Angular distributions in tt¯H(H→bb¯) reconstructed events at the LHC

The associated production of a Higgs boson and a top-quark pair, tt¯H, in proton-proton collisions is addressed in this paper for a center of mass energy of 13TeV at the LHC. Dileptonic final states of tt¯H events with two oppositely charged leptons and four jets from the decays t→bW+→bℓ+νℓ, t¯→b¯W−→b¯ℓ−ν¯ℓ and h→bb¯, are used. Signal events, generated with MadGraph5_aMC@NLO, are fully reconstructed by applying a kinematic fit. New angular distributions of the decay products as well as angular asymmetries are explored in order to improve discrimination of tt¯H signal events over the dominant irreducible background contribution, tt¯bb¯. Even after the full kinematic fit reconstruction of the events, the proposed angular distributions and asymmetries are still quite different in the tt¯H signal and the dominant background (tt¯bb¯).

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

Biodiversidad marina en la isla Lobos de Tierra, Perú. 2011

Entre el 29 de setiembre y 3 de octubre 2011, se determinó la estructura de las comunidades, en términos de abundancia relativa, riqueza y diversidad y relación con el medio ambiente de la isla Lobos de Tierra (noreste de isla Rata, El Ñopo y La Grama). En los cálculos de diversidad específi ca se usó métodos uni y multivariados para hacer comparaciones en los lugares estudiados. En la zona mesolitoral se registró alta riqueza específi ca asociada a comunidades de fondos duros destacando el noreste de isla Rata con 58 especies. El grupo dominante fue moluscos en todas las zonas de estudio, sobresaliendo Tegula corvus y Acanthopleura echinata con mayores niveles de abundancia (296 a 412 ind.m-2). El índice de diversidad (H’) promedio por estación mostró valores >1,5 bits/ind en todas las zonas, con valores de dominancia y equitatividad <1,0. En el submareal, la riqueza fue de 124 especies. Los crustáceos y poliquetos tuvieron la mayor riqueza de especies y densidad. Los principales representantes fueron Gammarus sp. (26.607 ind.m-2), Spionidae (2.227 ind.m-2) y Diopatra rhizoicola (2.073 ind.m-2). El índice de diversidad promedio fue 2,2 bits, valor considerado de alta diversidad. La fauna íctica submareal estuvo conformada por 16 especies, destacando los géneros Auchenionchus y Labrisomus y en el intermareal se registraron 7 especies destacando Tomicodon chilensis. Se detectaron 24 especies de macroalgas: Rhodophyta (16 especies), Chlorophyta (5 especies) y Phaeophyta (3 especies), predominó Caulerpa fi liformis (submareal) y Gymnogongrus furcellatus (intermareal).

On the consequences of misspecifing assumptions concerning residuals distribution in a repeated measures and nonlinear mixed modelling context

In this paper we describe the results of a simulation study performed to elucidate the robustness of the Lindstrom and Bates (1990) approximation method under non-normality of the residuals, under different situations. Concerning the fixed effects, the observed coverage probabilities and the true bias and mean square error values, show that some aspects of this inferential approach are not completely reliable. When the true distribution of the residuals is asymmetrical, the true coverage is markedly lower than the nominal one. The best results are obtained for the skew normal distribution, and not for the normal distribution. On the other hand, the results are partially reversed concerning the random effects. Soybean genotypes data are used to illustrate the methods and to motivate the simulation scenarios

Impact of incorrect assumptions on the covariance structure of random effects and/or residuals in nonlinear mixed models for repeated measures data

In this paper we analyse, using Monte Carlo simulation, the possible consequences of incorrect assumptions on the true structure of the random effects covariance matrix and the true correlation pattern of residuals, over the performance of an estimation method for nonlinear mixed models. The procedure under study is the well known linearization method due to Lindstrom and Bates (1990), implemented in the nlme library of S-Plus and R. Its performance is studied in terms of bias, mean square error (MSE), and true coverage of the associated asymptotic confidence intervals. Ignoring other criteria like the convenience of avoiding over parameterised models, it seems worst to erroneously assume some structure than do not assume any structure when this would be adequate.

