1,736 research outputs found
EBUS-GS and VBN for GGO lesions
No full textBackground: Endobronchial ultrasonography with guide sheath (EBUS-GS) could be useful for diagnosing ground-glass opacity (GGO) predominant-type lesions in the peripheral lung. Furthermore, several studies have reported that transbronchial biopsy using EBUS-GS and virtual bronchoscopic navigation (VBN) was safe and effective for diagnosing small peripheral lung lesions. Our objectives were to diagnose solitary peripheral GGO predominant-type lesions by transbronchial biopsy using EBUS-GS and VBN under radiographic fluoroscopic guidance, and to evaluate the clinical factors associated with diagnostic yield. Methods: The medical records of 169 patients with GGO predominant-type lesions who underwent transbronchial biopsy using EBUS-GS and VBN under radiographic fluoroscopic guidance were retrospectively reviewed. Results: Endobronchial ultrasonography images could be obtained for 156 (92%) of 169 GGO predominant-type lesions, and 116 (69%) were successfully diagnosed by this method (20 of 31 pure GGO lesions [65%]; 96 of 138 mixed GGO predominant-type lesions [70%]). The mean size of diagnosed lesions was significantly larger than that of nondiagnosed lesions (22 mm versus 18 mm, p < 0.01). Regarding diagnostic yield based on computed tomography sign, cases with presence of a bronchus leading directly to a lesion had significantly higher diagnostic yield than the other lesions (p < 0.01). Conclusions: The addition of VBN to EBUS-GS could be useful in clinical practice for diagnosing GGO predominant-type lesions in the peripheral lung
Rigorous results on the strongly correlated electron systems by the spin-reflection-positivity method
No full textIn this talk, we shall briefly review some results on the strongly correlated electron systems, derived recently by applying Lieb's spin-reflection-positivity method. To explain the basic ideas of this method to a wide audience, we emphasize the important role played by Marshall's rule in studying the many-body systems.Physics, AppliedPhysics, Condensed MatterPhysics, MathematicalSCI(E)CPCI-S(ISTP)
Antiferromagnetic correlation in the half-filled strongly correlated electron models at nonzero temperature: A rigorous result
No full textAs an extension of our previous rigorous investigation on the spin correlations in the ground states of the half-filled Hubbard model and the periodic Anderson model [G. S. Tian, Phys. Rev. B 50, 6246 (1994)], in the present paper we study the behavior of these correlation functions at finite temperature. We show rigorously that, at any T not equal0, the predominant spin correlations in these systems are antiferromagnetic. Furthermore, based on this result, we also show that a quasi-one (or two)-dimensional itinerant electron ferrimagnet must have a gapless branch of ferromagnetic excitations. This conclusion is consistent with the previous results derived by the spin-wave theory.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000169283000058&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Physics, Condensed MatterSCI(E)10ARTICLE22null6
A 1-GS/s 6–8-b Cryo-CMOS SAR ADC for Quantum Computing
No full textThis article presents a two-times interleaved, loop-unrolled SAR analog-to-digital converter (ADC) operational from 300 down to 4.2 K. The 6-8-bit resolution and the sampling speed up to 1 GS/s are targeted at digitizing the multi-channel frequency-multiplexed input in a spin-qubit reflectometry readout for quantum computing. To optimize the circuit for the altered device behavior at cryogenic temperatures, a modified common-mode switching scheme is adopted as well as a flexible calibration. The design is implemented in 40-nm CMOS technology and achieves 36.2-dB signal to noise and distortion ratio (SNDR) for Nyquist input at 4.2 K while maintaining a Walden figure of merit (FOM textsubscript W) of 200 pJ/conv-step (for a 10.8-mW power consumption), including the clock receiver, and 15 pJ/conv-step (for a 0.8-mW power consumption) for just the core ADC. With these specifications, the ADC can support the simultaneous readout of 20 qubit channels with a power consumption of 0.5 mW/qubit, thus advancing toward the full integration of the cryogenic readout for future large-scale quantum processors.QCD/Sebastiano LabElectronicsQuantum Circuit Architectures and Technolog
Development of a numerical methodology for flowforming process simulation of complex geometry tubes
No full textPublisher Copyright: © 2017 Author(s).Nowadays, the incremental flowforming process is widely explored because of the usage of complex tubular products is increasing due to the light-weighting trend and the use of expensive materials. The enhanced mechanical properties of finished parts combined with the process efficiency in terms of raw material and energy consumption are the key factors for its competitiveness and sustainability, which is consistent with EU industry policy. As a promising technology, additional steps for extending the existing flowforming limits in the production of tubular products are required. The objective of the present research is to further expand the current state of the art regarding limitations on tube thickness and diameter, exploring the feasibility to flowform complex geometries as tubes of elevated thickness of up to 60 mm. In this study, the analysis of the backward flowforming process of 7075 aluminum tubular preform is carried out to define the optimum process parameters, machine requirements and tooling geometry as demonstration case. Numerical simulation studies on flowforming of thin walled tubular components have been considered to increase the knowledge of the technology. The calculation of the rotational movement of the mesh preform, the high ratio thickness/length and the thermomechanical condition increase significantly the computation time of the numerical simulation model. This means that efficient and reliable tools able to predict the forming loads and the quality of flowformed thick tubes are not available. This paper aims to overcome this situation by developing a simulation methodology based on FEM simulation code including new strategies. Material characterization has also been performed through tensile test to able to design the process. Finally, to check the reliability of the model, flowforming tests at industrial environment have been developed.Peer reviewe
The New Prostate Cancer Grading System Does Not Improve Prediction of Clinical Recurrence After Radical Prostatectomy: Results of a Large, Two‐Center Validation Study
