294 research outputs found
Riemannian Acceleration with Preconditioning for symmetric eigenvalue problems
In this paper, we propose a Riemannian Acceleration with Preconditioning
(RAP) for symmetric eigenvalue problems, which is one of the most important
geodesically convex optimization problem on Riemannian manifold, and obtain the
acceleration. Firstly, the preconditioning for symmetric eigenvalue problems
from the Riemannian manifold viewpoint is discussed. In order to obtain the
local geodesic convexity, we develop the leading angle to measure the quality
of the preconditioner for symmetric eigenvalue problems. A new Riemannian
acceleration, called Locally Optimal Riemannian Accelerated Gradient (LORAG)
method, is proposed to overcome the local geodesic convexity for symmetric
eigenvalue problems. With similar techniques for RAGD and analysis of local
convex optimization in Euclidean space, we analyze the convergence of LORAG.
Incorporating the local geodesic convexity of symmetric eigenvalue problems
under preconditioning with the LORAG, we propose the Riemannian Acceleration
with Preconditioning (RAP) and prove its acceleration. Additionally, when the
Schwarz preconditioner, especially the overlapping or non-overlapping domain
decomposition method, is applied for elliptic eigenvalue problems, we also
obtain the rate of convergence as , where is a constant
independent of the mesh sizes and the eigenvalue gap,
, is
the parameter from the stable decomposition, and
are the smallest two eigenvalues of the elliptic operator. Numerical results
show the power of Riemannian acceleration and preconditioning.Comment: Due to the limit in abstract of arXiv, the abstract here is shorter
than in PD
Frame-wise streaming end-to-end speaker diarization with non-autoregressive self-attention-based attractors
This work proposes a frame-wise online/streaming end-to-end neural
diarization (FS-EEND) method in a frame-in-frame-out fashion. To frame-wisely
detect a flexible number of speakers and extract/update their corresponding
attractors, we propose to leverage a causal speaker embedding encoder and an
online non-autoregressive self-attention-based attractor decoder. A look-ahead
mechanism is adopted to allow leveraging some future frames for effectively
detecting new speakers in real time and adaptively updating speaker attractors.
The proposed method processes the audio stream frame by frame, and has a low
inference latency caused by the look-ahead frames. Experiments show that,
compared with the recently proposed block-wise online methods, our method
FS-EEND achieves state-of-the-art diarization results, with a low inference
latency and computational cost
Subthreshold α2-Adrenergic Activation Counteracts Glucagon-Like Peptide-1 Potentiation of Glucose-Stimulated Insulin Secretion
The pancreatic β cell harbors α2-adrenergic and glucagon-like peptide-1 (GLP-1) receptors on its plasma membrane to sense the corresponding ligands adrenaline/noradrenaline and GLP-1 to govern glucose-stimulated insulin secretion. However, it is not known whether these two signaling systems interact to gain the adequate and timely control of insulin release in response to glucose. The present work shows that the α2-adrenergic agonist clonidine concentration-dependently depresses glucose-stimulated insulin secretion from INS-1 cells. On the contrary, GLP-1 concentration-dependently potentiates insulin secretory response to glucose. Importantly, the present work reveals that subthreshold α2-adrenergic activation with clonidine counteracts GLP-1 potentiation of glucose-induced insulin secretion. This counteractory process relies on pertussis toxin- (PTX-) sensitive Gi proteins since it no longer occurs following PTX-mediated inactivation of Gi proteins. The counteraction of GLP-1 potentiation of glucose-stimulated insulin secretion by subthreshold α2-adrenergic activation is likely to serve as a molecular mechanism for the delicate regulation of insulin release
Salient Object Detection via Integrity Learning
Albeit current salient object detection (SOD) works have achieved fantastic
progress, they are cast into the shade when it comes to the integrity of the
predicted salient regions. We define the concept of integrity at both the micro
and macro level. Specifically, at the micro level, the model should highlight
all parts that belong to a certain salient object, while at the macro level,
the model needs to discover all salient objects from the given image scene. To
facilitate integrity learning for salient object detection, we design a novel
Integrity Cognition Network (ICON), which explores three important components
to learn strong integrity features. 1) Unlike the existing models that focus
more on feature discriminability, we introduce a diverse feature aggregation
(DFA) component to aggregate features with various receptive fields (i.e.,,
kernel shape and context) and increase the feature diversity. Such diversity is
the foundation for mining the integral salient objects. 2) Based on the DFA
features, we introduce the integrity channel enhancement (ICE) component with
the goal of enhancing feature channels that highlight the integral salient
objects at the macro level, while suppressing the other distracting ones. 3)
After extracting the enhanced features, the part-whole verification (PWV)
method is employed to determine whether the part and whole object features have
strong agreement. Such part-whole agreements can further improve the
micro-level integrity for each salient object. To demonstrate the effectiveness
of ICON, comprehensive experiments are conducted on seven challenging
benchmarks, where promising results are achieved
Experimental study on critical heat flux characteristics of R134a flow boiling in horizontal helically-coiled tubes
