676 research outputs found
Weak degeneracy of regular graphs
Motivated by the study of greedy algorithms for graph coloring, Bernshteyn
and Lee introduced a generalization of graph degeneracy, which is called weak
degeneracy. In this paper, we show the lower bound of the weak degeneracy for
-regular graphs is exactly , which is tight. This
result refutes the conjecture of Bernshteyn and Lee on this lower bound
A Novel Multiplex Network-based Sensor Information Fusion Model and Its Application to Industrial Multiphase Flow System
This work was supported by National Natural Science Foundation of China under Grant No. 61473203, and the Natural Science Foundation of Tianjin, China under Grant No. 16JCYBJC18200.Peer reviewedPostprin
The optimal connection model for blood vessels segmentation and the MEA-Net
Vascular diseases have long been regarded as a significant health concern.
Accurately detecting the location, shape, and afflicted regions of blood
vessels from a diverse range of medical images has proven to be a major
challenge. Obtaining blood vessels that retain their correct topological
structures is currently a crucial research issue. Numerous efforts have sought
to reinforce neural networks' learning of vascular geometric features,
including measures to ensure the correct topological structure of the
segmentation result's vessel centerline. Typically, these methods extract
topological features from the network's segmentation result and then apply
regular constraints to reinforce the accuracy of critical components and the
overall topological structure. However, as blood vessels are three-dimensional
structures, it is essential to achieve complete local vessel segmentation,
which necessitates enhancing the segmentation of vessel boundaries.
Furthermore, current methods are limited to handling 2D blood vessel
fragmentation cases. Our proposed boundary attention module directly extracts
boundary voxels from the network's segmentation result. Additionally, we have
established an optimal connection model based on minimal surfaces to determine
the connection order between blood vessels. Our method achieves
state-of-the-art performance in 3D multi-class vascular segmentation tasks, as
evidenced by the high values of Dice Similarity Coefficient (DSC) and
Normalized Surface Dice (NSD) metrics. Furthermore, our approach improves the
Betti error, LR error, and BR error indicators of vessel richness and
structural integrity by more than 10% compared to other methods, and
effectively addresses vessel fragmentation and yields blood vessels with a more
precise topological structure.Comment: 19 page
Suppression and Enhancement of Boiling Associated with Multiple Droplet Impingement
Spray cooling has proven to be efficient in managing thermal load in high power
applications. Reliability of electronic products lies on the thermal management and
understanding of heat transfer mechanisms of the most commonly used thermal
management schemes such as spray cooling. Many experiments have been done to
understand the heat transfer mechanisms associated with spray cooling. However, most
of them have relied on comprehensive spray cooling experiments where multiple physical
variables are at play simultaneously. Furthermore, experiments with single streams of
droplets have not been able to elucidate the effects of the onset of boiling (ONB) during
the droplet impingement process. Therefore, efforts have been undertaken to consider the
effects of using three droplet streams arranged in a triangulated fashion. The effects of
using triangulated multiple droplet impingements on the suppression or enhancement of
boiling on heated surfaces has been investigated. Moreover, the effects of using screen
laminated on the suppression of ONB during the droplet impingement process has been
studied in detail. The main goal of this project is to study the effects of multiple droplet
impingement on the flat heater surface in the spray cooling with and without the use of
metallic screen laminates. Single and triple droplet impingement experiments have been
performed to understand the droplet behavior in spray cooling systems where multiple
droplets simultaneously impact a heated surface.
The experiments consisted of using a stainless steel screen laminate over a sample surface to observe the suppression or enhancement of pool boiling which tends to occur at the periphery of each droplet impingement zone. An infrared-based imaging technique was used to measure surface temperature during droplet impingement. The heat transfer performance has been evaluated in terms of heat flux, droplet frequency and volume flow rate. The results indicate that droplet stream spacing and the use of copper meshes can enhance surface cooling significantly. Specifically, droplet stream spacing of 1000 µm with copper meshes with a 6 mm hole and gap of 0.2 mm lead to enhanced surface cooling during the multiple droplet impingement process. It is expected that the results and conclusions of this study will be useful in understanding the physics of spray cooling which should help design better spray cooling system
A DEEP X-RAY SURVEY OF THE LOCKMAN HOLE NORTHWEST
I present the X-ray analysis of the Chandra Large Area Synoptic X-ray Survey (CLASXS) of the Lockman Hole Northwest field. The contiguous solid angle of the survey is about 0.4 sqr degree and the flux limits are 5x10^-16 erg/cm^2/s in the 0.4-2 keV band and 3x10^-15 erg/cm^2/s in the ~keV band. The survey bridges the gap between deep pencil beam surveys, and shallower, larger area surveys, allowing a better probe of the X-ray sources that contribute most of the 2--10 keV cosmic X-ray background. A total of 525 X-ray point sources and 4 extended sources have been found. The number counts, X-ray spectra evolution, X-ray variability of the X-ray sources are presented. We show 3 of the 4 extended sources are likely galaxy clusters or galaxy groups. We report the discovery of a gravitational lensing arc associated with one of these sources.
I present the spatial correlation function analysis of non-stellar X-ray point sources in the CLASXS and Chandra Deep Field North (CDFN). I calculate both redshift-space and projected correlation functions in comoving coordinates.The correlation function for the CLASXS field over scales of 3 Mpc < s < 200 Mpc can be modeled as a power-law of the form xi(s)=(s/s_0)^{-gamma}, with gamma = 1.6^{+0.4}_{-0.3} and s_0 = 8.05^{+1.4}_{-1.5} Mpc. The redshift-space correlation function for CDFN on scales of 1 Mpc <s < 100 Mpc is found to have a similar correlation length,
but a shallower slope. The real-space correlation functions are derived from the projected correlation functions. By comparing the real- and redshift-space correlation functions, we are able to estimate
the redshift distortion parameter beta = 0.4 +/- 0.2 at an effective redshift z = 0.94. We found the clustering does not dependence significantly on X-ray color or luminosity.
A mild evolution in the clustering amplitude is found, indicating a rapid increase of bias with redshift. The typical mass of the dark matter halo derived from the bias estimates show little change with redshift. The average halo mass is found to be log(M_{halo}/M_sun}) ~ 12.4
Determination of Boiling Range of Xylene Mixed in PX Device Using Artificial Neural Networks
Determination of boiling range of xylene mixed in PX device is currently a
crucial topic in the practical applications because of the recent disputes of
PX project in China. In our study, instead of determining the boiling range of
xylene mixed by traditional approach in laboratory or industry, we successfully
established two Artificial Neural Networks (ANNs) models to determine the
initial boiling point and final boiling point respectively. Results show that
the Multilayer Feedforward Neural Networks (MLFN) model with 7 nodes (MLFN-7)
is the best model to determine the initial boiling point of xylene mixed, with
the RMS error 0.18; while the MLFN model with 4 nodes (MLFN-4) is the best
model to determine the final boiling point of xylene mixed, with the RMS error
0.75. The training and testing processes both indicate that the models we
developed are robust and precise. Our research can effectively avoid the damage
of the PX device to human body and environment
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