Immunization and Aging: a Learning Process in the Immune Network

The immune system can be thought as a complex network of different interacting elements. A cellular automaton, defined in shape-space, was recently shown to exhibit self-regulation and complex behavior and is, therefore, a good candidate to model the immune system. Using this model to simulate a real immune system we find good agreement with recent experiments on mice. The model exhibits the experimentally observed refractory behavior of the immune system under multiple antigen presentations as well as loss of its plasticity caused by aging.Comment: 4 latex pages, 3 postscript figures attached. To be published in Physical Review Letters (Tentatively scheduled for 5th Oct. issue

Origens, crescimento e progressos na cotonicultura do Brasil.

Origens e crescimento da cotonicultura; Progressos na cotonicultura.bitstream/item/130108/1/ORIGEM-CRESCIMENTO.pd

Magnetic Properties of the Metamagnet Ising Model in a three-dimensional Lattice in a Random and Uniform Field

By employing the Monte Carlo technique we study the behavior of Metamagnet Ising Model in a random field. The phase diagram is obtained by using the algorithm of Glaubr in a cubic lattice of linear size $L$ with values ranging from 16 to 42 and with periodic boundary conditions.Comment: 4 pages, 6 figure

Phenomenological study of the electronic transport coefficients of graphene

Using a semi-classical approach and input from experiments on the conductivity of graphene, we determine the electronic density dependence of the electronic transport coefficients -- conductivity, thermal conductivity and thermopower -- of doped graphene. Also the electronic density dependence of the optical conductivity is obtained. Finally we show that the classical Hall effect (low field) in graphene has the same form as for the independent electron case, characterized by a parabolic dispersion, as long as the relaxation time is proportional to the momentum.Comment: 4 pages, 1 figur

Forecast foreign exchange rate: the case study of PKR/USD

The main aim of this paper is to forecast the future values of the exchange rate of the USD. Dollar (USD) and Pakistani Rupee (PR). For this purpose was used the ARIMA model to forecast the future exchange rates, because the time series was stationary at first difference. Data reported to five years ranging from the first day of April 2014 to 31st March 2019. The results proved that ARIMA (1,1,9) is the most suitable model to forecast the exchange rate. The difference between the forecasted values and actual values are less than 1%; therefore, it was found that the ARIMA is robust and this model will be helpful for the government functionaries, monetary policymakers, economists and other stakeholders to identify and forecast the future trend of the exchange rate and make their policies accordingly.info:eu-repo/semantics/publishedVersio