664 research outputs found
Improving Autonomous Vehicle Mapping and Navigation in Work Zones Using Crowdsourcing Vehicle Trajectories
Prevalent solutions for Connected and Autonomous vehicle (CAV) mapping
include high definition map (HD map) or real-time Simultaneous Localization and
Mapping (SLAM). Both methods only rely on vehicle itself (onboard sensors or
embedded maps) and can not adapt well to temporarily changed drivable areas
such as work zones. Navigating CAVs in such areas heavily relies on how the
vehicle defines drivable areas based on perception information. Difficulties in
improving perception accuracy and ensuring the correct interpretation of
perception results are challenging to the vehicle in these situations. This
paper presents a prototype that introduces crowdsourcing trajectories
information into the mapping process to enhance CAV's understanding on the
drivable area and traffic rules. A Gaussian Mixture Model (GMM) is applied to
construct the temporarily changed drivable area and occupancy grid map (OGM)
based on crowdsourcing trajectories. The proposed method is compared with SLAM
without any human driving information. Our method has adapted well with the
downstream path planning and vehicle control module, and the CAV did not
violate driving rule, which a pure SLAM method did not achieve.Comment: Presented at TRBAM. Journal version in progres
SSHNN: Semi-Supervised Hybrid NAS Network for Echocardiographic Image Segmentation
Accurate medical image segmentation especially for echocardiographic images
with unmissable noise requires elaborate network design. Compared with manual
design, Neural Architecture Search (NAS) realizes better segmentation results
due to larger search space and automatic optimization, but most of the existing
methods are weak in layer-wise feature aggregation and adopt a ``strong
encoder, weak decoder" structure, insufficient to handle global relationships
and local details. To resolve these issues, we propose a novel semi-supervised
hybrid NAS network for accurate medical image segmentation termed SSHNN. In
SSHNN, we creatively use convolution operation in layer-wise feature fusion
instead of normalized scalars to avoid losing details, making NAS a stronger
encoder. Moreover, Transformers are introduced for the compensation of global
context and U-shaped decoder is designed to efficiently connect global context
with local features. Specifically, we implement a semi-supervised algorithm
Mean-Teacher to overcome the limited volume problem of labeled medical image
dataset. Extensive experiments on CAMUS echocardiography dataset demonstrate
that SSHNN outperforms state-of-the-art approaches and realizes accurate
segmentation. Code will be made publicly available.Comment: Submitted to ICASSP202
Observation of spin-tensor induced topological phase transitions of triply degenerate points with a trapped ion
Triply degenerate points (TDPs), which correspond to new types of topological
semimetals, can support novel quasiparticles possessing effective integer spins
while preserving Fermi statistics. Here by mapping the momentum space to the
parameter space of a three-level system in a trapped ion, we experimentally
explore the transitions between different types of TDPs driven by
spin-tensor--momentum couplings. We observe the phase transitions between TDPs
with different topological charges by measuring the Berry flux on a loop
surrounding the gap-closing lines, and the jump of the Berry flux gives the
jump of the topological charge (up to a factor) across the transitions.
For the Berry flux measurement, we employ a new method by examining the
geometric rotations of both spin vectors and tensors, which lead to a
generalized solid angle equal to the Berry flux. The controllability of
multi-level ion offers a versatile platform to study high-spin physics and our
work paves the way to explore novel topological phenomena therein.Comment: 9 pages, 10 figure
Clinical Efficacy of Temozolomide and Its Predictors in Aggressive Pituitary Tumors and Pituitary Carcinomas: A Systematic Review and Meta-Analysis
Background: A growing number of evidences suggest that TMZ applications can generate impressive benefits for APT and PC patients. However, the definite role of TMZ for individuals remains unclarified due to the variation between studies. And the predictive factors to alter its efficacy remain debatable.Objective: To evaluate the long-term effectiveness and safety profile of TMZ in the treatment of pituitary malignancies, and delineate the predictors during its clinical employment.Results: A literature retrieval was conducted from online databases for studies published up to December 31, 2020. Twenty one studies involving 429 patients were identified. TMZ exhibited 41% radiological overall response rate (rORR). The biochemical response rate was determinate in 53% of the functioning subset. Two-year and 4-year survival rate were 79 and 61%, respectively. TMZ prolonged the median PFS and OS as 20.18 and 40.24 months. TMZ-related adverse events occurred in 19% of patients. Regarding predictors of TMZ response, rORR was dramatically improved in patients with low/intermediate MGMT expression than those with high-MGMT (>50%) (p < 0.001). The benefit of TMZ varied according to functioning subtype of patients, with greater antitumor activities in functioning subgroups and fewer activities in non-functioning sets (p < 0.001). Notably, the concomitant therapy of radiotherapy and TMZ significantly increased the rORR (p = 0.007).Conclusion: TMZ elicits clinical benefits with moderate adverse events in APT and PC patients. MGMT expression and clinical subtype of secreting function might be vital predictors of TMZ efficacy. In the future, the combination of radiotherapy with TMZ may further improve the clinical outcomes than TMZ monotherapy
Nodal s± pairing symmetry in an iron-based superconductor with only hole pockets
The origin of high-temperature superconductivity in iron-based superconductors is still not understood; determination of the pairing symmetry is essential for understanding the superconductivity mechanism. In the iron-based superconductors that have hole pockets around the Brillouin zone centre and electron pockets around the zone corners, the pairing symmetry is generally considered to be s±, which indicates a sign change in the superconducting gap between the hole and electron pockets. For the iron-based superconductors with only hole pockets, however, a couple of pairing scenarios have been proposed, but the exact symmetry is still controversial. Here we determine that the pairing symmetry in KFe2As2—which is a prototypical iron-based superconductor with hole pockets both around the zone centre and around the zone corners—is also of the s± type. Our laser-based angle-resolved photoemission measurements have determined the superconducting gap distribution and identified the locations of the gap nodes on all the Fermi surfaces around the zone centres and the zone corners. These results unify the pairing symmetry in hole-doped iron-based superconductors and point to spin fluctuation as the pairing glue in generating superconductivity
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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