenotyped animals. The objective of this study is to compare the prediction performance of single-step model with a 2-step models and the pedigree-based models in a nuclear population of layers. A total of 1,344 chickens across 4 generations were genotyped by a 600 K SNP chip. Four traits were analyzed, i.e., body weight at 28 wk (BW28), egg weight at 28 wk (EW28), laying rate at 38 wk (LR38), and Haugh unit at 36 wk (HU36). In predicting offsprings, individuals from generation 1 to 3 were used as training data and females from generation 4 were used as validation set. The accuracies of predicted breeding values by pedigree BLUP (PBLUP), genomic BLUP (GBLUP), SSGBLUP and single-step blending (SSBlending) were compared for both genotyped and ungenotyped individuals. For genotyped females, GBLUP performed no better than PBLUP because of the small size of training data, while the 2 single-step models predicted more accurately than the PBLUP model. The average predictive ability of SSGBLUP and SSBlending were 16.0% and 10.8% higher than the PBLUP model across traits, respectively. Furthermore, the predictive abilities for ungenotyped individuals were also enhanced. The average improvements of prediction abilities were 5.9% and 1.5% for SSGBLUP and SSBlending model, respectively. It was concluded that single-step models, especially the SSGBLUP model, can yield more accurate prediction of genetic merits and are preferable for practical implementation of genomic selection in layers. © 2017 Poultry Science Association Inc.

Estimation of position resolution for DOI-PET detector using diameter 0.2 mm WLS fibers [ANIMMA--2015-IO-x5

International Nuclear Information System (INIS)

Kaneko, Naomi; Ito, H.; Han, S.; Kawai, H.; Kodama, S.; Kobayashi, A.; Tabata, M.; Kamada, K.; Shoji, Y.; Yoshikawa, A.

2015-01-01

We have been developing a submillimeter resolution and low-cost DOI-PET detector using wavelength shifting fibers (WLSF), scintillating crystal plates and MPPCs (Hamamatsu Photonics). Conventional design of DOI-PET detectors had approximately mm 3 of resolution by using some scintillating blocks with a volume of 1 mm 3 , which detects gamma-ray. They are expensive due to difficulties in processing scintillating crystals and a large number of photo-detectors, and these technologies are likely to reach the limit of the resolution. Development of a lower cost DOI-PET detector with higher resolution is challenging to popularize the PET diagnosis. We propose two type of PET detector. One is a whole body PET system, and the other is a PET system for brain or small animals. Each PET system consists 6 blocks. The former consists of 6 layers of crystal plates with 300 mm x 300 mm x 4 mm. The latter consists of 16 crystal layers, forming 4 x 4 crystal arrays. The size of the crystal plate is 40 mm x 40 mm x 1 mm. Wavelength shifting fiber (WLSF) sheets are attached to above and up and down side of crystal planes. The whole PET system has 8 MPPCs attached on each side. For the brain PET detector, 9 WLSF fibers are attached on the each side. The expected position resolution would be less than 1 mm at the former system. We have performed an experimental performance estimation for the system component using 22 Na radioactive source. We achieved a collection efficiency of 10% using the WLSF sheet and Ce:Gd 3 (Al,Ga) 5 O 12 (GAGG) crystals at 511 keV. The linear relationship between reconstruction position and incident position was obtained, and a resolution of 0.7 mm (FWHM) for x-axis of DOI by the WLSF readout was achieved. (authors)

SiGe BiCMOS manufacturing platform for mmWave applications

Science.gov (United States)

Kar-Roy, Arjun; Howard, David; Preisler, Edward; Racanelli, Marco; Chaudhry, Samir; Blaschke, Volker

2010-10-01

TowerJazz offers high volume manufacturable commercial SiGe BiCMOS technology platforms to address the mmWave market. In this paper, first, the SiGe BiCMOS process technology platforms such as SBC18 and SBC13 are described. These manufacturing platforms integrate 200 GHz fT/fMAX SiGe NPN with deep trench isolation into 0.18μm and 0.13μm node CMOS processes along with high density 5.6fF/μm2 stacked MIM capacitors, high value polysilicon resistors, high-Q metal resistors, lateral PNP transistors, and triple well isolation using deep n-well for mixed-signal integration, and, multiple varactors and compact high-Q inductors for RF needs. Second, design enablement tools that maximize performance and lowers costs and time to market such as scalable PSP and HICUM models, statistical and Xsigma models, reliability modeling tools, process control model tools, inductor toolbox and transmission line models are described. Finally, demonstrations in silicon for mmWave applications in the areas of optical networking, mobile broadband, phased array radar, collision avoidance radar and W-band imaging are listed.

Inverse and Predictive Modeling

Energy Technology Data Exchange (ETDEWEB)

Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-27

The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

Extracting dimer structures from simulations of organic-based materials using QM/MM methods

Energy Technology Data Exchange (ETDEWEB)

Pérez-Jiménez, A.J., E-mail: aj.perez@ua.es; Sancho-García, J.C., E-mail: jc.sancho@ua.es

2015-09-28

Highlights: • DFT geometries of isolated dimers in organic crystals differ from experimental ones. • This can be corrected using QM/MM geometry optimizations. • The QM = B3LYP–D3(ZD)/cc-pVDZ and MM = GAFF combination works reasonably well. - Abstract: The functionality of weakly bound organic materials, either in Nanoelectronics or in Materials Science, is known to be strongly affected by their morphology. Theoretical predictions of the underlying structure–property relationships are frequently based on calculations performed on isolated dimers, but the optimized structure of the latter may significantly differ from experimental data even when dispersion-corrected methods are used for it. Here, we address this problem on two organic crystals, namely coronene and 5,6,11,12-tetrachlorotetracene, concluding that it is caused by the absence of the surrounding monomers present in the crystal, and that it can be efficiently cured when the dimer is embedded into a general Quantum Mechanics/Molecular Mechanics (QM/MM) geometry optimization scheme. We also investigate how the size of the MM region affects the results. These findings may be helpful for the simulation of the morphology of active materials in crystalline or glassy samples.

Linear sign in cystic brain lesions ≥5 mm: A suggestive feature of perivascular space.

Science.gov (United States)

Sung, Jinkyeong; Jang, Jinhee; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-Soo

2017-11-01

To determine the prevalence of a linear sign within enlarged perivascular space (EPVS) and chronic lacunar infarction (CLI) ≥ 5 mm on T2-weighted imaging (T2WI) and time-of-flight (TOF) magnetic resonance angiography (MRA), and to evaluate the diagnostic value of the linear signs for EPVS over CLI. This study included 101 patients with cystic lesions ≥ 5 mm on brain MRI including TOF MRA. After classification of cystic lesions into EPVS or CLI, two readers assessed linear signs on T2WI and TOF MRA. We compared the prevalence and the diagnostic performance of linear signs. Among 46 EPVS and 51 CLI, 84 lesions (86.6%) were in basal ganglia. The prevalence of T2 and TOF linear signs was significantly higher in the EPVS than in the CLI (P linear signs showed high sensitivity (> 80%). TOF linear sign showed significantly higher specificity (100%) and accuracy (92.8% and 90.7%) than T2 linear sign (P linear signs were more frequently observed in EPVS than CLI. They showed high sensitivity in differentiation of them, especially for basal ganglia. TOF sign showed higher specificity and accuracy than T2 sign. • Linear sign is a suggestive feature of EPVS. • Time-of-flight magnetic resonance angiography can reveal the lenticulostriate artery within perivascular spaces. • Linear sign helps differentiation of EPVS and CLI, especially in basal ganglia.

Prediction Model for Gastric Cancer Incidence in Korean Population.

Directory of Open Access Journals (Sweden)

Bang Wool Eom

Full Text Available Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea.Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell's C-statistics, and the calibration was evaluated using a calibration plot and slope.During a median of 11.4 years of follow-up, 19,465 (1.4% and 5,579 (0.7% newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women.In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance.

Archaeological predictive model set.

Science.gov (United States)

2015-03-01

This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

Model predictive control of a wind turbine modelled in Simpack

International Nuclear Information System (INIS)

Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

2014-01-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

Model predictive control of a wind turbine modelled in Simpack

Science.gov (United States)

Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

2014-06-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

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

Science.gov (United States)

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

2017-09-01

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.

Discovery of a Highly Potent, Cell-Permeable Macrocyclic Peptidomimetic (MM-589) Targeting the WD Repeat Domain 5 Protein (WDR5)–Mixed Lineage Leukemia (MLL) Protein–Protein Interaction

Energy Technology Data Exchange (ETDEWEB)

Karatas, Hacer; Li, Yangbing; Liu, Liu; Ji, Jiao; Lee, Shirley; Chen, Yong; Yang, Jiuling; Huang, Liyue; Bernard, Denzil; Xu, Jing; Townsend, Elizabeth C.; Cao, Fang; Ran, Xu; Li, Xiaoqin; Wen, Bo; Sun, Duxin; Stuckey, Jeanne A; Lei, Ming; Dou, Yali; Wang, Shaomeng (Michigan)

2017-06-06

We report herein the design, synthesis, and evaluation of macrocyclic peptidomimetics that bind to WD repeat domain 5 (WDR5) and block the WDR5–mixed lineage leukemia (MLL) protein–protein interaction. Compound 18 (MM-589) binds to WDR5 with an IC50 value of 0.90 nM (Ki value <1 nM) and inhibits the MLL H3K4 methyltransferase (HMT) activity with an IC50 value of 12.7 nM. Compound 18 potently and selectively inhibits cell growth in human leukemia cell lines harboring MLL translocations and is >40 times better than the previously reported compound MM-401. Cocrystal structures of 16 and 18 complexed with WDR5 provide structural basis for their high affinity binding to WDR5. Additionally, we have developed and optimized a new AlphaLISA-based MLL HMT functional assay to facilitate the functional evaluation of these designed compounds. Compound 18 represents the most potent inhibitor of the WDR5–MLL interaction reported to date, and further optimization of 18 may yield a new therapy for acute leukemia.

Overview of Millimeter Wave Communications for Fifth-Generation (5G) Wireless Networks—With a Focus on Propagation Models

Science.gov (United States)

Rappaport, Theodore S.; Xing, Yunchou; MacCartney, George R.; Molisch, Andreas F.; Mellios, Evangelos; Zhang, Jianhua

2017-12-01

This paper provides an overview of the features of fifth generation (5G) wireless communication systems now being developed for use in the millimeter wave (mmWave) frequency bands. Early results and key concepts of 5G networks are presented, and the channel modeling efforts of many international groups for both licensed and unlicensed applications are described here. Propagation parameters and channel models for understanding mmWave propagation, such as line-of-sight (LOS) probabilities, large-scale path loss, and building penetration loss, as modeled by various standardization bodies, are compared over the 0.5-100 GHz range.

A lithographically patterned capacitor with horizontal nanowires of length 2.5 mm.

