Phage display selection of ligand residues important for Src homology 3 domain binding specificity.

The Src homology 3 (SH3) domain is a 50-aa modular unit present in many cellular proteins involved in intracellular signal transduction. It functions to direct protein-protein interactions through the recognition of proline-rich motifs on associated proteins. SH3 domains are important regulatory elements that have been demonstrated to specify distinct regulatory pathways important for cell growth, migration, differentiation, and responses to the external milieu. By the use of synthetic peptides, ligands have been shown to consist of a minimum core sequence and to bind to SH3 domains in one of two pseudosymmetrical orientations, class I and class II. The class I sites have the consensus sequence ZP(L/P)PP psi P whereas the class II consensus is PP psi PPZ (where psi is a hydrophobic residue and Z is a SH3 domain-specific residue). We previously showed by M13 phage display that the Src, Fyn, Lyn, and phosphatidylinositol 3-kinase (PI3K) SH3 domains preferred the same class I-type core binding sequence, RPLPP psi P. These results failed to explain the specificity for cellular proteins displayed by SH3 domains in cells. In the current study, class I and class II core ligand sequences were displayed on the surface of bacteriophage M13 with five random residues placed either N- or C-terminal of core ligand residues. These libraries were screened for binding to the Src, Fyn, Lyn, Yes, and PI3K SH3 domains. By this approach, additional ligand residue preferences were identified that can increase the affinity of SH3 peptide ligands at least 20-fold compared with core peptides. The amino acids selected in the flanking sequences were similar for Src, Fyn, and Yes SH3 domains; however, Lyn and PI3K SH3 domains showed distinct binding specificities. These results indicate that residues that flank the core binding sequences shared by many SH3 domains are important determinants of SH3 binding affinity and selectivity.

A protein-binding domain, EH, identified in the receptor tyrosine kinase substrate Eps15 and conserved in evolution.

In this report we structurally and functionally define a binding domain that is involved in protein association and that we have designated EH (for Eps15 homology domain). This domain was identified in the tyrosine kinase substrate Eps15 on the basis of regional conservation with several heterogeneous proteins of yeast and nematode. The EH domain spans about 70 amino acids and shows approximately 60% overall amino acid conservation. We demonstrated the ability of the EH domain to specifically bind cytosolic proteins in normal and malignant cells of mesenchymal, epithelial, and hematopoietic origin. These observations prompted our search for additional EH-containing proteins in mammalian cells. Using an EH domain-specific probe derived from the eps15 cDNA, we cloned and characterized a cDNA encoding an EH-containing protein with overall similarity to Eps15; we designated this protein Eps15r (for Eps15-related). Structural comparison of Eps15 and Eps15r defines a family of signal transducers possessing extensive networking abilities including EH-mediated binding and association with Src homology 3-containing proteins.

Evaluating knowledge-based approaches to the multilingual extension of a temporal expression normalizer

The extension to new languages is a well known bottleneck for rule-based systems. Considerable human effort, which typically consists in re-writing from scratch huge amounts of rules, is in fact required to transfer the knowledge available to the system from one language to a new one. Provided sufficient annotated data, machine learning algorithms allow to minimize the costs of such knowledge transfer but, up to date, proved to be ineffective for some specific tasks. Among these, the recognition and normalization of temporal expressions still remains out of their reach. Focusing on this task, and still adhering to the rule-based framework, this paper presents a bunch of experiments on the automatic porting to Italian of a system originally developed for Spanish. Different automatic rule translation strategies are evaluated and discussed, providing a comprehensive overview of the challenge.

