944 resultados para least mean-square methods


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Introduction: Prior repeated-sprints (6) has become an interesting method to resolve the debate surrounding the principal factors that limits the oxygen uptake (V'O2) kinetics at the onset of exercise [i.e., muscle O2 delivery (5) or metabolic inertia (3)]. The aim of this study was to compare the effects of two repeated-sprints sets of 6x6s separated by different recovery duration between the sprints on V'O2 and muscular de-oxygenation [HHb] kinetics during a subsequent heavy-intensity exercise. Methods: 10 male subjects performed a 6-min constant-load cycling test (T50) at intensity corresponding to half of the difference between V'O2max and the ventilatory threshold. Then, they performed two repeated-sprints sets of 6x6s all-out separated by different recovery duration between the sprints (S1:30s and S2:3min) followed, after 7-min-recovery, by the T50 (S1T50 and S2T50, respectively). V'O2, [HHb] of the vastus lateralis (VL) and surface electromyography activity [i.e., root-mean-square (RMS) and the median frequency of the power density spectrum (MDF)] from VL and vastus medialis (VM) were recorded throughout T50. Models using a bi-exponential function for the overall T50 and a mono-exponential for the first 90s of T50 were used to define V'O2 and [HHb] kinetics respectively. Results: V'O2 mean value was higher in S1 (2.9±0.3l.min-1) than in S2 (1.2±0.3l.min-1); (p<0.001). The peripheral blood flow was increased after sprints as attested by a higher basal heart rate (HRbaseline) (S1T50: +22%; S2T50: +17%; p≤0.008). Time delay [HHb] was shorter for S1T50 and S2T50 than for T50 (-22% for both; p≤0.007) whereas the mean response time of V'O2 was accelerated only after S1 (S1T50: 32.3±2.5s; S2T50: 34.4±2.6s; T50: 35.7±5.4s; p=0.031). There were no significant differences in RMS between the three conditions (p>0.05). MDF of VM was higher during the first 3-min in S1T50 than in T50 (+6%; p≤0.05). Conclusion: The study show that V'O2 kinetics was speeded by prior repeated-sprints with a short (30s) but not a long (3min) inter-sprints-recovery even though the [HHb] kinetics was accelerated and the peripheral blood flow was enhanced after both sprints. S1, inducing a greater PCr depletion (1) and change in the pattern of the fibres recruitment (increase in MDF) compared with S2, may decrease metabolic inertia (2), stimulate the oxidative phosphorylation activation (4) and accelerate V'O2 kinetics at the beginning of the subsequent high-intensity exercise.

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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

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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.

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Soil organic matter (SOM) plays an important role in carbon (C) cycle and soil quality. Considering the complexity of factors that control SOM cycling and the long time it usually takes to observe changes in SOM stocks, modeling constitutes a very important tool to understand SOM cycling in forest soils. The following hypotheses were tested: (i) soil organic carbon (SOC) stocks would be higher after several rotations of eucalyptus than in low-productivity pastures; (ii) SOC values simulated by the Century model would describe the data better than the mean of observations. So, the aims of the current study were: (i) to evaluate the SOM dynamics using the Century model to simulate the changes of C stocks for two eucalyptus chronosequences in the Rio Doce Valley, Minas Gerais State, Brazil; and (ii) to compare the C stocks simulated by Century with the C stocks measured in soils of different Orders and regions of the Rio Doce Valley growing eucalyptus. In Belo Oriente (BO), short-rotation eucalyptus plantations had been cultivated for 4.0; 13.0, 22.0, 32.0 and 34.0 years, at a lower elevation and in a warmer climate, while in Virginópolis (VG), these time periods were 8.0, 19.0 and 33.0 years, at a higher elevation and in a milder climate. Soil samples were collected from the 0-20 cm layer to estimate C stocks. Results indicate that the C stocks simulated by the Century model decreased after 37 years of poorly managed pastures in areas previously covered by native forest in the regions of BO and VG. The substitution of poorly managed pastures by eucalyptus in the early 1970´s led to an average increase of C of 0.28 and 0.42 t ha-1 year-1 in BO and VG, respectively. The measured C stocks under eucalyptus in distinct soil Orders and independent regions with variable edapho-climate conditions were not far from the values estimated by the Century model (root mean square error - RMSE = 20.9; model efficiency - EF = 0.29) despite the opposite result obtained with the statistical procedure to test the identity of analytical methods. Only for lower soil C stocks, the model over-estimated the C stock in the 0-20 cm layer. Thus, the Century model is highly promising to detect changes in C stocks in distinct soil orders under eucalyptus, as well as to indicate the impact of harvest residue management on SOM in future rotations.

