Drosophila 5-HT2 serotonin receptor: coexpression with fushi-tarazu during segmentation.

Serotonin, first described as a neurotransmitter in invertebrates, has been investigated mostly for its functions in the mature central nervous system of higher vertebrates. Serotonin receptor diversity has been described in the mammalian brain and in insects. We report the isolation of a cDNA coding for a Drosophila melanogaster serotonin receptor that displays a sequence, a gene organization, and pharmacological properties typical of the mammalian 5-HT2 serotonin receptor subtype. Its mRNA can be detected in the adult fly; moreover, a high level of expression occurs at 3 hr of Drosophila embryogenesis. This early embryonic expression is surprisingly organized in a seven-stripe pattern that appears at the cellular blastoderm stage. In addition, this pattern is in phase with that of the even-parasegment-expressed pair-rule gene fushi-tarazu and is similarly modified by mutations affecting segmentation genes. Simultaneously with this pair-rule expression, the complete machinery of serotonin synthesis is present and leads to a peak of ligand concomitant with a peak of 5-HT2-specific receptor sites in blastoderm embryos.

The Role of Passage Topic Knowledge in Typical and Poor Comprehenders' Recall

This dissertation examines the role of topic knowledge (TK) in comprehension among typical readers and those with Specifically Poor Comprehension (SPC), i.e., those who demonstrate deficits in understanding what they read despite adequate decoding. Previous studies of poor comprehension have focused on weaknesses in specific skills, such as word decoding and inferencing ability, but this dissertation examined a different factor: whether deficits in availability and use of TK underlie poor comprehension. It is well known that TK tends to facilitate comprehension among typical readers, but its interaction with working memory and word decoding is unclear, particularly among participants with deficits in these skills. Across several passages, we found that SPCs do in fact have less TK to assist their interpretation of a text. However, we found no evidence that deficits in working memory or word decoding ability make it difficult for children to benefit from their TK when they have it. Instead, children across the skill spectrum are able to draw upon TK to assist their interpretation of a passage. Because TK is difficult to assess and studies vary in methodology, another goal of this dissertation was to compare two methods for measuring it. Both approaches score responses to a concept question to assess TK, but in the first, a human rater assigns a score whereas in the second, a computer algorithm, Latent Semantic Analysis (LSA; Landauer & Dumais, 1997) assigns a score. We found similar results across both methods of assessing TK, suggesting that a continuous measure is not appreciably more sensitive to variations in knowledge than discrete human ratings. This study contributes to our understanding of how best to measure TK, the factors that moderate its relationship with recall, and its role in poor comprehension. The findings suggest that teaching practices that focus on expanding TK are likely to improve comprehension across readers with a variety of abilities.

A new marketing segmentation approach based on marginal individual utilities: applying CRM is not a chimera anymore

In the advent of Customer Relationship Management, a more accurate profile of the consumer is needed. The objective of this paper is to show the usefulness of knowing consumer’s complete utility function through his/her marginal utilities. This approach allows one to form groups of individuals with similar preferences (as traditional segmentation methods do) and to treat them individually (which represents an advance). The empirical application is carried out, on a sample of 2,127 individuals, in the context of tourism, where the customer relationship management philosophy is gaining more and more relevance.

New framework for score segmentation and analysis in OpenMusic

We present new tools for the segmentation and analysis of musical scores in the OpenMusic computer-aided composition environment. A modular object-oriented framework enables the creation of segmentations on score objects and the implementation of automatic or semi-automatic analysis processes. The analyses can be performed and displayed thanks to customizable classes and callbacks. Concrete examples are given, in particular with the implementation of a semi-automatic harmonic analysis system and a framework for rhythmic transcription.

Automatic Abdominal Aortic Aneurysm segmentation in MR images

Abdominal Aortic Aneurism is a disease related to a weakening in the aortic wall that can cause a break in the aorta and the death. The detection of an unusual dilatation of a section of the aorta is an indicative of this disease. However, it is difficult to diagnose because it is necessary image diagnosis using computed tomography or magnetic resonance. An automatic diagnosis system would allow to analyze abdominal magnetic resonance images and to warn doctors if any anomaly is detected. We focus our research in magnetic resonance images because of the absence of ionizing radiation. Although there are proposals to identify this disease in magnetic resonance images, they need an intervention from clinicians to be precise and some of them are computationally hard. In this paper we develop a novel approach to analyze magnetic resonance abdominal images and detect the lumen and the aortic wall. The method combines different algorithms in two stages to improve the detection and the segmentation so it can be applied to similar problems with other type of images or structures. In a first stage, we use a spatial fuzzy C-means algorithm with morphological image analysis to detect and segment the lumen; and subsequently, in a second stage, we apply a graph cut algorithm to segment the aortic wall. The obtained results in the analyzed images are pretty successful obtaining an average of 79% of overlapping between the automatic segmentation provided by our method and the aortic wall identified by a medical specialist. The main impact of the proposed method is that it works in a completely automatic way with a low computational cost, which is of great significance for any expert and intelligent system.

A tale of oversimplification and deregulation: the mainstream approach to labour market segmentation and the recent responses to the crisis in European countries. WP C.S.D.L.E. “Massimo D’Antona”.INT – 102/2013

After advocating flexibilization of non-standard work contracts for many years, some European and international institutions and several policy makers now indicate the standard employment relationship and its regulation as a cause of segmentation between the labour market of "guaranteed" insiders, employed under permanent contracts with effective protection against unfair dismissal, and the market of the “not-guaranteed” outsiders, working with non-standard contracts. Reforms of employment legislation are therefore being promoted and approved in different countries, allegedly aiming to balance the legal protection afforded to standard and non-standard workers. This article firstly argues that this approach is flawed as it oversimplifies reasons of segmentation as it concentrates on an “insiders-outsiders” discourse that cannot easily be transplanted in continental Europe. After reviewing current legislative changes in Italy, Spain and Portugal, it is then argued that lawmakers are focused on “deregulation” rather than “balancing protection” when approving recent reforms. Finally, the mainstream approach to segmentation and some of its derivative proposals, such as calls to introduce a “single permanent contract”, are called into question, as they seem to neglect the essential role of job protection in underpinning the effectiveness of fundamental and constitutional rights at the workplace.

FISICO: Fast Image SegmentatIon COrrection.

BACKGROUND AND PURPOSE In clinical diagnosis, medical image segmentation plays a key role in the analysis of pathological regions. Despite advances in automatic and semi-automatic segmentation techniques, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a lower number of interactions, and a user-independent solution to reduce the time frame between image acquisition and diagnosis. METHODS We present a new interactive method for correcting image segmentations. Our method provides 3D shape corrections through 2D interactions. This approach enables an intuitive and natural corrections of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle and knee joint segmentations from MR images. RESULTS Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively.