Lowering the radioactivity of the photomultiplier tubes for the XENON1T dark matter experiment

The low-background, VUV-sensitive 3-inch diameter photomultiplier tube R11410 has been developed by Hamamatsu for dark matter direct detection experiments using liquid xenon as the target material. We present the results from the joint effort between the XENON collaboration and the Hamamatsu company to produce a highly radio-pure photosensor (version R11410-21) for the XENON1T dark matter experiment. After introducing the photosensor and its components, we show the methods and results of the radioactive contamination measurements of the individual materials employed in the photomultiplier production. We then discuss the adopted strategies to reduce the radioactivity of the various PMT versions. Finally, we detail the results from screening 286 tubes with ultra-low background germanium detectors, as well as their implications for the expected electronic and nuclear recoil background of the XENON1T experiment.

The Nurturing of Seagliders By the National Oceanographic Partnership Program

The National Oceanographic Partnership Program provided critical support to the development of Seaglider long-range autonomous underwater vehicles. This support enabled: (1) development and integration of chemical and biological sensors, (2) transition to low-power, bi-directional satellite communication, and (3) software upgrades to enhance capability and reliability. Sponsored improvements led to setting the mission endurance and range records for autonomous underwater vehicles, wide use by the oceanographic community and licensing for commercialization.

A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^

(Table 1) Cesium-137 concentrations and salinity in surface waters from the Atlantic and Pacific Oceans in January-May 1978

Cesium-137 concentrations of surface waters were measured during Cruise 20 of R/V Dmitry Mendeleev across the Atlantic and Pacific Oceans. The measurements were combined with simultaneous salinity measurements. The radioactivity field of surface waters is governed by presence of closed circulation systems and their component currents. Crossing the oceans from west to east decrease in cesium-137 concentrations was noted. In surface waters in the northeastern periphery of the southern anticyclonic gyre in the Pacific Ocean Cs-137 concentrations increased (up to 21.5 Bq/m**3) due to a series of nuclear tests on the Muroroa Atoll.

Phosphate d18O pore-water profiles of sediment core GeoB11807-2 and GeoB11804-4

Phosphorus cycling in the ocean is influenced by biological and geochemical processes that are reflected in the oxygen isotope signature of dissolved inorganic phosphate (Pi). Extending the Pi oxygen isotope record from the water column into the seabed is difficult due to low Pi concentrations and small amounts of marine porewaters available for analysis. We obtained porewater profiles of Pi oxygen isotopes using a refined protocol based on the original micro-extraction designed by Colman (2002). This refined and customized method allows the conversion of ultra-low quantities (0.5 - 1 µmol) of porewater Pi to silver phosphate (Ag3PO4) for routine analysis by mass spectrometry. A combination of magnesium hydroxide co-precipitation with ion exchange resin treatment steps is used to remove dissolved organic matter, anions, and cations from the sample before precipitating Ag3PO4. Samples as low as 200 µg were analyzed in a continuous flow isotope ratio mass spectrometer setup. Tests with external and laboratory internal standards validated the preservation of the original phosphate oxygen isotope signature (d18OP) during micro extraction. Porewater data on d18OP has been obtained from two sediment cores of the Moroccan margin. The d18OP values are in a range of +19.49 to +27.30 per mill. We apply a simple isotope mass balance model to disentangle processes contributing to benthic P cycling and find evidence for Pi regeneration outbalancing microbial demand in the upper sediment layers. This highlights the great potential of using d18OP to study microbial processes in the subseafloor and at the sediment water interface.

Flujo de potencia entre estructuras complejas sometidas a excitaciones de alta frecuencia y aplicaciones a la detección de daño estructural

