Benthic macroinvertebrates assemblages and macrohabitat connectivity in Mediterranean-climate streams of northern California

Abstract. Drought leads to a loss of longitudinal and lateral hydrologic connectivity, which causes direct or indirect changes in stream ecosystem properties. Changes in macrohabitat availability from a rifflepool sequence to isolated pools are among the most conspicuous consequences of connectivity loss. Macroinvertebrate assemblages were compared among 3 distinct stream macrohabitats (riffles [R], pools connected to riffles [Pc], disconnected pools [Pd]) of 19 Mediterranean-climate sites in northern California to examine the influence of loss of habitat resulting from drought disturbance. At the time of sampling, 10 sites were perennial and included R and Pc macrohabitats, whereas 9 sites were intermittent and included only Pd macrohabitats. Taxa richness was more variable in Pd, and taxa richness was significantly lower in Pd than in Pc but not R. These results suggested a decline in richness between Pc and Pd that might be associated with loss of connectivity. Lower Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness relative to Odonata, Coleoptera, and Heteroptera (OCH) richness was observed for Pd than R and Pc macrohabitats. Family composition was more similar between R and Pc than between R or Pc and Pd macrohabitats. This similarity may be associated with greater connectivity between R and Pc macrohabitats. Correspondence analysis indicated that macroinvertebrate composition changed along a gradient from R to Pc and Pd that was related to a perennialintermittent gradient across sites. High variability among macroinvertebrate assemblages in Pd could have been related to variability in the duration of intermittency. In cluster analysis, macroinvertebrate assemblages were grouped by macrohabitat first and then by site, suggesting that the macrohabitat filter had a greater influence on macroinvertebrate assemblages than did local site characteristics. Few taxa were found exclusively in Pc, and this macrohabitat shared numerous taxa with R and Pd, indicating that Pc may act as a bridge between R and Pd during drought. Drought is regarded as a ramp disturbance, but our results suggest that the response of macroinvertebrate assemblages to the loss of hydrological connectivity among macrohabitats is gradual, at least in Mediterranean-climate streams where drying is gradual. However, the changes may be more dramatic in arid and semiarid streams or in Mediterranean-climate streams if drying is rapid.

Evolutionary analysis of genetic variants involved in rare diseases

Next-generation sequencing techniques such as exome sequencing can successfully detect all genetic variants in a human exome and it has been useful together with the implementation of variant filters to identify causing-disease mutations. Two filters aremainly used for the mutations identification: low allele frequency and the computational annotation of the genetic variant. Bioinformatic tools to predict the effect of a givenvariant may have errors due to the existing bias in databases and sometimes show a limited coincidence among them. Advances in functional and comparative genomics are needed in order to properly annotate these variants.The goal of this study is to: first, functionally annotate Common Variable Immunodeficiency disease (CVID) variants with the available bioinformatic methods in order to assess the reliability of these strategies. Sencondly, as the development of new methods to reduce the number of candidate genetic variants is an active and necessary field of research, we are exploring the utility of gene function information at organism level as a filter for rare disease genes identification. Recently, it has been proposed that only 10-15% of human genes are essential and therefore we would expect that severe rare diseases are mostly caused by mutations on them. Our goal is to determine whether or not these rare and severe diseases are caused by deleterious mutations in these essential genes. If this hypothesis were true, taking into account essential genes as a filter would be an interesting parameter to identify causingdisease mutations.

Susceptibilitat genètica al càncer gàstric: caracterització de les interaccions de segon ordre entre gens i variants identificades en l’estudi EPIC‐EURGAST

En aquest Treball de Final de Grau s’exposen els resultats de l’anàlisi de les dades genètiques del projecte EurGast2 "Genetic susceptibility, environmental exposure and gastric cancer risk in an European population”, estudi cas‐control niat a la cohort europea EPIC “European Prospective lnvestigation into Cancer and Nutrition”, que té per objectiu l’estudi dels factors genètics i ambientals associats amb el risc de desenvolupar càncer gàstric (CG). A partir de les dades resultants de l’estudi EurGast2, en el què es van analitzar 1.294 SNPs en 365 casos de càncer gàstric i 1.284 controls en l’anàlisi Single SNP previ, la hipòtesi de partida del present Treball de Final de Grau és que algunes variants amb un efecte marginal molt feble, però que conjuntament amb altres variants estarien associades al risc de CG, podrien no haver‐se detectat. Així doncs, l’objectiu principal del projecte és la identificació d’interaccions de segon ordre entre variants genètiques de gens candidats implicades en la carcinogènesi de càncer gàstric. L’anàlisi de les interaccions s’ha dut a terme aplicant el mètode estadístic Model‐based Multifactor Dimensionality Reduction Method (MB‐MDR), desenvolupat per Calle et al. l’any 2008 i s’han aplicat dues metodologies de filtratge per seleccionar les interaccions que s’exploraran: 1) filtratge d’interaccions amb un SNP significatiu en el Single SNP analysis i 2) filtratge d’interaccions segons la mesura Sinèrgia. Els resultats del projecte han identificat 5 interaccions de segon ordre entre SNPs associades significativament amb un major risc de desenvolupar càncer gàstric, amb p‐valor inferior a 10‐4. Les interaccions identificades corresponen a interaccions entre els gens MPO i CDH1, XRCC1 i GAS6, ADH1B i NR5A2 i IL4R i IL1RN (que s’ha validat en les dues metodologies de filtratge). Excepte CDH1, cap altre d’aquests gens s’havia associat significativament amb el CG o prioritzat en les anàlisis prèvies, el que confirma l’interès d’analitzar les interaccions genètiques de segon ordre. Aquestes poden ser un punt de partida per altres anàlisis destinades a confirmar gens putatius i a estudiar a nivell biològic i molecular els mecanismes de carcinogènesi, i orientades a la recerca de noves dianes terapèutiques i mètodes de diagnosi i pronòstic més eficients.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

High-Resolution Mass Spectrometry applied to the identification of new metabolites and transformation products of quinolones in chicken muscle tissues

The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.

