Simultaneous fluorescence-activated cell sorter analysis of two distinct transcriptional elements within a single cell using engineered green fluorescent proteins.

Green fluorescent protein (GFP) is widely used as a reporter gene in both prokaryotes and eukaryotes. However, the fluorescence levels of wild-type GFP (wtGFP) are not bright enough for fluorescence-activated cell sorting or flow cytometry. Several GFP variants were generated that are brighter or have altered excitation spectra when expressed in prokaryotic cells. We engineered two GFP genes with different combinations of these mutations, GFP(S65T,V163A) termed GFP-Bex1, and GFP(S202F,T203I,V163A) termed GFP-Vex1. Both show enhanced brightness and improved signal-to-noise ratios when expressed in mammalian cells and appropriately excited, compared with wtGFP. Each mutant retains only one of the two excitation peaks of the wild-type protein. GFP-Bex1 excites at 488 nm (blue) and GFP-Vex1 excites at 406 nm (violet), both of which are available laser lines. Excitation at these wavelengths allows for the independent analyses of these mutants by fluorescence-activated cell sorting, permitting simultaneous, quantitative detection of expression from two different genes within single mammalian cells.

Rapid Scan Electron Paramagnetic Resonance (EPR) and Digital EPR Development

Rapid scan electron paramagnetic resonance (EPR) was developed in the Eaton laboratory at the University of Denver. Applications of rapid scan to wider spectra, such as for immobilized nitroxides, spin-labeled proteins, irradiated tooth and fingernail samples were demonstrated in this dissertation. The scan width has been increased from 55 G to 160 G. The signal to noise (S/N) improvement for slowly tumbling spin-labeled protein samples that is provided by rapid scan EPR will be highly advantageous for biophysical studies. With substantial improvement in S/N by rapid scan, the dose estimation for irradiated tooth enamels became more reliable than the traditional continuous wave (CW) EPR. An alternate approach of rapid scan, called field-stepped direct detection EPR, was developed to reconstruct wider EPR signals. A Mn2+ containing crystal was measured by field-stepped direct detection EPR, which had a spectrum more than 6000 G wide. Since the field-stepped direct detection extends the advantages of rapid scan to much wider scan ranges, this methodology has a great potential to replace the traditional CW EPR. With recent advances in digital electronics, a digital rapid scan spectrometer was built based on an arbitrary waveform generator (AWG), which can excite spins and detect EPR signals with a fully digital system. A near-baseband detection method was used to acquire the in-phase and quadrature signals in one physical channel. The signal was analyzed digitally to generate ideally orthogonal quadrature signals. A multiharmonic algorithm was developed that employed harmonics of the modulation frequencies acquired in the spectrometer transient mode. It was applied for signals with complicated lineshapes, and can simplify the selection of modulation amplitude. A digital saturation recovery system based on an AWG was built at X-band (9.6 GHz). To demonstrate performance of the system, the spin-lattice relaxation time of a fused quartz rod was measured at room temperature with fully digital excitation and detection.

Astrophysical parameters of LS 2883 and implications for the PSR B1259-63 gamma-ray binary

Only a few binary systems with compact objects display TeV emission. The physical properties of the companion stars represent basic input for understanding the physical mechanisms behind the particle acceleration, emission, and absorption processes in these so-called gamma-ray binaries. Here we present high-resolution and high signal-to-noise optical spectra of LS 2883, the Be star forming a gamma-ray binary with the young non-accreting pulsar PSR B1259-63, showing it to rotate faster and be significantly earlier and more luminous than previously thought. Analysis of the interstellar lines suggests that the system is located at the same distance as (and thus is likely a member of) Cen OB1. Taking the distance to the association, d = 2.3 kpc, and a color excess of E(B – V) = 0.85 for LS 2883 results in MV ≈ –4.4. Because of fast rotation, LS 2883 is oblate (R eq sime 9.7 R ☉ and R pole sime 8.1 R ☉) and presents a temperature gradient (T eq≈ 27,500 K, log g eq = 3.7; T pole≈ 34,000 K, log g pole = 4.1). If the star did not rotate, it would have parameters corresponding to a late O-type star. We estimate its luminosity at log(L */L ☉) sime 4.79 and its mass at M * ≈ 30 M ☉. The mass function then implies an inclination of the binary system i orb ≈ 23°, slightly smaller than previous estimates. We discuss the implications of these new astrophysical parameters of LS 2883 for the production of high-energy and very high-energy gamma rays in the PSR B1259-63/LS 2883 gamma-ray binary system. In particular, the stellar properties are very important for prediction of the line-like bulk Comptonization component from the unshocked ultrarelativistic pulsar wind.

