Evaluating Cooling Tower Scheme and Mechanical Drag Coefficient Formulation in High-Resolution Regional Model

A cooling tower scheme considering quantitative sensible and latent heat flux released from air condition was implemented in building energy model (BEM) and coupled to the regional model (WRF). A mechanical drag coefficient formulation was implemented into the WRF/BEM to improve the representation of the wind speed in complex urban environments. Two simulations used default WRF/BEP+BEM and improved WRF/BEM to estimate the improvement effects focusing on dry day and wet day for summer 2015, respectively. The cooling tower system in commercial area not only induces the significant increase of the anthropogenic heat partition by 90% of the total heat flux releasing as latent but also further changes the surface heat flux feature. When the cooling tower is introduced, averaged surface latent heat flux in urban area is increased to about 60 W·m−2 with the peak of 150 W·m−2 in dry day and 40 W·m−2 with the peak of 150 W·m−2 in wet day. Maximum and minimum temperature error improved by 2–3 degrees. In the vertical model, the performance of boundary layer structure in rural area is much better than in urban area. The average wind speed error improved by 2–3 m/s in urban area with new calculation scheme

The role of TGF-β in the development of thyrocyte hyperplasia in NOD.H2h4 mice [abstract]

Faculty Mentor: Helen Mullen, ImmunologyAbstract only availableWild type (WT) NOD.H-2h4 mice develop lymphocytic spontaneous autoimmune thyroiditis (L-SAT) and IFN-γ-/- NOD.H-2h4 mice develop severe thyroid epithelial cell (TEC) hyperplasia when given 0.05% NaI water. Since hyperplastic TEC in IFN-γ-/- mice strongly express TGF-β, transgenic NOD.H-2h4 mice expressing TGF-β on TEC were generated to test the hypothesis that overexpression of TGF-β on TEC would promote earlier and/or more severe TEC hyperplasia. Consistent with this hypothesis, all IFN-γ-/- NOD.H-2h4 mice developed severe thyrocyte hyperplasia, and compared to WT Tg- mice with L-SAT, all WT Tg+ mice developed thyrocyte hyperplasia with minimal lymphocyte infiltration 2 months after NaI water. The goal of this study was to compare lymphocyte activation in WT transgenic and nontransgenic mice to determine the mechanisms by which overexpression of TGF-β in thyroids inhibits L-SAT in TGF-β transgenic WT mice. Flow cytometry indicated that CD4 and CD8 splenic T-cells from WT Tg- mice with L-SAT and WT Tg+ mice with severe hyperplasia were similarly activated. By RT-PCR, splenocytes of WT Tg+ mice expressed slightly higher levels of TGF-β compared to WT Tg- mice. However, other cytokines did not differ significantly between WT Tg+ and WT Tg- mice, suggesting lymphocytes in both groups were activated to a similar extent. Splenocytes from both WT Tg+ and WT Tg- mice induced L-SAT after transfer to NOD.H-2h4 SCID recipients, suggesting splenocytes from Tg+ mice were activated and could induce L-SAT in Tg- recipients. RT-PCR and immunohistochemical staining showed that thyroids of WT Tg+ mice expressed more TGF-β and less IFN-γ than WT Tg- thyroids. These results suggest that overexpression of TGF-β on thyrocytes inhibits L-SAT and promotes thyrocyte hyperplasia in NOD.H-2h4 mice. Further research is needed to determine the mechanism by which TGF-β mediates these effects

Interaction of RNA-binding protein HuR and miR-466i regulates GM-CSF expression.

Granulocyte-macrophage colony-stimulating factor (GM-CSF) produced by T helper 17 (Th17) cells plays an essential role in autoimmune diseases. Transcriptional regulation of Th17 cell differentiation has been extensively studied, but post-transcriptional regulation of Th17 cell differentiation has remained less well characterized. The RNA-binding protein HuR functions to promote the stability of target mRNAs via binding the AU-rich elements of the 3\u27 untranslated region (3\u27UTR) of numerous pro-inflammatory cytokines including IL-4, IL-13, IL-17 and TNF-α. However, whether HuR regulates GM-CSF expression in Th17 cells has not been fully investigated. Here we showed that HuR conditional knockout (KO) Th17 cells have decreased GM-CSF mRNA in comparison with wild-type (WT) Th17 cells, and that HuR binds directly to GM-CSF mRNA 3\u27UTR. Interestingly, HuR deficiency increased the levels of certain microRNA expression in Th17 cells; for example, miR-466i functioned to mediate GM-CSF and IL-17 mRNA decay, which was confirmed by in vitro luciferase assay. Furthermore, we found that HuR promoted Mxi1 expression to inhibit certain miRNA expression. Taken together, these findings indicate that interaction of HuR and miR-466i orchestrates GM-CSF expression in Th17 cells

