Deterministic Response Research Articles

In SilicoNanodosimetry: New Insights into Nontargeted Biological Responses to Radiation

The long-held view that radiation-induced biological damage must be initiated in the cell nucleus, either on or near DNA itself, is being confronted by mounting evidence to suggest otherwise. While the efficacy of cell death may be determined by radiation damage to nuclear DNA, a plethora of less deterministic biological responses has been observed when DNA is not targeted. These so-called nontargeted responses cannot be understood in the framework of DNA-centric radiobiological models; what is needed are new physically motivated models that address the damage-sensing signalling pathways triggered by the production of reactive free radicals. To this end, we have conducted a series of in silico experiments aimed at elucidating the underlying physical processes responsible for nontargeted biological responses to radiation. Our simulation studies implement new results on very low-energy electromagnetic interactions in liquid water (applicable down to nanoscales) and we also consider a realistic simulation of extranuclear microbeam irradiation of a cell. Our results support the idea that organelles with important functional roles, such as mitochondria and lysosomes, as well as membranes, are viable targets for ionizations and excitations, and their chemical composition and density are critical to determining the free radical yield and ensuing biological responses.

Seascape Metrics of Shelf-Margin Reefs and Reef Sand Aprons of Holocene Carbonate Platforms

Shelf-margin reefs and reef sand aprons are important geomorphic and facies elements associated with many isolated platforms today and in the stratigraphic record. Although it is generally appreciated that shelf-margin reefs and reef sand aprons have formed at or near breaks in slope at the rims of platforms throughout geologic time, possible environmental causes for variation in their sizes are not well understood. To provide better constraints for assessing possible reasons for such variability in ancient systems, this study relates local, regional, and global patterns of variation in the seascape attributes of Holocene shelf-margin reef and reef sand apron systems to a suite of potential environmental controls. Landsat data from more than 60 isolated carbonate platforms and atolls from the Caribbean Sea, Indian Ocean, South Pacific Ocean, Central Pacific Ocean, South China Sea, and Indonesian Seas were investigated by digitization and spatial analysis of facies belts, and compared with regional environmental parameters. The results of this analysis suggest that: (1) Reefs cover from < 1 to 55% of the spatial extent of lithotopes on platforms (mean = 20%), whereas reef sand aprons represent between 0 and 65% (mean = 20%). (2) The spatial extent of reefs is inversely related to platform size, but reef sand aprons show no comparable trend. (3) Widths of reefs and reef sand aprons are variable within and among platforms, but widths from all platforms and from platforms within different regions are characterized by log-normal size-frequency distributions. (4) Widths of these facies belts vary as a function of environmental factors such as swell period, swell height, tidal amplitude, latitude, and margin orientation relative to direction of wind and wave approach. These data indicate the presence of trends in widths of facies belts within different regions that correlate with regional oceanographic patterns. Nonetheless, marked variability is evident on individual platforms, among platforms within each region, and globally; these variations are not related to any of the parameterized environmental variables. This observation are interpreted to reflect the influences of unknown (and in some cases, unknowable) spatial and historical contingencies such as the depth to bedrock, character of earlier Holocene sea-level change, or changes in physical oceanographic state (waves or tides). The collective influence of these parameters, each of which individually may have the potential to invoke a deterministic response, may be reflected in reef and sand aprons with log-normal width-frequency distributions, interpreted to reflect multiplicative random effects. Collectively, however, these results suggest that accurate, a priori prediction of the details of the sizes of analogous facies bodies in the stratigraphic record may be impossible, especially in the deep geologic past, where biologic and physical controls are even less well constrained.

Discrete Domain Analysis Of Dexterous Hand Model By Simulation Aspect

Dexterity, adroitness in using the hands or body, is the prime or essential aspect in modeling dexterous hand. Deterministic response analysis of Dexterous Hand Model (DHM) advances the research area with the development of prosthetic control. Simulation procedure implies to build up stability of the reference transfer function of Dexterous Hand. Stability analysis with all simulation aspect is required to expand the discrete domain transfer function. The present work deals with the discussion of stability criteria and simulation in discrete domain by approaching Jury Test with sampled data control model.

