Adaptive evolution of a candidate gene for aging in Drosophila

Examination of the phenotypic effects of specific mutations has been extensively used to identify candidate genes affecting traits of interest. However, such analyses do not reveal anything about the evolutionary forces acting at these loci, or whether standing allelic variation contributes to phenotypic variance in natural populations. The Drosophila gene methuselah (mth) has been proposed as having major effects on organismal stress response and longevity phenotype. Here, we examine patterns of polymorphism and divergence at mth in population level samples of Drosophila melanogaster, D. simulans, and D. yakuba. Mth has experienced an unusually high level of adaptive amino acid divergence concentrated in the intra- and extracellular loop domains of the receptor protein, suggesting the historical action of positive selection on those regions of the molecule that modulate signal transduction. Further analysis of single nucleotide polymorphisms (SNPs) in D. melanogaster provided evidence for contemporary and spatially variable selection at the mth locus. In ten surveyed populations, the most common mth haplotype exhibited a 40% cline in frequency that coincided with population level differences in multiple life-history traits including lifespan. This clinal pattern was not associated with any particular SNP in the coding region, indicating that selection is operating at a closely linked site that may be involved in gene expression. Together, these consistently nonneutral patterns of inter- and intraspecific variation suggest adaptive evolution of a signal transduction pathway that may modulate lifespan in nature.

Mechanical bases of frequency tuning and neural excitation at the base of the cochlea: Comparison of basilar-membrane vibrations and auditory-nerve-fiber responses in chinchilla

We review the mechanical origin of auditory-nerve excitation, focusing on comparisons of the magnitudes and phases of basilar-membrane (BM) vibrations and auditory-nerve fiber responses to tones at a basal site of the chinchilla cochlea with characteristic frequency ≈ 9 kHz located 3.5 mm from the oval window. At this location, characteristic frequency thresholds of fibers with high spontaneous activity correspond to magnitudes of BM displacement or velocity in the order of 1 nm or 50 μm/s. Over a wide range of stimulus frequencies, neural thresholds are not determined solely by BM displacement but rather by a function of both displacement and velocity. Near-threshold, auditory-nerve responses to low-frequency tones are synchronous with peak BM velocity toward scala tympani but at 80–90 dB sound pressure level (in decibels relative to 20 microPascals) and at 100–110 dB sound pressure level responses undergo two large phase shifts approaching 180°. These drastic phase changes have no counterparts in BM vibrations. Thus, although at threshold levels the encoding of BM vibrations into spike trains appears to involve only relatively minor signal transformations, the polarity of auditory-nerve responses does not conform with traditional views of how BM vibrations are transmitted to the inner hair cells. The response polarity at threshold levels, as well as the intensity-dependent phase changes, apparently reflect micromechanical interactions between the organ of Corti, the tectorial membrane and the subtectorial fluid, and/or electrical and synaptic processes at the inner hair cells.

Adaptive mutations in Escherichia coli as a model for the multiple mutational origins of tumors.

The cells in most tumors are found to carry multiple mutations; however, based upon mutation rates determined by fluctuation tests, the frequency of such multiple mutations should be so low that tumors are never detected within human populations. Fluctuation tests, which determine the cell-division-dependent mutation rate per cell generation in growing cells, may not be appropriate for estimating mutation rates in nondividing or very slowly dividing cells. Recent studies of time-dependent, "adaptive" mutations in nondividing populations of microorganisms suggest that similar measurements may be more appropriate to understanding the mutation origins of tumors. Here I use the ebgR and ebgA genes of Escherichia coli to measure adaptive mutation rates where multiple mutations are required for rapid growth. Mutations in either ebgA or ebgR allow very slow growth on lactulose (4-O-beta-D-galactosyl-D-fructose), with doubling times of 3.2 and 17.3 days, respectively. However, when both mutations are present, cells can grow rapidly with doubling times of 2.7 hr. I show that during prolonged (28-day) selection for growth on lactulose, the number of lactulose-utilizing mutants that accumulate is 40,000 times greater than can be accounted for on the basis of mutation rates measured by fluctuation tests, but is entirely consistent with the time-dependent adaptive mutation rates measured under the same conditions of prolonged selection.

