Wind ensamble forecasting using an adaptive mass-consistent model

[EN]Ensemble forecasting [1] is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in [2]. The wind _eld forecasting is based on a mass-consistent model and a log-linear wind pro_le using as input data the resulting forecast wind from Harmonie [3], a Non-Hydrostatic Dynamic model. The mass-consistent model parameters are estimated by using genetic algorithms [4]. The mesh is generated using the meccano method [5] and adapted to the geometry. The main source of uncertainties in this model is the parameter estimation and the in- trinsic uncertainties of the Harmonie Model…

Ensemble wind forecasting based on the HARMONIE model and adaptive finite elements in complex orography

[EN]Ensemble forecasting is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in. The wind field forecasting is based on a mass-consistent model and a log-linear wind profile using as input data the resulting forecast wind from Harmonie, a Non-Hydrostatic Dynamic model used experimentally at AEMET with promising results. The mass-consistent model parameters are estimated by using genetic algorithms. The mesh is generated using the meccano method and adapted to the geometry…

Der Austausch von Stickstoffmonoxid zwischen Boden und Atmosphäre unter besonderer Berücksichtigung des Bodenwassergehaltes

Stickstoffmonoxid (NO) ist als reaktives Spurengas eine wichtige Komponente atmosphärenchemischer Prozesse und hat somit einen bedeutenden Einfluss auf die Zusammensetzung der Atmosphäre. Eine Hauptquelle des Spurengases stellen bodenmikrobiologische Prozesse dar, deren regionaler und globaler Anteil weiterhin mit größeren Unsicherheiten geschätzt wird. Ursache für die schwere Abschätzbarkeit der NO-Freisetzung aus Böden ist die hohe räumliche Variabilität der steuernden Faktoren. Als einer der wichtigsten Faktoren, die die Freisetzung von NO aus Böden regeln, gilt der Bodenwassergehalt. Ziel der vorliegenden Arbeit ist es, den Zusammenhang zwischen NO-Freisetzung, Bodenwassergehalt, den Bodeneigenschaften und den Standortbedingungen zu untersuchen und diesen möglichst zu quantifizieren. Dazu sind Bodenproben unterschiedlicher Landnutzungen in einem kleineren Wassereinzugsgebiet im Rheingau im Labor, unter kontrollierten Bedingungen, untersucht. Der charakteristische Zusammenhang zwischen Bodenfeuchte und NO-Freisetzung, die sogenannte Bodenfeuchtekurve, kann demnach weitestgehend auf die gemessenen Bodenmerkmale der untersuchten Proben zurückgeführt werden. Anhand der Bodenmerkmale kann die Bodenfeuchtekurve zufriedenstellend vorhergesagt werden. Dabei zeigt vor allem der Humusgehalt der Böden einen dominierenden Einfluss. Er ist die Variable, die die Unterschiede der Böden beim Zusammenhang zwischen Bodenfeuchte und NO-Freisetzung am besten und hinreichend erklären kann. Zur Konstruktion der Bodenfeuchtekurve müssen die optimale Bodenfeuchte und die dabei herrschende Freisetzung, sowie die obere Bodenfeuchte, bei der keine NO-Freisetzung mehr stattfindet, bekannt sein. Diese charakteristischen Punkte lassen sich durch lineare Regressionsmodelle gut aus den Bodeneigenschaften ableiten. Auf räumlicher Ebene werden die Bodeneigenschaften durch die standörtlichen Bedingungen geprägt, die wiederum Ausdruck der landschaftlichen Ausstattung sind. In der Kulturlandschaft kann der Mensch aufgrund seiner Landnutzungsansprüche als der dominierende Faktor angesehen werden. Die Landnutzung orientiert sich an den landschaftlichen Bedingungen und bestimmt in hohem Maße wichtige Bodeneigenschaften, die zu den erklärenden Merkmalen bei der Beziehung zwischen Bodenwassergehalt und NO-Freisetzung gehören. Die in erster Linie wirtschaftlich orientierten Kartenwerke Bodenschätzung, Weinbergsbodenkartierung und forstliche Standortkartierung sind dementsprechend geeignete Grundlagen, um eine Regionalisierung der Landschaft in - bezüglich der NO-Freisetzung - weitgehend homogene Flächen durchführen zu können. Eine hierauf beruhende Regionalisierung ist dazu geeignet, die räumliche Variabilität der NO-Freisetzung in räumlich sinnvoller Auflösung besser abschätzen zu können.

