How to (dis)solve Nagel's paradox about moral luck and responsibility

Abstract In this paper I defend a solution to the moral luck problem based on what I call "a fair opportunity account of control." I focus on Thomas Nagel's claim that moral luck reveals a paradox, and argue that the apparent paradox emerges only because he assumes that attributions of responsibility require agents to have total control over their actions. I argue that a more modest understanding of what it takes for someone to be a responsible agent-i.e., being capable of doing the right thing for the right reasons-dissolves the paradox and shows that responsibility and luck aren't at odds.

National Immunization Program: Computerized System as a tool for new challenges

The scope and coverage of the Brazilian Immunization Program can be compared with those in developed countries because it provides a large number of vaccines and has a considerable coverage. The increasing complexity of the program brings challenges regarding its development, high coverage levels, access equality, and safety. The Immunization Information System, with nominal data, is an innovative tool that can more accurately monitor these indicators and allows the evaluation of the impact of new vaccination strategies. The main difficulties for such a system are in its implementation process, training of professionals, mastering its use, its constant maintenance needs and ensuring the information contained remain confidential. Therefore, encouraging the development of this tool should be part of public health policies and should also be involved in the three spheres of government as well as the public and private vaccination services.

Transplants: bioethics and justice

Bioethics, as a branch of philosophy that focuses on questions relative to health and human life, is closely tied to the idea of justice and equality. As such, in understanding the concept of equality in its original sense, that is, in associating it to the idea to treat "unequals" (those who are unequal or different, in terms of conditions or circumstances) unequally (differentially), in proportion to their inequalities (differences), we see that the so-called "one-and-only waiting list" for transplants established in law no. 9.434/97, ends up not addressing the concept of equality and justice, bearing upon bioethics, even when considering the objective criteria of precedence established in regulation no. 9.4347/98, Thus, the organizing of transplants on a one-and-only waiting list, with a few exceptions that are weakly applicable, without a case by case technical and grounded analysis, according to each particular necessity, ends up institutionalizing inequalities, condemning patients to happenstance and, consequently, departs from the ratio legis, which aims at seeking the greatest application of justice in regards to organ transplants. We conclude, therefore, that from an analysis of the legislation and of the principles of bioethics and justice, there is a need for the creation of a collegiate of medical experts, that, based on medical criteria and done in a well established manner, can analyze each case to be included on the waiting list, deferentially and according to the necessity; thus, precluding that people in special circumstances be treated equal to people in normal circumstances.

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.

Um caso especial de integrais binômias

The present paper shows that the sum of two binomial integrals, such as A ∫ x p (a + bx q)r dx + B ∫ x p (a + bx q)r dx, where A and B are real constants and p, q, r are rational numbers, can, in special cases, lead to elementary integrals, even if each by itself is not elementary. An example of the case considered is given by the integral ∫ x _____-___ 3 dx = 1/2 ∫ x-½ (x - 1)-⅓ dx - 6 √ x ³√(x - 1)4 = 1/3 ∫ x-½ (x - 1)-¾ dx On the rigth hand side of the last equality both integral are not elementary. But the use of integration by parts of one of them leads to the solution: ∫ x _____-___ 3 dx = x½ (x - 1)-⅓ + C. 6 √ x ³√(x - 1)4

Introdução e avaliação de clones de goiabeira de polpa branca (Psidium guajava L.) na região do Submédio São Francisco

Objetivando avaliar a variabilidade genética e selecionar alternativas de cultivo para o mercado de goiaba " in natura" com polpa branca, foram introduzidas e avaliadas, na região do Submédio São Francisco, 22 variedades de goiaba, provenientes de um banco de gemoplasma do IPA. As mudas foram propagadas através de enxerto, utilizando-se de quatro plantas por acesso, no espaçamento de 6,0 x 6,0 m. Foram avaliados, no período de 1993 a 1998, os seguintes descritores: produção por planta (em kg), número de frutos colhidos/ciclo e peso médio do fruto em grama. Destacaram-se, no conjunto dos descritores avaliados, principalmente peso médio do fruto, um dos mais importantes descritores em goiaba para mesa, as variedades Banaras e Luck Now, com potencial agronômico para produção comercial, com produção de 98,07 kg/planta, 813 frutos/ciclo e peso médio do fruto de 176 g e 118.22 kg, 940 frutos, e peso médio de 131.39 g (média de seis anos), respectivamente. Com relação ao grau Brix, a Banaras apresentou 11,1 e a Luck Now 12,1 e uma relação SST/Acidez de 2.8 e 3.0, respectivamente.

Contact with friction using the augmented Lagrangian Method: a conditional constrained minimization problem

This work presents a formulation of the contact with friction between elastic bodies. This is a non linear problem due to unilateral constraints (inter-penetration of bodies) and friction. The solution of this problem can be found using optimization concepts, modelling the problem as a constrained minimization problem. The Finite Element Method is used to construct approximation spaces. The minimization problem has the total potential energy of the elastic bodies as the objective function, the non-inter-penetration conditions are represented by inequality constraints, and equality constraints are used to deal with the friction. Due to the presence of two friction conditions (stick and slip), specific equality constraints are present or not according to the current condition. Since the Coulomb friction condition depends on the normal and tangential contact stresses related to the constraints of the problem, it is devised a conditional dependent constrained minimization problem. An Augmented Lagrangian Method for constrained minimization is employed to solve this problem. This method, when applied to a contact problem, presents Lagrange Multipliers which have the physical meaning of contact forces. This fact allows to check the friction condition at each iteration. These concepts make possible to devise a computational scheme which lead to good numerical results.

Alan Greenspan, the confidence strategy

To evaluate the Greenspan era, we nevertheless need to address three questions: Is his success due to talent or just luck? Does he have a system of monetary policy or is he himself the system? What will be his legacy? Greenspan was certainly lucky, but he was also clairvoyant. Above all, he has developed a profoundly original monetary policy. His confidence strategy is clearly opposed to the credibility strategy developed in central banks and the academic milieu after 1980, but also inflation targeting, which today constitutes the mainstream monetary policy regime. The question of his legacy seems more nuanced. However, Greenspan will remain 'for a considerable period of time' a highly heterodox and original central banker. His political vision, his perception of an uncertain world, his pragmatism and his openness form the structure of a powerful alternative system, the confidence strategy, which will leave its mark on the history of monetary policy.

The developmental state in Brazil: comparative and historical perspectives

The record of successful developmental states in East Asia and the partial successes of developmental states in Latin America suggest several common preconditions for effective state intervention including a Weberian bureaucracy, monitoring of implementation, reciprocity (subsidies in exchange for performance), and collaborative relations between government and business. Although Brazil failed to develop the high technology manufacturing industry and exports that have fueled sustained growth in East Asia, its developmental state had a number of important, and often neglected, successes, especially in steel, automobiles, mining, ethanol, and aircraft manufacturing. Where Brazil's developmental state was less successful was in promoting sectors like information technology and nuclear energy, as well as overall social and regional equality. In addition, some isolated initiatives by state governments were also effective in promoting particular local segments of industry and agriculture. Comparisons with East Asia, highlight the central role of state enterprises in Brazil that in effect internalized monitoring and reciprocity and bypassed collaboration between business and government (that was overall rarer in Brazil).