A tour through Sweden, Swedish-Lapland, Finland and Denmark. In a series of letters, illustrated with engravings : by Matthew Consett, esq.

P. 143-158 are misnumbered 142-157.

Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil

This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.

Anaerobic-aerobic treatment of swine wastewater in uasb and batch reactors in series

In this work it was evaluated the performance of two systems of swine wastewater treatment consisting of two-stage upflow anaerobic sludge blanket (UASB) reactors, with and without post-treatment in sequencing batch reactor (SBR), fed continuously, with aerobic phase. The UASB reactors in the first stage had 908 L in the sets I and II, and in the second stage 350 and 188 L, respectively. In the set II the post-treatment was performed in a SBR of 3,000 L. The hydraulic detention times in the anaerobic treatment systems were 100, 75 and 58 h in the set I; 87, 65 and 51 h in the set II; and 240 and 180 h in the SBR. The volumetric organic load applied in the first stage UASB reactors ranged from 6.9 to 12.6 g total COD (L d)-1 in the set I and 7.5 to 9.8 g total COD (L d)-1 in the set II. The average removal efficiencies of total COD, total phosphorus (Ptotal), and Kjeldahl and organic nitrogen (KN and Norg) in the anaerobic treatment systems were similar and reached maximum values of 97%, 64%, 68%, and 98%. In the SBR, the removal efficiencies of total COD and thermotolerant coliforms were up to 62 and 92% resulting, respectively, in effluent concentrations of 135 mg L-1 and 2x10(4)MPN (100 mL)-1. For Ptotal, total nitrogen (TN) and Norg, the average removal efficiencies in the SBR were up to 58, 25 and 73%, respectively.

Plastic surgery in chest wall reconstruction: relevant aspects - case series

Objective: to discuss the participation of Plastic Surgery in the reconstruction of the chest wall, highlighting relevant aspects of interdisciplinaryness. Methods: we analyzed charts from 20 patients who underwent extensive resection of the thoracic integument, between 2000 and 2014, recording the indication of resection, the extent and depth of the raw areas, types of reconstructions performed and complications. Results: among the 20 patients, averaging 55 years old, five were males and 15 females. They resections were: one squamous cell carcinoma, two basal cell carcinomas, five chondrosarcomas and 12 breast tumors. The extent of the bloody areas ranged from 4x9 cm to 25x40 cm. In 12 patients the resection included the muscular plane. In the remaining eight, the tumor removal achieved a total wall thickness. For reconstruction we used: one muscular flap associated with skin grafting, nine flaps and ten regional fasciocutaneous flaps. Two patients undergoing reconstruction with fasciocutaneous flaps had partially suffering of the flap, solved with employment of a myocutaneous flap. The other patients displayed no complications with the techniques used, requiring only one surgery. Conclusion: the proper assessment of local tissues and flaps available for reconstruction, in addition to the successful integration of Plastic Surgery with the specialties involved in the treatment, enable extensive resections of the chest wall and reconstructions that provide patient recovery.

Pregnancy in women undergoing hemodialysis: case series in a Southeast Brazilian reference center

PURPOSE: To describe maternal and neonatal outcomes in pregnant women undergoing hemodialysis in a referral center in Brazilian Southeast side.METHODS: Retrospective and descriptive study, with chart review of all pregnancies undergoing hemodialysis that were followed-up at an outpatient clinic of high- risk prenatal care in Southeast Brazil.RESULTS: Among the 16 women identified, 2 were excluded due to follow-up loss. In 14 women described, hypertension was the most frequent cause of chronic renal failure (half of cases). The majority (71.4%) had performed hemodialysis treatment for more than one year and all of them underwent 5 to 6 hemodialysis sessions per week. Eleven participants had chronic hypertension, 1 of which was also diabetic, and 6 of them were smokers. Regarding pregnancy complications, 1 of the hypertensive women developed malignant hypertension (with fetal growth restriction and preterm delivery at 29 weeks), 2 had acute pulmonary edema and 2 had abruption placenta. The mode of delivery was cesarean section in 9 women (64.3%). All neonates had Apgar score at five minutes above 7.CONCLUSIONS: To improve perinatal and maternal outcomes of women undergoing hemodialysis, it is important to ensure multidisciplinary approach in referral center, strict control of serum urea, hemoglobin and maternal blood pressure, as well as close monitoring of fetal well-being and maternal morbidities. Another important strategy is suitable guidance for contraception in these women.

