Automatic object segmentation using perceptual grouping of regions with contextual constraints

Image segmentation is still considered a very challenging subject despite years of research effort poured into the field. The problem is exacerbated when there is need for specific object detection. Since objects can be visually non-homogeneous, techniques that attempt to segment images into visually uniform regions using only the bottom-up cues, tend to fail. We propose a novel two-step model that incorporates both bottom-up information and top-down object constraints. Firstly, a set of uniform regions are generated using an extension of contour detection, seeded region growing, and graph-based methods. The second step applies co-occurrence constraints on the image regions in order to perceptually group regions into objects. This unsupervised segmentation process models each object using higher-level knowledge in the form of visual co-occurrences of its constituent parts. Experiments on the horse and ImageCLEF databases show that the proposed technique performs comparably well with existing state-of-the-art techniques

T Cell Migration from Inflamed Skin to Draining Lymph Nodes Requires Intralymphatic Crawling Supported by ICAM-1/LFA-1 Interactions.

T cells are the most abundant cell type found in afferent lymph, but their migration through lymphatic vessels (LVs) remains poorly understood. Performing intravital microscopy in the murine skin, we imaged T cell migration through afferent LVs in vivo. T cells entered into and actively migrated within lymphatic capillaries but were passively transported in contractile collecting vessels. Intralymphatic T cell number and motility were increased during contact-hypersensitivity-induced inflammation and dependent on ICAM-1/LFA-1 interactions. In vitro, blockade of endothelial cell-expressed ICAM-1 reduced T cell adhesion, crawling, and transmigration across lymphatic endothelium and decreased T cell advancement from capillaries into lymphatic collectors in skin explants. In vivo, T cell migration to draining lymph nodes was significantly reduced upon ICAM-1 or LFA-1 blockade. Our findings indicate that T cell migration through LVs occurs in distinct steps and reveal a key role for ICAM-1/LFA-1 interactions in this process

Lombardi Drawings of Graphs

We introduce the notion of Lombardi graph drawings, named after the American abstract artist Mark Lombardi. In these drawings, edges are represented as circular arcs rather than as line segments or polylines, and the vertices have perfect angular resolution: the edges are equally spaced around each vertex. We describe algorithms for finding Lombardi drawings of regular graphs, graphs of bounded degeneracy, and certain families of planar graphs.Comment: Expanded version of paper appearing in the 18th International Symposium on Graph Drawing (GD 2010). 13 pages, 7 figure

Infinite motion and 2-distinguishability of graphs and groups

A group A acting faithfully on a set X is 2-distinguishable if there is a 2-coloring of X that is not preserved by any nonidentity element of A, equivalently, if there is a proper subset of X with trivial setwise stabilizer. The motion of an element a in A is the number of points of X that are moved by a, and the motion of the group A is the minimal motion of its nonidentity elements. When A is finite, the Motion Lemma says that if the motion of A is large enough (specifically at least 2 log_2 |A|), then the action is 2-distinguishable. For many situations where X has a combinatorial or algebraic structure, the Motion Lemma implies that the action of Aut(X) on X is 2-distinguishable in all but finitely many instances. We prove an infinitary version of the Motion Lemma for countably infinite permutation groups, which states that infinite motion is large enough to guarantee 2-distinguishability. From this we deduce a number of results, including the fact that every locally finite, connected graph whose automorphism group is countably infinite is 2-distinguishable. One cannot extend the Motion Lemma to uncountable permutation groups, but nonetheless we prove that (under the permutation topology) every closed permutation group with infinite motion has a dense subgroup which is 2-distinguishable. We conjecture an extension of the Motion Lemma which we expect holds for a restricted class of uncountable permutation groups, and we conclude with a list of open questions. The consequences of our results are drawn for orbit equivalence of infinite permutation groups

In vivo imaging of extracellular matrix remodeling by tumor-associated fibroblasts.