Rectification and signal averaging of weak electric fields by biological cells.

Oscillating electric fields can be rectified by proteins in cell membranes to give rise to a dc transport of a substance across the membrane or a net conversion of a substrate to a product. This provides a basis for signal averaging and may be important for understanding the effects of weak extremely low frequency (ELF) electric fields on cellular systems. We consider the limits imposed by thermal and "excess" biological noise on the magnitude and exposure duration of such electric field-induced membrane activity. Under certain circumstances, the excess noise leads to an increase in the signal-to-noise ratio in a manner similar to processes labeled "stochastic resonance." Numerical results indicate that it is difficult to reconcile biological effects with low field strengths.

Adaptive phase measurements for narrowband squeezed beams

We have previously [Phys. Rev. A 65, 043803 (2002)] analyzed adaptive measurements for estimating the continuously varying phase of a coherent beam, and a broadband squeezed beam. A real squeezed beam must have finite photon flux N and hence can be significantly squeezed only over a limited frequency range. In this paper we analyze adaptive phase measurements of this type for a realistic model of a squeezed beam. We show that, provided it is possible to suitably choose the parameters of the beam, a mean-square phase uncertainty scaling as (N/kappa)(-5/8) is possible, where kappa is the linewidth of the beam resulting from the fluctuating phase. This is an improvement over the (N/kappa)(-1/2) scaling found previously for coherent beams. In the experimentally realistic case where there is a limit on the maximum squeezing possible, the variance will be reduced below that for coherent beams, though the scaling is unchanged.

Performance comparisons between greedy and lagrange algorithms in adaptive MIMO MC-CDMA systems

This paper describes two algorithms for adaptive power and bit allocations in a multiple input multiple output multiple-carrier code division multiple access (MIMO MC-CDMA) system. The first is the greedy algorithm, which has already been presented in the literature. The other one, which is proposed by the authors, is based on the use of the Lagrange multiplier method. The performances of the two algorithms are compared via Monte Carlo simulations. At present stage, the simulations are restricted to a single user MIMO MC-CDMA system, which is equivalent to a MIMO OFDM system. It is assumed that the system operates in a frequency selective fading environment. The transmitter has a partial knowledge of the channel whose properties are measured at the receiver. The use of the two algorithms results in similar system performances. The advantage of the Lagrange algorithm is that is much faster than the greedy algorithm. ©2005 IEEE

On waveform analysis, the adaptive task technique, and the effect of vibration on manual control skill

A re-examination of fundamental concepts and a formal structuring of the waveform analysis problem is presented in Part I. eg. the nature of frequency is examined and a novel alternative to the classical methods of detection proposed and implemented which has the advantage of speed and independence from amplitude. Waveform analysis provides the link between Parts I and II. Part II is devoted to Human Factors and the Adaptive Task Technique. The Historical, Technical and Intellectual development of the technique is traced in a review which examines the evidence of its advantages relative to non-adaptive fixed task methods of training, skill assessment and man-machine optimisation. A second review examines research evidence on the effect of vibration on manual control ability. Findings are presented in terms of percentage increment or decrement in performance relative to performance without vibration in the range 0-0.6Rms'g'. Primary task performance was found to vary by as much as 90% between tasks at the same Rms'g'. Differences in task difficulty accounted for this difference. Within tasks vibration-added-difficulty accounted for the effects of vibration intensity. Secondary tasks were found to be largely insensitive to vibration except secondaries which involved fine manual adjustment of minor controls. Three experiments are reported next in which an adaptive technique was used to measure the % task difficulty added by vertical random and sinusoidal vibration to a 'Critical Compensatory Tracking task. At vibration intensities between 0 - 0.09 Rms 'g' it was found that random vibration added (24.5 x Rms'g')/7.4 x 100% to the difficulty of the control task. An equivalence relationship between Random and Sinusoidal vibration effects was established based upon added task difficulty. Waveform Analyses which were applied to the experimental data served to validate Phase Plane analysis and uncovered the development of a control and possibly a vibration isolation strategy. The submission ends with an appraisal of subjects mentioned in the thesis title.

