It's a bug's life

Although the mechanisms of anterior-posterior axis formation are well understood in Drosophila, both embryological and molecular studies suggest significant variation in the mechanisms generating this axis within the Insecta class as a whole.

Assignment of Rfp-Y to the chicken major histocompatibility complex/NOR microchromosome and evidence for high-frequency recombination associated with the nucleolar organizer region.

Rfp-Y is a second region in the genome of the chicken containing major histocompatibility complex (MHC) class I and II genes. Haplotypes of Rfp-Y assort independently from haplotypes of the B system, a region known to function as a MHC and to be located on chromosome 16 (a microchromosome) with the single nucleolar organizer region (NOR) in the chicken genome. Linkage mapping with reference populations failed to reveal the location of Rfp-Y, leaving Rfp-Y unlinked in a map containing >400 markers. A possible location of Rfp-Y became apparent in studies of chickens trisomic for chromosome 16 when it was noted that the intensity of restriction fragments associated with Rfp-Y increased with increasing copy number of chromosome 16. Further evidence that Rfp-Y might be located on chromosome 16 was obtained when individuals trisomic for chromosome 16 were found to transmit three Rfp-Y haplotypes. Finally, mapping of cosmid cluster III of the molecular map of chicken MHC genes (containing a MHC class II gene and two rRNA genes) to Rfp-Y validated the assignment of Rfp-Y to the MHC/NOR microchromosome. A genetic map can now be drawn for a portion of chicken chromosome 16 with Rfp-Y, encompassing two MHC class I and three MHC class II genes, separated from the B system by a region containing the NOR and exhibiting highly frequent recombination.

kappa-Opioid receptor in humans: cDNA and genomic cloning, chromosomal assignment, functional expression, pharmacology, and expression pattern in the central nervous system.

Using the mouse delta-opioid receptor cDNA as a probe, we have isolated genomic clones encoding the human mu- and kappa-opioid receptor genes. Their organization appears similar to that of the human delta receptor gene, with exon-intron boundaries located after putative transmembrane domains 1 and 4. The kappa gene was mapped at position q11-12 in human chromosome 8. A full-length cDNA encoding the human kappa-opioid receptor has been isolated. The cloned receptor expressed in COS cells presents a typical kappa 1 pharmacological profile and is negatively coupled to adenylate cyclase. The expression of kappa-opioid receptor mRNA in human brain, as estimated by reverse transcription-polymerase chain reaction, is consistent with the involvement of kappa-opioid receptors in pain perception, neuroendocrine physiology, affective behavior, and cognition. In situ hybridization studies performed on human fetal spinal cord demonstrate the presence of the transcript specifically in lamina II of the dorsal horn. Some divergences in structural, pharmacological, and anatomical properties are noted between the cloned human and rodent receptors.