Here we integrated multiphoton laser scanning microscopy and the registration of second harmonic generation images of collagen fibers to overcome difficulties in tracking stromal cell-matrix interactions for several days in live mice. We show that the matrix-modifying hormone relaxin increased tumor-associated fibroblast (TAF) interaction with collagen fibers by stimulating beta1-integrin activity, which is necessary for fiber remodeling by matrix metalloproteinases

Cell-surface sensors for real-time probing of cellular environments

Author Manuscript 2012 August 1.The ability to explore cell signalling and cell-to-cell communication is essential for understanding cell biology and developing effective therapeutics. However, it is not yet possible to monitor the interaction of cells with their environments in real time. Here, we show that a fluorescent sensor attached to a cell membrane can detect signalling molecules in the cellular environment. The sensor is an aptamer (a short length of single-stranded DNA) that binds to platelet-derived growth factor (PDGF) and contains a pair of fluorescent dyes. When bound to PDGF, the aptamer changes conformation and the dyes come closer to each other, producing a signal. The sensor, which is covalently attached to the membranes of mesenchymal stem cells, can quantitatively detect with high spatial and temporal resolution PDGF that is added in cell culture medium or secreted by neighbouring cells. The engineered stem cells retain their ability to find their way to the bone marrow and can be monitored in vivo at the single-cell level using intravital microscopy.National Institutes of Health (U.S.) (Grant HL097172)National Institutes of Health (U.S.) (Grant HL095722)National Institutes of Health (U.S.) (Grant DE019191)National Institutes of Health (U.S.) (Grant NIAID 5RC1AI086152)Charles A. Dana FoundationAmerican Heart Association (Grant 0970178N)National Science Foundation (U.S.) (Graduate Fellowship

Transcription factor FOXP2 is a flow-induced regulator of collecting lymphatic vessels.

The lymphatic system is composed of a hierarchical network of fluid absorbing lymphatic capillaries and transporting collecting vessels. Despite distinct functions and morphologies, molecular mechanisms that regulate the identity of the different vessel types are poorly understood. Through transcriptional analysis of murine dermal lymphatic endothelial cells (LECs), we identified Foxp2, a member of the FOXP family of transcription factors implicated in speech development, as a collecting vessel signature gene. FOXP2 expression was induced after initiation of lymph flow in vivo and upon shear stress on primary LECs in vitro. Loss of FOXC2, the major flow-responsive transcriptional regulator of lymphatic valve formation, abolished FOXP2 induction in vitro and in vivo. Genetic deletion of Foxp2 in mice using the endothelial-specific Tie2-Cre or the tamoxifen-inducible LEC-specific Prox1-CreER <sup>T2</sup> line resulted in enlarged collecting vessels and defective valves characterized by loss of NFATc1 activity. Our results identify FOXP2 as a new flow-induced transcriptional regulator of collecting lymphatic vessel morphogenesis and highlight the existence of unique transcription factor codes in the establishment of vessel-type-specific endothelial cell identities

The importance of multimodality in sarcasm detection for sentiment analysis

Sentiment analysis is the computational study of opinions given by the users of online media platforms e.g. Twitter, Facebook, Instagram. The output will be in the form of polarity: positive, negative or indifferent. The field has become very useful for the industry as it can feed them the information of what is sought after by their customers in a given time. It has also rapidly became a topic of interest in the research world, for its importance and subjectivity. One of the most challenging issue in sentiment analysis is sarcasm. The existence of sarcasm is mostly ignored by the researchers in the field of sentiment analysis as it is considered to be too complex. Sarcasm is what most researchers regarded as a subset of irony. It is the utterance of positive statement with negative intent. Intent is hard to detect not only for computers but also for humans. The listener is deemed to have a certain degree of background knowledge or context of what the speaker is saying to understand sarcasm. The researches that takes sarcasm into account or solely focuses on sarcasm is in the trend of using context outside the target word for sarcasm detection, and the most popular approach is deep learning. However, both deep learning and context need a lot of features. In this paper, we will look at some researches that focuses on sarcasm detection and their agreement that more than text is needed to properly detect sarcasm. Also in this paper is the trends undergone by sarcasm detection researchers and their proposed techniques