Aplicació en línia d'un sistema variable de control multivariable en un Reactor ..

L’objecte del present treball és la realització d’una aplicació que permeti portar a terme el control estadístic multivariable en línia d’una planta SBR.Aquesta eina ha de permetre realitzar un anàlisi estadístic multivariable complet del lot en procés, de l’últim lot finalitzat i de la resta de lots processats a la planta.L’aplicació s’ha de realitzar en l’entorn LabVIEW. L’elecció d’aquest programa vecondicionada per l’actualització del mòdul de monitorització de la planta que s’estàdesenvolupant en aquest mateix entorn

Assessing farmers' vulnerability to climate change : a case study in Karnataka, India

In the context of observed climate change impacts and their effect on agriculture and crop production, this study intends to assess the vulnerability of rural livelihoods through a study case in Karnataka, India. The social approach of climate change vulnerability in this study case includes defining and exploring factors that determine farmers’ vulnerability in four villages. Key informant interviews, farmer workshops and structured household interviews were used for data collection. To analyse the data, we adapted and applied three vulnerability indices: Livelihood Vulnerability Index (LVI), LVI-IPCC and the Livelihood Effect Index (LEI), and used descriptive statistical methods. The data was analysed at two scales: whole sample-level and household level. The results from applying the indices for the whole-sample level show that this community's vulnerability to climate change is moderate, whereas the household-level results show that most of the households' vulnerability is high-very high, while 15 key drivers of vulnerability were identified. Results and limitations of the study are discussed under the rural livelihoods framework, in which the indices are based, allowing a better understanding of the social behaviouraltrends, as well as an holistic and integrated view of the climate change, agriculture, and livelihoods processes shaping vulnerability. We conclude that these indices, although a straightforward method to assess vulnerability, have limitations that could account for inaccuracies and inability to be standardised for benchmarking, therefore we stress the need for further research.

The glasses of the transept's rosette of the Cathedral of Tarragona: characterization, classification and decay.

The glasses of the rosette forming the main window of the transept of the Gothic Cathedral of Tarragona have been characterised by means of SEM/EDS, XRD, FTIR and electronic microprobe. The multivariate statistical treatment of these data allow to establish a classification of the samples forming groups having an historical significance and reflecting ancient restorations. Furthermore, the decay patterns and mechanisms have been determined and the weathering by-products characterised. It has been demonstrated a clear influence of the bioactivity in the decay of these glasses, which activity is partially controlled by the chemical composition of the glasses.

The glasses of the transept's rosette of the Cathedral of Tarragona: characterization, classification and decay.

The glasses of the rosette forming the main window of the transept of the Gothic Cathedral of Tarragona have been characterised by means of SEM/EDS, XRD, FTIR and electronic microprobe. The multivariate statistical treatment of these data allow to establish a classification of the samples forming groups having an historical significance and reflecting ancient restorations. Furthermore, the decay patterns and mechanisms have been determined and the weathering by-products characterised. It has been demonstrated a clear influence of the bioactivity in the decay of these glasses, which activity is partially controlled by the chemical composition of the glasses.

Kernel-PCA data integration with enhanced interpretability

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge.

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

Bioavailability of sinking organic matter in the Blanes canyon and the adjacent open slope (NW Mediterranean Sea)

Submarine canyons are sites of intense energy and material exchange between the shelf and the deep adjacent basins. To test the hypothesis that active submarine canyons represent preferential conduits of available food for the deep-sea benthos, two mooring lines were deployed at 1200 m depth from November 2008 to November 2009 inside the Blanes canyon and on the adjacent open slope (Catalan Margin, NW Mediterranean Sea). We investigated the fluxes, biochemical composition and food quality of sinking organic carbon (OC). OC fluxes in the canyon and the open slope varied among sampling periods, though not onsistently in the two sites. In particular, while in the open slope the highest OC fluxes were observed in August 2009, in the canyon the highest OC fluxes occurred in AprilMay 2009. For almost the entire study period, the OC fluxes in the canyon were significantly higher than those in the open slope, whereas OC contents of sinking particles collected in the open slope were consistently higher than those in the canyon. This result confirms that submarine canyons are effective conveyors of OC to the deep sea. Particles transferred to the deep sea floor through the canyons are predominantly of inorganic origin, significantly higher than that reaching the open slope at a similar water depth. Using multivariate statistical tests, two major clusters of sampling periods were identified: one in the canyon that grouped trap samples collected in December 2008, oncurrently with the occurrence of a major storm at the sea surface, and associated with increased fluxes of nutritionally available particles from the upper shelf. Another cluster grouped samples from both the canyon and the open slope collected in March 2009, concurrently with the occurrence of the seasonal phytoplankton bloom at the sea surface, and associated with increased fluxes of total phytopigments. Our results confirm the key ecological role of submarine canyons for the functioning of deep-sea ecosystems, and highlight the importance of canyons in linking episodic storms and primary production occurring at the sea surface to the deep sea floor.

