992 resultados para process variations


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Moving grate, LEPOL, Particle, Limestone, Decomposition, Clinker, Fluidisation

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Abstract Background: Due to the importance of coronary artery disease (CAD), continuous investigation of the risk factors (RFs) is needed. Objective: To evaluate the prevalence of RFs for CAD in cities in Rio Grande do Sul State, and compare it with that reported in a similar study conducted in the same cities in 2002. Methods: Cross-sectional study on 1,056 healthy adults, investigating the prevalence and absolute and relative frequencies of the following RFs for CAD: obesity, systemic arterial hypertension (SAH), dyslipidemias, smoking, sedentary lifestyle, diabetes mellitus, and family history, as well as age and sex. Data was collected in 19 cities, host of the Offices of the Regional Coordinators of Health, as in the 2002 study. Results: Twenty-six percent of the sample consisted of older adults and 57% were women. The prevalence of sedentary lifestyle was 44%, history family 50%, smoking 23%, overweight/obesity 68%, dyslipidemia (high cholesterol levels) 43%, SAH 40%, and diabetes 11%. When compared to the 2002 study, the prevalence of active smoking and sedentary behavior decreased, whereas the prevalence of hypertension, dyslipidemia and obesity increased. Obesity is the most prevalent RF in women, and SAH the most prevalent in men. Conclusions: The prevalence of RFs for CAD in Rio Grande do Sul State remains high. Hypertension, obesity and dyslipidemia are still prevalent and require major prevention programs. Smoking and physical inactivity have decreased in the state, suggesting the efficacy of related campaigns.

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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2010

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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2010

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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.

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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012

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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

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This article describes the problem of commercializing of scientific researches in universities. Management tasks are reduced to subtasks and combined formal algorithm. The overall control problem is reduced to a set of formal subtasks combined into a single algorithm. Here the necessity of joint control of all commercialization projects as well as the use of information systems for the successful implementation of the existing commercialpotential is shown.

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This work presents the results of an investigation of processes in the melting zone during Electron Beam Welding(EBW) through analysis of the secondary current in the plasma.The studies show that the spectrum of the secondary emission signal during steel welding has a pronounced periodic component at a frequency of around 15–25 kHz. The signal contains quasi-periodic sharp peaks (impulses). These impulses have stochastically varying amplitude and follow each other inseries, at random intervals between series. The impulses have a considerable current (up to 0.5 A). It was established that during electron-beam welding with the focal spot scanning these impulses follow each other almost periodically. It was shown that the probability of occurrence of these high-frequency perturbation increases with the concentration of energy in the interaction zone. The paper also presents hypotheses for the mechanism of the formation of the high-frequency oscillations in the secondary current signal in the plasma.

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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

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The organic and inorganic forms of soil nitrogen and how they participate in the process of fixation, immobilization and mineralization of ammonium in soils were evaluated, after different periods of incubaton, utilizing two soils, a Lithic Haplustoll and a Typic Eutrorthox. The results obtained permit to suggest that : 1) The method for determination of the ammonium fixing capacity based on the extraction with 2N KC1, is considered to be subject to interferences of other soil fractions capable of retaining ammonium. 2) The increase in exchangeable ammonium content is related to the decrease in amino acids and hydrolyzable ammonium. 3) The immobilization and mineralization processes are still held under mil microbial. The forms more affected by this condition are amino acids and hydrolyzable ammonium.

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The goal of this study was to evaluate the effects of seasonal variations on energy metabolism in different tissues of the freshwater crayfish Parastacus brasiliensis (von Martens, 1869). Crayfish were collected monthly from January 2001 to January 2003 in São Francisco de Paula, Rio Grande do Sul, Brazil, in a stream and in a culture tank. Haemolymph samples were collected from each crayfish in the field with a syringe, by puncturing the membrane at the base of the chelipeds. Hepatopancreas, gills, and abdominal muscle were removed for determination of free glucose, glycogen, total lipids, and triglycerides. The haemolymph samples were used for determination of glucose, total proteins, total lipids, and triglycerides. Statistical analysis revealed significant differences in biochemical composition in crayfish collected in the stream compared to the experimental tank during the year, principally in glucose and triglycerides in haemolymph, glycogen and total lipids in all tissues study, and triglycerides only in abdominal muscle. The regular food intake partially modified these seasonal variations of the metabolic pattern. Environmental conditions (e.g., food availability and water temperature) and reproductive period appeared to be the main factors influencing the seasonal patterns of variation in energy metabolism.

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Crustacean growth studies typically use modal analysis rather than focusing on the growth of individuals. In the present work, we use geometric morphometrics to determine how organism shape and size varies during the life of the freshwater crab, Aegla uruguayana Schmitt, 1942. A total of 66 individuals from diverse life cycle stages were examined daily and each exuvia was recorded. Digital images of the dorsal region of the cephalothorax were obtained for each exuvia and were subsequently used to record landmark configurations. Moult increment and intermoult period were estimated for each crab. Differences in shape between crabs of different sizes (allometry) and sexes (sexual dimorphism; SD) were observed. Allometry was registered among specimens; however, SD was not statistically significant between crabs of a given size. The intermoult period increased as size increased, but the moult frequency was similar between the sexes. Regarding ontogeny, juveniles had short and blunt rostrum, robust forehead region, and narrow cephalothorax. Unlike juveniles crabs, adults presented a well-defined anterior and posterior cephalothorax region. The rostrum was long and stylised and the forehead narrow. Geometric morphometric methods were highly effective for the analysis of aeglid-individual- growth and avoided excessive handling of individuals through exuvia analysis.