Nursing student-patient relationship and associated factors

The purpose of this study was to analyse the nursing student-patient relationship and factors associated with this relationship from the point of view of both students and patients, and to identify factors that predict the type of relationship. The ultimate goal is to improve supervised clinical practicum with a view to supporting students in their reciprocal collaborative relationships with patients, increase their preparedness to meet patients’ health needs, and thus to enhance the quality of patient care. The study was divided into two phases. In the first phase (1999-2005), a literature review concerning the student-patient relationship was conducted (n=104 articles) and semi-structured interviews carried out with nursing students (n=30) and internal medicine patients (n=30). Data analysis was by means of qualitative content analysis and Student-Patient Relationship Scales, which were specially developed for this research. In the second phase (2005-2007), the data were collected by SPR scales among nursing students (n=290) and internal medicine patients (n=242). The data were analysed statistically by SPSS 12.0 software. The results revealed three types of student-patient relationship: a mechanistic relationship focusing on the student’s learning needs; an authoritative relationship focusing on what the student assumes is in the patient’s best interest; and a facilitative relationship focusing on the common good of both student and patient. Students viewed their relationship with patients more often as facilitative and authoritative than mechanistic, while in patients’ assessments the authoritative relationship occurred most frequently and the facilitative relationship least frequently. Furthermore, students’ and patients’ views on their relationships differed significantly. A number of background factors, contextual factors and consequences of the relationship were found to be associated with the type of relationship. In the student data, factors that predicted the type of relationship were age, current year of study and support received in the relationship with patient. The higher the student’s age, the more likely the relationship with the patient was facilitative. Fourth year studies and the support of a person other than a supervisor were significantly associated with an authoritative relationship. Among patients, several factors were found to predict the type of nursing student-patient relationships. Significant factors associated with a facilitative relationship were university-level education, several previous hospitalizations, admission to hospital for a medical problem, experience of caring for an ill family member and patient’s positive perception of atmosphere during collaboration and of student’s personal and professional growth. In patients, positive perceptions of student’s personal and professional attributes and patient’s improved health and a greater commitment to self-care, on the other hand, were significantly associated with an authoritative relationship, whereas positive perceptions of one’s own attributes as a patient were significantly associated with a mechanistic relationship. It is recommended that further research on the student-patient relationship and related factors should focus on questions of content, methodology and education.

Intelligent Internet Data Searching

In this thesis author approaches the problem of automated text classification, which is one of basic tasks for building Intelligent Internet Search Agent. The work discusses various approaches to solving sub-problems of automated text classification, such as feature extraction and machine learning on text sources. Author also describes her own multiword approach to feature extraction and pres-ents the results of testing this approach using linear discriminant analysis based classifier, and classifier combining unsupervised learning for etalon extraction with supervised learning using common backpropagation algorithm for multilevel perceptron.

