The joint influence of gender and amount of smoking on weight gain one year after smoking cessation.

Weight gain is often associated with smoking cessation and may discourage smokers from quitting. This study estimated the weight gained one year after smoking cessation and examined the risk factors associated with weight gain in order to identify socio-demographic groups at higher risk of increased weight after quitting. We analyzed data from 750 adults in two randomized controlled studies that included smokers motivated to quit and found a gradient in weight gain according to the actual duration of abstinence during follow-up. Subjects who were abstinent for at least 40 weeks gained 4.6 kg (SD = 3.8) on average, compared to 1.2 kg (SD = 2.6) for those who were abstinent less than 20 weeks during the 1-year follow-up. Considering the duration of abstinence as an exposure variable, we found an age effect and a significant interaction between sex and the amount of smoking before quitting: younger subjects gained more weight than older subjects; among light smokers, men gained more weight on average than women one year after quitting, while the opposite was observed among heavy smokers. Young women smoking heavily at baseline had the highest risk of weight gain after quitting.

Compact amplifier integrated microstrip antenna

compact microstrip antenna integrated with an amplifier having an area reduction of 70%, compared to the standard circular microstrip patch antenna, is presented. The antenna also provides an enhanced gain of 10-dB more than its passive counter part. The measured 2:1 VSWR band width is -4% at 790 MHz, which is 2.5 times larger than that of the passive microstrip antenna

Fabrication and characterization of dye-doped polymer optical fiber as a light amplifier

The fabrication and characterization of a Rhodamine 6G-doped polymer optical fiber amplifier have been carried out. Two different schemes were employed to characterize the optical fiber: the stripe illumination technique to study the fiber as a gain medium and another technique to study its performance as an amplifier. We observed a spectral narrowing from 42 to 7 nm when the pump energy was increased to 6 mJ in the stripe illumination geometry. A gain of 18 dB was obtained in the amplifier configuration. The effects of pump power and dye concentration on the performance of the fiber as an amplifier were also studied.

Fabrication and characterization of dye mixture doped polymer optical fiber as a broad wavelength optical amplifier

Rhodamine 6G and Rhodamine B dye mixture doped polymer optical fiber amplifier (POFA), which can operate in a broad wavelength region (60 nm), has been successfully fabricated and tested. Tunable operation of the amplifier over a broad wavelength region is achieved by mixing different ratios of the dyes. The dye doped POFA is pumped axially using 532 nm, 10 ns laser pulses from a frequency doubled Q-switched Nd: YAG laser and the signals are taken from an optical parametric oscillator. A maximum gain of 22.3 dB at 617 nm wavelength has been obtained for a 7 cm long dye mixture doped POFA. The effects of pump energy and length of the fiber on the performance of the fiber amplifier are also studied. There exists an optimum length for which the amplifier gain is at a maximum value.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Optical Characterization of Organic Gain Materials for UV-emitting Hybrid Complex Coupled VCSELs

In this thesis, optical gain measurement setup based on variable stripe length method is designed, implemented and improved. The setup is characterized using inorganic and organic samples. The optical gain of spiro-quaterphenyl is calculated and compared with measurements from the setup. Films with various thicknesses of spiro-quaterphenyl, methoxy-spiro-quaterphenyl and phenoxy-spiro-quaterphenyl are deposited by a vacuum vapor deposition technique forming asymmetric slab waveguides. The optical properties, laser emission threshold, optical gain and loss coefficient for these films are measured. Additionally, the photodegradation during pumping process is investigated.

On the power amplifier nonlinearity in MIMO transmit beamforming systems

In this paper, single-carrier multiple-input multiple-output (MIMO) transmit beamforming (TB) systems in the presence of high-power amplifier (HPA) nonlinearity are investigated. Specifically, due to the suboptimality of the conventional maximal ratio transmission/maximal ratio combining (MRT/MRC) under HPA nonlinearity, we propose the optimal TB scheme with the optimal beamforming weight vector and combining vector, for MIMO systems with nonlinear HPAs. Moreover, an alternative suboptimal but much simpler TB scheme, namely, quantized equal gain transmission (QEGT), is proposed. The latter profits from the property that the elements of the beamforming weight vector have the same constant modulus. The performance of the proposed optimal TB scheme and QEGT/MRC technique in the presence of the HPA nonlinearity is evaluated in terms of the average symbol error probability and mutual information with the Gaussian input, considering the transmission over uncorrelated quasi-static frequency-flat Rayleigh fading channels. Numerical results are provided and show the effects on the performance of several system parameters, namely, the HPA parameters, numbers of antennas, quadrature amplitude modulation modulation order, number of pilot symbols, and cardinality of the beamforming weight vector codebook for QEGT.

