930 resultados para stars: variables: T Tauri
Resumo:
Owing to widespread applications, synthesis and characterization of silver nanoparticles is recently attracting considerable attention. Increasing environmental concerns over chemical synthesis routes have resulted in attempts to develop biomimetic approaches. One of them is synthesis using plant parts, which eliminates the elaborate process of maintaining the microbial culture and often found to be kinetically favourable than other bioprocesses. The present study deals with investigating the effect of process variables like reductant concentrations, reaction pH, mixing ratio of the reactants and interaction time on the morphology and size of silver nanoparticles synthesized using aqueous extract of Azadirachta indica (Neem) leaves. The formation of crystalline silver nanoparticles was confirmed using X-ray diffraction analysis. By means of UV spectroscopy, Scanning and Transmission Electron Microscopy techniques, it was observed that the morphology and size of the nanoparticles were strongly dependent on the process parameters. Within 4 h interaction period, nanoparticles below 20-nm-size with nearly spherical shape were produced. On increasing interaction time (ageing) to 66 days, both aggregation and shape anisotropy (ellipsoidal, polyhedral and capsular) of the particles increased. In alkaline pH range, the stability of cluster distribution increased with a declined tendency for aggregation of the particles. It can be inferred from the study that fine tuning the bioprocess parameters will enhance possibilities of desired nano-product tailor made for particular applications.
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Einstein's general relativity is a classical theory of gravitation: it is a postulate on the coupling between the four-dimensional, continuos spacetime and the matter fields in the universe, and it yields their dynamical evolution. It is believed that general relativity must be replaced by a quantum theory of gravity at least at extremely high energies of the early universe and at regions of strong curvature of spacetime, cf. black holes. Various attempts to quantize gravity, including conceptually new models such as string theory, have suggested that modification to general relativity might show up even at lower energy scales. On the other hand, also the late time acceleration of the expansion of the universe, known as the dark energy problem, might originate from new gravitational physics. Thus, although there has been no direct experimental evidence contradicting general relativity so far - on the contrary, it has passed a variety of observational tests - it is a question worth asking, why should the effective theory of gravity be of the exact form of general relativity? If general relativity is modified, how do the predictions of the theory change? Furthermore, how far can we go with the changes before we are face with contradictions with the experiments? Along with the changes, could there be new phenomena, which we could measure to find hints of the form of the quantum theory of gravity? This thesis is on a class of modified gravity theories called f(R) models, and in particular on the effects of changing the theory of gravity on stellar solutions. It is discussed how experimental constraints from the measurements in the Solar System restrict the form of f(R) theories. Moreover, it is shown that models, which do not differ from general relativity at the weak field scale of the Solar System, can produce very different predictions for dense stars like neutron stars. Due to the nature of f(R) models, the role of independent connection of the spacetime is emphasized throughout the thesis.
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The paper presents simple graphical procedures for position synthesis of plane linkage mechanisms to generate functions of two independent variables. The procedures are based on point-position reduction and permit synthesis of the linkage to satisfy up to six arbitrarily selected precision positions.
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The paper presents simple graphical procedures for the position synthesis of plane linkage mechanisms with sliding inputs and output to generate functions of two independent variables. The procedures are based on point position reduction and permit synthesis of the linkage to satisfy up to five arbitrarily selected precision positions.
Resumo:
In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).
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A computer code is developed as a part of an ongoing project on computer aided process modelling of forging operation, to simulate heat transfer in a die-billet system. The code developed on a stage-by-stage technique is based on an Alternating Direction Implicit scheme. The experimentally validated code is used to study the effect of process specifics such as preheat die temperature, machine ascent time, rate of deformation, and dwell time on the thermal characteristics in a batch coining operation where deformation is restricted to surface level only.
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A technique based on empirical orthogonal functions is used to estimate hydrologic time-series variables at ungaged locations. The technique is applied to estimate daily and monthly rainfall, temperature and runoff values. The accuracy of the method is tested by application to locations where data are available. The second-order characteristics of the estimated data are compared with those of the observed data. The results indicate that the method is quick and accurate.
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Hamiltonian systems in stellar and planetary dynamics are typically near integrable. For example, Solar System planets are almost in two-body orbits, and in simulations of the Galaxy, the orbits of stars seem regular. For such systems, sophisticated numerical methods can be developed through integrable approximations. Following this theme, we discuss three distinct problems. We start by considering numerical integration techniques for planetary systems. Perturbation methods (that utilize the integrability of the two-body motion) are preferred over conventional "blind" integration schemes. We introduce perturbation methods formulated with Cartesian variables. In our numerical comparisons, these are superior to their conventional counterparts, but, by definition, lack the energy-preserving properties of symplectic integrators. However, they are exceptionally well suited for relatively short-term integrations in which moderately high positional accuracy is required. The next exercise falls into the category of stability questions in solar systems. Traditionally, the interest has been on the orbital stability of planets, which have been quantified, e.g., by Liapunov exponents. We offer a complementary aspect by considering the protective effect that massive gas giants, like Jupiter, can offer to Earth-like planets inside the habitable zone of a planetary system. Our method produces a single quantity, called the escape rate, which characterizes the system of giant planets. We obtain some interesting results by computing escape rates for the Solar System. Galaxy modelling is our third and final topic. Because of the sheer number of stars (about 10^11 in Milky Way) galaxies are often modelled as smooth potentials hosting distributions of stars. Unfortunately, only a handful of suitable potentials are integrable (harmonic oscillator, isochrone and Stäckel potential). This severely limits the possibilities of finding an integrable approximation for an observed galaxy. A solution to this problem is torus construction; a method for numerically creating a foliation of invariant phase-space tori corresponding to a given target Hamiltonian. Canonically, the invariant tori are constructed by deforming the tori of some existing integrable toy Hamiltonian. Our contribution is to demonstrate how this can be accomplished by using a Stäckel toy Hamiltonian in ellipsoidal coordinates.
