Sweden is known for being at the forefront of becoming a cashless society.However, cash continues to be an important part of the payment ecosystem butthere are limited studies and data regarding the preference for holding cash. Previousstudies have shown that the use of cash is declining with regards to comers and thatthere are behavior differences between cultures and sociodemographic groups inregards to characteristics and preferences for payment methods. The aim of thisstudy was to investigate the informational attributes that drives the preference forholding cash by studying two extreme cases, Sweden which is a pioneer of cashlesssociety, and Germany which is one of the most conservative cash-intensivecountries in the Western world. Primary quantitative data was derived fromstandardized questionnaires issued in both countries by Loomis AB; the data wasdescribed and analyzed with applicable statistical procedures. A multivariate analysiswas performed on a specific segment of the collected data were the respondents hadbeen asked to rate cash associated statements based on their agreeableness towardsthem. These segments were then examined through a Principal component analysisto determine the underlying dimensions regarding preferences for cash. Our resultssuggest that Germans withdrew cash more frequently, from a wider spectrum ofdenominations and carried it to a larger extend than Swedes. Swedes made limitedwithdrawals, of small denominations and preferred to carry smaller amounts of cash.The results also show that there were differences in the perception and preferencesfor cash between sociodemographic groups, with e.g. older age groups being used to itand the youngest using it due to ‘status quo bias’. The main conclusions include thatthe informational attributes such as security, anonymity, ease of use and paymentinfrastructure was the main drives for the preferences of holding cash. / Sverige är känt för att vara i framkanten gällande transformationen till att bli ettkontantlöst samhälle. Kontanter fortsätter dock att vara en viktig del avbetalningsekosystemet, men det finns begränsade studier och data om preferensenför att hålla kontanter. Tidigare studier har visat att användningen av kontanterminskat i dagligvaru- och sällanköpshandeln och att det finns beteendeskillnadermellan kulturer och sociodemografiska grupper med avseende på egenskaper ochpreferenser för betalningsmetoder. Syftet med denna studie var att undersöka deinformativa attribut som driver preferensen för att hålla pengar genom att studeratvå extrema fall, Sverige som är en pionjär gällande det kontantlösa samhället ochTyskland som är ett av de mest konservativa kontantanvändande länderna ivästvärlden. Kvantitativa data härleddes från standardiserade frågeformulärutfärdade i de båda länderna av Loomis AB; data beskrevs och analyserades medtillämpliga statistiska förfaranden, mer specifikt en multivariantanalys som gjordespå ett visst segment av de insamlade uppgifterna, där de svarande blev ombedda attbedöma kontantanvändningen genom associerade uttalanden baserat på derasöverensstämmelse med dem. Dessa segment undersöktes sedan genom enhuvudkomponentanalys för att bestämma de underliggande dimensionerna gällandepreferenser för kontanter. Våra resultat tyder på att tyskar tar ut pengar merfrekvent, från ett bredare spektrum av valörer och bär i större utsträckning merkontanter än svenskar. Svenskar har en begränsad uttagsfrekvens, främst av småvalörer samt att de föredrar att bära kontanter i en liten utsträckning. Fortsatt visarResultaten att det fanns skillnader i perception och preferenser för kontanter mellansociodemografiska grupper, exempelvis är äldre åldersgrupper vana vidkontantanvändning och att de yngre åldersgrupperna använder kontanter på grundav "status quo bias". De viktigaste slutsatserna är att de informativa attribut somsäkerhet, anonymitet, användarvänlighet och betalningsinfrastruktur är de viktigastedrivkrafterna gällande preferensen att hålla kontanter.

