945 resultados para Mean-Periodic Function
Resumo:
Patients’ bowel dysfunction is a major factor that weakens the results of surgical care as it can cause pain and weaken patients’ rehabilitation. Bowel dysfunction is a common postoperative problem, yet most incidents remain undocumented. The nursing profession has a significant role in enhancing the bowel function postoperatively. However, studies of postoperative bowel function after hepatectomy are scarce and somewhat incongruous. Enhanced recovery protocols are innovative models of care aiming for better outcomes of surgical care. Enhanced recovery protocols can improve gastrointestinal function after surgery, yet patients are also known to be satisfied with their care. The aim was to investigate if postoperative bowel function day varies between patients in terms of age, gender, ASA score, type of surgery, histology, patients’ experienced pain and experienced satisfaction three days after discharge and three months after operation in patients undergoing hepatectomy. The goal was to produce information for basis of scientific research, to give nurses in clinical setting more tools to work with hepatectomy patients undergoing enhanced recovery protocol and to produce information to nurse managers to use in process management of patients undergoing enhanced recovery protocol. The design of this study is descriptive. Data was collected retrospectively from hepatectomy patients (n = 134) undergoing enhanced recovery protocol within the first year of enhanced recovery protocol implementation. The data was based on registers and analyzed statistically. Mean age of patients was 62 years and mean day of discharge was 4. Main (n = 72) histology of the patients was colorectal liver metastases. Mean bowel function day was 3. Most of the patients were very satisfied or satisfied with the care three days after discharge (99%) and three months (90%) after operation. Most of the patients (72%) experienced moderate pain three days after discharge, but three months after operation 47% of the patients did not experience pain and 48% experienced moderate pain. There were no statistically significant differences in bowel function between different age groups, genders, ASA score groups or histologies. Neither were there statistically significant differences in postoperative bowel function in terms of experienced satisfaction or pain. There were statistically significant differences in postoperative bowel function between different types of surgery (p < 0.01). Nurses should take into consideration hepatectomy patients’ type of surgery and pay special attention in supporting major open hepatectomy patients’ postoperative bowel function. Nurses should educate patients undergoing major open hepatectomy about prolonged postoperative bowel function.
Resumo:
In a 1955 paper, Ky Fan, Olga Taussky, and John Todd presented discrete analogues of inequalities of Wirtinger type, and by taking limits they were able to recover the continuous inequalities. We generalize their techniques to mixed and higher derivatives and inequalities with weight functions in the integrals. We have also considered analogues of inequalities of Müller and Redheffer and have used these inequalities to derive a necessary and sufficient condition on ordered pairs of numbers so that the first number is the square norm of the kth derivative of some periodic function and the second number is the square norm of the mth derivative of the same periodic function.
Resumo:
We have studied the Fano resonance in photon-assisted transport through a quantum dot. Both the coherent current and the spectral density of shot noise have been calculated. It is predicted that the shape of the Fano profile will also appear in satellite peaks. It is found that the variations of Fano profiles with the strengths of nonresonant transmissions are not synchronous in absorption and emission sidebands. The effect of interference on photon-assisted pumped current has also been investigated. We further predict the current and spectral density of shot noise as a periodic function of the phase, which exhibits an intrinsic property of resonant and nonresonant channels in the structures.
Resumo:
The problem of using information available from one variable X to make inferenceabout another Y is classical in many physical and social sciences. In statistics this isoften done via regression analysis where mean response is used to model the data. Onestipulates the model Y = µ(X) +ɛ. Here µ(X) is the mean response at the predictor variable value X = x, and ɛ = Y - µ(X) is the error. In classical regression analysis, both (X; Y ) are observable and one then proceeds to make inference about the mean response function µ(X). In practice there are numerous examples where X is not available, but a variable Z is observed which provides an estimate of X. As an example, consider the herbicidestudy of Rudemo, et al. [3] in which a nominal measured amount Z of herbicide was applied to a plant but the actual amount absorbed by the plant X is unobservable. As another example, from Wang [5], an epidemiologist studies the severity of a lung disease, Y , among the residents in a city in relation to the amount of certain air pollutants. The amount of the air pollutants Z can be measured at certain observation stations in the city, but the actual exposure of the residents to the pollutants, X, is unobservable and may vary randomly from the Z-values. In both cases X = Z+error: This is the so called Berkson measurement error model.In more classical measurement error model one observes an unbiased estimator W of X and stipulates the relation W = X + error: An example of this model occurs when assessing effect of nutrition X on a disease. Measuring nutrition intake precisely within 24 hours is almost impossible. There are many similar examples in agricultural or medical studies, see e.g., Carroll, Ruppert and Stefanski [1] and Fuller [2], , among others. In this talk we shall address the question of fitting a parametric model to the re-gression function µ(X) in the Berkson measurement error model: Y = µ(X) + ɛ; X = Z + η; where η and ɛ are random errors with E(ɛ) = 0, X and η are d-dimensional, and Z is the observable d-dimensional r.v.