Correlation between species composition and soil properties in the pastures of Plana de Vic (Catalonia, Spain)

The correlation between the species composition of pasture communities and soil properties in Plana de Vic has been studied using two multivariate methods, Correspondence Analysis (CA) for the vegetation data and Principal Component Analysis (PCA) for the soil data. To analyse the pastures, we took 144 vegetation relevés (comprising 201 species) that have been classified into 10 phytocoenological communities elsewhere. Most of these communities are almost entirely built up by perennials, ranging from xerophilous, clearly Mediterranean, to mesophilous, related to medium-European pastures, but a few occurring in shallow soils are dominated by therophytes. As for the soil properties, we analysed texture, pH, depth, bulk density, organic matter, C/N ratio and the carbonates content of 25 samples, correspondingto representative relevés of the communities studied.

Discovery of a 29-gene panel in peripheral blood mononuclear cells for the detection of colorectal cancer and adenomas using high throughput real-time PCR.

Colorectal cancer (CRC) is the second leading cause of cancer-related death in developed countries. Early detection of CRC leads to decreased CRC mortality. A blood-based CRC screening test is highly desirable due to limited invasiveness and high acceptance rate among patients compared to currently used fecal occult blood testing and colonoscopy. Here we describe the discovery and validation of a 29-gene panel in peripheral blood mononuclear cells (PBMC) for the detection of CRC and adenomatous polyps (AP). Blood samples were prospectively collected from a multicenter, case-control clinical study. First, we profiled 93 samples with 667 candidate and 3 reference genes by high throughput real-time PCR (OpenArray system). After analysis, 160 genes were retained and tested again on 51 additional samples. Low expressed and unstable genes were discarded resulting in a final dataset of 144 samples profiled with 140 genes. To define which genes, alone or in combinations had the highest potential to discriminate AP and/or CRC from controls, data were analyzed by a combination of univariate and multivariate methods. A list of 29 potentially discriminant genes was compiled and evaluated for its predictive accuracy by penalized logistic regression and bootstrap. This method discriminated AP >1cm and CRC from controls with a sensitivity of 59% and 75%, respectively, with 91% specificity. The behavior of the 29-gene panel was validated with a LightCycler 480 real-time PCR platform, commonly adopted by clinical laboratories. In this work we identified a 29-gene panel expressed in PBMC that can be used for developing a novel minimally-invasive test for accurate detection of AP and CRC using a standard real-time PCR platform.

All-sky search algorithms for monochromatic signals in bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

Sellun kuivauskoneen ajettavuusongelman monimuuttujainen tarkastelu

Tässä työssä on tutkittu sellun kuivauskoneella koivusellua kuivattaessa esiintyvää ajettavuusongelmaa. Tähän ongelmaan on etsitty ratkaisua monimuuttujamenetelmien avulla. Työn kirjallisuusosassa on lyhyesti käyty läpi sellun kuivauskoneiden historia lieriöviirakoneista nykyaikaisiin kaksoisviirasovelluksiin. Lisäksi kirjallisuusosassa on käsitelty tässä työssä käytettyjen monimuuttujamenetelmien perusteet ja käyty esimerkin omaisesti läpi joitakin kemometrian sovelluksia puunjalostusteollisuudessa. Työn kokeellisessa osassa on haettu tiedonkeruujärjestelmästä massan ominaisuuksista ja kuivauskoneen ajoparametreistä koostuvaa dataa vuoden 1999 ajalta. Tästä datasta on tehty PCA-mallit vuoden 1999 jokaisen kuukauden datasta ja diskriminoiva PLS-malli ajettavuuden kannalta hyvästä ja huonosta jaksosta koostuvasta datasta. Kuivauskoneelta on koottu dataa myös ottamalla kiertovesi- ja selluarkkinäytteitä. Kiertovesinäytteiden analyysituloksista on tehty PCA-mallit ja lisäksi analyysitulokset on tarkasteltu yksimuuttujaisesti. Selluarkkinäytteistä on määritetty UV-spektrit ja niistä on tehty PCA-mallit, jotta spektreistä saataisiin mahdollisimman paljon informaatiota. Työssä on havaittu yhdeksi selitykseksi ajettavuusongelmalle kuivauskoneen kiertovesien likaantuminen. Kiertovesiä ja massarainan pintakemiaa tulisi kuitenkin tutkia laajemmassa mittakaavassa kuin tämän työn puitteissa on ollut mahdollista tutkia.

