Hydrochemical Atlas of the Arctic Ocean

Introduction: Chemical composition of water determines its physical properties and character of processes proceeding in it: freezing temperature, volume of evaporation, density, color, transparency, filtration capacity, etc. Presence of chemical elements in water solution confers waters special physical properties exerting significant influence on their circulation, creates necessary conditions for development and inhabitance of flora and fauna, and imparts to the ocean waters some chemical features that radically differ them from the land waters (Alekin & Liakhin, 1984). Hydrochemical information helps to determine elements of water circulation, convection depth, makes it easier to distinguish water masses and gives additional knowledge of climatic variability of ocean conditions. Hydrochemical information is a necessary part of biological research. Water chemical composition can be the governing characteristics determining possibility and limits of use of marine objects, both stationary and moving in sea water. Subject of investigation of hydrochemistry is study of dynamics of chemical composition, i.e. processes of its formation and hydrochemical conditions of water bodies (Alekin & Liakhin 1984). The hydrochemical processes in the Arctic Ocean are the least known. Some information on these processes can be obtained in odd publications. A generalizing study of hydrochemical conditions in the Arctic Ocean based on expeditions conducted in the years 1948-1975 has been carried out by Rusanov et al. (1979). The "Atlas of the World Ocean: the Arctic Ocean" contains a special section "Hydrochemistry" (Gorshkov, 1980). Typical vertical profiles, transects and maps for different depths - 0, 100, 300, 500, 1000, 2000, 3000 m are given in this section for the following parameters: dissolved oxygen, phosphate, silicate, pH and alkaline-chlorine coefficient. The maps were constructed using the data of expeditions conducted in the years 1948-1975. The illustrations reflect main features of distribution of the hydrochemical elements for multi-year period and represent a static image of hydrochemical conditions. Distribution of the hydrochemical elements on the ocean surface is given for two seasons - winter and summer, for the other depths are given mean annual fields. Aim of the present Atlas is description of hydrochemical conditions in the Arctic Ocean on the basis of a greater body of hydrochemical information for the years 1948-2000 and using the up-to-date methods of analysis and electronic forms of presentation of hydrochemical information. The most wide-spread characteristics determined in water samples were used as hydrochemical indices. They are: dissolved oxygen, phosphate, silicate, pH, total alkalinity, nitrite and nitrate. An important characteristics of water salt composition - "salinity" has been considered in the Oceanographic Atlas of the Arctic Ocean (1997, 1998). Presentation of the hydrochemical characteristics in this Hydrochemical Atlas is wider if compared with that of the former Atlas (Gorshkov, 1980). Maps of climatic distribution of the hydrochemical elements were constructed for all the standard depths, and seasonal variability of the hydrochemical parameters is given not only for the surface, but also for the underlying standard depths up to 400 m and including. Statistical characteristics of the hydrochemical elements are given for the first time. Detailed accuracy estimates of initial data and map construction are also given in the Atlas. Calculated values of mean-root deviations, maximum and minimum values of the parameters demonstrate limits of their variability for the analyzed period of observations. Therefore, not only investigations of chemical statics are summarized in the Atlas, but also some elements of chemical dynamics are demonstrated. Digital arrays of the hydrochemical elements obtained in nodes of a regular grid are the new form of characteristics presentation in the Atlas. It should be mentioned that the same grid and the same boxes were used in the Atlas, as those that had been used by creation of the US-Russian climatic Oceanographic Atlas. It allows to combine hydrochemical and oceanographic information of these Atlases. The first block of the digital arrays contains climatic characteristics calculated using direct observational data. These climatic characteristics were not calculated in the regions without observations, and the information arrays for these regions have gaps. The other block of climatic information in a gridded form was obtained with the help of objective analysis of observational data. Procedure of the objective analysis allowed us to obtain climatic estimates of the hydrochemical characteristics for the whole water area of the Arctic Ocean including the regions not covered by observations. Data of the objective analysis can be widely used, in particular, in hydrobiological investigations and in modeling of hydrochemical conditions of the Arctic Ocean. Array of initial measurements is a separate block. It includes all the available materials of hydrochemical observations in the form, as they were presented in different sources. While keeping in mind that this array contains some amount of perverted information, the authors of the Atlas assumed it necessary to store this information in its primary form. Methods of data quality control can be developed in future in the process of hydrochemical information accumulation. It can be supposed that attitude can vary in future to the data that were rejected according to the procedure accepted in the Atlas. The hydrochemical Atlas of the Arctic Ocean is the first specialized and electronic generalization of hydrochemical observations in the Arctic Ocean and finishes the program of joint efforts of Russian and US specialists in preparation of a number of atlases for the Arctic. The published Oceanographic Atlas (1997, 1998), Atlas of Arctic Meteorology and Climate (2000), Ice Atlas of the Arctic Ocean prepared for publication and Hydrochemical Atlas of the Arctic Ocean represent a united series of fundamental generalizations of empirical knowledge of Arctic Ocean nature at climatic level. The Hydrochemical Atlas of the Arctic Ocean was elaborated in the result of joint efforts of the SRC of the RF AARI and IARC. Dr. Ye. Nikiforov was scientific supervisor of the Atlas, Dr. R. Colony was manager on behalf of the USA and Dr. L. Timokhov - on behalf of Russia.

