The field of wireless communication is under massive development and the demands on the cellular system, especially, are constantly increasing as the utilizing devices are increasing in number and diversity. A key component of wireless communication is the knowledge of the channel, i.e, how the signal is affected when sent over the wireless medium. Channel prediction is one concept which can improve current techniques or enable new ones in order to increase the performance of the cellular system. Firstly, this report will investigate the concept of a predictor antenna on new, extensive measurements which represent many different environments and scenarios. A predictor antenna is a separate antenna that is placed in front of the main antenna on the roof of a vehicle. The predictor antenna could enable good channel prediction for high velocity vehicles. The measurements show to be too noisy to be used directly in the predictor antenna concept but show potential if the measurements can be noise-filtered without distorting the signal. The use of low-pass filter and Kalman filter to do this, did not give the desired results but the technique to do this should be further investigated. Secondly, a interpolation technique will be presented which utilizes predictions with different prediction horizon by estimating intermediate channel components using interpolation. This could save channel feedback resources as well as give a better robustness to bad channel predictions by letting fresh, local, channel predictions be used as quality reference of the interpolated channel estimates. For a linear interpolation between 8-step and 18-step Kalman predictions with Normalized Mean Square Error (NMSE) of -15.02 dB and -10.88 dB, the interpolated estimates had an average NMSE of -13.14 dB, while lowering the required feedback data by about 80 %. The use of a warning algorithm reduced the NMSE by a further 0.2 dB. It mainly eliminated the largest prediction error which otherwise could lead to retransmission, which is not desired.

Ante la capacidad predictiva de la teoría de la acción planificada en diversas gamas de conducta y la necesidad de explicar el rendimiento académico, no abordado hasta el momento por dicho modelo, se planteó como objetivos construir un instrumento que mida la acción planificada hacia el estudio, así como obtener sus evidencias de validez, y determinar si la acción planificada hacia el estudio predice el rendimiento académico en estudiantes de Psicología de una universidad particular de Trujillo. El estudio fue instrumental y ex post facto retrospectivo de grupo único. La muestra no probabilística de 153 participantes, respondió a la Escala de Acción Planificada para la Dedicación al Estudio (APDE), versión retrospectiva. Se obtuvo las evidencias de validez basadas en el contenido del instrumento (V=1; p<0.05); en su dimensionalidad (4 factores que explican el 66% de la varianza de la prueba) y la fiabilidad (α ordinal= 0.77 a 0.88); sin embargo, el modelo teórico de Ajzen no explica el rendimiento académico (CFI= .947, RMSEA= .120). Se concluye que la Escala APDE posee adecuadas evidencias de validez; sin embargo al no predecir el rendimiento académico, se sugiere adicionar otras variables en modelos predictivos y efectuar investigaciones prospectivas con muestras de mayor tamaño.

The current study employed a Monte Carlo design to examine whether samplebased and formula-based estimates of cross-validated R2 differ in accuracy when predictor selection is and is not performed. Analyses were conducted on three datasets with 5, 10, or 15 predictors and different predictor-criterion relationships. Results demonstrated that, in most cases, a formula-based estimate of the cross-validated R2 was as accurate as a sample-based estimate. The one exception was the five predictor case wherein the formula-based estimate exhibited substantially greater bias than the estimate from a sample-based cross validation study. Thus, formula-based estimates, which have an enormous practical advantage over a two sample cross validation study, can be used in most cases without fear of greater error.

