The C∞-convergence of SG circle patterns to the Riemann mapping

AbstractThurston conjectured that the Riemann mapping function from a simply connected region onto the unit disk can be approximated by regular hexagonal packings. Schramm introduced circle patterns with combinatorics of the square grid (SG) and showed that SG circle patterns converge to meromorphic functions. He and Schramm proved that hexagonal disk packings converge in C∞ to the Riemann mapping. In this paper we show a similar C∞-convergence for SG circle patterns

Domain Adaptation and Image Classification via Deep Conditional Adaptation Network

Unsupervised domain adaptation aims to generalize the supervised model trained on a source domain to an unlabeled target domain. Marginal distribution alignment of feature spaces is widely used to reduce the domain discrepancy between the source and target domains. However, it assumes that the source and target domains share the same label distribution, which limits their application scope. In this paper, we consider a more general application scenario where the label distributions of the source and target domains are not the same. In this scenario, marginal distribution alignment-based methods will be vulnerable to negative transfer. To address this issue, we propose a novel unsupervised domain adaptation method, Deep Conditional Adaptation Network (DCAN), based on conditional distribution alignment of feature spaces. To be specific, we reduce the domain discrepancy by minimizing the Conditional Maximum Mean Discrepancy between the conditional distributions of deep features on the source and target domains, and extract the discriminant information from target domain by maximizing the mutual information between samples and the prediction labels. In addition, DCAN can be used to address a special scenario, Partial unsupervised domain adaptation, where the target domain category is a subset of the source domain category. Experiments on both unsupervised domain adaptation and Partial unsupervised domain adaptation show that DCAN achieves superior classification performance over state-of-the-art methods. In particular, DCAN achieves great improvement in the tasks with large difference in label distributions (6.1\% on SVHN to MNIST, 5.4\% in UDA tasks on Office-Home and 4.5\% in Partial UDA tasks on Office-Home)

Unsupervised Domain Adaptation via Discriminative Manifold Propagation

Unsupervised domain adaptation is effective in leveraging rich information from a labeled source domain to an unlabeled target domain. Though deep learning and adversarial strategy made a significant breakthrough in the adaptability of features, there are two issues to be further studied. First, hard-assigned pseudo labels on the target domain are arbitrary and error-prone, and direct application of them may destroy the intrinsic data structure. Second, batch-wise training of deep learning limits the characterization of the global structure. In this paper, a Riemannian manifold learning framework is proposed to achieve transferability and discriminability simultaneously. For the first issue, this framework establishes a probabilistic discriminant criterion on the target domain via soft labels. Based on pre-built prototypes, this criterion is extended to a global approximation scheme for the second issue. Manifold metric alignment is adopted to be compatible with the embedding space. The theoretical error bounds of different alignment metrics are derived for constructive guidance. The proposed method can be used to tackle a series of variants of domain adaptation problems, including both vanilla and partial settings. Extensive experiments have been conducted to investigate the method and a comparative study shows the superiority of the discriminative manifold learning framework.Comment: To be published in IEEE Transactions on Pattern Analysis and Machine Intelligenc

Screening and analysis of soda saline-alkali stress induced up- regulated genes in sugar sorghum

Soil salinization severely constrains the growth of crops, which ultimately leads to reduced yields. Because Sorghum dochna (common name sugar sorghum) has the advantageous properties of excellent salt stress resis- tance, high biomass, and tremendous flexibility for utilization as food, livestock feed, and industrial products, this species holds great potential to be further developed as a primary alternative crop. To elucidate the molecular mechanism that governs sugar sorghum’s adaptation to high salinity environments, we constructed a suppression subtractive hybridization (SSH) cDNA library from sugar sorghum transcripts that contains the soda saline-alkali induced up-regulated genes from the resistant variety M-81E. The SSH cDNA library was screened by using the colony hybridization method, and the ESTs obtained were sequenced and analyzed. A total of 200 EST clones were identified, representing 127 unigenes (6 contigs and 121 singlets). A Blast analysis showed that 48 ESTs (46.6%) have annotated functions in GenBank, 55 ESTs (53.4%) have unknown functions (or encode hypothetical proteins), and 24 ESTs (18.9%) have no blast hits. The majority of the hypothetical ESTs from the cDNA library displayed very high sequence similarity with their homologs found through GenBank. A clustering analysis of the ESTs with known functions indicated that a wide variety of genes were induced during the salt stress treatment. These genes were found to function in photosynthesis, material and energy metabolism (carbohydrates, lipids, amino acids, co-enzymes, ions, etc.), synthesis or maintenance of constituents of the cell wall and cell membrane, signal transduction, transcriptional regulation, and as water channels. This indicates that sugar sorghum tolerance to soda saline-alkali stress results from the coordinated functions of many genes