Recently, Attention Deficit Hyperactive Disorder (ADHD) is getting a lot of attention mainly for two reasons. First, it is one of the most commonly found childhood behavioral disorders. Around 5-10% of the children all over the world are diagnosed with ADHD. Second, the root cause of the problem is still unknown and therefore no biological measure exists to diagnose ADHD. Instead, doctors need to diagnose it based on the clinical symptoms, such as inattention, impulsivity and hyperactivity, which are all subjective. Functional Magnetic Resonance Imaging (fMRI) data has become a popular tool to understand the functioning of the brain such as identifying the brain regions responsible for different cognitive tasks or analyzing the statistical differences of the brain functioning between the diseased and control subjects. ADHD is also being studied using the fMRI data. In this dissertation we aim to solve the problem of automatic diagnosis of the ADHD subjects using their resting state fMRI (rs-fMRI) data. As a core step of our approach, we model the functions of a brain as a connectivity network, which is expected to capture the information about how synchronous different brain regions are in terms of their functional activities. The network is constructed by representing different brain regions as the nodes where any two nodes of the network are connected by an edge if the correlation of the activity patterns of the two nodes is higher than some threshold. The brain regions, represented as the nodes of the network, can be selected at different granularities e.g. single voxels or cluster of functionally homogeneous voxels. The topological differences of the constructed networks of the ADHD and control group of subjects are then exploited in the classification approach. We have developed a simple method employing the Bag-of-Words (BoW) framework for the classification of the ADHD subjects. We represent each node in the network by a 4-D feature vector: node degree and 3-D location. The 4-D vectors of all the network nodes of the training data are then grouped in a number of clusters using K-means; where each such cluster is termed as a word. Finally, each subject is represented by a histogram (bag) of such words. The Support Vector Machine (SVM) classifier is used for the detection of the ADHD subjects using their histogram representation. The method is able to achieve 64% classification accuracy. The above simple approach has several shortcomings. First, there is a loss of spatial information while constructing the histogram because it only counts the occurrences of words ignoring the spatial positions. Second, features from the whole brain are used for classification, but some of the brain regions may not contain any useful information and may only increase the feature dimensions and noise of the system. Third, in our study we used only one network feature, the degree of a node which measures the connectivity of the node, while other complex network features may be useful for solving the proposed problem. In order to address the above shortcomings, we hypothesize that only a subset of the nodes of the network possesses important information for the classification of the ADHD subjects. To identify the important nodes of the network we have developed a novel algorithm. The algorithm generates different random subset of nodes each time extracting the features from a subset to compute the feature vector and perform classification. The subsets are then ranked based on the classification accuracy and the occurrences of each node in the top ranked subsets are measured. Our algorithm selects the highly occurring nodes for the final classification. Furthermore, along with the node degree, we employ three more node features: network cycles, the varying distance degree and the edge weight sum. We concatenate the features of the selected nodes in a fixed order to preserve the relative spatial information. Experimental validation suggests that the use of the features from the nodes selected using our algorithm indeed help to improve the classification accuracy. Also, our finding is in concordance with the existing literature as the brain regions identified by our algorithms are independently found by many other studies on the ADHD. We achieved a classification accuracy of 69.59% using this approach. However, since this method represents each voxel as a node of the network which makes the number of nodes of the network several thousands. As a result, the network construction step becomes computationally very expensive. Another limitation of the approach is that the network features, which are computed for each node of the network, captures only the local structures while ignore the global structure of the network. Next, in order to capture the global structure of the networks, we use the Multi-Dimensional Scaling (MDS) technique to project all the subjects from an unknown network-space to a low dimensional space based on their inter-network distance measures. For the purpose of computing distance between two networks, we represent each node by a set of attributes such as the node degree, the average power, the physical location, the neighbor node degrees, and the average powers of the neighbor nodes. The nodes of the two networks are then mapped in such a way that for all pair of nodes, the sum of the attribute distances, which is the inter-network distance, is minimized. To reduce the network computation cost, we enforce that the maximum relevant information is preserved with minimum redundancy. To achieve this, the nodes of the network are constructed with clusters of highly active voxels while the activity levels of the voxels are measured based on the average power of their corresponding fMRI time-series. Our method shows promise as we achieve impressive classification accuracies (73.55%) on the ADHD-200 data set. Our results also reveal that the detection rates are higher when classification is performed separately on the male and female groups of subjects. So far, we have only used the fMRI data for solving the ADHD diagnosis problem. Finally, we investigated the answers of the following questions. Do the structural brain images contain useful information related to the ADHD diagnosis problem? Can the classification accuracy of the automatic diagnosis system be improved combining the information of the structural and functional brain data? Towards that end, we developed a new method to combine the information of structural and functional brain images in a late fusion framework. For structural data we input the gray matter (GM) brain images to a Convolutional Neural Network (CNN). The output of the CNN is a feature vector per subject which is used to train the SVM classifier. For the functional data we compute the average power of each voxel based on its fMRI time series. The average power of the fMRI time series of a voxel measures the activity level of the voxel. We found significant differences in the voxel power distribution patterns of the ADHD and control groups of subjects. The Local binary pattern (LBP) texture feature is used on the voxel power map to capture these differences. We achieved 74.23% accuracy using GM features, 77.30% using LBP features and 79.14% using combined information. In summary this dissertation demonstrated that the structural and functional brain imaging data are useful for the automatic detection of the ADHD subjects as we achieve impressive classification accuracies on the ADHD-200 data set. Our study also helps to identify the brain regions which are useful for ADHD subject classification. These findings can help in understanding the pathophysiology of the problem. Finally, we expect that our approaches will contribute towards the development of a biological measure for the diagnosis of the ADHD subjects.