Analysis and compensation of power amplifier nonlinearity in MIMO transmit diversity systems

The nonlinearity of high-power amplifiers (HPAs) has a crucial effect on the performance of multiple-input-multiple-output (MIMO) systems. In this paper, we investigate the performance of MIMO orthogonal space-time block coding (OSTBC) systems in the presence of nonlinear HPAs. Specifically, we propose a constellation-based compensation method for HPA nonlinearity in the case with knowledge of the HPA parameters at the transmitter and receiver, where the constellation and decision regions of the distorted transmitted signal are derived in advance. Furthermore, in the scenario without knowledge of the HPA parameters, a sequential Monte Carlo (SMC)-based compensation method for the HPA nonlinearity is proposed, which first estimates the channel-gain matrix by means of the SMC method and then uses the SMC-based algorithm to detect the desired signal. The performance of the MIMO-OSTBC system under study is evaluated in terms of average symbol error probability (SEP), total degradation (TD) and system capacity, in uncorrelated Nakagami-m fading channels. Numerical and simulation results are provided and show the effects on performance of several system parameters, such as the parameters of the HPA model, output back-off (OBO) of nonlinear HPA, numbers of transmit and receive antennas, modulation order of quadrature amplitude modulation (QAM), and number of SMC samples. In particular, it is shown that the constellation-based compensation method can efficiently mitigate the effect of HPA nonlinearity with low complexity and that the SMC-based detection scheme is efficient to compensate for HPA nonlinearity in the case without knowledge of the HPA parameters.

Suckling and allosuckling in river buffalo calves and its relation with weight gain

The aim of the present study was to investigate if river buffalo calves (Bubalus bubalis) have equal access to all cows and if milk is thus equally available to all of them. We recorded suckling/allosuckling behaviour and weight gain (WG) of 29 calves (14 males and 15 females), with special consideration to their sex, birth order (BO) and age. Cows' nursing behaviour and milli production (MP) were also considered. While males tended to be born earlier than females during this study, this was not the trend in the overall herd records. The cows' MP was not effected by the calves' sex. However, bull-calves presented greater mean WG, and mean times spent in individual filial (IF) and in communal nonfilial (CNF) suckling than heifer-calves, which showed greater communal filial (CF) suckling than the former during the first 4 months of life. The WG was associated with IF for bull-calves (r = 0.680 and 0.765, respectively, for the periods from birth to 4th and 8th months of age), and to CNF for heifer-calves (r = 0.628, for the period from birth to 8th month). Results from multiple regression analysis showed independent effects of each suckling category on the calf WG, and such effects were variable according to the calf's sex. BO was negatively correlated to calves' WG (bull-calves: r(s) = - 0.873 and - 0.799, from birth to 4th and gth months, respectively; heifer-calves: r(s) = - 0.531 from birth to 4th month). Specifically for bull-calves, there was a positive correlation between BO and MP (r(s) = 0.528 and 0.633, from birth to 4th and 8th months of age, respectively). The correlation between BO and IF was negative in both sexes, indicating that calves that were born early had more opportunities to suckle individually from their mothers. For heifer-calves, BO was positively correlated with CF (two periods), and negatively with CNF (from birth to 8th month of age), suggesting that heifer-calves were most often accompanied by other calves during suckling when they were born later. The data taken together indicate that sex and/or BO influenced decisively social interactions during suckling, promoting differential development among the calves. In animal husbandry, if a homogenous WG is desired, these factors have to be taken into consideration. (C) 2000 Elsevier B.V. B.V. All rights reserved.

New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks

The present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).

Effects of nitric oxide synthesis inhibitor or fluoxetine treatment on depression-like state and cardiovascular changes induced by chronic variable stress in rats

Comorbidity between mood disorders and cardiovascular disease has been described extensively. However, available antidepressants can have cardiovascular side effects. Treatment with selective inhibitors of neuronal nitric oxide synthase (nNOS) induces antidepressant effects, but whether the antidepressant-like effects of these drugs are followed by cardiovascular changes has not been previously investigated. Here, we tested in male rats exposed to chronic variable stress (CVS) the hypothesis that nNOS blockers are advantageous compared with conventional antidepressants in terms of cardiovascular side effects. We compared the effects of chronic treatment with the preferential nNOS inhibitor 7-nitroindazole (7-NI) with those evoked by the conventional antidepressant fluoxetine on alterations that are considered as markers of depression (immobility in the forced swimming test, FST, decreased body weight gain and increased plasma corticosterone concentration) and cardiovascular changes caused by CVS. Rats were exposed to a 14-day CVS protocol, while being concurrently treated daily with either 7-NI (30 mg/kg) or fluoxetine (10 mg/kg). Fluoxetine and 7-NI prevented the increase in immobility in the FST induced by CVS and reduced plasma corticosterone concentration in stressed rats. Both these treatments also prevented the CVS-evoked reduction of the depressor response to vasodilator agents and baroreflex changes. Fluoxetine and 7-NI-induced cardiovascular changes independent of stress exposure, including cardiac autonomic imbalance, increased intrinsic heart rate and vascular sympathetic modulation, a reduction of the pressor response to vasoconstrictor agents, and impairment of baroreflex activity. Altogether, these findings provide evidence that fluoxetine and 7-NI have similar effects on the depression-like state induced by CVS and on cardiovascular function.

