Parasitic arthropods of some wild rodents from Juréia-Itatins Ecological Station, State of São Paulo, Brazil

A study of the associations between three species of rodents in the Atlantic forest and their parasitic arthropods was undertaken at the Juréia-Itatins Ecological Station, located in the State of São Paulo, Southeastern Brazil, from March 1989 to February 1990. Individuals of three species, Oryzomys russatus, Proechimys iheringi and Nectomys squamipes were captured and examined for ectoparasites. Eleven species of parasitic arthropods were found, including four species of insects and seven of Acari. Parasitism intensity, phenology, and rainfall were positively correlated with the abundance of the ectoparasites and their hosts. The most abundant host was O. russatus (Muridae: Sigmodontinae), and the most common parasite on it was the laelapid mite Gigantolaelaps oudemansi. The cuterebrid Metacuterebra apicalis caused myiasis in O. russatus. A mutualistic association between the staphylinid beetle Amblyopinus sp. and its host P. iheringi (Echimyidae) was observed. The few N. squamipes captured had small numbers of ectoparasites.

Screening of some plants used in the Brazilian folk medicine for the treatment of infectious diseases

Extracts of 13 Brazilian medicinal plants were screened for their antimicrobial activity against bacteria and yeasts. Of these, 10 plant extracts showed varied levels of antibacterial activity. Piper regnellii presented a good activity against Staphylococus aureus and Bacillus subtilis, a moderate activity on Pseudomonas aeruginosa, and a weak activity against Escherichia coli. Punica granatum showed good activity on S. aureus and was inactive against the other standard strains. Eugenia uniflora presented moderate activity on both S. aureus and E. coli. Psidium guajava,Tanacetum vulgare, Arctium lappa, Mikania glomerata, Sambucus canadensis, Plantago major and Erythrina speciosa presented some degree of antibacterial activity. Spilanthes acmella, Lippia alba, and Achillea millefolium were considered inactive. Five of the plant extracts presented compounds with Rf values similar to the antibacterial compounds visible on bioautogram. Of these, three plants belong to the Asteraceae family. This may mean that the same compounds are responsible for the antibacterial activity in these plants. Anticandidal activity was detected in nine plant extracts (P. guajava, E. uniflora, P. granatum, A. lappa, T. vulgare, M. glomerata, L. alba, P. regnellii, and P. major). The results might explain the ethnobotanical use of the studied species for the treatment of various infectious diseases.

Differential phosphorylation of some proteins of the neuronal cytoskeleton during brain development.

The cytoskeleton is important for neuronal morphogenesis. During the postnatal development of cat brain, the molecular composition of the neuronal cytoskeleton changes with maturation. Several of its proteins change in their rate of expression, in their degree of phosphorylation, in their subcellular distribution, or in their biochemical properties. It is proposed that phosphorylation is an essential mechanism to regulate the plasticity of the early, juvenile-type cytoskeleton. Among such proteins are several microtubule-associated proteins (MAPs), such as MAP5a, MAP2c or the juvenile tau proteins. Phosphorylation may also act on neurofilaments, postulated to be involved in the adult-type stabilization of axons. These observations imply that phosphorylation may affect cytoskeleton function in axons and dendrites at various developmental stages. Yet, the mechanisms of phosphorylation and its regulation cascades are largely unknown. In view of the topic of this issue on CD15, the potential role of matrix molecules being involved in the modulation of phosphorylation activity and of cytoskeletal properties is addressed.

Applications of stochastic analysis in finance and statistical inference

First: A continuous-time version of Kyle's model (Kyle 1985), known as the Back's model (Back 1992), of asset pricing with asymmetric information, is studied. A larger class of price processes and of noise traders' processes are studied. The price process, as in Kyle's model, is allowed to depend on the path of the market order. The process of the noise traders' is an inhomogeneous Lévy process. Solutions are found by the Hamilton-Jacobi-Bellman equations. With the insider being risk-neutral, the price pressure is constant, and there is no equilibirium in the presence of jumps. If the insider is risk-averse, there is no equilibirium in the presence of either jumps or drifts. Also, it is analised when the release time is unknown. A general relation is established between the problem of finding an equilibrium and of enlargement of filtrations. Random announcement time is random is also considered. In such a case the market is not fully efficient and there exists equilibrium if the sensitivity of prices with respect to the global demand is time decreasing according with the distribution of the random time. Second: Power variations. it is considered, the asymptotic behavior of the power variation of processes of the form _integral_0^t u(s-)dS(s), where S_ is an alpha-stable process with index of stability 0&alpha&2 and the integral is an Itô integral. Stable convergence of corresponding fluctuations is established. These results provide statistical tools to infer the process u from discrete observations. Third: A bond market is studied where short rates r(t) evolve as an integral of g(t-s)sigma(s) with respect to W(ds), where g and sigma are deterministic and W is the stochastic Wiener measure. Processes of this type are particular cases of ambit processes. These processes are in general not of the semimartingale kind.

