Towards open-universe image parsing with broad coverage

One of the main goals of computer vision is to develop algorithms that allow the computer to interpret an image not as a pattern of colors but as the semantic relationships that make up a real world three-dimensional scene. In this dissertation, I present a system for image parsing, or labeling the regions of an image with their semantic categories, as a means of scene understanding. Most existing image parsing systems use a fixed set of a few hundred hand-labeled images as examples from which they learn how to label image regions, but our world cannot be adequately described with only a few hundred images. A new breed of open universe datasets have recently started to emerge. These datasets not only have more images but are constantly expanding, with new images and labels assigned by users on the web. Here I present a system that is able to both learn from these larger datasets of labeled images and scale as the dataset expands, thus greatly broadening the number of class labels that can correctly be identified in an image. Throughout this work I employ a retrieval-based methodology: I first retrieve images similar to the query and then match image regions from this set of retrieved images. My system can assign to each image region multiple forms of meaning: for example, it can simultaneously label the wing of a crow as an animal, crow, wing, and feather. I also broaden the label coverage by using both region and detector based similarity measures to effectively match a broad range to label types. This work shows the power of retrieval-based systems and the importance of having a diverse set of image cues and interpretations.Doctor of Philosoph

Statistical mechanics for static granular media: open questions

International audienceThe theoretical description of granular materials, or assemblies of macroscopic particles, is a formidable task. Not only are granular materials out of thermal equilibrium, but they are also characterized by dissipative interactions and by static friction. Following a suggestion by S.~F. Edwards, researchers have investigated the possible existence of a statistical mechanics of static granular systems, which would permit the description of macroscopic properties of mechanically stable granular assemblies from just a few parameters. The formulation and the validity of such an approach is still a matter of debate. This ''emerging area'' focuses on three important questions concerning such a statistical mechanics approach. First, we consider how the phase space of interest is affected by the requirement of mechanical stability. Second, we explore how the intensive parameters analogous to temperature can be determined from experimental or numerical data. Finally, we contrast different ways to express the granular counterpart to the classical Hamiltonian, known as the volume function

Cigarette smoking differentially affects immunoglobulin class levels in serum and saliva: An investigation and review

The aim of the present study was to compare concentrations of IgG, IgA, IgM and IgD in both serum and saliva samples from smoking and non-smoking subjects using a protein microarray assay. The findings were also compared to previous studies. Serum and saliva were collected from 48 smoking male subjects and 48 age-matched neversmoker male subjects. The protein microarray assays for detection of human IgG, IgM, IgA and IgD were established and optimized using Ig class-specific affinity purified goat anti-human Ig-Fc capture antibodies and horseradish peroxidase (HRP)- conjugated goat anti-human Ig-Fc detection antibodies. The Ig class specificity of the microarray assays was verified and the optimal dilutions of serum and saliva samples was determined for quantification of Ig levels against standard curves. We found that smoking is associated with reduced IgG concentrations and enhanced IgA concentrations in both serum and saliva. By contrast, smoking differentially affected IgM concentrations – causing increased concentrations in serum, but decreased concentrations in saliva. Smoking was associated with decreased IgD concentrations in serum, and did not have a significant effect on the very low IgD concentrations in saliva. Thus, cigarette smoking differentially affects the levels of Ig classes systemically and in the oral mucosa. Although there is variation between the results of different published studies, there is a consensus that smokers have significantly reduced levels of IgG in both serum and saliva. A functional antibody deficiency associated with smoking may compromise the body’s response to infection and result in a predisposition to the development of autoimmunity

IgE autoantibodies and their association with the disease activity and phenotype in Bullous Pemphigoid: a systematic review

Bullous Pemphigoid (BP) is the most common autoimmune skin disease of blistering character. The underlying pathophysiological mechanism involves an immune attack, usually by IgG class autoantibodies, on the autoantigen BP 180/BPAg2, which is a type XVII collagen (COL17) protein acting as the adhesion molecule between the epidermis and the basement membrane of the dermis. About 40 years ago, following consistent findings of elevated total serum IgE levels in BP patients, it was hypothesized that IgE may be involved in the pathophysiology of BP. Our objective was to determine whether there is strong evidence for an association between IgE class autoantibodies and the clinical severity or phenotype of BP. Three databases were searched for relevant studies and appropriate exclusion and inclusion criteria were applied. Data was extracted and assessed in relation to the study questions concerning the clinical significance of IgE autoantibodies in BP. Nine studies found that anti-BP180 autoantibodies of IgE class are associated with increased severity of BP, whereas two studies did not find such an association. The number of studies which found an association between higher IgE autoantibody levels and the erythematous urticarial phenotype of BP (5) were equal in number to the studies which found no such association (5). In conclusion, higher serum IgE autoantibody levels are associated with more severe clinical manifestations of BP. There is insufficient evidence to support higher IgE autoantibody levels being associated with specific clinical phenotypes of BP

Joint Distribution and Transitions of Pain and Activity in Critically Ill Patients

Pain and physical function are both essential indices of recovery in critically ill patients in the Intensive Care Units (ICU). Simultaneous monitoring of pain intensity and patient activity can be important for determining which analgesic interventions can optimize mobility and function, while minimizing opioid harm. Nonetheless, so far, our knowledge of the relation between pain and activity has been limited to manual and sporadic activity assessments. In recent years, wearable devices equipped with 3-axis accelerometers have been used in many domains to provide a continuous and automated measure of mobility and physical activity. In this study, we collected activity intensity data from 57 ICU patients, using the Actigraph GT3X device. We also collected relevant clinical information, including nurse assessments of pain intensity, recorded every 1-4 hours. Our results show the joint distribution and state transition of joint activity and pain states in critically ill patients.Comment: Accepted for Publication in EMBC 202