Timed mind maps using MINDMANAGER & MS-PROJECT for educational innovation

The adaptation to the European Higher Education Area (EHEA) is becoming a great challenge for the University Community, especially for its teaching and research staff, which is involved actively in the teaching-learning process. It is also inducing a paradigm change for lecturers and students. Among the methodologies used for processes of teaching innovation, system thinking plays an important role when working mainly with mind maps, and is focused to highlighting the essence of the knowledge, allowing its visual representation. In this paper, a method for using these mind maps for organizing a particular subject is explained. This organization is completed with the definition of duration, precedence relationships and resources for each of these activities, as well as with their corresponding monitoring. Mind maps are generated by means of the MINDMANAGER package whilst Ms-PROJECT is used for establishing tasks relationships, durations, resources, and monitoring. Summarizing, a procedure and the necessary set of applications for self organizing and managing (timed) scheduled teaching tasks has been described in this paper.

Towards a Transfer Model of Scientific and Technological Knowledge: the Case of Mexico

This paper shows the development of a science-technological knowledge transfer model in Mexico, as a means to boost the limited relations between the scientific and industrial environments. The proposal is based on the analysis of eight organizations (research centers and firms) with varying degrees of skill in the practice of science-technological knowledge transfer, and carried out by the case study approach. The analysis highlights the synergistic use of the organizational and technological capabilities of each organization, as a means to identification of the knowledge transfer mechanisms best suited to enabling the establishment of cooperative processes, and achieve the R&D and innovation activities results.

Timed mind maps using mindmanager & msproject for educational innovation

The adaptation to the European Higher Education Area (EHEA) is becoming a great challenge for the University Community, especially for its teaching and research staff, which is involved actively in the teaching-learning process. It is also inducing a paradigm change for lecturers and students. Among the methodologies used for processes of teaching innovation, system thinking plays an important role when working mainly with mind maps, and is focused to highlighting the essence of the knowledge, allowing its visual representation. In this paper, a method for using these mind maps for organizing a particular subject is explained. This organization is completed with the definition of duration, precedence relationships and resources for each of these activities, as well as with their corresponding monitoring. Mind maps are generated by means of the MINDMANAGER package whilst Ms-PROJECT is used for establishing tasks relationships, durations, resources, and monitoring. Summarizing, a procedure and the necessary set of applications for self organizing and managing (timed) scheduled teaching tasks has been described in this paper

Conceptual framework for the design, implementation and validation of psychomotor skills’ assessment systems in minimally invasive surgery

