ECG component delineation by Prony's method

A simple, non-iterative method for component wave delineation from the electrocardiogram (ECG) is derived by modelling its discrete cosine transform (DCT) as a sum of damped cosinusoids. Amplitude, phase, damping factor and frequency parameters of each of the cosinusoids are estimated by the extended Prony method. Different component waves are represented by non-overlapping clusters of model poles in the z plane and thus a component wave is derived by the addition of the inverse transformed (IDCT) impulse responses of the poles in the cluster. Akaike's information criterion (AIC) is used to determine the model order. The method performed satisfactory even in the presence of artifacts. The efficacy of the method is illustrated by analysis of continuous strips of ECG data.

Statistical analysis of synthetic earthquake catalogs generated by models with various levels of fault zone disorder

The stress release model, a stochastic version of the elastic rebound theory, is applied to the large events from four synthetic earthquake catalogs generated by models with various levels of disorder in distribution of fault zone strength (Ben-Zion, 1996) They include models with uniform properties (U), a Parkfield-type asperity (A), fractal brittle properties (F), and multi-size-scale heterogeneities (M). The results show that the degree of regularity or predictability in the assumed fault properties, based on both the Akaike information criterion and simulations, follows the order U, F, A, and M, which is in good agreement with that obtained by pattern recognition techniques applied to the full set of synthetic data. Data simulated from the best fitting stress release models reproduce, both visually and in distributional terms, the main features of the original catalogs. The differences in character and the quality of prediction between the four cases are shown to be dependent on two main aspects: the parameter controlling the sensitivity to departures from the mean stress level and the frequency-magnitude distribution, which differs substantially between the four cases. In particular, it is shown that the predictability of the data is strongly affected by the form of frequency-magnitude distribution, being greatly reduced if a pure Gutenburg-Richter form is assumed to hold out to high magnitudes.

Fracture statistics of brittle materials: Weibull or normal distribution

The fit of fracture strength data of brittle materials (Si3N4, SiC, and ZnO) to the Weibull and normal distributions is compared in terms of the Akaike information criterion. For Si3N4, the Weibull distribution fits the data better than the normal distribution, but for ZnO the result is just the opposite. In the case of SiC, the difference is not large enough to make a clear distinction between the two distributions. There is not sufficient evidence to show that the Weibull distribution is always preferred to other distributions, and the uncritical use of the Weibull distribution for strength data is questioned.

Influence of threshold stress on the estimation of the Weibull statistics

The influence of threshold stress on the estimation of the Weibull statistics is discussed in terms of the Akaike information criterion. Numerical simulations show that, if sample data are limited in number and threshold stress is not too large, the two-parameter Weibull distribution is still a preferred choice. For example, the fit of strength data of glass and ceramics to the two- and three-parameter Weibull distributions is compared.

The degree of predictability of earthquakes in several regions of China: statistical analysis of historical data

The stress release model, a stochastic version of the elastic-rebound theory, is applied to the historical earthquake data from three strong earthquake-prone regions of China, including North China, Southwest China, and the Taiwan seismic regions. The results show that the seismicity along a plate boundary (Taiwan) is more active than in intraplate regions (North and Southwest China). The degree of predictability or regularity of seismic events in these seismic regions, based on both the Akaike information criterion (AIC) and fitted sensitivity parameters, follows the order Taiwan, Southwest China, and North China, which is further identified by numerical simulations. (c) 2004 Elsevier Ltd. All rights reserved.

Multi-model inference ranking and applications to physics at the Large Hadron Collider

In the measurement of the Higgs Boson decaying into two photons the parametrization of an appropriate background model is essential for fitting the Higgs signal mass peak over a continuous background. This diphoton background modeling is crucial in the statistical process of calculating exclusion limits and the significance of observations in comparison to a background-only hypothesis. It is therefore ideal to obtain knowledge of the physical shape for the background mass distribution as the use of an improper function can lead to biases in the observed limits. Using an Information-Theoretic (I-T) approach for valid inference we apply Akaike Information Criterion (AIC) as a measure of the separation for a fitting model from the data. We then implement a multi-model inference ranking method to build a fit-model that closest represents the Standard Model background in 2013 diphoton data recorded by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC). Potential applications and extensions of this model-selection technique are discussed with reference to CMS detector performance measurements as well as in potential physics analyses at future detectors.

