Sleepless night, the moon is bright: longitudinal study of lunar phase and sleep

Popular belief holds that the lunar cycle affects human physiology, behaviour and health. We examined the influence of moon phase on sleep duration in a secondary analysis of a feasibility study of mobile telephone base stations and sleep quality. We studied 31 volunteers (18 women and 13 men, mean age 50 years) from a suburban area of Switzerland longitudinally over 6 weeks, including two full moons. Subjective sleep duration was calculated from sleep diary data. Data were analysed using multiple linear regression models with random effects. Mean sleep duration was 6 h 49 min. Subjective sleep duration varied with the lunar cycle, from 6 h 41 min at full moon to 7 h 00 min at new moon (P < 0.001). Average sleep duration was shortened by 68 min during the week compared with weekends (P < 0.001). Men slept 17 min longer than women (P < 0.001) and sleep duration decreased with age (P < 0.001). There was also evidence that rating of fatigue in the morning was associated with moon phase, with more tiredness (P = 0.027) at full moon. The study was designed for other purposes and the association between lunar cycle and sleep duration will need to be confirmed in further studies.

Optimal beam forming for laser beam propagation through random media

Focusing optical beams on a target through random propagation media is very important in many applications such as free space optical communica- tions and laser weapons. Random media effects such as beam spread and scintillation can degrade the optical system's performance severely. Compensation schemes are needed in these applications to overcome these random media effcts. In this research, we investigated the optimal beams for two different optimization criteria: one is to maximize the concentrated received intensity and the other is to minimize the scintillation index at the target plane. In the study of the optimal beam to maximize the weighted integrated intensity, we derive a similarity relationship between pupil-plane phase screen and extended Huygens-Fresnel model, and demonstrate the limited utility of maximizing the average integrated intensity. In the study ofthe optimal beam to minimize the scintillation index, we derive the first- and second-order moments for the integrated intensity of multiple coherent modes. Hermite-Gaussian and Laguerre-Gaussian modes are used as the coherent modes to synthesize an optimal partially coherent beam. The optimal beams demonstrate evident reduction of scintillation index, and prove to be insensitive to the aperture averaging effect.

Saddlepoint approximations to sensitivities of tail probabilities of random sums and comparisons with Monte Carlo estimators

This article proposes computing sensitivities of upper tail probabilities of random sums by the saddlepoint approximation. The considered sensitivity is the derivative of the upper tail probability with respect to the parameter of the summation index distribution. Random sums with Poisson or Geometric distributed summation indices and Gamma or Weibull distributed summands are considered. The score method with importance sampling is considered as an alternative approximation. Numerical studies show that the saddlepoint approximation and the method of score with importance sampling are very accurate. But the saddlepoint approximation is substantially faster than the score method with importance sampling. Thus, the suggested saddlepoint approximation can be conveniently used in various scientific problems.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

Absolute polarity determination of teeth cementum by phase sensitive second harmonic generation microscopy

The absolute sign of local polarity in relation to the biological growth direction has been investigated for teeth cementum using phase sensitive second harmonic generation microscopy (PS-SHGM) and a crystal of 2-cyclooctylamino-5-nitropyridine (COANP) as a nonlinear optic (NLO) reference material. A second harmonic generation (SHG) response was found in two directions of cementum: radial (acellular extrinsic fibers that are oriented more or less perpendicular to the root surface) and circumferential (cellular intrinsic fibers that are oriented more or less parallel to the surface). A mono-polar state was demonstrated for acellular extrinsic cementum. However, along the different parts of cementum in circumferential direction, two corresponding domains were observed featuring an opposite sign of polarity indicative for a bi-polar microscopic state of cellular intrinsic cementum. The phase information showed that the orientation of radial collagen fibrils of cementum is regularly organized with the donor (D) groups pointing to the surface. Circumferential collagen molecules feature orientational disorder and are oriented up and down in random manner showing acceptor or donor groups at the surface of cementum. Considering that the cementum continues to grow in thickness throughout life, we can conclude that the cementum is growing circumferentially in two opposite directions and radially in one direction. A Markov chain type model for polarity formation in the direction of growth predicts D-groups preferably appearing at the fiber front.

Thermodynamical Phase Noise in Oscillators Based on L-C Resonators

Using a new Admittance-based model for electrical noise able to handle Fluctuations and Dissipations of electrical energy, we explain the phase noise of oscillators that use feedback around L-C resonators. We show that Fluctuations produce the Line Broadening of their output spectrum around its mean frequency f0 and that the Pedestal of phase noise far from f0 comes from Dissipations modified by the feedback electronics. The charge noise power 4FkT/R C2/s that disturbs the otherwise periodic fluctuation of charge these oscillators aim to sustain in their L-C-R resonator, is what creates their phase noise proportional to Leeson’s noise figure F and to the charge noise power 4kT/R C2/s of their capacitance C that today’s modelling would consider as the current noise density in A2/Hz of their resistance R. Linked with this (A2/Hz?C2/s) equivalence, R becomes a random series in time of discrete chances to Dissipate energy in Thermal Equilibrium (TE) giving a similar series of discrete Conversions of electrical energy into heat when the resonator is out of TE due to the Signal power it handles. Therefore, phase noise reflects the way oscillators sense thermal exchanges of energy with their environment.

