THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS

The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the principles of neural science provide an instance of how biological processes may inspire novel methods in mathematical modeling and engineering. The application ofmathematical models towards understanding neural signals and systems represents a vibrant field of research that has spanned over half a century. During this period, multiple approaches to neuronal modeling have been adopted, and each approach is adept at elucidating a specific aspect of nervous system function. Thus while bio-physical models have strived to comprehend the dynamics of actual physical processes occurring within a nerve cell, the phenomenological approach has conceived models that relate the ionic properties of nerve cells to transitions in neural activity. Further-more, the field of neural networks has endeavored to explore how distributed parallel processing systems may become capable of storing memory. Through this project, we strive to explore how some of the insights gained from biophysical neuronal modeling may be incorporated within the field of neural net-works. We specifically study the capabilities of a simple neural model, the Resonate-and-Fire (RAF) neuron, whose derivation is inspired by biophysical neural modeling. While reflecting further biological plausibility, the RAF neuron is also analytically tractable, and thus may be implemented within neural networks. In the following thesis, we provide a brief overview of the different approaches that have been adopted towards comprehending the properties of nerve cells, along with the framework under which our specific neuron model relates to the field of neuronal modeling. Subsequently, we explore some of the time-dependent neurocomputational capabilities of the RAF neuron, and we utilize the model to classify logic gates, and solve the classic XOR problem. Finally we explore how the resonate-and-fire neuron may be implemented within neural networks, and how such a network could be adapted through the temporal backpropagation algorithm.

Optimization of the irrigation time and irrigation frequency by using Hydrus-2D and a capacitance FDR sensor

The evolution of water content on a sandy soil during the sprinkler irrigation campaign, in the summer of 2010, of a field of sugar beet crop located at Valladolid (Spain) is assessed by a capacitive FDR (Frequency Domain Reflectometry) EnviroScan. This field is one of the experimental sites of the Spanish research center for the sugar beet development (AIMCRA). The objective of the work focus on monitoring the soil water content evolution of consecutive irrigations during the second two weeks of July (from the 12th to the 28th). These measurements will be used to simulate water movement by means of Hydrus-2D. The water probe logged water content readings (m3/m3) at 10, 20, 40 and 60 cm depth every 30 minutes. The probe was placed between two rows in one of the typical 12 x 15 m sprinkler irrigation framework. Furthermore, a texture analysis at the soil profile was also conducted. The irrigation frequency in this farm was set by the own personal farmer 0 s criteria that aiming to minimizing electricity pumping costs, used to irrigate at night and during the weekend i.e. longer irrigation frequency than expected. However, the high evapotranspiration rates and the weekly sugar beet water consumption—up to 50mm/week—clearly determined the need for lower this frequency. Moreover, farmer used to irrigate for six or five hours whilst results from the EnviroScan probe showed the soil profile reaching saturation point after the first three hours. It must be noted that AIMCRA provides to his members with a SMS service regarding weekly sugar beet water requirement; from the use of different meteorological stations and evapotranspiration pans, farmers have an idea of the weekly irrigation needs. Nevertheless, it is the farmer 0 s decision to decide how to irrigate. Thus, in order to minimize water stress and pumping costs, a suitable irrigation time and irrigation frequency was modeled with Hydrus-2D. Results for the period above mentioned showed values of water content ranging from 35 and 30 (m3/m3) for the first 10 and 20cm profile depth (two hours after irrigation) to the minimum 14 and 13 (m3/m3) ( two hours before irrigation). For the 40 and 60 cm profile depth, water content moves steadily across the dates: The greater the root activity the greater the water content variation. According to the results in the EnviroScan probe and the modeling in Hydrus-2D, shorter frequencies and irrigation times are suggested.

Adaptive time synchronization and frequency offset estimation for CO-OFDM

We propose a robust adaptive time synchronization and frequency offset estimation method for coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems by applying electrical dispersion pre-compensation (pre-EDC) to the pilot symbol. This technique effectively eliminates the timing error due to the fiber chromatic dispersion, thus increasing significantly the accuracy of the frequency offset estimation process and improving the overall system performance. In addition, a simple design of the pilot symbol is proposed for full-range frequency offset estimation. This pilot symbol can also be used to carry useful data to effectively reduce the overhead due to time synchronization by a factor of 2.

