A determinação dos números de indivíduos mínimos necessários na experimentação genética

The main object of the present paper consists in giving formulas and methods which enable us to determine the minimum number of repetitions or of individuals necessary to garantee some extent the success of an experiment. The theoretical basis of all processes consists essentially in the following. Knowing the frequency of the desired p and of the non desired ovents q we may calculate the frequency of all possi- ble combinations, to be expected in n repetitions, by expanding the binomium (p-+q)n. Determining which of these combinations we want to avoid we calculate their total frequency, selecting the value of the exponent n of the binomium in such a way that this total frequency is equal or smaller than the accepted limit of precision n/pª{ 1/n1 (q/p)n + 1/(n-1)| (q/p)n-1 + 1/ 2!(n-2)| (q/p)n-2 + 1/3(n-3) (q/p)n-3... < Plim - -(1b) There does not exist an absolute limit of precision since its value depends not only upon psychological factors in our judgement, but is at the same sime a function of the number of repetitions For this reasen y have proposed (1,56) two relative values, one equal to 1-5n as the lowest value of probability and the other equal to 1-10n as the highest value of improbability, leaving between them what may be called the "region of doubt However these formulas cannot be applied in our case since this number n is just the unknown quantity. Thus we have to use, instead of the more exact values of these two formulas, the conventional limits of P.lim equal to 0,05 (Precision 5%), equal to 0,01 (Precision 1%, and to 0,001 (Precision P, 1%). The binominal formula as explained above (cf. formula 1, pg. 85), however is of rather limited applicability owing to the excessive calculus necessary, and we have thus to procure approximations as substitutes. We may use, without loss of precision, the following approximations: a) The normal or Gaussean distribution when the expected frequency p has any value between 0,1 and 0,9, and when n is at least superior to ten. b) The Poisson distribution when the expected frequecy p is smaller than 0,1. Tables V to VII show for some special cases that these approximations are very satisfactory. The praticai solution of the following problems, stated in the introduction can now be given: A) What is the minimum number of repititions necessary in order to avoid that any one of a treatments, varieties etc. may be accidentally always the best, on the best and second best, or the first, second, and third best or finally one of the n beat treatments, varieties etc. Using the first term of the binomium, we have the following equation for n: n = log Riim / log (m:) = log Riim / log.m - log a --------------(5) B) What is the minimun number of individuals necessary in 01der that a ceratin type, expected with the frequency p, may appaer at least in one, two, three or a=m+1 individuals. 1) For p between 0,1 and 0,9 and using the Gaussean approximation we have: on - ó. p (1-p) n - a -1.m b= δ. 1-p /p e c = m/p } -------------------(7) n = b + b² + 4 c/ 2 n´ = 1/p n cor = n + n' ---------- (8) We have to use the correction n' when p has a value between 0,25 and 0,75. The greek letters delta represents in the present esse the unilateral limits of the Gaussean distribution for the three conventional limits of precision : 1,64; 2,33; and 3,09 respectively. h we are only interested in having at least one individual, and m becomes equal to zero, the formula reduces to : c= m/p o para a = 1 a = { b + b²}² = b² = δ2 1- p /p }-----------------(9) n = 1/p n (cor) = n + n´ 2) If p is smaller than 0,1 we may use table 1 in order to find the mean m of a Poisson distribution and determine. n = m: p C) Which is the minimun number of individuals necessary for distinguishing two frequencies p1 and p2? 1) When pl and p2 are values between 0,1 and 0,9 we have: n = { δ p1 ( 1-pi) + p2) / p2 (1 - p2) n= 1/p1-p2 }------------ (13) n (cor) We have again to use the unilateral limits of the Gaussean distribution. The correction n' should be used if at least one of the valors pl or p2 has a value between 0,25 and 0,75. A more complicated formula may be used in cases where whe want to increase the precision : n (p1 - p2) δ { p1 (1- p2 ) / n= m δ = δ p1 ( 1 - p1) + p2 ( 1 - p2) c= m / p1 - p2 n = { b2 + 4 4 c }2 }--------- (14) n = 1/ p1 - p2 2) When both pl and p2 are smaller than 0,1 we determine the quocient (pl-r-p2) and procure the corresponding number m2 of a Poisson distribution in table 2. The value n is found by the equation : n = mg /p2 ------------- (15) D) What is the minimun number necessary for distinguishing three or more frequencies, p2 p1 p3. If the frequecies pl p2 p3 are values between 0,1 e 0,9 we have to solve the individual equations and sue the higest value of n thus determined : n 1.2 = {δ p1 (1 - p1) / p1 - p2 }² = Fiim n 1.2 = { δ p1 ( 1 - p1) + p1 ( 1 - p1) }² } -- (16) Delta represents now the bilateral limits of the : Gaussean distrioution : 1,96-2,58-3,29. 2) No table was prepared for the relatively rare cases of a comparison of threes or more frequencies below 0,1 and in such cases extremely high numbers would be required. E) A process is given which serves to solve two problemr of informatory nature : a) if a special type appears in n individuals with a frequency p(obs), what may be the corresponding ideal value of p(esp), or; b) if we study samples of n in diviuals and expect a certain type with a frequency p(esp) what may be the extreme limits of p(obs) in individual farmlies ? I.) If we are dealing with values between 0,1 and 0,9 we may use table 3. To solve the first question we select the respective horizontal line for p(obs) and determine which column corresponds to our value of n and find the respective value of p(esp) by interpolating between columns. In order to solve the second problem we start with the respective column for p(esp) and find the horizontal line for the given value of n either diretly or by approximation and by interpolation. 2) For frequencies smaller than 0,1 we have to use table 4 and transform the fractions p(esp) and p(obs) in numbers of Poisson series by multiplication with n. Tn order to solve the first broblem, we verify in which line the lower Poisson limit is equal to m(obs) and transform the corresponding value of m into frequecy p(esp) by dividing through n. The observed frequency may thus be a chance deviate of any value between 0,0... and the values given by dividing the value of m in the table by n. In the second case we transform first the expectation p(esp) into a value of m and procure in the horizontal line, corresponding to m(esp) the extreme values om m which than must be transformed, by dividing through n into values of p(obs). F) Partial and progressive tests may be recomended in all cases where there is lack of material or where the loss of time is less importent than the cost of large scale experiments since in many cases the minimun number necessary to garantee the results within the limits of precision is rather large. One should not forget that the minimun number really represents at the same time a maximun number, necessary only if one takes into consideration essentially the disfavorable variations, but smaller numbers may frequently already satisfactory results. For instance, by definition, we know that a frequecy of p means that we expect one individual in every total o(f1-p). If there were no chance variations, this number (1- p) will be suficient. and if there were favorable variations a smaller number still may yield one individual of the desired type. r.nus trusting to luck, one may start the experiment with numbers, smaller than the minimun calculated according to the formulas given above, and increase the total untill the desired result is obtained and this may well b ebefore the "minimum number" is reached. Some concrete examples of this partial or progressive procedure are given from our genetical experiments with maize.