Optimizing Amplifier Placements in a Multiwavelength Optical LAN/MAN: The Unequally Powered Wavelengths Case

Optical networks based on passive-star couplers and employing WDM have been proposed for deployment in local and metropolitan areas. These networks suffer from splitting, coupling, and attenuation losses. Since there is an upper bound on transmitter power and a lower bound on receiver sensitivity, optical amplifiers are usually required to compensate for the power losses mentioned above. Due to the high cost of amplifiers, it is desirable to minimize their total number in the network. However, an optical amplifier has constraints on the maximum gain and the maximum output power it can supply; thus, optical amplifier placement becomes a challenging problem. In fact, the general problem of minimizing the total amplifier count is a mixed-integer nonlinear problem. Previous studies have attacked the amplifier-placement problem by adding the “artificial” constraint that all wavelengths, which are present at a particular point in a fiber, be at the same power level. This constraint simplifies the problem into a solvable mixed integer linear program. Unfortunately, this artificial constraint can miss feasible solutions that have a lower amplifier count but do not have the equally powered wavelengths constraint. In this paper, we present a method to solve the minimum amplifier- placement problem, while avoiding the equally powered wavelength constraint. We demonstrate that, by allowing signals to operate at different power levels, our method can reduce the number of amplifiers required.

Nonlinear Characterization and Modelling of GaN HEMTs for Microwave Power Amplifier Applications

Semiconductors technologies are rapidly evolving driven by the need for higher performance demanded by applications. Thanks to the numerous advantages that it offers, gallium nitride (GaN) is quickly becoming the technology of reference in the field of power amplification at high frequency. The RF power density of AlGaN/GaN HEMTs (High Electron Mobility Transistor) is an order of magnitude higher than the one of gallium arsenide (GaAs) transistors. The first demonstration of GaN devices dates back only to 1993. Although over the past few years some commercial products have started to be available, the development of a new technology is a long process. The technology of AlGaN/GaN HEMT is not yet fully mature, some issues related to dispersive phenomena and also to reliability are still present. Dispersive phenomena, also referred as long-term memory effects, have a detrimental impact on RF performances and are due both to the presence of traps in the device structure and to self-heating effects. A better understanding of these problems is needed to further improve the obtainable performances. Moreover, new models of devices that take into consideration these effects are necessary for accurate circuit designs. New characterization techniques are thus needed both to gain insight into these problems and improve the technology and to develop more accurate device models. This thesis presents the research conducted on the development of new charac- terization and modelling methodologies for GaN-based devices and on the use of this technology for high frequency power amplifier applications.

Ruminant rhombencephalitis-associated Listeria monocytogenes alleles linked to a multilocus variable-number tandem-repeat analysis complex

Listeria monocytogenes is among the most important food-borne pathogens and is well adapted to persist in the environment. To gain insight into the genetic relatedness and potential virulence of L. monocytogenes strains causing central nervous system (CNS) infections, we used multilocus variable-number tandem-repeat analysis (MLVA) to subtype 183 L. monocytogenes isolates, most from ruminant rhombencephalitis and some from human patients, food, and the environment. Allelic-profile-based comparisons grouped L. monocytogenes strains mainly into three clonal complexes and linked single-locus variants (SLVs). Clonal complex A essentially consisted of isolates from human and ruminant brain samples. All but one rhombencephalitis isolate from cattle were located in clonal complex A. In contrast, food and environmental isolates mainly clustered into clonal complex C, and none was classified as clonal complex A. Isolates of the two main clonal complexes (A and C) obtained by MLVA were analyzed by PCR for the presence of 11 virulence-associated genes (prfA, actA, inlA, inlB, inlC, inlD, inlE, inlF, inlG, inlJ, and inlC2H). Virulence gene analysis revealed significant differences in the actA, inlF, inlG, and inlJ allelic profiles between clinical isolates (complex A) and nonclinical isolates (complex C). The association of particular alleles of actA, inlF, and newly described alleles of inlJ with isolates from CNS infections (particularly rhombencephalitis) suggests that these virulence genes participate in neurovirulence of L. monocytogenes. The overall absence of inlG in clinical complex A and its presence in complex C isolates suggests that the InlG protein is more relevant for the survival of L. monocytogenes in the environment.

The joint influence of gender and amount of smoking on weight gain one year after smoking cessation

Weight gain is often associated with smoking cessation and may discourage smokers from quitting. This study estimated the weight gained one year after smoking cessation and examined the risk factors associated with weight gain in order to identify socio-demographic groups at higher risk of increased weight after quitting. We analyzed data from 750 adults in two randomized controlled studies that included smokers motivated to quit and found a gradient in weight gain according to the actual duration of abstinence during follow-up. Subjects who were abstinent for at least 40 weeks gained 4.6 kg (SD = 3.8) on average, compared to 1.2 kg (SD = 2.6) for those who were abstinent less than 20 weeks during the 1-year follow-up. Considering the duration of abstinence as an exposure variable, we found an age effect and a significant interaction between sex and the amount of smoking before quitting: younger subjects gained more weight than older subjects; among light smokers, men gained more weight on average than women one year after quitting, while the opposite was observed among heavy smokers. Young women smoking heavily at baseline had the highest risk of weight gain after quitting.