Rational Function Interpolation of Electromagnetic Transfer Functions of High-Speed Interconnect Systems from Discrete Time-Domain and Frequency-Domain Data

We present new methodologies to generate rational function approximations of broadband electromagnetic responses of linear and passive networks of high-speed interconnects, and to construct SPICE-compatible, equivalent circuit representations of the generated rational functions. These new methodologies are driven by the desire to improve the computational efficiency of the rational function fitting process, and to ensure enhanced accuracy of the generated rational function interpolation and its equivalent circuit representation. Toward this goal, we propose two new methodologies for rational function approximation of high-speed interconnect network responses. The first one relies on the use of both time-domain and frequency-domain data, obtained either through measurement or numerical simulation, to generate a rational function representation that extrapolates the input, early-time transient response data to late-time response while at the same time providing a means to both interpolate and extrapolate the used frequency-domain data. The aforementioned hybrid methodology can be considered as a generalization of the frequency-domain rational function fitting utilizing frequency-domain response data only, and the time-domain rational function fitting utilizing transient response data only. In this context, a guideline is proposed for estimating the order of the rational function approximation from transient data. The availability of such an estimate expedites the time-domain rational function fitting process. The second approach relies on the extraction of the delay associated with causal electromagnetic responses of interconnect systems to provide for a more stable rational function process utilizing a lower-order rational function interpolation. A distinctive feature of the proposed methodology is its utilization of scattering parameters. For both methodologies, the approach of fitting the electromagnetic network matrix one element at a time is applied. It is shown that, with regard to the computational cost of the rational function fitting process, such an element-by-element rational function fitting is more advantageous than full matrix fitting for systems with a large number of ports. Despite the disadvantage that different sets of poles are used in the rational function of different elements in the network matrix, such an approach provides for improved accuracy in the fitting of network matrices of systems characterized by both strongly coupled and weakly coupled ports. Finally, in order to provide a means for enforcing passivity in the adopted element-by-element rational function fitting approach, the methodology for passivity enforcement via quadratic programming is modified appropriately for this purpose and demonstrated in the context of element-by-element rational function fitting of the admittance matrix of an electromagnetic multiport.

Iron deficiency and frequency of HFE C282Y gene mutation in Brazilian blood donors

Limited data are available about iron deficiency (ID) in Brazilian blood donors. This study evaluated the frequencies of ID and iron-deficiency anaemia (IDA) separately and according to frequency of blood donations. The protective effect of the heterozygous genotype for HFE C282Y mutation against ID and IDA in female blood donors was also determined. Five hundred and eight blood donors were recruited at the Blood Bank of Santa Casa in Sao Paulo, Brazil. Haemoglobin and serum ferritin concentrations were measured. The genotype for HFE C282Y mutation was determined by polymerase chain reaction followed by restriction fragment length polymorphism analysis. The ID was found in 21 center dot 1% of the women and 2 center dot 6% of the men whereas the IDA was found in 6 center dot 8 and 0 center dot 3%, respectively. The ID was found in 11 center dot 9% of the women in group 1 (first-time blood donors) and the frequency increased to 38 center dot 9% in women of the group 3 (blood donors donating once or more times in the last 12 months). No ID was found in men from group 1; however the ID frequency increased to 0 center dot 9% in group 2 (who had donated blood before but not in the last 12 months) and 5 center dot 0% in group 3. In summary, the heterozygous genotype was not associated with reduction of ID or IDA frequencies in both genders, but in male blood donors it was associated with a trend to elevated ferritin levels (P = 0 center dot 060). ID is most frequent in Brazilian women but was also found in men of group 3.