Screening and analysis of soda saline-alkali stress induced up- regulated genes in sugar sorghum

Soil salinization severely constrains the growth of crops, which ultimately leads to reduced yields. Because Sorghum dochna (common name sugar sorghum) has the advantageous properties of excellent salt stress resistance, high biomass, and tremendous flexibility for utilization as food, livestock feed, and industrial products, this species holds great potential to be further developed as a primary alternative crop. To elucidate the molecular mechanism that governs sugar sorghum’s adaptation to high salinity environments, we constructed a suppression subtractive hybridization (SSH) cDNA library from sugar sorghum transcripts that contains the soda saline-alkali induced up-regulated genes from the resistant variety M-81E. The SSH cDNA library was screened by using the colony hybridization method, and the ESTs obtained were sequenced and analyzed. A total of 200 EST clones were identified, representing 127 unigenes (6 contigs and 121 singlets). A Blast analysis showed that 48 ESTs (46.6%) have annotated functions in GenBank, 55 ESTs (53.4%) have unknown functions (or encode hypothetical proteins), and 24 ESTs (18.9%) have no blast hits. The majority of the hypothetical ESTs from the cDNA library displayed very high sequence similarity with their homologs found through GenBank. A clustering analysis of the ESTs with known functions indicated that a wide variety of genes were induced during the salt stress treatment. These genes were found to function in photosynthesis, material and energy metabolism (carbohydrates, lipids, amino acids, co-enzymes, ions, etc.), synthesis or maintenance of constituents of the cell wall and cell membrane, signal transduction, transcriptional regulation, and as water channels. This indicates that sugar sorghum tolerance to soda saline-alkali stress results from the coordinated functions of many genes

第702回千葉医学会例会・第1内科教室同門会例会 5.

Significance of the difference on evolutionary rates and the number of PTM sites between different types of proteins. (XLSX 9 kb

Integrated label-free erbium-doped fiber laser biosensing system for detection of single cell Staphylococcus aureus

A critical challenge to realize ultra-high sensitivity with optical fiber interferometers for label free biosensing is to achieve high quality factors (Q-factor) in liquid. In this work a high Q-factor of 105, which significantly improves the detection resolution is described based on a structure of single mode -core-only -single mode fiber (SCS) with its multimode (or Mach-Zehnder) interference effect as a filter that is integrated into an erbium-doped fiber laser (EDFL) system for excitation. In the case study, the section of core-only fiber is functionalized with porcine immunoglobulin G (IgG) antibodies, which could selectively bind to bacterial pathogen of Staphylococcus aureus (S. aureus). The developed microfiber-based biosensing platform called SCS-based EDFL biosensors can effectively detect concentrations of S. aureus from 10 to 105 CFU/mL, with a responsivity of 42.6 p.m./(CFU/mL) for the wavelength shift of the measured spectrum. The limit of detection (LoD) is estimated as 7.3 CFU/mL based on the measurement of S. aureus with minimum concentration of 10 CFU/mL. In addition, when a lower concentration of 1 CFU/mL is applied to the biosensor, a wavelength shift of 0.12 nm is observed in 10% of samples (1/10), indicating actual LoD of 1 CFU/mL for the proposed biosensor. Attributed to its good sensitivity, stability, reproducibility and specificity, the proposed EDFL based biosensing platform has great potentials for diagnostics

Measurement of the polarisation of W bosons produced with large transverse momentum in pp collisions at sqrt(s) = 7 TeV with the ATLAS experiment

This paper describes an analysis of the angular distribution of W->enu and W->munu decays, using data from pp collisions at sqrt(s) = 7 TeV recorded with the ATLAS detector at the LHC in 2010, corresponding to an integrated luminosity of about 35 pb^-1. Using the decay lepton transverse momentum and the missing transverse energy, the W decay angular distribution projected onto the transverse plane is obtained and analysed in terms of helicity fractions f0, fL and fR over two ranges of W transverse momentum (ptw): 35 < ptw < 50 GeV and ptw > 50 GeV. Good agreement is found with theoretical predictions. For ptw > 50 GeV, the values of f0 and fL-fR, averaged over charge and lepton flavour, are measured to be : f0 = 0.127 +/- 0.030 +/- 0.108 and fL-fR = 0.252 +/- 0.017 +/- 0.030, where the first uncertainties are statistical, and the second include all systematic effects.Comment: 19 pages plus author list (34 pages total), 9 figures, 11 tables, revised author list, matches European Journal of Physics C versio