Science.gov (United States)

Yan, Wenbo; Thai, Mya Le; Dutta, Rajen; Li, Xiaowei; Xing, Wendong; Penner, Reginald M

2014-04-09

A symmetrical hybrid capacitor consisting of interdigitated, horizontal nanowires is described. Each of the 750 nanowires within the capacitor is 2.5 mm in length, consisting of a gold nanowire core (40 × ≈200 nm) encapsulated within a hemicylindrical shell of δ-phase MnO2 (thickness = 60-220 nm). These Au@δ-MnO2 nanowires are patterned onto a planar glass surface using lithographically patterned nanowire electrodeposition (LPNE). A power density of 165 kW/kg and energy density of 24 Wh/kg were obtained for a typical nanowire array in which the MnO2 shell thickness was 68 ± 8 nm. Capacitors incorporating these ultralong nanowires lost ≈10% of their capacity rapidly, during the first 20 discharge cycles, and then retained 90% of their maximum capacity for the ensuing 6000 cycles. The ability of capacitors consisting of ultralong Au@δ-MnO2 nanowires to simultaneously deliver high power and high capacity with acceptable cycle life is demonstrated.

Computational Modeling in Plasma Processing for 300 mm Wafers

Science.gov (United States)

Meyyappan, Meyya; Arnold, James O. (Technical Monitor)

1997-01-01

Migration toward 300 mm wafer size has been initiated recently due to process economics and to meet future demands for integrated circuits. A major issue facing the semiconductor community at this juncture is development of suitable processing equipment, for example, plasma processing reactors that can accomodate 300 mm wafers. In this Invited Talk, scaling of reactors will be discussed with the aid of computational fluid dynamics results. We have undertaken reactor simulations using CFD with reactor geometry, pressure, and precursor flow rates as parameters in a systematic investigation. These simulations provide guidelines for scaling up in reactor design.

Study on distributions and recoveries of tetrachlorodibenzo-p-dioxin and octachlorodibenzo-p-dioxin in a mm5 sampling train

International Nuclear Information System (INIS)

Finkel, J.M.; James, R.H.; Baughman, K.W.

1990-12-01

14 C-dioxin tracers were used to evaluate whole MM5 sampling train recoveries of dioxin and to determine the distribution of dioxins spiked into a sampling train that was concurrently sampling emissions from a burn of either natural gas ('clean' burn) or kerosene ('dirty' burn). The spike tests were made with a pilot-scale furnace constructed and operated in the laboratory. Recovery of 14 C-dioxin from the MM5 sampling train was determined by scintillation spectrometry. The experimental results indicate that the amount of spiked TCDD- 14 C recovered was approximately 85% during a natural gas test and 83% during a kerosene test. The amount of spiked OCDD- 14 C recovered was approximately 88% during a kerosene test. Also, the data indicate that during the kerosene tests OCDD- 14 C is collected primarily in the front half of the sampling train but TCDD- 14 C is often found in the XAD and the rear filter bell, riser and condenser of the sampling train. During the natural gas tests, TCDD- 14 C was primarily in the XAD. The distribution of the TCDD- 14 C in the kerosene tests was dependent on the rigid operation of the sampling train. The information from the study will be used to determine procedural areas that need improvements or modifications to allow the efficient collection and accurate determination of trace levels of dioxins and furans using the MM5 Method

A Model for Predicting Student Performance on High-Stakes Assessment

Science.gov (United States)

Dammann, Matthew Walter

2010-01-01

This research study examined the use of student achievement on reading and math state assessments to predict success on the science state assessment. Multiple regression analysis was utilized to test the prediction for all students in grades 5 and 8 in a mid-Atlantic state. The prediction model developed from the analysis explored the combined…

Confronting species distribution model predictions with species functional traits.

Science.gov (United States)

Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

2016-02-01

Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

Simulation and prediction the impact of climate change into water resources in Bengawan Solo watershed based on CCAM (Conformal Cubic Atmospheric Model) data

Science.gov (United States)

Sipayung, Sinta B.; Nurlatifah, Amalia; Siswanto, Bambang

2018-05-01

Bengawan Solo Watershed is one of the largest watersheds in Indonesia. This watershed flows in many areas both in Central Java and East Java. Therefore, the water resources condition greatly affects many people. This research will be conducted on prediction of climate change effect on water resources condition in terms of rainfall conditions in Bengawan Solo River Basin. The goal of this research is to know and predict the climate change impact on water resources based on CCAM (Conformal Cubic Atmosphere Model) with downscaling baseline (historical) model data from 1949 to 2005 and RCP 4.5 from 2006 to 2069. The modeling data was validated with in-situ data (measurement data). To analyse the water availability condition in Bengawan Solo Watershed, the simulation of river flow and water balance condition were done in Bengawan Solo River. Simulation of river flow and water balance conditions were done with ArcSWAT model using climate data from CCAM, DEM SRTM 90 meter, soil type, and land use data. The results of this simulation indicate there is (i) The CCAM data itself after validation has a pretty good result when compared to the insitu data. Based on CCAM simulation results, it is predicted that in 2040-2069 rainfall in Bengawan Solo River Basin will decrease, to a maximum of only about 1 mm when compared to 1971-2000. (ii) The CCAM rainfall prediction itself shows that rainfall in Bengawan Solo River basin will decline until 2069 although the decline itself is not significant and tends to be negligible (rainfall is considered unchanged) (iii) Both in the DJF and JJA seasons, precipitation is predicted to decline as well despite the significant decline. (iv) The river flow simulation show that the water resources in Bengawan Solo River did not change significantly. This event occurred because the rainfall also did not change greatly and close to 0 mm/month.

Minimal see-saw model predicting best fit lepton mixing angles

International Nuclear Information System (INIS)

King, Stephen F.

2013-01-01

We discuss a minimal predictive see-saw model in which the right-handed neutrino mainly responsible for the atmospheric neutrino mass has couplings to (ν e ,ν μ ,ν τ ) proportional to (0,1,1) and the right-handed neutrino mainly responsible for the solar neutrino mass has couplings to (ν e ,ν μ ,ν τ ) proportional to (1,4,2), with a relative phase η=−2π/5. We show how these patterns of couplings could arise from an A 4 family symmetry model of leptons, together with Z 3 and Z 5 symmetries which fix η=−2π/5 up to a discrete phase choice. The PMNS matrix is then completely determined by one remaining parameter which is used to fix the neutrino mass ratio m 2 /m 3 . The model predicts the lepton mixing angles θ 12 ≈34 ∘ ,θ 23 ≈41 ∘ ,θ 13 ≈9.5 ∘ , which exactly coincide with the current best fit values for a normal neutrino mass hierarchy, together with the distinctive prediction for the CP violating oscillation phase δ≈106 ∘

Flow Test to Predict Early Hypotony and Hypertensive Phase After Ahmed Glaucoma Valve (AGV) Surgical Implantation.

Science.gov (United States)

Cheng, Jason; Beltran-Agullo, Laura; Buys, Yvonne M; Moss, Edward B; Gonzalez, Johanna; Trope, Graham E

2016-06-01

To assess the validity of a preimplantation flow test to predict early hypotony [intraocular pressure (IOP)≤5 mm Hg on 2 consecutive visits and hypertensive phase (HP) (IOP>21 mm Hg) after Ahmed Glaucoma Valve (AGV) implantation. Prospective interventional study on patients receiving an AGV. A preimplantation flow test using a gravity-driven reservoir and an open manometer was performed on all AGVs. Opening pressure (OP) and closing pressure (CP) were defined as the pressure at which fluid was seen to flow or stop flowing through the AGV, respectively. OP and CP were measured twice per AGV. Patients were followed for 12 weeks. In total, 20 eyes from 19 patients were enrolled. At 12 weeks the mean IOP decreased from 29.2±9.1 to 16.8±5.2 mm Hg (P<0.01). The mean AGV OP was 17.5±5.4 mm Hg and the mean CP was 6.7±2.3 mm Hg. Early (within 2 wk postoperative) HP occurred in 37% and hypotony in 16% of cases. An 18 mm Hg cutoff for the OP gave a sensitivity of 0.71, specificity of 0.83, positive predictive value of 0.71, and negative predictive value of 0.83 for predicting an early HP. A 7 mm Hg cutoff for the CP yielded a sensitivity of 1.0, specificity of 0.38, positive predictive value of 0.23, and negative predictive value of 1.0 for predicting hypotony. Preoperative OP and CP may predict early hypotony or HP and may be used as a guide as to which AGV valves to discard before implantation surgery.

Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

Science.gov (United States)

Li, Jin; Tran, Maggie; Siwabessy, Justy

2016-01-01

Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

Density-Dependent Formulation of Dispersion-Repulsion Interactions in Hybrid Multiscale Quantum/Molecular Mechanics (QM/MM) Models

DEFF Research Database (Denmark)

Curutchet, Carles; Cupellini, Lorenzo; Kongsted, Jacob

2018-01-01

embedding approaches, respectively, nonelectrostatic dispersion and repulsion interactions are instead commonly described through classical potentials despite their quantum mechanical origin. Here we present an extension of the Tkatchenko-Scheffler semiempirical van der Waals (vdWTS) scheme aimed......Mixed multiscale quantum/molecular mechanics (QM/MM) models are widely used to explore the structure, reactivity, and electronic properties of complex chemical systems. Whereas such models typically include electrostatics and potentially polarization in so-called electrostatic and polarizable...... at describing dispersion and repulsion interactions between quantum and classical regions within a QM/MM polarizable embedding framework. Starting from the vdWTSexpression, we define a dispersion and a repulsion term, both of them density-dependent and consistently based on a Lennard-Jones-like potential. We...

Confidence scores for prediction models

DEFF Research Database (Denmark)

Gerds, Thomas Alexander; van de Wiel, MA

2011-01-01

In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation,...

THE ENIGMATIC CORE L1451-mm: A FIRST HYDROSTATIC CORE? OR A HIDDEN VeLLO?