Autonomic activity during human sleep as a function of time and sleep stage

While there is a developing understanding of the influence of sleep on cardiovascular autonomic activity in humans, there remain unresolved issues. In particular, the effect of time within the sleep period, independent of sleep stage, has not been investigated. Further, the influence of sleep on central sympathetic nervous system (SNS) activity is uncertain because results using the major method applicable to humans, the low frequency (LF) component of heart rate Variability (HRV), have been contradictory, and because the method itself is open to criticism. Sleep and cardiac activity were measured in 14 young healthy subjects on three nights. Data was analysed in 2-min epochs. All epochs meeting specified criteria were identified, beginning 2 h before, until 7 h after, sleep onset. Epoch values were allocated to 30-min bins and during sleep were also classified into stage 2, slow wave sleep (SWS) and rapid eye movement (REM) sleep. The measures of cardiac activity were heart irate (HR), blood pressure (BP), high frequency (HF) and LF components of HRV and pre-ejection period (PEP). During non-rapid eye movement (NREM) sleep autonomic balance shifted from sympathetic to parasympathetic dominance, although this appeared to be more because of a shift in parasympathetic nervous system (PNS) activity. Autonomic balance during REM was in general similar to wakefulness. For BP and the HF and LF components the change occurred abruptly at sleep onset and was then constant over time within each stage of sleep, indicating that any change in autonomic balance over the sleep period is a consequence of the changing distribution of sleep stages. Two variables, HR and PEP, did show time effects reflecting a circadian influence over HR and perhaps time asleep affecting PEP. While both the LF component and PEP showed changes consistent with reduced sympathetic tone during sleep, their pattern of change over time differed.

Differences in lung function, growth parameters and frequency of hospital admissions between adolescents with cystic fibrosis-related diabetes and controls

As survival of patients with CF increases,glucose intolerance and cystic fibrosisrelated diabetes (CFRD),ar e increasingly recognised common complications. CFRD may be preceded by a pre-diabetic state. Using markers identified as being associated with CFRD may improve targeted screening. Aim: To identify features consistently predicting CFRD in paediatric patients. Patients diagnosed with CFRD between January 1997–January 2002 were compared with age and sex matched controls. Clinical,micr obiological, and hospitalisation data was collected at time of CFRD diagnosis,and at six monthly intervals for 3 yr prior to diagnosis. Eight patients with CFRD were identified,mean age 13.7 yr (S.D. 3.49) at time of diagnosis. Control patients underwent OGTT to ensure normal glucose tolerance. Patients with CFRD had a lower FEV1 up to 12 months prior to diagnosis however, this was only significant at diagnosis. There was no difference in weight and height z scores between the 2 groups; however,the decrease in weight and height z scores in the CFRD group over 3 yr prior to diagnosis was significant. Mean number of days in hospital and admissions per patient significantly increased in the CFRD group,6 months prior to diagnosis. No other significant differences were observed between the 2 groups. Conclusions: This study has shown a difference in lung function,gr owth parameters and frequency of hospital admissions between patients with CFRD and controls. These differences may be utilised as tools for targeted screening in the paediatricyadolescent population. Further larger scale studies are required to improve guidelines for targeted screening in this population.

Fractional derivatives: probability interpretation and frequency response of rational approximations

The theory of fractional calculus (FC) is a useful mathematical tool in many applied sciences. Nevertheless, only in the last decades researchers were motivated for the adoption of the FC concepts. There are several reasons for this state of affairs, namely the co-existence of different definitions and interpretations, and the necessity of approximation methods for the real time calculation of fractional derivatives (FDs). In a first part, this paper introduces a probabilistic interpretation of the fractional derivative based on the Grünwald-Letnikov definition. In a second part, the calculation of fractional derivatives through Padé fraction approximations is analyzed. It is observed that the probabilistic interpretation and the frequency response of fraction approximations of FDs reveal a clear correlation between both concepts.