Thermodynamical Phase Noise in Oscillators Based on L-C Resonators (Foundations)

Using a new Admittance-based model for electrical noise able to handle Fluctuations and Dissipations of electrical energy, we explain the phase noise of oscillators that use feedback around L-C resonators. We show that Fluctuations produce the Line Broadening of their output spectrum around its mean frequency f0 and that the Pedestal of phase noise far from f0 comes from Dissipations modified by the feedback electronics. The charge noise power 4FkT/R C2/s that disturbs the otherwise periodic fluctuation of charge these oscillators aim to sustain in their L-C-R resonator, is what creates their phase noise proportional to Leeson’s noise figure F and to the charge noise power 4kT/R C2/s of their capacitance C that today’s modelling would consider as the current noise density in A2/Hz of their resistance R. Linked with this (A2/Hz?C2/s) equivalence, R becomes a random series in time of discrete chances to Dissipate energy in Thermal Equilibrium (TE) giving a similar series of discrete Conversions of electrical energy into heat when the resonator is out of TE due to the Signal power it handles. Therefore, phase noise reflects the way oscillators sense thermal exchanges of energy with their environment

Node sampling using random centrifugal walks

Sampling a network with a given probability distribution has been identified as a useful operation. In this paper we propose distributed algorithms for sampling networks, so that nodes are selected by a special node, called the source, with a given probability distribution. All these algorithms are based on a new class of random walks, that we call Random Centrifugal Walks (RCW). A RCW is a random walk that starts at the source and always moves away from it. Firstly, an algorithm to sample any connected network using RCW is proposed. The algorithm assumes that each node has a weight, so that the sampling process must select a node with a probability proportional to its weight. This algorithm requires a preprocessing phase before the sampling of nodes. In particular, a minimum diameter spanning tree (MDST) is created in the network, and then nodes weights are efficiently aggregated using the tree. The good news are that the preprocessing is done only once, regardless of the number of sources and the number of samples taken from the network. After that, every sample is done with a RCW whose length is bounded by the network diameter. Secondly, RCW algorithms that do not require preprocessing are proposed for grids and networks with regular concentric connectivity, for the case when the probability of selecting a node is a function of its distance to the source. The key features of the RCW algorithms (unlike previous Markovian approaches) are that (1) they do not need to warm-up (stabilize), (2) the sampling always finishes in a number of hops bounded by the network diameter, and (3) it selects a node with the exact probability distribution.

Phase transitions in number theory: from the birthday problem to Sidon sets

In this work, we show how number theoretical problems can be fruitfully approached with the tools of statistical physics. We focus on g-Sidon sets, which describe sequences of integers whose pairwise sums are different, and propose a random decision problem which addresses the probability of a random set of k integers to be g-Sidon. First, we provide numerical evidence showing that there is a crossover between satisfiable and unsatisfiable phases which converts to an abrupt phase transition in a properly defined thermodynamic limit. Initially assuming independence, we then develop a mean-field theory for the g-Sidon decision problem. We further improve the mean-field theory, which is only qualitatively correct, by incorporating deviations from independence, yielding results in good quantitative agreement with the numerics for both finite systems and in the thermodynamic limit. Connections between the generalized birthday problem in probability theory, the number theory of Sidon sets and the properties of q-Potts models in condensed matter physics are briefly discussed

Atomistic modeling of Ge damage accumulation, amorphization and solid phase epitaxial regrowth