Artificial Neural Networks (ANNs) are powerful predictors, however, they essentially function like 'black boxes' because they lack explanatory power. Various algorithms have been developed to examine input influences and interactions thus enhancing understanding of the function being modeled. The study of facial attractiveness is one domain that could potentially benefit from ANN models. The literature shows that the relationship between attractiveness and facial attributes is complex and not yet fully understood. In this project, a feed-forward ANN was trained with backpropagation to 0.86 classification using 8-fold cross validation. The dataset consisted of 88 female facial images, each containing 17 geofacial measurements, a random noise variable, and a rating. Input 'clamping' and the Connection Weight Approach (Olden & Jackson, 2002), were implemented and the results were examined in terms of the facial attractiveness domain. In general, the results suggest that more feminized and asymmetrical features enhance facial attractiveness.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, and previous studies have focused on the epidemiology, mechanisms and risk factors for this global disease (Ryder and Benjamin 1999). Various studies have examined the mechanism, epidemiology, and risk factors for AF. One of the most common triggers for AF is believed to be premature atrial contractions (PACs) usually arising from the pulmonary veins of the left atrium, but the relationship between AF and premature ventricular complexes (PVCs) is not well understood. Studies investigating the triggers of premature beats in both the atria and ventricles are similar, so it is possible that treatment for one arrhythmia may affect the incidence of another. It is hypothesized that due to commonly shared mechanisms of triggered activity or automaticity between PACs and PVCs, and shared risk factors, that patients with AF undergoing treatment with catheter ablation may be prone to develop PVCs. OBJECTIVE: To investigate the incidence of clinically detected PVCs among patients undergoing catheter ablation for AF, and clinical predictors of PVC development in this cohort of patients. We also aim to evaluate if incident PVC detection is associated with recurrent AF following AF ablation in a cohort of 317 patients receiving treatment at a single academic medical center. METHODS: A total of 375 patients undergoing AF ablation from 2009-2012 were reviewed, and patients that underwent repeat ablations were excluded, yielding 317 patients for analysis. T-tests and Chi-squared analyses were used in univariate analyses to test for significance between characteristics of AF patients who did and did not develop PVCs. Kaplan-Meier analyses and Cox proportional hazards models were used for univariate and multivariate survival analyses, respectively, to assess the risks of incident PVC development. RESULTS: Of 317 patients with AF undergoing pulmonary vein isolation (PVI) ablation, 36.3% developed clinically detectable PVCs following ablation. A history of clinically evident PVC prior to catheter ablation for AF was associated with an 80% increase in risk of incident PVC development (HR=1.83, 95% CI 1.02-3.26, p=0.041). Additionally, a history of prior angioplasty, stent, or percutaneous coronary intervention (PCI) was associated with a 73% decreased risk of incident PVCs (HR=0.27, 95% CI 0.08-0.88, p=0.03). In patients with a history of PVC prior to ablation, or who developed PVCs after ablation, there was no significant difference in the risk of AF recurrence (HR=1.01, 95% CI 0.70-1.46, p=0.96; and HR=1.09, 95% CI 0.78-1.53, p=0.60, respectively). CONCLUSIONS: Over 1 in 3 patients develop clinically detected PVCs following catheter ablation. Predictors of incident PVC development include a history of PVC, whereas a history of angioplasty, stent, or PCI was associated with less incident PVC development. Furthermore, there was no significant association between both a history of PVC or incident PVC and risk of recurrent AF following ablation.

To improve application performance, current processors rely on prediction-based hardware optimizations, such as data prefetching and branch prediction. These hardware optimizations store application metadata in on-chip predictor tables and use the metadata to anticipate and optimize for future application behavior. As application footprints grow, the predictor tables need to scale for predictors to remain effective. One important challenge in processor design is to decide which hardware optimizations to implement and how much resources to dedicate to a specific optimization. Traditionally, processor architects employ a one-size-fits-all approach when designing predictor-based hardware optimizations: for each optimization, a fixed portion of the on-chip resources is allocated to the predictor storage. This approach often leads to sub-optimal designs where: 1) resources are wasted for applications that do not benefit from a particular predictor or require only small predictor tables, or 2) predictors under-perform for applications that need larger predictor tables that can not be built due to area-latency-power constraints. This thesis introduces Predictor Virtualization (PV), a framework that uses the traditional processor memory hierarchy to store application metadata used in speculative hardware optimizations. This allows to emulate large, more accurate predictor tables, which, in return, leads to higher application performance. PV exploits the current trend of unprecedentedly large on- chip secondary caches and allocates on demand a small portion of the cache capacity to store application metadata used in hardware optimizations, adjusting to the application’s need for predictor resources. As a consequence, PV is a pay-as-you-go technique that emulates large predictor tables without increasing the dedicated storage overhead. To demonstrate the benefits of virtualizing hardware predictors, we present virtualized designs for three different hardware optimizations: a state-of-the-art data prefetcher, conventional branch target buffers and an object-pointer prefetcher. While each of these hardware predictors exhibit different characteristics that lead to different virtualized designs, virtualization improves the cost-performance trade-off for all these optimizations. PV increases the utility of traditional processor caches: in addition to being accelerators for slow off-chip memories, on-chip caches are leveraged for increasing the effectiveness of predictor-based hardware optimizations.