A simple method to purify biologically and antigenically preserved bloodstream trypomastigotes of Trypanosoma cruzi using Deae-cellulose columns

A method to purify trypanosomastigotes of some strains of Trypanosoma cruzi (Y, CL, FL, F, "Berenice", "Colombiana" and "São Felipe") from mouse blood by using DEAE-cellulose columns was standardized. This procedure is a modification of the Lanham & Godfrey methods and differs in some aspects from others described to purify T. cruzi bloodstream trypomastigotes, mainly by avoidance of prior purifications of parasites. By this method, the broad trypomastigotes were mainly isolated, accounting for higher recoveries obtained with strains having higher percentages of these forms: processing of infected blood from irradiated mice could be advantageous by increasing the recovery of parasites (percentage and/or total number) and elution of more slender trypomastigotes. Trypomastigotes purified by this method presented normal morphology and motility, remained infective to triatomine bugs and mice, showing in the latter prepatent periods and courses parasitemia similar to those of control parasites, and also reproducing the polymorphism pattern of each strain. Their virulence and pathogenicity also remained considerably preserved, the latter property being evaluated by LD 50 tests, mortality rates and mean survival time of inoculated mice. Moreover, these parasites presented positive, clear and peripheral immunofluorescence reaction at titres similar to those of control organisms, thus suggesting important preservation of their surface antigens.

Modeling water movement in horizontal columns using fractal theory

Fractal mathematics has been used to characterize water and solute transport in porous media and also to characterize and simulate porous media properties. The objective of this study was to evaluate the correlation between the soil infiltration parameters sorptivity (S) and time exponent (n) and the parameters dimension (D) and the Hurst exponent (H). For this purpose, ten horizontal columns with pure (either clay or loam) and heterogeneous porous media (clay and loam distributed in layers in the column) were simulated following the distribution of a deterministic Cantor Bar with fractal dimension H" 0.63. Horizontal water infiltration experiments were then simulated using Hydrus 2D software. The sorptivity (S) and time exponent (n) parameters of the Philip equation were estimated for each simulation, using the nonlinear regression procedure of the statistical software package SAS®. Sorptivity increased in the columns with the loam content, which was attributed to the relation of S with the capillary radius. The time exponent estimated by nonlinear regression was found to be less than the traditional value of 0.5. The fractal dimension estimated from the Hurst exponent was 17.5 % lower than the fractal dimension of the Cantor Bar used to generate the columns.