Essays in Applied and Labor Economics

This thesis consists of three self-contained papers. In the first paper I analyze the labor supply behavior of Bologna Pizza Delivery Vendors. Recent influential papers analyze labor supply behavior of taxi drivers (Camerer et al., 1997; and Crawford and Meng, 2011) and suggest that reference-dependence preferences have an important influence on drivers’ labor-supply decisions. Unlike previous papers, I am able to identify an exogenous and transitory change in labor demand. Using high frequency data on orders and rainfall as an exogenous demand shifter, I invariably find that reference-dependent preferences play no role in their labor’ supply decisions and the behavior of pizza vendors is perfectly consistent with the predictions of the standard model of labor’ supply. In the second paper, I investigate how the voting behavior of Members of Parliament is influenced by the Members seating nearby. By exploiting the random seating arrangements in the Icelandic Parliament, I show that being seated next to Members of a different party increases the probability of not being aligned with one’s own party. Using the exact spatial orientation of the peers, I provide evidence that supports the hypothesis that interaction is the main channel that explain these results. In the third paper, I provide an estimate of the trade flows that there would have been between the UK and Europe if the UK had joined the Euro. As an alternative approach to the standard log-linear gravity equation I employ the synthetic control method. I show that the aggregate trade flows between Britain and Europe would have been 13% higher if the UK had adopted the Euro.

Distribuzione spazio temporale dei pesci demersali sulla piattaforma continentale del Golfo di Antalya

Le variabili ambientali e lo sfruttamento della pesca sono dei possibili fattori nel determinare la struttura della comunità demersale. L’area di studio è il Golfo di Antalya, con un area aperta ed una chiusa ad ogni attività di pesca, il periodo di studio ha coperto tre stagioni (primavera, estate, autunno). Lo scopo è quello di delineare un quadro generale sulla distribuzione spaziale e temporale delle risorse alieutiche demersali in quest’area. In questo lavoro di tesi la PCA è stata usata al fine di determinare le variabili ambientali (ossigeno, salinità, temperatura, pH, materia sospesa) che determinano maggiormente la differenza tra le stazioni, tecniche di analisi multivariata hanno invece indagato una possibile variazione su scala spaziale e temporale dei parametri abiotici. La Cluster Analysis effettuata sui dati di abbondanza ha delineato quattro raggruppamenti principali, due ad una profondità minore di 100 m e due ad una profondità maggiore (40% di similarità). Questi risultati sono confermati dall’analisi MDS. L’analisi SIMPER ha messo in evidenza le specie che maggiormente incidono sulla differenza tra strati di profondità. Gli indici di biodiversità sono stati calcolati per indagare la diversità e la variabilità temporale e spaziale della comunità demersale. Due procedure la BIO-ENV e la DistLM (Distance-based linear models) sono state effettuate per individuare le variabili abiotiche che potrebbero essere responsabili dei diversi raggruppamenti nella struttura del popolamento demersale. Le specie commerciali: Mullus barbatus, Upeneus moluccensis, Upeneus pori sono state prese come oggetto per la ricerca di possibili effetti della pesca a livello di popolazione. Per i dati di abbondanza e di biomassa di queste specie è stata eseguita l’analisi multivariata MANOVA (Multivariate Analysis of Variance) al fine di trovare eventuali variazioni dovute ai fattori profondità, stagione e transetto. Per ogni specie è stata valutata la sex ratio. Il metodo Bhattacharya ha permesso di determinare le classi di età e la loro abbondanza. In ultimo la relazione peso-lunghezza è stata ricavata separatamente per gli individui maschi e femmine al fine di determinare il tipo di crescita per ogni sesso.

Mining tissue microarray data to uncover combinations of biomarker expression patterns that improve intermediate staging and grading of clear cell renal cell cancer

PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.

Abnormal bone geometry at the metacarpal bone shaft of rheumatoid arthritis patients with maintained muscle-bone relationship

OBJECTIVES:: Metacarpal juxta-articular bone is altered in Rheumatoid Arthritis (RA). However, a detailed analysis of disease related geometrical adaptations of the metacarpal shaft is missing. The aim of the present study was to assess the role of RA disease, forearm muscle cross-sectional area (CSA), age and sex on bone geometry at the metacarpal shaft. METHODS:: In 64 RA patients and 128 control subjects geometric properties of the third metacarpal bone mid-shaft and forearm muscle CSA were measured by peripheral quantitative computed tomography (pQCT). Linear models were performed for cortical CSA, total bone CSA, polar stress-strain Index (polar SSI, a surrogate for bone's resistance to bending and torsion), cortical thickness and Metacarpal Index (MI=cortical CSA/total CSA) with explanatory variables muscle CSA, age, RA status and sex. RESULTS:: Forearm muscle CSA was associated with cortical and total metacarpal CSA, and polar SSI. RA group status was associated with all bone parameters except cortical CSA. There was a significant interaction between RA status and age, indicating that the RA group had a greater age-related decrease in cortical CSA, cortical thickness and MI. CONCLUSIONS:: Bone geometry of the metacarpal shaft is altered in RA patients compared to healthy controls. While bone mass of the metacarpal shaft is adapted to forearm muscle mass, cortical thickness and MI are reduced but outer bone shaft circumference and polar SSI increased in RA patients. These adaptations correspond to an enhanced aging pattern in RA patients.