Gear modifications for fishing octopus, Octopus vulgaris, on live-bottom and adjacent flat bottom habitats in coastal waters off North Carolina

The Common Octopus, Octopus vulgaris, is an r-selected mollusk found off the coast of North Carolina that interests commercial fishermen because of its market value and the cost-effectiveness of unbaited pots that can catch it. This study sought to: 1) determine those gear and environmental factors that influenced catch rates of octopi, and 2) evaluate the feasibility of small-scale commercial operations for this species. Pots were fished from August 2010 through September 2011 set in strings over hard and sandy bottom in waters from 18 to 30 m deep in Onslow Bay, N.C. Three pot types were fished in each string; octopus pots with- and without lids, and conch pots. Proportional catch was modeled as a function of gear design and environmental factors (location, soak time, bottom type, and sea surface water temperature) using binomially distributed generalized linear models (GLM’s); parsimony of each GLM was assessed with Akaike Information Criteria (AIC). A total of 229 octopi were caught throughout the study. Pots with lids, pots without lids, and conch pots caught an average of 0.15, 0.17, and 0.11 octopi, respectively, with high variability in catch rates for each pot type. The GLM that best fit the data described proportional catch as a function of sea surface temperature, soak time, and station; greatest proportional catches occurred over short soak times, warmest temperatures, and less well known reef areas. Due to operating expenses (fuel, crew time, and maintenance), low catch rates of octopi, and high gear loss, a directed fishery for this species is not economically feasible at the catch rates found in this study. The model fitting to determine factors most influential on catch rates should help fishermen determine seasons and gear soak times that are likely to maximize catch rates. Potting for octopi may be commercially practical as a supplemental activity when targeting demersal fish species that are found in similar habitats and depth ranges in coastal waters off North Carolina.

An environmentally based growth model that uses finite difference calculus with maximum likelihood method: its application to the brackish water bivalve Corbicula japonica in Lake Abashiri, Japan

We present a growth analysis model that combines large amounts of environmental data with limited amounts of biological data and apply it to Corbicula japonica. The model uses the maximum-likelihood method with the Akaike information criterion, which provides an objective criterion for model selection. An adequate distribution for describing a single cohort is selected from available probability density functions, which are expressed by location and scale parameters. Daily relative increase rates of the location parameter are expressed by a multivariate logistic function with environmental factors for each day and categorical variables indicating animal ages as independent variables. Daily relative increase rates of the scale parameter are expressed by an equation describing the relationship with the daily relative increase rate of the location parameter. Corbicula japonica grows to a modal shell length of 0.7 mm during the first year in Lake Abashiri. Compared with the attain-able maximum size of about 30 mm, the growth of juveniles is extremely slow because their growth is less susceptible to environmental factors until the second winter. The extremely slow growth in Lake Abashiri could be a geographical genetic variation within C. japonica.

Optymalizacja metod analizy Főrsterowskiego rezonansowego przeniesienia energii (FRET) pojedynczych cząsteczek

Wydział Chemii: Zakład Chemii Fizycznej

Los contratistas de cosecha de plantaciones forestales : análisis de las funciones de producción y de la influencia de la innovación tecnológica como factor en las mismas

La cosecha de plantaciones forestales ha crecido sostenidamente en Sudamérica en los últimos años. Esta se desarrolla mayoritariamente con empresas contratistas, que abastecen plantas industriales. Esta Tesis tiene por objetivos analizar por medio de funciones de producción y de la innovación, las empresas contratistas de cosecha en Misiones y Corrientes (Argentina), Paraná, Santa Catarina y Rio Grande do Sul (Brasil), y Uruguay. Los datos fueron obtenidos por encuestas personalizadas: 22 en Argentina, 35 en Brasil, y 10 en Uruguay, entre 2008 y 2012. Se evaluaron modelos de costos y producción. El crecimiento de las empresas fue analizado con modelos lineales mixtos. La producción relevada fue de 17,7 millones de metros cúbicos, (58,3 por ciento del total regional). Los modelos de producción del tipo Cobb-Douglas, mostraron muy alta necesidad de capital al inicio, con un cambio a partir de las 50.000 t/mes, y fueron asintóticos desde las 100.000 t/mes. Los contratistas en Argentina produjeron en promedio 13.636 t/mes, con 30,7 empleados por empresa. En Brasil, produjeron 25.649t/mes, con 65,12 empleados. Los modelos de costo por tonelada resultaron en 5,82 US$/t para 18.000 t/mes para Argentina. En Brasil el costo mínimo fue de 11,23 US$/t para 25.000 t/mes. En Uruguay fue de 18,43 US$/t para 15.000 t/mes. En los tres países existió preponderancia de contratos con celulósicas. No se encontró ninguna contratista que desarrolle los indicadores de producción o de costo por tonelada que obtuvieron estas empresas mutualistas. En los análisis de producción de los últimos 10 años, fueron significativos el número de empleados, y la mecanización. Cuando se consideraron la capacidad de hacer negocios y la innovación, fue solo significativa esta última. La inclusión de las variables aleatorias, país y edad de la empresa, produjo mejores AIC (Akaike Information Criterion). En el análisis del crecimiento de las empresas en los últimos 10 años, resultaron significativos el capital y el número de empleados. En los últimos 5 años, ocurrió lo contrario, fueron significativas la innovación y la capacidad de hacer negocios. Se puede concluir que el capital es el principal factor para predecir la capacidad productiva de una contratista. Existen diferencias de escala entre las empresas de los tres países, así como en los sectores de cada país. A los largo de los últimos 10 años, las empresas han ido creciendo basándose en diferentes estrategias, al principio en capital y empleados, y últimamente en la capacidad de hacer negocios y en la innovación. Sudamérica, Cosecha forestal.

Bivariate distribution modeling with tree diameter and height data

The Logit-Logistic (LL), Johnson's SB, and the Beta (GBD) are flexible four-parameter probability distribution models in terms of the (skewness-kurtosis) region covered, and each has been used for modeling tree diameter distributions in forest stands. This article compares bivariate forms of these models in terms of their adequacy in representing empirical diameter-height distributions from 102 sample plots. Four bivariate models are compared: SBB, the natural, well-known, and much-used bivariate generalization of SB; the bivariate distributions with LL, SB, and Beta as marginals, constructed using Plackett's method (LL-2P, etc.). All models are fitted using maximum likelihood, and their goodness-of-fits are compared using minus log-likelihood (equivalent to Akaike's Information Criterion, the AIC). The performance ranking in this case study was SBB, LL-2P, GBD-2P, and SB-2P

Channel characterization for single- and multiple-antenna wearable systems used for indoor body-to-body communications

In this paper, an analysis of radio channel characteristics for single- and multiple-antenna bodyworn systems for use in body-to-body communications is presented. The work was based on an extensive measurement campaign conducted at 2.45 GHz representative of an indoor sweep and search scenario for fire and rescue personnel. Using maximum-likelihood estimation in conjunction with the Akaike information criterion (AIC), five candidate probability distributions were investigated and from these the kappa - mu distribution was found to best describe small-scale fading observed in the body-to-body channels. Additional channel parameters such as autocorrelation and the cross-correlation coefficient between fading signal envelopes were also analyzed. Low cross correlation and small differences in mean signal levels between potential dual-branch diversity receivers suggested that the prospect of successfully implementing diversity in this type application is extremely good. Moreover, using selection combination, maximal ratio, and equal gain combining, up to 8.69-dB diversity gain can be made available when four spatially separated antennas are used at the receiver. Additional improvements in the combined envelopes through lower level crossing rates and fade durations at low signal levels were also observed.