Augmented state Kalman filtering for AUV navigation

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position

High-Resolution Mass Spectrometry applied to the identification of transformation products of quinolones from stability studies and new metabolites of enrofloxacin in chicken muscle tissues

The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.

High-resolution mass spectrometry applied to theidentification of transformation products of quinolones from stability studies and new metabolites of enrofloxacin in chicken muscle tissues

The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach

This paper proposes a spatial filtering technique forthe reception of pilot-aided multirate multicode direct-sequencecode division multiple access (DS/CDMA) systems such as widebandCDMA (WCDMA). These systems introduce a code-multiplexedpilot sequence that can be used for the estimation of thefilter weights, but the presence of the traffic signal (transmittedat the same time as the pilot sequence) corrupts that estimationand degrades the performance of the filter significantly. This iscaused by the fact that although the traffic and pilot signals areusually designed to be orthogonal, the frequency selectivity of thechannel degrades this orthogonality at hte receiving end. Here,we propose a semi-blind technique that eliminates the self-noisecaused by the code-multiplexing of the pilot. We derive analyticallythe asymptotic performance of both the training-only andthe semi-blind techniques and compare them with the actual simulatedperformance. It is shown, both analytically and via simulation,that high gains can be achieved with respect to training-onlybasedtechniques.

System identification using a linear combination of cumulant slices

In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Estudi comparatiu dels filtres de Kalman i IMM per a navegació

Els sistemes híbrids de navegació integren mesures de posició i velocitat provinents de satèl·lits (GPS) i d’unitats de mesura inercials (IMU).Les dades d’aquests sensors s’han de fusionar i suavitzar, i per a aquest propòsit existeixen diversos algorismes de filtratge, que tracten les dades conjuntament o per separat. En aquest treball s’han codificat en Matlab els algorismes dels filtres de Kalman i IMM, i s’han comparat les seves prestacions en diverses trajectòries d’un vehicle. S’han avaluat quantitativament els errors dels dos filtres, i s’han sintonitzat els seus paràmetres per a minimitzar aquests errors. Amb una correcta sintonia dels filtres, s’ha comprovat que el filtre IMM és superior al filtre de Kalman, tant per maniobres brusques com per maniobres suaus, malgrat que la complexitat i el temps de càlcul requerit són majors.

The effect of age at the first mating and herd size on the lifetime productivity of sows

The effect of age at the first mating and herd size were evaluated in the reference Spanish Databank (BDporc) of 37 698 sows born between 1991 and 1995 and with individual lifetime records. The data included dates of births at entrance and culling, first mating, repetitive mating and conception, first farrowing and weaning records. Individual records were validated before the analysis by screening them through a tolerance “filter” in order to eliminate the extreme values from the analysis. The total database of the sows was classified in 7 classes according to age at the first mating (< 210, 210–220, 221–230, 231–240, 241–250, 251–270, and > 270 days) and in 6 classes of herd size (< 200, 200–300, 301–400, 401–600, 601–800, and > 800 sows). The total number of litters and number of weaned piglets obtained from each sow during the lifetime production were significantly (P < 0.05) greater for gilts between 221 and 240 d of age at the first mating. There was a significant (P < 0.001) effect of the herd size on the reproductive performance of the sow, and the best performance was obtained with herds with 401 to 600 sows compared to < 200 or > 800 sow-herds. Furthermore, a significant (P < 0.001) interaction between age at the first mating and herd size was detected and can be associated with a particular pattern for the herd size class 401–600 sows with the best performances obtained for the sows first mated at less than 200 days. For the other herd sizes, the results indicated that sows mated for the first time at the right age, 221–240 days, are more productive, both in the number and size of the parities throughout lifetime production.

Effluent particle removal by microirrigation system filters

La distribución del número y del volumen de partículas, y la eficiencia de eliminación de las partículas y los sólidos en suspensión de diferentes efluentes y sus filtrados, fueron analizadas para estudiar si los filtros más usuales en los sistemas de riego localizado eliminan las partículas que pueden obturar los goteros. En la mayoría de los efluentes y filtrados fue mínimo el número de partículas con diámetros superiores a 20 μm. Sin embargo, al analizar la distribución del volumen de las partículas, en los filtrados aparecieron partículas de dimensiones superiores a la luz de los filtros de anillas y malla, siendo el filtro de arena el que retuvo las partículas de mayor diámetro. La eficiencia de los filtros para retener partículas se debió más al tipo de efluente que al filtro. Se verificó también que la distribución del número de partículas sigue una relación de tipo potencial. Analizando el exponente β de la ley potencial, se halló que los filtros no modificaron significativamente la distribución del número de partículas de los efluentes.