135 research outputs found
ECM-OPCC: Efficient Context Model for Octree-based Point Cloud Compression
Recently, deep learning methods have shown promising results in point cloud
compression. For octree-based point cloud compression, previous works show that
the information of ancestor nodes and sibling nodes are equally important for
predicting current node. However, those works either adopt insufficient context
or bring intolerable decoding complexity (e.g. >600s). To address this problem,
we propose a sufficient yet efficient context model and design an efficient
deep learning codec for point clouds. Specifically, we first propose a
window-constrained multi-group coding strategy to exploit the autoregressive
context while maintaining decoding efficiency. Then, we propose a dual
transformer architecture to utilize the dependency of current node on its
ancestors and siblings. We also propose a random-masking pre-train method to
enhance our model. Experimental results show that our approach achieves
state-of-the-art performance for both lossy and lossless point cloud
compression. Moreover, our multi-group coding strategy saves 98% decoding time
compared with previous octree-based compression method
Resonant dipolar collisions of ultracold molecules induced by microwave dressing
We demonstrate microwave dressing on ultracold, fermionic
NaK ground-state molecules and observe resonant dipolar
collisions with cross sections exceeding three times the -wave unitarity
limit. The origin of these collisions is the resonant alignment of the
approaching molecules' dipoles along the intermolecular axis, which leads to
strong attraction. We explain our observations with a conceptually simple
two-state picture based on the Condon approximation. Furthermore, we perform
coupled-channels calculations that agree well with the experimentally observed
collision rates. While collisions are observed here as laser-induced loss,
microwave dressing on chemically stable molecules trapped in box potentials may
enable the creation of strongly interacting dipolar gases of molecules.Comment: 6 pages, 4 figure
Flatband Line States in Photonic Super-Honeycomb Lattices
We establish experimentally a photonic super-honeycomb lattice (sHCL) by use
of a cw-laser writing technique, and thereby demonstrate two distinct flatband
line states that manifest as noncontractible-loop-states in an infinite
flatband lattice. These localized states (straight and zigzag lines) observed
in the sHCL with tailored boundaries cannot be obtained by superposition of
conventional compact localized states because they represent a new topological
entity in flatband systems. In fact, the zigzag-line states, unique to the
sHCL, are in contradistinction with those previously observed in the Kagome and
Lieb lattices. Their momentum-space spectrum emerges in the high-order
Brillouin zone where the flat band touches the dispersive bands, revealing the
characteristic of topologically protected bandcrossing. Our experimental
results are corroborated by numerical simulations based on the coupled mode
theory. This work may provide insight to Dirac like 2D materials beyond
graphene
A holistic review on fatigue properties of additively manufactured metals
Additive manufacturing (AM) technology is undergoing rapid development and
emerging as an advanced technique that can fabricate complex near-net shaped
and light-weight metallic parts with acceptable strength and fatigue
performance. A number of studies have indicated that the strength or other
mechanical properties of AM metals are comparable or even superior to that of
conventionally manufactured metals, but the fatigue performance is still a
thorny problem that may hinder the replacement of currently used metallic
components by AM counterparts when the cyclic loading and thus fatigue failure
dominates. This article reviews the state-of-art published data on the fatigue
properties of AM metals, principally including -- data and fatigue crack
growth data. The AM techniques utilized to generate samples in this review
include powder bed fusion (e.g., EBM, SLM, DMLS) and directed energy deposition
(e.g., LENS, WAAM). Further, the fatigue properties of AM metallic materials
that involve titanium alloys, aluminum alloys, stainless steel, nickel-based
alloys, magnesium alloys, and high entropy alloys, are systematically
overviewed. In addition, summary figures or tables for the published data on
fatigue properties are presented for the above metals, the AM techniques, and
the influencing factors (manufacturing parameters, e.g., built orientation,
processing parameter, and post-processing). The effects of build direction,
particle, geometry, manufacturing parameters, post-processing, and
heat-treatment on fatigue properties, when available, are provided and
discussed. The fatigue performance and main factors affecting the fatigue
behavior of AM metals are finally compared and critically analyzed, thus
potentially providing valuable guidance for improving the fatigue performance
of AM metals.Comment: 201 pages, 154 figure
Simultaneous Identification of Multiple Causal Mutations in Rice
Next-generation sequencing technologies (NGST) are being used to discover causal mutations in ethyl methanesulfonate (EMS)-mutagenized plant populations. However, the published protocols often deliver too many candidate sites and sometimes fail to find the mutant gene of interest. Accurate identification of the causal mutation from massive background polymorphisms and sequencing deficiencies remains challenging. Here we describe a NGST-based method, named SIMM, that can simultaneously identify the causal mutations in multiple independent mutants. Multiple rice mutants derived from the same parental line were back-crossed, and for each mutant, the derived F2 individuals of the recessive mutant phenotype were pooled and sequenced. The resulting sequences were aligned to the Nipponbare reference genome, and single nucleotide polymorphisms (SNPs) were subsequently compared among the mutants. Allele index (AI) and Euclidean distance (ED) were incorporated into the analysis to reduce noises caused by background polymorphisms and re-sequencing errors. Corrections of sequence bias against GC- and AT-rich sequences in the candidate region were conducted when necessary. Using this method, we successfully identified seven new mutant alleles from Huanghuazhan (HHZ), an elite indica rice cultivar in China. All mutant alleles were validated by phenotype association assay.Guangdong Innovative Research Team Program [201001S0104725509]; Ministry of Agriculture Transgenic Project [2012ZX08001001]; National Program on Key Basic Research Project of China [973 Program] [2011CB100101, 2013CBA01402]; National High Technology Research and Development Program of China [863 Program] [2014AA10A602]; Natural Science Foundation of China [31110103917]; Shenzhen Commission on Innovation and Technology [KQF201109160004A, CXZZ20140411140647863]SCI(E)ARTICLE
Ultra-high strength metal matrix composites (MMCs) with extended ductility manufactured by size-controlled powder and spherical cast tungsten carbide
The main challenge of particle reinforced metal matrix composites (MMCs) is balancing strength and ductility. This research uses type 420 stainless steel and spherical cast tungsten carbide (WC/W2C) with a similar powder size and range as raw powders to manufacture laser powder bed fusion (LPBF) 420 + 5 wt% WC/W2C MMCs. LPBF 420 + 5 wt% WC/W2C MMCs contain austenite, martensite, and W-rich carbides (WC/W2C, FeW3C, M6C, and M7C3) from nanometre to micrometre scale. The well-balanced composition creates a crack-free reaction layer between the reinforced particles and matrix. This reaction layer consists of two distinct layers, depending on the element concentration. The LPBF 420 + 5 wt% WC/W2C MMCs achieved an excellent compressive strength of ∼5.5 GPa and a considerable fracture strain exceeding 50 %. The underlying mechanisms for the improved mechanical properties are discussed, providing further insight to advance the application of MMCs via additive manufacturing
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