Generating Person Images with Appearance-aware Pose Stylizer

Generation of high-quality person images is challenging, due to the sophisticated entanglements among image factors, e.g., appearance, pose, foreground, background, local details, global structures, etc. In this paper, we present a novel end-to-end framework to generate realistic person images based on given person poses and appearances. The core of our framework is a novel generator called Appearance-aware Pose Stylizer (APS) which generates human images by coupling the target pose with the conditioned person appearance progressively. The framework is highly flexible and controllable by effectively decoupling various complex person image factors in the encoding phase, followed by re-coupling them in the decoding phase. In addition, we present a new normalization method named adaptive patch normalization, which enables region-specific normalization and shows a good performance when adopted in person image generation model. Experiments on two benchmark datasets show that our method is capable of generating visually appealing and realistic-looking results using arbitrary image and pose inputs.Comment: Appearing at IJCAI 2020. The code is available at https://github.com/siyuhuang/PoseStylize

A Simple yet Effective Framework for Active Learning to Rank

While China has become the biggest online market in the world with around 1 billion internet users, Baidu runs the world largest Chinese search engine serving more than hundreds of millions of daily active users and responding billions queries per day. To handle the diverse query requests from users at web-scale, Baidu has done tremendous efforts in understanding users' queries, retrieve relevant contents from a pool of trillions of webpages, and rank the most relevant webpages on the top of results. Among these components used in Baidu search, learning to rank (LTR) plays a critical role and we need to timely label an extremely large number of queries together with relevant webpages to train and update the online LTR models. To reduce the costs and time consumption of queries/webpages labeling, we study the problem of Activ Learning to Rank (active LTR) that selects unlabeled queries for annotation and training in this work. Specifically, we first investigate the criterion -- Ranking Entropy (RE) characterizing the entropy of relevant webpages under a query produced by a sequence of online LTR models updated by different checkpoints, using a Query-By-Committee (QBC) method. Then, we explore a new criterion namely Prediction Variances (PV) that measures the variance of prediction results for all relevant webpages under a query. Our empirical studies find that RE may favor low-frequency queries from the pool for labeling while PV prioritizing high-frequency queries more. Finally, we combine these two complementary criteria as the sample selection strategies for active learning. Extensive experiments with comparisons to baseline algorithms show that the proposed approach could train LTR models achieving higher Discounted Cumulative Gain (i.e., the relative improvement {\Delta}DCG4=1.38%) with the same budgeted labeling efforts.Comment: This paper is accepted to Machine Intelligence Research and a short version is presented in NeurIPS 2022 Workshop on Human in the Loop Learnin

The ecological impact of pest-induced tree dieback on insect biodiversity in Yunnan pine plantations, China

China has recently announced a reform of forestry policy, with a major goal being to transform from plantation to heterogeneous forests, which have higher resistance to pests and disease and house more biodiversity. One driver of reform is increased intensity and frequency of pest-induced tree-dieback events. To inform management, we ask what effects these events have on insect biodiversity in Pinus yunnanensis monocultures in Yunnan province, the province with one of the highest proportions of forest cover in China. We sampled aerial arthropods (mostly insect) biodiversity along gradients of Pinus yunnanensis dieback severity using Malaise traps and used metabarcoding to characterise the insect community. We used MS-GDM (‘multi-site generalized dissimilarity modelling of zeta diversity’), zeta-decline analysis, and iNEXT (‘Interpolation and extrapolation for species diversity’) to assess community change as functions of forest-structure covariates. Metabarcoding of Malaise-trapped insects reveals that bark-beetle induced forest dieback does not result in detectable differences in species diversity but does result in compositional change, with the biggest turnover occurring between 0% and infested-0%-open-canopy forests and 20%-infested-20%-open-canopy forests. Zeta-decline analysis found that the insect community in low-infestation forests is characterized by a stochastic assembly, while in high-infestation forests, the community structure is consistent with niche assembly. Our results thus suggest that bark-beetle dieback mimics natural forest-gap dynamics, consistent with the interpretation of bark beetles as a keystone species in European conifer forests, where it has been proposed that forest heterogeneity can be created efficiently by allowing natural disturbances, including bark-beetle outbreaks, to proceed naturally, without being mitigated by deadwood removal and dense replanting. In Yunnan’s situation, and given predicted increases in bark-beetle dieback severity and frequency, this strategy should probably be supplemented with anthropogenic treatments, such as deadwood enhancement and planting of multiple tree species, to accelerate the succession of plantations into heterogeneous forests

A Novel Role of Matrix Metalloproteinase-8 in Macrophage Differentiation and Polarization

This work forms part of the research themes contributing to the translational research portfolio of Barts and the London Cardiovascular Biomedical Research Unit, which is supported and funded by the National Institute of Health Research