Power supply noise and logic error probability

Voltage fluctuations caused by parasitic impedances in the power supply rails of modern ICs are a major concern in nowadays ICs. The voltage fluctuations are spread out to the diverse nodes of the internal sections causing two effects: a degradation of performances mainly impacting gate delays anda noisy contamination of the quiescent levels of the logic that drives the node. Both effects are presented together, in thispaper, showing than both are a cause of errors in modern and future digital circuits. The paper groups both error mechanismsand shows how the global error rate is related with the voltage deviation and the period of the clock of the digital system.

Factores de explotación asociados a la duración del anestro postparto en vacas nodrizas de razas Parda de Montaña y Pirenaica

Para determinar los factores de explotación relacionados con la reactivación ovárica postparto en vacas nodrizas se realizó un análisis global de una serie de indicadores productivos y la duración del anestro postparto (APP) de 549 vacas explotadas en condiciones extensivas. Debido a la naturaleza multifactorial del proceso en estudio se eligió la metodología estadística multivariante (Análisis Factorial de Correspondencias Múltiples y Análisis Cluster). La duración del APP estuvo asociada a cuatro factores que explicaron el 59% de la heterogeneidad inicial de la muestra y que se definieron como: «Alimentación preparto» (19% de la inercia), «Alimentación postparto-Edad» (16.4%), «Manejo del ternero» (13%) y «Dificultad al parto» (10.5%). Estos factores se introdujeron en un Análisis Cluster que identificó cinco grupos de vacas con características productivas y reproductivas diferentes, y que denominamos como: «Primíparas», «Acceso restringido», «Acceso Libre-Parda de Montaña», «Parto de otoño» y «Parto de primavera». La raza no estuvo relacionada con la duración del APP, aunque el análisis Cluster asoció los largos APP inducidos por la crianza libre con la raza Parda de Montaña. En la raza Parda de Montaña, la duración del APP fue mayor en primavera que en otoño debido a diferencias nutricionales más que a un efecto estacional en sí. El parto de otoño se adaptó mejor a las condiciones de montaña seca.

Salivary cotinine concentrations in daily smokers in Barcelona, Spain: a cross-sectional study

Background: Characterizing and comparing the determinant of cotinine concentrations in different populations should facilitate a better understanding of smoking patterns and addiction. This study describes and characterizes determinants of salivary cotinine concentration in a sample of Spanish adult daily smoker men and women. Methods: A cross-sectional study was carried out between March 2004 and December 2005 in a representative sample of 1245 people from the general population of Barcelona, Spain. A standard questionnaire was used to gather information on active tobacco smoking and passive exposure, and a saliva specimen was obtained to determine salivary cotinine concentration. Two hundred and eleven adult smokers (>16 years old) with complete data were included in the analysis. Determinants of cotinine concentrations were assessed using linear regression models. Results: Salivary cotinine concentration was associated with the reported number of cigarettes smoked in the previous 24 hours (R2 = 0.339; p < 0.05). The inclusion of a quadratic component for number of cigarettes smoked in the regression analyses resulted in an improvement of the fit (R2 = 0.386; p < 0.05). Cotinine concentration differed significantly by sex, with men having higher levels. Conclusion: This study shows that salivary cotinine concentration is significantly associated with the number of cigarettes smoked and sex, but not with other smoking-related variables.

