Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

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.

Practical algorithms for a family of waterfilling solutions

Many engineering problems that can be formulatedas constrained optimization problems result in solutionsgiven by a waterfilling structure; the classical example is thecapacity-achieving solution for a frequency-selective channel.For simple waterfilling solutions with a single waterlevel and asingle constraint (typically, a power constraint), some algorithmshave been proposed in the literature to compute the solutionsnumerically. However, some other optimization problems result insignificantly more complicated waterfilling solutions that includemultiple waterlevels and multiple constraints. For such cases, itmay still be possible to obtain practical algorithms to evaluate thesolutions numerically but only after a painstaking inspection ofthe specific waterfilling structure. In addition, a unified view ofthe different types of waterfilling solutions and the correspondingpractical algorithms is missing.The purpose of this paper is twofold. On the one hand, itoverviews the waterfilling results existing in the literature from aunified viewpoint. On the other hand, it bridges the gap betweena wide family of waterfilling solutions and their efficient implementationin practice; to be more precise, it provides a practicalalgorithm to evaluate numerically a general waterfilling solution,which includes the currently existing waterfilling solutions andothers that may possibly appear in future problems.

Neural plasticity associated with recently versus often heard objects.

In natural settings the same sound source is often heard repeatedly, with variations in spectro-temporal and spatial characteristics. We investigated how such repetitions influence sound representations and in particular how auditory cortices keep track of recently vs. often heard objects. A set of 40 environmental sounds was presented twice, i.e. as prime and as repeat, while subjects categorized the corresponding sound sources as living vs. non-living. Electrical neuroimaging analyses were applied to auditory evoked potentials (AEPs) comparing primes vs. repeats (effect of presentation) and the four experimental sections. Dynamic analysis of distributed source estimations revealed i) a significant main effect of presentation within the left temporal convexity at 164-215ms post-stimulus onset; and ii) a significant main effect of section in the right temporo-parietal junction at 166-213ms. A 3-way repeated measures ANOVA (hemisphere×presentation×section) applied to neural activity of the above clusters during the common time window confirmed the specificity of the left hemisphere for the effect of presentation, but not that of the right hemisphere for the effect of section. In conclusion, spatio-temporal dynamics of neural activity encode the temporal history of exposure to sound objects. Rapidly occurring plastic changes within the semantic representations of the left hemisphere keep track of objects heard a few seconds before, independent of the more general sound exposure history. Progressively occurring and more long-lasting plastic changes occurring predominantly within right hemispheric networks, which are known to code for perceptual, semantic and spatial aspects of sound objects, keep track of multiple exposures.

Probabilistic algorithms for blind adaptive multiuser detection

In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

Brain glucose sensing and neural regulation of insulin and glucagon secretion.

Glucose homeostasis requires the tight regulation of glucose utilization by liver, muscle and white or brown fat, and glucose production and release in the blood by liver. The major goal of maintaining glycemia at ∼ 5 mM is to ensure a sufficient flux of glucose to the brain, which depends mostly on this nutrient as a source of metabolic energy. This homeostatic process is controlled by hormones, mainly glucagon and insulin, and by autonomic nervous activities that control the metabolic state of liver, muscle and fat tissue but also the secretory activity of the endocrine pancreas. Activation or inhibition of the sympathetic or parasympathetic branches of the autonomic nervous systems are controlled by glucose-excited or glucose-inhibited neurons located at different anatomical sites, mainly in the brainstem and the hypothalamus. Activation of these neurons by hyper- or hypoglycemia represents a critical aspect of the control of glucose homeostasis, and loss of glucose sensing by these cells as well as by pancreatic β-cells is a hallmark of type 2 diabetes. In this article, aspects of the brain-endocrine pancreas axis are reviewed, highlighting the importance of central glucose sensing in the control of counterregulation to hypoglycemia but also mentioning the role of the neural control in β-cell mass and function. Overall, the conclusions of these studies is that impaired glucose homeostasis, such as associated with type 2 diabetes, but also defective counterregulation to hypoglycemia, may be caused by initial defects in glucose sensing.

