Unpaired Multi-View Graph Clustering with Cross-View Structure Matching

Multi-view clustering (MVC), which effectively fuses information from multiple views for better performance, has received increasing attention. Most existing MVC methods assume that multi-view data are fully paired, which means that the mappings of all corresponding samples between views are pre-defined or given in advance. However, the data correspondence is often incomplete in real-world applications due to data corruption or sensor differences, referred as the data-unpaired problem (DUP) in multi-view literature. Although several attempts have been made to address the DUP issue, they suffer from the following drawbacks: 1) Most methods focus on the feature representation while ignoring the structural information of multi-view data, which is essential for clustering tasks; 2) Existing methods for partially unpaired problems rely on pre-given cross-view alignment information, resulting in their inability to handle fully unpaired problems; 3) Their inevitable parameters degrade the efficiency and applicability of the models. To tackle these issues, we propose a novel parameter-free graph clustering framework termed Unpaired Multi-view Graph Clustering framework with Cross-View Structure Matching (UPMGC-SM). Specifically, unlike the existing methods, UPMGC-SM effectively utilizes the structural information from each view to refine cross-view correspondences. Besides, our UPMGC-SM is a unified framework for both the fully and partially unpaired multi-view graph clustering. Moreover, existing graph clustering methods can adopt our UPMGC-SM to enhance their ability for unpaired scenarios. Extensive experiments demonstrate the effectiveness and generalization of our proposed framework for both paired and unpaired datasets.Comment: 15 page

Fast Continual Multi-View Clustering with Incomplete Views

Multi-view clustering (MVC) has gained broad attention owing to its capacity to exploit consistent and complementary information across views. This paper focuses on a challenging issue in MVC called the incomplete continual data problem (ICDP). In specific, most existing algorithms assume that views are available in advance and overlook the scenarios where data observations of views are accumulated over time. Due to privacy considerations or memory limitations, previous views cannot be stored in these situations. Some works are proposed to handle it, but all fail to address incomplete views. Such an incomplete continual data problem (ICDP) in MVC is tough to solve since incomplete information with continual data increases the difficulty of extracting consistent and complementary knowledge among views. We propose Fast Continual Multi-View Clustering with Incomplete Views (FCMVC-IV) to address it. Specifically, it maintains a consensus coefficient matrix and updates knowledge with the incoming incomplete view rather than storing and recomputing all the data matrices. Considering that the views are incomplete, the newly collected view might contain samples that have yet to appear; two indicator matrices and a rotation matrix are developed to match matrices with different dimensions. Besides, we design a three-step iterative algorithm to solve the resultant problem in linear complexity with proven convergence. Comprehensive experiments on various datasets show the superiority of FCMVC-IV

Scalable Incomplete Multi-View Clustering with Structure Alignment

The success of existing multi-view clustering (MVC) relies on the assumption that all views are complete. However, samples are usually partially available due to data corruption or sensor malfunction, which raises the research of incomplete multi-view clustering (IMVC). Although several anchor-based IMVC methods have been proposed to process the large-scale incomplete data, they still suffer from the following drawbacks: i) Most existing approaches neglect the inter-view discrepancy and enforce cross-view representation to be consistent, which would corrupt the representation capability of the model; ii) Due to the samples disparity between different views, the learned anchor might be misaligned, which we referred as the Anchor-Unaligned Problem for Incomplete data (AUP-ID). Such the AUP-ID would cause inaccurate graph fusion and degrades clustering performance. To tackle these issues, we propose a novel incomplete anchor graph learning framework termed Scalable Incomplete Multi-View Clustering with Structure Alignment (SIMVC-SA). Specially, we construct the view-specific anchor graph to capture the complementary information from different views. In order to solve the AUP-ID, we propose a novel structure alignment module to refine the cross-view anchor correspondence. Meanwhile, the anchor graph construction and alignment are jointly optimized in our unified framework to enhance clustering quality. Through anchor graph construction instead of full graphs, the time and space complexity of the proposed SIMVC-SA is proven to be linearly correlated with the number of samples. Extensive experiments on seven incomplete benchmark datasets demonstrate the effectiveness and efficiency of our proposed method. Our code is publicly available at https://github.com/wy1019/SIMVC-SA

