Analysis of Dyscalculia Evidences through Artificial Intelligence Systems

Dyscalculia is usually perceived of as a specific learning difficulty for mathematics or, more appropriately, arithmetic. Because definitions and diagnoses of dyscalculia are in their infancy and sometimes are contradictory. However, mathematical learning difficulties are certainly not in their infancy and are very prevalent and often devastating in their impact. Co-occurrence of learning disorders appears to be the rule rather than the exception. Co-occurrence is generally assumed to be a consequence of risk factors that are shared between disorders, for example, working memory. However, it should not be assumed that all dyslexics have problems with mathematics, although the percentage may be very high, or that all dyscalculics have problems with reading and writing. Because mathematics is very developmental, any insecurity or uncertainty in early topics will impact on later topics, hence to need to take intervention back to basics. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work will focus on the development of a Decision Support System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, grounded on a Case-based approach to computing, that allows for the handling of incomplete, unknown, or even self-contradictory information.

Development of Mass Spectrometry-based analytical tools for characterization of bioconjugate vaccines in E. coli

Antigen design is generally driven by the need to obtain enhanced stability,efficiency and safety in vaccines.Unfortunately,the antigen modification is rarely proceeded in parallel with analytical tools development characterization.The analytical tools set up is required during steps of vaccine manufacturing pipeline,for vaccine production modifications,improvements or regulatory requirements.Despite the relevance of bioconjugate vaccines,robust and consistent analytical tools to evaluate the extent of carrier glycosylation are missing.Bioconjugation is a glycoengineering technology aimed to produce N-glycoprotein in vivo in E.coli cells,based on the PglB-dependent system by C. jejuni,applied for production of several glycoconjugate vaccines.This applicability is due to glycocompetent E. coli ability to produce site-selective glycosylated protein used,after few purification steps, as vaccines able to elicit both humoral and cell-mediate immune-response.Here, S.aureus Hla bioconjugated with CP5 was used to perform rational analytical-driven design of the glycosylation sites for the glycosylation extent quantification by Mass Spectrometry.The aim of the study was to develop a MS-based approach to quantify the glycosylation extent for in-process monitoring of bioconjugate production and for final product characterization.The three designed consensus sequences differ for a single amino-acid residue and fulfill the prerequisites for engineered bioconjugate more appropriate from an analytical perspective.We aimed to achieve an optimal MS detectability of the peptide carrying the consensus sequences,complying with the well-characterized requirements for N-glycosylation by PglB.Hla carrier isoforms,bearing these consensus sequences allowed a recovery of about 20 ng/μg of periplasmic protein glycosylated at 40%.The SRM-MS here developed was successfully applied to evaluate the differential site occupancy when carrier protein present two glycosites.The glycosylation extent in each glycosite was determined and the difference in the isoforms were influenced either by the overall source of protein produced and by the position of glycosite insertion.The analytical driven design of the bioconjugated antigen and the development of accurate,precise and robust analytical method allowed to finely characterize the vaccine.

Development of Optimal Energy Management Strategies for a Hybrid Boat

The present work proposes different approaches to extend the mathematical methods of supervisory energy management used in terrestrial environments to the maritime sector, that diverges in constraints, variables and disturbances. The aim is to find the optimal real-time solution that includes the minimization of a defined track time, while maintaining the classical energetic approach. Starting from analyzing and modelling the powertrain and boat dynamics, the energy economy problem formulation is done, following the mathematical principles behind the optimal control theory. Then, an adaptation aimed in finding a winning strategy for the Monaco Energy Boat Challenge endurance trial is performed via ECMS and A-ECMS control strategies, which lead to a more accurate knowledge of energy sources and boat’s behaviour. The simulations show that the algorithm accomplishes fuel economy and time optimization targets, but the latter adds huge tuning and calculation complexity. In order to assess a practical implementation on real hardware, the knowledge of the previous approaches has been translated into a rule-based algorithm, that let it be run on an embedded CPU. Finally, the algorithm has been tuned and tested in a real-world race scenario, showing promising results.

Developing the digital literacies of academic staff: an institutional approach

Institutional engagement with digital literacies at the University of Brighton has been promoted through the creation of a Digital Literacies Framework (DLF) aimed at academic staff. The DLF consists of 38 literacies divided into four categories that align to the following key areas of academic work: • Learning and teaching • Research • Communication and collaboration • Administration For each literacy, there is an explanation of what the literacy is, why it is important and how to gain it, with links to resources and training opportunities. After an initial pilot, the DLF website was launched in the summer of 2014. This paper discusses the strategic context and policy development of the DLF, its initial conception and subsequent development based on a pilot phase, feedback and evaluation. It critically analyses two of the ways that engagement with the DLF have been promoted: (1) formal professional development schemes and (2) the use of a ‘School-based’ approach. It examines the successes and challenges of the University of Brighton's scheme and makes some suggestions for subsequent steps including taking a course-level approach.

