Exploring Object Relation in Mean Teacher for Cross-Domain Detection

Rendering synthetic data (e.g., 3D CAD-rendered images) to generate annotations for learning deep models in vision tasks has attracted increasing attention in recent years. However, simply applying the models learnt on synthetic images may lead to high generalization error on real images due to domain shift. To address this issue, recent progress in cross-domain recognition has featured the Mean Teacher, which directly simulates unsupervised domain adaptation as semi-supervised learning. The domain gap is thus naturally bridged with consistency regularization in a teacher-student scheme. In this work, we advance this Mean Teacher paradigm to be applicable for cross-domain detection. Specifically, we present Mean Teacher with Object Relations (MTOR) that novelly remolds Mean Teacher under the backbone of Faster R-CNN by integrating the object relations into the measure of consistency cost between teacher and student modules. Technically, MTOR firstly learns relational graphs that capture similarities between pairs of regions for teacher and student respectively. The whole architecture is then optimized with three consistency regularizations: 1) region-level consistency to align the region-level predictions between teacher and student, 2) inter-graph consistency for matching the graph structures between teacher and student, and 3) intra-graph consistency to enhance the similarity between regions of same class within the graph of student. Extensive experiments are conducted on the transfers across Cityscapes, Foggy Cityscapes, and SIM10k, and superior results are reported when comparing to state-of-the-art approaches. More remarkably, we obtain a new record of single model: 22.8% of mAP on Syn2Real detection dataset.Comment: CVPR 2019; The codes and model of our MTOR are publicly available at: https://github.com/caiqi/mean-teacher-cross-domain-detectio

A Multi-Level Approach to Waste Object Segmentation

We address the problem of localizing waste objects from a color image and an optional depth image, which is a key perception component for robotic interaction with such objects. Specifically, our method integrates the intensity and depth information at multiple levels of spatial granularity. Firstly, a scene-level deep network produces an initial coarse segmentation, based on which we select a few potential object regions to zoom in and perform fine segmentation. The results of the above steps are further integrated into a densely connected conditional random field that learns to respect the appearance, depth, and spatial affinities with pixel-level accuracy. In addition, we create a new RGBD waste object segmentation dataset, MJU-Waste, that is made public to facilitate future research in this area. The efficacy of our method is validated on both MJU-Waste and the Trash Annotation in Context (TACO) dataset.Comment: Paper appears in Sensors 2020, 20(14), 381

Invasiveness of the Yersinia pestis ail protein contributes to host dissemination in pneumonic and oral plague

Yersinia pestis, a Gram-negative bacterium, is the etiologic agent of plague. A hallmark of Y. pestis infection is the organism's ability to rapidly disseminate through an animal host. Y. pestis expresses the outer membrane protein, Ail (Attachment invasion locus), which is associated with host invasion and serum resistance. However, whether Ail plays a role in host dissemination remains unclear. In this study, C57BL/6J mice were challenged with a defined Y. pestis strain, KimD27, or an isogenic ail-deleted mutant derived from KimD27 via metacarpal paw pad inoculation, nasal drops, orogastric infection, or tail vein injection to mimic bubonic, pneumonic, oral, or septicemic plague, respectively. Our results showed that ail-deleted Y. pestis KimD27 lost the ability to invade host cells, leading to failed host dissemination in the pneumonic and oral plague models but not in the bubonic or septicemic plague models, which do not require invasiveness. Therefore, this study demonstrated that whether Ail plays a role in Y. pestis pathogenesis depends on the infection route.Peer reviewe

The Farnesyltransferase β-Subunit Ram1 Regulates Sporisorium scitamineum Mating, Pathogenicity and Cell Wall Integrity