Energy Technology Data Exchange (ETDEWEB)

Pineda, Jaime E.; Goodman, Alyssa A.; Bourke, Tyler; Foster, Jonathan B.; Robitaille, Thomas; Kauffmann, Jens [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Arce, Hector G.; Tanner, Joel [Department of Astronomy, Yale University, P.O. Box 208101, New Haven, CT 06520-8101 (United States); Schnee, Scott [National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903 (United States); Tafalla, Mario [Observatorio Astronomico Nacional (IGN), Alfonso XII 3, E-28014 Madrid (Spain); Caselli, Paola [School of Physics and Astronomy, University of Leeds, Leeds LS2 9JT (United Kingdom); Anglada, Guillem, E-mail: jaime.pineda@manchester.ac.uk [Instituto de Astrofisica de Andalucia, CSIC, Apartado 3004, E-18080 Granada (Spain)

2011-12-20

We present the detection of a dust continuum source at 3 mm (CARMA) and 1.3 mm (Submillimeter Array, SMA), and {sup 12}CO (2-1) emission (SMA) toward the L1451-mm dense core. These detections suggest a compact object and an outflow where no point source at mid-infrared wavelengths is detected using Spitzer. An upper limit for the dense core bolometric luminosity of 0.05 L{sub Sun} is obtained. By modeling the broadband spectral energy distribution and the continuum interferometric visibilities simultaneously, we confirm that a central source of heating is needed to explain the observations. This modeling also shows that the data can be well fitted by a dense core with a young stellar object (YSO) and a disk, or by a dense core with a central first hydrostatic core (FHSC). Unfortunately, we are not able to decide between these two models, which produce similar fits. We also detect {sup 12}CO (2-1) emission with redshifted and blueshifted emission suggesting the presence of a slow and poorly collimated outflow, in opposition to what is usually found toward YSOs but in agreement with prediction from simulations of an FHSC. This presents the best candidate, so far, for an FHSC, an object that has been identified in simulations of collapsing dense cores. Whatever the true nature of the central object in L1451-mm, this core presents an excellent laboratory to study the earliest phases of low-mass star formation.

THE ENIGMATIC CORE L1451-mm: A FIRST HYDROSTATIC CORE? OR A HIDDEN VeLLO?

International Nuclear Information System (INIS)

Pineda, Jaime E.; Goodman, Alyssa A.; Bourke, Tyler; Foster, Jonathan B.; Robitaille, Thomas; Kauffmann, Jens; Arce, Héctor G.; Tanner, Joel; Schnee, Scott; Tafalla, Mario; Caselli, Paola; Anglada, Guillem

2011-01-01

We present the detection of a dust continuum source at 3 mm (CARMA) and 1.3 mm (Submillimeter Array, SMA), and 12 CO (2-1) emission (SMA) toward the L1451-mm dense core. These detections suggest a compact object and an outflow where no point source at mid-infrared wavelengths is detected using Spitzer. An upper limit for the dense core bolometric luminosity of 0.05 L ☉ is obtained. By modeling the broadband spectral energy distribution and the continuum interferometric visibilities simultaneously, we confirm that a central source of heating is needed to explain the observations. This modeling also shows that the data can be well fitted by a dense core with a young stellar object (YSO) and a disk, or by a dense core with a central first hydrostatic core (FHSC). Unfortunately, we are not able to decide between these two models, which produce similar fits. We also detect 12 CO (2-1) emission with redshifted and blueshifted emission suggesting the presence of a slow and poorly collimated outflow, in opposition to what is usually found toward YSOs but in agreement with prediction from simulations of an FHSC. This presents the best candidate, so far, for an FHSC, an object that has been identified in simulations of collapsing dense cores. Whatever the true nature of the central object in L1451-mm, this core presents an excellent laboratory to study the earliest phases of low-mass star formation.

Model Predictive Control for Offset-Free Reference Tracking

Czech Academy of Sciences Publication Activity Database

Belda, Květoslav

2016-01-01

Roč. 5, č. 1 (2016), s. 8-13 ISSN 1805-3386 Institutional support: RVO:67985556 Keywords : offset-free reference tracking * predictive control * ARX model * state-space model * multi-input multi-output system * robotic system * mechatronic system Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2016/AS/belda-0458355.pdf

Predictive modeling of crystal accumulation in high-level waste glass melters processing radioactive waste

Energy Technology Data Exchange (ETDEWEB)

Matyáš, Josef; Gervasio, Vivianaluxa; Sannoh, Sulaiman E.; Kruger, Albert A.

2017-11-01

The effectiveness of HLW vitrification is limited by precipitation/accumulation of spinel crystals [(Fe, Ni, Mn, Zn)(Fe, Cr)2O4] in the glass discharge riser of Joule-heated ceramic melters during idling. These crystals do not affect glass durability; however, if accumulated in thick layer, they can clog the melter and prevent discharge of molten glass into canisters. To address this problem, an empirical model was developed that can predict thicknesses of accumulated layers as a function of glass composition. This model predicts well the accumulation of single crystals and/or small-scale agglomerates, but, excessive agglomeration observed in high-Ni-Fe glass resulted in an under-prediction of accumulated layers, which gradually worsen over time as an increased number of agglomerates formed. Accumulation rate of ~53.8 ± 3.7 µm/h determined for this glass will result in ~26 mm thick layer in 20 days of melter idling.

Babcock and Wilcox model for predicting in-reactor densification

International Nuclear Information System (INIS)

Buescher, B.J.; Pegram, J.W.

1977-07-01

The B and W densification model is based on a correlation between in-reactor densification and a thermal resintering test. The densification model has been found to predict in-reactor densification with a remarkable degree of accuracy for fuel pellets operated at heat rates above 5 kW/ft and with considerable conservatism for pellelts operating at heat rates below 5 kW/ft

A new, accurate predictive model for incident hypertension.

Science.gov (United States)

Völzke, Henry; Fung, Glenn; Ittermann, Till; Yu, Shipeng; Baumeister, Sebastian E; Dörr, Marcus; Lieb, Wolfgang; Völker, Uwe; Linneberg, Allan; Jørgensen, Torben; Felix, Stephan B; Rettig, Rainer; Rao, Bharat; Kroemer, Heyo K

2013-11-01

Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures. The primary study population consisted of 1605 normotensive individuals aged 20-79 years with 5-year follow-up from the population-based study, that is the Study of Health in Pomerania (SHIP). The initial set was randomly split into a training and a testing set. We used a probabilistic graphical model applying a Bayesian network to create a predictive model for incident hypertension and compared the predictive performance with the established Framingham risk score for hypertension. Finally, the model was validated in 2887 participants from INTER99, a Danish community-based intervention study. In the training set of SHIP data, the Bayesian network used a small subset of relevant baseline features including age, mean arterial pressure, rs16998073, serum glucose and urinary albumin concentrations. Furthermore, we detected relevant interactions between age and serum glucose as well as between rs16998073 and urinary albumin concentrations [area under the receiver operating characteristic (AUC 0.76)]. The model was confirmed in the SHIP validation set (AUC 0.78) and externally replicated in INTER99 (AUC 0.77). Compared to the established Framingham risk score for hypertension, the predictive performance of the new model was similar in the SHIP validation set and moderately better in INTER99. Data mining procedures identified a predictive model for incident hypertension, which included innovative and easy-to-measure variables. The findings promise great applicability in screening settings and clinical practice.

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

Science.gov (United States)

Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

2010-01-01

The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

Solvent Boundary Potentials for Hybrid QM/MM Computations Using Classical Drude Oscillators: A Fully Polarizable Model.

Science.gov (United States)

Boulanger, Eliot; Thiel, Walter

2012-11-13

Accurate quantum mechanical/molecular mechanical (QM/MM) treatments should account for MM polarization and properly include long-range electrostatic interactions. We report on a development that covers both these aspects. Our approach combines the classical Drude oscillator (DO) model for the electronic polarizability of the MM atoms with the generalized solvent boundary Potential (GSBP) and the solvated macromolecule boundary potential (SMBP). These boundary potentials (BP) are designed to capture the long-range effects of the outer region of a large system on its interior. They employ a finite difference approximation to the Poisson-Boltzmann equation for computing electrostatic interactions and take into account outer-region bulk solvent through a polarizable dielectric continuum (PDC). This approach thus leads to fully polarizable three-layer QM/MM-DO/BP methods. As the mutual responses of each of the subsystems have to be taken into account, we propose efficient schemes to converge the polarization of each layer simultaneously. For molecular dynamics (MD) simulations using GSBP, this is achieved by considering the MM polarizable model as a dynamical degree of freedom, and hence contributions from the boundary potential can be evaluated for a frozen state of polarization at every time step. For geometry optimizations using SMBP, we propose a dual self-consistent field approach for relaxing the Drude oscillators to their ideal positions and converging the QM wave function with the proper boundary potential. The chosen coupling schemes are evaluated with a test system consisting of a glycine molecule in a water ball. Both boundary potentials are capable of properly reproducing the gradients at the inner-region atoms and the Drude oscillators. We show that the effect of the Drude oscillators must be included in all terms of the boundary potentials to obtain accurate results and that the use of a high dielectric constant for the PDC does not lead to a polarization

Proceedings of Conference on Variable-Resolution Modeling, Washington, DC, 5-6 May 1992

Science.gov (United States)

1992-05-01

lag (MM Kim (S󈨘-M 881 received the B.S.IM1. and M.S.F.n degrees from Ptisan National t.’ni- veisnv. Korea , and kwmpook National Univer- sity. Koiea...position in the Department Electronics. National Fisheries University of Pusan. Pusan. Korea , research interests include artificial intelligence...with the data or the modeler/analyst/ gamer is forced to make up interactions such as fire allocation, detailed acquisition predictions, small unit

Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model

Directory of Open Access Journals (Sweden)

Erasmo Cadenas

2016-02-01

Full Text Available Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA. This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX. This uses the variables: barometric pressure, air temperature, wind direction and solar radiation or relative humidity, as well as delayed wind speed. Both models were developed from two databases from two sites: an hourly average measurements database from La Mata, Oaxaca, Mexico, and a ten minute average measurements database from Metepec, Hidalgo, Mexico. The main objective was to compare the impact of the various meteorological variables on the performance of the multivariate model of wind speed prediction with respect to the high performance univariate linear model. The NARX model gave better results with improvements on the ARIMA model of between 5.5% and 10. 6% for the hourly database and of between 2.3% and 12.8% for the ten minute database for mean absolute error and mean squared error, respectively.

The cardiovascular event reduction tool (CERT)--a simplified cardiac risk prediction model developed from the West of Scotland Coronary Prevention Study (WOSCOPS).

Science.gov (United States)

L'Italien, G; Ford, I; Norrie, J; LaPuerta, P; Ehreth, J; Jackson, J; Shepherd, J

2000-03-15

The clinical decision to treat hypercholesterolemia is premised on an awareness of patient risk, and cardiac risk prediction models offer a practical means of determining such risk. However, these models are based on observational cohorts where estimates of the treatment benefit are largely inferred. The West of Scotland Coronary Prevention Study (WOSCOPS) provides an opportunity to develop a risk-benefit prediction model from the actual observed primary event reduction seen in the trial. Five-year Cox model risk estimates were derived from all WOSCOPS subjects (n = 6,595 men, aged 45 to 64 years old at baseline) using factors previously shown to be predictive of definite fatal coronary heart disease or nonfatal myocardial infarction. Model risk factors included age, diastolic blood pressure, total cholesterol/ high-density lipoprotein ratio (TC/HDL), current smoking, diabetes, family history of fatal coronary heart disease, nitrate use or angina, and treatment (placebo/ 40-mg pravastatin). All risk factors were expressed as categorical variables to facilitate risk assessment. Risk estimates were incorporated into a simple, hand-held slide rule or risk tool. Risk estimates were identified for 5-year age bands (45 to 65 years), 4 categories of TC/HDL ratio ( or = 7.5), 2 levels of diastolic blood pressure ( or = 90 mm Hg), from 0 to 3 additional risk factors (current smoking, diabetes, family history of premature fatal coronary heart disease, nitrate use or angina), and pravastatin treatment. Five-year risk estimates ranged from 2% in very low-risk subjects to 61% in the very high-risk subjects. Risk reduction due to pravastatin treatment averaged 31%. Thus, the Cardiovascular Event Reduction Tool (CERT) is a risk prediction model derived from the WOSCOPS trial. Its use will help physicians identify patients who will benefit from cholesterol reduction.