Sähkönjakeluverkon komponenttien pitoajat

Suomessa sähkönjakeluverkkoyhtiöt toimivat verkkovastuualueillaan yksinoikeudella. Verkkovastuualuiden ominaispiirteet voivat olla hyvin erilaiset. Energiamarkkinavirasto valvoo sähkömarkkinalainsäädännön noudattamista jakeluverkkotoiminnassa. Jakeluverkonhaltijat on velvoitettu Energiamarkkinaviraston valvontamallin kautta määrittämään tiettyjen rajoitusten mukaisesti verkkokomponenteillensa sopivimmat teknistaloudelliset pitoajat. Nämä pitoajat vaikuttavat varsinkin verkkoyhtiön tuottomahdollisuuksiin ja asiakkaiden siirtohintoihin. Lisäksi huomioon on otettava jaettavan sähkön laatu, verkon käyttövarmuus sekä vaikutukset ympäristöön ja turvallisuuteen. Pitoaikojen matemaattinen mallintaminen on usein monimutkaista. Teknistaloudellinen pitoaika valitaankin monesti kokemuksen ja harkinnan perusteella. Tärkeimmät reunaehdot jakeluverkkokomponenttien teknistaloudellisten pitoaikojen valinnalle muodostavat verkkovastuualueen sähkönkulutuksen kasvun sekä infrastruktuurin muutoksen nopeudet. Hitaan muutoksen alueilla verkkokomponenttien teknistaloudelliset pitoajat lähenevät teknisiä pitoaikoja, joihin vaikuttavat voimakkaasti verkkovastuualueen maantieteelliset ja ilmastolliset ominaispiirteet. Yhtiöittäin vaihtelevat verkon rakennus- ja ylläpitomenetelmät tulee myös huomioida. Tässä diplomityössä keskitytään pääosin sähkönjakeluverkon komponenttien teknistaloudelliseen pitoaikaan verkon ja verkkovastuualueen ominaispiirteiden kautta. Aluksi määritellään jakeluverkon pitoaika usealla eri tavalla, sekä selvitetään pitoajan merkitystä nykytilanteessa. Lisäksi työn alkuosassa esitellään Energiamarkkinaviraston vuoden 2005 alusta käyttöönotettu jakeluverkkotoiminnan hinnoittelun kohtuullisuuden valvontamalli ja käydään läpi teknistaloudellisen pitoajan merkitys siinä. Sen jälkeen tarkastellaan jakeluverkkokomponenttien ja niiden osien tekniseen pitoaikaan vaikuttavia tekijöitä. Erityisesti puupylväisiin ja niihin liittyviin ajankohtaisiin asioihin kiinnitetään huomiota, koska puupylväät määräävät monesti koko ilmajohtorakenteen uusimisajankohdan. Lisäksi suolakyllästeiselle puupylväälle esitetään yleinen rappeutumismalli ja jakelumuuntajan rappeutumistapahtumaa tutkitaan. Lopuksi tarkastellaan Graninge Kainuu Oy:tä jakeluverkonhaltijana sekä määritetään sen verkkovastuualueelle ominaisia komponenttien teknisiä ja teknistaloudellisia pitoaikoja haastattelujen, tuoreimpien lähteiden, tutkimustulosten, vertailun ja harkinnan avulla.

Verkkoliiketoiminnan tehokkuusmittauksen ohjausvaikutusten analysointijärjestelmä

Tässä diplomityössä oli tavoitteena suunnitella ja toteuttaa verkkoliiketoiminnan tehokkuusmittauksen ohjausvaikutusten analysointijärjestelmä. Verkkoliiketoiminta on monopoliasemassa olevaa liiketoimintaa, jossa ei ole kilpailusta johtuvaa pakotetta pitää liiketoimintaa tehokkaana ja hintoja alhaisina. Tämän vuoksi verkkoliiketoiminnan hinnoittelua ja toiminnan tehokkuutta tulee valvoa viranomaisen toimesta. Tehokkuusmittauksessa käytettäväksi menetelmäksi on valittu DEA-menetelmä (Data Envelopment Analysis). Tässä työssä on esitelty DEA-menetelmän teoreettiset perusteet sekä verkkoliiketoiminnan tehokkuusmittauksessa havaitut ongelmat. Näiden perusteella on määritelty analysointijärjestelmältä vaadittavat ominaisuudet sekä kehitetty kyseinen järjestelmä. Tärkeimmiksi järjestelmän ominaisuuksiksi osoittautuivat herkkyysanalyysin tekeminen ja etenkin sitä kautta suoritettava keskeytysten hinnan laskeminen sekä mahdollisuudet painokertoimien rajoittamiselle. Työn loppuosassa on esitelty järjestelmästä saatavia konkreettisia tuloksia, joiden avulla on pyritty havainnollistamaan järjestelmän käyttömahdollisuuksia.