An experimental investigation into the influence of user state and environment on fading characteristics in wireless body area networks at 2.45 GHz

Using seven strategically placed, time-synchronized bodyworn receivers covering the head, upper front and back torso, and the limbs, we have investigated the effect of user state: stationary or mobile and local environment: anechoic chamber, open office area and hallway upon first and second order statistics for on-body fading channels. Three candidate models were considered: Nakagami, Rice and lognormal. Using maximum likelihood estimation and the Akaike information criterion it was established that the Nakagami-m distribution best described small-scale fading for the majority of on-body channels over all the measurement scenarios. When the user was stationary, Nakagami-m parameters were found to be much greater than 1, irrespective of local surroundings. For mobile channels, Nakagami-m parameters significantly decreased, with channels in the open office area and hallway experiencing the worst fading conditions.

Role of Predalors, Habitat Attributes, and Spatial Autocorrelation on the Distribution of Eggs in the Northern Spectacled Salamander (Salamandrina perspicillata)

We predicted that the probability of egg occurrence of salamander Salamandrina perspicillata depended on stream features and predation by native crayfish Austropotamobius fulcisianus and the introduced trout Salmo trutta. We assessed the presence of S. perspicillata at 54 sites within a natural reserve of southern Tuscany, Italy. Generalized linear models with binomial errors were constructed using egg presence/absence and altitude, stream mean size and slope, electrical conductivity, water pH and temperature, and a predation factor, defined according to the presence/absence of crayfish and trout. Some competing models also included an autocovariate term, which estimated how much the response variable at any one sampling point reflected response values at surrounding points. The resulting models were compared using Akaike's information criterion. Model selection led to a subset of 14 models with Delta AIC(c) <7 (i.e., models ranging from substantial support to considerably less support), and all but one of these included an effect of predation. Models with the autocovariate term had considerably more support than those without the term. According to multimodel inference, the presence of trout and crayfish reduced the probability of egg occurrence from a mean level of 0.90 (SE limits: 0.98-0.55) to 0.12 (SE limits: 0.34-0.04). The presence of crayfish alone had no detectable effects (SE limits: 0.86-0.39). The results suggest that introduced trout have a detrimental effect on the reproductive output of S. perspicillata and confirm the fundamental importance of distinguishing the roles of endogenous and exogenous forces that act on population distribution.

Testing metabolic scaling theory using intraspecific allometries in Antarctic microarthropods

Quantitative scaling relationships among body mass, temperature and metabolic rate of organisms are still controversial, while resolution may be further complicated through the use of different and possibly inappropriate approaches to statistical analysis. We propose the application of a modelling strategy based on the theoretical approach of Akaike's information criteria and non-linear model fitting (nlm). Accordingly, we collated and modelled available data at intraspecific level on the individual standard metabolic rate of Antarctic microarthropods as a function of body mass (M), temperature (T), species identity (S) and high rank taxa to which species belong (G) and tested predictions from metabolic scaling theory (mass-metabolism allometric exponent b = 0.75, activation energy range 0.2-1.2 eV). We also performed allometric analysis based on logarithmic transformations (lm). Conclusions from lm and nlm approaches were different. Best-supported models from lm incorporated T, M and S. The estimates of the allometric scaling exponent linking body mass and metabolic rate resulted in a value of 0.696 +/- 0.105 (mean +/- 95% CI). In contrast, the four best-supported nlm models suggested that both the scaling exponent and activation energy significantly vary across the high rank taxa (Collembola, Cryptostigmata, Mesostigmata and Prostigmata) to which species belong, with mean values of b ranging from about 0.6 to 0.8. We therefore reached two conclusions: 1, published analyses of arthropod metabolism based on logarithmic data may be biased by data transformation; 2, non-linear models applied to Antarctic microarthropod metabolic rate suggest that intraspecific scaling of standard metabolic rate in Antarctic microarthropods is highly variable and can be characterised by scaling exponents that greatly vary within taxa, which may have biased previous interspecific comparisons that neglected intraspecific variability.