Advances in quantum and molecular mechanical (QM/MM) simulations for organic and enzymatic reactions.

Science.gov (United States)

Acevedo, Orlando; Jorgensen, William L

2010-01-19

Application of combined quantum and molecular mechanical (QM/MM) methods focuses on predicting activation barriers and the structures of stationary points for organic and enzymatic reactions. Characterization of the factors that stabilize transition structures in solution and in enzyme active sites provides a basis for design and optimization of catalysts. Continued technological advances allowed for expansion from prototypical cases to mechanistic studies featuring detailed enzyme and condensed-phase environments with full integration of the QM calculations and configurational sampling. This required improved algorithms featuring fast QM methods, advances in computing changes in free energies including free-energy perturbation (FEP) calculations, and enhanced configurational sampling. In particular, the present Account highlights development of the PDDG/PM3 semi-empirical QM method, computation of multi-dimensional potentials of mean force (PMF), incorporation of on-the-fly QM in Monte Carlo (MC) simulations, and a polynomial quadrature method for efficient modeling of proton-transfer reactions. The utility of this QM/MM/MC/FEP methodology is illustrated for a variety of organic reactions including substitution, decarboxylation, elimination, and pericyclic reactions. A comparison to experimental kinetic results on medium effects has verified the accuracy of the QM/MM approach in the full range of solvents from hydrocarbons to water to ionic liquids. Corresponding results from ab initio and density functional theory (DFT) methods with continuum-based treatments of solvation reveal deficiencies, particularly for protic solvents. Also summarized in this Account are three specific QM/MM applications to biomolecular systems: (1) a recent study that clarified the mechanism for the reaction of 2-pyrone derivatives catalyzed by macrophomate synthase as a tandem Michael-aldol sequence rather than a Diels-Alder reaction, (2) elucidation of the mechanism of action of fatty

Isothermal analysis of intermetallic MmNi5-xAlx in air decomposition processes

International Nuclear Information System (INIS)

Obregon, S.A.; Andrade Gamboa, J.J.; Esquivel, M.R.

2012-01-01

In this paper, it is analyzed the behavior of the degree of reaction as function of time α (t) of a sample of MmNi 4.3 Al 0.7 (Mm mischmetal = La 0.25 Ce 0.52 Nd 0.17 Pr 0.06 ) at different temperatures. The curves were obtained by isothermal calorimetric techniques. As a result of this study, it was observed that the kinetics of intermetallic can be separated into two main stages. At temperatures below 350 o C, the first stage is the oxidation of Mm and Al. At temperatures over 400 o C, the oxidation of Ni is also produced parallel to the above mentioned reactions. But the kinetics of the last one is at least three orders of magnitude slower. It was also observed that no thermal event occurs below 180 o C. It indicates that the intermetallic do not react at temperatures below this temperature value (author)

Ground Motion Prediction Model Using Artificial Neural Network

Science.gov (United States)

Dhanya, J.; Raghukanth, S. T. G.

2018-03-01

This article focuses on developing a ground motion prediction equation based on artificial neural network (ANN) technique for shallow crustal earthquakes. A hybrid technique combining genetic algorithm and Levenberg-Marquardt technique is used for training the model. The present model is developed to predict peak ground velocity, and 5% damped spectral acceleration. The input parameters for the prediction are moment magnitude ( M w), closest distance to rupture plane ( R rup), shear wave velocity in the region ( V s30) and focal mechanism ( F). A total of 13,552 ground motion records from 288 earthquakes provided by the updated NGA-West2 database released by Pacific Engineering Research Center are utilized to develop the model. The ANN architecture considered for the model consists of 192 unknowns including weights and biases of all the interconnected nodes. The performance of the model is observed to be within the prescribed error limits. In addition, the results from the study are found to be comparable with the existing relations in the global database. The developed model is further demonstrated by estimating site-specific response spectra for Shimla city located in Himalayan region.

A climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control.

Science.gov (United States)

Phung, Dung; Talukder, Mohammad Radwanur Rahman; Rutherford, Shannon; Chu, Cordia

2016-10-01

To develop a prediction score scheme useful for prevention practitioners and authorities to implement dengue preparedness and controls in the Mekong Delta region (MDR). We applied a spatial scan statistic to identify high-risk dengue clusters in the MDR and used generalised linear-distributed lag models to examine climate-dengue associations using dengue case records and meteorological data from 2003 to 2013. The significant predictors were collapsed into categorical scales, and the β-coefficients of predictors were converted to prediction scores. The score scheme was validated for predicting dengue outbreaks using ROC analysis. The north-eastern MDR was identified as the high-risk cluster. A 1 °C increase in temperature at lag 1-4 and 5-8 weeks increased the dengue risk 11% (95% CI, 9-13) and 7% (95% CI, 6-8), respectively. A 1% rise in humidity increased dengue risk 0.9% (95% CI, 0.2-1.4) at lag 1-4 and 0.8% (95% CI, 0.2-1.4) at lag 5-8 weeks. Similarly, a 1-mm increase in rainfall increased dengue risk 0.1% (95% CI, 0.05-0.16) at lag 1-4 and 0.11% (95% CI, 0.07-0.16) at lag 5-8 weeks. The predicted scores performed with high accuracy in diagnosing the dengue outbreaks (96.3%). This study demonstrates the potential usefulness of a dengue prediction score scheme derived from complex statistical models for high-risk dengue clusters. We recommend a further study to examine the possibility of incorporating such a score scheme into the dengue early warning system in similar climate settings. © 2016 John Wiley & Sons Ltd.

Accurate and dynamic predictive model for better prediction in medicine and healthcare.

Science.gov (United States)

Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

2018-05-01

Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

Energy Technology Data Exchange (ETDEWEB)

Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A [Duke University Medical Center, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States)

2014-06-15

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

International Nuclear Information System (INIS)

Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

2014-01-01

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

Solar energy prediction and verification using operational model forecasts and ground-based solar measurements

International Nuclear Information System (INIS)

Kosmopoulos, P.G.; Kazadzis, S.; Lagouvardos, K.; Kotroni, V.; Bais, A.

2015-01-01

The present study focuses on the predictions and verification of these predictions of solar energy using ground-based solar measurements from the Hellenic Network for Solar Energy and the National Observatory of Athens network, as well as solar radiation operational forecasts provided by the MM5 mesoscale model. The evaluation was carried out independently for the different networks, for two forecast horizons (1 and 2 days ahead), for the seasons of the year, for varying solar elevation, for the indicative energy potential of the area, and for four classes of cloud cover based on the calculated clearness index (k_t): CS (clear sky), SC (scattered clouds), BC (broken clouds) and OC (overcast). The seasonal dependence presented relative rRMSE (Root Mean Square Error) values ranging from 15% (summer) to 60% (winter), while the solar elevation dependence revealed a high effectiveness and reliability near local noon (rRMSE ∼30%). An increment of the errors with cloudiness was also observed. For CS with mean GHI (global horizontal irradiance) ∼ 650 W/m"2 the errors are 8%, for SC 20% and for BC and OC the errors were greater (>40%) but correspond to much lower radiation levels (<120 W/m"2) of consequently lower energy potential impact. The total energy potential for each ground station ranges from 1.5 to 1.9 MWh/m"2, while the mean monthly forecast error was found to be consistently below 10%. - Highlights: • Long term measurements at different atmospheric cases are needed for energy forecasting model evaluations. • The total energy potential at the Greek sites presented ranges from 1.5 to 1.9 MWh/m"2. • Mean monthly energy forecast errors are within 10% for all cases analyzed. • Cloud presence results of an additional forecast error that varies with the cloud cover.

Compressive forces achieved in simulated equine third metacarpal bone lateral condylar fractures of varying fragment thickness with Acutrak Plus screw and 4.5 mm AO cortical screws.

Science.gov (United States)

Lewis, Andrew J; Sod, Gary A; Burba, Daniel J; Mitchell, Colin F

2010-01-01

To compare compression pressure (CP) of 6.5 mm Acutrak Plus (AP) and 4.5 mm AO cortical screws (AO) when inserted in simulated lateral condylar fractures of equine 3rd metacarpal (MC3) bones. Paired in vitro biomechanical testing. Cadaveric equine MC3 bones (n=12 pair). Complete lateral condylar osteotomies were created parallel to the midsagittal ridge at 20, 12, and 8 mm axial to the epicondylar fossa on different specimens grouped accordingly. Interfragmentary compression was measured using a pressure sensor placed in the fracture plane before screw placement for fracture fixation. CP was acquired and mean values of CP for each fixation method were compared between the 6.5 mm (AP) and 4.5 mm (AO) for each group using a paired t-test within each fracture fragment thickness group with statistical significance set at Pfractures, especially complete fractures. Because interfragmentary compression plays a factor in the overall stability of a repair, it is recommended for use only in patients with thin lateral condyle fracture fragments, as the compression tends to decrease with an increase in thickness.

Accelerator Quality HTS Dipole Magnet Demonstrator designs for the EuCARD-2, 5 Tesla 40 mm Clear Aperture Magnet

CERN Document Server

Kirby, G; Ballarino, A; Bottura, L; Chouika, N; Clement, S; Datskov, V; Fajardo, L; Fleiter, J; Gauthier, R; Lambert, L; Lopes, M; Perez, J; DeRijk, G; Rijllart, A; Rossi, L; Ten Kate, H; Durante, M; Fazilleau, P; Lorin, C; Haro, E; Stenvall, A; Caspi, S; Marchevsky, M; Goldacker, W; Kario, A

2014-01-01

Future high-energy accelerators will need very high magnetic fields in the range of 20 T. The EuCARD-2 work-package-10 is a collaborative push to take HTS materials into an accelerator quality demonstrator magnet. The demonstrator will produce 5 T standalone and between 17 T and 20 T, when inserted into the 100 mm aperture of Fresca-2 high field out-sert magnet. The HTS magnet will demonstrate the field strength and field quality that can be achieved. An effective quench detection and protection system will have to be developed to operate with the HTS superconducting materials. This paper presents a ReBCO magnet design using multi strand Roebel cable that develops a stand-alone field of 5 T in a 40 mm clear aperture and discusses the challenges associated with good field quality using this type of material. A selection of magnet designs is presented as result of a first phase of development.