Electrical investigation of p-type 4H-SiC heavily doped by ion implantation

In the last decades, an increasing interest in the research field of wide bandgap semiconductors was observed, mostly due to the progressive approaching of silicon-based devices to their theoretical limits. 4H-SiC is an example among these, and is a mature compound for applications. The main advantages offered 4H-SiC in comparison with silicon are an higher breakdown field, an higher thermal conductivity, a higher operating temperature, very high hardness and melting point, biocompatibility, but also low switching losses in high frequencies applications and lower on-resistances in unipolar devices. Then, 4H-SiC power devices offer great performance improvement; moreover, they can work in hostile environments where silicon power devices cannot function. Ion implantation technology is a key process in the fabrication of almost all kinds of SiC devices, owing to the advantage of a spatially selective doping. This work is dedicated to the electrical investigation of several differently-processed 4H-SiC ion- implanted samples, mainly through Hall effect and space charge spectroscopy experiments. It was also developed the automatic control (Labview) of several experiments. In the work, the effectiveness of high temperature post-implant thermal treatments (up to 2000°C) were studied and compared considering: (i) different methods, (ii) different temperatures and (iii) different duration of the annealing process. Preliminary p + /n and Schottky junctions were also investigated as simple test devices. 1) Heavy doping by ion implantation of single off-axis 4H-SiC layers The electrical investigation is one of the most important characterization of ion-implanted samples, which must be submitted to mandatory post-implant thermal treatment in order to both (i) recover the lattice after ion bombardment, and (ii) address the implanted impurities into lattice sites so that they can effectively act as dopants. Electrical investigation can give fundamental information on the efficiency of the electrical impurity activation. To understand the results of the research it should be noted that: (a) To realize good ohmic contacts it is necessary to obtain spatially defined highly doped regions, which must have conductivity as low as possible. (b) It has been shown that the electrical activation efficiency and the electrical conductivity increase with the annealing temperature increasing. (c) To maximize the layer conductivity, temperatures around 1700°C are generally used and implantation density high till to 10 21 cm -3 . In this work, an original approach, different from (c), is explored by the using very high annealing temperature, around 2000°C, on samples of Al + -implant concentration of the order of 10 20 cm -3 . Several Al + -implanted 4H-SiC samples, resulting of p-type conductivity, were investigated, with a nominal density varying in the range of about 1-5∙10 20 cm -3 and subjected to two different high temperature thermal treatments. One annealing method uses a radiofrequency heated furnace till to 1950°C (Conventional Annealing, CA), the other exploits a microwave field, providing a fast heating rate up to 2000°C (Micro-Wave Annealing, MWA). In this contest, mainly ion implanted p-type samples were investigated, both off-axis and on-axis <0001> semi-insulating 4H-SiC. Concerning p-type off-axis samples, a high electrical activation of implanted Al (50-70%) and a compensation ratio below 10% were estimated. In the work, the main sample processing parameters have been varied, as the implant temperature, CA annealing duration, and heating/cooling rates, and the best values assessed. MWA method leads to higher hole density and lower mobility than CA in equivalent ion implanted layers, resulting in lower resistivity, probably related to the 50°C higher annealing temperature. An optimal duration of the CA treatment was estimated in about 12-13 minutes. A RT resistivity on the lowest reported in literature for this kind of samples, has been obtained. 2) Low resistivity data: variable range hopping Notwithstanding the heavy p-type doping levels, the carrier density remained less than the critical one required for a semiconductor to metal transition. However, the high carrier densities obtained was enough to trigger a low temperature impurity band (IB) conduction. In the heaviest doped samples, such a conduction mechanism persists till to RT, without significantly prejudice the mobility values. This feature can have an interesting technological fall, because it guarantee a nearly temperature- independent carrier density, it being not affected by freeze-out effects. The usual transport mechanism occurring in the IB conduction is the nearest neighbor hopping: such a regime is effectively consistent with the resistivity temperature behavior of the lowest doped samples. In the heavier doped samples, however, a trend of the resistivity data compatible with a variable range hopping (VRH) conduction has been pointed out, here highlighted for the first time in p-type 4H-SiC. Even more: in the heaviest doped samples, and in particular, in those annealed by MWA, the temperature dependence of the resistivity data is consistent with a reduced dimensionality (2D) of the VRH conduction. In these samples, TEM investigation pointed out faulted dislocation loops in the basal plane, whose average spacing along the c-axis is comparable with the optimal length of the hops in the VRH transport. This result suggested the assignment of such a peculiar behavior to a kind of spatial confinement into a plane of the carrier hops. 3) Test device the p + -n junction In the last part of the work, the electrical properties of 4H-SiC diodes were also studied. In this case, a heavy Al + ion implantation was realized on n-type epilayers, according to the technological process applied for final devices. Good rectification properties was shown from these preliminary devices in their current-voltage characteristics. Admittance spectroscopy and deep level transient spectroscopy measurements showed the presence of electrically active defects other than the dopants ones, induced in the active region of the diodes by ion implantation. A critical comparison with the literature of these defects was performed. Preliminary to such an investigation, it was assessed the experimental set up for the admittance spectroscopy and current-voltage investigation and the automatic control of these measurements.

The assignment of credit through bills of exchange and transmission documents in Andalusi Law

The exchange traffic was a practice that suited the modus vivendi of caravanners and traders in the Islamic world. The inclusion of the Iberian.Peninsula into the most important commercial routes of Muslims – such as the silk route through the North Africa – provides a very solid reason to deepen in the study of the sources that have been preserved about the role that certain credit instruments, which represented an alternative to the coin, might have played in trade centres.

Automatic extraction of syntactic semantic patterns for multilingual resources

In this paper we present an automatic system for the extraction of syntactic semantic patterns applied to the development of multilingual processing tools. In order to achieve optimum methods for the automatic treatment of more than one language, we propose the use of syntactic semantic patterns. These patterns are formed by a verbal head and the main arguments, and they are aligned among languages. In this paper we present an automatic system for the extraction and alignment of syntactic semantic patterns from two manually annotated corpora, and evaluate the main linguistic problems that we must deal with in the alignment process.