Critical heat flux (CHF) experiments were performed to study the R134a CHF characteristics in horizontal helically-coiled tubes. The stainless steel test sections were heated uniformly, with tube inner diameters of 3.8e11 mm, coil diameters of 135e370 mm, helical pitches of 40e105 mm and heated lengths of 0.85e7.54 m. The experimental conditions are pressures of 0.30e1.10 MPa, mass fluxes of 60e480 kg m 2 s 1, inlet qualities of 0.32e0.36 and heat fluxes of 6.0 103e9.0 104Wm 2. It was found that the wall temperatures jumped abruptly once the CHF occurred. The CHF values decrease with increasing heated lengths, coil diameters and inner diameters, but the DNB (departure from nucleate boiling) CHF seems independent when length-to-diameter L/di> 200. The coil-to-diameter ratios are more important than length-to-diameter ratios for CHF in helically-coiled tubes, while the helical pitches have little effect on CHF. The CHF value increases greatly with increasing mass flux and decreases smoothly with increasing pressure. It decreases nearly linearly with increasing inlet and critical qualities, but it varies more acutely at xcr< 0.5 than higher critical qualities. New correlations for R134a flow boiling CHF in horizontal helically-coiled tubes were developed for applications
cis-Diammine(glycolato-κ2 O 1,O 2)platinum(II)
The reaction of cis-[Pt(NO3)2(NH3)2] and sodium glycolate yielded the title compound, [Pt(C2H2O3)(NH3)2]. The PtII atom, coordinated by two N atoms of ammine and two O atoms of the carboxylate and oxido groups of the glycolate ligand, is in a square-planar environment. In the crystal structure, molecules are connected by intermolecular N—H⋯O hydrogen bonds, forming a three-dimensional network
Multi-Host Model-Based Identification of \u3ci\u3eArmillifer agkistrodontis\u3c/i\u3e (Pentastomida), a New Zoonotic Parasite from China
Background: Pentastomiasis is a rare parasitic infection of humans. Pentastomids are dioecious obligate parasites requiring multiple hosts to complete their life cycle. Despite their worm-like appearance, they are commonly placed into a separate sub-class of the subphylum Crustacea, phylum Arthropoda. However, their systematic position is not uncontested and historically, they have been considered as a separate phylum.
Methodology/Principal Findings: An appraisal of Armillifer agkistrodontis was performed in terms of morphology and genetic identification after its lifecycle had been established in a multi-host model, that is, mice and rats as intermediate hosts, and snakes (Agkistrodon acutus and Python molurus) as definitive hosts. Different stages of the parasite, including eggs, larvae and adults, were isolated and examined morphologically using light and electron microscopes. Phylogenetic and cluster analysis were also undertaken, focusing on the 18S rRNA and the Cox1 gene. The time for lifecycle completion was about 14 months, including 4 months for the development of eggs to infectious larvae in the intermediate host and 10 months for infectious larvae to mature in the final host. The main morphological difference between A. armillatus and Linguatula serrata is the number of abdominal annuli. Based on the 18S rRNA sequence, the shortest hereditary distance was found between A. agkistrodontis and Raillietiella spp. The highest degree of homology in the Cox 1 nucleic acid sequences and predicted amino acid sequences was found between A. agkistrodontis and A. armillatus.
Conclusion: This is the first time that a multi-host model of the entire lifecycle of A. agkistrodontis has been established. Morphologic and genetic analyses supported the notion that pentastomids should be placed into the phylum Arthropoda
Multi-host Model-Based Identification of Armillifer agkistrodontis (Pentastomida), a New Zoonotic Parasite from China
Little information is currently available on the lifecycle and morphology of pentastomids, a new zoonotic parasite in China. The lifecycle of Armillifer agkistrodontis was established in multiple hosts, i.e., an intermediate host and a definitive host, and the parasite examined in terms of morphology and genetic relationship with other species. The time required for the completion of an entire lifecycle was about 14 months. The main morphological difference between A. armillatus and L. serrata is the number of abdominal annuli. The genetic data supported the notion that pentastomids belong to the phylum Arthropoda. Based on the 18S rRNA sequence, the shortest hereditary distance was found between A. agkistrodontis and Raillietiella spp. The highest similarity in the Cox 1 nucleic acid sequences was found between A. agkistrodontis and A. armillatus. The established multi-host model provides a possible approach to confirm suspected infections and offers an opportunity to further study this parasite
IHTC14-23415 DRY-OUT CHF CHARACTERISTICS OF R134a FLOW BOILING IN A HORIZONTAL HELICALLY-COILED TUBE
ABSTRACT An experimental study was carried out to investigate the dry-out critical heat flux (CHF) characteristics of R134a flow boiling in a horizontal helically-coiled tube. The test section was heated uniformly by DC high-power sources and the geometrical parameters are the outer diameter of 10 mm, inner diameter of 8. In total of sixty-eight 0.2 mm T-type thermocouples were set along the tube to measure wall temperatures exactly. A method based on the event-driven Agilent BenchLink Data Logger Pro software was developed to determine the occurrence of CHF. It was found that the wall temperatures jumped abruptly once the CHF occurred. The CHF usually starts to form at the front and offside (270°and 90°) of the sections near outlet. The CHF value increases largely with increasing mass flux and decreases slightly with increasing pressure. It decreases nearly linearly with increasing inlet qualities, while it decreases acutely with increasing critical qualities under larger mass flux conditions. An experimental correlation was developed to estimate dry-out CHF of R134a flow boiling in horizontal helically-coiled tubes under current conditions compared with the calculated results of Bowring and Shah correlations
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