Accelerator Quality HTS Dipole Magnet Demonstrator Designs for the EuCARD-2, 5 Tesla 40 mm Clear Aperture Magnet

CERN Document Server

Kirby, G A; Ballarino, A; Bottura, L; Chouika, N; Clement, S; Datskov, V; Fajardo, L; Fleiter, J; Gauthier, R; Gentini, L; Lambert, L; Lopes, M; Perez, J C; de Rijk, G; Rijllart, A; Rossi, L; ten Kate, H; Durante, M; Fazilleau, P; Lorin, C; Härö, E; Stenvall, A; Caspi, S; Marchevsky, M; Goldacker, W; Kario, A

2015-01-01

Future high-energy accelerators will need very high magnetic fields in the range of 20 T. The EuCARD-2 work-package-10 is a collaborative push to take HTS materials into an accelerator quality demonstrator magnet. The demonstrator will produce 5 T standalone and between 17 T and 20 T, when inserted into the 100 mm aperture of Fresca-2 high field out-sert magnet. The HTS magnet will demonstrate the field strength and field quality that can be achieved. An effective quench detection and protection system will have to be developed to operate with the HTS superconducting materials. This paper presents a ReBCO magnet design using multi strand Roebel cable that develops a stand-alone field of 5 T in a 40 mm clear aperture and discusses the challenges associated with good field quality using this type of material. A selection of magnet designs is presented as result of a first phase of development.

Impact of platform switching on inter-proximal bone levels around 8.5 mm implants in the posterior region; 5-year results from a randomized clinical trial

NARCIS (Netherlands)

Telleman, Gerdien; Raghoebar, Gerry M.; Vissink, Arjan; Meijer, Henny J. A.

Aim: To assess the medium- term results of 8.5 mm implants supplied with a conventional platform- matched implant- abutment connection or a platform- switched design. Materials and Methods: Eighty patients with one or more missing teeth in the maxillary or mandibular posterior zone were randomly

Calibration of flavour tagging with B+ -> J/psi(mm)K+ and B0 ->J/psi(mm)K* control channels at LHCb

CERN Document Server

Calvi, M; Leroy, O; Musy, M; Poss, S; Vecchi, S

2009-01-01

B+ -> J/psi(mm)K+ and B0 ->J/psi(mm)K* are suitable control channels for the calibration of flavour tagging for CP measurements in Bs ->J/psi(mm) phi and B0 ->J/psi(mm)KS channels; in the first case if opposite side tagging only is considered. In this note we describe the calibration of the probability of mistag performed with B+ ->J/psi(mm)K+ events and the measurement of the mistag performed with B0 ->J/psi(mm)K* events in a fit to flavour oscillation as a function of proper time. Models are developed to extract this information from selected events taking into account different background components. An expected statistical sensitivity on the average opposite side mistag rate sigma(wOS)/ wOS = 0.3 % is obtained for B0 ->J/psi(mm)K* events, in 2 fb-1 of data.

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

Science.gov (United States)

Diallo, Ousmane H.

2012-01-01

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Integrated predictive modelling simulations of burning plasma experiment designs

International Nuclear Information System (INIS)

Bateman, Glenn; Onjun, Thawatchai; Kritz, Arnold H

2003-01-01

Models for the height of the pedestal at the edge of H-mode plasmas (Onjun T et al 2002 Phys. Plasmas 9 5018) are used together with the Multi-Mode core transport model (Bateman G et al 1998 Phys. Plasmas 5 1793) in the BALDUR integrated predictive modelling code to predict the performance of the ITER (Aymar A et al 2002 Plasma Phys. Control. Fusion 44 519), FIRE (Meade D M et al 2001 Fusion Technol. 39 336), and IGNITOR (Coppi B et al 2001 Nucl. Fusion 41 1253) fusion reactor designs. The simulation protocol used in this paper is tested by comparing predicted temperature and density profiles against experimental data from 33 H-mode discharges in the JET (Rebut P H et al 1985 Nucl. Fusion 25 1011) and DIII-D (Luxon J L et al 1985 Fusion Technol. 8 441) tokamaks. The sensitivities of the predictions are evaluated for the burning plasma experimental designs by using variations of the pedestal temperature model that are one standard deviation above and below the standard model. Simulations of the fusion reactor designs are carried out for scans in which the plasma density and auxiliary heating power are varied

Combining multiple models to generate consensus: Application to radiation-induced pneumonitis prediction

Energy Technology Data Exchange (ETDEWEB)

Das, Shiva K.; Chen Shifeng; Deasy, Joseph O.; Zhou Sumin; Yin Fangfang; Marks, Lawrence B. [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710 (United States); Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri 63110 (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710 (United States); Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, North Carolina 27599 (United States)

2008-11-15

The fusion of predictions from disparate models has been used in several fields to obtain a more realistic and robust estimate of the ''ground truth'' by allowing the models to reinforce each other when consensus exists, or, conversely, negate each other when there is no consensus. Fusion has been shown to be most effective when the models have some complementary strengths arising from different approaches. In this work, we fuse the results from four common but methodologically different nonlinear multivariate models (Decision Trees, Neural Networks, Support Vector Machines, Self-Organizing Maps) that were trained to predict radiation-induced pneumonitis risk on a database of 219 lung cancer patients treated with radiotherapy (34 with Grade 2+ postradiotherapy pneumonitis). Each model independently incorporated a small number of features from the available set of dose and nondose patient variables to predict pneumonitis; no two models had all features in common. Fusion was achieved by simple averaging of the predictions for each patient from all four models. Since a model's prediction for a patient can be dependent on the patient training set used to build the model, the average of several different predictions from each model was used in the fusion (predictions were made by repeatedly testing each patient with a model built from different cross-validation training sets that excluded the patient being tested). The area under the receiver operating characteristics curve for the fused cross-validated results was 0.79, with lower variance than the individual component models. From the fusion, five features were extracted as the consensus among all four models in predicting radiation pneumonitis. Arranged in order of importance, the features are (1) chemotherapy; (2) equivalent uniform dose (EUD) for exponent a=1.2 to 3; (3) EUD for a=0.5 to 1.2, lung volume receiving >20-30 Gy; (4) female sex; and (5) squamous cell histology. To facilitate

MO-FG-303-03: Demonstration of Universal Knowledge-Based 3D Dose Prediction

Energy Technology Data Exchange (ETDEWEB)

Shiraishi, S; Moore, K L [University of California, San Diego, La Jolla, CA (United States)

2015-06-15

Purpose: To demonstrate a knowledge-based 3D dose prediction methodology that can accurately predict achievable radiotherapy distributions. Methods: Using previously treated plans as input, an artificial neural network (ANN) was trained to predict 3D dose distributions based on 14 patient-specific anatomical parameters including the distance (r) to planning target volume (PTV) boundary, organ-at-risk (OAR) boundary distances, and angular position ( θ,φ). 23 prostate and 49 stereotactic radiosurgery (SRS) cases with ≥1 nearby OARs were studied. All were planned with volumetric-modulated arc therapy (VMAT) to prescription doses of 81Gy for prostate and 12–30Gy for SRS. Site-specific ANNs were trained using all prostate 23 plans and using a 24 randomly-selected subset for the SRS model. The remaining 25 SRS plans were used to validate the model. To quantify predictive accuracy, the dose difference between the clinical plan and prediction were calculated on a voxel-by-voxel basis δD(r,θ,φ)=Dclin(r,θ,φ)-Dpred(r, θ,φ). Grouping voxels by boundary distance, the mean <δ Dr>=(1/N)Σ -θ,φ D(r,θ,φ) and inter-quartile range (IQR) quantified the accuracy of this method for deriving DVH estimations. The standard deviation (σ) of δ D quantified the 3D dose prediction error on a voxel-by-voxel basis. Results: The ANNs were highly accurate in predictive ability for both prostate and SRS plans. For prostate, <δDr> ranged from −0.8% to +0.6% (max IQR=3.8%) over r=0–32mm, while 3D dose prediction accuracy averaged from σ=5–8% across the same range. For SRS, from r=0–34mm the training set <δDr> ranged from −3.7% to +1.5% (max IQR=4.4%) while the validation set <δDr> ranged from −2.2% to +5.8% (max IQR=5.3%). 3D dose prediction accuracy averaged σ=2.5% for the training set and σ=4.0% over the same interval. Conclusion: The study demonstrates this technique’s ability to predict achievable 3D dose distributions for VMAT SRS and prostate. Future

MO-FG-303-03: Demonstration of Universal Knowledge-Based 3D Dose Prediction

International Nuclear Information System (INIS)

Shiraishi, S; Moore, K L

2015-01-01

Purpose: To demonstrate a knowledge-based 3D dose prediction methodology that can accurately predict achievable radiotherapy distributions. Methods: Using previously treated plans as input, an artificial neural network (ANN) was trained to predict 3D dose distributions based on 14 patient-specific anatomical parameters including the distance (r) to planning target volume (PTV) boundary, organ-at-risk (OAR) boundary distances, and angular position ( θ,φ). 23 prostate and 49 stereotactic radiosurgery (SRS) cases with ≥1 nearby OARs were studied. All were planned with volumetric-modulated arc therapy (VMAT) to prescription doses of 81Gy for prostate and 12–30Gy for SRS. Site-specific ANNs were trained using all prostate 23 plans and using a 24 randomly-selected subset for the SRS model. The remaining 25 SRS plans were used to validate the model. To quantify predictive accuracy, the dose difference between the clinical plan and prediction were calculated on a voxel-by-voxel basis δD(r,θ,φ)=Dclin(r,θ,φ)-Dpred(r, θ,φ). Grouping voxels by boundary distance, the mean =(1/N)Σ -θ,φ D(r,θ,φ) and inter-quartile range (IQR) quantified the accuracy of this method for deriving DVH estimations. The standard deviation (σ) of δ D quantified the 3D dose prediction error on a voxel-by-voxel basis. Results: The ANNs were highly accurate in predictive ability for both prostate and SRS plans. For prostate, ranged from −0.8% to +0.6% (max IQR=3.8%) over r=0–32mm, while 3D dose prediction accuracy averaged from σ=5–8% across the same range. For SRS, from r=0–34mm the training set ranged from −3.7% to +1.5% (max IQR=4.4%) while the validation set ranged from −2.2% to +5.8% (max IQR=5.3%). 3D dose prediction accuracy averaged σ=2.5% for the training set and σ=4.0% over the same interval. Conclusion: The study demonstrates this technique’s ability to predict achievable 3D dose distributions for VMAT SRS and prostate. Future investigations will attempt to

Multi-model analysis in hydrological prediction

Science.gov (United States)

Lanthier, M.; Arsenault, R.; Brissette, F.