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In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

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BACKGROUND: In a simulation based on a pharmacokinetic model we demonstrated that increasing the erythropoiesis stimulating agents (ESAs) half-life or shortening their administration interval decreases hemoglobin variability. The benefit of reducing the administration interval was however lessened by the variability induced by more frequent dosage adjustments. The purpose of this study was to analyze the reticulocyte and hemoglobin kinetics and variability under different ESAs and administration intervals in a collective of chronic hemodialysis patients. METHODS: The study was designed as an open-label, randomized, four-period cross-over investigation, including 30 patients under chronic hemodialysis at the regional hospital of Locarno (Switzerland) in February 2010 and lasting 2 years. Four subcutaneous treatment strategies (C.E.R.A. every 4 weeks Q4W and every 2 weeks Q2W, Darbepoetin alfa Q4W and Q2W) were compared with each other. The mean square successive difference of hemoglobin, reticulocyte count and ESAs dose was used to quantify variability. We distinguished a short- and a long-term variability based respectively on the weekly and monthly successive difference. RESULTS: No difference was found in the mean values of biological parameters (hemoglobin, reticulocytes, and ferritin) between the 4 strategies. ESAs type did not affect hemoglobin and reticulocyte variability, but C.E.R.A induced a more sustained reticulocytes response over time and increased the risk of hemoglobin overshooting (OR 2.7, p = 0.01). Shortening the administration interval lessened the amplitude of reticulocyte count fluctuations but resulted in more frequent ESAs dose adjustments and in amplified reticulocyte and hemoglobin variability. Q2W administration interval was however more favorable in terms of ESAs dose, allowing a 38% C.E.R.A. dose reduction, and no increase of Darbepoetin alfa. CONCLUSIONS: The reticulocyte dynamic was a more sensitive marker of time instability of the hemoglobin response under ESAs therapy. The ESAs administration interval had a greater impact on hemoglobin variability than the ESAs type. The more protracted reticulocyte response induced by C.E.R.A. could explain both, the observed higher risk of overshoot and the significant increase in efficacy when shortening its administration interval.Trial registrationClinicalTrials.gov NCT01666301.

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This paper focused on four alternatives of analysis of experiments in square lattice as far as the estimation of variance components and some genetic parameters are concerned: 1) intra-block analysis with adjusted treatment and blocks within unadjusted repetitions; 2) lattice analysis as complete randomized blocks; 3) intrablock analysis with unadjusted treatment and blocks within adjusted repetitions; 4) lattice analysis as complete randomized blocks, by utilizing the adjusted means of treatments, obtained from the analysis with recovery of interblock information, having as mean square of the error the mean effective variance of this same analysis with recovery of inter-block information. For the four alternatives of analysis, the estimators and estimates were obtained for the variance components and heritability coefficients. The classification of material was also studied. The present study suggests that for each experiment and depending of the objectives of the analysis, one should observe which alternative of analysis is preferable, mainly in cases where a negative estimate is obtained for the variance component due to effects of blocks within adjusted repetitions.

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Introduction: Prior repeated-sprints (6) has become an interesting method to resolve the debate surrounding the principal factors that limits the oxygen uptake (V'O2) kinetics at the onset of exercise [i.e., muscle O2 delivery (5) or metabolic inertia (3)]. The aim of this study was to compare the effects of two repeated-sprints sets of 6x6s separated by different recovery duration between the sprints on V'O2 and muscular de-oxygenation [HHb] kinetics during a subsequent heavy-intensity exercise. Methods: 10 male subjects performed a 6-min constant-load cycling test (T50) at intensity corresponding to half of the difference between V'O2max and the ventilatory threshold. Then, they performed two repeated-sprints sets of 6x6s all-out separated by different recovery duration between the sprints (S1:30s and S2:3min) followed, after 7-min-recovery, by the T50 (S1T50 and S2T50, respectively). V'O2, [HHb] of the vastus lateralis (VL) and surface electromyography activity [i.e., root-mean-square (RMS) and the median frequency of the power density spectrum (MDF)] from VL and vastus medialis (VM) were recorded throughout T50. Models using a bi-exponential function for the overall T50 and a mono-exponential for the first 90s of T50 were used to define V'O2 and [HHb] kinetics respectively. Results: V'O2 mean value was higher in S1 (2.9±0.3l.min-1) than in S2 (1.2±0.3l.min-1); (p<0.001). The peripheral blood flow was increased after sprints as attested by a higher basal heart rate (HRbaseline) (S1T50: +22%; S2T50: +17%; p≤0.008). Time delay [HHb] was shorter for S1T50 and S2T50 than for T50 (-22% for both; p≤0.007) whereas the mean response time of V'O2 was accelerated only after S1 (S1T50: 32.3±2.5s; S2T50: 34.4±2.6s; T50: 35.7±5.4s; p=0.031). There were no significant differences in RMS between the three conditions (p>0.05). MDF of VM was higher during the first 3-min in S1T50 than in T50 (+6%; p≤0.05). Conclusion: The study show that V'O2 kinetics was speeded by prior repeated-sprints with a short (30s) but not a long (3min) inter-sprints-recovery even though the [HHb] kinetics was accelerated and the peripheral blood flow was enhanced after both sprints. S1, inducing a greater PCr depletion (1) and change in the pattern of the fibres recruitment (increase in MDF) compared with S2, may decrease metabolic inertia (2), stimulate the oxidative phosphorylation activation (4) and accelerate V'O2 kinetics at the beginning of the subsequent high-intensity exercise.