The basidiomycetous fungus Sporisorium scitamineum causes a serious sugarcane smut disease in major sugarcane growing areas. Sexual mating is essential for infection to the host; however, its underlying molecular mechanism has not been fully studied. In this study, we identified a conserved farnesyltransferase (FTase) β subunit Ram1 in S. scitamineum. The ram1Δ mutant displayed significantly reduced mating/filamentation, thus of weak pathogenicity to the host cane. The ram1Δ mutant sporidia showed more tolerant toward cell wall stressor Congo red compared to that of the wild-type. Transcriptional profiling showed that Congo red treatment resulted in notable up-regulation of the core genes involving in cell wall integrity pathway in ram1Δ sporidia compared with that of WT, indicating that Ram1 may be involved in cell wall integrity regulation. In yeast the heterodimeric FTase is responsible for post-translational modification of Ras (small G protein) and a-factor (pheromone). We also identified and characterized two conserved Ras proteins, Ras1 and Ras2, respectively, and a MAT-1 pheromone precursor Mfa1. The ras1Δ, ras2Δ and mfa1Δ mutants all displayed reduced mating/filamentation similar as the ram1Δ mutant. However, both ras1Δ and ras2Δ mutants were hypersensitive to Congo red while the mfa1Δ mutant was the same as wild-type. Overall our study displayed that RAM1 plays an essential role in S. scitamineum mating/filamentation, pathogenicity, and cell wall stability

Dietary sodium enhances the expression of SLC4 family transporters, IRBIT, L-IRBIT, and PP1 in rat kidney: Insights into the molecular mechanism for renal sodium handling

The kidney plays a central role in maintaining the fluid and electrolyte homeostasis in the body. Bicarbonate transporters NBCn1, NBCn2, and AE2 are expressed at the basolateral membrane of the medullary thick ascending limb (mTAL). In a previous study, NBCn1, NBCn2, and AE2 are proposed to play as a regulatory pathway to decrease NaCl reabsorption in the mTAL under high salt condition. When heterologously expressed, the activity of these transporters could be stimulated by the InsP3R binding protein released with inositol 1,4,5-trisphosphate (IRBIT), L-IRBIT (collectively the IRBITs), or protein phosphatase PP1. In the present study, we characterized by immunofluorescence the expression and localization of the IRBITs, and PP1 in rat kidney. Our data showed that the IRBITs were predominantly expressed from the mTAL through the distal renal tubules. PP1 was predominantly expressed in the TAL, but is also present in high abundance from the distal convoluted tubule through the medullary collecting duct. Western blotting analyses showed that the abundances of NBCn1, NBCn2, and AE2 as well as the IRBITs and PP1 were greatly upregulated in rat kidney by dietary sodium. Co-immunoprecipitation study provided the evidence for protein interaction between NBCn1 and L-IRBIT in rat kidney. Taken together, our data suggest that the IRBITs and PP1 play an important role in sodium handling in the kidney. We propose that the IRBITs and PP1 stimulates NBCn1, NBCn2, and AE2 in the basolateral mTAL to inhibit sodium reabsorption under high sodium condition. Our study provides important insights into understanding the molecular mechanism for the regulation of sodium homeostasis in the body

The redshift evolution of the distribution of star formation among dark matter halos as seen in the infrared

Recent studies revealed a strong correlation between the star formation rate (SFR) and stellar mass of star-forming galaxies, the so-called star-forming main sequence. An empirical modeling approach (2-SFM) which distinguishes between the main sequence and rarer starburst galaxies is capable of reproducing most statistical properties of infrared galaxies. In this paper, we extend this approach by establishing a connection between stellar mass and halo mass with the technique of abundance matching. Based on a few, simple assumptions and a physically motivated formalism, our model successfully predicts the (cross-)power spectra of the cosmic infrared background (CIB), the cross-correlation between CIB and cosmic microwave background (CMB) lensing, and the correlation functions of bright, resolved infrared galaxies measured by Herschel, Planck, ACT and SPT. We use this model to infer the redshift distribution these observables, as well as the level of correlation between CIB-anisotropies at different wavelengths. We also predict that more than 90% of cosmic star formation activity occurs in halos with masses between 10^11.5 and 10^13.5 Msun. Taking into account subsequent mass growth of halos, this implies that the majority of stars were initially (at z>3) formed in the progenitors of clusters, then in groups at 0.5<z<3 and finally in Milky-Way-like halos at z<0.5. At all redshifts, the dominant contribution to the star formation rate density stems from halos of mass ~10^12 Msun, in which the instantaneous star formation efficiency is maximal (~70%). The strong redshift-evolution of SFR in the galaxies that dominate the CIB is thus plausibly driven by increased accretion from the cosmic web onto halos of this characteristic mass scale

Regional effects of China's monetary policy during the economic transition period: Based on China's city classification system under the new normal.