Nash Standard Six series

kuv., 24 x 18 cm

Estimating Attractor Dimension on the Nonlinear Pendulum Time Series

Chaotic dynamical systems exhibit trajectories in their phase space that converges to a strange attractor. The strangeness of the chaotic attractor is associated with its dimension in which instance it is described by a noninteger dimension. This contribution presents an overview of the main definitions of dimension discussing their evaluation from time series employing the correlation and the generalized dimension. The investigation is applied to the nonlinear pendulum where signals are generated by numerical integration of the mathematical model, selecting a single variable of the system as a time series. In order to simulate experimental data sets, a random noise is introduced in the time series. State space reconstruction and the determination of attractor dimensions are carried out regarding periodic and chaotic signals. Results obtained from time series analyses are compared with a reference value obtained from the analysis of mathematical model, estimating noise sensitivity. This procedure allows one to identify the best techniques to be applied in the analysis of experimental data.

Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

Interactions between soybean and weeds in a replacement series system, considering the effects of water stress

Due to the increase of water deficiency in many farm regions and its meaning on weed interference, competitive interactions between soybean and three weeds were evaluated under water stress (20 to 40 days after transplanting) and no stress conditions. Three independent experiments were carried out in a growth chamber, being each one composed by the weeds Alternanthera tenella, Tridax procumbens or Digitaria ciliaris, along with the crop, in which soil water condition and plant composition effects were evaluated while in competition. A replacement series system was used, including both monoculture of each species and a mixture with a ratio of 50% between weed and soybean. A completely randomized design was used in factorial arrangement, with treatments distributed in three levels for plant composition factor (soybean and weeds monocultures, in addition to the soybean + weed mixture) and two levels for the water factor (with or without stress), amounting six treatments in each experiment. Soybean dry mass was higher than weed dry mass, when growing without water stress. However, under water stress conditions, the dry mass of soy was reduced in all experiments, mainly in the D. ciliaris comparative experiment. Water restriction was also significant in the plants' photosynthesis reduction in most of the experiments, reducing leaf area duration and efficiency of water use. Analysing all variables shows greater weed tolerance than soybean when submitted to water deficit and with distinct changes of their interactions and mechanism of competition, in each experiment.

A comparative analysis of preprocessing techniques of cardiac event series for the study of heart rhythm variability using simulated signals

In the present study, using noise-free simulated signals, we performed a comparative examination of several preprocessing techniques that are used to transform the cardiac event series in a regularly sampled time series, appropriate for spectral analysis of heart rhythm variability (HRV). First, a group of noise-free simulated point event series, which represents a time series of heartbeats, was generated by an integral pulse frequency modulation model. In order to evaluate the performance of the preprocessing methods, the differences between the spectra of the preprocessed simulated signals and the true spectrum (spectrum of the model input modulating signals) were surveyed by visual analysis and by contrasting merit indices. It is desired that estimated spectra match the true spectrum as close as possible, showing a minimum of harmonic components and other artifacts. The merit indices proposed to quantify these mismatches were the leakage rate, defined as a measure of leakage components (located outside some narrow windows centered at frequencies of model input modulating signals) with respect to the whole spectral components, and the numbers of leakage components with amplitudes greater than 1%, 5% and 10% of the total spectral components. Our data, obtained from a noise-free simulation, indicate that the utilization of heart rate values instead of heart period values in the derivation of signals representative of heart rhythm results in more accurate spectra. Furthermore, our data support the efficiency of the widely used preprocessing technique based on the convolution of inverse interval function values with a rectangular window, and suggest the preprocessing technique based on a cubic polynomial interpolation of inverse interval function values and succeeding spectral analysis as another efficient and fast method for the analysis of HRV signals

The time series convergence of dispersion in financial analysts' forecasts

Finansanalytiker har en stor betydelse för finansmarknaderna, speciellt igenom att förmedla information genom resultatprognoser. Typiskt är att analytiker i viss grad är oeniga i sina resultatprognoser, och det är just denna oenighet analytiker emellan som denna avhandling studerar. Då ett företag rapporterar förluster tenderar oenigheten gällande ett företags framtid att öka. På ett intuitivt plan är det lätt att tolka detta som ökad osäkerhet. Det är även detta man finner då man studerar analytikerrapporter - analytiker ser ut att bli mer osäkra då företag börjar gå med förlust, och det är precis då som även oenigheten mellan analytikerna ökar. De matematisk-teoretiska modeller som beskriver analytikers beslutsprocesser har däremot en motsatt konsekvens - en ökad oenighet analytiker emellan kan endast uppkomma ifall analytikerna blir säkrare på ett individuellt plan, där den drivande kraften är asymmetrisk information. Denna avhandling löser motsägelsen mellan ökad säkerhet/osäkerhet som drivkraft bakom spridningen i analytikerprognoser. Genom att beakta mängden publik information som blir tillgänglig via resultatrapporter är det inte möjligt för modellerna för analytikers beslutsprocesser att ge upphov till de nivåer av prognosspridning som kan observeras i data. Slutsatsen blir därmed att de underliggande teoretiska modellerna för prognosspridning är delvis bristande och att spridning i prognoser istället mer troligt följer av en ökad osäkerhet bland analytikerna, i enlighet med vad analytiker de facto nämner i sina rapporter. Resultaten är viktiga eftersom en förståelse av osäkerhet runt t.ex. resultatrapportering bidrar till en allmän förståelse för resultatrapporteringsmiljön som i sin tur är av ytterst stor betydelse för prisbildning på finansmarknader. Vidare används typiskt ökad prognosspridning som en indikation på ökad informationsasymmetri i redovisningsforskning, ett fenomen som denna avhandling därmed ifrågasätter.