Performance assessment of vehicular connectivity in hybrid electric vehicles for fuel and emissions reduction

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.

Prospects For Early Investigational Therapies For Sickle Cell Disease.

Sickle cell disease (SCD) is a genetic disorder characterized by the production of abnormal hemoglobin that polymerizes at low oxygen concentrations, causing the erythrocyte to adopt a sickle-shaped morphology. SCD pathophysiology is extremely complex and can lead to numerous clinical complications, including painful vaso-occlusive crises (VOC), end-organ damage, and a shortened lifespan. An impressive number of investigational drugs are currently in early stages of clinical development with prospects for use either as chronic therapies to reduce VOC frequency and end-organ damage in SCD or for use at the time of VOC onset. Many of these agents have been developed using a pathophysiological-based approach to SCD, targeting one or more of the mechanisms that contribute to the disease process. It is plausible that a multi-drug approach to treating the disease will evolve in the coming years, whereby hydroxyurea (HU) (the only drug currently FDA-approved for SCD) is used in combination with drugs that amplify nitric oxide signaling and/or counteract hemolytic effects, platelet activation and inflammation.

As diferenças rítmicas entre o português europeu e o português brasileiro: uma abordagem otimalista e minimalista

The aim of this paper is to discuss some rhythmic differences between European and Brazilian Portuguese and their relationship to pretonic vowel reduction phenomena. After the basic facts of PE and PB are presented, we show that the issue cannot be discussed without taking into account secondary stress placement, and we proceed to present the algorithm-based approach to secondary stress in Portuguese, representative of Metrical Phonology analyses. After showing that this deterministic approach cannot adequately explain the variable position of secondary stress in both languages regarding words with an even number of pretonic syllables, we argue for the interpretation of secondary stress and therefore for the construction of rhythmic units at the PF interface, as suggested in Chomsky s Minimalist Program. We also propose, inspired by the constrain hierarchies as proposed in Optimality Theory, that such interpretation must take into account two different constraint rankings, in EP and BP. These different rankings would ultimately explain the rhythmic differences between both languages, as well as the different behavior of pretonic vowels with respect to reduction processes.

Etiologic diagnosis of bovine infectious abortion by PCR

Infectious abortion is a significant cause of reproductive failure and economic losses in cattle. The goal of this study was to detect nucleic acids of several infectious agents known to cause abortion including Arcanobacterium pyogenes, Bovine Herpesvirus 1, Brucella abortus, Campylobacter fetus subsp. venerealis, Chlamydophila abortus, Leptospira sp., Listeria monocytogenes, Salmonella sp., Mycoplasma bovis, Mycoplasma bovigenitalium, Neospora caninum, and Tritrichomonas foetus. Tissue homogenates from 42 fetuses and paraffin-embedded tissues from 28 fetuses and 14 placentas/endometrium were included in this study. Brucella abortus was detected in 14.2% (12/84) of the samples. Salmonella sp. DNA was amplified from 2 fetuses, and there was one positive for Neospora caninum, and another for Listeria monocytogenes. This PCR-based approach resulted in identification of the etiology in 19% of samples, or 20% if considered fetal tissues only.

E-contracting with price configuration for Web services and QoS

The large amount of information in electronic contracts hampers their establishment due to high complexity. An approach inspired in Software Product Line (PL) and based on feature modelling was proposed to make this process more systematic through information reuse and structuring. By assessing the feature-based approach in relation to a proposed set of requirements, it was showed that the approach does not allow the price of services and of Quality of Services (QoS) attributes to be considered in the negotiation and included in the electronic contract. Thus, this paper also presents an extension of such approach in which prices and price types associated to Web services and QoS levels are applied. An extended toolkit prototype is also presented as well as an experiment example of the proposed approach.

Experimental investigation on adaptive robust controller designs applied to a free-floating space manipulator

This paper aims to formulate and investigate the application of various nonlinear H(infinity) control methods to a fiee-floating space manipulator subject to parametric uncertainties and external disturbances. From a tutorial perspective, a model-based approach and adaptive procedures based on linear parametrization, neural networks and fuzzy systems are covered by this work. A comparative study is conducted based on experimental implementations performed with an actual underactuated fixed-base planar manipulator which is, following the DEM concept, dynamically equivalent to a free-floating space manipulator. (C) 2011 Elsevier Ltd. All rights reserved.