With the substantial size of the interest rate markets, the importance of accurate pricing, risk measurement and performance attribution can not be understated. However, the models used on the markets often have underlying issues with capturing the market's fundamental behavior. With this thesis, we aim to improve the pricing, risk measurement, and performance attribution of interest rate swap portfolios. The paper is divided into six main parts, by subject, to aid in achieving these goals. To begin with, we validate all cash flows with SEB to increase the validity of the results. Next, we implement an optimization-based model developed by Jörgen Blomvall to estimate multiple yield curves.  By considering innovations of the daily in-sample curves, risk factors are computed with principal component analysis. These risk factors are then used to simulate one-day and ten-day ahead scenarios for the multiple yield curves using a Monte Carlo method. Given these simulated scenarios, risk measures are then computed. When backtested, these risk measurements give an indication on the overall accuracy of the methodology, including the estimated curves, the derived risk factors, and the simulation methodology. Along with the simulation, on each out-of-sample day, monetary performance attribution for the portfolios is also performed. The performance attribution indicates what drives the value change in the portfolio. This can be used in order to evaluate the estimated yield curves and derived risk factors. The risk measurement and performance attribution is done for three different portfolios of interest rate swaps on the EUR, USD, and SEK markets. However, the risk factors are only estimated for EUR data and used for all portfolios.  The main difference to previous work in this area is that, for all implementations, a multiple yield curve environment is studied. Different PCA algorithms are evaluated to increase the precision and speed of the risk factor calculation. Mean reverting risk factors are developed in the simulation framework, along with a Latin hypercube sampling method accounting for dependence in the random variables to reduce variance. We also study the EUR and SEK markets, while the focus in previous literature is on the USD market. Lastly, we calculate and backtest the risk measures value-at-risk and expected shortfall for one-day and ten-day horizons. Four different PCA methods are implemented, a bidiagonal divide and conquer SVD algorithm, a randomized SVD method, an Arnoldi method, and an optimization-based PCA algorithm. We opt to use the first one due to high accuracy and the ability to calculate all eigenpairs. However, we recommend to use the Arnoldi method in future implementations and to further study the optimization-based method. The Latin hypercube sampling with dependence method is able to produce random variables with the same correlation as the input variables. In the simulation, we are able to produce results that pass all backtests for the risk measures considering the USD portfolio. For the EUR and SEK portfolios, it is shown that the risk measures are too conservative. The results of the mean reversion method indicate that it produces slightly less conservative estimates for the ten-day horizon. In the performance attribution, we show that we are able to produce results with small error terms, therefore indicating accurately estimated term structures, risk factors, and pricing. We conclude that we are partly able to fulfill the stated purpose of this thesis due to having produced accurate pricing and satisfactory performance attribution results for all portfolios, and stable risk measures for the USD portfolio. However, it is not possible to state with certainty that improved risk measurements have been achieved for the EUR and SEK portfolios. Although, we present several alternative approaches to remedy this in future implementations.

Pour un processus d’évaluation linguistique plus précis et rapide, il est important d’identifier les mécanismes cognitifs qui soutiennent des tâches langagières couramment utilisées. Une façon de mieux comprendre ses mécanismes est d’explorer la variance partagée entre les tâches linguistiques en utilisant l’analyse factorielle exploratoire. Peu d’études ont employé cette méthode pour étudier ces mécanismes dans le fonctionnement normal du langage. Par conséquent, notre objectif principal est d’explorer comment un ensemble de tâches linguistiques se regroupent afin d’étudier les mécanismes cognitifs sous-jacents de ses tâches. Nous avons évalué 201 participants en bonne santé âgés entre 18 et 75 ans (moyenne=45,29, écart-type= 15,06) et avec une scolarité entre 5 et 23 ans (moyenne=11,10, écart-type=4,68), parmi ceux-ci, 62,87% étaient des femmes. Nous avons employé deux batteries linguistiques : le Protocole d’examen linguistique de l’aphasie Montréal-Toulouse et Protocole Montréal d’Évaluation de la Communication – version abrégé. Utilisant l’analyse en composantes principales avec une rotation Direct-oblimin, nous avons découvert quatre composantes du langage : la sémantique picturale (tâches de compréhension orale, dénomination orale et dénomination écrite), l'exécutif linguistique (tâches d’évocation lexicale - critères sémantique, orthographique et libre), le transcodage et la sémantique (tâches de lecture, dictée et de jugement sémantique) et la pragmatique (tâches d'interprétation d'actes de parole indirecte et d'interprétation de métaphores). Ces quatre composantes expliquent 59,64 % de la variance totale. Deuxièmement, nous avons vérifié l'association entre ces composantes et deux mesures des fonctions exécutives dans un sous-ensemble de 33 participants. La performance de la flexibilité cognitive a été évaluée en soustrayant le - temps A au temps B du Trail Making Test et celle de la mémoire de travail en prenant le total des réponses correctes au test du n-back. La composante exécutive linguistique était associée à une meilleure flexibilité cognitive (r=-0,355) et la composante transcodage et sémantique à une meilleure performance de mémoire de travail (r=.0,397). Nos résultats confirment l’hétérogénéité des processus sous-jacent aux tâches langagières et leur relation intrinsèque avec d'autres composantes cognitives, tels que les fonctions exécutives. / To a more accurate and time-efficient language assessment process, it is important to identify the cognitive mechanisms that sustain commonly used language tasks. One way to do so is to explore the shared variance across language tasks using the technique of principal components analysis. Few studies applied this technique to investigate these mechanisms in normal language functioning. Therefore, our main goal is to explore how a set of language tasks are going to group to investigate the underlying cognitive mechanisms of commonly used tasks. We assessed 201 healthy participants aged between 18 and 75 years old (mean = 45.29, SD = 15.06) and with a formal education between 5 and 23 years (mean = 11.10, SD =4.68), of these 62.87% were female. We used two language batteries: the Montreal-Toulouse language assessment battery and the Montreal Communication Evaluation Battery – brief version. Using a Principal Component Analysis with a Direct-oblimin rotation, we discovered four language components: pictorial semantics (auditory comprehension, naming and writing naming tasks), language-executive (unconstrained, semantic, and phonological verbal fluency tasks), transcoding and semantics (reading, dictation, and semantic judgment tasks), and pragmatics (indirect speech acts interpretation and metaphors interpretation tasks). These four components explained 59.64% of the total variance. Secondarily, we sought to verify the association between these components with two executive measures in a subset of 33 participants. Cognitive flexibility was assessed by the time B-time A score of the Trail Making Test and working memory by the total of correct answers on the n-back test. The language-executive component was associated with a better cognitive flexibility score (r=-.355) and the transcoding and semantics one with a better working memory performance (r=.397). Our findings confirm the heterogeneity process underlying language tasks and their intrinsic relationship to other cognitive components, such as executive functions.