Las técnicas de cirugía de mínima invasión (CMI) se están consolidando hoy en día como alternativa a la cirugía tradicional, debido a sus numerosos beneficios para los pacientes. Este cambio de paradigma implica que los cirujanos deben aprender una serie de habilidades distintas de aquellas requeridas en cirugía abierta. El entrenamiento y evaluación de estas habilidades se ha convertido en una de las mayores preocupaciones en los programas de formación de cirujanos, debido en gran parte a la presión de una sociedad que exige cirujanos bien preparados y una reducción en el número de errores médicos. Por tanto, se está prestando especial atención a la definición de nuevos programas que permitan el entrenamiento y la evaluación de las habilidades psicomotoras en entornos seguros antes de que los nuevos cirujanos puedan operar sobre pacientes reales. Para tal fin, hospitales y centros de formación están gradualmente incorporando instalaciones de entrenamiento donde los residentes puedan practicar y aprender sin riesgos. Es cada vez más común que estos laboratorios dispongan de simuladores virtuales o simuladores físicos capaces de registrar los movimientos del instrumental de cada residente. Estos simuladores ofrecen una gran variedad de tareas de entrenamiento y evaluación, así como la posibilidad de obtener información objetiva de los ejercicios. Los diferentes estudios de validación llevados a cabo dan muestra de su utilidad; pese a todo, los niveles de evidencia presentados son en muchas ocasiones insuficientes. Lo que es más importante, no existe un consenso claro a la hora de definir qué métricas son más útiles para caracterizar la pericia quirúrgica. El objetivo de esta tesis doctoral es diseñar y validar un marco de trabajo conceptual para la definición y validación de entornos para la evaluación de habilidades en CMI, en base a un modelo en tres fases: pedagógica (tareas y métricas a emplear), tecnológica (tecnologías de adquisición de métricas) y analítica (interpretación de la competencia en base a las métricas). Para tal fin, se describe la implementación práctica de un entorno basado en (1) un sistema de seguimiento de instrumental fundamentado en el análisis del vídeo laparoscópico; y (2) la determinación de la pericia en base a métricas de movimiento del instrumental. Para la fase pedagógica se diseñó e implementó un conjunto de tareas para la evaluación de habilidades psicomotoras básicas, así como una serie de métricas de movimiento. La validación de construcción llevada a cabo sobre ellas mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. Adicionalmente, los resultados obtenidos en la validación de apariencia fueron en general positivos en todos los grupos considerados (noveles, residentes, expertos). Para la fase tecnológica, se introdujo el EVA Tracking System, una solución para el seguimiento del instrumental quirúrgico basado en el análisis del vídeo endoscópico. La precisión del sistema se evaluó a 16,33ppRMS para el seguimiento 2D de la herramienta en la imagen; y a 13mmRMS para el seguimiento espacial de la misma. La validación de construcción con una de las tareas de evaluación mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. La validación concurrente con el TrEndo® Tracking System por su parte presentó valores altos de correlación para 8 de las 9 métricas analizadas. Finalmente, para la fase analítica se comparó el comportamiento de tres clasificadores supervisados a la hora de determinar automáticamente la pericia quirúrgica en base a la información de movimiento del instrumental, basados en aproximaciones lineales (análisis lineal discriminante, LDA), no lineales (máquinas de soporte vectorial, SVM) y difusas (sistemas adaptativos de inferencia neurodifusa, ANFIS). Los resultados muestran que en media SVM presenta un comportamiento ligeramente superior: 78,2% frente a los 71% y 71,7% obtenidos por ANFIS y LDA respectivamente. Sin embargo las diferencias estadísticas medidas entre los tres no fueron demostradas significativas. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la definición de sistemas de evaluación de habilidades para cirugía de mínima invasión, a la utilidad del análisis de vídeo como fuente de información y a la importancia de la información de movimiento de instrumental a la hora de caracterizar la pericia quirúrgica. Basándose en estos cimientos, se han de abrir nuevos campos de investigación que contribuyan a la definición de programas de formación estructurados y objetivos, que puedan garantizar la acreditación de cirujanos sobradamente preparados y promocionen la seguridad del paciente en el quirófano. Abstract Minimally invasive surgery (MIS) techniques have become a standard in many surgical sub-specialties, due to their many benefits for patients. However, this shift in paradigm implies that surgeons must acquire a complete different set of skills than those normally attributed to open surgery. Training and assessment of these skills has become a major concern in surgical learning programmes, especially considering the social demand for better-prepared professionals and for the decrease of medical errors. Therefore, much effort is being put in the definition of structured MIS learning programmes, where practice with real patients in the operating room (OR) can be delayed until the resident can attest for a minimum level of psychomotor competence. To this end, skills’ laboratory settings are being introduced in hospitals and training centres where residents may practice and be assessed on their psychomotor skills. Technological advances in the field of tracking technologies and virtual reality (VR) have enabled the creation of new learning systems such as VR simulators or enhanced box trainers. These systems offer a wide range of tasks, as well as the capability of registering objective data on the trainees’ performance. Validation studies give proof of their usefulness; however, levels of evidence reported are in many cases low. More importantly, there is still no clear consensus on topics such as the optimal metrics that must be used to assess competence, the validity of VR simulation, the portability of tracking technologies into real surgeries (for advanced assessment) or the degree to which the skills measured and obtained in laboratory environments transfer to the OR. The purpose of this PhD is to design and validate a conceptual framework for the definition and validation of MIS assessment environments based on a three-pillared model defining three main stages: pedagogical (tasks and metrics to employ), technological (metric acquisition technologies) and analytical (interpretation of competence based on metrics). To this end, a practical implementation of the framework is presented, focused on (1) a video-based tracking system and (2) the determination of surgical competence based on the laparoscopic instruments’ motionrelated data. The pedagogical stage’s results led to the design and implementation of a set of basic tasks for MIS psychomotor skills’ assessment, as well as the definition of motion analysis parameters (MAPs) to measure performance on said tasks. Validation yielded good construct results for parameters such as time, path length, depth, average speed, average acceleration, economy of area and economy of volume. Additionally, face validation results showed positive acceptance on behalf of the experts, residents and novices. For the technological stage the EVA Tracking System is introduced. EVA provides a solution for tracking laparoscopic instruments from the analysis of the monoscopic video image. Accuracy tests for the system are presented, which yielded an average RMSE of 16.33pp for 2D tracking of the instrument on the image and of 13mm for 3D spatial tracking. A validation experiment was conducted using one of the tasks and the most relevant MAPs. Construct validation showed significant differences for time, path length, depth, average speed, average acceleration, economy of area and economy of volume; especially between novices and residents/experts. More importantly, concurrent validation with the TrEndo® Tracking System presented high correlation values (>0.7) for 8 of the 9 MAPs proposed. Finally, the analytical stage allowed comparing the performance of three different supervised classification strategies in the determination of surgical competence based on motion-related information. The three classifiers were based on linear (linear discriminant analysis, LDA), non-linear (support vector machines, SVM) and fuzzy (adaptive neuro fuzzy inference systems, ANFIS) approaches. Results for SVM show slightly better performance than the other two classifiers: on average, accuracy for LDA, SVM and ANFIS was of 71.7%, 78.2% and 71% respectively. However, when confronted, no statistical significance was found between any of the three. Overall, this PhD corroborates the investigated research hypotheses regarding the definition of MIS assessment systems, the use of endoscopic video analysis as the main source of information and the relevance of motion analysis in the determination of surgical competence. New research fields in the training and assessment of MIS surgeons can be proposed based on these foundations, in order to contribute to the definition of structured and objective learning programmes that guarantee the accreditation of well-prepared professionals and the promotion of patient safety in the OR.

