Long-term evaluation of a sequential batch reactor (SBR) treating dairy wastewater for carbon removal.

Many dairy industries have been using SBR wastewater treatment plants because they allow optimal working condition to be reached. However, to take advantage of SBR capabilities, strong process automation is needed. The aim of this work is to study the factors that influence SBR performance to improve modelling and control. To better understand the whole process we studied the kinetic modelling, the carbon removal mechanism and the relation between reactor performance, aerobic heterotrophic activity and bacterial population dynamics (by terminal restriction fragment length polymorphisms of 16S rDNA, T-RFLP). The heterotrophic activity values presented high variability during some periods; however, this was not reflected on the reactor performance. As sludge health indicator, the average activity in a period was better than individual values. Although all the carbon removal mechanisms are still unclear for this process, they seemed to be influenced by non-respirometric ways (storage, biosorption, accumulation, etc.). The variability of heterotrophic activity could be correlated with the bacterial population diversity over time. Despite the high variability of the activity, a simple kinetic model (pseudo ASM1) based on apparent constant parameters was developed and calibrated. Such modellisation provided a good tool for control purposes.

Correlations between frequency-domain HRV indices and lagged Poincaré plot width in healthy and diabetic subjects.

The conventional Poincaré plot for heart rate variability (HRV) analysis is a scatterplot of successive (lag 1) pairs of RR intervals (intervals between heartbeats), and its width (SD1) is considered a measure of short-term variability. It has been shown that SD1 correlates better with HF than with LF (high- and low-frequency bands of the spectrum, respectively). Our aim was to assess how these correlations were affected when SD1 was obtained for longer lags. 10 min ECGs were used to construct Poincaré plots with lags of 1-10 heartbeats in two groups of subjects, one with normal HRV and the other with impaired HRV (control and diabetic groups respectively, N = 15 each). SD1 was quantified for these subjects and HRV spectral indices were estimated. The diabetic group had lower LF, HF and SD1 than the control group (p < 0.05). In both groups, SD1 tended to increase as the lag increased. In the control group, SD1 for lags 1 and 2 was highly correlated with HF (r(s) > 0.9), while SD1 for lags 4 correlated better with LF (r(s) 0.9) than with HF (0.65

Short-term studies of heart rate variability: comparison of two methods for recording.

Heart rate variability (HRV) is often analysed using short-term studies. Our objective was to compare two of them in a group of diabetic patients (reduced HRV) and in a control group. From the same 10 min surface electrocardiogram (ECG) two recordings were obtained. In one of them the whole signal was acquired through an A/D converter (post-event method). In the other (real-time method), an interface between the electrocardiograph and a parallel port of a computer was used to perform real-time processing of the ECG signal. The R-R intervals were measured after a visual validation in the post-event method. In the real-time method, the stored R-R intervals were automatically filtered. For both methods HRV indexes were calculated using the same software. The values of mean R-R intervals for each subject were almost identical regardless of the method. Accordingly, we found a high correlation between HRV indexes obtained from both methods (all Spearman values > or = 0.9441 and P < 0.0001). In addition, we found similar P values in the comparisons between the diabetic and control groups. We conclude that both methods are suitable for HRV analysis. Therefore, the selection of method can be based on other considerations such as the capability to store the ECG of the post-event method or the speed of analysis and lower cost of the real-time one.

Electric images of two low resistance objects in weakly electric fish.

Electroreceptive fish detect nearby objects by processing the information contained in the pattern of electric currents through their skin. In weakly electric fish, these currents arise from a self-generated field (the electric organ discharge), depending on the electrical properties of the surrounding medium. The electric image can be defined as the pattern of transepidermal voltage distributed over the receptive surface. To understand electrolocation it is necessary to know how electric image of objects are generated. In pulse mormyrids, the electric organ is localized at the tail, far from the receptors and fires a short biphasic pulse. Consequently, if all the elements in the environment are resistive, the stimulus at every point on the skin has the same waveform. Then, any measure of the amplitude (for example, the peak to peak amplitude) could be the unique parameter of the stimulus at any point of the skin. We have developed a model to calculate the image, corroborating that images are spread over the whole sensory surface and have an opposite center-surround, "Mexican-hat" shape. As a consequence, the images of different objects superimpose. We show theoretically and by simulation that the image of a pair of objects is not the simple addition of the individual images of these objects.