A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

A high-fructose diet impairs basal and stress-mediated lipid metabolism in healthy male subjects

Rapport de synthèse : La consommation de boissons sucrées contenant du fructose a remarquablement augmenté ces dernières décennies et, on pense qu'elle joue un rôle important dans l'épidémie actuelle d'obésité et de troubles métaboliques. Des études faites sur des rats ont montré qu'une alimentation riche en sucre ou fructose induisait une obésité, une résistance à l'insuline, diabète, dyslipidémie et une hypertension artérielle, tandis que chez l'homme, une alimentation riche en fructose conduit, après quelques jours, au développement d'une hypertryglycémie et une résistance hépatique à l'insuline. Nous avons entrepris une étude de 7 jours d'alimentation riche en fructose ou d'une alimentation contrôlée chez six hommes en bonne santé. Les NEFA plasmatiques et la beta-hydroxybutyrate, l'oxydation nette de lipide (calorimétrie indirecte) et l'oxydation exogène de lipide (13 CO2) ont été surveillés dans des conditions basales, et après un chargement en lipide (huile d'olive marqué au 13C-trioléine), puis durant un stress mental standardisé. La clearance de lactate et les effets métaboliques de la perfusion de lactate exogène ont également été évalués. Nos résultats ont montré que l'alimentation riche en fructose diminue la concentration plasmatique de NEFA, de beta-hydroxybutyrate de même que l'oxydation des lipides dans les conditions de bases et après surcharge en lipides. De plus, l'alimentation riche en fructose amortie l'augmentation des NEFA plasmatique et l'oxydation des lipides exogènes durant le stress mental. Elle augmente également la concentration basale de lactate et la production de lactate de respectivement 31.8% et 53.8%, tandis que la clearance du lactate reste inchangée. L'injection de lactate diminue le taux des NEFA lors de l'alimentation de contrôle et l'alimentation de base, et l'oxydation nette de lipide lors de l'alimentation de contrôle et l'alimentation riche en fructose. Ces résultats indiquent que 7 jours d'alimentation riche en fructose inhibent remarquablement la lipolyse et l'oxydation des lipides. L'alimentation riche en fructose augmente aussi la production de lactate, et l'augmentation de l'utilisation de lactate peut contribuer à supprimer l'oxydation des lipides. Abstact : The effects of a 7 d high-fructose diet (HFrD) or control diet on lipid metabolism were studied in a group of six healthy lean males. Plasma NEFA and β-hydroxybutyrate concentrations, net lipid oxidation (indirect calorimetry) and exogenous lipid oxidation (13CO2 production) were monitored in basal conditions, after lipid loading (olive oil labelled with [13C] triolein) and during a standardised mental stress. Lactate clearance and the metabolic effects of an exogenous lactate infusion were also monitored. The HFrD lowered plasma concentrations of NEFA and (β-hydroxybutyrate as well as lipid oxidation in both basal and after lipid-loading conditions. In addition, the HFrD blunted the increase in plasma NEFA and exogenous lipid oxidation during mental stress. The HFrD also increased basal lactate concentrations by 31.8%, and lactate production by 53.8 %, while lactate clearance remained unchanged. Lactate infusion lowered plasma NEFA with the control diet, and net lipid oxidation with both the HFrD and control diet. These results indicate that a 7 d HFrD markedly inhibits lipolysis and lipid oxidation. The HFrD also increases lactate production, and the ensuing increased lactate utilisation may contribute to suppress lipid oxidation.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

Organic and inorganic geochemistry of Ljubija siderite deposits, NW Bosnia and Herzegovina

The Ljubija siderite deposits, hosted by a Carboniferous sedimentary complex within the Inner Dinarides, occur as stratabound replacement-type ore bodies in limestone blocks and as siderite-sulfides veins in shale. Three principal types of ore textures have been recognized including massive dark siderite and ankerite, siderite with zebra texture, and siderite veins. The ore and host rocks have been investigated by a combination of inorganic (major, trace, and rare earth element concentrations), organic (characterization of hydrocarbons including biomarkers), and stable isotope geochemical methods (isotope ratios of carbonates, sulfides, sulfates, kerogen, and individual hydrocarbons). New results indicate a marine origin of the host carbonates and a hydrothermal-metasomatic origin of the Fe mineralization. The differences in ore textures (e.g., massive siderite, zebra siderite) are attributed to physicochemical variations (e.g., changes in acidity, temperature, and/or salinity) of the mineralizing fluids and to the succession and intensity of replacement of host limestone. Vein siderite was formed by precipitation from hydrothermal fluids in the late stage of mineralization. The equilibrium fractionation of stable isotopes reveals higher formation temperatures for zebra siderites (around 245A degrees C) then for siderite vein (around 185A degrees C). Sulfur isotope ratios suggest Permian seawater or Permian evaporites as the main sulfur source. Fluid inclusion composition confirms a contribution of the Permian seawater to the mineralizing fluids and accord with a Permian mineralization age. Organic geochemistry data reflect mixing of hydrocarbons at the ore site and support the hydrothermal-metasomatic origin of the Ljubija iron deposits.

Multimodal Highlighting of Structural Abnormalities in Diabetic Rat and Human Corneas.