Large-scale ecological restoration of high-diversity tropical forests in SE Brazil

The complex interactions among endangered ecosystems, landowners` interests, and different models of land tenure and use, constitute an important series of challenges for those seeking to maintain and restore biodiversity and augment the flow of ecosystem services. Over the past 10 years, we have developed a data-based approach to address these challenges and to achieve medium and large-scale ecological restoration of riparian areas on private lands in the state of Sao Paulo, southeastern Brazil. Given varying motivations for ecological restoration, the location of riparian areas within landholdings, environmental zoning of different riparian areas, and best-practice restoration methods were developed for each situation. A total of 32 ongoing projects, covering 527,982 ha, were evaluated in large sugarcane farms and small mixed farms, and six different restoration techniques have been developed to help upscale the effort. Small mixed farms had higher portions of land requiring protection as riparian areas (13.3%), and lower forest cover of riparian areas (18.3%), than large sugarcane farms (10.0% and 36.9%, respectively for riparian areas and forest cover values). In both types of farms, forest fragments required some degree of restoration. Historical anthropogenic degradation has compromised forest ecosystem structure and functioning, despite their high-diversity of native tree and shrub species. Notably, land use patterns in riparian areas differed markedly. Large sugarcane farms had higher portions of riparian areas occupied by highly mechanized agriculture, abandoned fields, and anthropogenic wet fields created by siltation in water courses. In contrast, in small mixed crop farms, low or non-mechanized agriculture and pasturelands were predominant. Despite these differences, plantations of native tree species covering the entire area was by far the main restoration method needed both by large sugarcane farms (76.0%) and small mixed farms (92.4%), in view of the low resilience of target sites, reduced forest cover, and high fragmentation, all of which limit the potential for autogenic restoration. We propose that plantations should be carried out with a high-diversity of native species in order to create biologically viable restored forests, and to assist long-term biodiversity persistence at the landscape scale. Finally, we propose strategies to integrate the political, socio-economic and methodological aspects needed to upscale restoration efforts in tropical forest regions throughout Latin America and elsewhere. (C) 2010 Elsevier BA/. All rights reserved.

Contextual Deliberation of Cognitive Agents in Defeasible Logic

This article extends Defeasible Logic to deal with the contextual deliberation process of cognitive agents. First, we introduce meta-rules to reason with rules. Meta-rules are rules that have as a consequent rules for motivational components, such as obligations, intentions and desires. In other words, they include nested rules. Second, we introduce explicit preferences among rules. They deal with complex structures where nested rules can be involved.

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

An archaeobotanical perspective on Holocene plant-use practices in lowland northern New Guinea

Existing archaeobotanical and palynological records of plant use in the northern New Guinea lowlands are reviewed in light of recent work at Kuk and theoretical refocusing on plant use practice. A practice-based approach is supported as the most useful way of investigating the highly problematical area of tropical plant food production. The existing direct record of past plant use in lowland New Guinea is considered woefully inadequate to achieve this task, as is that in Near Oceania and Island Southeast Asia. Archaeobotanical methods exist to fill the void, but full implementation requires a change in general archaeological and palaeoecological practice.

Vaccination, atherosclerosis and systemic lupus erythematosus

Atherosclerosis is an inflammatory disease, leading to the formation of pro-inflammatory and pro-oxidative lipids that generate an immune response. Several antigens have been shown to activate the immune response and affect the development of atherogenesis. Systemic lupus erythematosus is an autoimmune and inflammatory disease strongly associated with premature development of atherosclerotic plaques. Modulation of the immune system could represent a useful approach to prevent and/or treat atherosclerosis. A vaccination-based approach might be a useful, effective tool in the modern arsenal of cardiovascular therapies and could be used on a large scale at a low cost. In non-systemic lupus erythematosus populations, vaccines against oxidized low-density lipoprotein, beta-2-glycoprotein I, heat shock proteins, lipoproteins, cholesterol, molecules involved in cholesterol metabolism, and other molecules (CD99, vascular endothelial growth factor-receptor, and interleukin-2) have been tested, with promising results. However, there are no studies of vaccination against atherosclerosis in systemic lupus erythematosus. Lupus (2009) 18, 1209-1212.