Environmental Monitoring using Image Analysis

Tärkeä tehtävä ympäristön tarkkailussa on arvioida ympäristön nykyinen tila ja ihmisen siihen aiheuttamat muutokset sekä analysoida ja etsiä näiden yhtenäiset suhteet. Ympäristön muuttumista voidaan hallita keräämällä ja analysoimalla tietoa. Tässä diplomityössä on tutkittu vesikasvillisuudessa hai vainuja muutoksia käyttäen etäältä hankittua mittausdataa ja kuvan analysointimenetelmiä. Ympäristön tarkkailuun on käytetty Suomen suurimmasta järvestä Saimaasta vuosina 1996 ja 1999 otettuja ilmakuvia. Ensimmäinen kuva-analyysin vaihe on geometrinen korjaus, jonka tarkoituksena on kohdistaa ja suhteuttaa otetut kuvat samaan koordinaattijärjestelmään. Toinen vaihe on kohdistaa vastaavat paikalliset alueet ja tunnistaa kasvillisuuden muuttuminen. Kasvillisuuden tunnistamiseen on käytetty erilaisia lähestymistapoja sisältäen valvottuja ja valvomattomia tunnistustapoja. Tutkimuksessa käytettiin aitoa, kohinoista mittausdataa, minkä perusteella tehdyt kokeet antoivat hyviä tuloksia tutkimuksen onnistumisesta.

Partial cricotracheal resection for paediatric subglottic stenosis: update of the Lausanne experience with 129 cases.

OBJECTIVES: Partial cricotracheal resection (PCTR) is widely accepted for treating severe paediatric laryngotracheal stenosis (LTS). However, it remains limited to a few experienced centres. Here we report an update of the Lausanne experience in paediatric PCTR performed or supervised by a senior surgeon (Philippe Monnier). METHODS: An ongoing database of 129 paediatric patients who underwent PCTR for benign LTS between March 1978 and July 2012 at our hospital was retrospectively reviewed. Demographic characteristics and information on preoperative status, stenosis and surgery were collected. Primary outcomes were measured as overall and operation-specific decannulation rates (ODR and OSDR, respectively), and secondary outcomes as morbidity, mortality and postoperative functional results. RESULTS: A total of 129 paediatric patients [79 males and 50 females; mean age, 4.1 years (1 month-16 years, median age of 2 years old)] underwent PCTR during the study period. ODR and OSDR were 90 and 81%, respectively. The decannulation rates were significantly superior for single-stage PCTR compared with double-stage PCTR in both ODR and OSDR. Eight patients died postoperatively for reasons unrelated to surgery. Partial anastomotic dehiscence was seen in 13 patients, 9 of whom were successfully treated by revision surgery. Respiratory, voice and swallowing functions were near normal or only minimally impaired in 86, 65 and 81% of patients, respectively. CONCLUSIONS: PCTR is effective and feasible with good ODR and OSDR for highgrade / severe LTS. Glottic involvement and the presence of comorbidities were negative predictive factors of decannulation. Early detection and reintervention of postoperative incipient dehiscence contribute to avoiding the progress to late restenosis; however, voice improvement remains a challenge.

Polymorphisms in DNA-repair genes in a cohort of prostate cancer patients from different areas in Spain: heterogeneity between populations as a confounding factor in association studies

Background: Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics. Objective: To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias. Design, Setting, and Participants: A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArrayH NT Cycler. Outcome Measurements and Statistical Analysis: Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer. Results and Limitations: We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics. Conclusion: Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out.

El Aprendizaje de las habilidades sociales en la universidad. Análisis de una experiencia formativa en los grados de educación Social y trabajo Social

Se presenta una metodología formativa desarrollada en la asignatura de habilidades sociales de los grados otorgados por la Facultad de Educación Social y Trabajo Social Pere Tarrés de la Universidad Ramón Llull (Barcelona-España). A partir del análisis inicial de las competencias sociales de los estudiantes, se establece un plan de trabajo con la finalidad de que mejoren las habilidades sociales necesarias en el contexto profesional. La metodología se plantea como práctica supervisada que requiere la incorporación del estudiante en la organización, desarrollo y evaluación de la asignatura. Para facilitar esa incorporación se ha introducido un recurso narrativo que da sentido a todas las actividades. Se ha utilizado como indicadores de la validez social de esta metodología los datos recogidos a través encuestas de satisfacción de los estudiantes. Los resultados positivos de la experiencia justifican su difusión y su uso en otras universidades.