Measuring protected-area effectiveness using vertebrate distributions from leech iDNA

Protected areas are key to meeting biodiversity conservation goals, but direct measures of effectiveness have proven difficult to obtain. We address this challenge by using environmental DNA from leech-ingested bloodmeals to estimate spatially-resolved vertebrate occupancies across the 677 km 2 Ailaoshan reserve in Yunnan, China. From 30,468 leeches collected by 163 park rangers across 172 patrol areas, we identify 86 vertebrate species, including amphibians, mammals, birds and squamates. Multi-species occupancy modelling shows that species richness increases with elevation and distance to reserve edge. Most large mammals (e.g. sambar, black bear, serow, tufted deer) follow this pattern; the exceptions are the three domestic mammal species (cows, sheep, goats) and muntjak deer, which are more common at lower elevations. Vertebrate occupancies are a direct measure of conservation outcomes that can help guide protected-area management and improve the contributions that protected areas make towards global biodiversity goals. Here, we show the feasibility of using invertebrate-derived DNA to estimate spatially-resolved vertebrate occupancies across entire protected areas

Sciences for The 2.5-meter Wide Field Survey Telescope (WFST)

The Wide Field Survey Telescope (WFST) is a dedicated photometric survey facility under construction jointly by the University of Science and Technology of China and Purple Mountain Observatory. It is equipped with a primary mirror of 2.5m in diameter, an active optical system, and a mosaic CCD camera of 0.73 Gpix on the main focus plane to achieve high-quality imaging over a field of view of 6.5 square degrees. The installation of WFST in the Lenghu observing site is planned to happen in the summer of 2023, and the operation is scheduled to commence within three months afterward. WFST will scan the northern sky in four optical bands (u, g, r, and i) at cadences from hourly/daily to semi-weekly in the deep high-cadence survey (DHS) and the wide field survey (WFS) programs, respectively. WFS reaches a depth of 22.27, 23.32, 22.84, and 22.31 in AB magnitudes in a nominal 30-second exposure in the four bands during a photometric night, respectively, enabling us to search tremendous amount of transients in the low-z universe and systematically investigate the variability of Galactic and extragalactic objects. Intranight 90s exposures as deep as 23 and 24 mag in u and g bands via DHS provide a unique opportunity to facilitate explorations of energetic transients in demand for high sensitivity, including the electromagnetic counterparts of gravitational-wave events detected by the second/third-generation GW detectors, supernovae within a few hours of their explosions, tidal disruption events and luminous fast optical transients even beyond a redshift of 1. Meanwhile, the final 6-year co-added images, anticipated to reach g about 25.5 mag in WFS or even deeper by 1.5 mag in DHS, will be of significant value to general Galactic and extragalactic sciences. The highly uniform legacy surveys of WFST will also serve as an indispensable complement to those of LSST which monitors the southern sky.Comment: 46 pages, submitted to SCMP

Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia

Integrative omics analysis reveals insights into small colony variants of Staphylococcus aureus induced by sulfamethoxazole-trimethoprim

Abstract Background Long-term treatment with trimethoprim-sulfamethoxazole (SXT) can lead to the formation of small-colony variants (SCVs) of Staphylococcus aureus. However, the mechanism behind SCVs formation remains poorly understood. In this study, we explored the phenotype and omics-based characterization of S. aureus SCVs induced by SXT and shed light on the potential causes of SCV formation. Methods Stable SCVs were obtained by continuously treating S. aureus isolates using 12/238 µg/ml of SXT, characterized by growth kinetics, antibiotic susceptibility testing, and auxotrophism test. Subsequently, a pair of representative strains (SCV and its parental strain) were selected for genomic, transcriptomic and metabolomic analysis. Results Three stable S. aureus SCVs were successfully screened and proven to be homologous to their corresponding parental strains. Phenotypic tests showed that all SCVs were non-classical mechanisms associated with impaired utilization of menadione, heme and thymine, and exhibited slower growth and higher antibiotic minimum inhibitory concentrations (MICs), compared to their corresponding parental strains. Genomic data revealed 15 missense mutations in 13 genes in the representative SCV, which were involved in adhesion, intramolecular phosphate transfer on ribose, transport pathways, and phage-encoded proteins. The combination analysis of transcriptome and metabolome identified 35 overlapping pathways possible associated with the phenotype switching of S. aureus. These pathways mainly included changes in metabolism, such as purine metabolism, pyruvate metabolism, amino acid metabolism, and ABC transporters, which could play a crucial role in promoting SCVs development by affecting nucleic acid synthesis and energy metabolism in bacteria. Conclusion This study provides profound insights into the causes of S. aureus SCV formation induced by SXT. The findings may offer valuable clues for developing new strategies to combat S. aureus SCV infections