Determination of fat-soluble vitamins in vegetable oils through microwave-assisted high-performance liquid chromatography

In this manuscript, a study of the effect of microwave radiation on the high-performance liquid chromatography separation of tocopherols and vitamin K1 was conducted. The novelty of the application was the use of a relatively low polarity mobile phase in which the dielectric heating effect was minimized to evaluate the nonthermal effect of the microwave radiation over the separation process. Results obtained show that microwave-assisted high-performance liquid chromatography had a shorter analysis time from 31.5 to 13.3 min when the lowest microwave power was used. Moreover, narrower peaks were obtained; hence the separation was more efficient maintaining or even increasing the resolution between the peaks. This result confirms that the increase in mobile phase temperature is not the only variable for improving the separation process but also other nonthermal processes must intervene. Fluorescence detection demonstrated better signal-to-noise compared to photodiode arrayed detection mainly due to the independent effect of microwave pulses on the baseline noise, but photodiode array detection was finally chosen as it allowed a simultaneous detection of nonfluorescent compounds. Finally, a determination of the content of the vitamin E homologs was carried out in different vegetable oils. Results were coherent with those found in the literature.

Ultra-wideband multistatic SAR for the detection and location of landmines

Techniques for improving the signal to clutter ratio of an. ultra-wideband SAR designed to detect small mine-like objects in the surface of the ground were investigated. In particular, images were collected using different bistatic antenna configurations in an attempt to decorrelate the clutter with respect to the targets. The images were converted to a reference depression angle, summed, and then converted to ground coordinates. The resulting target strengths were then compared with the amplitude distribution of the ground clutter to show the improvement obtained. While some improvement was demonstrated, this was for the relatively easy scenario of targets on the surface partially obscured by grass. Detection based on thresholding the raw RF signal (the bipolar response) rather than the envelope (baseband I-2 + Q(2)) was also considered to further enhance target-to-clutter ratios.

Role of polarisation in automatic target recognition using resonance descriptions

The role of polarisation in late time complex resonance based target identification is investigated numerically for the case of an L-shaped wire. While repeated extraction of the resonances for varying polarisation allows for better signal-to-noise immunity, it is also found that there are preferred polarisations for each complex resonance. The first few of these polarisations are extracted for the sample target.

Effect of mutual coupling on the interference rejection capabilities of linear and circular arrays in CDMA systems

This paper is concerned with assessing the interference rejection capabilities of linear and circular array of dipoles that can be part of a base station of a code-division multiple-access cellular communication system. The performance criteria for signal-to-interference ratio (SIR) improvement employed in this paper is the spatial interference suppression coefficient. We first derive an expression for this figure of merit and then analyze and compare the SIR performance of the two types of arrays. For a linear array, we quantitatively assess the degradation in SIR performance, as we move from array broadside to array end-fire direction. In addition, the effect of mutual coupling is taken into account.

Tracking the states of a nonlinear system in the weight-space of a feed-forward neural network

Nonlinear, non-stationary signals are commonly found in a variety of disciplines such as biology, medicine, geology and financial modeling. The complexity (e.g. nonlinearity and non-stationarity) of such signals and their low signal to noise ratios often make it a challenging task to use them in critical applications. In this paper we propose a new neural network based technique to address those problems. We show that a feed forward, multi-layered neural network can conveniently capture the states of a nonlinear system in its connection weight-space, after a process of supervised training. The performance of the proposed method is investigated via computer simulations.

