An Algerian Phacopid fauna, described by Lemaître in 1952, is reexamined here. Species arereevaluated in order to be in agreement with modern taxonomy. To characterize the size and shape of our specimens, as well as inter- and intraspecific variations, a morphometric analysis was performed. Only holaspids were analyzed. Results of our analysis show that genera can be be well differentiated thanks to quantitative methods. However, at a specific level, only Austerops lemaitrii nov. sp. is well- defined. Other species can be defined, however, thanks to quantitative methods. Shape variations during growth were also defined in order to understand the evolution of our specimens. Three species show a correlation between shape and size variations for cephala, and two species for the pygidia, which show an ontogenic control of the shape. A covariate analysis was made between the shape of the cephala and the shape of the pygidia, and all of the specimens analyzed show a covariance betweencephalic and pygidial shape. / Trilobiter utgjorde en viktig del av faunun under paleozoikum. I denna artikel studeras ochomprövas en trilobitpopulation från Algeriets devon. För att bättre förstå populationstillväxt och evolution görs analyser av storlek (biometrisk analys) och form (morfometrisk analys). Resultaten visar att de olika släktena är väldefinierade och att tillväxten av somliga arter påverkar formen.Analysen visar också på en samvariation mellan cephalons och pygidiums form.

As the main component of terrestrial energy and water balance, evapotranspiration (ET) moves a large amount of water and energy in the form of latent heat flux from bare soil and vegetated surfaces into the atmosphere. Despite the development of many methods and equations through past decades, accurate ET estimation is still a challenging task, especially for the Red River Valley of the North (RRV) that has limited updated information on ET either for landscape or agricultural water management. The overall objective of first study was to evaluate the ASCE-EWRI reference ET (ETo) method by developing an accurate crop coefficient (Kc) using an eddy covariance (EC) system over an unirrigated turfgrass site. The results showed that with mean ETgrass/ETo ratio as 0.96 for the entire growing seasons of turfgrass, the ASCE-EWRI ETo method is valid for guiding the turfgrass irrigation management in cold climate conditions. In a Controlled drainage with subirrigation (CD+SI) field, an EC system was used to measure and quantify energy flux components along with soil water content (SWC) and water table depth (WTD) measurements during four corn growing. This study showed that the subsurface drainage along with the CD + SI system can be used for optimal water management with an improvement of 26.7% and 6.6% of corn yield during wet and dry year, respectively. For the final task, ET was measured using EC, Bowen ratio system (BREB), and soil water balance (SWB) method during the corn growing season. The comparison of the EC and the BREB system illustrated the advantages of using the residual method to close the energy balance closure of EC. Among the different time approaches for SWB method, ET by the SWB method using the average soil water contents between 24:00 to 2:00 time period showed non-significant differences (alpha = 0.05) compared to the BREB system during the observation periods. / USDA National Institute of Food and Agriculture project / USDA NCR SARE project / ND Soybean Council / ND Water Resources Research Institute / ND Agricultural Experimental Station / USDA Hatch project / NASA ROSES Project

Dans cette thèse nous nous intéressons au modèle linéaire général (modèle linéaire multivarié) en grande dimension. Nous proposons un nouvel estimateur parcimonieux des coefficients de ce modèle qui prend en compte la dépendance qui peut exister entre les différentes réponses. Cet estimateur est obtenu en estimant dans un premier temps la matrice de covariance des réponses puis en incluant cette matrice de covariance dans un critère Lasso. Les propriétés théoriques de cet estimateur sont étudiées lorsque le nombre de réponses peut tendre vers l’infini plus vite que la taille de l’échantillon. Plus précisément, nous proposons des conditions générales que doivent satisfaire les estimateurs de la matrice de covariance et de son inverse pour obtenir la consistance en signe des coefficients. Nous avons ensuite mis en place des méthodes, adaptées à la grande dimension, pour l’estimation de matrices de covariance qui sont supposées être des matrices de Toeplitz ou des matrices avec une structure par blocs, pas nécessairement diagonaux. Ces différentes méthodes ont enfin été appliquées à des problématiques de métabolomique, de protéomique et d’immunologie. / In this PhD thesis we study general linear model (multivariate linearmodel) in high dimensional settings. We propose a novel variable selection approach in the framework of multivariate linear models taking into account the dependence that may exist between the responses. It consists in estimating beforehand the covariance matrix of the responses and to plug this estimator in a Lasso criterion, in order to obtain a sparse estimator of the coefficient matrix. The properties of our approach are investigated both from a theoretical and a numerical point of view. More precisely, we give general conditions that the estimators of the covariance matrix and its inverse have to satisfy in order to recover the positions of the zero and non-zero entries of the coefficient matrix when the number of responses is not fixed and can tend to infinity. We also propose novel, efficient and fully data-driven approaches for estimating Toeplitz and large block structured sparse covariance matrices in the case where the number of variables is much larger than the number of samples without limiting ourselves to block diagonal matrices. These approaches are appliedto different biological issues in metabolomics, in proteomics and in immunology.