In recent years, financial trading has become more available. This has led to more market participants and more trades taking place each day. The increased activity also implies an increasing number of abusive trades. To detect the abusive trades, market surveillance systems are developed and used. In this thesis, two different methods were tested to detect these abusive trades on high-dimensional data. One was based on empirical quantiles, and the other was based on an unsupervised machine learning technique called isolation forest. The empirical quantile method uses empirical quantiles on dimensionally reduced data to determine if a datapoint is an outlier or not. Principal Component Analysis (PCA) is used to reduce the dimensionality of the data and handle the correlation between features.Isolation forest is a machine learning method that detects outliers by sorting each datapoint in a tree structure. If a datapoint is close to the root, it is more likely to be an outlier. Isolation forest have been proven to detect outliers in high-dimensional datasets successfully, but have not been tested before for market surveillance. The performance of both the quantile method and isolation forest was tested by using recall and run-time.  The conclusion was that the empirical quantile method did not detect outliers accurately when all dimensions of the data were used. The method most likely suffered from the curse of dimensionality and could not handle high dimensional data. However, the performance increased when the dimensionality was reduced. Isolation forest performed better than the empirical quantile method and detected 99% of all outliers by classifying 226 datapoints as outliers out of a dataset with 184 true outliers and 1882 datapoints. / Under de senaste åren har finansiell handel blivit mer tillgänglig för allmänheten. Detta har lett till fler deltagare på marknaderna och att fler affärer sker varje dag. Den ökade aktiviteten innebär också att de missbruk som förekommer ökar. För att upptäcka otillåtna affärer utvecklas och används marknadsövervakningssystem. I den här avhandlingen testades två olika metoder för att upptäcka dessa missbruk utifrån högdimensionell data. Den ena baserades på empiriska kvantiler och den andra baserades på en oövervakad maskininlärningsteknik som kallas isolationsskog. Den empiriska kvantilmetoden använder empiriska kvantiler på dimensionellt reducerad data för att avgöra om en datapunkt är ett extremvärde eller inte. För att reducera dimensionen av datan, och för att hantera korrelationen mellan variabler, används huvudkomponent analys (HKA).Isolationsskog är en maskininlärnings metod som upptäcker extremvärden genom att sortera varje datapunkt i en trädstruktur. Om en datapunkt är nära roten är det mer sannolikt att det är en extremvärde. Isolationsskog har visat sig framgångsrikt upptäcka extremvärden i högdimensionella datauppsättningar, men har inte testats för marknadsövervakning tidigare. För att mäta prestanda för båda metoderna användes recall och körtid. Slutsatsen är att den empiriska kvantilmetoden inte hittade extremvärden när alla dimensioner av datan användes. Metoden led med största sannolikhet av dimensionalitetens förbannelse och kunde inte hantera högdimensionell data, men när dimensionaliteten reducerades ökade prestandan. Isolationsskog presterade bättre än den empiriska kvantilmetoden och lyckades detektera 99% av alla extremvärden genom att klassificera 226 datapunkter som extremvärden ur ett dataset med 184 verkliga extremvärden och 1882 datapunkter.