Corrosion of steel reinforced concrete in the tropical coastal atmosphere of Havana City, Cuba

The influence of chloride deposition rate on concrete using an atmospheric corrosion approach is rarely studied in the literature. Seven exposure sites were selected in Havana City, Cuba, for exposure of reinforced concrete samples. Two significantly different atmospheric corrosivity levels with respect to corrosion of steel reinforced concrete were observed after two years of exposure depending on atmospheric chloride deposition and w/c ratio of the concrete. Changes in corrosion current are related to changes in chloride penetration and chloride atmospheric deposition. The influence of sulphur compound deposition could also be a parameter to consider in atmospheric corrosion of steel reinforced concrete.

Super/subcritical fluid chromatography with packed columns: state of the art and applications

Separations using supercritical fluid chromatography (SFC) with packed columns have been re-discovered and explored in recent years. SFC enables fast and efficient separations and, in some cases, gives better results than high performance liquid chromatography (HPLC). This paper provides an overview of recent advances in SFC separations using packed columns for both achiral and chiral separations. The most important types of stationary phases used in SFC are discussed as well as the most critical parameters involved in the separations and some recent applications.

Determining the concrete stiffness matrix through ultrasonic testing

The determination of the modulus tangent (Eci ) and of the modulus secant (Ecs) of the concrete can be done using compression test but, to be simpler, it is used relations with characteristic strength (f ck). Relations are also used to determine the transversal modulus (Gc) and, in the case of the Poisson's ratio (ν), a fixed value 0.20 is established. The objective of this research was to evaluate the use of the ultrasonic propagation waves to determine these properties. For the tests were used specimens with f ck varying from 10 to 35 MPa. For the ultrasonic tests were used cylindrical and cubic specimens. The modulus of deformation obtained by ultrasound was statistically equivalent to the obtained by compression tests. The results of modules obtained using the relations with f ck was far away from those obtained by ultrasound or by compression tests. The Poisson's ratio obtained by ultrasound was superior to the fixed value. We can conclude that the concrete characterization by ultrasound is consistent and, to this characterization the cylindrical specimen, normally used to determine f ck, can be used.

Physiological evaluation of heat stress in gestating sows under different housing systems in bedding and concrete floor

The purpose of this paper was to observe the use of bedding (wood shavings) in physiological variables that indicate thermal stress in gestating sows. The experiment was conducted in order to evaluate the effect of two types of floor (concrete and wood shavings). Worse microclimatic conditions were observed in bedding systems (P<0.05), with an increase in temperature and enthalpy of 1.14 ºC and 2.37 kJ.kg dry air-1, respectively. The floor temperature at the dirty area was higher in the bedding presence in comparison to its absence. In spite of the worse microclimatic conditions in the bedding, the rectal temperature did not differ significantly (P>0.05) but the skin surface temperature was higher in the bedding systems. The same occurred with the respiratory rates. The physical characteristics of the floor material influenced the rate of heat loss by conductance. Estimated values were 35.04 and 7.99 W m-2 for the conductive heat loss between the animal and floor for treatments with or without bedding, respectively. The use of bedding in sow rearing has a negative impact on microclimatic conditions, what implies in thermoregulatory damages.

Experimental Analysis of Fracture Processes in Concrete

This paper draws on the basic problems related to the determination of parameters to characterize the structural behavior of concretes using Fracture Mechanics concepts. Experimental procedures and results are discussed.

SEPARATION OF SATURED AND UNSATURATED FATTY ACIDS FROM PALM FATTY ACIDS DISTILLATES IN CONTINUOUS MULTISTAGE COUNTERCURRENT COLUMNS WITH SUPERCRITICAL CARBON DIOXIDE AS SOLVENT: A PROCESS DESIGN METHODOLOGY

In this work the separation of multicomponent mixtures in counter-current columns with supercritical carbon dioxide has been investigated using a process design methodology. First the separation task must be defined, then phase equilibria experiments are carried out, and the data obtained are correlated with thermodynamic models or empirical functions. Mutual solubilities, Ki-values, and separation factors aij are determined. Based on this data possible operating conditions for further extraction experiments can be determined. Separation analysis using graphical methods are performed to optimize the process parameters. Hydrodynamic experiments are carried out to determine the flow capacity diagram. Extraction experiments in laboratory scale are planned and carried out in order to determine HETP values, to validate the simulation results, and to provide new materials for additional phase equilibria experiments, needed to determine the dependence of separation factors on concetration. Numerical simulation of the separation process and auxiliary systems is carried out to optimize the number of stages, solvent-to-feed ratio, product purity, yield, and energy consumption. Scale-up and cost analysis close the process design. The separation of palmitic acid and (oleic+linoleic) acids from PFAD-Palm Fatty Acids Distillates was used as a case study.