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study.

To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

The neural basis for writing from dictation in the temporoparietal cortex.

Cortical electrical stimulation mapping was used to study neural substrates of the function of writing in the temporoparietal cortex. We identified the sites involved in oral language (sentence reading and naming) and writing from dictation, in order to spare these areas during removal of brain tumours in 30 patients (23 in the left, and 7 in the right hemisphere). Electrostimulation of the cortex impaired writing ability in 62 restricted cortical areas (.25 cm2). These were found in left temporoparietal lobes and were mostly located along the superior temporal gyrus (Brodmann's areas 22 and 42). Stimulation of right temporoparietal lobes in right-handed patients produced no writing impairments. However there was a high variability of location between individuals. Stimulation resulted in combined symptoms (affecting oral language and writing) in fourteen patients, whereas in eight other patients, stimulation-induced pure agraphia symptoms with no oral language disturbance in twelve of the identified areas. Each detected area affected writing in a different way. We detected the various different stages of the auditory-to-motor pathway of writing from dictation: either through comprehension of the dictated sentences (word deafness areas), lexico-semantic retrieval, or phonologic processing. In group analysis, barycentres of all different types of writing interferences reveal a hierarchical functional organization along the superior temporal gyrus from initial word recognition to lexico-semantic and phonologic processes along the ventral and the dorsal comprehension pathways, supporting the previously described auditory-to-motor process. The left posterior Sylvian region supports different aspects of writing function that are extremely specialized and localized, sometimes being segregated in a way that could account for the occurrence of pure agraphia that has long-been described in cases of damage to this region.

Ochratoxin A at nanomolar concentration perturbs the homeostasis of neural stem cells in highly differentiated but not in immature three-dimensional brain cell cultures.

Ochratoxin A (OTA), a fungal contaminant of basic food commodities, is known to be highly cytotoxic, but the pathways underlying adverse effects at subcytotoxic concentrations remain to be elucidated. Recent reports indicate that OTA affects cell cycle regulation. Therefore, 3D brain cell cultures were used to study OTA effects on mitotically active neural stem/progenitor cells, comparing highly differentiated cultures with their immature counterparts. Changes in the rate of DNA synthesis were related to early changes in the mRNA expression of neural stem/progenitor cell markers. OTA at 10nM, a concentration below the cytotoxic level, was ineffective in immature cultures, whereas in mature cultures it significantly decreased the rate of DNA synthesis together with the mRNA expression of key transcriptional regulators such as Sox2, Mash1, Hes5, and Gli1; the cell cycle activator cyclin D2; the phenotypic markers nestin, doublecortin, and PDGFRα. These effects were largely prevented by Sonic hedgehog (Shh) peptide (500ngml(-1)) administration, indicating that OTA impaired the Shh pathway and the Sox2 regulatory transcription factor critical for stem cell self-renewal. Similar adverse effects of OTA in vivo might perturb the regulation of stem cell proliferation in the adult brain and in other organs exhibiting homeostatic and/or regenerative cell proliferation.

Dysregulated activation of the CXCR4/CXCL12 Axisand its role in the malignant phenotype of neural crest-derived neuroblastoma tumours