Algoritmos metaheurísticos en el problema del particionado hardware/software de sistemas embebidos

El particionado hardware/software es una tarea fundamental en el co-diseño de sistemas embebidos. En ella se decide, teniendo en cuenta las métricas de diseño, qué componentes se ejecutarán en un procesador de propósito general (software) y cuáles en un hardware específico. En los últimos años se han propuesto diversas soluciones al problema del particionado dirigidas por algoritmos metaheurísticos. Sin embargo, debido a la diversidad de modelos y métricas utilizadas, la elección del algoritmo más apropiado sigue siendo un problema abierto. En este trabajo se presenta una comparación de seis algoritmos metaheurísticos: Búsqueda aleatoria (Random search), Búsqueda tabú (Tabu search), Recocido simulado (Simulated annealing), Escalador de colinas estocástico (Stochastic hill climbing), Algoritmo genético (Genetic algorithm) y Estrategia evolutiva (Evolution strategy). El modelo utilizado en la comparación está dirigido a minimizar el área ocupada y el tiempo de ejecución, las restricciones del modelo son consideradas como penalizaciones para incluir en el espacio de búsqueda otras soluciones. Los resultados muestran que los algoritmos Escalador de colinas estocástico y Estrategia evolutiva son los que mejores resultados obtienen en general, seguidos por el Algoritmo genético.

Partición hardware software de un codificador JPEG utilizando escalador de colinas estocástico

La partición hardware/software es una etapa clave dentro del proceso de co-diseño de los sistemas embebidos. En esta etapa se decide qué componentes serán implementados como co-procesadores de hardware y qué componentes serán implementados en un procesador de propósito general. La decisión es tomada a partir de la exploración del espacio de diseño, evaluando un conjunto de posibles soluciones para establecer cuál de estas es la que mejor balance logra entre todas las métricas de diseño. Para explorar el espacio de soluciones, la mayoría de las propuestas, utilizan algoritmos metaheurísticos; destacándose los Algoritmos Genéticos, Recocido Simulado. Esta decisión, en muchos casos, no es tomada a partir de análisis comparativos que involucren a varios algoritmos sobre un mismo problema. En este trabajo se presenta la aplicación de los algoritmos: Escalador de Colinas Estocástico y Escalador de Colinas Estocástico con Reinicio, para resolver el problema de la partición hardware/software. Para validar el empleo de estos algoritmos se presenta la aplicación de este algoritmo sobre un caso de estudio, en particular la partición hardware/software de un codificador JPEG. En todos los experimentos es posible apreciar que ambos algoritmos alcanzan soluciones comparables con las obtenidas por los algoritmos utilizados con más frecuencia.

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.

Flexible processing architecture for maintaining QoS in embedded systems applications

Comunicación presentada en las V Jornadas de Computación Empotrada, Valladolid, 17-19 Septiembre 2014

Aviation English: Structure and Importance of an International Airborne Language

In today’s globalized world, air travel is one of the fastest growing markets. Millions of aircrafts take off and then touch down all around the world each day. This well-synchronized symphony, however, is much more complex than it seems, and communication – language - plays a crucial role during a plane’s journey. Misunderstandings and miscommunications can have disastrous effects, so the adoption of a standard phraseology to be used during flight is a means to overcome language barriers, avoid ambiguous expressions and guarantee a safe and effective operation of an aircraft. Little is known about the interaction that goes on between pilots and air traffic controllers (ATCOs), and even though the language of aviation is English, cockpit communication can be hard to understand for people who are not familiar with this specific language. The scope of this thesis is to examine the origins of this uncommon language, the characteristics and peculiarities of air communication and to shed a little light on this mystery called Aviation English.

General language abilities following management of childhood supratentorial tumour: Part 1

Background. To date few studies have investigated the impact of management for supratentorial tumour on the language abilities of children. In reporting children with brain tumour as part of a larger cohort of various aetiologies of brain injury, such studies have failed to differentiate between the causes of acquired childhood language disorders, or specifically report associated information relating to site and treatment. Material and methods. The present study examined the general language abilities of six children managed for supratentorial tumour, using a comprehensive standardized general language assessment battery, including receptive and expressive components, receptive vocabulary, and naming. Results. At a group level, children managed for supratentorial tumour performed below an individually matched control group in the area of general expressive language. However, at an individual case level it was revealed that only two cases exhibited specific language deficits. Reduced performance in the area of expressive language and syntax was evident in the language profile of one child treated surgically for a left parietal astrocytoma, while a child treated surgically for an optic nerve glioma demonstrated difficulties in receptive semantic abilities. The remaining four cases with similar treatments and locations demonstrated intact general language abilities. Conclusions. Factors such as site, long-term presence of tumour prior to diagnosis, young age at diagnosis, and variations in time post treatment were considered to have contributed to the findings. The need for long-term monitoring of language abilities post treatment as well as larger group sizes and the investigation of higher-level abilities was highlighted

