208 research outputs found
One-step Multi-view Clustering with Diverse Representation
Multi-view clustering has attracted broad attention due to its capacity to
utilize consistent and complementary information among views. Although
tremendous progress has been made recently, most existing methods undergo high
complexity, preventing them from being applied to large-scale tasks. Multi-view
clustering via matrix factorization is a representative to address this issue.
However, most of them map the data matrices into a fixed dimension, which
limits the expressiveness of the model. Moreover, a range of methods suffer
from a two-step process, i.e., multimodal learning and the subsequent
-means, inevitably causing a sub-optimal clustering result. In light of
this, we propose a one-step multi-view clustering with diverse representation
method, which incorporates multi-view learning and -means into a unified
framework. Specifically, we first project original data matrices into various
latent spaces to attain comprehensive information and auto-weight them in a
self-supervised manner. Then we directly use the information matrices under
diverse dimensions to obtain consensus discrete clustering labels. The unified
work of representation learning and clustering boosts the quality of the final
results. Furthermore, we develop an efficient optimization algorithm to solve
the resultant problem with proven convergence. Comprehensive experiments on
various datasets demonstrate the promising clustering performance of our
proposed method
Performance Analysis of Buffer-Aided Relaying System Based on Data and Energy Coupling Queuing Model for Cooperative Communication Networks
Diketopiperazine alkaloids from a mangrove rhizosphere soil derived fungus Aspergillus effuses H1-1
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Early Gastric Cancer: Current Advances of Endoscopic Diagnosis and Treatment
Endoscopy is a major method for early gastric cancer screening because of its high detection rate, but its diagnostic accuracy depends heavily on the availability of endoscopic instruments. Many novel endoscopic techniques have been shown to increase the diagnostic yield of early gastric cancer. With the improved detection rate of EGC, the endoscopic treatment has become widespread due to advances in the instruments available and endoscopist’s experience. The aim of this review is to summarize frequently-used endoscopic diagnosis and treatment in early gastric cancer (EGC)
Key Lab on Wideband Wireless Communications and Sensor Network Technology of Ministry of Education
A fairness-aware resource allocation scheme in a cooperative orthogonal frequency division multiple (OFDM) network is proposed based on jointly optimizing the subcarrier pairing, power allocation, and channel-user assignment. Compared with traditional OFDM relaying networks, the source is permitted to retransfer the same data transmitted by it in the first time slot, further improving the system capacity performance. The problem which maximizes the energy efficiency (EE) of the system with total power constraint and minimal spectral efficiency constraint is formulated into a mixed-integer nonlinear programming (MINLP) problem which has an intractable complexity in general. The optimization model is simplified into a typical fractional programming problem which is testified to be quasiconcave. Thus we can adopt Dinkelbach method to deal with MINLP problem proposed to achieve the optimal solution. The simulation results show that the joint resource allocation method proposed can achieve an optimal EE performance under the minimum system service rate requirement with a good global convergence
H11-induced immunoprotection is predominantly linked to N-glycan moieties during Haemonchus contortus infection
Nematodes are one of the largest groups of animals on the planet. Many of them are major pathogens of humans, animals and plants, and cause destructive diseases and socioeconomic losses worldwide. Despite their adverse impacts on human health and agriculture, nematodes can be challenging to control, because anthelmintic treatments do not prevent re-infection, and excessive treatment has led to widespread drug resistance in nematode populations. Indeed, many nematode species of livestock animals have become resistant to almost all classes of anthelmintics used. Most efforts to develop commercial anti-nematode vaccines (native or recombinant) for use in animals and humans have not succeeded, although one effective (dead) vaccine (Barbervax) has been developed to protect animals against one of the most pathogenic parasites of livestock animals – Haemonchus contortus (the barber’s pole worm). This vaccine contains native molecules, called H11 and H-Gal-GP, derived from the intestine of this blood-feeding worm. In its native form, H11 alone consistently induces high levels (75-95%) of immunoprotection in animals against disease (haemonchosis), but recombinant forms thereof do not. Here, to test the hypothesis that post-translational modification (glycosylation) of H11 plays a crucial role in achieving such high immunoprotection, we explored the N-glycoproteome and N-glycome of H11 using the high-resolution mass spectrometry and assessed the roles of N-glycosylation in protective immunity against H. contortus. Our results showed conclusively that N-glycan moieties on H11 are the dominant immunogens, which induce high IgG serum antibody levels in immunised animals, and that anti-H11 IgG antibodies can confer specific, passive immunity in naïve animals. This work provides the first detailed account of the relevance and role of protein glycosylation in protective immunity against a parasitic nematode, with important implications for the design of vaccines against metazoan parasites.Peer Reviewe
Chloctanspirones A and B, novel chlorinated polyketides with an unprecedented skeleton, from marine sediment derived fungus Penicillium terrestre
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Isolation of an imported subgenotype B5 strain of human enterovirus A71 in Chongqing City, China, 2014
Single cell atlas for 11 non-model mammals, reptiles and birds.
The availability of viral entry factors is a prerequisite for the cross-species transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Large-scale single-cell screening of animal cells could reveal the expression patterns of viral entry genes in different hosts. However, such exploration for SARS-CoV-2 remains limited. Here, we perform single-nucleus RNA sequencing for 11 non-model species, including pets (cat, dog, hamster, and lizard), livestock (goat and rabbit), poultry (duck and pigeon), and wildlife (pangolin, tiger, and deer), and investigated the co-expression of ACE2 and TMPRSS2. Furthermore, cross-species analysis of the lung cell atlas of the studied mammals, reptiles, and birds reveals core developmental programs, critical connectomes, and conserved regulatory circuits among these evolutionarily distant species. Overall, our work provides a compendium of gene expression profiles for non-model animals, which could be employed to identify potential SARS-CoV-2 target cells and putative zoonotic reservoirs
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