Simulation of optical fibre communication systems influenced by stimulated brillouin scattering

Boyd's SBS model which includes distributed thermal acoustic noise (DTAN) has been enhanced to enable the Stokes-spontaneous density depletion noise (SSDDN) component of the transmitted optical field to be simulated, probably for the first time, as well as the full transmitted field. SSDDN would not be generated from previous SBS models in which a Stokes seed replaces DTAN. SSDDN becomes the dominant form of transmitted SBS noise as model fibre length (MFL) is increased but its optical power spectrum remains independent of MFL. Simulations of the full transmitted field and SSDDN for different MFLs allow prediction of the optical power spectrum, or system performance parameters which depend on this, for typical communication link lengths which are too long for direct simulation. The SBS model has also been innovatively improved by allowing the Brillouin Shift Frequency (BS) to vary over the model fibre length, for the nonuniform fibre model (NFM) mode, or to remain constant, for the uniform fibre model (UFM) mode. The assumption of a Gaussian probability density function (pdf) for the BSF in the NFM has been confirmed by means of an analysis of reported Brillouin amplified power spectral measurements for the simple case of a nominally step-index single-mode pure silica core fibre. The BSF pdf could be modified to match the Brillouin gain spectra of other fibre types if required. For both models, simulated backscattered and output powers as functions of input power agree well with those from a reported experiment for fitting Brillouin gain coefficients close to theoretical. The NFM and UFM Brillouin gain spectra are then very similar from half to full maximum but diverge at lower values. Consequently, NFM and UFM transmitted SBS noise powers inferred for long MFLs differ by 1-2 dB over the input power range of 0.15 dBm. This difference could be significant for AM-VSB CATV links at some channel frequencies. The modelled characteristic of Carrier-to-Noise Ratio (CNR) as a function of input power for a single intensity modulated subcarrier is in good agreement with the characteristic reported for an experiment when either the UFM or NFM is used. The difference between the two modelled characteristics would have been more noticeable for a higher fibre length or a lower subcarrier frequency.

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

Energy efficient transmission protocol for distributed source coding in sensor networks

Distributed source coding (DSC) has recently been considered as an efficient approach to data compression in wireless sensor networks (WSN). Using this coding method multiple sensor nodes compress their correlated observations without inter-node communications. Therefore energy and bandwidth can be efficiently saved. In this paper, we investigate a randombinning based DSC scheme for remote source estimation in WSN and its performance of estimated signal to distortion ratio (SDR). With the introduction of a detailed power consumption model for wireless sensor communications, we quantitatively analyze the overall network energy consumption of the DSC scheme. We further propose a novel energy-aware transmission protocol for the DSC scheme, which flexibly optimizes the DSC performance in terms of either SDR or energy consumption, by adapting the source coding and transmission parameters to the network conditions. Simulations validate the energy efficiency of the proposed adaptive transmission protocol. © 2007 IEEE.

Wireless power and data transfer via a common inductive link using frequency division multiplexing

For wireless power transfer (WPT) systems, communication between the primary side and the pickup side is a challenge because of the large air gap and magnetic interferences. A novel method, which integrates bidirectional data communication into a high-power WPT system, is proposed in this paper. The power and data transfer share the same inductive link between coreless coils. Power/data frequency division multiplexing technique is applied, and the power and data are transmitted by employing different frequency carriers and controlled independently. The circuit model of the multiband system is provided to analyze the transmission gain of the communication channel, as well as the power delivery performance. The crosstalk interference between two carriers is discussed. In addition, the signal-to-noise ratios of the channels are also estimated, which gives a guideline for the design of mod/demod circuits. Finally, a 500-W WPT prototype has been built to demonstrate the effectiveness of the proposed WPT system.

