The acquisition of skilled motor performance: Fast and slow experience-driven changes in primary motor cortex

Behavioral and neurophysiological studies suggest that skill learning can be mediated by discrete, experience-driven changes within specific neural representations subserving the performance of the trained task. We have shown that a few minutes of daily practice on a sequential finger opposition task induced large, incremental performance gains over a few weeks of training. These gains did not generalize to the contralateral hand nor to a matched sequence of identical component movements, suggesting that a lateralized representation of the learned sequence of movements evolved through practice. This interpretation was supported by functional MRI data showing that a more extensive representation of the trained sequence emerged in primary motor cortex after 3 weeks of training. The imaging data, however, also indicated important changes occurring in primary motor cortex during the initial scanning sessions, which we proposed may reflect the setting up of a task-specific motor processing routine. Here we provide behavioral and functional MRI data on experience-dependent changes induced by a limited amount of repetitions within the first imaging session. We show that this limited training experience can be sufficient to trigger performance gains that require time to become evident. We propose that skilled motor performance is acquired in several stages: “fast” learning, an initial, within-session improvement phase, followed by a period of consolidation of several hours duration, and then “slow” learning, consisting of delayed, incremental gains in performance emerging after continued practice. This time course may reflect basic mechanisms of neuronal plasticity in the adult brain that subserve the acquisition and retention of many different skills.

Binding of the cellulose-binding domain of exoglucanase Cex from Cellulomonas fimi to insoluble microcrystalline cellulose is entropically driven.

Isothermal titration microcalorimetry is combined with solution-depletion isotherm data to analyze the thermodynamics of binding of the cellulose-binding domain (CBD) from the beta-1,4-(exo)glucanase Cex of Cellulomonas fimi to insoluble bacterial microcrystalline cellulose. Analysis of isothermal titration microcalorimetry data against two putative binding models indicates that the bacterial microcrystalline cellulose surface presents two independent classes of binding sites, with the predominant high-affinity site being characterized by a Langmuir-type Ka of 6.3 (+/-1.4) x 10(7) M-1 and the low-affinity site by a Ka of 1.1 (+/-0.6) x 10(6) M-1. CBDCex binding to either site is exothermic, but is mainly driven by a large positive change in entropy. This differs from protein binding to soluble carbohydrates, which is usually driven by a relatively large exothermic standard enthalpy change for binding. Differential heat capacity changes are large and negative, indicating that sorbent and protein dehydration effects make a dominant contribution to the driving force for binding.

Temperature chaos in 3D Ising spin glasses is driven by rare events

Temperature chaos has often been reported in the literature as a rare-event–driven phenomenon. However, this fact has always been ignored in the data analysis, thus erasing the signal of the chaotic behavior (still rare in the sizes achieved) and leading to an overall picture of a weak and gradual phenomenon. On the contrary, our analysis relies on a largedeviations functional that allows to discuss the size dependences. In addition, we had at our disposal unprecedentedly large configurations equilibrated at low temperatures, thanks to the Janus computer. According to our results, when temperature chaos occurs its effects are strong and can be felt even at short distances.

A model driven framework for geographic knowledge discovery

Geographic knowledge discovery (GKD) is the process of extracting information and knowledge from massive georeferenced databases. Usually the process is accomplished by two different systems, the Geographic Information Systems (GIS) and the data mining engines. However, the development of those systems is a complex task due to it does not follow a systematic, integrated and standard methodology. To overcome these pitfalls, in this paper, we propose a modeling framework that addresses the development of the different parts of a multilayer GKD process. The main advantages of our framework are that: (i) it reduces the design effort, (ii) it improves quality systems obtained, (iii) it is independent of platforms, (iv) it facilitates the use of data mining techniques on geo-referenced data, and finally, (v) it ameliorates the communication between different users.

Applying model-driven engineering to the development of Rich Internet Applications for Business Intelligence

Business Intelligence (BI) applications have been gradually ported to the Web in search of a global platform for the consumption and publication of data and services. On the Internet, apart from techniques for data/knowledge management, BI Web applications need interfaces with a high level of interoperability (similar to the traditional desktop interfaces) for the visualisation of data/knowledge. In some cases, this has been provided by Rich Internet Applications (RIA). The development of these BI RIAs is a process traditionally performed manually and, given the complexity of the final application, it is a process which might be prone to errors. The application of model-driven engineering techniques can reduce the cost of development and maintenance (in terms of time and resources) of these applications, as they demonstrated by other types of Web applications. In the light of these issues, the paper introduces the Sm4RIA-B methodology, i.e., a model-driven methodology for the development of RIA as BI Web applications. In order to overcome the limitations of RIA regarding knowledge management from the Web, this paper also presents a new RIA platform for BI, called RI@BI, which extends the functionalities of traditional RIAs by means of Semantic Web technologies and B2B techniques. Finally, we evaluate the whole approach on a case study—the development of a social network site for an enterprise project manager.

