Interactive Calculus in a Virtual Learning Environment

The teaching of higher level mathematics for technical students in a virtual learningenvironment poses some difficulties, but also opportunities, now specific to that virtuality.On the other hand, resources and ways to do now manly available in VLEs might soon extend to all kinds of environments.In this short presentation we will discuss anexperience carried at Universitat Oberta deCatalunya (UOC) involving (an on line university), first, the translation of LaTeX written existent materials to a web based format(specifically, a combination of XHTML andMathML), and then the integration of a symbolic calculator software (WIRIS) running as a Java applet embedded in the materials, intending to achieve an evolution from memorising concepts and repetitive algorithms to understanding and experiment concepts and the use of those algorithms.

Fostering Collaborative Knowledge Building by the Effective Provision of Knowledge about the Discussion Process

Peer-reviewed

Emprego de nebulizador pneumático de ICP-MS como câmara de diluição em sistemas de injeção em fluxo para determinações multielementares

An automatic dispenser based on a flow-injection system used to introduce sample and analytical solution into an inductively coupled plasma mass spectrometer through a spray chamber is proposed. Analytical curves were constructed after the injection of 20 to 750 µL aliquots of a multielement standard solution (20.0 µg L-1 in Li, Be, Al, V, Cr, Mn, Ni, Co, Cu, Zn, As, Se, Sr, Ag, Cd, Ba, Tl, Pb) and the acquisition of the integrated transient signals. The linear concentration range could be extended to ca. five decades. The performance of the system was checked by analyzing a NIST 1643d reference material. Accuracy could be improved by the proper selection of the injected volume. Besides good precision (r.s.d. < 2%), the results obtained with the proposed procedure were closer to the certified values of the reference material than those obtained by direct aspiration or by injecting 125 µL of several analytical solutions and samples.

Sistema de termostatização para aplicação em análise por injeção em fluxo

A on-line thermostatization system that use simples materials, for flow injection and continuous flow analysis is described. The proposed system showed good performance between 10 to 40ºC.

Eletrodissolução de ligas de latão empregando sistemas de análise em fluxo para a determinação de cobre, zinco e chumbo por ICP-AES

An on-line electrodissolution procedure implemented in a flow injection system for determination of copper, zinc and lead in brasses alloys by ICP-AES is described. Sample dissolution procedure was carried out by using a PTFE chamber and a DC power supply with constant current. Solid sample was attached to chamber as anode and a gold tubing coupled in the chamber was used as cathode. An electrolytic solution flowing through the gold tubing closed the electric circuit with sample, in order to provide condition for electric dissolution when the DC power supply was switched on. The best results were achieved by using a 1.5 mol l-1 nitric acid solution as electrolyte and a 2.5 A current intensity. The procedure presented a good performance characterized by a relative standard deviation better than < 5% (n=5) and a sample throughput of 180 determinations per hour for Cu, Zn and Pb. Results were in agreement with those obtained by conventional acid dissolution (99% confidence level).

Dissolução eletrolítica para a determinação de elementos de liga em aço ferramenta por ICP-AES

Different methods have been applied to solve special problems of metal analysis. First, the solid samples of tool steels were analyzed by X-ray fluorescence. Alternatively, an on-line electrodissolution implemented in a flow injection system and conventional dissolution procedure for determination of W, Mo, V and Cr in tool steels by ICP-AES is described. The resulting analyte solutions were compared with conventional dissolution procedure and determination by ICP-AES. The electrolytic procedure presented a good performance characterized by a sample throughput of 164 determinations per hour. Results were in agreement with those obtained by conventional acid dissolution.

The influence of genetic and environmental factors among MDMA users in cognitive performance

This study is aimed to clarify the association between MDMA cumulative use and cognitive dysfunction, and the potential role of candidate genetic polymorphisms in explaining individual differences in the cognitive effects of MDMA. Gene polymorphisms related to reduced serotonin function, poor competency of executive control and memory consolidation systems, and high enzymatic activity linked to bioactivation of MDMA to neurotoxic metabolites may contribute to explain variations in the cognitive impact of MDMA across regular users of this drug. Sixty ecstasy polydrug users, 110 cannabis users and 93 non-drug users were assessed using cognitive measures of Verbal Memory (California Verbal Learning Test, CVLT), Visual Memory (Rey-Osterrieth Complex Figure Test, ROCFT), Semantic Fluency, and Perceptual Attention (Symbol Digit Modalities Test, SDMT). Participants were also genotyped for polymorphisms within the 5HTT, 5HTR2A, COMT, CYP2D6, BDNF, and GRIN2B genes using polymerase chain reaction and TaqMan polymerase assays. Lifetime cumulative MDMA use was significantly associated with poorer performance on visuospatial memory and perceptual attention. Heavy MDMA users (>100 tablets lifetime use) interacted with candidate gene polymorphisms in explaining individual differences in cognitive performance between MDMA users and controls. MDMA users carrying COMT val/val and SERT s/s had poorer performance than paired controls on visuospatial attention and memory, and MDMA users with CYP2D6 ultra-rapid metabolizers performed worse than controls on semantic fluency. Both MDMA lifetime use and gene-related individual differences influence cognitive dysfunction in ecstasy users.