To improve application performance, current processors rely on prediction-based hardware optimizations, such as data prefetching and branch prediction. These hardware optimizations store application metadata in on-chip predictor tables and use the metadata to anticipate and optimize for future application behavior. As application footprints grow, the predictor tables need to scale for predictors to remain effective. One important challenge in processor design is to decide which hardware optimizations to implement and how much resources to dedicate to a specific optimization. Traditionally, processor architects employ a one-size-fits-all approach when designing predictor-based hardware optimizations: for each optimization, a fixed portion of the on-chip resources is allocated to the predictor storage. This approach often leads to sub-optimal designs where: 1) resources are wasted for applications that do not benefit from a particular predictor or require only small predictor tables, or 2) predictors under-perform for applications that need larger predictor tables that can not be built due to area-latency-power constraints. This thesis introduces Predictor Virtualization (PV), a framework that uses the traditional processor memory hierarchy to store application metadata used in speculative hardware optimizations. This allows to emulate large, more accurate predictor tables, which, in return, leads to higher application performance. PV exploits the current trend of unprecedentedly large on- chip secondary caches and allocates on demand a small portion of the cache capacity to store application metadata used in hardware optimizations, adjusting to the application’s need for predictor resources. As a consequence, PV is a pay-as-you-go technique that emulates large predictor tables without increasing the dedicated storage overhead. To demonstrate the benefits of virtualizing hardware predictors, we present virtualized designs for three different hardware optimizations: a state-of-the-art data prefetcher, conventional branch target buffers and an object-pointer prefetcher. While each of these hardware predictors exhibit different characteristics that lead to different virtualized designs, virtualization improves the cost-performance trade-off for all these optimizations. PV increases the utility of traditional processor caches: in addition to being accelerators for slow off-chip memories, on-chip caches are leveraged for increasing the effectiveness of predictor-based hardware optimizations.

By using a conceptual framework derived from social exchange theory, this study examined the relationship between financial problems and divorce. Nationally representative data from the " Marital Instability Over the Life Course" panel study was used to determine if financial problems reported at one interview could predict those who would divorce by the subsequent interview. A self-replicating design allowed data analyses for three separate time periods: 1980-1983 , 1983- 1988, and 1988-1992. The sample used in this study consisted of l,620 married men and women under the age of 55. Additionally, the participants were in their first marriages. Divorce was the only dependent variable. The independent variables inc luded eight financial problems: (a) husband's job interferes with family life, (b) husband 's job satisfaction, (c) wife's job satisfaction, (d) wife's work preference, (e) sat isfaction with spouse as breadwinner, (f) satisfaction with financial situation, (g) spending money

OBJECTIU: Avaluar el paper del DC en l'aparició de demència a una població de pacients majors de 64 anys, procedents de 54 equips d'Atenció Primària de salut d'arreu del territori català als 3 anys i mig de seguiment, segons presència prèvia o absència de DC. Avaluar també si existeix una associació entre la mortalitat, la institucionalització, la inclusió en el programa ATDOM, la comorbiditat (AVC, IAM, arteriopatia perifèrica) i el consum de recursos dels pacients en relació a la presència o absència de DC DISSENY: Estudi de cohorts retrospectiuÀMBIT: 54 Equips d'Atenció Primària d'arreu de CatalunyaSUBJECTES: 712 pacients dividits en dues cohorts segons presència o absència de DCMEDICIONS. Variables resultat (aparició d'events- demència, èxitus, institucionalització, inclussió al programa ATDOM, AVC incident i temps fins aquesta aparició-) i nombre de visites a professionals. Variables explicatives : DC, edat, sexe, màxim nivell d'estudis, CAP, FRCV (HTA, DM, DL), patologia càrdiovascular prèvia (IAM, AVC, AP), patologies relacionades amb demència (acxfa, hipotiroidisme), altres patologies cròniques.Anàlisi de supervivència (associació entre factors predictors: Hazard Ratio; distribució del temps fins a l'esdeveniment segons DC corbes de supervivència de Kaplan-Maier ; associació entre DC i el temps fins a cada esdeveniment, model de regressió de riscos proporcionals de Cox o model estès de Cox). Nivell de significació: 5%; paquet estadístic Stata/Se versió 9.1Resultats: Presenten demència 72 individus, 66 del grup de deteriorats i 6 del grup de no deteriorats (Chi quadrat 66,47; P<0,000). Densitat d'incidència global de demència: 38,14 (IC 95%: 30,27-48,05) per 1000 persones-any. La presència de DC (HR que varia en el temps; 3,53 als 4 anys de seguiment) i l'edat (HR 2,59; IC 95%1,62-4,14 i P<0,001 per majors de 80 anys) expliquen l'aparició de demència. Per la resta de variables, els models són els següents. Èxitus: DC, l'edat, la comorbiditat, l'ingrés al programa ATDOM i el fet de patir un AVC ; Institucionalització: DC, l'ingrés al programa ATDOM, el fet de patir un AVC i el fet de patir demència;ATDOM: DC, l'edat, el fet de patir un AVC i el fet de no tenir DL. AVC: edat i la DM. No influeixen la HTA ni la DL ni el DC. La comorbiditat i el seguiment de la HTA expliquen la càrrega assistencial dels metges. El seguiment de la HTA, el seguiment de la DM i el sexe masculí expliquen la càrrega assistencial de les infermeres. Ni el DC ni la demència influeixen en la càrrega assistencialCONCLUSIONS: el DC és un predictor de la incidència de demència (HR varia en el temps), èxitus (HR=1,86), institucionalització (HR=4,99) i ATDOM (HR=1,87). No hem pogut demostrar que tingui aquest paper en el cas de la incidència d'AVC ni en el consum de recursos sanitaris. / "Study of the freqüency of cognitive impairment (CI) in Catalonia and prediction role of cognitive impairment. First Phase of Cuida'l study"TEXT:OBJECTIVE. To know the role of CI in dementia appearance in a population of people older than 64 years, from 54 Primary Care teams all arround Catalonia according to presence or absence of CI. DESIGN: Retrospective cohort studySETTING: Primary Care PARTICIPANTS: 712 patients divided into two cohorts according to presence or absence of CI. MEASUREMENTS: Result Variables: Dementia, death, institutionalisation, home care, stroke and times until these events. Number of visits to physician and nurse. Explicative variables: CI, age, sex, educational level, primary care team, cardiovascular risk factors, previous cardiovascular diseases, diseases related to dementia, and other chronic diseasesSurvival analysis. Signification level 5%. Statistical software: Stata 9.1.MAIN RESULTS: 72 patients adquired dementia (66 with previous CI, 6 without (Chi quadrat 66,47; P<0,000). Global density of incidence of dementia: 38,14 (CI 95%: 30,27-48,05) 1000 persons-year. The presence of CI (HR time-changing: 3,53 at 4 years of follow-up) and age HR 2,59; CI 95%1,62-4,14 and P<0,001 for older than 80 years explain the diagnosis of dementia). CI is explains mortality, institutionalisation, and home care. But has no role on stroke and sanitary services use.CONCLUSIONS: CI has a role on dementia (HR time-changing), death (HR=1,86), institutionalisation (HR=4,99) and home care (HR=1,87).KEY WORDS: Cognitive impairment, prediction role, dementia, primary care

Abstract The aim of this study was to explore the prognosis and predictors of outcomes in DSM-III-R schizophrenic psychoses within the Northern Finland 1966 Birth Cohort (NFBC 1966, N = 12 017). Firstly, clinical and social outcomes were explored by using different definitions of good and poor outcomes, and early developmental, socio-demographic, illness-related and school-related predictors of outcome in schizophrenia (N = 59) were studied. Secondly, associations between early motor development and the course of illness in schizophrenia (N = 109) were explored. Thirdly, patterns of psychiatric hospitalisations in schizophrenic psychoses (N = 115) were studied. Fourthly, recovery in schizophrenia (N = 59) and other schizophrenia spectrum psychoses (N = 12) was assessed. As a result, good clinical outcome varied from 10% to 59%, and good social outcome 15–46%, depending on definition. Poor clinical outcome varied 41–77% and poor social outcome 37–54%. Lack of friends in childhood, father's high social class, lower school performance and earlier age of illness onset predicted poor outcomes. There were some associations between development