A Novel Euler's Elastica based Segmentation Approach for Noisy Images via using the Progressive Hedging Algorithm

Euler's Elastica based unsupervised segmentation models have strong capability of completing the missing boundaries for existing objects in a clean image, but they are not working well for noisy images. This paper aims to establish a Euler's Elastica based approach that properly deals with random noises to improve the segmentation performance for noisy images. We solve the corresponding optimization problem via using the progressive hedging algorithm (PHA) with a step length suggested by the alternating direction method of multipliers (ADMM). Technically, all the simplified convex versions of the subproblems derived from the major framework of PHA can be obtained by using the curvature weighted approach and the convex relaxation method. Then an alternating optimization strategy is applied with the merits of using some powerful accelerating techniques including the fast Fourier transform (FFT) and generalized soft threshold formulas. Extensive experiments have been conducted on both synthetic and real images, which validated some significant gains of the proposed segmentation models and demonstrated the advantages of the developed algorithm

WHAT WE OWE TO THE GLOBAL POOR: A DISCUSSION OF THOMAS POGGE'S VIEW

Master'sMASTER OF ART

Dense Invariant Feature Based Support Vector Ranking for Cross-Camera Person Re-identification

Recently, support vector ranking has been adopted to address the challenging person re-identification problem. However, the ranking model based on ordinary global features cannot well represent the significant variation of pose and viewpoint across camera views. To address this issue, a novel ranking method which fuses the dense invariant features is proposed in this paper to model the variation of images across camera views. An optimal space for ranking is learned by simultaneously maximizing the margin and minimizing the error on the fused features. The proposed method significantly outperforms the original support vector ranking algorithm due to the invariance of the dense invariant features, the fusion of the bidirectional features and the adaptive adjustment of parameters. Experimental results demonstrate that the proposed method is competitive with state-of-the-art methods on two challenging datasets, showing its potential for real-world person re-identification

Starch/microcrystalline cellulose hybrid gels as gastric-floating drug delivery systems

We report hybrid gels based on a high-amylose starch and microcrystalline cellulose with demonstrated properties for gastric-floating drug delivery purposes. The starch/cellulose gels were prepared by ionic liquid dissolution and regeneration, resulting in a continuous surface and a porous interior and a type-II crystalline structure of cellulose. These polysaccharide gels displayed satisfactory elasticity (0.88), recovery (0.26–0.36) and equilibrium swelling (1013–1369%). The hybrid gels were loaded with ranitidine hydrochloride as a model drug and subsequently, low-density starch/cellulose tablets were fabricated by vacuum-freeze-drying. In vitro tests in a simulated gastric fluid indicate that the 3:7 (wt./wt.) starch/cellulose system could maintain the buoyancy for up to 24 h with a release of 45.87% for the first 1 h and a sustained release for up to 10 h. Therefore, our results have demonstrated the excellent gastric-floating ability and sustainable drug release behavior of the starch/cellulose hybrid gels

Nosocomial outbreak of KPC-2- and NDM-1-producing Klebsiella pneumoniae in a neonatal ward: a retrospective study

Sequencing for MLST. (DOCX 21 kb

Memories are One-to-Many Mapping Alleviators in Talking Face Generation

Talking face generation aims at generating photo-realistic video portraits of a target person driven by input audio. Due to its nature of one-to-many mapping from the input audio to the output video (e.g., one speech content may have multiple feasible visual appearances), learning a deterministic mapping like previous works brings ambiguity during training, and thus causes inferior visual results. Although this one-to-many mapping could be alleviated in part by a two-stage framework (i.e., an audio-to-expression model followed by a neural-rendering model), it is still insufficient since the prediction is produced without enough information (e.g., emotions, wrinkles, etc.). In this paper, we propose MemFace to complement the missing information with an implicit memory and an explicit memory that follow the sense of the two stages respectively. More specifically, the implicit memory is employed in the audio-to-expression model to capture high-level semantics in the audio-expression shared space, while the explicit memory is employed in the neural-rendering model to help synthesize pixel-level details. Our experimental results show that our proposed MemFace surpasses all the state-of-the-art results across multiple scenarios consistently and significantly.Comment: Project page: see https://memoryface.github.i

Comparing Different Diagnostic Guidelines for Gestational Diabetes Mellitus in Relation to Birthweight in Sri Lankan Women

Introduction: While the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria is widely adopted in many countries, clinicians have questioned the applicability of these diagnostic thresholds for different races/ethnicities. We first compared the prevalence of gestational diabetes mellitus (GDM) diagnosed with different criteria including IADPSG, World Health Organization (WHO) 1999 and Sri Lankan national guidelines, and subsequently related individual guidelines-specific GDM prevalence to offspring birthweight in Sri Lanka.Materials and Methods: We retrospectively collected data on singleton pregnancies (n = 795) from two tertiary hospitals in Sri Lanka. We applied three diagnostic guidelines to define GDM, namely IADPSG criteria, the Sri Lankan national and WHO 1999 guidelines. We calculated the age- and first booking BMI-adjusted prevalence rates of GDM and assessed the association of GDM (using each guideline) with birthweight.Results: The age- and first booking BMI-adjusted GDM prevalence rates were 31.2, 28.0, and 13.1% for IADPSG criteria, Sri Lankan national and WHO 1999 guidelines, respectively. The IADPSG criteria identified 90 distinctive GDM cases at a lower cut-off of fasting glucose (from 5.1 to 5.5 mmol/L) while Sri Lankan national guideline identified 15 distinctive GDM cases at a lower cut-off for 2-h glucose (from 7.8 to 8.4 mmol/L). After adjusting for age, GDM diagnosed by IADPSG criteria was associated with higher birthweight [90.8 g, 95% CI: 10.8, 170.9], while the associations for GDM diagnosed either by Sri Lankan national or WHO 1999 guidelines were not significant.Conclusion: Adopting the IADPSG criteria for diagnosing GDM may be important in Sri Lankan pregnant population

Epidemiology and Control of Legionellosis, Singapore

To determine trends and clinical and epidemiologic features of legionellosis in Singapore, we studied cases reported during 2000–2009. During this period, 238 indigenous and 33 imported cases of legionellosis were reported. Cases were reported individually and sporadically throughout each year. Although the annual incidence of indigenous cases had decreased from 0.46 cases per 100,000 population in 2003 to 0.16 cases per 100,000 in 2009, the proportion of imported cases increased correspondingly from 6.2% during 2000–2004 to 27.3% during 2005–2009 (p<0.0005). The prevalence of Legionella bacteria in cooling towers and water fountains was stable (range 12.1%–15.3%) during 2004–August 2008