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[ES] La selección de gametos de alta calidad es un requisito indispensable a tener en cuenta en los programas de reproduccion asistida. El desarrollo de herramientas biotecnológicas como la criopreservación de gametos, juega un papel importante en la producción acuicola y en la formación de bancos de germoplasma, que contribuiran luego en la mejora genética de las poblaciónes de peces, principalmente aquellas en peligro y que pudieran estar más afectadas ante futuros cambios climáticos. En la primera fase de esta tesis realizada en la Unesp, se trabajó con una especie neotropical de elevada importancia económica para la region Suramericana. La segunda fase realizada en la UPV se trabajó con la Anguila europea (Anguilla anguilla), una especie clasificada en la Lista Roja de la (UICN) como especie "en peligro crítico de extinción". En la primera fase se buscó caracterizar la composición bioquímica del plasma y las características seminales de la especie para evaluar las posibles relaciones entre estos parámetros. El plasma seminal estuvo principalmente compuesto por iones de sodio (Na+) y dentro de los componentes orgánicos sobresalieron las proteínas totales y la glucosa. A través del análisis de componentes principales (PCA) se observó que la motilidad tenía una fuerte correlación positiva con el tiempo de motilidad, la concentración de espermatozoides y las proteínas totales. Estos análisis sirvieron de base para la creación de una solución diluyente utilizada posteriormente en la sustancia crioprotectora. Luego se determinó la influencia del plasma seminal como constituyente de la solución crioprotectora en la criopreservación de semen de P. reticulatum. Se utilizaron tres tratamientos: glucosa 5% + metanol 10% (T1), a este crioprotector se le agregó 30% de plasma seminal natural (T2) y 30% de plasma seminal artificial en base a los resultados de los componentes bioquímicos del plasma determinados para la especie en el experimento anterior (T3). Se evaluaron parámetros de motilidad espermática, capacidad fecundante del semen criopreservado, así como fragmentación del ADN. El tratamiento T1 resultó con los mejores valores de motilidad seguido del T2, y la capacidad fertilizante de estos dos tratamientos fue similar al control, sin embargo, el tratamiento T2 mostró menos daño en el ADN. Mediante el PCA se demostró que T1 tenía una mejor relación positiva con la fertilidad y la motilidad total y progresiva. Finalmente, evaluamos las estructuras de las subpoblaciones espermáticas en cada uno de los tratamientos utilizados. Mediante análisis multivariado en dos etapas, fue posible determinar tres subpoblaciones espermáticas en el semen crioconservado de la especie, SP1 (rápido-lineal), SP2 (rápido-no lineal) y SP3 (lento-lineal). T1 presentó el mayor porcentaje de SP1, siendo confirmado por la efectividad en la protección de las células de este tratamiento en el proceso de criopreservación de la especie. En la segunda fase que se está llevó a cabo en la UPV, el objetivo general fue determinar el efecto de la temperatura y el pH del agua de mar sobre la motilidad de los espermatozoides en la Anguila europea. Se determinó que el bajo pH del agua de mar (6.5-7.4) disminuyó la motilidad de los espermatozoides de anguila en comparación con el control (pH= 8.2). Cuando estudiamos el efecto combinado del pH del plasma seminal artificial y el pH de ASW (7.8 y 8.2), no encontramos diferencias estadísticas en la motilidad y cinética de los espermatozoides en relación con el pH del plasma seminal artificial, pero sí el pH del agua de mar. Se encontraron valores más altos de motilidad total (MOT), FA(rápidos) y ME (médios) con un pH de 8.2 que con un pH de 7.8. En contraste, la temperatura del agua de mar no afectó los parámetros de motilidad de los espermatozoides o la longevidad de los espermatozoides en el contexto del cambio climático. / [CA] La selecció de gàmetes d'alta qualitat és un requisit indispensable a tenir en compte en els programes de reproducció assistida. El desenvolupament d'eines biotecnològiques com la criopreservació de gàmetes, juga un paper important en la producció aqüicola i en la formació de bancs de germoplasma, que contribuiran després a la millora genètica de les població de peixos, principalment aquelles en perill i que poguessin estar més afectades davant de futurs canvis climàtics. A la primera fase d'aquesta tesi realitzada a la Unesp, es va treballar amb una espècie neotropical d'elevada importància econòmica per a la regió sud-americana. La segona fase realitzada a la UPV es va treballar amb l'Anguilla europea (Anguilla anguilla), una espècie classificada a la Llista Vermella de la (UICN) com a espècie "en perill crític d'extinció". A la primera fase es va buscar caracteritzar la composició bioquímica del plasma i les característiques seminals de l'espècie per avaluar les possibles relacions entre aquests paràmetres. El plasma seminal va estar principalment compost per ions de sodi (Na+) i dins dels components orgànics van sobresortir les proteïnes totals i la glucosa. A través de l'anàlisi de components principals (PCA), es va observar que la motilitat tenia una forta correlació positiva amb el temps de motilitat, la concentració d'espermatozoides i les proteïnes totals. Aquestes anàlisis van servir de base per a la creació d'una solució