Impact of N on the atomic-scale Sb distribution in quaternary GaAsSbN-capped InAs quantum dots

The use of GaAsSbN capping layers on InAs/GaAs quantum dots (QDs) has recently been proposed for micro- and optoelectronic applications for their ability to independently tailor electron and hole confinement potentials. However, there is a lack of knowledge about the structural and compositional changes associated with the process of simultaneous Sb and N incorporation. In the present work, we have characterized using transmission electron microscopy techniques the effects of adding N in the GaAsSb/InAs/GaAs QD system. Firstly, strain maps of the regions away from the InAs QDs had revealed a huge reduction of the strain fields with the N incorporation but a higher inhomogeneity, which points to a composition modulation enhancement with the presence of Sb-rich and Sb-poor regions in the range of a few nanometers. On the other hand, the average strain in the QDs and surroundings is also similar in both cases. It could be explained by the accumulation of Sb above the QDs, compensating the tensile strain induced by the N incorporation together with an In-Ga intermixing inhibition. Indeed, compositional maps of column resolution from aberration-corrected Z-contrast images confirmed that the addition of N enhances the preferential deposition of Sb above the InAs QD, giving rise to an undulation of the growth front. As an outcome, the strong redshift in the photoluminescence spectrum of the GaAsSbN sample cannot be attributed only to the N-related reduction of the conduction band offset but also to an enhancement of the effect of Sb on the QD band structure.