2017-12-01

Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

Acute Myocardial Infarction Readmission Risk Prediction Models: A Systematic Review of Model Performance.

Science.gov (United States)

Smith, Lauren N; Makam, Anil N; Darden, Douglas; Mayo, Helen; Das, Sandeep R; Halm, Ethan A; Nguyen, Oanh Kieu

2018-01-01

Hospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown. We systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models. Current AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions

Streamer free operation of a 2 mm gap resistive plate chamber with $C_{2}F_{5}H$

CERN Document Server

Cerron-Zeballos, E; Hatzifotiadou, D; Lamas-Valverde, J; Williams, M C S; Zichichi, A

1999-01-01

It is necessary to operate the resistive plate chamber (RPC) in avalanche mode to obtain high efficiency at elevated particle fluxes. We examine this mode of operation with a 2 mm gap RPC using gas mixtures containing C/sub 2/F/sub 4/H/sub 2/ and C/sub 2/F/sub 5/H. In order to explain the data we propose that the avalanche growth is strongly limited by space charge effects. (10 refs).

Impact of sampling interval in training data acquisition on intrafractional predictive accuracy of indirect dynamic tumor-tracking radiotherapy.

Science.gov (United States)

Mukumoto, Nobutaka; Nakamura, Mitsuhiro; Akimoto, Mami; Miyabe, Yuki; Yokota, Kenji; Matsuo, Yukinori; Mizowaki, Takashi; Hiraoka, Masahiro

2017-08-01

intervals. The intrafractional prediction error for the same motion pattern was 1.9 ± 0.7 mm in 3D for an 80 ms sampling interval, which increased larger than 1 mm in 10.0% of prediction models trained at a 2,000 ms sampling interval with a significant difference (P sampling intervals without a significant difference (P > 0.05). The intrafractional prediction error for the changed respiratory motion pattern increased to 5.1 ± 2.4 mm in 3D for an 80 ms sampling interval; however, there was not a significant difference in the robustness of the prediction model between the 80 ms sampling interval and other sampling intervals (P > 0.05). Although the training error of the prediction model was consistent for the all sampling intervals, the prediction model using the larger sampling interval of the 2,000 ms increased the intrafractional prediction error for the same motion pattern. The realistic accuracy of the prediction model was difficult to estimate using the larger sampling interval during the training process. It is recommended to construct the prediction model at sampling interval ≤ 1,000 ms and to reconstruct the model during treatment. © 2017 The Authors. Medical Physics published by Wiley periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Assessment of RELAP5/MOD3 with condensation experiment for pure steam condensation in a vercal tube

Energy Technology Data Exchange (ETDEWEB)

Kim, Sang Jae; No, Hee Cheon [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1999-12-31

The film condensation models in RELAP5/MOD3.1 and RELAP5/MOD3.2 are assessed with the data of experiment performed in the scaled down condensation experimental facility with a single vertical tube of inner diameter of 46 mm in the range of pressure 0.1 {approx} 7.5 MPa for the PSCS(Passive Secondary Condenser System). Both MOD3.1 and MOD3.2 don`t shows any reliable predictions of the experimental data. The RELAP5/MOD3.1 overpredicts the heat transfer coefficients of experiment, whereas the RELAP5/MOD3.2 underpredicts those data. It is recommended that the film condensation model in RELAP5/MOD3.2 should be modified to have a larger heat transfer coefficient than those of the present model to give the reliable predictions. 7 refs., 6 figs., 1 tab. (Author)

Assessment of RELAP5/MOD3 with condensation experiment for pure steam condensation in a vercal tube

Energy Technology Data Exchange (ETDEWEB)

Kim, Sang Jae; No, Hee Cheon [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1998-12-31

The film condensation models in RELAP5/MOD3.1 and RELAP5/MOD3.2 are assessed with the data of experiment performed in the scaled down condensation experimental facility with a single vertical tube of inner diameter of 46 mm in the range of pressure 0.1 {approx} 7.5 MPa for the PSCS(Passive Secondary Condenser System). Both MOD3.1 and MOD3.2 don`t shows any reliable predictions of the experimental data. The RELAP5/MOD3.1 overpredicts the heat transfer coefficients of experiment, whereas the RELAP5/MOD3.2 underpredicts those data. It is recommended that the film condensation model in RELAP5/MOD3.2 should be modified to have a larger heat transfer coefficient than those of the present model to give the reliable predictions. 7 refs., 6 figs., 1 tab. (Author)

EFEKTIFITAS SKELING-PENGHALUSAN AKAR DENGAN DAN TANPA APLIKASI SUBGINGIVAL POVIDON-IODIN 10% PADA POKET 5-7mm

Directory of Open Access Journals (Sweden)

Irma Ervina

2015-08-01

Full Text Available In deep periodontal lesions, scaling and root planning (SRP failed to complete elimination of periodontal bacteria, so chemical antimicrobial agents are used topically to destroy microorganism. Povidon-iodin 10% is one of antimicrobial agents that can be applied topically and directly in the pocket. The aim of the research were evaluated the efficacy of povidon-iodin 10% as chemical antimicrobial agents locally applied into periodontal pocket. The data are obtained from patients with chronic adult periodontitis, baseline periodontal pocket depth (PPD are 5-7 mm. The teeth are scaled and root planed after clinical examinations (plaque index, papilla bleeding index and periodontal pocket depth and test sites or control sites are assigned randomly. Topically application of povidon-iodin 10% at test sites and aquabides at control sites is applied at day 1st and day 7th. The clinical parameters are assessed at day 14th. The results of the research showed that application of povidon-iodin 10% after SRP provide statistically significant more favorable papilla bleeding index reduction than SRP + aquabides after 14 day. The pocket depth reduction at test sites are greater than control cites (baseline PPD=6 and 7 mm. The conclusions of the research showed that application subgingival povidon-iodin 10% as adjuctive to SRP significantly reduce PBI and PPD (6 & 7 mm than without application povidon-iodin 10%.

Damage assessment of low-cycle fatigue by crack growth prediction. Development of growth prediction model and its application

International Nuclear Information System (INIS)

Kamaya, Masayuki; Kawakubo, Masahiro

2012-01-01

In this study, the fatigue damage was assumed to be equivalent to the crack initiation and its growth, and fatigue life was assessed by predicting the crack growth. First, a low-cycle fatigue test was conducted in air at room temperature under constant cyclic strain range of 1.2%. The crack initiation and change in crack size during the test were examined by replica investigation. It was found that a crack of 41.2 μm length was initiated almost at the beginning of the test. The identified crack growth rate was shown to correlate well with the strain intensity factor, whose physical meaning was discussed in this study. The fatigue life prediction model (equation) under constant strain range was derived by integrating the crack growth equation defined using the strain intensity factor, and the predicted fatigue lives were almost identical to those obtained by low-cycle fatigue tests. The change in crack depth predicted by the equation also agreed well with the experimental results. Based on the crack growth prediction model, it was shown that the crack size would be less than 0.1 mm even when the estimated fatigue damage exceeded the critical value of the design fatigue curve, in which a twenty-fold safety margin was used for the assessment. It was revealed that the effect of component size and surface roughness, which have been investigated empirically by fatigue tests, could be reasonably explained by considering the crack initiation and growth. Furthermore, the environmental effect on the fatigue life was shown to be brought about by the acceleration of crack growth. (author)

Influence of oil on flow condensation heat transfer of R410A inside 4.18 mm and 1.6 mm inner diameter horizontal smooth tubes

Energy Technology Data Exchange (ETDEWEB)

Huang, Xiangchao; Ding, Guoliang; Hu, Haitao; Zhu, Yu.; Peng, Hao [Institute of Refrigeration and Cryogenics, Shanghai Jiaotong University, Shanghai 200240 (China); Gao, Yifeng [International Copper Association Shanghai Office, Shanghai 200020 (China); Deng, Bin [Institute of Heat Transfer Technology, Golden Dragon Precise Copper Tube Group Inc., Shanghai 200135 (China)

2010-01-15

The influence of oil on condensation heat transfer of R410A inside 4.18 mm and 1.6 mm inner diameter horizontal smooth tubes is investigated experimentally. The experimental condensing temperature is 40 C, and nominal oil concentration range is from 0% to 5%. The test results indicate that the presence of oil deteriorates the heat transfer, and the deterioration effect becomes obvious with the increase of oil concentration. At oil concentration of 5%, the heat transfer coefficient decreases by maximum 24.9% and 28.5% for 4.18 mm and 1.6 mm tubes, respectively. A new correlation for heat transfer coefficients of R410A-oil mixture flow condensation inside smooth tubes is proposed, which agrees with all the experimental data within a deviation of -30% {proportional_to} +20%. (author)

A model to predict the beginning of the pollen season

DEFF Research Database (Denmark)

Toldam-Andersen, Torben Bo

1991-01-01

for fruit trees are generally applicable, and give a reasonable description of the growth processes of other trees. This type of model can therefore be of value in predicting the start of the pollen season. The predicted dates were generally within 3-5 days of the observed. Finally the possibility of frost...

Prediction of compatibility of crude oils with condensate (C5+); Previsao de compatibilidade de petroleos e condensado (C5+)

Energy Technology Data Exchange (ETDEWEB)

Zilio, Evaldo Lopez; Santos, Maria de Fatima Pereira dos [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil); Ramos, Antonio Carlos da Silva; Rolemberg, Marlus Pinheiro [Universidade Federal do Maranhao (UFMA), Sao Luis, MA (Brazil)

2008-07-01

Due to the recent raise of the national natural gas demand and to the need of flowing the condensates (C5+) produced from the NGPP (Natural Gas Processing Plant) by adding them to the streams of the crude oil, there was the need to carry out the compatibility prediction of one condensate with two onshore crude oils from Espirito Santo. The model to predict the compatibility among crude oils and among crude oils and oil products is based on the use of the solubility parameter of the oils. To apply it, the solubility parameter of each crude oil or oil product is measured and the parameter of their blend is calculated. If this value is beneath the asphaltenes flocculation parameter, the blend is incompatible; if it is above, the blend is compatible. In this article, the compatibility predictions were done according to the Solubility Parameter Model to two blends: the condensate C with the crude oil X and with the crude oil Y. The model predictions are that both blends are incompatible at given proportions. To check the predictions, the same two blends were experimentally carried out. It must be emphasized that the compatibility tests were done at atmospheric pressure and at the temperature of 15 deg C. These tests consist in adding the condensate to the crude oil with a titrater and visualizing the asphaltenes precipitation at an optical microscope. The experimental results were equivalent to the values predicted by the model. It is worth mentioning that there were several practical difficulties, as the high volatility of the condensate and the fact that the temperatures to determine the parameters and to carry out the tests were very lower than the operation temperature. Therefore, a security factor was applied on the predictions (less 20%). (author)

A QM/MM refinement of an experimental DNA structure with metal-mediated base pairs.