diluent utilitzada posteriorment a la substància crioprotectora. Després es va determinar la influència del plasma seminal com a constituent de la solució crioprotectora en la criopreservació de semen de P. reticulatum. Es van utilitzar tres tractaments: glucosa 5% + metanol 10% (T1), a aquest crioprotector se li va afegir 30% de plasma seminal natural (T2) i 30% de plasma seminal artificial sobre la base dels resultats dels components bioquímics del plasma determinats per a l'espècie a l'experiment anterior (T3). S'avaluaren paràmetres de motilitat espermàtica, capacitat fecundant del semen criopreservat, així com fragmentació de l'ADN. El tractament T1 va resultar amb els millors valors de motilitat seguit del T2, i la capacitat fertilitzant d'aquests dos tractaments va ser similar al control, però el tractament T2 va mostrar menys mal a l'ADN. Mitjançant el PCA es va demostrar que T1 tenia una millor relació positiva amb la fertilitat i la motilitat total i progressiva. Finalment, avaluem les estructures de les subpoblacions espermàtiques a cadascun dels tractaments utilitzats. Mitjançant anàlisi multivariada en dues etapes, va ser possible determinar tres subpoblacions espermàtiques en el semen crioconservat de l'espècie, SP1 (ràpid-lineal), SP2 (ràpid-no lineal) i SP3 (lent-lineal). T1 va presentar el percentatge més gran de SP1, i va ser confirmat per l'efectivitat en la protecció de les cèl·lules d'aquest tractament en el procés de criopreservació de l'espècie. A la segona fase que es va dur a terme a la UPV, l'objectiu general va ser determinar l'efecte de la temperatura i el pH de l'aigua de mar sobre la motilitat dels espermatozoides a l'Anguila europea. Es va determinar que el pH baix de l'aigua de mar (6.5-7.4) va disminuir la motilitat dels espermatozoides d'anguila en comparació del control (pH= 8.2). Quan estudiem l'efecte combinat del pH del plasma seminal artificial i el pH d'ASW (7.8 i 8.2), no trobem diferències estadístiques en la motilitat i la cinètica dels espermatozoides en relació amb el pH del plasma seminal artificial, però sí el pH de l'aigua de mar. Es van trobar valors més alts de motilitat total (MOT), FA(ràpids) i ME (metges) amb un pH de 8.2 que amb un pH de 7.8. En contrast, la temperatura de l'aigua de mar no va afectar els paràmetres de motilitat dels espermatozous o la longevitat dels espermatozous en el context del canvi climàtic. / [EN] The selection of high-quality gametes is an essential requirement to take into account in assisted reproduction programs. The development of biotechnological tools such as cryopreservation of gametes plays an important role in aquaculture production and in the formation of germplasm banks, which will later contribute to the genetic improvement of fish populations, mainly those in danger and that could be more affected by future climate changes. In the first phase of this thesis carried out at Unesp, we worked with a neotropical species of high economic importance for the South American region. The second phase carried out at the UPV worked with the European Eel (Anguilla anguilla), a species classified on the (IUCN) Red List as a "critically endangered" species. In the first phase, we sought to characterize the biochemical composition of the plasma and the seminal characteristics of the species to evaluate the possible relationships between these parameters. The seminal plasma was mainly composed of sodium ions (Na+) and within the organic components, total proteins and glucose stood out. Through principal component analysis (PCA) it was observed that motility had a strong positive correlation with motility time, sperm concentration and total proteins. These analyzes served as the basis for the creation of a diluent solution later used in the cryoprotective substance. Then the influence of seminal plasma as a constituent of the cryoprotectant solution in the cryopreservation of P. reticulatum semen was determined. Three treatments were used: 5% glucose + 10% methanol (T1), 30% natural seminal plasma (T2) and 30% artificial seminal plasma were added to this cryoprotectant based on the results of the determined biochemical components of the plasma. for the species in the previous experiment (T3). Parameters of sperm motility, fertilizing capacity of cryopreserved semen, as well as DNA fragmentation were evaluated. Treatment T1 resulted with the best motility values followed by T2, and the fertilizing capacity of these two treatments was similar to the control, however, treatment T2 showed less DNA damage. Using PCA, it was shown that T1 had a better positive relationship with fertility and total and progressive motility. Finally, we evaluated the structures of the sperm subpopulations in each of the treatments used. Through two-stage multivariate analysis, it was possible to determine three sperm subpopulations in the cryopreserved semen of the species, SP1 (fast-linear), SP2 (fast-nonlinear) and SP3 (slow-linear). T1 presented the highest percentage of SP1, being confirmed by the effectiveness in protecting the cells of this treatment in the cryopreservation process of the species. In the second phase that is being carried out at the UPV, the general objective was to determine the effect of temperature and pH of seawater on sperm motility in the European Eel. It was determined that the low pH of seawater (6.5-7.4) decreased the motility of