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Introduction: Prior repeated-sprints (6) has become an interesting method to resolve the debate surrounding the principal factors that limits the oxygen uptake (V'O2) kinetics at the onset of exercise [i.e., muscle O2 delivery (5) or metabolic inertia (3)]. The aim of this study was to compare the effects of two repeated-sprints sets of 6x6s separated by different recovery duration between the sprints on V'O2 and muscular de-oxygenation [HHb] kinetics during a subsequent heavy-intensity exercise. Methods: 10 male subjects performed a 6-min constant-load cycling test (T50) at intensity corresponding to half of the difference between V'O2max and the ventilatory threshold. Then, they performed two repeated-sprints sets of 6x6s all-out separated by different recovery duration between the sprints (S1:30s and S2:3min) followed, after 7-min-recovery, by the T50 (S1T50 and S2T50, respectively). V'O2, [HHb] of the vastus lateralis (VL) and surface electromyography activity [i.e., root-mean-square (RMS) and the median frequency of the power density spectrum (MDF)] from VL and vastus medialis (VM) were recorded throughout T50. Models using a bi-exponential function for the overall T50 and a mono-exponential for the first 90s of T50 were used to define V'O2 and [HHb] kinetics respectively. Results: V'O2 mean value was higher in S1 (2.9±0.3l.min-1) than in S2 (1.2±0.3l.min-1); (p<0.001). The peripheral blood flow was increased after sprints as attested by a higher basal heart rate (HRbaseline) (S1T50: +22%; S2T50: +17%; p≤0.008). Time delay [HHb] was shorter for S1T50 and S2T50 than for T50 (-22% for both; p≤0.007) whereas the mean response time of V'O2 was accelerated only after S1 (S1T50: 32.3±2.5s; S2T50: 34.4±2.6s; T50: 35.7±5.4s; p=0.031). There were no significant differences in RMS between the three conditions (p>0.05). MDF of VM was higher during the first 3-min in S1T50 than in T50 (+6%; p≤0.05). Conclusion: The study show that V'O2 kinetics was speeded by prior repeated-sprints with a short (30s) but not a long (3min) inter-sprints-recovery even though the [HHb] kinetics was accelerated and the peripheral blood flow was enhanced after both sprints. S1, inducing a greater PCr depletion (1) and change in the pattern of the fibres recruitment (increase in MDF) compared with S2, may decrease metabolic inertia (2), stimulate the oxidative phosphorylation activation (4) and accelerate V'O2 kinetics at the beginning of the subsequent high-intensity exercise.