and learning of basic skills at about age 1 and subsequent illness course. Those who learnt later (within normal limits) had mostly better outcomes, compared to early learners. A total of 81% of patients with schizophrenic psychoses were re-hospitalised during the follow-up and short first hospitalisation and family history of psychosis were linked to increased risk of re-hospitalisations. One (1.7%) schizophrenia subject and three (25%) subjects with other schizophrenia spectrum disorder recovered fully; one (1.7%) schizophrenia subject and two (16.7%) spectrum subjects experienced partial recovery after several years of follow-up. In this dissertation study outcomes and some predictors were analysed in a population-based sample of individuals with relatively young age and short duration of illness. In general, both clinical and social outcomes were heterogeneous and relatively poor, and the results were influenced by the definitions of outcomes. Persons having a sub-optimal developmental trajectory with family history of psychosis, poor social contacts, poor school performance, and early age of illness onset and those with short first hospitalisation seem to have the worst outcome. In addition, the neuromotor development of these individuals is complex and late development does not associate clearly with poor outcome of illness. The results of this study indicate that the outcome of schizophrenic psychoses is not good enough and that more effective treatments and rehabilitation for schizophrenia patients are needed. Also, there is a need for structured criteria for good and poor outcome and recovery in schizophrenia. / Tiivistelmä Tämän tutkimuksen tavoitteena oli tutkia DSM-III-R skitsofrenian ja muiden skitsofrenian kaltaisten psykoosien taudinkulkua ja ennustetta sekä niihin liittyviä tekijöitä Pohjois-Suomen vuoden 1966 syntymäkohortissa. Ensimmäiseksi tutkimuksessa selvitettiin skitsofrenian (N = 59) taudinkulkua ja sitä ennustavia sosio-demografisia ja kehitykseen, sairauteen ja koulumenestykseen liittyviä tekijöitä. Toiseksi, tutkittiin varhaislapsuuden kehityksen ja skitsofreenisten psykoosien (N = 109) taudinkulun välistä yhteyttä. Kolmanneksi, skitsofreenista psykoosia sairastavien henkilöiden (N = 115) psykiatrisia sairaalahoitoja ja niihin liittyviä tekijöitä tutkittiin. Neljänneksi tutkimuksessa selvitettiin skitsofreniasta (N = 59) ja muista skitsofreniaspektrin psykooseista (N = 12) toipumista. Tässä tutkimuksessa 10–59 % potilaista voi kliinisesti hyvin ja 15–46 % sosiaalisesti hyvin kun taas 41–77 % voi kliinisesti ja 37–54 % sosiaalisesti huonosti. Tulokset riippuivat paljolti siitä, mitä hyvän ja huonon taudinkulun kriteereitä käytettiin. Lapsuudessa ystävien puute, isän korkea sosiaaliluokka, huono koulumenestys ja taudin varhainen alkamisikä liittyivät huonoon taudinkulkuun. Aineistosta löydettiin yhteys (normaalirajoissa olevan) myöhäisemmän kehityksen ja hyvän taudinkulun välillä. Seurannassa 81 % potilaista joutui ensimmäisen sairaalahoidon jälkeen uudelleen sairaalaan. Lyhyt ensimmäinen sairaalahoito ja suvussa esiintyvä psykoosi liittyivät kohonneeseen riskiin joutua uudelleen sairaalaan. Skitsofreniapotilaista yksi (1.7 %) oli täysin ja yksi (1.7 %) osittain toipunut. Muista skitsofreniaspektrin potilaista kolme (25 %) oli täysin ja kaksi (16.7 %) osittain toipuneita usean vuoden seurannan jälkeen. Tässä tutkimuksessa selvitettiin skitsofrenian taudinkulkua ja analysoitiin taudinkulkuun vaikuttavia tekijöitä yleisväestöön pohjautuvassa aineistossa. Tulosten mukaan skitsofreniaa sairastavien henkilöiden sosiaalinen ja kliininen taudinkulku oli vaihteleva ja enimmäkseen suhteellisen huono. Tulokset riippuivat paljon siitä, millaisia hyvän ja huonon taudinkulun kriteereitä käytettiin. Henkilöillä, joilla on suvussa psykooseja, varhainen sairastumisikä, joilla on ollut huono koulumenestys ja vähäisiä sosiaalisia kontakteja lapsuudessa, ja joilla on ollut lyhyt ensimmäinen sairaalahoito, sairauden kulku on usein huono. Skitsofreniaa sairastavien henkilöiden viivästynyt varhainen motorinen kehitys ei ole yksiselitteisesti yhteydessä huonoon taudinkulkuun. Tämän tutkimuksen tulosten perusteella skitsofrenian ennuste ei ole yleensä hyvä. Yhteiskunnan tulisi entistä enemmän panostaa skitsofreniapotilaiden kokonaisvaltaiseen hoitoon ja kuntouttamiseen. Aiemman kirjallisuuden ja tämän tutkimuksen tulosten perusteella on myös selkeä tarve yhdenmukaisille ja strukturoiduille hyvän ja huonon ennusteen ja toipumisen kriteereille skitsofreniassa.