Enhancing the expressiveness of linguistic structures

In the information society large amounts of information are being generated and transmitted constantly, especially in the most natural way for humans, i.e., natural language. Social networks, blogs, forums, and Q&A sites are a dynamic Large Knowledge Repository. So, Web 2.0 contains structured data but still the largest amount of information is expressed in natural language. Linguistic structures for text recognition enable the extraction of structured information from texts. However, the expressiveness of the current structures is limited as they have been designed with a strict order in their phrases, limiting their applicability to other languages and making them more sensible to grammatical errors. To overcome these limitations, in this paper we present a linguistic structure named ?linguistic schema?, with a richer expressiveness that introduces less implicit constraints over annotations.

A visual framework to accelerate knowledge discovery based on dimensionality reduction minimizing degradation of quality

Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

Towards Mapping Experience Design for the Internet of Things.

We are witnessing a fundamental transformation in how Internet of Things (IoT) is having an impact on the experience users have with data-driven devices, smart appliances, and connected products. The experience of any place is commonly defined as the result of a series of user engagements with a surrounding place in order to carry out daily activities (Golledge, 2002). Knowing about users? experiences becomes vital to the process of designing a map. In the near future, a user will be able to interact directly with any IoT device placed in his surrounding place and very little is known on what kinds of interactions and experiences a map might offer (Roth, 2015). The main challenge is to develop an experience design process to devise maps capable of supporting different user experience dimensions such as cognitive, sensory-physical, affective, and social (Tussyadiah and Zach, 2012). For example, in a smart city of the future, the IoT devices allowing a multimodal interaction with a map could help tourists in the assimilation of their knowledge about points of interest (cognitive experience), their association of sounds and smells to these places (sensory-physical experience), their emotional connection to them (affective experience) and their relationships with other nearby tourists (social experience). This paper aims to describe a conceptual framework for developing a Mapping Experience Design (MXD) process for building maps for smart connected places of the future. Our MXD process is focussed on the cognitive dimension of an experience in which a person perceives a place as a "living entity" that uses and feeds through his experiences. We want to help people to undergo a meaningful experience of a place through mapping what is being communicated during their interactions with the IoT devices situated in this place. Our purpose is to understand how maps can support a person?s experience in making better decisions in real-time.

Residual delay maps unveil global patterns of atmospheric nonlinearity and produce improved local forecasts

We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems.

Coexistence of linear zones and pinwheels within orientation maps in cat visual cortex

Revealing the layout of cortical maps is important both for understanding the processes involved in their development and for uncovering the mechanisms underlying neural computation. The typical organization of orientation maps in the cat visual cortex is radial; complete orientation cycles are mapped around orientation singularities. In contrast, long linear zones of orientation representation have been detected in the primary visual cortex of the tree shrew. In this study, we searched for the existence of long linear sequences and wide linear zones within orientation preference maps of the cat visual cortex. Optical imaging based on intrinsic signals was used. Long linear sequences and wide linear zones of preferred orientation were occasionally detected along the border between areas 17 and 18, as well as within area 18. Adjacent zones of distinct radial and linear organizations were observed across area 18 of a single hemisphere. However, radial and linear organizations were not necessarily segregated; long (7.5 mm) linear sequences of preferred orientation were found embedded within a typical pinwheel-like organization of orientation. We conclude that, although the radial organization is dominant, perfectly linear organization may develop and perform the processing related to orientation in the cat visual cortex.

Identifying the role of natural resources in knowledge-based strategies of development

Knowledge has adopted a preferential role in the explanation of development while the evidence about the effect of natural resources in countries’ performance is more controversial in the economic literature. This paper tries to demonstrate that natural resources may positively affect growth in countries with a strong natural resources specialization pattern although the magnitude of these effects depend on the type of resources and on other aspects related to the production and innovation systems. The positive trajectory described by a set of national economies mainly specialized in natural resources and low-tech industries invites us to analyze what is the combination of factors that serves as engine for a sustainable development process. With panel data for the period 1996-2008 we estimate an applied growth model where both traditional factors and other more related to innovation and absorptive capabilities are taken into account. Our empirical findings show that according to the postulates of a knowledge-based approach, a framework that combines physical and intangible factors is more suitable for the definition of development strategies in those prosperous economies dominated by natural resources and connected activities, while the internationalization process of activities and technologies become also a very relevant aspect.

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.

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.