Issues in Establishing Climate Sensitivity in Recent Studies

Numerous attempts have been made to constrain climate sensitivity with observations [1-10] (with [6] as LC09, [8] as SB11). While all of these attempts contain various caveats and sources of uncertainty, some efforts have been shown to contain major errors and are demonstrably incorrect. For example, multiple studies [11-13] separately addressed weaknesses in LC09 [6]. The work of Trenberth et al. [13], for instance, demonstrated a basic lack of robustness in the LC09 method that fundamentally undermined their results. Minor changes in that study’s subjective assumptions yielded major changes in its main conclusions. Moreover, Trenberth et al. [13] criticized the interpretation of El Niño-Southern Oscillation (ENSO) as an analogue for exploring the forced response of the climate system. In addition, as many cloud variations on monthly time scales result from internal atmospheric variability, such as the Madden-Julian Oscillation, cloud variability is not a deterministic response to surface temperatures. Nevertheless, many of the problems in LC09 [6] have been perpetuated, and Dessler [10] has pointed out similar issues with two more recent such attempts [7,8]. Here we briefly summarize more generally some of the pitfalls and issues involved in developing observational constraints on climate feedbacks. [...]

Random vibration of a train traversing a bridge subjected to traveling seismic waves

Non-stationary random vibration of 3D time-dependent train–bridge systems subjected to multi-point earthquake excitations, including wave passage effect, is investigated using the pseudo-excitation method (PEM). The motion equation of such a system is established by coupling the train and bridge through wheel–rail contact relationships and accounting for the phase-lags between pier excitations. The horizontal and vertical earthquake excitations are both assumed to be uniformly modulated, fully coherent random excitations with different phases, while the excitation due to track irregularities is assumed to be a 3D, fully coherent random excitation with velocity-dependent time lags. PEM is first proven to be applicable to such time-dependent systems, and is then used to transform the random excitations into a series of deterministic pseudo excitations. By solving for the corresponding deterministic pseudo responses, various non-stationary random responses, including the time-dependent power spectral density functions (PSD) and standard deviations (SD), can be obtained easily. A case study is then presented in which the China-Star high-speed train traverses a seven-span continuous bridge that is being excited by an earthquake. The results show the effectiveness and accuracy of the proposed method by comparison with a Monte Carlo simulation. Additionally, the influences of seismic apparent wave velocity and train speed on the system random responses are discussed.

Efficient design of experiments for structural optimization using significance screening

When performing structural optimization of large scale engineering problems, the choice of experiment design is important. However, classical experiment designs are developed to deal with undesired but inevitable scatter and are thus not ideal for sampling of deterministic computational responses. In this paper, a novel screening and design of computer experiments algorithm is presented. It is based on the concept of orthogonal design variable significances and is applicable for problems where design variables do not simultaneously have a significant influence on any of the constraints. The algorithm presented uses significance orthogonality to combine several one-factor-at-a-time experiments in one several-factors-at-a-time experiment. The procedure results in a reduced experiment design matrix. In the reduced experiment design, each variable is varied exactly once but several variables may be varied simultaneously, if their significances with respect to the constraints are orthogonal. Moreover, a measure of influence, as well as an influence significance threshold, is defined. In applications, the value of the threshold is left up to the engineer. To assist in this choice, a relation between model simplification, expressed in terms of the significance threshold, and computational cost is established in a screening. The relation between efficiency and loss of accuracy for the proposed approach is discussed and demonstrated. For two solid mechanics type problems studied herein, the necessary number of simulations could be reduced by 25% and 64%, respectively, with negligible losses in accuracy.