The development of calibration and adaptive filtering procedures for neuromagnetic studies of human visual function

This thesis first considers the calibration and signal processing requirements of a neuromagnetometer for the measurement of human visual function. Gradiometer calibration using straight wire grids is examined and optimal grid configurations determined, given realistic constructional tolerances. Simulations show that for gradiometer balance of 1:104 and wire spacing error of 0.25mm the achievable calibration accuracy of gain is 0.3%, of position is 0.3mm and of orientation is 0.6°. Practical results with a 19-channel 2nd-order gradiometer based system exceed this performance. The real-time application of adaptive reference noise cancellation filtering to running-average evoked response data is examined. In the steady state, the filter can be assumed to be driven by a non-stationary step input arising at epoch boundaries. Based on empirical measures of this driving step an optimal progression for the filter time constant is proposed which improves upon fixed time constant filter performance. The incorporation of the time-derivatives of the reference channels was found to improve the performance of the adaptive filtering algorithm by 15-20% for unaveraged data, falling to 5% with averaging. The thesis concludes with a neuromagnetic investigation of evoked cortical responses to chromatic and luminance grating stimuli. The global magnetic field power of evoked responses to the onset of sinusoidal gratings was shown to have distinct chromatic and luminance sensitive components. Analysis of the results, using a single equivalent current dipole model, shows that these components arise from activity within two distinct cortical locations. Co-registration of the resulting current source localisations with MRI shows a chromatically responsive area lying along the midline within the calcarine fissure, possibly extending onto the lingual and cuneal gyri. It is postulated that this area is the human homologue of the primate cortical area V4.

Minimizing nasty surprises with better informed decision-making in self-adaptive systems

Designers of self-adaptive systems often formulate adaptive design decisions, making unrealistic or myopic assumptions about the system's requirements and environment. The decisions taken during this formulation are crucial for satisfying requirements. In environments which are characterized by uncertainty and dynamism, deviation from these assumptions is the norm and may trigger 'surprises'. Our method allows designers to make explicit links between the possible emergence of surprises, risks and design trade-offs. The method can be used to explore the design decisions for self-adaptive systems and choose among decisions that better fulfil (or rather partially fulfil) non-functional requirements and address their trade-offs. The analysis can also provide designers with valuable input for refining the adaptation decisions to balance, for example, resilience (i.e. Satisfiability of non-functional requirements and their trade-offs) and stability (i.e. Minimizing the frequency of adaptation). The objective is to provide designers of self adaptive systems with a basis for multi-dimensional what-if analysis to revise and improve the understanding of the environment and its effect on non-functional requirements and thereafter decision-making. We have applied the method to a wireless sensor network for flood prediction. The application shows that the method gives rise to questions that were not explicitly asked before at design-time and assists designers in the process of risk-aware, what-if and trade-off analysis.

Fiber-type transitions and satellite cell activation in low-frequency-stimulated muscles of young and aging rats

We examined satellite cell content and the activity of satellite cell progeny in tibialis anterior muscles of young (15 weeks) and aging (101 weeks) Brown Norway (BN) rats, after they were exposed for 50 days to a standardized and highly reproducible regime of chronic low-frequency electrical stimulation. Chronic low-frequency electrical stimulation was successful in inducing fast-to-slow fiber-type transformation, characterized by a 2.3-fold increase in the proportion of IIA fibers and fourfold and sevenfold decreases in the proportion of IID/X and IIB fibers in both young and aging BN rats. These changes were accompanied by a twofold increase in the satellite cell content in both the young and aging groups; satellite cell content reached a level that was significantly higher in the young group (p < .04). The total muscle precursor cell content (i.e., satellite cells plus progeny), however, did not differ between groups, because there was a greater number of satellite cell progeny passing through the proliferative and differentiative compartments of the aging group. The resulting 1.5-fold increase in myonuclear content was similar in the young and aging groups. We conclude that satellite cells and satellite cell progeny of aging BN rats possess an unaltered capacity to contribute to the adaptive response.