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Introduction Exposure to hypoxia leads to several reactions of the organism, which try to compensate the reduced oxygen level in the blood. Acute response is characterized by an increase in pulmonary ventilation (Hypoxia Ventilatory Response, HVR) and in cardiac output (cardiac response to hypoxia). Heart rate (HR) at rest and during exercise is higher at high altitude than at sea level, whereas HRmax is lower. These cardiac adaptations are partially explained by an increased sympathetic stimulation associated with a reduced parasympathetic tone (12). The precise mechanisms of HRmax decline in acute hypoxia are however still to be identified, although several hypothesis have been suggested, such as a direct effect of hypoxia on the electrophysiological properties, an influence of skeletal maximal VO2 or a modulation of the autonomic nervous system (8). Some authors have reported that endurance trained athletes present an increased sensitivity to hypoxia shown by a large reduction in VO2max and an important decrease in arterial saturation. (9,11, 13) A hypoxia test can assess the sensibility of chemoreceptors to the reduction of oxygen by calculating hypoxic ventilatory and cardiac responses, knowing that low sensibility is correlated with poor acclimatization. Two parameters results from the differences in ventilation (and heart rate) divided by the difference in the arterial oxygen saturation between normoxia and hypoxia (18). Objective The hypothesis tested by this study is that parasympathetic reactivation after moderate effort in hypoxic condition can be used as a marker of individual sensibility to hypoxia. Parasympathetic reactivation is a marker of vagal tone that predict endurance capacity and aerobic fitness (2,7). Methods Subjects This study uses data obtained from two groups of athletes participating into two larger studies about adaptation to hypoxia. One group is composed of elite athletes (Swiss ski mountaineering team), the other one of mid-level athletes (ski mountaineering amateurs). The particularity of this target population is that they often train at high altitude, and therefore could show a better response to hypoxia than athleltes of other disciplines. Protocol The athletes performed a submaximal exercise (6min run at 9 km/h, flat) followed by 10 min of seated rest either in an hypoxic chamber (simulated altitude of 3000m) or in normoxic conditions. During the resting phase parasympathetic reactivation was assessed by beat-to-beat HR measurements.A test of tolerance to altitude was also performed. Analysis Parasympathetic reactivation, assessed by the calculation of the root mean square of successive differences in the R-R intervals (RMSSD)(4), is compared to individual responses at altitude, in order to appreciate the correlation between the two phenomena.

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OBJECTIVES: To investigate the effect of a change in second-hand smoke (SHS) exposure on heart rate variability (HRV) and pulse wave velocity (PWV), this study utilized a quasi-experimental setting when a smoking ban was introduced. METHODS: HRV, a quantitative marker of autonomic activity of the nervous system, and PWV, a marker of arterial stiffness, were measured in 55 non-smoking hospitality workers before and 3-12 months after a smoking ban and compared to a control group that did not experience an exposure change. SHS exposure was determined with a nicotine-specific badge and expressed as inhaled cigarette equivalents per day (CE/d). RESULTS: PWV and HRV parameters significantly changed in a dose-dependent manner in the intervention group as compared to the control group. A one CE/d decrease was associated with a 2.3 % (95 % CI 0.2-4.4; p = 0.031) higher root mean square of successive differences (RMSSD), a 5.7 % (95 % CI 0.9-10.2; p = 0.02) higher high-frequency component and a 0.72 % (95 % CI 0.40-1.05; p < 0.001) lower PWV. CONCLUSIONS: PWV and HRV significantly improved after introducing smoke-free workplaces indicating a decreased cardiovascular risk.

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The objective of this study was to improve the simulation of node number in soybean cultivars with determinate stem habits. A nonlinear model considering two approaches to input daily air temperature data (daily mean temperature and daily minimum/maximum air temperatures) was used. The node number on the main stem data of ten soybean cultivars was collected in a three-year field experiment (from 2004/2005 to 2006/2007) at Santa Maria, RS, Brazil. Node number was simulated using the Soydev model, which has a nonlinear temperature response function [f(T)]. The f(T) was calculated using two methods: using daily mean air temperature calculated as the arithmetic average among daily minimum and maximum air temperatures (Soydev tmean); and calculating an f(T) using minimum air temperature and other using maximum air temperature and then averaging the two f(T)s (Soydev tmm). Root mean square error (RMSE) and deviations (simulated minus observed) were used as statistics to evaluate the performance of the two versions of Soydev. Simulations of node number in soybean were better with the Soydev tmm version, with a 0.5 to 1.4 node RMSE. Node number can be simulated for several soybean cultivars using only one set of model coefficients, with a 0.8 to 2.4 node RMSE.

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3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

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This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

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A comparative performance analysis of four geolocation methods in terms of their theoretical root mean square positioning errors is provided. Comparison is established in two different ways: strict and average. In the strict type, methods are examined for a particular geometric configuration of base stations(BSs) with respect to mobile position, which determines a givennoise profile affecting the respective time-of-arrival (TOA) or timedifference-of-arrival (TDOA) estimates. In the average type, methodsare evaluated in terms of the expected covariance matrix ofthe position error over an ensemble of random geometries, so thatcomparison is geometry independent. Exact semianalytical equationsand associated lower bounds (depending solely on the noiseprofile) are obtained for the average covariance matrix of the positionerror in terms of the so-called information matrix specific toeach geolocation method. Statistical channel models inferred fromfield trials are used to define realistic prior probabilities for therandom geometries. A final evaluation provides extensive resultsrelating the expected position error to channel model parametersand the number of base stations.