Note on ""Continuous matter creation and the acceleration of the universe: the growth of density fluctuations""

Recently, de Roany and Pacheco (Gen Relativ Gravit, doi:10.1007/s10714-010-1069-2) performed a Newtonian analysis on the evolution of perturbations for a class of relativistic cosmological models with Creation of Cold Dark Matter (CCDM) proposed by the present authors (Lima et al. in JCAP 1011:027, 2010). In this note we demonstrate that the basic equations adopted in their work do not recover the specific (unperturbed) CCDM model. Unlike to what happens in the original CCDM cosmology, their basic conclusions refer to a decelerating cosmological model in which there is no transition from a decelerating to an accelerating regime as required by SNe type Ia and complementary observations.

Seed Cell Wall Storage Polysaccharides: Models to Understand Cell Wall Biosynthesis and Degradation

Cell wall storage polysaccharides (CWSPs) are found as the principal storage compounds in seeds of many taxonomically important groups of plants. These groups developed extremely efficient biochemical mechanisms to disassemble cell walls and use the products of hydrolysis for growth. To accumulate these storage polymers, developing seeds also contain relatively high activities of noncellulosic polysaccharide synthases and thus are interesting models to seek the discovery of genes and enzymes related to polysaccharide biosynthesis. CWSP systems offer opportunities to understand phenomena ranging from polysaccharide deposition during seed maturation to the control of source-sink relationship in developing seedlings. By studying polysaccharide biosynthesis and degradation and the consequences for cell and physiological behavior, we can use these models to develop future biotechnological applications.

Animal models for genetic neuromuscular diseases

The neuromuscular disorders are a heterogeneous group of genetic diseases, caused by mutations in genes coding sarcolemmal, sarcomeric, and citosolic muscle proteins. Deficiencies or loss of function of these proteins leads to variable degree of progressive loss of motor ability. Several animal models, manifesting phenotypes observed in neuromuscular diseases, have been identified in nature or generated in laboratory. These models generally present physiological alterations observed in human patients and can be used as important tools for genetic, clinic, and histopathological studies. The mdx mouse is the most widely used animal model for Duchenne muscular dystrophy (DMD). Although it is a good genetic and biochemical model, presenting total deficiency of the protein dystrophin in the muscle, this mouse is not useful for clinical trials because of its very mild phenotype. The canine golden retriever MD model represents a more clinically similar model of DMD due to its larger size and significant muscle weakness. Autosomal recessive limb-girdle MD forms models include the SJL/J mice, which develop a spontaneous myopathy resulting from a mutation in the Dysferlin gene, being a model for LGMD2B. For the human sarcoglycanopahties (SG), the BIO14.6 hamster is the spontaneous animal model for delta-SG deficiency, whereas some canine models with deficiency of SG proteins have also been identified. More recently, using the homologous recombination technique in embryonic stem cell, several mouse models have been developed with null mutations in each one of the four SG genes. All sarcoglycan-null animals display a progressive muscular dystrophy of variable severity and share the property of a significant secondary reduction in the expression of the other members of the sarcoglycan subcomplex and other components of the Dystrophin-glycoprotein complex. Mouse models for congenital MD include the dy/dy (dystrophia-muscularis) mouse and the allelic mutant dy(2J)/dy(2J) mouse, both presenting significant reduction of alpha 2-laminin in the muscle and a severe phenotype. The myodystrophy mouse (Large(myd)) harbors a mutation in the glycosyltransferase Large, which leads to altered glycosylation of alpha-DG, and also a severe phenotype. Other informative models for muscle proteins include the knockout mouse for myostatin, which demonstrated that this protein is a negative regulator of muscle growth. Additionally, the stress syndrome in pigs, caused by mutations in the porcine RYR1 gene, helped to localize the gene causing malignant hypertermia and Central Core myopathy in humans. The study of animal models for genetic diseases, in spite of the existence of differences in some phenotypes, can provide important clues to the understanding of the pathogenesis of these disorders and are also very valuable for testing strategies for therapeutic approaches.