Application of ensemble averaging to the analysis of electromyography recordings under whole body vibratory stimulation

The aim of this study is to evaluate the application of ensemble averaging to the analysis of electromyography recordings under whole body vibratory stimulation. Recordings from Rectus Femoris, collected during vibratory stimulation at different frequencies, are used. Each signal is subdivided in intervals, which time duration is related to the vibration frequency. Finally the average of the segmented intervals is performed. By using this method for the majority of the recordings the periodic components emerge. The autocorrelation of few seconds of signals confirms the presence of a pseudosinusoidal components strictly related to the soft tissues oscillations caused by the mechanical waves. © 2014 IEEE.

Light self-focusing in the atmosphere:thin window model

Ultra-high power (exceeding the self-focusing threshold by more than three orders of magnitude) light beams from ground-based laser systems may find applications in space-debris cleaning. The propagation of such powerful laser beams through the atmosphere reveals many novel interesting features compared to traditional light self-focusing. It is demonstrated here that for the relevant laser parameters, when the thickness of the atmosphere is much shorter than the focusing length (that is, of the orbit scale), the beam transit through the atmosphere in lowest order produces phase distortion only. This means that by using adaptive optics it may be possible to eliminate the impact of self-focusing in the atmosphere on the laser beam. The area of applicability of the proposed "thin window" model is broader than the specific physical problem considered here. For instance, it might find applications in femtosecond laser material processing.

Competition and fixation of cohorts of adaptive mutations under Fisher geometrical model

One of the simplest models of adaptation to a new environment is Fisher's Geometric Model (FGM), in which populations move on a multidimensional landscape defined by the traits under selection. The predictions of this model have been found to be consistent with current observations of patterns of fitness increase in experimentally evolved populations. Recent studies investigated the dynamics of allele frequency change along adaptation of microbes to simple laboratory conditions and unveiled a dramatic pattern of competition between cohorts of mutations, i.e., multiple mutations simultaneously segregating and ultimately reaching fixation. Here, using simulations, we study the dynamics of phenotypic and genetic change as asexual populations under clonal interference climb a Fisherian landscape, and ask about the conditions under which FGM can display the simultaneous increase and fixation of multiple mutations-mutation cohorts-along the adaptive walk. We find that FGM under clonal interference, and with varying levels of pleiotropy, can reproduce the experimentally observed competition between different cohorts of mutations, some of which have a high probability of fixation along the adaptive walk. Overall, our results show that the surprising dynamics of mutation cohorts recently observed during experimental adaptation of microbial populations can be expected under one of the oldest and simplest theoretical models of adaptation-FGM.

Energy norm a-posteriori error estimation for hp-adaptive discontinuous Galerkin methods for elliptic problems in three dimensions

We develop the energy norm a-posteriori error estimation for hp-version discontinuous Galerkin (DG) discretizations of elliptic boundary-value problems on 1-irregularly, isotropically refined affine hexahedral meshes in three dimensions. We derive a reliable and efficient indicator for the errors measured in terms of the natural energy norm. The ratio of the efficiency and reliability constants is independent of the local mesh sizes and weakly depending on the polynomial degrees. In our analysis we make use of an hp-version averaging operator in three dimensions, which we explicitly construct and analyze. We use our error indicator in an hp-adaptive refinement algorithm and illustrate its practical performance in a series of numerical examples. Our numerical results indicate that exponential rates of convergence are achieved for problems with smooth solutions, as well as for problems with isotropic corner singularities.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.