No full textBACKGROUND. A new prostate cancer (PCa) grading system (namely, Gleason score-GS = 9) was recently proposed and assessed on biochemical recurrence ( BCR) showing improved predictive abilities compared to the commonly used three- tier system (GS = 8). We assessed the predictive ability of the five-tier grade group (GG) system on harder clinical endpoint, namely clinical recurrence (CR).METHODS. Between 2005 and 2014, 9,728 clinically localized PCa patients were treated with radical prostatectomy (RP) at two tertiary referral centers. Kaplan-Meier curves, multivariable Cox regression analyses, and concordance index (C-index) were used to assess CR after treatment according to four Gleason grade classifications at biopsy and RP: Group 1: = 8; Group 2: = 8; Group 3: = 9; Group 4: = 9. Same analyses were repeated in patients who had BCR (n = 1,624). Decision curve analyses were performed to evaluate and compare the net benefit associated with the use of the four Gleason grade classifications.RESULTS. Overall, 443 (4.6%) patients had CR. The hazard ratio of the GS 3 + 4, 4 + 3, 8, and >= 9 relative to GS <= 6 were 3.63, 5.93, 11.44, 18.08 and 4.93, 9.99, 15.31 and 25.12 in the pre-and post-treatment models, respectively. The C-index of the five-tier GG system was slightly higher relative to the other 3 Gleason grade classifications both in the pre-(range: 0.001-0.006) and post-treatment models (range: 0-0.008). Similar findings were observed when we focused our analyses in patients with BCR after RP. The use of the five-tier GG system did not result into higher net- benefit relative to the other three Gleason grade classifications.CONCLUSIONS. The difference in accuracy between the five-tier GG system and the other Gleason grade classifications, using CR as an endpoint, is clinically negligible. Current evidence suggests that the five-tier GG system represents a simplifieduser-friendly scheme available for patient counseling rather than a new histopathological diagnostic system that improves the prediction of CR. (C) 2016 Wiley Periodicals, Inc
Chromosome abnormalities in lymphocytes and fibroblasts of subjects with multiple endocrine neoplasia type 1.
No full textOptimizing Support Vector Machines with ISBA-A-gs Land Surface Variables as a Surrogate Model to Simulate ASCAT Derived Parameters
No full textThe TU-Wien developed a soil moisture retrieval algorithm that uses the incidence angle dependence of backscatter to obtain soil moisture estimates (Wagner et al., 1999). The core of this algorithm is a second order Taylor expansion with which the backscatter is normalized at a reference angle. Studies have shown that the first and second order derivative within this Taylor expansion, known as slope and curvature, are somehow related to the wet biomass and structure of vegetation. The general approach to forward model satellite observations with land surface variables in a data assimilation framework is through a radiative transfer model (Albergel et al., 2017). However, this requires plenty of assumptions about the vegetation canopy (such as stem height, shape, size, orientation etc.) and is therefore relatively inefficient for understanding the impact of soil moisture and vegetation dynamics on backscatter on a large scale. This study investigates the possibility of using support vector machines as a surrogate model instead of a radiative transfer model to link the TU-Wien normalized backscatter and slope to land surface variables soil moisture and leaf area index. The land surface variables are simulations from the CO2-responsive ISBA-A-gs land surface model. Support vector machines have the advantage of providing implicit kernel functions, which make them very useful for non-linear problems. The ISBA-A-gs data is provided by Météo-France. In total, 1324 support vector machines have been optimized through a cross validated grid search. The optimized hyperparameters were shown to have spatial consistency and look promising as an initial approach to forward modelling backscatter and slope. The SVM performances are further investigated through corresponding land cover types of grid points and the land surface variables.Geoscience and Remote Sensin
STABILITY OF THE NAGAOKA STATE IN THE ONE-BAND HUBBARD-MODEL
No full textWe discuss the stability of the saturated ferromagnetic state of the one-band Hubbard model in the thermodynamic limit. We prove rigorously that the Nagaoka state is stable on a d-dimensional (d = 2,3) simple-cubic lattice if the number of holes N(h) is less than N-LAMBDA-alpha, 0 less-than-or-equal-to alpha < 1/2d. Finally, we explain briefly why the Nagaoka state is probably unstable when N(h) >> N-LAMBDA-1/2d.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:A1991GD96700045&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Physics, Condensed MatterSCI(E)26ARTICLE94444-44484
Turning Maneuver Prediction of Connected Vehicles at Signalized Intersections: A Dictionary Learning-Based Approach
No full textVehicle-to-Infrastructure (V2I) communication has provided a solution for the improvement of the traffic efficiency of smart city intersections. For example, turning maneuvers prediction at signalized intersections in a connected environment helps traffic command centers time traffic lights and dynamically predict traffic flow. However, the modeling methods used in existing research on this topic have some limitations, such as poor scalability and interpretability of machine learning. Thus, this study proposes a dictionary learning-based approach to predict turning maneuvers before the intersection. The proposed dictionary model estimates the LogDet divergence-based sparse inverse covariance matrix (LDbSICM) of driving behavior samples. The graphical lasso method is used to estimate the sparse inverse covariance matrix of the driving samples to construct a dictionary library of the maneuver behavior. The LogDet divergence is used to calculate the difference between each inverse covariance matrix. A driving simulator is utilized to collect experimental data consisting of turning left (TL), turning right (TR), and going straight (GS) behaviors to establish and evaluate the proposed model. The experimental results demonstrate that the proposed dictionary learning-based turning maneuver prediction model achieves 100% prediction accuracy for TL and GS and 97.2% for TR. The proposed model has substantial advantages over existing methods. The model can predict TL, TR, and GS in a connected environment 270, 280, and 290 m, respectively, before the intersection. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
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