Résumé: Le neuroblastome (NB) est un néoplasme dévastateur de la petite enfance, pour lequel il n'existe pas encore de traitement efficace. Les chimiokines et leurs récepteurs ont été impliqués dans la croissance des tumeurs et la formation de métastases, et en particulier, il a été rapporté que l'axe CXCR4/CXCL12 dirigeait le guidage, ainsi que l'invasion des cellules cancéreuses vers des organes spécifiques. Notre étude avait pour objectif d'analyser le rôle de CxCR4 exogène dans le comportement malin du NB, en étudiant la croissance des cellules tumorales, leur capacité de survie, de migration et d'invasion in vitro et en validant ces résultats grâce à un modèle orthotopique murin de la progression tumorale du NB in vivo. La surexpression de CXCR4 dans les cellules faiblement métastatiques IGR-NB8 n'exprimant pas CXCR4, a augmenté la mobilité des cellules vers CXCL12 in vitro. De plus, les cellules surexprimant CXCR4 ont été moins affectées par la privation de sérum que les cellules contrôles. Le volume des tumeurs chez les animaux greffés de manière orthotopique avec les cellules NB8-CXCR4-C3 était significativement plus élevé que celui des tumeurs issues des cellules contrôles NB8-E6 au moment du sacrifice des animaux. Cependant, aucune induction des métastases n'a été observée. La lignée cellulaire IGR-N91, aux propriétés invasives et métastatiques in vivo, exprime constitutivement des quantités modérées de CXCR4. La surexpression du récepteur dans cette lignée a accéléré la croissance tumorale in vivo, mais n'a pas augmenté pas l'occurrence des métastases. Les cellules IGR-N91, dans lesquelles l'expression de CXCR4 a été éteinte, suite à l'introduction de shRNA stable contre CXCR4, a présenté une croissance cellulaire plus lente, in vitro et in vivo. Afin d'identifier les gènes et les voies de signalisation impliqués dans les effets dépendants de CXCR4-CXCL12 dans le NB, des analyses du profil d'expression des gènes ont été effectuées sur les lignées cellulaires transfectées ou non (contrôle). Trois clones contrôles ont été comparés à 3 clones surexprimant CXCR4 pour chacune des lignées (IGR-NB8 et IGR-N91). Les analyses biostatiques ont identifié 10 gènes induits, dont CXCR4, et 31 gènes réprimés, communs entre tous les clones surexprimant CXCR4. Ces observations démontrent que la surexpression de CXCR4 dans le NB stimule la croissance, la survie et la migration chémotactique des cellules tumorales, mais est insuffisante pour induire ou augmenter leurs capacités invasives et métastatiques. Les voies de signalisation activées suite à la surexpression de CXCR4 et identifiées à travers le profil global de l'expression des gènes pourraient être des cibles intéressantes pour le développement de drogues capables d'inhiber la croissance tumorale. Abstact: Neuroblastoma (NB) is a devastating childhood neoplasm for which there is not yet an efficient treatment. Chemokines and their receptors have been involved in tumour growth and metastasis, and in particular the CXCR4/CXCL12 axis has been reported to mediate organ-specific cancer cells homing and invasion. The purpose of the study was to investigate the role of ectopic CXCR4 in the malignant behaviour of NB by studying tumour cell growth, survival, migration, and invasion in vitro and by validating these results using a murine orthotopic model of NB tumour progression in vivo. CXCR4 overexpression in the low metastatic, CXCR4-negative IGR-NB8 cells resulted in CXCL12-mediated chemotaxis in vitro. Furthermore, CXCR4 overexpressing cells were less affected by serum deprivation than mock-transduced cells. In vivo studies revealed that, at sacrifice, volumes of tumours developing in mice with orthotopically implanted NB8-CXCR4-C3 cells, were significantly increased compared to NB8-E6 control tumours. However, no induction of metastases was observed. The in vivo invasive and metastatic cell line IGR-N91 cell line constitutively expresses moderate levels of CXCR4. Overexpression of CXCR4 enhanced in vivo tumour growth but did not increase the occurrence of metastases. IGR-N91 cells where CXCR4 has been knocked-down by stable shRNA grew slower in vitro and in vivo. To identify genes and pathways involved in the CXCR4/CXCL12-mediated effects in NB expression, profiles analyses (Affymetrix) were performed on transduced and control cell lines. Three mock-transduced clones were compared to three CXCR4 overexpressing clones of either cell line IGR-NB8 and IGR-N91. Biostatistical analysis identified 10 commonly upregulated genes (including CXCR4) and 31 downregulated genes common to all CXCR4 overexpressing clones. These observations demonstrate that overexpression of CXCR4 in NB stimulates tumour cell growth, survival, and chemotactic migration but is not sufficient to induce or enhance invasive and metastatic capacities. Activated pathways upon CXCR4 overexpression, identified through global gene expression profiling may be interesting targets for drugs inhibiting tumour growth.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.