eel sperm compared to the control (pH= 8.2). When we studied the combined effect of the pH of the artificial seminal plasma and the pH of ASW (7.8 and 8.2), we did not find statistical differences in the motility and kinetics of the sperm in relation to the pH of the artificial seminal plasma, but we did find the pH of the water of sea Higher values of total motility (MOT), FA (fast) and ME (medium) were found at a pH of 8.2 than at a pH of 7.8. In contrast, seawater temperature did not affect sperm motility parameters or sperm longevity in the context of climate change. / I also thank the Coordination for the Improvement of Higher Education Personnel (CAPES/PROEX) (N° 88887.302629/2018-00), National Council for Scientific, Technological Development CNPq (N° 200452/2022-3) and the Brazilian fostering agencies Foundation for Research Support of the State of Sao Paulo FAPESP (N° 2020/15020-0), for its financial support in Brazil. In Spain, the ThinkInAzul programme, supported by the Spanish Ministry of Science and Innovation (MCIN) with funding from the European Union NextGenerationEU (PRTR-C17.I1) and the Generalitat Valenciana (THINKINAZUL/2021/012) to SEASPERM, which has made it possible the preparation of this work. To the AUIP (Ibero-American Postgraduate University Association) for the Academic Mobility scholarship between Institutions Associated with the AUIP 2022 / Padilla Sánchez, M. (2023). Sperm Quality and Cryopreservation in Teleost: Effect of Seminal Plasma Component and Climate Change [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/201549

[pt] Neste estudo, tentamos estimar o impacto da medida intervencionista mais recente e amplamente adotada pelo Banco Central do Brasil no mercado de câmbio sobre a Curva de Cupom Cambial: a emissão de Swaps Cambiais. O objetivo do BCB com essa intervenção era prover o setor privado de proteção contra a volatilidade cambial à época. O trabalho foca no efeito dessas medidas na curva de Cupom Cambial por conta da importância do funcionamento dessa curva para a correta precificação do mercado de dólar futuro, já que, no Brasil, a formação da taxa de câmbio se dá no preço futuro de dólar e não no preço à vista, como é comum nos outros países. Através de Análise de Componentes Principais sobre a Curva de Cupom Cambial, encontramos seus três primeiros componentes (nível, inclinação e curvatura) e os utilizamos para regredi-los em variáveis independentes que representam a série de emissões de Swap por parte do BC. Os resultados indicam que os Swaps Cambiais geram mudanças significativas no nível geral da Curva de Cupom Cambial. Já os Swaps Reversos não apresentam impacto estatisticamente significante no nível, mas sim na inclinação da curva. / [en] In this study, we try to estimate the impact of the most recent currency intervention measure widely adopted by the Central Bank of Brazil and how it affects the Cupom Cambial Curve: the issue of Foreign Exchange Swaps. The BCB s objective with this intervention was to provide the private sector with hedge against exchange rate volatility. This paper focus on the effect of these measures on the Cupom Curve due to the importance of the comprehension of this curve for the correct pricing of the future dollar market, given that, in Brazil, the formation of the foreign exchange rate occurs with the future dollar price and not in the spot price, as is more common in other countries. Through Principal Component Analysis on the Foreign Exchange Coupon Curve, we find its three components (level, slope and curvature) and use it as an explained variable to regress it with independent variables that represent the series of Swap issued by the Central Bank. The results indicate that the Foreign Exchange Swaps generate significant changes in the overall level of the Cupom Cambial Curve. Otherwise, Reverse Swaps don t represent a statistically significant impact on the level but do impact the slope of the curve.

The Enhanced Biological Phosphorus Removal (EBPR) process is characterized as the most sustainable process to remove phosphorus from wastewater albeit with high variability in performance efficiency. Thus, unpredictable upsets in the EBPR system is the norm across several wastewater treatment plants throughout Sweden, forcing the hand of the operators to dose higher volume of chemicals to reach the effluent requirements. As future effluent requirements are getting stricter and since higher chemical usage is environmentally and economically unsustainable, this investigation was setup to evaluate which environmental, operational and/or wastewater characteristics correlate with EBPR upsets at full-scale wastewater treatment plant (WWTP), more specifically at Lundåkra WWTP operated by Nordvästra Skånes Vatten och Avlopp (NSVA). The data used in the investigation was collected between 1St January 2018 and 31St December 2020 for a vast number of parameters known to play a key role in biological phosphorus removal. Online sensors as well as external and internal analysis contributed to the data which included parameters such as ‘Total flow at the plant’, ‘pH of the incoming water’, ‘Temperature in aeration basins’, ‘Dissolved oxygen (DO) levels in aeration basins’, ‘Nitrate in aeration basins’, ‘Sludge content in aeration basins’, etc. Other relevant parameters such as ‘Hydraulic retention time (HRT) in the treatment units’, ‘Sludge