Science.gov (United States)

Kumbhar, Sadhana; Johannsen, Silke; Sigel, Roland K O; Waller, Mark P; Müller, Jens

2013-10-01

A series of hybrid quantum mechanical/molecular mechanical (QM/MM) calculations was performed on models of a DNA duplex with artificial silver(I)-mediated imidazole base pairs. The optimized structures were compared to the original experimental NMR structure (Nat. Chem. 2 (2010) 229-234). The metal⋯metal distances are significantly shorter (~0.5Å) in the QM/MM model than in the original NMR structure. As a result, argentophilic interactions are feasible between the silver(I) ions of neighboring metal-mediated base pairs. Using the computationally determined metal⋯metal distances, a re-refined NMR solution structure of the DNA duplex was obtained. In this new NMR structure, all experimental constraints remain fulfilled. The new NMR structure shows less deviation from the regular B-type conformation than the original one. This investigation shows that the application of QM/MM models to generate additional constraints to be used during NMR structural refinements represents an elegant approach to obtaining high-resolution NMR structures. Copyright © 2013 Elsevier Inc. All rights reserved.

Predictive Modeling in Race Walking

Directory of Open Access Journals (Sweden)

Krzysztof Wiktorowicz

2015-01-01

Full Text Available This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers’ training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 122 training plans for 21 athletes. In order to choose the best model leave-one-out cross-validation method is used. The main contribution of the paper is to propose the nonlinear modifications for linear models in order to achieve smaller prediction error. It is shown that the best model is a modified LASSO regression with quadratic terms in the nonlinear part. This model has the smallest prediction error and simplified structure by eliminating some of the predictors.

Response of Soil Temperature to Climate Change in the CMIP5 Earth System Models

Science.gov (United States)

Phillips, C. L.; Torn, M. S.; Koven, C. D.

2014-12-01

Predictions of soil temperature changes are as critical to policy development and climate change adaptation as predictions of air temperature, but have received comparatively little attention. Soil temperature determines seed germination and growth of wild and agricultural plants, and impacts climate through both geophysical and carbon-cycle feedbacks. The Intergovernmental Panel on Climate Change 5th Assessment Report does not report soil temperature predictions, but focuses instead on surface air temperatures, despite the fact that mean annual soil temperatures and mean surface air temperatures are often different from each other. Here we aim to fill this important knowledge gap by reporting soil temperature and moisture predictions for 15 earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison 5 Project (CMIP5). Under the RCP 4.5 and 8.5 emissions scenarios, soil warming is predicted to almost keep pace with soil air warming, with about 10% less warming in soil than air, globally. The slower warming of soil compared to air is likely related to predictions of soil drying, with drier soils having reduced soil heat capacity and thermal conductivity. Mollisol soils, which are typically regarded as the most productive soil order for cultivating cereal crops, are anticipated to see warming in North America of 3.5 to 5.5 °C at the end of the 21st century (2080-2100) compared to 1986-2005. One impact of soil warming is likely to be an acceleration of germination timing, with the 3°C temperature threshold for wheat germination anticipated to advance by several weeks in Mollisol regions. Furthermore, soil warming at 1 m depth is predicted to be almost equivalent to warming at 1 cm depth in frost-free regions, indicating vulnerability of deep soil carbon pools to destabilization. To assess model performance we compare the models' predictions with observations of damping depth, and offsets between mean annual soil and air temperature

Adding propensity scores to pure prediction models fails to improve predictive performance

Directory of Open Access Journals (Sweden)

Amy S. Nowacki

2013-08-01

Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

Model-free and model-based reward prediction errors in EEG.

Science.gov (United States)

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations

Directory of Open Access Journals (Sweden)

P. Koutrakis

2011-08-01

Full Text Available Epidemiological studies investigating the human health effects of PM2.5 are susceptible to exposure measurement errors, a form of bias in exposure estimates, since they rely on data from a limited number of PM2.5 monitors within their study area. Satellite data can be used to expand spatial coverage, potentially enhancing our ability to estimate location- or subject-specific exposures to PM2.5, but some have reported poor predictive power. A new methodology was developed to calibrate aerosol optical depth (AOD data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS. Subsequently, this method was used to predict ground daily PM2.5 concentrations in the New England region. 2003 MODIS AOD data corresponding to the New England region were retrieved, and PM2.5 concentrations measured at 26 US Environmental Protection Agency (EPA PM2.5 monitoring sites were used to calibrate the AOD data. A mixed effects model which allows day-to-day variability in daily PM2.5-AOD relationships was used to predict location-specific PM2.5 levels. PM2.5 concentrations measured at the monitoring sites were compared to those predicted for the corresponding grid cells. Both cross-sectional and longitudinal comparisons between the observed and predicted concentrations suggested that the proposed new calibration approach renders MODIS AOD data a potentially useful predictor of PM2.5 concentrations. Furthermore, the estimated PM2.5 levels within the study domain were examined in relation to air pollution sources. Our approach made it possible to investigate the spatial patterns of PM2.5 concentrations within the study domain.

Combining GPS measurements and IRI model predictions

International Nuclear Information System (INIS)

Hernandez-Pajares, M.; Juan, J.M.; Sanz, J.; Bilitza, D.

2002-01-01

The free electrons distributed in the ionosphere (between one hundred and thousands of km in height) produce a frequency-dependent effect on Global Positioning System (GPS) signals: a delay in the pseudo-orange and an advance in the carrier phase. These effects are proportional to the columnar electron density between the satellite and receiver, i.e. the integrated electron density along the ray path. Global ionospheric TEC (total electron content) maps can be obtained with GPS data from a network of ground IGS (international GPS service) reference stations with an accuracy of few TEC units. The comparison with the TOPEX TEC, mainly measured over the oceans far from the IGS stations, shows a mean bias and standard deviation of about 2 and 5 TECUs respectively. The discrepancies between the STEC predictions and the observed values show an RMS typically below 5 TECUs (which also includes the alignment code noise). he existence of a growing database 2-hourly global TEC maps and with resolution of 5x2.5 degrees in longitude and latitude can be used to improve the IRI prediction capability of the TEC. When the IRI predictions and the GPS estimations are compared for a three month period around the Solar Maximum, they are in good agreement for middle latitudes. An over-determination of IRI TEC has been found at the extreme latitudes, the IRI predictions being, typically two times higher than the GPS estimations. Finally, local fits of the IRI model can be done by tuning the SSN from STEC GPS observations

Modelling daily PM2.5 concentrations at high spatio-temporal resolution across Switzerland.

Science.gov (United States)

de Hoogh, Kees; Héritier, Harris; Stafoggia, Massimo; Künzli, Nino; Kloog, Itai

2018-02-01

Spatiotemporal resolved models were developed predicting daily fine particulate matter (PM 2.5 ) concentrations across Switzerland from 2003 to 2013. Relatively sparse PM 2.5 monitoring data was supplemented by imputing PM 2.5 concentrations at PM 10 sites, using PM 2.5 /PM 10 ratios at co-located sites. Daily PM 2.5 concentrations were first estimated at a 1 × 1km resolution across Switzerland, using Multiangle Implementation of Atmospheric Correction (MAIAC) spectral aerosol optical depth (AOD) data in combination with spatiotemporal predictor data in a four stage approach. Mixed effect models (1) were used to predict PM 2.5 in cells with AOD but without PM 2.5 measurements (2). A generalized additive mixed model with spatial smoothing was applied to generate grid cell predictions for those grid cells where AOD was missing (3). Finally, local PM 2.5 predictions were estimated at each monitoring site by regressing the residuals from the 1 × 1km estimate against local spatial and temporal variables using machine learning techniques (4) and adding them to the stage 3 global estimates. The global (1 km) and local (100 m) models explained on average 73% of the total,71% of the spatial and 75% of the temporal variation (all cross validated) globally and on average 89% (total) 95% (spatial) and 88% (temporal) of the variation locally in measured PM 2.5 concentrations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nonlinear chaotic model for predicting storm surges

Directory of Open Access Journals (Sweden)

M. Siek

2010-09-01

Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM).

Science.gov (United States)

Sinitskiy, Anton V; Voth, Gregory A

2018-01-07

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM)

Science.gov (United States)

Sinitskiy, Anton V.; Voth, Gregory A.

2018-01-01

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

Design, Modelling and Teleoperation of a 2 mm Diameter Compliant Instrument for the da Vinci Platform.

Science.gov (United States)

Francis, P; Eastwood, K W; Bodani, V; Looi, T; Drake, J M

2018-05-07

This work explores the feasibility of creating and accurately controlling an instrument for robotic surgery with a 2 mm diameter and a three degree-of-freedom (DoF) wrist which is compatible with the da Vinci platform. The instrument's wrist is composed of a two DoF bending notched-nitinol tube pattern, for which a kinematic model has been developed. A base mechanism for controlling the wrist is designed for integration with the da Vinci Research Kit. A basic teleoperation task is successfully performed using two of the miniature instruments. The performance and accuracy of the instrument suggest that creating and accurately controlling a 2 mm diameter instrument is feasible and the design and modelling proposed in this work provide a basis for future miniature instrument development.

A study of modelling simplifications in ground vibration predictions for railway traffic at grade

Science.gov (United States)

Germonpré, M.; Degrande, G.; Lombaert, G.

2017-10-01

Accurate computational models are required to predict ground-borne vibration due to railway traffic. Such models generally require a substantial computational effort. Therefore, much research has focused on developing computationally efficient methods, by either exploiting the regularity of the problem geometry in the direction along the track or assuming a simplified track structure. This paper investigates the modelling errors caused by commonly made simplifications of the track geometry. A case study is presented investigating a ballasted track in an excavation. The soil underneath the ballast is stiffened by a lime treatment. First, periodic track models with different cross sections are analyzed, revealing that a prediction of the rail receptance only requires an accurate representation of the soil layering directly underneath the ballast. A much more detailed representation of the cross sectional geometry is required, however, to calculate vibration transfer from track to free field. Second, simplifications in the longitudinal track direction are investigated by comparing 2.5D and periodic track models. This comparison shows that the 2.5D model slightly overestimates the track stiffness, while the transfer functions between track and free field are well predicted. Using a 2.5D model to predict the response during a train passage leads to an overestimation of both train-track interaction forces and free field vibrations. A combined periodic/2.5D approach is therefore proposed in this paper. First, the dynamic axle loads are computed by solving the train-track interaction problem with a periodic model. Next, the vibration transfer to the free field is computed with a 2.5D model. This combined periodic/2.5D approach only introduces small modelling errors compared to an approach in which a periodic model is used in both steps, while significantly reducing the computational cost.

A statistical model for predicting muscle performance

Science.gov (United States)

Byerly, Diane Leslie De Caix

The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

Predictions of soil-water potentials in the north-western Sonoran Desert

Energy Technology Data Exchange (ETDEWEB)

Young, D.R.; Nobel, P.S.