Análise de fármacos em material biológico: acoplamento microextração em fase sólida "no tubo" e cromatografia líquida de alta eficiência

A new solid phase microextraction (SPME) system, known as in-tube SPME, was recently developed using an open tubular fused-silica capilary column, instead of an SPME fiber, as the SPME device. On-line in-tube SPME is usually used in combination with high performance liquid chromatography. Drugs in biological samples are directly extracted and concentrated in the stationary phase of capillary columns by repeated draw/eject cycles of sample solution, and then directly transferred to the liquid chromatographic column. In-tube SPME is suitable for automation. Automated sample handling procedures not only shorten the total analysis time, but also usually provide better accuracy and precision relative to manual techniques. In-tube SPME has been demonstrated to be a very effective and highly sensitive technique to determine drugs in biological samples for various purposes such as therapeutic drug monitoring, clinical toxicology, bioavailability and pharmacokinetics.

The Effect of Operational Disturbances on Reliability and Operation Time Distribution of NCmachine Tools in FMS

This thesis concentrates on studying the operational disturbance behavior of machine tools integrated into FMS. Operational disturbances are short term failures of machine tools which are especially disruptive to unattended or unmanned operation of FMS. The main objective was to examine the effect of operational disturbances on reliability and operation time distribution for machine tools. The theoretical part of the thesis covers the fimdamentals of FMS relating to the subject of this study. The concept of FMS, its benefits and operator's role in FMS operation are reviewed. The importance of reliability is presented. The terms describing the operation time of machine tools are formed by adopting standards and references. The concept of failure and indicators describing reliability and operational performance for machine tools in FMSs are presented. The empirical part of the thesis describes the research methodology which is a combination of automated (ADC) and manual data collection. By using this methodology it is possible to have a complete view of the operation time distribution for studied machine tools. Data collection was carried out in four FMSs consisting of a total of 17 machine tools. Each FMS's basic features and the signals of ADC are described. The indicators describing the reliability and operation time distribution of machine tools were calculated according to collected data. The results showed that operational disturbances have a significant influence on machine tool reliability and operational performance. On average, an operational disturbance occurs every 8,6 hours of operation time and has a down time of 0,53 hours. Operational disturbances cause a 9,4% loss in operation time which is twice the amount of losses caused by technical failures (4,3%). Operational disturbances have a decreasing influence on the utilization rate. A poor operational disturbance behavior decreases the utilization rate. It was found that the features of a part family to be machined and the method technology related to it are defining the operational disturbance behavior of the machine tool. Main causes for operational disturbances were related to material quality variations, tool maintenance, NC program errors, ATC and machine tool control. Operator's role was emphasized. It was found that failure recording activity of the operators correlates with the utilization rate. The more precisely the operators record the failure, the higher is the utilization rate. Also the FMS organizations which record failures more precisely have fewer operational disturbances.

Coneixement lingüístic i matemàtic d'escolars de nivel sociocultural baix en programes d'immersió = Linguistic and mathematic knowledge in pupils of low sociocultural level in immersiom programmes

This piece of research compares knowledge of Catalan, Castilian and mathematics, as well as the attitudes to these two languages, of a sample of non-Catalan speaking pupils of low sociocultural level in their fourth year of primary school. Some of the pupils had followed an immersion programme in Catalan, whereas others had approached Catalan through their habitual language (Castilian). The findings show that not only did the immersion pupils obtain significantly better results in L2 (Catalan), but their mother tongue (Castilian) competence was undiminished and their performance on the mathematics test was superior to that of the other group. Moreover, the findings indicate that in pupils starting out from less favourable conditions (a low sociocultural level and a low I.Q.) the effect of the educational approach variable is greater than in other cases

Farmacología y toxicología en I+D+i: adquisición de competencias a través de un ejemplo de desarrollo de un fármaco

The implementation of the subject Pharmacology and Toxicology in R+D+i in the Pharmacy Degree, has led to the launch of a new methodological approach and teaching performance with the aim of developing the generic skills of the University of Barcelona (e.g., self-learning, team-working). An additional objective was students' integration of knowledge from different subjects in the degree which form the basis of the preclinical and clinical development of a drug. For this purpose, the teaching strategy used in the development of the subject was based on: 1) re-developing the content that students had been taught previously or were being taught in the same semester as a part of other subjects, and framing them in the environment of the pharmaceutical industry, 2) introducing new and previously unseen contents to do with drug development and toxicology, 3) developing a battery of activities to be undertaken by teams of students relating to the R+D+i of a particular drug. During the development of these activities, students have to acquire generic skills in addition to the subject-specific skills. The results obtained from the student survey give us grounds for satisfaction and allow us to consider that we have reached the goal of improving students' learning in Pharmacology and Toxicology applied to drug development in the pharmaceutical world today.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Höyryturbiinin käytönaikaisen suorituskyvyn seuranta

Tässä diplomityössä jatkettiin Loviisan voimalaitoksen höyryturbiinien suorituskyvyn parannuspotentiaalien tutkimusta. Tavoitteena oli kehittää laitoksen höyryturbiinien suorituskyvyn käytönaikaisia on-line-mittauksia. Selvityksessä perehdyttiin norjalaisen IFE:n kehittämään stationääritilan TEMPOohjelmaan( The Thermal Performance Monitoring And Optimisation system), sen käyttöohjeisiin ja toimintaperiaatteisiin. Työssä esiteltiin laajasti tiedon yhteensovittamisen laskentateoriaa, johon TEMPOn toiminta perustuu. Työssä tarkasteltiin turbiinin todellista paisuntaprosessia, koska sen ymmärtäminen on tärkeässä osassa turbiinin suorituskyvyn valvonnassa. Tutkimuksessa esiteltiin myös turbiineille mahdollisia vikoja sekä niiden syntymisprosesseja. Työssä tarkasteltiin TEMPOn sovittamien tulostiedostojen analysointiohjelman toimivuutta havaitsemalla itse aiheutettuja poikkeamia todellisiin mittaustiedostoihin. Analysointiohjelmalla muodostettuja kuvaajia vertailtiin todellisen prosessin ajotilanteen kuvaajiin ja tarkasteltiin, kuinka poikkeamia on mahdollista havaita kuvaajien avulla. TEMPO-ohjelmalle löydettiin tutkimuksen edetessä kehittämisehdotuksia. Näillä muutoksilla ohjelma saadaan mallintamaan Loviisan voimalaitoksen turbiiniprosessia tarkemmin ja tuloksista saadaan hyödyllisempiä.

Experiences among primary school teachers in Tanzania

The overall aim of the study was to explore primary school teachers’ experiences of constraints to their work, and actions taken for improvement after undergoing in-service courses in the Education Quality Improvement through Pedagogy program. The research interest was thus to deepen the understanding of teachers’ experiences of constraints to their work and experiences of actions taken to improve classroom actions. In order to achieve this ambition, the study was conducted with primary school teachers in Shinyanga district-Tanzania. Two research questions guided the study: What do teachers experience as constraints to their work? The second: How have teachers improved their classroom actions after undergoing professional development courses? The theoretical framework of the study is centred on limiting and enabling frames on teachers’ work and professional development. In order to understand the classroom situations, qualitative research was designed applying a phenomenological approach with semi-structured interview, observation and videotaping to collect data. Forty experienced primary school teachers from ten primary schools participated in the study. The results of the first research question indicate that teachers face many constraints in their work. Three categories identified as interactional, environmental and professional role constraints. The most critical experienced by all teachers is teaching in large classes and inadequate teaching and learning materials. The results of the second research question show that teachers’ actions taken for improving their work were influenced by professional development activities. Three main categories including expanded interaction, expanded use of environment and expanded professional roles were identified. Generally, the knowledge generated is relevant for viewing teachers’ experiences of the challenges they encounter in teaching and the importance of professional development beyond the sampled respondents. The results suggest that constant provision of teachers’ professional development could improve teaching performance.

Evaluating Performance of Content Marketing: YouTube Marketing in Finnish Food and Drink Industry

The purpose of this research was to define content marketing and to discover how content marketing performance can be measured especially on YouTube. Further, the aim was to find out what companies are doing to measure content marketing and what kind of challenges they face in the process. In addition, preferences concerning the measurement were examined. The empirical part was conducted through multiple-case study and cross-case analysis methods. The qualitative data was collected from four large companies in Finnish food and drink industry through semi-structured phone interviews. As a result of this research, a new definition for content marketing was derived. It is suggested that return on objective, or in this case, brand awareness and engagement are used as the main metrics of content marketing performance on YouTube. The major challenge is the nature of the industry, as companies cannot connect the outcome directly to sales.