A novel approach to the determination of clinical decision thresholds

Our objective was to determine the test and treatment thresholds for common acute primary care conditions. We presented 200 clinicians with a series of web-based clinical vignettes, describing patients with possible influenza, acute coronary syndrome (ACS), pneumonia, deep vein thrombosis (DVT) and urinary tract infection (UTI). We randomly varied the probability of disease and asked whether the clinician wanted to rule out disease, order tests or rule in disease. By randomly varying the probability, we obtained clinical decisions across a broad range of disease probabilities that we used to create threshold curves. For influenza, the test (4.5% vs 32%, p<0.001) and treatment (55% vs 68%, p=0.11) thresholds were lower for US compared with Swiss physicians. US physicians had somewhat higher test (3.8% vs 0.7%, p=0.107) and treatment (76% vs 58%, p=0.005) thresholds for ACS than Swiss physicians. For both groups, the range between test and treatment thresholds was greater for ACS than for influenza (which is sensible, given the consequences of incorrect diagnosis). For pneumonia, US physicians had a trend towards higher test thresholds and lower treatment thresholds (48% vs 64%, p=0.076) than Swiss physicians. The DVT and UTI scenarios did not provide easily interpretable data, perhaps due to poor wording of the vignettes. We have developed a novel approach for determining decision thresholds. We found important differences in thresholds for US and Swiss physicians that may be a function of differences in healthcare systems. Our results can also guide development of clinical decision rules and guidelines.

Laitepuhdistamon ylijäämäliete ja sen kuiva-ainepitoisuuden nostaminen

Työssä tutkittiin pienpuhdistamon ylijäämälietteen ominaisuuksia ja käyttäytymistä pienpuhdistamon ylijäämälietteen tiivistys- tai kuivausmenetelmän kehittämisen teoriapohjaksi. Työ sisältää myös lietteiden tiivistysmenetelmien kustannustarkastelua. Kokeellisessa osuudessa käytettiin työn teettäjän Oy KWH Pipe Ab:n valmistamien pienpuhdistamojen ylijäämälietettä. Tutkittava ylijäämäliete oli peräisin asukasvastineluvultaan 5–95 pienistä aktiivilietelaitepuhdistamoista. Tiivistys- tai kuivausmenetelmän kehittämisen tarkoituksena on saavuttaa kustannussäästöjä pienpuhdistamon ylijäämälietteen kuljetusmatkojen vähentämisen kautta. Soveltuvia vertailtavia sovelluksia ovat staattiseen laskeuttamiseen perustuvat menetelmät, mekaaniset ruuvi- ja linkokuivaimet, kuivauslava ja flotaatio. Tarkasteltavien menetelmien tuli olla käytöltä ja huollolta sekä käyttökuluiltaan edullisia ja yksinkertaisia. Ylijäämälietteiden ominaisuuksia ja käyttäytymistä tutkittiin kirjallisuuslähteistä ja käytännön kokein. Kokeissa tarkasteltiin ylijäämälietteen laskeutumis- ja nousuominaisuuksia, redox-potentiaalin vaihtelua seisovassa näytteessä ja flotaation onnistumista testattavalle lietteelle. Kokeet tehtiin kullakin kerralla eri ajankohtana otetuille lietenäytteille, käytettyjä puhdistamoja oli useita ja mitoitus, kuormitus sekä jäteveden laatu vaihteli paljon.