A Hardware-Software Approach for On-Line Soft Error Mitigation in Interrupt-Driven Applications

Integrity assurance of configuration data has a significant impact on microcontroller-based systems reliability. This is especially true when running applications driven by events which behavior is tightly coupled to this kind of data. This work proposes a new hybrid technique that combines hardware and software resources for detecting and recovering soft-errors in system configuration data. Our approach is based on the utilization of a common built-in microcontroller resource (timer) that works jointly with a software-based technique, which is responsible to periodically refresh the configuration data. The experiments demonstrate that non-destructive single event effects can be effectively mitigated with reduced overheads. Results show an important increase in fault coverage for SEUs and SETs, about one order of magnitude.

Bulk geochemical and lipid biomarker data for sediment core W8402A-14

Eleven sediment samples taken downcore and representing the past 26 kyr of deposition at MANOP site C (0°57.2°N, 138°57.3°W) were analyzed for lipid biomarker composition. Biomarkers of both terrestrial and marine sources of organic carbon were identified. In general, concentration profiles for these biomarkers and for total organic carbon (TOC) displayed three common stratigraphic features in the time series: (1) a maximum within the surface sediment mixed layer (<=4 ka); (2) a broad minimum extending throughout the interglacial deposit; and (3) a deep, pronounced maximum within the glacial deposit. Using the biomarker records, a simple binary mixing model is described that assesses the proportion of terrestrial to marine TOC in these sediments. Best estimates from this model suggest that ~20% of the TOC is land-derived, introduced by long-range eolian transport, and the remainder is derived from marine productivity. The direct correlation between the records for terrestrial and marine TOC with depth in this core fits an interpretation that primary productivity at site C has been controlled by wind-driven upwelling at least over the last glacial/interglacial cycle. The biomarker records place the greatest wind strength and highest primary productivity within the time frame of 18 to 22 kyr B.P. Diagenetic effects limit our ability to ascertain directly from the biomarker records the absolute magnitude that different types of primary productivity have changed at this ocean location over the past 26 kyr.

Establishing fluxes of carbon dioxide and a transect of pCO2 during the late fall of precipitation driven Northern fjord

Senior thesis written for Oceanography 445

Cobalt complexes of tripodal hexadentate ligands: Electrochemically driven rearrangements

The Co-III complexes of the hexadentate tripodal ligands HOsen (3-(2'-aminoethylamino)-2,2-bis((2 ''-aminoethylamino) methyl) propan-1-ol) and HOten (3-(2'-aminoethylthia)-2,2-bis((2 ''-aminoethylthia) methyl) propan-1-ol) have been synthesized and fully characterized. The crystal structures of [Co(HOsen)]Cl-3 center dot H2O and [Co(HOten)](ClO4)Cl-2 are reported and in both cases the ligands coordinate as tripodal hexadentate N-6 and N3S3 donors, respectively. Cyclic voltammetry of the N3S3 coordinated complex [Co(HOten)](3+) is complicated and electrode dependent. On a Pt working electrode an irreversible Co-III/II couple ( formal potential - 157 mV versus Ag-AgCl) is seen, which is indicative of dissociation of the divalent complex formed at the electrode. The free HOten released by the dissociation of [Co(HOten)](2+) can be recaptured by Hg as shown by cyclic voltammetry experiments on a static Hg drop electrode ( or in the presence of Hg2+ ions), which leads to the formation of an electroactive Hg-II complex of the N3S3 ligand (formal potential + 60 mV versus Ag-AgCl). This behaviour is in contrast to the facile and totally reversible voltammetry of the hexaamine complex [Co(HOsen)](3+) ( formal potential (Co-III/II) - 519 mV versus Ag-AgCl), which is uncomplicated by any coupled chemical reactions. Akinetic and thermodynamic analysis of the [Co(HOten)](2+)/[Hg(HOten)](2+) system is presented on the basis of digital simulation of the experimental voltammetric data.

Observations in a maternity ward: Usability considerations for EHRs in an interrupt driven environment

With the increasing demand on healthcare systems it is imperative that all care is provided as efficiently and effectively as possible. Technology within the medical domain offers an exciting opportunity to augment work practices in order to meet these needs. This research project explores the implications of the interrupt-driven nature of work in clinical situations on documentation within an environment that increasingly involves electronic health records (EHRs). Midwives in a busy maternity ward were observed and interviewed about the work practices they employed to document information associated with patient care. The results showed that the interrupt-driven nature of the workplace, a feature common to many healthcare settings, led to a tension between the work and the work to document the work. Further, the IT environment in which the information was collected was not designed to cater for frequent interruption of the data entry process. Several recommendations for improving the IT environment are proposed to support health professionals in documenting patient data whilst attending to the interruptions. The recommendations include timeout screens, push technology, use of handheld PDAs, and cues to augment documentation in an interrupted session. Copyright © 2008 RMIT Publishing