The RNA-binding protein HuR contributes to neuroinflammation by promoting C-C chemokine receptor 6 (CCR6) expression on Th17 cells.

In both multiple sclerosis and experimental autoimmune encephalomyelitis (EAE), the C-C chemokine receptor 6 (CCR6) is critical for pathogenic T helper 17 (Th17) cell migration to the central nervous system (CNS). Whereas many cytokines and their receptors are potently regulated via post-transcriptional mechanisms in response to various stimuli, how CCR6 expression is post-transcriptionally regulated in Th17 cells is unknown. Here, using RNA-binding protein HuR conditional knock-out (KO) and wild-type (WT) mice, we present evidence that HuR post-transcriptionally regulates CCR6 expression by binding to and stabilizing Ccr6 mRNA and by promoting CCR6 translation. We also found that HuR down-regulates several microRNA expressions, which could target the 3\u27-UTR of Ccr6 mRNA for decay. Accordingly, knock-out of HuR reduced CCR6 expression on Th17 cells and impaired their migration to CNS compared with the response of WT Th17 cells and thereby ameliorated EAE. Together, these findings highlight how HuR contributes to Th17 cell-mediated autoimmune neuroinflammation and support the notion that targeting HuR might be a potential therapeutic intervention for managing autoimmune disorders of the CNS

B cell–deficient NOD.H-2h4 mice have CD4+CD25+ T regulatory cells that inhibit the development of spontaneous autoimmune thyroiditis

Wild-type (WT) NOD.H-2h4 mice develop spontaneous autoimmune thyroiditis (SAT) when given 0.05% NaI in their drinking water, whereas B cell–deficient NOD.H-2h4 mice are SAT resistant. To test the hypothesis that resistance of B cell–deficient mice to SAT was due to the activity of regulatory CD4+CD25+ T (T reg) cells activated if autoantigen was initially presented on non–B cells, CD25+ T reg cells were transiently depleted in vivo using anti-CD25. B cell–deficient NOD.H-2h4 mice given three weekly injections of anti-CD25 developed SAT 8 wk after NaI water. Thyroid lesions were similar to those in WT mice except there were no B cells in thyroid infiltrates. WT and B cell–deficient mice had similar numbers of CD4+CD25+Foxp3+ cells. Mice with transgenic nitrophenyl-specific B cells unable to secrete immunoglobulin were also resistant to SAT, and transient depletion of T reg cells resulted in severe SAT with both T and B cells in thyroid infiltrates. T reg cells that inhibit SAT were eliminated by day 3 thymectomy, indicating they belong to the subset of naturally occurring T reg cells. However, T reg cell depletion did not increase SAT severity in WT mice, suggesting that T reg cells may be nonfunctional when effector T cells are activated; i.e., by autoantigen-presenting B cells

Classifiability-based Optimal Discriminatory Projection Pursuit

Linear Discriminant Analysis (LDA) might be the most widely used linear feature extraction method in pattern recognition. Based on the analysis on the several limitations of traditional LDA, this paper makes an effort to propose a new computational paradigm named Optimal Discriminatory Projection Pursuit (ODPP), which is totally different from the traditional LDA and its variants. Only two simple steps are involved in the proposed ODPP: one is the construction of candidate projection set; the other is the optimal discriminatory projection pursuit. For the former step, candidate projections are generated as the difference vectors between nearest between-class boundary samples with redundancy well-controlled, while the latter is efficiently achieved by classifiability-based AdaBoost learning from the large candidate projection set. We show that the new 'projection pursuit' paradigm not only does not suffer from the limitations of the traditional LDA but also inherits good generalizability from the boundary attribute of candidate projections. Extensive experimental comparisons with LDA and its variants on synthetic and real data sets show that the proposed method consistently has better performances. ?2008 IEEE.EI