El tema central de investigación en esta Tesis es el estudio del comportamientodinámico de una estructura mediante modelos que describen la distribución deenergía entre los componentes de la misma y la aplicación de estos modelos parala detección de daños incipientes.Los ensayos dinámicos son un modo de extraer información sobre las propiedadesde una estructura. Si tenemos un modelo de la estructura se podría ajustar éstepara que, con determinado grado de precisión, tenga la misma respuesta que elsistema real ensayado. Después de que se produjese un daño en la estructura,la respuesta al mismo ensayo variará en cierta medida; actualizando el modelo alas nuevas condiciones podemos detectar cambios en la configuración del modeloestructural que nos condujeran a la conclusión de que en la estructura se haproducido un daño.De este modo, la detección de un daño incipiente es posible si somos capacesde distinguir una pequeña variación en los parámetros que definen el modelo. Unrégimen muy apropiado para realizar este tipo de detección es a altas frecuencias,ya que la respuesta es muy dependiente de los pequeños detalles geométricos,dado que el tamaño característico en la estructura asociado a la respuesta esdirectamente proporcional a la velocidad de propagación de las ondas acústicas enel sólido, que para una estructura dada es inalterable, e inversamente proporcionala la frecuencia de la excitación. Al mismo tiempo, esta característica de la respuestaa altas frecuencias hace que un modelo de Elementos Finitos no sea aplicable enla práctica, debido al alto coste computacional.Un modelo ampliamente utilizado en el cálculo de la respuesta de estructurasa altas frecuencias en ingeniería es el SEA (Statistical Energy Analysis). El SEAaplica el balance energético a cada componente estructural, relacionando la energíade vibración de estos con la potencia disipada por cada uno de ellos y la potenciatransmitida entre ellos, cuya suma debe ser igual a la potencia inyectada a cadacomponente estructural. Esta relación es lineal y viene caracterizada por los factoresde pérdidas. Las magnitudes que intervienen en la respuesta se consideranpromediadas en la geometría, la frecuencia y el tiempo.Actualizar el modelo SEA a datos de ensayo es, por lo tanto, calcular losfactores de pérdidas que reproduzcan la respuesta obtenida en éste. Esta actualización,si se hace de manera directa, supone la resolución de un problema inversoque tiene la característica de estar mal condicionado. En la Tesis se propone actualizarel modelo SEA, no en término de los factores de pérdidas, sino en términos deparámetros estructurales que tienen sentido físico cuando se trata de la respuestaa altas frecuencias, como son los factores de disipación de cada componente, susdensidades modales y las rigideces características de los elementos de acoplamiento.Los factores de pérdidas se calculan como función de estos parámetros. Estaformulación es desarrollada de manera original en esta Tesis y principalmente sefunda en la hipótesis de alta densidad modal, es decir, que en la respuesta participanun gran número de modos de cada componente estructural.La teoría general del método SEA, establece que el modelo es válido bajounas hipótesis sobre la naturaleza de las excitaciones externas muy restrictivas,como que éstas deben ser de tipo ruido blanco local. Este tipo de carga es difícil dereproducir en condiciones de ensayo. En la Tesis mostramos con casos prácticos queesta restricción se puede relajar y, en particular, los resultados son suficientementebuenos cuando la estructura se somete a una carga armónica en escalón.Bajo estas aproximaciones se desarrolla un algoritmo de optimización por pasosque permite actualizar un modelo SEA a un ensayo transitorio cuando la carga esde tipo armónica en escalón. Este algoritmo actualiza el modelo no solamente parauna banda de frecuencia en particular sino para diversas bandas de frecuencia demanera simultánea, con el objetivo de plantear un problema mejor condicionado.Por último, se define un índice de daño que mide el cambio en la matriz depérdidas cuando se produce un daño estructural en una localización concreta deun componente. Se simula numéricamente la respuesta de una estructura formadapor vigas donde producimos un daño en la sección de una de ellas; como se tratade un cálculo a altas frecuencias, la simulación se hace mediante el Método delos Elementos Espectrales para lo que ha sido necesario desarrollar dentro de laTesis un elemento espectral de tipo viga dañada en una sección determinada. Losresultados obtenidos permiten localizar el componente estructural en que se haproducido el daño y la sección en que éste se encuentra con determinado grado deconfianza.AbstractThe main subject under research in this Thesis is the study of the dynamic behaviourof a structure using models that describe the energy distribution betweenthe components of the structure and the applicability of these models to incipientdamage detection.Dynamic tests are a way to extract information about the properties of astructure. If we have a model of the structure, it can be updated in order toreproduce the same response as in experimental tests, within a certain degree ofaccuracy. After damage occurs, the response will change to some extent; modelupdating to the new test conditions can help to detect changes in the structuralmodel leading to the conclusión that damage has occurred.In this way incipient damage detection is possible if we are able to detect srnallvariations in the model parameters. It turns out that the high frequency regimeis highly relevant for incipient damage detection, because the response is verysensitive to small structural geometric details. The characteristic length associatedwith the response is proportional to the propagation speed of acoustic waves insidethe solid, but inversely proportional to the excitation frequency. At the same time,this fact makes the application of a Finite Element Method impractical due to thehigh computational cost.A widely used model in engineering when dealing with the high frequencyresponse is SEA (Statistical Energy Analysis). SEA applies the energy balance toeach structural component, relating their vibrational energy with the dissipatedpower and the transmitted power between the different components; their summust be equal to the input power to each of them. This relationship is linear andcharacterized by loss factors. The magnitudes considered in the response shouldbe averaged in geometry, frequency and time.SEA model updating to test data is equivalent to calculating the loss factorsthat provide a better fit to the experimental response. This is formulated as an illconditionedinverse problem. In this Thesis a new updating algorithm is proposedfor the study of the high frequency response regime in terms of parameters withphysical meaning such as the internal dissipation factors, modal densities andcharacteristic coupling stiffness. The loss factors are then calculated from theseparameters. The approach is developed entirely in this Thesis and is mainlybased on a high modal density asumption, that is to say, a large number of modescontributes to the response.General SEA theory establishes the validity of the model under the asumptionof very restrictive external excitations. These should behave as a local white noise.This kind of excitation is difficult to reproduce in an experimental environment.In this Thesis we show that in practical cases this assumption can be relaxed, inparticular, results are good enough when the structure is excited with a harmonicstep function.Under these assumptions an optimization algorithm is developed for SEAmodel updating to a transient test when external loads are harmonic step functions.This algorithm considers the response not only in a single frequency band,but also for several of them simultaneously.A damage index is defined that measures the change in the loss factor matrixwhen a damage has occurred at a certain location in the structure. The structuresconsidered in this study are built with damaged beam elements; as we are dealingwith the high frequency response, the numerical simulation is implemented witha Spectral Element Method. It has therefore been necessary to develop a spectralbeam damaged element as well. The reported results show that damage detectionis possible with this algorithm, moreover, damage location is also possible withina certain degree of accuracy.

