In this work, we study a more realistic challenging scenario in multiview clustering (MVC), referred to as incomplete MVC (IMVC) where some instances in certain views are missing. The key to IMVC is how to adequately exploit complementary and consistency information under the incompleteness of data. However, most existing methods address the incompleteness problem at the instance level and they require sufficient information to perform data recovery. In this work, we develop a new approach to facilitate IMVC based on the graph propagation perspective. Specifically, a partial graph is used to describe the similarity of samples for incomplete views, such that the issue of missing instances can be translated into the missing entries of the partial graph. In this way, a common graph can be adaptively learned to self-guide the propagation process by exploiting the consistency information, and the propagated graph of each view is in turn used to refine the common self-guided graph in an iterative manner. Thus, the associated missing entries can be inferred through graph propagation by exploiting the consistency information across all views. On the other hand, existing approaches focus on the consistency structure only, and the complementary information has not been sufficiently exploited due to the data incompleteness issue. By contrast, under the proposed graph propagation framework, an exclusive regularization term can be naturally adopted to exploit the complementary information in our method. Extensive experiments demonstrate the effectiveness of the proposed method in comparison with state-of-the-art methods. The source code of our method is available at the https://github.com/CLiu272/TNNLS-PGP.

A total of 334 Salmonella isolates were recovered from 6,223 pet rectal samples collected at 50 pet clinics, 42 pet shops, 7 residential areas, and 4 plazas. Forty serovars were identified that included all strains except for one isolate that did not cluster via self-agglutination, with Salmonella Typhimurium monophasic variant, Salmonella Kentucky, Salmonella Enteritidis, Salmonella Pomona, and Salmonella Give being the predominant serovars. Fifty-one sequence types were identified among the isolates, and ST198, ST11, ST19, ST451, ST34, and ST155 were the most common. The top four dominant antimicrobials to which isolates were resistant were sulfisoxazole, ampicillin, doxycycline, and tetracycline, and 217 isolates exhibited multidrug resistance. The prevalence of β-lactamase genes in Salmonella isolates was 59.6%, and among these isolates, 185 harbored blaTEM, followed by blaCTX-M (66) and blaOXA (10). Moreover, six PMQR genes, namely, including qnrA (4.8%), qnrB (4.2%), qnrD (0.9%), qnrS (18.9%), aac(6')-Ib-cr (16.5%), and oqxB (1.5%), were detected. QRDR mutations (76.6%) were very common in Salmonella isolates, with the most frequent mutation in parC (T57S) (47.3%). Furthermore, we detected six tetracycline resistance genes in 176 isolates, namely, tet(A) (39.5%), tet(B) (8.1%), tet(M) (7.7%), tet(D) (5.4%), tet(J) (3.3%), and tet(C) (1.8%), and three sulfonamide resistance genes in 303 isolates, namely, sul1 (84.4%), sul2 (31.1%), and sul3 (4.2%). Finally, we found 86 isolates simultaneously harboring four types of resistance genes that cotransferred 2-7 resistance genes to recipient bacteria. The frequent occurrence of antimicrobial resistance, particularly in dogs and cats, suggests that antibiotic misuse may be driving multidrug-resistant Salmonella among pets.IMPORTANCEPet-associated human salmonellosis has been reported for many years, and antimicrobial resistance in pet-associated Salmonella has become a serious public health problem and has attracted increasing attention. There are no reports of Salmonella from pets and their antimicrobial resistance in Chongqing, China. In this study, we investigated the prevalence, serovar diversity, sequence types, and antimicrobial resistance of Salmonella strains isolated from pet fecal samples in Chongqing. In addition, β-lactamase, QRDR, PMQR, tetracycline and sulfonamide resistance genes, and mutations in QRDRs in Salmonella isolates were examined. Our findings demonstrated the diversity of serovars and sequence types of Salmonella isolates. The isolates were widely resistant to antimicrobials, notably with a high proportion of multidrug-resistant strains, which highlights the potential direct or indirect transmission of multidrug-resistant Salmonella from pets to humans. Furthermore, resistance genes were widely prevalent in the isolates, and most of the resistance genes were spread horizontally between strains.