Beyond verbal fluency: Investigating the long-term effects of bilateral subthalamic (STN) deep brain stimulation (DBS) on language in two cases

Cognitive functioning has been described as largely impervious to chronic STN-DBS administered over 12-month periods. In relation to the domain of language, however, the effects of STN-DBS are yet to be thoroughly delineated. Verbal fluency tasks represent an almost exclusively applied index of linguistic proficiency relative to neuropsychological research within this population. Comprehensive investigations of the impact of STN-DBS on language function, however, have never been undertaken. The more precise elucidation of the role of the STN in the mediation of language processes, by way of assessments which probe language comprehension and production mechanisms, served as the primary focus of this research. Longitudinal analysis also afforded consideration of the way in which cognitive-linguistic circuits respond to STN-DBS over time. Bilateral STN-DBS primarily effected clinically reliable fluctuations (i.e., both improvements and declines) in performance in both subjects on tasks demanding cognitive-linguistic flexibility in the formulation and comprehension of complex language. Of particular note, both subjects demonstrated a cumulative increase in the proportion of reliable post-operative improvements achieved over time. The findings of this research lend support to models of subcortical participation in language which endorse a role for the STN, and suggest that bilateral STN-DBS may serve to enhance the proficiency of basal ganglia-thalamocortical linguistic circuits over time.

Fitness assessment of document model

Document classification is a supervised machine learning process, where predefined category labels are assigned to documents based on the hypothesis derived from training set of labelled documents. Documents cannot be directly interpreted by a computer system unless they have been modelled as a collection of computable features. Rogati and Yang [M. Rogati and Y. Yang, Resource selection for domain-specific cross-lingual IR, in SIGIR 2004: Proceedings of the 27th annual international conference on Research and Development in Information Retrieval, ACM Press, Sheffied: United Kingdom, pp. 154-161.] pointed out that the effectiveness of document classification system may vary in different domains. This implies that the quality of document model contributes to the effectiveness of document classification. Conventionally, model evaluation is accomplished by comparing the effectiveness scores of classifiers on model candidates. However, this kind of evaluation methods may encounter either under-fitting or over-fitting problems, because the effectiveness scores are restricted by the learning capacities of classifiers. We propose a model fitness evaluation method to determine whether a model is sufficient to distinguish positive and negative instances while still competent to provide satisfactory effectiveness with a small feature subset. Our experiments demonstrated how the fitness of models are assessed. The results of our work contribute to the researches of feature selection, dimensionality reduction and document classification.