1986-03-01

A simple computer model was developed to predict soil-water potential at a Sonoran Desert site. The variability of precipitation there, coupled with the low water-holding capacity of the sandy soil, result in large temporal and spatial variations in soil-water potential. Predicted soil-water potentials for depths of 5, 10 and 20 cm were in close agreement with measured values as the soil dried after an application of water. Predicted values at a depth of 10 cm, the mean rooting depth of Agave deserti and other succulents common at the study site, also agreed with soil-water potentials measured in the field throughout 1 year. Both soil-water potential and evaporation from the soil surface were very sensitive to simulated changes in the hydraulic conductivity of the soil. The annual duration of soil moisture adequate for succulents was dependent on the rainfall as well as on the spacing and amount of individual rainfalls. The portion of annual precipitation evaporated from the soil surface varied from 73% in a dry year (77 mm precipitation) to 59% in a wet year (597 mm). Besides using the actual precipitation events, simulations were performed using the figures for total monthly precipitation. Based on the average number of rainfalls for a particular month, the rainfall was distributed throughout the month in the model. Predictions using both daily and monthly inputs were in close agreement, especially for the number of days during a year when the soil-water potential was sufficient for water absorption by the succulent plants (above -0.5 MPa).

Computed Tomographic Imaging of Subchondral Fatigue Cracks in the Distal End of the Third Metacarpal Bone in the Thoroughbred Racehorse Can Predict Crack Micromotion in an Ex-Vivo Model

Science.gov (United States)

Dubois, Marie-Soleil; Morello, Samantha; Rayment, Kelsey; Markel, Mark D.; Vanderby, Ray; Kalscheur, Vicki L.; Hao, Zhengling; McCabe, Ronald P.; Marquis, Patricia; Muir, Peter

2014-01-01

Articular stress fracture arising from the distal end of the third metacarpal bone (MC3) is a common serious injury in Thoroughbred racehorses. Currently, there is no method for predicting fracture risk clinically. We describe an ex-vivo biomechanical model in which we measured subchondral crack micromotion under compressive loading that modeled high speed running. Using this model, we determined the relationship between subchondral crack dimensions measured using computed tomography (CT) and crack micromotion. Thoracic limbs from 40 Thoroughbred racehorses that had sustained a catastrophic injury were studied. Limbs were radiographed and examined using CT. Parasagittal subchondral fatigue crack dimensions were measured on CT images using image analysis software. MC3 bones with fatigue cracks were tested using five cycles of compressive loading at -7,500N (38 condyles, 18 horses). Crack motion was recorded using an extensometer. Mechanical testing was validated using bones with 3 mm and 5 mm deep parasagittal subchondral slots that modeled naturally occurring fatigue cracks. After testing, subchondral crack density was determined histologically. Creation of parasagittal subchondral slots induced significant micromotion during loading (pThoroughbred horses in-vivo to assess risk of condylar fracture. Horses with parasagittal crack arrays that exceed 30 mm2 may have a high risk for development of condylar fracture. PMID:25077477

Extracting falsifiable predictions from sloppy models.

Science.gov (United States)

Gutenkunst, Ryan N; Casey, Fergal P; Waterfall, Joshua J; Myers, Christopher R; Sethna, James P

2007-12-01

Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte-Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

Assessment of correlations and models for the prediction of CHF in water subcooled flow boiling

Science.gov (United States)

Celata, G. P.; Cumo, M.; Mariani, A.

1994-01-01

The present paper provides an analysis of available correlations and models for the prediction of Critical Heat Flux (CHF) in subcooled flow boiling in the range of interest of fusion reactors thermal-hydraulic conditions, i.e. high inlet liquid subcooling and velocity and small channel diameter and length. The aim of the study was to establish the limits of validity of present predictive tools (most of them were proposed with reference to light water reactors (LWR) thermal-hydraulic studies) in the above conditions. The reference dataset represents almost all available data (1865 data points) covering wide ranges of operating conditions in the frame of present interest (0.1 less than p less than 8.4 MPa; 0.3 less than D less than 25.4 mm; 0.1 less than L less than 0.61 m; 2 less than G less than 90.0 Mg/sq m/s; 90 less than delta T(sub sub,in) less than 230 K). Among the tens of predictive tools available in literature four correlations (Levy, Westinghouse, modified-Tong and Tong-75) and three models (Weisman and Ileslamlou, Lee and Mudawar and Katto) were selected. The modified-Tong correlation and the Katto model seem to be reliable predictive tools for the calculation of the CHF in subcooled flow boiling.

Detailed physical properties prediction of pure methyl esters for biodiesel combustion modeling

International Nuclear Information System (INIS)

An, H.; Yang, W.M.; Maghbouli, A.; Chou, S.K.; Chua, K.J.

2013-01-01

Highlights: ► Group contribution methods from molecular level have been used for the prediction. ► Complete prediction of the physical properties for 5 methyl esters has been done. ► The predicted results can be very useful for biodiesel combustion modeling. ► Various models have been compared and the best model has been identified. ► Predicted properties are over large temperature ranges with excellent accuracies. -- Abstract: In order to accurately simulate the fuel spray, atomization, combustion and emission formation processes of a diesel engine fueled with biodiesel, adequate knowledge of biodiesel’s physical properties is desired. The objective of this work is to do a detailed physical properties prediction for the five major methyl esters of biodiesel for combustion modeling. The physical properties considered in this study are: normal boiling point, critical properties, vapor pressure, and latent heat of vaporization, liquid density, liquid viscosity, liquid thermal conductivity, gas diffusion coefficients and surface tension. For each physical property, the best prediction model has been identified, and very good agreements have been obtained between the predicted results and the published data where available. The calculated results can be used as key references for biodiesel combustion modeling.

Progresses in Ab Initio QM/MM Free Energy Simulations of Electrostatic Energies in Proteins: Accelerated QM/MM Studies of pKa, Redox Reactions and Solvation Free Energies

Energy Technology Data Exchange (ETDEWEB)

Kamerlin, Shina C. L.; Haranczyk, Maciej; Warshel, Arieh

2009-03-01

Hybrid quantum mechanical / molecular mechanical (QM/MM) approaches have been used to provide a general scheme for chemical reactions in proteins. However, such approaches still present a major challenge to computational chemists, not only because of the need for very large computer time in order to evaluate the QM energy but also because of the need for propercomputational sampling. This review focuses on the sampling issue in QM/MM evaluations of electrostatic energies in proteins. We chose this example since electrostatic energies play a major role in controlling the function of proteins and are key to the structure-function correlation of biological molecules. Thus, the correct treatment of electrostatics is essential for the accurate simulation of biological systems. Although we will be presenting here different types of QM/MM calculations of electrostatic energies (and related properties), our focus will be on pKa calculations. This reflects the fact that pKa of ionizable groups in proteins provide one of the most direct benchmarks for the accuracy of electrostatic models of macromolecules. While pKa calculations by semimacroscopic models have given reasonable results in many cases, existing attempts to perform pKa calculations using QM/MM-FEP have led to large discrepancies between calculated and experimental values. In this work, we accelerate our QM/MM calculations using an updated mean charge distribution and a classical reference potential. We examine both a surface residue (Asp3) of the bovine pancreatic trypsin inhibitor, as well as a residue buried in a hydrophobic pocket (Lys102) of the T4-lysozyme mutant. We demonstrate that by using this approach, we are able to reproduce the relevant sidechain pKas with an accuracy of 3 kcal/mol. This is well within the 7 kcal/mol energy difference observed in studies of enzymatic catalysis, and is thus sufficient accuracy to determine the main contributions to the catalytic energies of enzymes. We also provide an

Improvement of diagnostic confidence for detection of multiple myeloma involvement of the ribs by a new CT software generating rib unfolded images: Comparison with 5- and 1-mm axial images

Energy Technology Data Exchange (ETDEWEB)

Homann, Georg; Mustafa, Deedar Farhad; Nikolaou, Konstantin; Horger, Marius [Eberhard Karls University Tuebingen, Department of Diagnostic and Interventional Radiology, Tuebingen (Germany); Weisel, Katja [Eberhard Karls University Tuebingen, Department of Internal Medicine II, Tuebingen (Germany); Ditt, Hendrik [Healthcare Sector Imaging and Therapy Division, Siemens AG, Forchheim (Germany)

2015-04-02

To investigate the performance of a new CT software generating rib unfolded images for improved detection of rib osteolyses in patients with multiple myeloma. One hundred sixteen patients who underwent whole-body reduced-dose multidetector computed tomography (WBRD-MDCT) for multiple myeloma diagnosis and during follow-up were retrospectively evaluated. Nonenhanced CT scans with 5- and 1-mm slice thickness were interpreted by two readers with focus on detection of rib involvement (location, number, fracture). Image analysis of ''unfolded,'' 1-mm-based CT rib images was subsequently undertaken. We classified the number of lytic bone lesions into 0, 1, 2, <5, <10 and ≥10. For all three data sets the reading time was registered. An approximated sum of 6,727 myeloma-related rib lesions was found. On a patient-based analysis, CT (5 mm), CT (1 mm) and CT (1 mm ''unfolded rib'') yielded a sensitivity, specificity and accuracy of 79.7/94.7/87.1, 88.1/93/90.5 and 98.3/96.5/97.4, respectively. In a lesion-based analysis, the sensitivity, specificity and accuracy of the three evaluations were 69.7/87.2/70.5, 79.8/55.9/78 and 96.5/89.7/96.1. Mean reading time for 5 mm/1 mm axial images and unfolded images was 178.7/215.1/90.8 s, respectively. The generation of ''unfolded rib'' images improves detection of rib involvement in patients with multiple myeloma and significantly reduces reading time. (orig.)

The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

Science.gov (United States)

Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

2015-05-01

A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

Science.gov (United States)

Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

2012-01-01

The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

Initial results from 50mm short SSC dipoles at Fermilab

International Nuclear Information System (INIS)

Bossert, R.C.; Brandt, J.S.; Carson, J.A.; Coulter, K.; Delchamps, S.; Ewald, K.D.; Fulton, H.; Gonczy, I.; Gourlay, S.A.; Jaffery, T.S.; Kinney, W.; Koska, W.; Lamm, M.J.; Strait, J.B.; Wake, M.; Gordon, M.; Hassan, N.; Sims, R.; Winters, M.

1991-03-01

Several short model SSC 50 mm bore dipoles are being built and tested at Fermilab. Mechanical design of these magnets has been determined from experience involved in the construction and testing of 40 mm dipoles. Construction experience includes coil winding, curing and measuring, coil end part design and fabrication, ground insulation, instrumentation, collaring and yoke assembly. Fabrication techniques are explained and construction problems are discussed. Similarities and differences from the 40 mm dipole tooling and management components are outlined. Test results from the first models are presented. 19 refs., 12 figs

EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH