Educational data mining and learning analytics : Clasificación de las matriculaciones de A.D.E. en la UOC

Trabajo de investigación que realiza un estudio clasificatorio de las asignaturas matriculadas en la carrera de Administración y Dirección de Empresas de la UOC en relación a su resultado. Se proponen diferentes métodos y modelos de comprensión del entorno en el que se realiza el estudio.

Electric Motor and Frequency Converter Markets in Latin America and Especially in the Mining Industry of Chile

Latinalaisen Amerikan osuus maailmantaloudesta on pieni verrattuna sen maantieteelliseen kokoon, väkilukuun ja luonnonvaroihin. Aluetta pidetään kuitenkin yhtenä tulevaisuuden merkittävistä kasvumarkkinoista. Useissa Latinalaisen Amerikan maissa on teollisuutta, joka hyödyntää luonnonvaroja ja tuottaa raaka-aineita sekä kotimaan että ulkomaiden markkinoille. Tällaisia tyypillisiä teollisuudenaloja Latinalaisessa Amerikassa ovat kaivos- ja metsäteollisuus sekä öljyn ja maakaasun tuotanto. Näiden teollisuudenalojen tuotantolaitteiden ja koneiden valmistusta ei Latinalaisessa Amerikassa juurikaan ole. Ne tuodaan yleensä Pohjois-Amerikasta ja Euroopasta. Tässä diplomityössä tutkitaan sähkömoottorien ja taajuusmuuttajien markkinapotentiaalia Latinalaisessa Amerikassa. Tutkimuksessa perehdytään Latinalaisen Amerikan maiden kansantalouksien tilaan sekä arvioidaan sähkömoottorien ja taajuusmuuttajien markkinoiden kokoa tullitilastojen avulla. Chilen kaivosteollisuudessa arvioidaan olevan erityistä potentiaalia. Diplomityössä selvitetään ostoprosessin kulkua Chilen kaivosteollisuudessa ja eri asiakastyyppien roolia siinä sekä tärkeimpiä päätöskriteerejä toimittaja- ja teknologiavalinnoissa.

Automatic target validation based on neuroscientific literature mining for tractography.

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/.

Evaluation of GPRS Radio Link Control Layer in Weak RF Field

General Packet Radio Service (GPRS) mahdollistaa pakettimuotoisen tiedonsiirron GSM-verkossa. Se tarjoaa yhteyden pakettidataverkkoihin, nostaen samalla tiedonsiirtonopeutta radiorajapinnassa. Radioresurssit ovat varattuna vain silloin kun on jotain lähetettävää, tehden täten radioresurssien käytön paljon tehokkaammaksi. Tämä diplomityö keskittyy GPRS protokollaan ja erityisesti sen datapinossa olevaan Radio Link Control (RLC) kerrokseen. RLC-kerros huolehtii GPRS- puhelimen ja tukiaseman välisen yhteyden luotettavuudesta. Työn tavoitteena on tutkia RLC-kerroksen toiminnallisuutta ja sen luotettavuutta heikossa kentässä, sekä selvittää heikon kentän vaikutusta uudelleenlähetyksiin. Työn tuloksena saadaan arvio signaalin voimakkuuden sekä uudelleen lähetysten vaikutuksesta GPRS:n datansiirtonopeuteen. Tämä työ käsittelee myös lyhyesti GSM-järjestelmää, koska lukijan on näin helpompaa ymmärtää myös GPRS-järjestelmän vaatimia teknisiä muutoksia. Tämä diplomityö on tehty osana Nokia Matkapuhelimet Oyj:ssä käynnissä olevaa GPRS tuotekehitysprojektia. Työn tuloksia käytetään testauksen tukena ja niitä on käytetty apuna RLC-kerroksen luotettavuustestauksen suunnittelussa.

Population Size and Civil Conflict Risk: Is There A Causal Link?

[spa] La estimación del impacto del tamaño de la populación sobre la probabilidad de conflicto civil se complica por el sesgo de endogeneidad y las variables omitidas. Este artículo trata el problema de causalidad utilizando métodos de variables instrumentales en un panel de 37 países del África Sub-sahariana en el período 1981-2004. Encontramos que un aumento de la población en un 1% aumenta la probabilidad de conflicto civil por un 5.2%.

Physical Activity and Snus: Is There a Link?

The study aimed at assessing the link between physical activity (PA), sports activity and snus use among young men in Switzerland. Data from the Cohort Study on Substance Use Risk Factors (C-SURF) were used to measure PA with the International Physical Activity Questionnaire and sports activity with a single item. Multivariate logistic regression analysis was conducted to measure the association between snus use, PA and sports activity. Similar models were run for smoking and snuff use. Snus use increased in a dose-response association with PA (high level: OR = 1.72; 95% CI 1.16-2.55) and with individuals exercising once a week or more often (OR = 1.65; 95% CI 1.26-2.16; p < 0.001) or almost every day (OR = 2.27; 95% CI 1.72-3.01; p < 0.001) in separate models. Entered simultaneously, only sports and exercise maintained a basically unchanged significant dose-response relationship, whereas PA became non-significant. A non-significant dose-response relation was found for cigarette smoking and snuff use, indicating that the association with sport is specific to snus and not to tobacco use in general or smokeless tobacco in particular. This study showed that the association between snus use and sports is not specific to Nordic countries.

Alternatively spliced proline-rich cassettes link WNK1 to aldosterone action.

The thiazide-sensitive NaCl cotransporter (NCC) is important for renal salt handling and blood-pressure homeostasis. The canonical NCC-activating pathway consists of With-No-Lysine (WNK) kinases and their downstream effector kinases SPAK and OSR1, which phosphorylate NCC directly. The upstream mechanisms that connect physiological stimuli to this system remain obscure. Here, we have shown that aldosterone activates SPAK/OSR1 via WNK1. We identified 2 alternatively spliced exons embedded within a proline-rich region of WNK1 that contain PY motifs, which bind the E3 ubiquitin ligase NEDD4-2. PY motif-containing WNK1 isoforms were expressed in human kidney, and these isoforms were efficiently degraded by the ubiquitin proteasome system, an effect reversed by the aldosterone-induced kinase SGK1. In gene-edited cells, WNK1 deficiency negated regulatory effects of NEDD4-2 and SGK1 on NCC, suggesting that WNK1 mediates aldosterone-dependent activity of the WNK/SPAK/OSR1 pathway. Aldosterone infusion increased proline-rich WNK1 isoform abundance in WT mice but did not alter WNK1 abundance in hypertensive Nedd4-2 KO mice, which exhibit high baseline WNK1 and SPAK/OSR1 activity toward NCC. Conversely, hypotensive Sgk1 KO mice exhibited low WNK1 expression and activity. Together, our findings indicate that the proline-rich exons are modular cassettes that convert WNK1 into a NEDD4-2 substrate, thereby linking aldosterone and other NEDD4-2-suppressing antinatriuretic hormones to NCC phosphorylation status.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair.

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

A Dependency Parsing Approach to Biomedical Text Mining

Biomedical research is currently facing a new type of challenge: an excess of information, both in terms of raw data from experiments and in the number of scientific publications describing their results. Mirroring the focus on data mining techniques to address the issues of structured data, there has recently been great interest in the development and application of text mining techniques to make more effective use of the knowledge contained in biomedical scientific publications, accessible only in the form of natural human language. This thesis describes research done in the broader scope of projects aiming to develop methods, tools and techniques for text mining tasks in general and for the biomedical domain in particular. The work described here involves more specifically the goal of extracting information from statements concerning relations of biomedical entities, such as protein-protein interactions. The approach taken is one using full parsing—syntactic analysis of the entire structure of sentences—and machine learning, aiming to develop reliable methods that can further be generalized to apply also to other domains. The five papers at the core of this thesis describe research on a number of distinct but related topics in text mining. In the first of these studies, we assessed the applicability of two popular general English parsers to biomedical text mining and, finding their performance limited, identified several specific challenges to accurate parsing of domain text. In a follow-up study focusing on parsing issues related to specialized domain terminology, we evaluated three lexical adaptation methods. We found that the accurate resolution of unknown words can considerably improve parsing performance and introduced a domain-adapted parser that reduced the error rate of theoriginal by 10% while also roughly halving parsing time. To establish the relative merits of parsers that differ in the applied formalisms and the representation given to their syntactic analyses, we have also developed evaluation methodology, considering different approaches to establishing comparable dependency-based evaluation results. We introduced a methodology for creating highly accurate conversions between different parse representations, demonstrating the feasibility of unification of idiverse syntactic schemes under a shared, application-oriented representation. In addition to allowing formalism-neutral evaluation, we argue that such unification can also increase the value of parsers for domain text mining. As a further step in this direction, we analysed the characteristics of publicly available biomedical corpora annotated for protein-protein interactions and created tools for converting them into a shared form, thus contributing also to the unification of text mining resources. The introduced unified corpora allowed us to perform a task-oriented comparative evaluation of biomedical text mining corpora. This evaluation established clear limits on the comparability of results for text mining methods evaluated on different resources, prompting further efforts toward standardization. To support this and other research, we have also designed and annotated BioInfer, the first domain corpus of its size combining annotation of syntax and biomedical entities with a detailed annotation of their relationships. The corpus represents a major design and development effort of the research group, with manual annotation that identifies over 6000 entities, 2500 relationships and 28,000 syntactic dependencies in 1100 sentences. In addition to combining these key annotations for a single set of sentences, BioInfer was also the first domain resource to introduce a representation of entity relations that is supported by ontologies and able to capture complex, structured relationships. Part I of this thesis presents a summary of this research in the broader context of a text mining system, and Part II contains reprints of the five included publications.

Metabolic syndrome and nonalcoholic fatty liver disease: Is insulin resistance the link?

Metabolic syndrome (MetS) is a disease composed of different risk factors such as obesity, type 2 diabetes or dyslipidemia. The prevalence of this syndrome is increasing worldwide in parallel with the rise in obesity. Nonalcoholic fatty liver disease (NAFLD) is now the most frequent chronic liver disease in western countries, affecting more than 30% of the general population. NAFLD encompasses a spectrum of liver manifestations ranging from simple steatosis to nonalcoholic steatohepatitis (NASH), fibrosis and cirrhosis, which may ultimately progress to hepatocellular carcinoma. There is accumulating evidence supporting an association between NAFLD and MetS. Indeed, NAFLD is recognized as the liver manifestation of MetS. Insulin resistance is increasingly recognized as a key factor linking MetS and NAFLD. Insulin resistance is associated with excessive fat accumulation in ectopic tissues, such as the liver, and increased circulating free fatty acids, which can further promote inflammation and endoplasmic reticulum stress. This in turn aggravates and maintains the insulin resistant state, constituting a vicious cycle. Importantly, evidence shows that most of the patients developing NAFLD present at least one of the MetS traits. This review will define MetS and NAFLD, provide an overview of the common pathophysiological mechanisms linking MetS and NAFLD, and give a perspective regarding treatment of these ever growing metabolic diseases.

Construction of an index of information from clinical practice in Radiology and Imaging Diagnosis based on text mining and thesaurus

Objective To construct a Portuguese language index of information on the practice of diagnostic radiology in order to improve the standardization of the medical language and terminology. Materials and Methods A total of 61,461 definitive reports were collected from the database of the Radiology Information System at Hospital das Clínicas – Faculdade de Medicina de Ribeirão Preto (RIS/HCFMRP) as follows: 30,000 chest x-ray reports; 27,000 mammography reports; and 4,461 thyroid ultrasonography reports. The text mining technique was applied for the selection of terms, and the ANSI/NISO Z39.19-2005 standard was utilized to construct the index based on a thesaurus structure. The system was created in *html. Results The text mining resulted in a set of 358,236 (n = 100%) words. Out of this total, 76,347 (n = 21%) terms were selected to form the index. Such terms refer to anatomical pathology description, imaging techniques, equipment, type of study and some other composite terms. The index system was developed with 78,538 *html web pages. Conclusion The utilization of text mining on a radiological reports database has allowed the construction of a lexical system in Portuguese language consistent with the clinical practice in Radiology.

Exploring the link between flexible working and organizational performance

The expansion of flexible work experienced since the 1980s in developed economies is consistent with a more generic trend towards organizational flexibility, which many authors see as essential in order to compete in the dynamic global environment (Volberda, 1998). From this point of view, the changing demands of the environment have forced organizations to seek the ability to adapt rapidly and effectively as a means to be successful or even to survive. In the quest for flexibility, every area of the organization has been scrutinized in order to render it as ¿agile¿ as possible. In the human resources arena, this analysis has led to the definition of diverse ¿flexible working practices¿ (FWP) that describe a wide range of employment practices, which differ from the traditional full-time job with a fixed salary and a permanent contract. These practices have been described using other terms, such as ¿alternative¿ (Polivka, 1996; Powell & Mainiero, 1999), ¿non-standard¿ (Kalleberg, 2000), or ¿atypical¿ (De Grip, Hoevenberg, &m Willems, 1997), which coincide in denoting their divergence from the most traditional forms of employment. This article will show that quite different practices have been embraced by the common term ¿flexible working practices.¿ Subsequently, the results of empirical research regarding the implications for organizational performance of a number of flexible practices will be commented on.