Machine learning techniques for automatic opinion detection in non-traditional textual genres

This paper presents a preliminary study in which Machine Learning experiments applied to Opinion Mining in blogs have been carried out. We created and annotated a blog corpus in Spanish using EmotiBlog. We evaluated the utility of the features labelled firstly carrying out experiments with combinations of them and secondly using the feature selection techniques, we also deal with several problems, such as the noisy character of the input texts, the small size of the training set, the granularity of the annotation scheme and the language object of our study, Spanish, with less resource than English. We obtained promising results considering that it is a preliminary study.

Exploring automatic feature selection for transition-based dependency parsing

En este artículo se investigan técnicas automáticas para encontrar un modelo óptimo de características en el caso de un analizador de dependencias basado en transiciones. Mostramos un estudio comparativo entre algoritmos de búsqueda, sistemas de validación y reglas de decisión demostrando al mismo tiempo que usando nuestros métodos es posible conseguir modelos complejos que proporcionan mejores resultados que los modelos que siguen configuraciones por defecto.

Automatic prediction of emotions from text in Spanish for expressive speech synthesis in the chat domain

This paper describes a module for the prediction of emotions in text chats in Spanish, oriented to its use in specific-domain text-to-speech systems. A general overview of the system is given, and the results of some evaluations carried out with two corpora of real chat messages are described. These results seem to indicate that this system offers a performance similar to other systems described in the literature, for a more complex task than other systems (identification of emotions and emotional intensity in the chat domain).

A new approach for semi-automatic rock mass joints recognition from 3D point clouds

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

This paper addresses the problem of the automatic recognition and classification of temporal expressions and events in human language. Efficacy in these tasks is crucial if the broader task of temporal information processing is to be successfully performed. We analyze whether the application of semantic knowledge to these tasks improves the performance of current approaches. We therefore present and evaluate a data-driven approach as part of a system: TIPSem. Our approach uses lexical semantics and semantic roles as additional information to extend classical approaches which are principally based on morphosyntax. The results obtained for English show that semantic knowledge aids in temporal expression and event recognition, achieving an error reduction of 59% and 21%, while in classification the contribution is limited. From the analysis of the results it may be concluded that the application of semantic knowledge leads to more general models and aids in the recognition of temporal entities that are ambiguous at shallower language analysis levels. We also discovered that lexical semantics and semantic roles have complementary advantages, and that it is useful to combine them. Finally, we carried out the same analysis for Spanish. The results obtained show comparable advantages. This supports the hypothesis that applying the proposed semantic knowledge may be useful for different languages.

Towards automatic tweet generation: A comparative study from the text summarization perspective in the journalism genre

In recent years, Twitter has become one of the most important microblogging services of the Web 2.0. Among the possible uses it allows, it can be employed for communicating and broadcasting information in real time. The goal of this research is to analyze the task of automatic tweet generation from a text summarization perspective in the context of the journalism genre. To achieve this, different state-of-the-art summarizers are selected and employed for producing multi-lingual tweets in two languages (English and Spanish). A wide experimental framework is proposed, comprising the creation of a new corpus, the generation of the automatic tweets, and their assessment through a quantitative and a qualitative evaluation, where informativeness, indicativeness and interest are key criteria that should be ensured in the proposed context. From the results obtained, it was observed that although the original tweets were considered as model tweets with respect to their informativeness, they were not among the most interesting ones from a human viewpoint. Therefore, relying only on these tweets may not be the ideal way to communicate news through Twitter, especially if a more personalized and catchy way of reporting news wants to be performed. In contrast, we showed that recent text summarization techniques may be more appropriate, reflecting a balance between indicativeness and interest, even if their content was different from the tweets delivered by the news providers.

Experiences on using Arduino for laboratory experiments of Automatic Control and Robotics

The free hardware platforms have become very important in engineering education in recent years. Among these platforms, Arduino highlights, characterized by its versatility, popularity and low price. This paper describes the implementation of four laboratory experiments for Automatic Control and Robotics courses at the University of Alicante, which have been developed based on Arduino and other existing equipment. Results were evaluated taking into account the views of students, concluding that the proposed experiments have been attractive to them, and they have acquired the knowledge about hardware configuration and programming that was intended.

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.