In vitro antimicrobial activity of a new series of 1,4-naphthoquinones

The antibacterial activity of a series of 1,4-naphthoquinones was demonstrated. Disk diffusion tests were carried out against several Gram-positive and Gram-negative bacteria. The compound 5-amino-8-hydroxy-1,4-naphthoquinone was the most effective, presenting inhibition zones measuring 20 mm against staphylococci, streptococci and bacilli at 50 µg/ml. Methicillin-resistant Staphylococcus aureus and several clinical isolates of this bacterium were also inhibited. Naphthazarin, 5-acetamido-8-hydroxy-1,4-naphthoquinone, and 2,3-diamino-1,4-naphthoquinone were the next most active compounds. The minimal inhibitory concentration of the active compounds was determined against S. aureus, ranging from 30 to 125 µg/ml. All compounds presented a minimal bactericidal concentration higher than 500 µg/ml, indicating that their effect was bacteriostatic. The EC50, defined as the drug concentration that produces 50% of maximal effect, was 8 µg/ml for 5-amino-8-hydroxy-1,4-naphthoquinone against S. aureus, S. intermedius, and S. epidermidis. These results indicate an effective in vitro activity of 5-amino-8-hydroxy-1,4-naphthoquinone and encourage further studies for its application in antibiotic therapy.

Parameter identification in time series models

Time series analysis can be categorized into three different approaches: classical, Box-Jenkins, and State space. Classical approach makes a basement for the analysis and Box-Jenkins approach is an improvement of the classical approach and deals with stationary time series. State space approach allows time variant factors and covers up a broader area of time series analysis. This thesis focuses on parameter identifiablity of different parameter estimation methods such as LSQ, Yule-Walker, MLE which are used in the above time series analysis approaches. Also the Kalman filter method and smoothing techniques are integrated with the state space approach and MLE method to estimate parameters allowing them to change over time. Parameter estimation is carried out by repeating estimation and integrating with MCMC and inspect how well different estimation methods can identify the optimal model parameters. Identification is performed in probabilistic and general senses and compare the results in order to study and represent identifiability more informative way.

Sentinel node biopsy in breast cancer: results in a large series

Sentinel lymph node biopsy (SLNB) is an appropriate method for the evaluation of axillary status in cases of early breast cancer. We report our experience in treating cases evaluated using SLNB. We analyzed a total of 1192 cases assessed by means of SLNB from July 1999 to December 2007. SLNB processing was successfully completed in 1154 cases with the use of blue dye or radiolabeled 99mTc-Dextran-500, or both. Of these 1154 patients, 857 were N0(i-) (no regional lymph node metastasis, negative immunohistochemistry, IHC), 96 were N0(i+) (no regional lymph node metastasis histologically, positive IHC, no IHC cluster greater than 0.2 mm) and 201 were N1mi (greater than 0.2 mm, none greater than 2.0 mm). Most of the tumors (70%) were invasive ductal carcinomas and tumors were staged as T1 in 770 patients (65%). A total of 274 patients underwent SLNB and axillary dissections up to April 2003. The inclusion criteria were tumor size equal to or less than 3 cm in diameter, no clinically palpable axillary lymph nodes, no neoadjuvant therapy. In 19 cases, the SLN could not be identified intraoperatively. A false-negative rate of 11% and a negative predictive value of 88.2% were obtained for the 255 assessable patients. The overall concordance between SLNB and axillary lymph node status was 92%. SLNB sensitivity for nodes was 81% and specificity was 100%. The higher sensitivity, specificity, accuracy, and lower false-negative rates of SLNB suggest that this method may be an appropriate alternative to total axillary dissection in early breast cancer patients.