Updating the geographical distribution and frequency of Aedes albopictus in Brazil with remarks regarding its range in the Americas

The geographical distribution of Aedes albopictus in Brazil was updated according to the data recorded across the country over the last eight years. Countrywide house indexes (HI) for Ae. albopictus in urban and suburban areas were described for the first time using a sample of Brazilian municipalities. This mosquito is currently present in at least 59% of the Brazilian municipalities and in 24 of the 27 federal units (i.e., 26 states and the Federal District). In 34 Brazilian municipalities, the HI values for Ae. albopictus were higher than those recorded for Ae. aegypti, reaching figures as high as HI = 7.72 in the Southeast Region. Remarks regarding the current range of this mosquito species in the Americas are also presented. Nineteen American countries are currently infested and few mainland American countries have not confirmed the occurrence of Ae. albopictus. The large distribution and high frequency of Ae. albopictus in the Americas may become a critical factor in the spread of arboviruses like chikungunya in the new world.

Positive time-frequency distributions based on joint marginal constraints

This correspondence studies the formulation of members ofthe Cohen-Posch class of positive time-frequency energy distributions.Minimization of cross-entropy measures with respect to different priorsand the case of no prior or maximum entropy were considered. It isconcluded that, in general, the information provided by the classicalmarginal constraints is very limited, and thus, the final distributionheavily depends on the prior distribution. To overcome this limitation,joint time and frequency marginals are derived based on a "directioninvariance" criterion on the time-frequency plane that are directly relatedto the fractional Fourier transform.

Dialysis, time and death: comparisons of two consecutive decades among patients treated at the same Brazilian dialysis center

The survival of hemodialysis patients is likely to be influenced not only by well-known risk factors like age and comorbidity, but also by changes in dialysis technology and practices accumulated along time. We compared the survival curves, dialysis routines and some risk factors of two groups of patients admitted to a Brazilian maintenance hemodialysis program during two consecutive decades: March 1977 to December 1986 (group 1, N = 162) and January 1987 to June 1997 (group 2, N = 237). The median treatment time was 22 months (range 1-198). Survival curves were constructed using the Kaplan-Meier method and compared using the log-rank method. The Cox proportional hazard regression model was used to investigate the more important variables associated with outcome. The most important changes in dialysis routine and in patient care during the total period of observation were the progressive increase in the dose of dialysis delivered, the prohibition of potassium-free dialysate, the use of bicarbonate as a buffer and the upgrading of the dialysis equipment. There were no significant differences between the survival curves of the two groups. Survival rates at 1, 5 and 10 years were 84, 53 and 29%, respectively, for group 1 and 77, 42 and 21% for group 2. Patients in group 1 were younger (45.5 ± 15.2 vs 55.2 ± 15.9 years, P<0.001) and had a lower prevalence of diabetes (11.1 vs 27.4%, P<0.001) and of cardiovascular disease (9.3 vs 20.7%, P<0.001). According to the Cox multivariate model, only age (hazard ratio (HR) 1.04, confidence interval (CI) 1.03-1.05, P<0.001) and diabetes (HR 2.55, CI 1.82-3.58, P<0.001) were independent predictors of mortality for the whole group. Patients of group 2 had a lower prevalence of sudden death (19.1 vs 9.7%, P<0.001). After adjusting for age, diabetes and other mortality risk factors, the risk of death was 17% lower in group 2, although this difference was not statistically significant. We conclude that the negative effects of advanced age and of higher frequency of comorbidity on the survival of group 2 patients were probably offset by improvements in patient care and in the quality and dose of dialysis delivered, so that the survival curves did not undergo significant changes along time.

Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

Time and the price impact of a trade

We use Hasbrouck's (1991) vector autoregressive model for prices and trades to empirically test and assess the role played by the waiting time between consecutive transactions in the process of price formation. We find that as the time duration between transactions decreases, the price impact of trades, the speed of price adjustment to trade‐related information, and the positive autocorrelation of signed trades all increase. This suggests that times when markets are most active are times when there is an increased presence of informed traders; we interpret such markets as having reduced liquidity.

EMG amplitude and frequency parameters of muscular activity: Effect of resistance training based on electromyographic fatigue threshold

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Electrogravimetric Real-Time and in Situ Michaelis-Menten Enzimatic Kinetics: Progress Curve of Acetylcholinesterase Hydrolysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)