Designing a Computer Vision System for Underwater Robotic Interventions

This thesis deals with the challenging problem of designing systems able to perceive objects in underwater environments. In the last few decades research activities in robotics have advanced the state of art regarding intervention capabilities of autonomous systems. State of art in fields such as localization and navigation, real time perception and cognition, safe action and manipulation capabilities, applied to ground environments (both indoor and outdoor) has now reached such a readiness level that it allows high level autonomous operations. On the opposite side, the underwater environment remains a very difficult one for autonomous robots. Water influences the mechanical and electrical design of systems, interferes with sensors by limiting their capabilities, heavily impacts on data transmissions, and generally requires systems with low power consumption in order to enable reasonable mission duration. Interest in underwater applications is driven by needs of exploring and intervening in environments in which human capabilities are very limited. Nowadays, most underwater field operations are carried out by manned or remotely operated vehicles, deployed for explorations and limited intervention missions. Manned vehicles, directly on-board controlled, expose human operators to risks related to the stay in field of the mission, within a hostile environment. Remotely Operated Vehicles (ROV) currently represent the most advanced technology for underwater intervention services available on the market. These vehicles can be remotely operated for long time but they need support from an oceanographic vessel with multiple teams of highly specialized pilots. Vehicles equipped with multiple state-of-art sensors and capable to autonomously plan missions have been deployed in the last ten years and exploited as observers for underwater fauna, seabed, ship wrecks, and so on. On the other hand, underwater operations like object recovery and equipment maintenance are still challenging tasks to be conducted without human supervision since they require object perception and localization with much higher accuracy and robustness, to a degree seldom available in Autonomous Underwater Vehicles (AUV). This thesis reports the study, from design to deployment and evaluation, of a general purpose and configurable platform dedicated to stereo-vision perception in underwater environments. Several aspects related to the peculiar environment characteristics have been taken into account during all stages of system design and evaluation: depth of operation and light conditions, together with water turbidity and external weather, heavily impact on perception capabilities. The vision platform proposed in this work is a modular system comprising off-the-shelf components for both the imaging sensors and the computational unit, linked by a high performance ethernet network bus. The adopted design philosophy aims at achieving high flexibility in terms of feasible perception applications, that should not be as limited as in case of a special-purpose and dedicated hardware. Flexibility is required by the variability of underwater environments, with water conditions ranging from clear to turbid, light backscattering varying with daylight and depth, strong color distortion, and other environmental factors. Furthermore, the proposed modular design ensures an easier maintenance and update of the system over time. Performance of the proposed system, in terms of perception capabilities, has been evaluated in several underwater contexts taking advantage of the opportunity offered by the MARIS national project. Design issues like energy power consumption, heat dissipation and network capabilities have been evaluated in different scenarios. Finally, real-world experiments, conducted in multiple and variable underwater contexts, including open sea waters, have led to the collection of several datasets that have been publicly released to the scientific community. The vision system has been integrated in a state of the art AUV equipped with a robotic arm and gripper, and has been exploited in the robot control loop to successfully perform underwater grasping operations.

Ontologies, taxonomies, thesauri:learning from texts

The use of ontologies as representations of knowledge is widespread but their construction, until recently, has been entirely manual. We argue in this paper for the use of text corpora and automated natural language processing methods for the construction of ontologies. We delineate the challenges and present criteria for the selection of appropriate methods. We distinguish three ma jor steps in ontology building: associating terms, constructing hierarchies and labelling relations. A number of methods are presented for these purposes but we conclude that the issue of data-sparsity still is a ma jor challenge. We argue for the use of resources external tot he domain specific corpus.

Independent component analysis for domain independent watermarking

A new principled domain independent watermarking framework is presented. The new approach is based on embedding the message in statistically independent sources of the covertext to mimimise covertext distortion, maximise the information embedding rate and improve the method's robustness against various attacks. Experiments comparing the performance of the new approach, on several standard attacks show the current proposed approach to be competitive with other state of the art domain-specific methods.

Investigation of dyslexia and SLI risk variants in reading- and language-impaired subjects

Dyslexia (or reading disability) and specific language impairment (or SLI) are common childhood disorders that show considerable co-morbidity and diagnostic overlaps and have been suggested to share some genetic aetiology. Recently, genetic risk variants have been identified for SLI and dyslexia enabling the direct evaluation of possible shared genetic influences between these disorders. In this study we investigate the role of variants in these genes (namely MRPL19/C20RF3, ROBO1, DCDC2, KIAA0319, DYX1C1, CNTNAP2, ATP2C2 and CMIP) in the aetiology of SLI and dyslexia. We perform case–control and quantitative association analyses using measures of oral and written language skills in samples of SLI and dyslexic families and cases. We replicate association between KIAA0319 and DCDC2 and dyslexia and provide evidence to support a role for KIAA0319 in oral language ability. In addition, we find association between reading-related measures and variants in CNTNAP2 and CMIP in the SLI families.