A prediction model for assessing residential radon concentration in Switzerland

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.

Concomitant Vascular Reconstruction During Pancreatectomy for Malignant Disease: A Propensity Score-Adjusted, Population-Based Trend Analysis Involving 10 206 Patients

OBJECTIVE To assess trends in the frequency of concomitant vascular reconstructions (VRs) from 2000 through 2009 among patients who underwent pancreatectomy, as well as to compare the short-term outcomes between patients who underwent pancreatic resection with and without VR. DESIGN Single-center series have been conducted to evaluate the short-term and long-term outcomes of VR during pancreatic resection. However, its effectiveness from a population-based perspective is still unknown. Unadjusted, multivariable, and propensity score-adjusted generalized linear models were performed. SETTING Nationwide Inpatient Sample from 2000 through 2009. PATIENTS A total of 10 206 patients were involved. MAIN OUTCOME MEASURES Incidence of VR during pancreatic resection, perioperative in-hospital complications, and length of hospital stay. RESULTS Overall, 10 206 patients were included in this analysis. Of these, 412 patients (4.0%) underwent VR, with the rate increasing from 0.7% in 2000 to 6.0% in 2009 (P < .001). Patients who underwent pancreatic resection with VR were at a higher risk for intraoperative (propensity score-adjusted odds ratio, 1.94; P = .001) and postoperative (propensity score-adjusted odds ratio, 1.36; P = .008) complications, while the mortality and median length of hospital stay were similar to those of patients without VR. Among the 25% of hospitals with the highest surgical volume, patients who underwent pancreatic surgery with VR had significantly higher rates of postoperative complications and mortality than patients without VR. CONCLUSIONS The frequency of VR during pancreatic surgery is increasing in the United States. In contrast with most single-center analyses, this population-based study demonstrated that patients who underwent VR during pancreatic surgery had higher rates of adverse postoperative outcomes than their counterparts who underwent pancreatic resection only. Prospective studies incorporating long-term outcomes are warranted to further define which patients benefit from VR.

Associations between prion protein genotype and type traits in East Friesian milk sheep

Linear models were used to analyse the relationships between the prion protein genotypes and the height at the withers and rump, the heart girth and the length of the trunk of 440 East Friesian milk sheep. Significant associations were found between the ARR allele and the height of the withers and rump, and heart girth. The average height at the withers of the homozygous ARR/ARR sheep was 1.9 cm less than that of ARQ/ARQ sheep and 1.6 cm less than in sheep heterozygous for ARR; the height at the rump, length of the trunk and heart girth were similarly smaller. In the ARR/ARR ewes, the average height at the withers was 2.6 cm less and the height at the rump was 1.9 cm less than in the ARQ/ARQ ewes.

A multi-level decomposition of variance in somatic symptom reporting in families with adolescent children

OBJECTIVES: This paper examines four different levels of possible variation in symptom reporting: occasion, day, person and family. DESIGN: In order to rule out effects of retrospection, concurrent symptom reporting was assessed prospectively using a computer-assisted self-report method. METHODS: A decomposition of variance in symptom reporting was conducted using diary data from families with adolescent children. We used palmtop computers to assess concurrent somatic complaints from parents and children six times a day for seven consecutive days. In two separate studies, 314 and 254 participants from 96 and 77 families, respectively, participated. A generalized multilevel linear models approach was used to analyze the data. Symptom reports were modelled using a logistic response function, and random effects were allowed at the family, person and day level, with extra-binomial variation allowed for on the occasion level. RESULTS: Substantial variability was observed at the person, day and occasion level but not at the family level. CONCLUSIONS: To explain symptom reporting in normally healthy individuals, situational as well as person characteristics should be taken into account. Family characteristics, however, would not help to clarify symptom reporting in all family members.

Whither PQL?