Efficient Data Management with Applications to IoT

The Internet of Things (IoT) consists of a worldwide “network of networks,” composed by billions of interconnected heterogeneous devices denoted as things or “Smart Objects” (SOs). Significant research efforts have been dedicated to port the experience gained in the design of the Internet to the IoT, with the goal of maximizing interoperability, using the Internet Protocol (IP) and designing specific protocols like the Constrained Application Protocol (CoAP), which have been widely accepted as drivers for the effective evolution of the IoT. This first wave of standardization can be considered successfully concluded and we can assume that communication with and between SOs is no longer an issue. At this time, to favor the widespread adoption of the IoT, it is crucial to provide mechanisms that facilitate IoT data management and the development of services enabling a real interaction with things. Several reference IoT scenarios have real-time or predictable latency requirements, dealing with billions of device collecting and sending an enormous quantity of data. These features create a new need for architectures specifically designed to handle this scenario, hear denoted as “Big Stream”. In this thesis a new Big Stream Listener-based Graph architecture is proposed. Another important step, is to build more applications around the Web model, bringing about the Web of Things (WoT). As several IoT testbeds have been focused on evaluating lower-layer communication aspects, this thesis proposes a new WoT Testbed aiming at allowing developers to work with a high level of abstraction, without worrying about low-level details. Finally, an innovative SOs-driven User Interface (UI) generation paradigm for mobile applications in heterogeneous IoT networks is proposed, to simplify interactions between users and things.

Perspectivas e metodologias de pesquisa da Comunicação Social no contexto da internet com o Big Data e da especialização Data Scientist

O trabalho desenvolvido analisa a Comunicação Social no contexto da internet e delineia novas metodologias de estudo para a área na filtragem de significados no âmbito científico dos fluxos de informação das redes sociais, mídias de notícias ou qualquer outro dispositivo que permita armazenamento e acesso a informação estruturada e não estruturada. No intento de uma reflexão sobre os caminhos, que estes fluxos de informação se desenvolvem e principalmente no volume produzido, o projeto dimensiona os campos de significados que tal relação se configura nas teorias e práticas de pesquisa. O objetivo geral deste trabalho é contextualizar a área da Comunicação Social dentro de uma realidade mutável e dinâmica que é o ambiente da internet e fazer paralelos perante as aplicações já sucedidas por outras áreas. Com o método de estudo de caso foram analisados três casos sob duas chaves conceituais a Web Sphere Analysis e a Web Science refletindo os sistemas de informação contrapostos no quesito discursivo e estrutural. Assim se busca observar qual ganho a Comunicação Social tem no modo de visualizar seus objetos de estudo no ambiente das internet por essas perspectivas. O resultado da pesquisa mostra que é um desafio para o pesquisador da Comunicação Social buscar novas aprendizagens, mas a retroalimentação de informação no ambiente colaborativo que a internet apresenta é um caminho fértil para pesquisa, pois a modelagem de dados ganha corpus analítico quando o conjunto de ferramentas promovido e impulsionado pela tecnologia permite isolar conteúdos e possibilita aprofundamento dos significados e suas relações.

Semi-supervised learning of hierarchical latent trait models for data visualisation

An interactive hierarchical Generative Topographic Mapping (HGTM) ¸iteH_GTM has been developed to visualise complex data sets. In this paper, we build a more general visualisation system by extending the HGTM visualisation system in 3 directions: bf (1) We generalize HGTM to noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM) developed in ¸iteKaban_pami. bf (2) We give the user a choice of initializing the child plots of the current plot in either em interactive, or em automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in ¸iteH_GTM, whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of LTMs is employed. bf (3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualisation plots, since they can highlight the boundaries between data clusters. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a toy example and apply our system to three more complex real data sets.

The impact of procurement-driven technological change on U.S. manufacturing productivity growth

As we enter the 21st Century, technologies originally developed for defense purposes such as computers and satellite communications appear to have become a driving force behind economic growth in the United States. Paradoxically, almost all previous econometric models suggest that the largely defense-oriented federal industrial R&D funding that helped create these technologies had no discernible effect on U.S. industrial productivity growth. This paper addresses this paradox by stressing that defense procurement as well as federal R&D expenditures were targeted to a few narrowly defined manufacturing sub-sectors that produced high tech weaponry. Analysis employing data from the NBER Manufacturing Productivity Database and the BEA' s Input Output tables then demonstrates that defense procurement policies did have significant effects on the productivity performance of disaggregated manufacturing industries because of a process of procurement-driven technological change.