Resumo:
Exam questions and solutions in PDF
Resumo:
Exam questions and solutions in LaTex. Diagrams for the questions are all together in the support.zip file, as .eps files
Resumo:
A positive summability trigonometric kernel {K(n)(theta)}(infinity)(n=1) is generated through a sequence of univalent polynomials constructed by Suffridge. We prove that the convolution {K(n) * f} approximates every continuous 2 pi-periodic function f with the rate omega(f, 1/n), where omega(f, delta) denotes the modulus of continuity, and this provides a new proof of the classical Jackson`s theorem. Despite that it turns out that K(n)(theta) coincide with positive cosine polynomials generated by Fejer, our proof differs from others known in the literature.
Resumo:
GPS active networks are more and more used in geodetic surveying and scientific experiments, as water vapor monitoring in the atmosphere and lithosphere plate movement. Among the methods of GPS positioning, Precise Point Positioning (PPP) has provided very good results. A characteristic of PPP is related to the modeling and/or estimation of the errors involved in this method. The accuracy obtained for the coordinates can reach few millimeters. Seasonal effects can affect such accuracy if they are not consistent treated during the data processing. Coordinates time series analyses have been realized using Fourier or Harmonics spectral analyses, wavelets, least squares estimation among others. An approach is presented in this paper aiming to investigate the seasonal effects included in the stations coordinates time series. Experiments were carried out using data from stations Manaus (NAUS) and Fortaleza (BRFT) which belong to the Brazilian Continuous GPS Network (RBMC). The coordinates of these stations were estimated daily using PPP and were analyzed through wavelets for identification of the periods of the seasonal effects (annual and semi-annual) in each time series. These effects were removed by means of a filtering process applied in the series via the least squares adjustment (LSQ) of a periodic function. The results showed that the combination of these two mathematical tools, wavelets and LSQ, is an interesting and efficient technique for removal of seasonal effects in time series.
Resumo:
For any positive integer n, the sine polynomials that are nonnegative in [0, π] and which have the maximal derivative at the origin are determined in an explicit form. Associated cosine polynomials Kn (θ) are constructed in such a way that {Kn(θ)} is a summability kernel. Thus, for each Pi 1 ≤ P ≤ ∞ and for any 27π-periodic function f ∈ Lp [-π, π], the sequence of convolutions Kn * f is proved to converge to f in Lp[-ππ]. The pointwise and almost everywhere convergences are also consequences of our construction.
Resumo:
GPS active networks are more and more used in geodetic surveying and scientific experiments, as water vapor monitoring in the atmosphere and lithosphere plate movement. Among the methods of GPS positioning, Precise Point Positioning (PPP) has provided very good results. A characteristic of PPP is related to the modeling and / or estimation of the errors involved in this method. The accuracy obtained for the coordinates can reach few millimeters. Seasonal effects can affect such accuracy if they are not consistent treated during the data processing. Coordinates time series analyses have been realized using Fourier or Harmonics spectral analyses, wavelets, least squares estimation among others. An approach is presented in this paper aiming to investigate the seasonal effects included in the stations coordinates time series. Experiments were carried out using data from stations Manaus (NAUS) and Fortaleza (BRFT) which belong to the Brazilian Continuous GPS Network (RBMC). The coordinates of these stations were estimated daily using PPP and were analyzed through wavelets for identification of the periods of the seasonal effects (annual and semi-annual) in each time series. These effects were removed by means of a filtering process applied in the series via the least squares adjustment (LSQ) of a periodic function. The results showed that the combination of these two mathematical tools, wavelets and LSQ, is an interesting and efficient technique for removal of seasonal effects in time series.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)