Problems of the randomization test for AB designs

N = 1 designs imply repeated registrations of the behaviour of the same experimental unit and the measurements obtained are often few due to time limitations, while they are also likely to be sequentially dependent. The analytical techniques needed to enhance statistical and clinical decision making have to deal with these problems. Different procedures for analysing data from single-case AB designs are discussed, presenting their main features and revising the results reported by previous studies. Randomization tests represent one of the statistical methods that seemed to perform well in terms of controlling false alarm rates. In the experimental part of the study a new simulation approach is used to test the performance of randomization tests and the results suggest that the technique is not always robust against the violation of the independence assumption. Moreover, sensitivity proved to be generally unacceptably low for series lengths equal to 30 and 40. Considering the evidence available, there does not seem to be an optimal technique for single-case data analysis

Bioavailability of sinking organic matter in the Blanes canyon and the adjacent open slope (NW Mediterranean Sea)

Submarine canyons are sites of intense energy and material exchange between the shelf and the deep adjacent basins. To test the hypothesis that active submarine canyons represent preferential conduits of available food for the deep-sea benthos, two mooring lines were deployed at 1200 m depth from November 2008 to November 2009 inside the Blanes canyon and on the adjacent open slope (Catalan Margin, NW Mediterranean Sea). We investigated the fluxes, biochemical composition and food quality of sinking organic carbon (OC). OC fluxes in the canyon and the open slope varied among sampling periods, though not onsistently in the two sites. In particular, while in the open slope the highest OC fluxes were observed in August 2009, in the canyon the highest OC fluxes occurred in April-May 2009. For almost the entire study period, the OC fluxes in the canyon were significantly higher than those in the open slope, whereas OC contents of sinking particles collected in the open slope were consistently higher than those in the canyon. This result confirms that submarine canyons are effective conveyors of OC to the deep sea. Particles transferred to the deep sea floor through the canyons are predominantly of inorganic origin, significantly higher than that reaching the open slope at a similar water depth. Using multivariate statistical tests, two major clusters of sampling periods were identified: one in the canyon that grouped trap samples collected in December 2008, oncurrently with the occurrence of a major storm at the sea surface, and associated with increased fluxes of nutritionally available particles from the upper shelf. Another cluster grouped samples from both the canyon and the open slope collected in March 2009, concurrently with the occurrence of the seasonal phytoplankton bloom at the sea surface, and associated with increased fluxes of total phytopigments. Our results confirm the key ecological role of submarine canyons for the functioning of deep-sea ecosystems, and highlight the importance of canyons in linking episodic storms and primary production occurring at the sea surface to the deep sea floor.

Quantifying Social Asymmetric Structures

Many social phenomena involve a set of dyadic relations among agents whose actions may be dependent. Although individualistic approaches have frequently been applied to analyze social processes, these are not generally concerned with dyadic relations nor do they deal with dependency. This paper describes a mathematical procedure for analyzing dyadic interactions in a social system. The proposed method mainly consists of decomposing asymmetric data into their symmetrical and skew-symmetrical parts. A quantification of skew-symmetry for a social system can be obtained by dividing the norm of the skew-symmetrical matrix by the norm of the asymmetric matrix. This calculation makes available to researchers a quantity related to the amount of dyadic reciprocity. Regarding agents, the procedure enables researchers to identify those whose behavior is asymmetric with respect to all agents. It is also possible to derive symmetric measurements among agents and to use multivariate statistical techniques.

¿Cómo optimizar una matriz de datos? Utilidades básicas del SPSS

Una vez se dispone de los datos introducidos en el paquete estadístico del SPSS (Statistical Package of Social Science), en una matriz de datos, es el momento de plantearse optimizar esa matriz para poder extraer el máximo rendimiento a los datos, según el tipo de análisis que se pretende realizar. Para ello, el propio SPSS tiene una serie de utilidades que pueden ser de gran utilidad. Estas utilidades básicas pueden diferenciarse según su funcionalidad entre: utilidades para la edición de datos, utilidades para la modificación de variables, y las opciones de ayuda que nos brinda. A continuación se presentan algunas de estas utilidades.

Kernel-PCA data integration with enhanced interpretability

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge.