Labeling theory | EPFL Graph Search

Labeling theory posits that self-identity and the behavior of individuals may be determined or influenced by the terms used to describe or classify them. It is associated with the concepts of self-fulfilling prophecy and stereotyping. Labeling theory holds that deviance is not inherent in an act, but instead focuses on the tendency of majorities to negatively label minorities or those seen as deviant from standard cultural norms. The theory was prominent during the 1960s and 1970s, and some modified versions of the theory have developed and are still currently popular. Stigma is defined as a powerfully negative label that changes a person's self-concept and social identity. Labeling theory is closely related to social-construction and symbolic-interaction analysis. Labeling theory was developed by sociologists during the 1960s. Howard Saul Becker's book Outsiders was extremely influential in the development of this theory and its rise to popularity. Labeling theory is also connected to other fields besides crime. For instance there is the labeling theory that corresponds to homosexuality. Alfred Kinsey and his colleagues were the main advocates in separating the difference between the role of a "homosexual" and the acts one does. An example is the idea that males performing feminine acts would imply that they are homosexual. Thomas J. Scheff states that labeling also plays a part with the "mentally ill". The label does not refer to criminal but rather acts that are not socially accepted due to mental disorders. One of the founders of social interactionism, George Herbert Mead, focused on the internal processes of how the mind constructs one's self-image. In Mind, Self, and Society (1934), he showed how infants come to know persons first and only later come to know things. According to Mead, thought is both a social and pragmatic process, based on the model of two persons discussing how to solve a problem. Mead's central concept is the self, the part of an individual's personality composed of self-awareness and self-image.

Simultaneous segmentation and anatomical labeling of the cerebral vasculature

Pascal Fua, David Robben

We present a novel algorithm for the simultaneous segmentation and anatomical labeling of the cerebral vasculature. Unlike existing approaches that first attempt to obtain a good segmentation and then perform labeling, we optimize for both by simultaneously taking into account the image evidence and the prior knowledge about the geometry and connectivity of the vasculature. This is achieved by first constructing an overcomplete graph capturing the vasculature, and then selecting and labeling the subset of edges that most likely represents the true vasculature. We formulate the latter problem as an Integer Program (IP), which can be solved efficiently to provable optimality. We evaluate our approach on a publicly available dataset of 50 cerebral MRA images, and demonstrate that it compares favorably against state-of-the-art methods. (C) 2016 Elsevier B.V. All rights reserved.

Elsevier2016

Study of Cell Adhesion and Tracking Methods for in Vivo Cell Localisation in a Tissue-Engineering Scaffold

Tanja Cloé Hausherr, Thaïs Cléa Laura Séverine Clouet

Bone fracture healing problems, because of the loss of tissue regeneration, can affect many old or multi-pathologic patients around the world. Among the therapeutic strategies, bone substitutes, such as poly-(L-lactitve acid) with 5% wt. % ß-tricalcium phosphate (PLA/5%ß-TCP) scaffolds, are promising as a clinical solution. One strategy to tune their osteoinductive properties is the addition of bone progenitor cells. Therefore, cell- free and cell-seeded PLA/5% ß-TCP scaffolds were implanted into femoral condyles of rats to promote bone regeneration. The in vivo study showed that the bone growth inside a cell-seeded scaffold with human bone progenitor cells was delayed compared to cell-free scaffold. What happened to the cells? Did they trigger an immune response, migrate or die? Therefore, the goals of this project are to evaluate the cell adhesion in vitro to the scaffold and to propose a reliable cell labeling method to track them in future in vivo studies. In the first aim, the adhesion of the cells was qualitatively assessed by the cell morphology and the presence of fibronectin using fluorescence imaging. To quantify their adherence, seeded scaffolds were washed up to 3 times with a 0.9 % NaCl solution. The luminescence of the scaffolds and the washing solutions was measured using a cell viability assay. These experiments demonstrated that after 72h of culture, the measured adherent bone progenitor cells on the scaffolds decreased after 3 washes down to 50 % while it stayed stable after 14 days of culture. In the second aim, we focused on methods to label the cells either once implanted or prior to implantation. The first method was to translate the in situ hybridization protocol with the human specific Alu sequence from paraffin embedded samples to resin embedded ones. The obtained results were so far inconclusive. Concerning the labeling of the cells before implantation, the transmembrane label PKH26 was investigated. Its staining efficacy was high just after labeling, while it decreased drastically over time due to cell division.

2015

Constraint consistency techniques for continuous domains

Jamila Sam

Constraint Satisfaction Problems (CSPs) are ubiquitous in computer science. Many problems, ranging from resource allocation and scheduling to fault diagnosis and design, involve constraint satisfaction as an essential component. A CSP is given by a set of variables and constraints on small subsets of these variables. It is solved by finding assignments of values to the variables such that all constraints are satisfied. In its most general form, a CSP is combinatorial and complex. In this thesis, we consider constraint satisfaction problems with variables in continuous, numerical domains. Contrary to most existing techniques, which focus on computing a single optimal solution, we address the problem of computing a compact representation of the space of all solutions that satisfy the constraints. This has the advantage that no optimization criterion has to be formulated beforehand, and that the space of possibilities can be explored systematically. In certain applications, such as diagnosis and design, these advantages are crucial. In consistency techniques, the solution space is represented by labels assigned to individual variables or combinations of variables. When the labeling is globally consistent, each label contains only those values or combinations of values which appear in at least one solution. This kind of labeling is a compact, sound and complete representation of the solution space, and can be combined with other reasoning methods. In practice, computing a globally consistent labeling is too complex. This is usually tackled in two ways. One way is to enforce consistencies locally, using propagation algorithms. This prunes the search space and hence reduces the subsequent search effort. The other way is to identify simplifying properties which guarantee that global consistency can be enforced tractably using local propagation algorithms. When constraints are represented by mathematical expressions, implementing local consistency algorithms is difficult because it requires tools for solving arbitrary systems of equations. In this thesis, we propose to approximate feasible solution regions by 2k-trees, thus providing a means of combining constraints logically rather than numerically. This representation, commonly used in computer vision and image processing, avoids using complex mathematical tools. We propose simple and stable algorithms for computing labels of arbitrary degrees of consistency using this representation. For binary constraints, it is known that simplifying convexity properties reduces the complexity of solving a CSP. These properties guarantee that local degrees of consistency are sufficient to ensure global consistency. We show how, in continuous domains, these results can be generalized to ternary and in fact arbitrary n-ary constraints. This leads to polynomial-time algorithms for computing globally consistent labels for a large class of constraint satisfaction problems with continuous variables. We describe and justify our representation of constraints and our consistency algorithms. We also give a complete analysis of the theoretical results we present. Finally, the developed techniques are illustrated using practical examples.

EPFL1995