In Vitro Activity of the Antifungal Plant Defensin RsAFP2 against Candida Isolates and Its In Vivo Efficacy in Prophylactic Murine Models of Candidiasis

We show that RsAFP2, a plant defensin that interacts with fungal glucosylceramides, is active against Candida albicans, inhibits to a lesser extent other Candida species, and is nontoxic to mammalian cells. Moreover, glucosylceramide levels in Candida species correlate with RsAFP2 sensitivity. We found RsAFP2 prophylactically effective against murine candidiasis.

Predator-prey models: an application for the plankton dynamics of lake Geneva

In this paper we present a hierarchical Bayesian analysis for a predator-prey model applied to ecology considering the use of Markov Chain Monte Carlo methods. We consider the introduction of a random effect in the model and the presence of a covariate vector. An application to ecology is considered using a data set related to the plankton dynamics of lake Geneva for the year 1990. We also discuss some aspects of discrimination of the proposed models.

A unified view on lifetime distributions arising from selection mechanisms

In this paper, we formulate a flexible density function from the selection mechanism viewpoint (see, for example, Bayarri and DeGroot (1992) and Arellano-Valle et al. (2006)) which possesses nice biological and physical interpretations. The new density function contains as special cases many models that have been proposed recently in the literature. In constructing this model, we assume that the number of competing causes of the event of interest has a general discrete distribution characterized by its probability generating function. This function has an important role in the selection procedure as well as in computing the conditional personal cure rate. Finally, we illustrate how various models can be deduced as special cases of the proposed model. (C) 2011 Elsevier B.V. All rights reserved.

On the unification of long-term survival models

In this paper we extend the long-term survival model proposed by Chen et al. [Chen, M.-H., Ibrahim, J.G., Sinha, D., 1999. A new Bayesian model for survival data with a surviving fraction. journal of the American Statistical Association 94, 909-919] via the generating function of a real sequence introduced by Feller [Feller, W., 1968. An Introduction to Probability Theory and its Applications, third ed., vol. 1, Wiley, New York]. A direct consequence of this new formulation is the unification of the long-term survival models proposed by Berkson and Gage [Berkson, J., Gage, R.P., 1952. Survival cure for cancer patients following treatment. journal of the American Statistical Association 47, 501-515] and Chen et al. (see citation above). Also, we show that the long-term survival function formulated in this paper satisfies the proportional hazards property if, and only if, the number of competing causes related to the occurrence of an event of interest follows a Poisson distribution. Furthermore, a more flexible model than the one proposed by Yin and Ibrahim [Yin, G., Ibrahim, J.G., 2005. Cure rate models: A unified approach. The Canadian journal of Statistics 33, 559-570] is introduced and, motivated by Feller`s results, a very useful competing index is defined. (c) 2008 Elsevier B.V. All rights reserved.

A conformal invariant growth model

We present a one-parameter extension of the raise and peel one-dimensional growth model. The model is defined in the configuration space of Dyck (RSOS) paths. Tiles from a rarefied gas hit the interface and change its shape. The adsorption rates are local but the desorption rates are non-local; they depend not only on the cluster hit by the tile but also on the total number of peaks (local maxima) belonging to all the clusters of the configuration. The domain of the parameter is determined by the condition that the rates are non-negative. In the finite-size scaling limit, the model is conformal invariant in the whole open domain. The parameter appears in the sound velocity only. At the boundary of the domain, the stationary state is an adsorbing state and conformal invariance is lost. The model allows us to check the universality of non-local observables in the raise and peel model. An example is given.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Peritrophic membrane role in enhancing digestive efficiency Theoretical and experimental models