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Implementação de um método robusto para o controle fiscal de umidade em queijo minas artesanal. Abordagem metrológica multivariada

This study developed and validated a method for moisture determination in artisanal Minas cheese, using near-infrared spectroscopy and partial-least-squares. The model robustness was assured by broad sample diversity, real conditions of routine analysis, variable selection, outlier detection and analytical validation. The model was built from 28.5-55.5% w/w, with a root-mean-square-error-of-prediction of 1.6%. After its adoption, the method stability was confirmed over a period of two years through the development of a control chart. Besides this specific method, the present study sought to provide an example multivariate metrological methodology with potential for application in several areas, including new aspects, such as more stringent evaluation of the linearity of multivariate methods.

Uusperheen voimavarat ja lasten hyvinvointi

The resources of the step family and the children’s well-being The present study investigates children's well-being in stepfamilies and fac¬tors, both external and internal, that are related to the children's well-being. Of the external factors, the study focuses on factors related to the structure of the stepfamily, parents' education, socio-economic status and factors related to work, livelihood and living conditions. The internal resources include the general functioning of the family, parenthood and parenting, family support networks and issues that the stepfamilies themselves consider important. Another important resource in a stepfamily is a functioning network of human relationships, which in the present study is approached from the maternal viewpoint. Changing family relations are considered a potential threat to the children's well-being. Therefore, in addition to looking into the stepfamily's resources, the other important goal of the study is to explore other factors potentially related to the well-being of children living in stepfamilies. In view of the stepfamily's resources, it is important to explore how the functioning of the relationships network is linked with the child's well-being. The study employs survey and interview data. The survey data (n=2236) are part of national survey data on the well-being of families and children and factors impacting them which were gathered as part of ”Origins of Exclusion in Early Childhood”, a research project carried out in 2002. The data consists of 667 stepfamilies. The interview data consists of interviews with 24 parents in stepfamilies. In the study, the analyses of survey and interview data are combined. Both descriptive statistical analyses and multivariate methods are employed. Content analysis is employed in the analysis of the interview data. The results indicate that the stepfamilies’ resources in general but their external resources in particular differed from those of the nuclear and single-parent families. The level of education and the socio-economic status of the stepfamily parents were somewhat lower than those of the nuclear family parents. The differences in relation to single-parent families were primarily related to the better economic status of the stepfamilies. The analysis of internal resources showed relatively minor differences: the stepfamilies assessed themselves a somewhat better general functioning of the family than did the nuclear families. Parenting issues caused more disagreement in stepfamilies than in nuclear families. The analysis of the functioning of the human relations in stepfamilies showed that the stepfamily mothers experienced the external relationships of the family (e.g., between the child and the absent father) as significantly more problematic than the relationships within the stepfamily. Living in a stepfamily thus challenges the functioning of the relationship between the child and the absent father. As a result of the analysis of the relationships networks in the stepfamilies, three groups were formed. One group had the nuclear family as an ideal goal, another valued an extended family composed of a variety of relationships, and the third one appreciated a strong intimate relationship between the parents. In the present study, the most common group was the multi-relationship, extended type of stepfamily. In conclusion, living in a stepfamily does not seem to pose a risk to the child’s well-being, but it may influence the family’s resources and thus have an indirect effect on the child’s well-being. In view of the resources of the stepfamily, the child’s well-being was best supported by a functioning network of human relationships in the stepfamily: there was a distinct connection with the children’s problems and the non-functioning of the relationships network. According to the mothers, the internal relationships in the stepfamily seemed to be more important than the external relationships of the family. A child’s functioning relationship with the absent father can be viewed as a positive resource, supporting the child’s well-being in the stepfamily.