PURPOSE: This study aimed to highlight structural corneal changes in a model of type 2 diabetes, using in vivo corneal confocal microscopy (CCM). The abnormalities were also characterized by transmission electron microscopy (TEM) and second harmonic generation (SHG) microscopy in rat and human corneas. METHODS: Goto-Kakizaki (GK) rats were observed at age 12 weeks (n = 3) and 1 year (n = 6), and compared to age-matched controls. After in vivo CCM examination, TEM and SHG microscopy were used to characterize the ultrastructure and the three-dimensional organization of the abnormalities. Human corneas from diabetic (n = 3) and nondiabetic (n = 3) patients were also included in the study. RESULTS: In the basal epithelium of GK rats, CCM revealed focal hyper-reflective areas, and histology showed proliferative cells with irregular basement membrane. In the anterior stroma, extracellular matrix modifications were detected by CCM and confirmed in histology. In the Descemet's membrane periphery of all the diabetic corneas, hyper-reflective deposits were highlighted using CCM and characterized as long-spacing collagen fibrils by TEM. SHG microscopy revealed these deposits with high contrast, allowing specific detection in diabetic human and rat corneas without preparation and characterization of their three-dimensional organization. CONCLUSION: Pathologic findings were observed early in the development of diabetes in GK rats. Similar abnormalities have been found in corneas from diabetic patients. TRANSLATIONAL RELEVANCE: This multidisciplinary study highlights diabetes-induced corneal abnormalities in an animal model, but also in diabetic donors. This could constitute a potential early marker for diagnosis of hyperglycemia-induced tissue changes.

Importância da Programação Linear na Determinação de Informações de Gestão - Caso Moave, Sa

A Investigação Operacional vem demonstrando ser uma valiosa ferramenta de gestão nos dias de hoje em que se vive num mercado cada vez mais competitivo. Através da Programação Linear pode-se reproduzir matematicamente um problema de maximização dos resultados ou minimização dos custos de produção com o propósito de auxiliar os gestores na tomada de decisão. A Programação Linear é um método matemático em que a função objectivo e as restrições assumem características lineares, com diversas aplicações no controlo de gestão, envolvendo normalmente problemas de utilização dos recursos disponíveis sujeitos a limitações impostas pelo processo produtivo ou pelo mercado. O objectivo geral deste trabalho é o de propor um modelo de Programação Linear para a programação ou produção e alocação de recursos necessários. Optimizar uma quantidade física designada função objectivo, tendo em conta um conjunto de condicionalismos endógenas às actividades em gestão. O objectivo crucial é dispor um modelo de apoio à gestão contribuindo assim para afectação eficiente de recursos escassos à disposição da unidade económica. Com o trabalho desenvolvido ficou patente a importância da abordagem quantitativa como recurso imprescindível de apoio ao processo de decisão. The operational research has proven to be a valuable management tool today we live in an increasingly competitive market. Through Linear Programming can be mathematically reproduce a problem of maximizing performance or minimizing production costs in order to assist managers in decision making. The Linear Programming is a mathematical method in which the objective function and constraints are linear features, with several applications in the control of management, usually involving problems of resource use are available subject to limitations imposed by the production process or the market. The overall objective of this work is to propose a Linear Programming model for scheduling or production and allocation of necessary resources. Optimizing a physical quantity called the objective function, given a set of endogenous constraints on management thus contributing to efficient allocation of scarce resources available to the economic unit. With the work has demonstrated the importance of the quantitative approach as essential resource to support the decision process.

Determinants of linear judgment: A meta-analysis of lens model studies

The mathematical representation of Brunswik s lens model has been usedextensively to study human judgment and provides a unique opportunity to conduct ameta-analysis of studies that covers roughly five decades. Specifically, we analyzestatistics of the lens model equation (Tucker, 1964) associated with 259 different taskenvironments obtained from 78 papers. In short, we find on average fairly high levelsof judgmental achievement and note that people can achieve similar levels of cognitiveperformance in both noisy and predictable environments. Although overall performancevaries little between laboratory and field studies, both differ in terms of components ofperformance and types of environments (numbers of cues and redundancy). An analysisof learning studies reveals that the most effective form of feedback is information aboutthe task. We also analyze empirically when bootstrapping is more likely to occur. Weconclude by indicating shortcomings of the kinds of studies conducted to date, limitationsin the lens model methodology, and possibilities for future research.

Deposits of transforming growth factor-beta-induced protein in granular corneal dystrophy type II after LASIK.

PURPOSE: To analyze components of the deposits in the corneal flap interface of granular corneal dystrophy type II (GCD II) patients after laser in situ keratomileusis (LASIK). METHODS: Four corneal GCD II specimens displaying disease exacerbation after LASIK were analyzed. Three of these specimens included the recipient corneal button after penetrating keratoplasty or deep lamellar keratoplasty for advanced GCD II after LASIK. The fourth specimen, a similar case of GCD II after LASIK, included the amputated corneal flap. Specimens were processed for histopathologic and immunohistochemical analyses. RESULTS: Corneal stromal deposits in the LASIK flaps of all specimens were stained with 3 anti-transforming growth factor-beta-induced protein (TGFBIp) antibodies. The deposits displayed bright red color staining with Masson trichrome; however, negative staining was seen with Congo red, suggesting that hyaline is the main component localizing to the TGFBIp deposits rather than amyloid. CONCLUSIONS: Amorphous granular material deposited along the interface of the LASIK flap in GCD II corneas is composed mainly of hyaline deposits.

Fusion of data sets in multivariate linear regression with errors-in-variables

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

Equivalence of piecewise-linear approximation and Lagrangian relaxation for network revenue management

The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Asymptotic robustness in multi-sample analysis of multivariate linear relations

Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.