The pentrophic membrane (PM) is an anatomical structure surrounding the food bolus in most insects. Rejecting the idea that PM has evolved from coating mucus to play the same protective role as it, novel functions were proposed and experimentally tested. The theoretical principles underlying the digestive enzyme recycling mechanism were described and used to develop an algorithm to calculate enzyme distributions along the midgut and to infer secretory and absorptive sites. The activity of a Spodoptera frugiperda microvillar aminopeptidase decreases by 50% if placed in the presence of midgut contents. S. frugiperda trypsin preparations placed into dialysis bags in stirred and unstirred media have activities of 210 and 160%, respectively, over the activities of samples in a test tube. The ectoperitrophic fluid (EF) present in the midgut caeca of Rhynchosciara americana may be collected. If the enzymes restricted to this fluid are assayed in the presence of PM contents (PMC) their activities decrease by at least 58%. The lack of PM caused by calcofluor feeding impairs growth due to an increase in the metabolic cost associated with the conversion of food into body mass. This probably results from an increase in digestive enzyme excretion and useless homeostatic attempt to reestablish destroyed midgut gradients. The experimental models support the view that PM enhances digestive efficiency by: (a) prevention of non-specific binding of undigested material onto cell Surface; (b) prevention of excretion by allowing enzyme recycling powered by an ectoperitrophic counterflux of fluid; (c) removal from inside PM of the oligomeric molecules that may inhibit the enzymes involved in initial digestion; (d) restriction of oligomer hydrolases to ectoperitrophic space (ECS) to avoid probable partial inhibition by non-dispersed undigested food. Finally,PM functions are discussed regarding insects feeding on any diet. (C) 2008 Elsevier Ltd. All rights reserved.

A Unified Load Generator for Geographically Distributed Generation ofNetwork Traffic

During the last decade, the Internet usage has been growing at an enormous rate which has beenaccompanied by the developments of network applications (e.g., video conference, audio/videostreaming, E-learning, E-Commerce and real-time applications) and allows several types ofinformation including data, voice, picture and media streaming. While end-users are demandingvery high quality of service (QoS) from their service providers, network undergoes a complex trafficwhich leads the transmission bottlenecks. Considerable effort has been made to study thecharacteristics and the behavior of the Internet. Simulation modeling of computer networkcongestion is a profitable and effective technique which fulfills the requirements to evaluate theperformance and QoS of networks. To simulate a single congested link, simulation is run with asingle load generator while for a larger simulation with complex traffic, where the nodes are spreadacross different geographical locations generating distributed artificial loads is indispensable. Onesolution is to elaborate a load generation system based on master/slave architecture.

MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELS

Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.

Testing common nonlinear features in vector nonlinear autoregressive models

This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Growth of transcendental meditation: a sociological study

Sociology, in concerning itself with methodology and cultural determinism,may have overlooked the value of human experience in determining social action. We feel that the structural-functionalist point of view is not mutually exclusive with that of symbolic interaction theory. The field of collective behavior has not adequately explained a certain incidence of human activity called Transcendental Meditation. This paper will define Transcendental Meditation in sociological terms and explore its growth in terms of structural-functionalism,as well as in terms of the symbol-making faculty of human experience. In the first chapter, the author will state his biases and background as well as the problem and purpose of the paper. In the second chapter, Transcendental Meditation will be defined through an explanation of its concepts in sociological terms. A view of the TM program will also be reported. Following this in the third chapter, the origins of TM will be discussed~showing its basis to be in a tradition of Indian gurus and following its development in the United states until the present. The history of TM will proceed through biography of leading figures, with special mention of innovations in the TM institution of teaching and events in the growth of the 'movement' of TOO that are of key importance. Having set down the history of TM, in the fourth chapter we will discuss TM in terms of various sociological models. We will try to identify TM as either a social movement; a charismatic organization or a bureaucracy. In the fifth chapter we will look more closely at the structure of the organization that teaches TM in regard to its own functioning; that is, compliance, communication, socialization and recruitment, and also in regard to its relationship with national institutions, such as military, industry, religion, and government. Finally, we will explore TM in terms of individual and group goals and offer an explanation defining the growth of TM. Throughout-the paper, sociological perspectives will be applied to phenomena that exist in the society today. It is not within the scope of this paper to verify all the sociological implications and appraisals offered. It is hoped that this will not invalidate the ensuing discussion. It is also hoped that this paper will expand the horizons of sociology and offer some direction in future studies of collective behavior. If this is accomplished, the author will be gratified and indebted to his teachers. If not the author takes full responsibility. This paper is dedicated therefore to Mr. Birge, Mr Morrione, Mr. Geib as well as to my parents who have encouraged me, my friends whom I have interviewed, and to His Holiness, Maharishi Mahesh Yogi whose teaching has uplifted hundred of thousands of people in the world and may bring about the development of new thresholds of peace and prosperity for mankind.