Analyzing urban traffic demand distribution and the correlation between traffic flow and the built environment based on detector data and POIs

Purpose This paper aims to determine the urban traffic flow spatiotemporal characteristics and correlation with the built environment using SCATS (Sydney Coordinated Adaptive Traffic System) and POIs (Point of Interests) data of Shenyang, China. Methods A standard analysis framework based on these data is proposed in the paper. The study analyzes the traffic volume spatiotemporal distributions and built environment influence factors determined by the geographical detector. An improved gravity model using simple structural parameters (lanes number and road length) is proposed to estimate the traffic flows of day and peak hour scales for specific flow ranges. Results The results show that the peak hours of different intersections and roads are heterogeneous and reveal trip time flexibility. The correlation between peak hour flows and day flows is significant in the multidimensional analysis. Based on the investigation of lanes, more interesting conclusions are found. In this case, when the numbers of lanes of intersections and roads are more than 14 and 4 respectively, the lane resources are wasted to a great extent. There is also a certain correlation between these factors. Proposed gravity model establishes the connection between structure and function of urban roads. Conclusions Flexible work time and places will be effective methods to reduce traffic congestion. The day flows could be estimated via a traffic survey on peak hour flows, especially in developing cities. The traffic flow mainly concentrates in a relatively small part of city roads. The maximum service traffic volumes exhibit segmentation, we should reconsider the maximum optimal lanes number of intersections and roads under better performance and utilization rate of the network. The effect of lanes number on the service traffic volumes is found to be more significant compared with the other factors. Our conclusions will be helpful for policy-makers and sustainable urban planning. Document type: Articl

Improving Face Sketch Recognition via Adversarial Sketch-Photo Transformation

International audiencefeature learning [7]-[10]. The benefit of the former category relates to the conversion of sketches into the same modality as photos, and hence lies in the ability to utilize existing photo-based face recognition methods. Thus, the applicability of the existing photo-based face recognition algorithms can be greatly expanded. Current methods for face photo-sketch transformation can be mainly grouped into example-based methods and regression-based methods. Example-based methods assume that the corresponding sketches (or patches of sketches) of two similar face photos (or patches of face photos) are also similar. Such methods rely on face photo-sketch pairs in the training set to synthesize images. In order to achieve good transformation results, these methods usually require a large number of photo-sketch pairs. However, the computational cost may also grow linearly with the increase of the training set size. Regression-based methods overcome the issues mentioned above and the most time-consuming part only exists in the training stage when learning the mapping between face photos and sketches, but the inference/testing stage can be fast. In this paper, we propose a Generative Adversarial Network (GAN) for face sketch-to-photo transformation , leveraging the advantages of CycleGAN [11] and conditional GANs [12]. We have designed a new feature-level loss, which is jointly used with the traditional image-level adversarial loss to ensure the quality of the synthesized photos. The proposed approach outperforms state-of-the-art approaches for synthesizing photos in terms of structural similarity index (SSIM). More importantly, the synthesized photos of our approach are found to be more instrumental in improving the sketch-to-photo matching accuracy. The rest of this paper is organized as follows: Section II summarizes representative methods of face photo-to-sketch transformation, and GANs. Section III provides details of the proposed method and the designed feature-level loss. Experimental results and analysis are presented in Section IV. Finally, we conclude this work in Section V. Abstract-Face sketch-photo transformation has broad applications in forensics, law enforcement, and digital entertainment, particular for face recognition systems that are designed for photo-to-photo matching. While there are a number of methods for face photo-to-sketch transformation, studies on sketch-to-photo transformation remain limited. In this paper, we propose a novel conditional CycleGAN for face sketch-to-photo transformation. Specifically, we leverage the advantages of CycleGAN and conditional GANs and design a feature-level loss to assure the high quality of the generated face photos from sketches. The generated face photos are used, as a replacement of face sketches, and particularly for face identification against a gallery set of mugshot photos. Experimental results on the public-domain database CUFSF show that the proposed approach is able to generate realistic photos from sketches, and the generated photos are instrumental in improving the sketch identification accuracy against a large gallery set