A compact lightweight multipurpose ground-penetrating radar for glaciological applications

We describe a compact lightweight impulse radar for radio-echo sounding of subsurface structures designed specifically for glaciological applications. The radar operates at frequencies between 10 and 75 MHz. Its main advantages are that it has a high signal-to-noise ratio and a corresponding wide dynamic range of 132 dB due mainly to its ability to perform real-time stacking (up to 4096 traces) as well as to the high transmitted power (peak voltage 2800 V). The maximum recording time window, 40 ?s at 100 MHz sampling frequency, results in possible radar returns from as deep as 3300 m. It is a versatile radar, suitable for different geophysical measurements (common-offset profiling, common midpoint, transillumination, etc.) and for different profiling set-ups, such as a snowmobile and sledge convoy or carried in a backpack and operated by a single person. Its low power consumption (6.6 W for the transmitter and 7.5 W for the receiver) allows the system to operate under battery power for mayor que7 hours with a total weight of menor que9 kg for all equipment, antennas and batteries.

A practical approach for outdoors distributed target localization in wireless sensor networks

Wireless sensor networks are posed as the new communication paradigm where the use of small, low-complexity, and low-power devices is preferred over costly centralized systems. The spectra of potential applications of sensor networks is very wide, ranging from monitoring, surveillance, and localization, among others. Localization is a key application in sensor networks and the use of simple, efficient, and distributed algorithms is of paramount practical importance. Combining convex optimization tools with consensus algorithms we propose a distributed localization algorithm for scenarios where received signal strength indicator readings are used. We approach the localization problem by formulating an alternative problem that uses distance estimates locally computed at each node. The formulated problem is solved by a relaxed version using semidefinite relaxation technique. Conditions under which the relaxed problem yields to the same solution as the original problem are given and a distributed consensusbased implementation of the algorithm is proposed based on an augmented Lagrangian approach and primaldual decomposition methods. Although suboptimal, the proposed approach is very suitable for its implementation in real sensor networks, i.e., it is scalable, robust against node failures and requires only local communication among neighboring nodes. Simulation results show that running an additional local search around the found solution can yield performance close to the maximum likelihood estimate.