Evapotranspiration (ET) of center pivot irrigated alfalfa was studied in the windy, arid, Curlew Valley, Northern Box Elder County, Utah, during the summers of 2009 and 2010. ET was estimated using eddy covariance (EC) and surface renewal (SR) techniques. ET estimates from the EC and SR analyses were compared with estimates using ASCE Standardized Reference ET Equation, with both dual and mean crop coefficients. EC energy balance closure was 0.80, on average, in 2009 and 0.76 in 2010. The SR weighting parameter (α) was calculated through linear regression of EC and SR sensible heat flux estimates. Alpha was found to be 0.70 if EC energy balance closure was forced and 0.55 if closure was not forced. ET from SR analysis with α = 0.70 (ETSRα=0.70) was 409 mm in 2009 and 331 mm in 2010. ET from EC analysis with forced closure (ETECforced) was 390 mm in 2009 and 326 mm in 2010. In contrast, ETSRα=0.55 was 408 and 333 mm in 2009 and 2010, respectively, while ETECunforced was 315 and 251 mm in 2009 and 2010, respectively. Combined ETECforced and ETSRforced were compared with estimated crop ET from the ASCE Std. Eq. with both dual and mean crop coefficients (ETcDual and ETcm, respectively). ETcDual was 689 mm in 2009, as compared to ETcm and ETEC-SRforced, which were 677 and 617 mm, respectively. In 2010 ETcDual was 674 mm, with ETcm and ETEC-SRforced being 629 and 576 mm, respectively. The Kcm approach more closely approximated the estimated wet soil evaporation determined from the ETEC-SRforced for the measurement conditions and stated assumptions. ETEC-SR estimates were compared with irrigation application information to approximate field scale water balances. Effective precipitation plus net irrigation application (less wind drift and evaporation) were nearly equal to ETEC-SRforced for 2nd and 3rd crops of alfalfa in 2009 and 2010. No deep percolation was calculated using ETEC-SRforced; however, soil moisture measurements were not sufficient to verify that this was true. The water balances suggested that the fields were being underirrigated which may have caused salt accumulation in the soil, as evidenced by the low reported yields.

A project report submitted to the Faculty of Engineering, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for 'the degree of Master of Science in Engineering. Johannesburg 1991. / The report describes the design of an algorithm which can be used for automatic controller tuning purposes. It uses an on-line parameter estimator and a pole assignrnent design method. The resulting control law is formulated to approximate a proportional-integral (PI) industrial controller. The development ofthe algorithm is based on the delta-operator, Some implementation aspects such as covariance resetting, dead zone, and signal conditioning are also discussed. Robust stability and performance are two issues that govern the design approach. Additionally transient and steady state system response criteria are utilized from the time and frequency domains. The design work is substantiated with the use of simulation and real plant tests. / AC2017

Testing the equality between two high-dimensional covariance matrices is challenging. As the most efficient way to measure evidential discrepancies in observed data, the likelihood ratio test is expected to be powerful when the null hypothesis is violated. However, when the data dimensionality becomes large and potentially exceeds the sample size by a substantial margin, likelihood ratio based approaches face practical and theoretical challenges. To solve this problem, this study proposes a method by which we first randomly project the original high-dimensional data into lower-dimensional space, and then apply the corrected likelihood ratio tests developed with random matrix theory. We show that testing with a single random projection is consistent under the null hypothesis. Through evaluating the power function, which is challenging in this context, we provide evidence that the test with a single random projection based on a random projection matrix with reasonable column sizes is more powerful when the two covariance matrices are unequal but component-wise discrepancy could be small -- a weak and dense signal setting. To more efficiently utilize this data information, we propose combined tests from multiple random projections from the class of meta-analyses. We establish the foundation of the combined tests from our theoretical analysis that the p-values from multiple random projections are asymptotically independent in the high-dimensional covariance matrices testing problem. Then, we show that combined tests from multiple random projections are consistent under the null hypothesis. In addition, our theory presents the merit of certain meta-analysis approaches over testing with a single random projection. Numerical evaluation of the power function of the combined tests from multiple random projections is also provided based on numerical evaluation of power function of testing with a single random projection. Extensive simulations and two real genetic data analyses confirm the merits and potential applications of our test. / Statistics

No description available.