Mentoring in the acquisition of professional skills through practices in companies by degree students

Abstract This work has had as objective to analyze the skills acquired through internships in business companies by students of the Faculty of Economics and Business at the University Pompeu Fabra. The internship is a basic item in order to obtain a hard connection between the University and social-economic world where University and Enterprises develop their activity. In this study we want to know about two aspects. The first one, we want to know the profit that is obtained from the Student as a consequence of internship and mentoring. Also, we want to study about the importance of mentoring as a principal element that establishes the relationship between the Student and the Company. Moreover, it has sought to analyze if certain factors such as the size of the company where the practices has been performed, the study rank level that was achieved or the fact of being a man or a woman, were among the determining factors at the time of acquiring the skills. The results presented here indicate that the size of the company that have been making the practices and the gender of the student are related to the acquisition of certain skills. There was not a statistically significant relationship related to the rank level have by the students in the practice. In the future we are going to study if the labor market Integration is easier if the Student has performed work placement. Keywords Skills; employability; internship; meatoring.

Immediate ecotoxicological effects of short-lived oil spills on marine biota.

Marine environments are frequently exposed to oil spills as a result of transportation, oil drilling or fuel usage. Whereas large oil spills and their effects have been widely documented, more common and recurrent small spills typically escape attention. To fill this important gap in the assessment of oil-spill effects, we performed two independent supervised full sea releases of 5 m(3) of crude oil, complemented by on-board mesocosm studies and sampling of accidentally encountered slicks. Using rapid on-board biological assays, we detect high bioavailability and toxicity of dissolved and dispersed oil within 24 h after the spills, occurring fairly deep (8 m) below the slicks. Selective decline of marine plankton is observed, equally relevant for early stages of larger spills. Our results demonstrate that, contrary to common thinking, even small spills have immediate adverse biological effects and their recurrent nature is likely to affect marine ecosystem functioning.

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

Opinion Mining

In this thesis we study the field of opinion mining by giving a comprehensive review of the available research that has been done in this topic. Also using this available knowledge we present a case study of a multilevel opinion mining system for a student organization's sales management system. We describe the field of opinion mining by discussing its historical roots, its motivations and applications as well as the different scientific approaches that have been used to solve this challenging problem of mining opinions. To deal with this huge subfield of natural language processing, we first give an abstraction of the problem of opinion mining and describe the theoretical frameworks that are available for dealing with appraisal language. Then we discuss the relation between opinion mining and computational linguistics which is a crucial pre-processing step for the accuracy of the subsequent steps of opinion mining. The second part of our thesis deals with the semantics of opinions where we describe the different ways used to collect lists of opinion words as well as the methods and techniques available for extracting knowledge from opinions present in unstructured textual data. In the part about collecting lists of opinion words we describe manual, semi manual and automatic ways to do so and give a review of the available lists that are used as gold standards in opinion mining research. For the methods and techniques of opinion mining we divide the task into three levels that are the document, sentence and feature level. The techniques that are presented in the document and sentence level are divided into supervised and unsupervised approaches that are used to determine the subjectivity and polarity of texts and sentences at these levels of analysis. At the feature level we give a description of the techniques available for finding the opinion targets, the polarity of the opinions about these opinion targets and the opinion holders. Also at the feature level we discuss the various ways to summarize and visualize the results of this level of analysis. In the third part of our thesis we present a case study of a sales management system that uses free form text and that can benefit from an opinion mining system. Using the knowledge gathered in the review of this field we provide a theoretical multi level opinion mining system (MLOM) that can perform most of the tasks needed from an opinion mining system. Based on the previous research we give some hints that many of the laborious market research tasks that are done by the sales force, which uses this sales management system, can improve their insight about their partners and by that increase the quality of their sales services and their overall results.

Construindo o estágio de docência da pós-graduação em química

The teaching apprenticeship established by CAPES for post-graduation scholarship beholders has been discussed and the criterion adopted for the implementation in the post-graduation in Inorganic Chemistry Program presented. A teaching plan for the new subject is proposed, based on the experience gained through a first group. An instrument for evaluation of the student's performance has been developed and analyzed. Aspects like knowledge, clearness, enthusiasm, confidence, good manage on the audio-visual resources, class length are mentioned by degree of importance and the major difficulties faced and pointed out by the students.

Aproximación al reajuste automático de centroides mediante la heurística de Lloyd para resolver el problema de las K-Medias

Peer-reviewed

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.