En los últimos años, el Ge ha ganado de nuevo atención con la finalidad de ser integrado en el seno de las existentes tecnologías de microelectrónica. Aunque no se le considera como un canddato capaz de reemplazar completamente al Si en el futuro próximo, probalemente servirá como un excelente complemento para aumentar las propiedades eléctricas en dispositivos futuros, especialmente debido a su alta movilidad de portadores. Esta integración requiere de un avance significativo del estado del arte en los procesos de fabricado. Técnicas de simulación, como los algoritmos de Monte Carlo cinético (KMC), proporcionan un ambiente atractivo para llevar a cabo investigación y desarrollo en este campo, especialmente en términos de costes en tiempo y financiación. En este estudio se han usado, por primera vez, técnicas de KMC con el fin entender el procesado “front-end” de Ge en su fabricación, específicamente la acumulación de dañado y amorfización producidas por implantación iónica y el crecimiento epitaxial en fase sólida (SPER) de las capas amorfizadas. Primero, simulaciones de aproximación de clisiones binarias (BCA) son usadas para calcular el dañado causado por cada ión. La evolución de este dañado en el tiempo se simula usando KMC sin red, o de objetos (OKMC) en el que sólamente se consideran los defectos. El SPER se simula a través de una aproximación KMC de red (LKMC), siendo capaz de seguir la evolución de los átomos de la red que forman la intercara amorfo/cristalina. Con el modelo de amorfización desarrollado a lo largo de este trabajo, implementado en un simulador multi-material, se pueden simular todos estos procesos. Ha sido posible entender la acumulación de dañado, desde la generación de defectos puntuales hasta la formación completa de capas amorfas. Esta acumulación ocurre en tres regímenes bien diferenciados, empezando con un ritmo lento de formación de regiones de dañado, seguido por una rápida relajación local de ciertas áreas en la fase amorfa donde ambas fases, amorfa y cristalina, coexisten, para terminar en la amorfización completa de capas extensas, donde satura el ritmo de acumulación. Dicha transición ocurre cuando la concentración de dañado supera cierto valor límite, el cual es independiente de las condiciones de implantación. Cuando se implantan los iones a temperaturas relativamente altas, el recocido dinámico cura el dañado previamente introducido y se establece una competición entre la generación de dañado y su disolución. Estos efectos se vuelven especialmente importantes para iones ligeros, como el B, el cual crea dañado más diluido, pequeño y distribuido de manera diferente que el causado por la implantación de iones más pesados, como el Ge. Esta descripción reproduce satisfactoriamente la cantidad de dañado y la extensión de las capas amorfas causadas por implantación iónica reportadas en la bibliografía. La velocidad de recristalización de la muestra previamente amorfizada depende fuertemente de la orientación del sustrato. El modelo LKMC presentado ha sido capaz de explicar estas diferencias entre orientaciones a través de un simple modelo, dominado por una única energía de activación y diferentes prefactores en las frecuencias de SPER dependiendo de las configuraciones de vecinos de los átomos que recristalizan. La formación de maclas aparece como una consecuencia de esta descripción, y es predominante en sustratos crecidos en la orientación (111)Ge. Este modelo es capaz de reproducir resultados experimentales para diferentes orientaciones, temperaturas y tiempos de evolución de la intercara amorfo/cristalina reportados por diferentes autores. Las parametrizaciones preliminares realizadas de los tensores de activación de tensiones son también capaces de proveer una buena correlación entre las simulaciones y los resultados experimentales de velocidad de SPER a diferentes temperaturas bajo una presión hidrostática aplicada. Los estudios presentados en esta tesis han ayudado a alcanzar un mejor entendimiento de los mecanismos de producción de dañado, su evolución, amorfización y SPER para Ge, además de servir como una útil herramienta para continuar el trabajo en este campo. In the recent years, Ge has regained attention to be integrated into existing microelectronic technologies. Even though it is not thought to be a feasible full replacement to Si in the near future, it will likely serve as an excellent complement to enhance electrical properties in future devices, specially due to its high carrier mobilities. This integration requires a significant upgrade of the state-of-the-art of regular manufacturing processes. Simulation techniques, such as kinetic Monte Carlo (KMC) algorithms, provide an appealing environment to research and innovation in the field, specially in terms of time and funding costs. In the present study, KMC techniques are used, for the first time, to understand Ge front-end processing, specifically damage accumulation and amorphization produced by ion implantation and Solid Phase Epitaxial Regrowth (SPER) of the amorphized layers. First, Binary Collision Approximation (BCA) simulations are used to calculate the damage caused by every ion. The evolution of this damage over time is simulated using non-lattice, or Object, KMC (OKMC) in which only defects are considered. SPER is simulated through a Lattice KMC (LKMC) approach, being able to follow the evolution of the lattice atoms forming the amorphous/crystalline interface. With the amorphization model developed in this work, implemented into a multi-material process simulator, all these processes can be simulated. It has been possible to understand damage accumulation, from point defect generation up to full amorphous layers formation. This accumulation occurs in three differentiated regimes, starting at a slow formation rate of the damage regions, followed by a fast local relaxation of areas into the amorphous phase where both crystalline and amorphous phases coexist, ending in full amorphization of extended layers, where the accumulation rate saturates. This transition occurs when the damage concentration overcomes a certain threshold value, which is independent of the implantation conditions. When implanting ions at relatively high temperatures, dynamic annealing takes place, healing the previously induced damage and establishing a competition between damage generation and its dissolution. These effects become specially important for light ions, as B, for which the created damage is more diluted, smaller and differently distributed than that caused by implanting heavier ions, as Ge. This description successfully reproduces damage quantity and extension of amorphous layers caused by means of ion implantation reported in the literature. Recrystallization velocity of the previously amorphized sample strongly depends on the substrate orientation. The presented LKMC model has been able to explain these differences between orientations through a simple model, dominated by one only activation energy and different prefactors for the SPER rates depending on the neighboring configuration of the recrystallizing atoms. Twin defects formation appears as a consequence of this description, and are predominant for (111)Ge oriented grown substrates. This model is able to reproduce experimental results for different orientations, temperatures and times of evolution of the amorphous/crystalline interface reported by different authors. Preliminary parameterizations for the activation strain tensors are able to also provide a good match between simulations and reported experimental results for SPER velocities at different temperatures under the appliance of hydrostatic pressure. The studies presented in this thesis have helped to achieve a greater understanding of damage generation, evolution, amorphization and SPER mechanisms in Ge, and also provide a useful tool to continue research in this field.