Establishing secret keys from the commonly-observed randomness of reciprocal wireless propagation channels has recently received considerable attention. In this work we propose improved strategies for channel estimation between MIMO or beamforming systems for secret key generation. The amount of mutual information that can be extracted from the channel matrix estimates is determined by the quality of channel matrix estimates. By allocating increased energy to channel estimation for higher gain beamforming combinations at the expense of low-gain combinations, key establishment performance can be increased. Formalizing the notion of preferential energy allocation to the most efficient excitations is the central theme of this dissertation. For probing with beamforming systems, we formulate a theoretically optimal probing strategy that upper bounds the number of key bits that can be generated from reciprocal channel observations. Specifically, we demonstrate that the eigenvectors of the channel spatial covariance matrix should be used as beamformer weights during channel estimation and we optimize the energy allocated to channel estimation for each beamformer weight under a total energy constraint. The optimal probing strategy is not directly implementable in practice, and therefore we propose two different modifications to the optimal algorithm based on a Kronecker approximation to the spatial covariance matrix. Though these approximations are suboptimal, they each perform well relative to the upper bound. To explore how effective an array is at extracting all of the information available in the propagation environment connecting two nodes, we apply the optimal beamformer probing strategy to a vector current basis function expansion on the array volume. We prove that the resulting key rate is a key rate spatial bound that upper bounds the key rate achievable by any set of antenna arrays probing the channel with the same total energy constraint. For MIMO systems we assume the channel is separable with a Kronecker model, and then for that model we propose an improved probing strategy that iteratively optimizes the energy allocation for each node using concave maximization. The performance of this iterative approach is better than that achieved using the traditional probing strategy in many realistic probing scenarios.

Plantation and managed forests are major sink of atmospheric CO2 in North America and across the world. If properly managed, these forests may help to offset anthropogenic greenhouse gas emissions to mitigate climate change. This study investigated the impacts of climate variability, extreme weather events, and disturbance (thinning) on the growth and carbon (C) exchanges of a young temperate coniferous plantation forest (48-year-old white pine (Pinus strobus)) in the Great Lakes region in Canada using long-term eddy covariance flux observations. CO2 fluxes, as well as meteorological and soil variables were continuously measured from 2008 to 2021 (14 years) to estimate net ecosystem productivity (NEP), ecosystem respiration (RE), and gross ecosystem productivity (GEP). Soil respiration (Rs) was also measured using automatic soil chambers from 2017 to 2019. Selective thinning was conducted first time in this stand in January 2021 to remove approximately 1/3 of the basal area. Study results showed that climate conditions in the early growing season, from late May to mid-July, determined the overall strength of C uptake in any given year. However, above-average temperature and precipitation in the late growing season significantly reduced NEP and even in some cases, transformed the forest into a net C source for short periods due to large pulses of RE. Mean annual GEP, RE and NEP values were 1660 ±199, 1087 ±96 and 592 ±169 g C m-2 yr-1, respectively, from 2008 to 2021. Thinning did not significantly impact the C uptake of the forest as the stand remained a net C sink with an annual NEP of 648 g C m-2 yr-1 in 2021. Changes in annual GEP, RE and NEP in 2021 remained within the range of interannual variability over the study period. Overall, Rs accounted for roughly 89% of the annual RE in this stand. A complete understanding of the response of forest C dynamics to climate variability and thinning in young plantation forests is critical to guiding future forest management efforts for enhancing the growth and C uptake of these forest plantations to maximize their potential in support of providing nature-based climate solutions. / Thesis / Master of Science (MSc)

In many applications, the quality of process outputs is described by more than one characteristic variable. These quality variables usually follow a multivariate normal (MN) distribution. This dissertation discusses the monitoring of the mean vector and the covariance matrix of MN processes. The first part of this dissertation develops a statistical process control (SPC) chart based on a generalized likelihood ratio (GLR) statistic to monitor the mean vector. The performance of the GLR chart is compared to the performance of the Hotelling Χ² chart, the multivariate exponentially weighted moving average (MEWMA) chart, and a multi-MEWMA combination. Results show that the Hotelling Χ² chart and the MEWMA chart are only effective for a small range of shift sizes in the mean vector, while the GLR chart and some carefully designed multi-MEWMA combinations can give similarly better overall performance in detecting a wide range of shift magnitudes. Unlike most of these other options, the GLR chart does not require specification of tuning parameter values by the user. The GLR chart also has the advantage in process diagnostics: at the time of a signal, estimates of change-point and out-of-control mean vector are immediately available to the user. All these advantages of the GLR chart make it a favorable option for practitioners. For the design of the GLR chart, a series of easy to use equations are provided to users for calculating the control limit to achieve the desired in-control performance. The use of this GLR chart with a variable sampling interval (VSI) scheme has also been evaluated and discussed. The rest of the dissertation considers the problem of monitoring the covariance matrix. Three GLR charts with different covariance matrix estimators have been discussed. Results show that the GLR chart with a multivariate exponentially weighted moving covariance (MEWMC) matrix estimator is slightly better than the existing method for detecting any general changes in the covariance matrix, and the GLR chart with a constrained maximum likelihood estimator (CMLE) gives much better overall performance for detecting a wide range of shift sizes than the best available options for detecting only variance increases. / Ph. D.