Applications of a transportable Raman spectrometer for the in situ detection of controlled substances at border controls

A transportable Raman spectrometer was tested for the detection of illicit drugs seized during border controls. In a first step, the analysis methodology was optimized using reference substances such as diacetylmorphine (heroin), cocaine and amphetamine (as powder or liquid forms). Adequate focalisation distance and times of analysis, influence of daylight and artificial light sources, repeatability and limits of detection were studied. In a second step the applications and limitations of the technique to detect the illicit substances in different mixtures and containers was evaluated. Transportable Raman spectroscopy was found to be adequate for a rapid screen of liquids and powders for the detection and identification of controlled substances. Additionally, it had the advantage over other portable techniques, such as ion mobility spectrometry, of being non-destructive and capable of rapid analysis of large quantities of substances through containers such as plastic bags and glass bottles.

Spectrum of some trianguled categories

In this paper, we compute the triangular spectrum (as de fined by P. Balmer) of two classes of tensor triangulated categories which are quite common in algebraic geometry. One of them is the derived category of G-equivariant sheaves on a smooth scheme X, for a fi nite group G. The other class is the derived category of split superschemes.

Applications of the hexanic fraction of Agave sisalana Perrine ex Engelm (Asparagaceae): control of inflammation and pain screening

The present study evaluated the anti-inflammatory and analgesic properties of Agave sisalana Perrine in classic models of inflammation and pain. The hexanic fraction of A. sisalana (HFAS) was obtained by acid hydrolysis followed by hexanic reflux. Anti-inflammatory properties were examined in three acute mouse models (xylene ear oedema, hind paw oedema and pleurisy) and a chronic mouse model (granuloma cotton pellet). The antinociceptive potential was evaluated in chemical (acetic-acid) and thermal (tail-flick and hot-plate test) models of pain. When given orally, HFAS (5, 10, 25 and 50 mg/kg) reduced ear oedema (p < 0.0001; 52%, 71%, 62% and 42%, respectively). HFAS also reduced hind paw oedema at doses of 10 mg/kg and 25 mg/kg (p < 0.05; 42% and 58%, respectively) and pleurisy at doses of 10 mg/kg and 25 mg/kg (41% and 50%, respectively). In a chronic model, HFAS reduced inflammation by 46% and 58% at doses of 10 mg/kg and 25 mg/kg, respectively. Moreover, this fraction showed analgesic properties against the abdominal writhing in an acetic acid model (at doses of 5-25 mg/kg) with inhibitory rates of 24%, 54% and 48%. The HFAS also showed an increased latency time in the hot-plate (23% and 28%) and tail-flick tests (61% and 66%) for the 25 mg/kg and 50 mg/kg doses, respectively. These results suggest that HFAS has anti-inflammatory and analgesic properties.

Where microbiology meets microengineering: design and applications of reporter bacteria.

Bacteria have long been the targets for genetic manipulation, but more recently they have been synthetically designed to carry out specific tasks. Among the simplest of these tasks is chemical compound and toxicity detection coupled to the production of a quantifiable reporter signal. In this Review, we describe the current design of bacterial bioreporters and their use in a range of assays to measure the presence of harmful chemicals in water, air, soil, food or biological specimens. New trends for integrating synthetic biology and microengineering into the design of bacterial bioreporter platforms are also highlighted.

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

Possible solution of some essential zero problems in compositional data analysis

One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

Understanding the hierarchy governance choice of some wineries in Brazil - case study of 3 Brazilian wineries

ABSTRACT This study aims to contribute towards understanding the multiple factors, which influence firm's governance decisions. To identify some of these factors, three cases in the Brazilian wine industry were analyzed: Miolo located in Vale dos Vinhedos (South of Brazil) and in Vale do Rio São Francisco (Northeast of Brazil); Don Laurindo located in Vale dos Vinhedos; and ViniBrasil located in Vale do Rio São Francisco. For the most part, all three firms procure the grapes they use for their wine production in-house. Only Miolo purchases an insignificant amount of grapes outside of its production. By Brazilian standards, these regions have a long tradition of grape production and it is not difficult to purchase sufficient quantity of grapes to produce wine. However, the wineries are concerned also about the quality of the grapes they use and purchasing high-quality grapes might be critical issue. On the other hand, the quality of grapes is easily measured and the cost to buy in the market is cheaper than producing in-house. Furthermore, also the level of asset specificity present in the grape-grower-wine-producer transaction seems, by itself, insufficient to justify the use of hierarchical governance forms. Then, the aim of the article is to analyze the reasons why these wineries largely rely on hierarchy governance forms to procure their grape-inputs. What explains their use of hierarchy governance, given that both asset specificity and measurement problems appear to be relatively low?