Investigation of particle identification methods for the analysis of the photoproduction of neutral kaons on a liquid deuterium target

The Photoproduction of neutral kaons off a deuteron target has been investigated at the Tohoku University Laboratory of Nuclear Science. The PID methods investigated incorporated a combination of momentum, velocity (β=v/c), and energy deposition per unit length (dE/dx) measurements. The analysis demonstrates that energy deposition and time of flight are exceedingly useful. A higher signal to background ratio was achieved for hard cuts in combination. A probabilistic likelihood estimation approach (LE) as a method for PID was also explored. The probability of a particle being correctly identified by this LE method and the preliminary results denote the need for highly precise limitations on the distributions from which the parameters would be extracted. It was confirmed that these PID are applicable approaches to properly identify pions for the analysis of this experiment. However, the background evident in the mass spectra points to the need for a higher level of proton identification.

Water temperature reconstructions based on paired Uk'37 and Tex86 records, and paired surface and subsurface Mg/Ca records

This dataset contains the collection of available published paired Uk'37 and Tex86 records spanning multi-millennial to multi-million year time scales, as well as a collection of Mg/Ca-derived temperatures measured in parallel on surface and subsurface dwelling foraminifera, both used in the analyses of Ho and Laepple, Nature Geoscience 2016. As the signal-to-noise ratios of proxy-derived Holocene temperatures are relatively low, we selected records that contain at least the last deglaciation (oldest sample >18kyr BP).

Seleção de características para identificação de diferentes proporções de tipos de fibras musculares por meio da eletromiografia de superfície

Skeletal muscle consists of muscle fiber types that have different physiological and biochemical characteristics. Basically, the muscle fiber can be classified into type I and type II, presenting, among other features, contraction speed and sensitivity to fatigue different for each type of muscle fiber. These fibers coexist in the skeletal muscles and their relative proportions are modulated according to the muscle functionality and the stimulus that is submitted. To identify the different proportions of fiber types in the muscle composition, many studies use biopsy as standard procedure. As the surface electromyography (EMGs) allows to extract information about the recruitment of different motor units, this study is based on the assumption that it is possible to use the EMG to identify different proportions of fiber types in a muscle. The goal of this study was to identify the characteristics of the EMG signals which are able to distinguish, more precisely, different proportions of fiber types. Also was investigated the combination of characteristics using appropriate mathematical models. To achieve the proposed objective, simulated signals were developed with different proportions of motor units recruited and with different signal-to-noise ratios. Thirteen characteristics in function of time and the frequency were extracted from emulated signals. The results for each extracted feature of the signals were submitted to the clustering algorithm k-means to separate the different proportions of motor units recruited on the emulated signals. Mathematical techniques (confusion matrix and analysis of capability) were implemented to select the characteristics able to identify different proportions of muscle fiber types. As a result, the average frequency and median frequency were selected as able to distinguish, with more precision, the proportions of different muscle fiber types. Posteriorly, the features considered most able were analyzed in an associated way through principal component analysis. Were found two principal components of the signals emulated without noise (CP1 and CP2) and two principal components of the noisy signals (CP1 and CP2 ). The first principal components (CP1 and CP1 ) were identified as being able to distinguish different proportions of muscle fiber types. The selected characteristics (median frequency, mean frequency, CP1 and CP1 ) were used to analyze real EMGs signals, comparing sedentary people with physically active people who practice strength training (weight training). The results obtained with the different groups of volunteers show that the physically active people obtained higher values of mean frequency, median frequency and principal components compared with the sedentary people. Moreover, these values decreased with increasing power level for both groups, however, the decline was more accented for the group of physically active people. Based on these results, it is assumed that the volunteers of the physically active group have higher proportions of type II fibers than sedentary people. Finally, based on these results, we can conclude that the selected characteristics were able to distinguish different proportions of muscle fiber types, both for the emulated signals as to the real signals. These characteristics can be used in several studies, for example, to evaluate the progress of people with myopathy and neuromyopathy due to the physiotherapy, and also to analyze the development of athletes to improve their muscle capacity according to their sport. In both cases, the extraction of these characteristics from the surface electromyography signals provides a feedback to the physiotherapist and the coach physical, who can analyze the increase in the proportion of a given type of fiber, as desired in each case.