A stochastic approximation algorithm with Markov chain Monte-Carlo method for incomplete data estimation problems

We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.

Critical transport properties of random metals in large magnetic fields

The threshold behavior of the transport properties of a random metal in the critical region near a metal–insulator transition is strongly affected by the measuring electromagnetic fields. In spite of the randomness, the electrical conductivity exhibits striking phase-coherent effects due to broken symmetry, which greatly sharpen the transition compared with the predictions of effective medium theories, as previously explained for electrical conductivities. Here broken symmetry explains the sign reversal of the T → 0 magnetoconductance of the metal–insulator transition in Si(B,P), also previously not understood by effective medium theories. Finally, the symmetry-breaking features of quantum percolation theory explain the unexpectedly very small electrical conductivity temperature exponent α = 0.22(2) recently observed in Ni(S,Se)2 alloys at the antiferromagnetic metal–insulator transition below T = 0.8 K.

Random locomotion and chemotaxis of human blood polymorphonuclear leukocytes (PMN) in the presence of EDTA: PMN in close quarters require neither leukocyte integrins nor external divalent cations

Divalent cations are thought essential for motile function of leukocytes in general, and for the function of critical adhesion molecules in particular. In the current study, under direct microscopic observation with concomitant time-lapse video recording, we examined the effects of 10 mM EDTA on locomotion of human blood polymorphonuclear leukocytes (PMN). In very thin slide preparations, EDTA did not impair either random locomotion or chemotaxis; motile behavior appeared to benefit from the close approximation of slide and coverslip (“chimneying”). In preparations twice as thick, PMN in EDTA first exhibited active deformability with little or no displacement, then rounded up and became motionless. However, on creation of a chemotactic gradient, the same cells were able to orient and make their way to the target, often, however, losing momentarily their purchase on the substrate. In either of these preparations without EDTA, specific antibodies to β2 integrins did not prevent random locomotion or chemotaxis, even when we added antibodies to β1 and αvβ3 integrins and to integrin-associated protein, and none of these antibodies added anything to the effects of EDTA. In the more turbulent environment of even more media, effects of anti-β2 integrins became evident: PMN still could locomote but adhered to substrate largely by their uropods and by uropod-associated filaments. We relate these findings to the reported independence from integrins of PMN in certain experimental and disease states. Moreover, we suggest that PMN locomotion in close quarters is not only integrin-independent, but independent of external divalent cations as well.

An equilibrium statistical model for the spreading phase of open-ocean convection

A “most probable state” equilibrium statistical theory for random distributions of hetons in a closed basin is developed here in the context of two-layer quasigeostrophic models for the spreading phase of open-ocean convection. The theory depends only on bulk conserved quantities such as energy, circulation, and the range of values of potential vorticity in each layer. The simplest theory is formulated for a uniform cooling event over the entire basin that triggers a homogeneous random distribution of convective towers. For a small Rossby deformation radius typical for open-ocean convection sites, the most probable states that arise from this theory strongly resemble the saturated baroclinic states of the spreading phase of convection, with a stabilizing barotropic rim current and localized temperature anomaly.

Coherent electron dynamics in a two-dimensional random system with mobility edges

We study numerically the dynamics of a one-electron wavepacket in a two-dimensional random lattice with long-range correlated diagonal disorder in the presence of a uniform electric field. The time-dependent Schrodinger equation is used for this purpose. We find that the wavepacket displays Bloch-like oscillations associated with the appearance of a phase of delocalized states in the strong correlation regime. The amplitude of oscillations directly reflects the bandwidth of the phase and allows us to measure it. The oscillations reveal two main frequencies whose values are determined by the structure of the underlying potential in the vicinity of the wavepacket maximum.