We analyse the regional effects of China's monetary policy during the economic transition period based on the city classification system under the New Normal. Using panel vector autoregressive (PVAR) models, we examine the differences in the influence of a unified monetary policy on four types of Chinese cities: first-tier, quasi-first-tier, second-tier, and third-tier cities, from perspective of economic output. Based on a comparative analysis of the results of impulse response function and variance decomposition, we conclude that whether for quantitative monetary policy or price-based monetary policy, the degree to which economic growth responds to the unified monetary policy varies across the four types of cities in the short and long terms. With reference to China's economic transition under the New Normal, in the short term, this phenomenon probably relate to the varying degrees of financial marketization among the four city types; in the long run, this phenomenon may be attributed to the difference in the progress of industrial upgrading of these urban areas. Based on the analysis above, we suggest policy implications for Chinese cities based on the structural monetary policy, industrial upgrading, and market-oriented financial sector reforms

Shockwave-Based Queue Estimation Approach For Undersaturated And Oversaturated Signalized Intersections Using Multi-Source Detection Data

With the progress of information and sensing technologies, estimating vehicular queue length at signalized intersections becomes feasible and has attracted considerable attention. The existing studies provided a solid theoretical foundation for the estimation; however, the studies have some restrictions or limitations more or less. This paper presents a new methodology for estimating vehicular queue length at signalized intersections using multi-source detection data under both undersaturated and oversaturated conditions. The methodology applies the shockwave theory to model queue dynamics. Using data from probe vehicles and point detectors, analytical formulations for calculating the maximum and minimum (residual) queue lengths of each cycle are developed. Ground truth data were collected from numerical experiments conducted at two intersections in Shanghai, China, to verify the proposed methodology. It is found that the methodology has mean absolute percentage errors of 17.09% and 12.28%, respectively, for maximum queue length estimation in two tests, which are reasonably effective. However, the methodology is unsatisfactory in estimating the residual queue length. Other limitations of the proposed models and algorithms are also discussed in the paper

Imbalance in Spatial Accessibility to Primary and Secondary Schools in China: Guidance for Education Sustainability

Compulsory education is an important aspect of the societal development. Meanwhile, education equality safeguards the effectiveness of education systems and is an important part of social equality. This study analyzes the inequality of compulsory education from the perspective of imbalanced spatial distribution. Unlike previous studies that have measured the spatial distribution of education simply based on the spatial position of primary and secondary schools, we explore spatial accessibility based on the shortest travel distance from residents to schools, and then analyze the inequality of compulsory education through the distribution of spatial accessibility. We use 2873 Chinese counties as statistical units, and perform a statistical and graphical analysis of their spatial accessibility using the Theil index and spatial autocorrelation analyses. To analyze the differences in the spatial accessibility distribution on the national and regional levels, we use three partitioned modes: the terrain partitioned mode, the economic development partitioned mode, and the province-level partitioned mode. We then analyze the spatial agglomeration characteristics and distribution patterns of compulsory education accessibility through global autocorrelation, local autocorrelation, and hot-spot and cold-spot analysis. The results demonstrate an obvious imbalance in the distribution of spatial accessibility to compulsory education at the national level. Accessibility and equality in eastern and central regions are significantly better than those in the western region; both are significantly better in coastal regions than in inland regions; and equality alone is better in the municipalities, such as Shanghai, Tianjin, and Chongqing, than in other provinces and autonomous regions. The spatial pattern analysis shows significant global autocorrelation and obvious clusters. Counties in cold-spot areas (clusters of good spatial accessibility) are large in number but small in size. Cold-spot areas present a ring-shaped structure in space with Henan Province as the core. Counties in hot-spot areas (clusters of weak spatial accessibility) are not as numerous, but most are large in size; hot-spot areas are mainly in the northwest regions, characterized by complex terrain and severe economic difficulty. This study can provide significant information to aid policy making related to compulsory education sustainability in China and can facilitate research on the equality and sustainable development of compulsory education