retention time (SRT) in aeration basin’, ‘Organic loading rate (OLR)’, etc. were calculated. Before the start of this investigation, the two possible explanations were presumed and they can be classified as: (i) upsets as a result of unsuitable environmental conditions and/or error in the operational strategy at the plant and (ii) upsets as a result of toxicity from higher concentration of metals in the influent specifically. Traditional statistical methods such as the t-distributed Stochastic Neighbor Embedding (t-SNE), Spearman Rank Correlation and Principal Component Analysis were used for the purpose of this study to test the first presumed explanation. The t-SNE plot showed that the upsets did not cluster into one large group but instead clamped up into smaller groups scattered across the length of the scale in both dimensions. This points towards the multivariate dependency of the EBPR process and exhibits that upsets might occur even with an operational strategy that produces good results otherwise. This, in turn, eludes to the fact that a non-included parameter such as the ‘daily metal concentrations in the influent’ could be responsible for some or all of the upsets. The Principal Component Analysis (PCA) plot, although noisy, offered an improvement strategy built around the key variables namely ‘nitrate in aeration basin 1 & 2’, ‘sludge content in aeration basin’, ‘SRT in aeration basin’, ‘O2 in aeration basin 1 & 2’ and ‘pH of incoming water’. Therefore, it is recommended that an improvement strategy be devised around them. Multiple causal factors increase the complexity of the analysis by decreasing the correlation coefficients, however, incorporation of the scatterplots presents a clearer picture. The parameters ‘nitrate in aeration basin 1 & 2’ and ‘sludge content in aeration basin’ showed the strongest correlation with phosphate values at the end of biological treatment at -0.32 and 0.42 respectively. The results also open the door to future research and provide direction for further investigations. / Den förbättrade biologiska fosforborttagningsprocessen karakteriseras som den mest hållbara processen för att avlägsna fosfor från avloppsvatten om än med stor variation i prestandaeffektivitet. Således är oförutsägbara störningar i systemet för förbättrad biologisk fosforavskiljning (EBPR) normen bland flera avloppsreningsverk i hela Sverige, vilket tvingar operatörerna att dosera högre volymer kemikalier för att nå avloppskraven. Eftersom framtida avloppskrav blir allt strängare och eftersom högre kemikalieanvändning är miljömässigt och ekonomiskt ohållbar, gjordes denna undersökning för att utvärdera vilka miljö-, drifts- och/eller avloppsvattenegenskaper som korrelerar med EBPR- störningar vid fullskaligt avloppsreningsverk. Närmare bestämt vid Lundåkra reningsverk som drivs av Nordvästra Skånes Vatten och Avlopp. Datan som användes i undersökningen samlades in mellan 1:a januari 2018 och 31:a december 2020 för ett fast antal parametrar som är kända att spela en nyckelroll vid borttagning av biologiskt P. Onlinesensorer samt externa och interna analyser bidrog till datan vilken inkluderade parametrar som 'Totalt flöde vid anläggningen', 'pH för det inkommande vattnet', 'Temperatur i luftningsbassänger', nivåer av upplöst syre (DO) i luftningsbassänger ',' Nitrat i luftningsbassänger ',' Slamhalt i luftningsbassänger ', etc. Andra relevanta parametrar som 'Hydraulisk retentionstid (HRT) i behandlingsenheterna ',' Slamretentionstid (SRT) i luftningsbassäng ',' Organisk belastningshastighet (OLR) ', etc. beräknades. Innan denna undersökning påbjörades antogs de två möjliga förklaringarna och de kan klassificeras som: (i) störningar till följd av olämpliga miljöförhållanden och/eller fel i driftstrategin vid anläggningen och (ii) störningar till följd av toxicitet från högre koncentration av metaller i inflödet specifikt. Traditionella statistiska metoder såsom t- Distributed Stochastic Neighbor Embedding (t-SNE), Spearman Rank Correlation och Principal Component Analysis användes i denna studie för att testa den första förmodade förklaringen. t-SNE- diagrammet visade att störningarna inte samlades i en stor grupp utan istället klämdes ihop i mindre grupper utspridda över skalans längd i båda dimensionerna. Detta pekar mot EBPR-processens multivariata beroende och visar att störningar kan uppstå även med en operativ strategi som annars ger bra resultat. Detta i sin tur undviker det faktum att en icke-inkluderad parameter som "dagliga metallkoncentrationer i inflödet" kan vara orsaken för några eller alla störningar. Principal Component Analysis (PCA)-diagrammet, trots att det var bullrigt, möjliggjorde en förbättringsstrategi byggd kring nyckelvariablerna, nämligen 'nitrat i luftningsbassäng 1 & 2', 'slamhalt i luftningsbassäng', 'SRT i luftningsbassäng', 'O2 i luftningsbassäng 1 & 2' och 'pH av inkommande vatten'. Därför rekommenderas att en förbättringsstrategi utarbetas kring dem. Flera kausala faktorer ökar komplexiteten i analysen genom att minska korrelationskoefficienterna, men spridningsdiagrammen ger en tydligare bild. Parametrarna ‘nitrat i luftningsbassäng 1 & 2’ och ‘slamhalt i luftningsbassäng’ visade starkast samband med fosfatvärden vid slutet av biologisk behandling vid -0,32 respektive 0,42. Resultaten lämnar dörren öppen för framtida forskning och kan vägleda vidare undersökningar.