Resumo:
Hypertension is one of the major risk factors for cardiovascular morbidity. The advantages of antihypertensive therapy have been clearly demonstrated, but only about 30% of hypertensive patients have their blood pressure (BP) controlled by such treatment. One of the reasons for this poor BP control may lie in the difficulty in predicting BP response to antihypertensive treatment. The average BP reduction achieved is similar for each drug in the main classes of antihypertensive agents, but there is a marked individual variation in BP responses to any given drug. The purpose of the present study was to examine BP response to four different antihypertensive monotherapies with regard to demographic characteristics, laboratory test results and common genetic polymorphisms. The subjects of the present study are participants in the pharmacogenetic GENRES Study. A total of 208 subjects completed the whole study protocol including four drug treatment periods of four weeks, separated by four-week placebo periods. The study drugs were amlodipine, bisoprolol, hydrochlorothiazide and losartan. Both office (OBP) and 24-hour ambulatory blood pressure (ABP) measurements were carried out. BP response to study drugs were related to basic clinical characteristics, pretreatment laboratory test results and common polymorphisms in genes coding for components of the renin-angiotensin system, alpha-adducin (ADD1), beta1-adrenergic receptor (ADRB1) and beta2-adrenergic receptor (ADRB2). Age was positively correlated with BP responses to amlodipine and with OBP and systolic ABP responses to hydrochlorothiazide, while body mass index was negatively correlated with ABP responses to amlodipine. Of the laboratory test results, plasma renin activity (PRA) correlated positively with BP responses to losartan, with ABP responses to bisoprolol, and negatively with ABP responses to hydrochlorothiazide. Uniquely to this study, it was found that serum total calcium level was negatively correlated with BP responses to amlodipine, whilst serum total cholesterol level was negatively correlated with ABP responses to amlodipine. There were no significant associations of angiotensin II type I receptor 1166A/C, angiotensin converting enzyme I/D, angiotensinogen Met235Thr, ADD1 Gly460Trp, ADRB1 Ser49Gly and Gly389Arg and ADRB2 Arg16Gly and Gln27Glu polymorphisms with BP responses to the study drugs. In conclusion, this study confirmed the relationship between pretreatment PRA levels and response to three classes of antihypertensive drugs. This study is the first to note a significant inverse relation between serum calcium level and responsiveness to a calcium channel blocker. However, this study could not replicate the observations that common polymorphisms in angiotensin II type I receptor, angiotensin converting enzyme, angiotensinogen, ADD1, ADRB1, or ADRB2 genes can predict BP response to antihypertensive drugs.
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Consider L independent and identically distributed exponential random variables (r.vs) X-1, X-2 ,..., X-L and positive scalars b(1), b(2) ,..., b(L). In this letter, we present the probability density function (pdf), cumulative distribution function and the Laplace transform of the pdf of the composite r.v Z = (Sigma(L)(j=1) X-j)(2) / (Sigma(L)(j=1) b(j)X(j)). We show that the r.v Z appears in various communication systems such as i) maximal ratio combining of signals received over multiple channels with mismatched noise variances, ii)M-ary phase-shift keying with spatial diversity and imperfect channel estimation, and iii) coded multi-carrier code-division multiple access reception affected by an unknown narrow-band interference, and the statistics of the r.v Z derived here enable us to carry out the performance analysis of such systems in closed-form.
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A review of the research work that has been carried out thus far relating the casting and heat treatment variables to the structure and mechanical properties of Al–7Si–Mg (wt-%) is presented here. Although specifications recommend a wide range of magnesium contents and a fairly high content of iron, a narrow range of magnesium contents, closer to either the upper or lower specified limits depending on the properties desired, and a low iron content will have to be maintained to obtain optimum and consistent mechanical properties. A few studies have revealed that the modification of eutectic silicon slightly increases ductility and fracture toughness and also that the effect of modification is predominant at low iron content. Generally, higher solidification rates give superior mechanical properties. Delayed aging (the time elapsed between quenching and artificial aging during precipitation hardening) severely affects the strength of the alloy. The mechanism of delayed aging can be explained on the basis of Pashley's kinetic model. It has been reported that certain trace additions (cadmium, indium, tin, etc.) neutralise the detrimental effect of delayed aging. In particular, it should be noted that delayed aging is not mentioned in any of the specifications. With reference to the mechanism by which trace additions neutralise the detrimental effect of delayed aging, various hypotheses have been postulated, of which impurity–vacancy interaction appears to be the most widely accepted.
Resumo:
During their main sequence evolution, massive stars can develop convective regions very close to their surface. These regions are caused by an opacity peak associated with iron ionization. Cantiello et al. (2009) found a possible connection between the presence of sub-photospheric convective motions and small scale stochastic velocities in the photosphere of early-type stars. This supports a physical mechanism where microturbulence is caused by waves that are triggered by subsurface convection zones. They further suggest that clumping in the inner parts of the winds of OB stars could be related to subsurface convection, and that the convective layers may also be responsible for stochastic excitation of non-radial pulsations. Furthermore, magnetic fields produced in the iron convection zone could appear at the surface of such massive stars. Therefore subsurface convection could be responsible for the occurrence of observable phenomena such as line profile variability and discrete absorption components. These phenomena have been observed for decades, but still evade a clear theoretical explanation. Here we present preliminary results from 3D MHD simulations of such subsurface convection.