Sequencing and Genomic Diversity Analysis of IncHI5 Plasmids

IncHI plasmids could be divided into five different subgroups IncHI1–5. In this study, the complete nucleotide sequences of seven blaIMP- or blaVIM-carrying IncHI5 plasmids from Klebsiella pneumoniae, K. quasipneumoniae, and K. variicola were determined and compared in detail with all the other four available sequenced IncHI5 plasmids. These plasmids carried conserved IncHI5 backbones composed of repHI5B and a repFIB-like gene (replication), parABC (partition), and tra1 (conjugal transfer). Integration of a number of accessory modules, through horizontal gene transfer, at various sites of IncHI5 backbones resulted in various deletions of surrounding backbone regions and thus considerable diversification of IncHI5 backbones. Among the accessory modules were three kinds of resistance accessory modules, namely Tn10 and two antibiotic resistance islands designated ARI-A and ARI-B. These two islands, inserted at two different fixed sites (one island was at one site and the other was at a different site) of IncHI5 backbones, were derived from the prototype Tn3-family transposons Tn1696 and Tn6535, respectively, and could be further discriminated as various intact transposons and transposon-like structures. The ARI-A or ARI-B islands from different IncHI5 plasmids carried distinct profiles of antimicrobial resistance markers and associated mobile elements, and complex events of transposition and homologous recombination accounted for assembly of these islands. The carbapenemase genes blaIMP-4, blaIMP-38 and blaVIM-1 were identified within various class 1 integrons from ARI-A or ARI-B of the seven plasmids sequenced in this study. Data presented here would provide a deeper insight into diversification and evolution history of IncHI5 plasmids

Molecular Encapsulation of Naphthalene Diimide (NDI) Based π-Conjugated Polymers: A Tool for Understanding Photoluminescence.

Funder: Royal Society; Id: http://dx.doi.org/10.13039/501100000288Funder: Winton Programme for the Physics of SustainabilityConjugated polymers are an important class of chromophores for optoelectronic devices. Understanding and controlling their excited state properties, in particular, radiative and non-radiative recombination processes are among the greatest challenges that must be overcome. We report the synthesis and characterization of a molecularly encapsulated naphthalene diimide-based polymer, one of the most successfully used motifs, and explore its structural and optical properties. The molecular encapsulation enables a detailed understanding of the effect of interpolymer interactions. We reveal that the non-encapsulated analogue P(NDI-2OD-T) undergoes aggregation enhanced emission; an effect that is suppressed upon encapsulation due to an increasing π-interchain stacking distance. This suggests that decreasing π-stacking distances may be an attractive method to enhance the radiative properties of conjugated polymers in contrast to the current paradigm where it is viewed as a source of optical quenching

Frequent alterations in cytoskeleton remodelling genes in primary and metastatic lung adenocarcinomas

The landscape of genetic alterations in lung adenocarcinoma derived from Asian patients is largely uncharacterized. Here we present an integrated genomic and transcriptomic analysis of 335 primary lung adenocarcinomas and 35 corresponding lymph node metastases from Chinese patients. Altogether 13 significantly mutated genes are identified, including the most commonly mutated gene TP53 and novel mutation targets such as RHPN2, GLI3 and MRC2. TP53 mutations are furthermore significantly enriched in tumours from patients harbouring metastases. Genes regulating cytoskeleton remodelling processes are also frequently altered, especially in metastatic samples, of which the high expression level of IQGAP3 is identified as a marker for poor prognosis. Our study represents the first large-scale sequencing effort on lung adenocarcinoma in Asian patients and provides a comprehensive mutational landscape for both primary and metastatic tumours. This may thus form a basis for personalized medical care and shed light on the molecular pathogenesis of metastatic lung adenocarcinoma

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

Stable acceptor-donor-acceptor type open-shell diradical with ultra-narrow bandgap and efficient photothermal conversion

It has been reported recently that open-shell diradical character could exist in narrow bandgap donor-acceptor (D-A) organic semiconductors in our previous work. The A-D-A type molecules play as important role in the organic electronic such as donors and acceptors (ITIC and Y6) in organic solar cells. However, their relatively poor chemical and photostability prevent their industrial application. In this work, we reported a stable A-D-A type open-shell diradical, named LY1-4Cl, by replacing the 2-(3-oxo-2,3-dihydro-1H-inden-1-yli-dene)malononitrile (IC)-series end group of typical closed-shell non-fullerene acceptor IT-4Cl. The new electron-withdrawing building block could give LY1-4Cl the redshift near-infrared (NIR) absorption, the smaller bandgap and highly enhanced photostability comparing with IT-4Cl. The open-shell diradical character of LY1-4Cl originates from the formation of quinoid diradical form. Moreover, benefiting from the broad NIR absorption and radical-promoted nonradiative transition, LY1-4Cl displayed high photothermal properties that an increasing temperature of 188℃ was recorded within 60 s under 808 nm laser irradiation of 0.8 W cm-2. This research provides a new strategy to design IC-free A-D-A type open-shell quinoid diradical with ultra-narrow bandgap, good photostability and efficient photothermal conversion