Generalized linear mixed models (GLMM) are generalized linear models with normally distributed random effects in the linear predictor. Penalized quasi-likelihood (PQL), an approximate method of inference in GLMMs, involves repeated fitting of linear mixed models with “working” dependent variables and iterative weights that depend on parameter estimates from the previous cycle of iteration. The generality of PQL, and its implementation in commercially available software, has encouraged the application of GLMMs in many scientific fields. Caution is needed, however, since PQL may sometimes yield badly biased estimates of variance components, especially with binary outcomes. Recent developments in numerical integration, including adaptive Gaussian quadrature, higher order Laplace expansions, stochastic integration and Markov chain Monte Carlo (MCMC) algorithms, provide attractive alternatives to PQL for approximate likelihood inference in GLMMs. Analyses of some well known datasets, and simulations based on these analyses, suggest that PQL still performs remarkably well in comparison with more elaborate procedures in many practical situations. Adaptive Gaussian quadrature is a viable alternative for nested designs where the numerical integration is limited to a small number of dimensions. Higher order Laplace approximations hold the promise of accurate inference more generally. MCMC is likely the method of choice for the most complex problems that involve high dimensional integrals.

PENALIZED FUNCTIONAL REGRESSION

We develop fast fitting methods for generalized functional linear models. An undersmooth of the functional predictor is obtained by projecting on a large number of smooth eigenvectors and the coefficient function is estimated using penalized spline regression. Our method can be applied to many functional data designs including functions measured with and without error, sparsely or densely sampled. The methods also extend to the case of multiple functional predictors or functional predictors with a natural multilevel structure. Our approach can be implemented using standard mixed effects software and is computationally fast. Our methodology is motivated by a diffusion tensor imaging (DTI) study. The aim of this study is to analyze differences between various cerebral white matter tract property measurements of multiple sclerosis (MS) patients and controls. While the statistical developments proposed here were motivated by the DTI study, the methodology is designed and presented in generality and is applicable to many other areas of scientific research. An online appendix provides R implementations of all simulations.

Hospital use of young children in Switzerland: a nation-wide study based on a complete survey over 4 years

Background Young children are known to be the most frequent hospital users compared to older children and young adults. Therefore, they are an important population from economic and policy perspectives of health care delivery. In Switzerland complete hospitalization discharge records for children [<5 years] of four consecutive years [2002–2005] were evaluated in order to analyze variation in patterns of hospital use. Methods Stationary and outpatient hospitalization rates on aggregated ZIP code level were calculated based on census data provided by the Swiss federal statistical office (BfS). Thirty-seven hospital service areas for children [HSAP] were created with the method of "small area analysis", reflecting user-based health markets. Descriptive statistics and general linear models were applied to analyze the data. Results The mean stationary hospitalization rate over four years was 66.1 discharges per 1000 children. Hospitalizations for respiratory problem are most dominant in young children (25.9%) and highest hospitalization rates are associated with geographical factors of urban areas and specific language regions. Statistical models yielded significant effect estimates for these factors and a significant association between ambulatory/outpatient and stationary hospitalization rates. Conclusion The utilization-based approach, using HSAP as spatial representation of user-based health markets, is a valid instrument and allows assessing the supply and demand of children's health care services. The study provides for the first time estimates for several factors associated with the large variation in the utilization and provision of paediatric health care resources in Switzerland.

Coagulation activity before and after acute psychosocial stress increases with age

OBJECTIVE: To assess whether stress further increases hypercoagulation in older individuals. We investigated whether acute stress-induced changes in coagulation parameters differ with age. It is known that hypercoagulation occurs in response to acute stress and that a shift in hemostasis toward a hypercoagulability state occurs with age. However, it is not yet known whether acute stress further increases hypercoagulation in older individuals, and thus may increase their risk for cardiovascular disease (CVD). METHODS: A total of 63 medication-free nonsmoking men, aged between 20 and 65 years (mean +/- standard error of the mean = 36.7 +/- 1.7 years), underwent an acute standardized psychosocial stress task combining public speaking and mental arithmetic in front of an audience. We measured plasma clotting factor VII activity (FVII:C), fibrinogen, and D-dimer at rest, immediately, and 20 minutes after stress. RESULTS: Increased age predicted greater increases in fibrinogen (beta = 0.26, p = 0.041; DeltaR(2) = 0.05), FVII:C (beta = 0.40, p = .006; DeltaR(2) = 0.11), and D-dimer (beta = 0.51, p < .001; DeltaR(2) = 0.18) from rest to 20 minutes after stress independent of body mass index and mean arterial blood pressure. General linear models revealed significant effects of age and stress on fibrinogen, FVII:C, and D-dimer (main effects: p < .04), and greater D-dimer stress reactivity with older age (interaction age-by-stress: F(1.5/90.4) = 4.36, p = .024; f = 0.33). CONCLUSIONS: Our results suggest that acute stress might increase vulnerability in the elderly for hypercoagulability and subsequent hemostasis-associated diseases like CVD.