Structural identification through the measure of deterministic and stochastic time-domain dynamic response

In the framework of time domain parametric identification techniques, least square methods are to date one of the most utilized approaches. The basic idea of the least square method stays in the minimization of the so called penalty function representing the error squared between selected measured response parameters and the correspondent quantities determined through the study of a pertinent finite element model. In this paper, both time-domain deterministic and stochastic response has been used for defining a suitable penalty function. The standard bounded variables least square approach has been used as a vehicle for identifying selected structural parameters. In this context a computationally competitive procedure for determining pertinent sensitivity matrix has been proposed. Various numerical examples including ASCE benchmark show the effectiveness of the proposed method also for determining deteriorating structural parameters simulating damage.

Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae

Stochasticity is an inherent feature of complex systems with nanoscale structure. In such systems information is represented by small collections of elements (e.g., a few electrons on a quantum dot), and small variations in the populations of these elements may lead to big uncertainties in the information. Unfortunately, little is known about how to work within this inherently noisy environment to design robust functionality into complex nanoscale systems. Here, we look to the biological cell as an intriguing model system where evolution has mediated the trade-offs between fluctuations and function, and in particular we look at the relationships and trade-offs between stochastic and deterministic responses in the gene expression of budding yeast (Saccharomyces cerevisiae). We find gene regulatory arrangements that control the stochastic and deterministic components of expression, and show that genes that have evolved to respond to stimuli (stress) in the most strongly deterministic way exhibit the most noise in the absence of the stimuli. We show that this relationship is consistent with a bursty two-state model of gene expression, and demonstrate that this regulatory motif generates the most uncertainty in gene expression when there is the greatest uncertainty in the optimal level of gene expression.

Timoshenko versus Euler beam theory: Pitfalls of a deterministic approach

The selection criteria for Euler–Bernoulli or Timoshenko beam theories are generally given by means of some deterministic rule involving beam dimensions. The Euler–Bernoulli beam theory is used to model the behavior of flexure-dominated (or “long”) beams. The Timoshenko theory applies for shear-dominated (or “short”) beams. In the mid-length range, both theories should be equivalent, and some agreement between them would be expected. Indeed, it is shown in the paper that, for some mid-length beams, the deterministic displacement responses for the two theories agrees very well. However, the article points out that the behavior of the two beam models is radically different in terms of uncertainty propagation. In the paper, some beam parameters are modeled as parameterized stochastic processes. The two formulations are implemented and solved via a Monte Carlo–Galerkin scheme. It is shown that, for uncertain elasticity modulus, propagation of uncertainty to the displacement response is much larger for Timoshenko beams than for Euler–Bernoulli beams. On the other hand, propagation of the uncertainty for random beam height is much larger for Euler beam displacements. Hence, any reliability or risk analysis becomes completely dependent on the beam theory employed. The authors believe this is not widely acknowledged by the structural safety or stochastic mechanics communities.

A multi-point univariate decomposition method for structural reliability analysis

A new multi-point univariate decomposition method is presented for structural reliability analysis involving multiple most probable points (MPPs). The method involves a novel function decomposition at all MPPs that facilitates local univariate approximations of a performance function in the rotated Gaussian space, Lagrange interpolation for univariate component functions and return mapping to the standard Gaussian space, and Monte Carlo simulation. In addition to the effort in identifying all MPPs, the computational effort in the multi-point univariate method can be viewed as performing deterministic response analysis at user-selected input defined by sample points. Compared with the existing multi-point FORM/SORM, the multi-point univariate method developed provides a higher-order approximation of the boundary of the failure domain. Both the point-fitted SORM and the univariate method entail linearly varying cost with respect to the number of variables. However, the univariate method with less than nine sample points requires fewer calculations of the performance function than the point-fitted SORM. Numerical results indicate that the proposed method consistently generates an accurate and computationally efficient estimate of the probability of failure.

Trial-to-Trial Variability in Evoked Neural Responses Exhibits a Very Low Frequency Temporal Signature

In functional magnetic resonance (fMRI) studies, the blood oxygen level dependent (BOLD) signal displays intrinsic spontaneous and task-independent very low frequency (VLF) oscillations (&lt; 0.1 Hz). Most prominent during rest, when they persist into task sessions they can predict trial-to-trial variability in both evoked behavior and brain responses by providing a baseline onto which deterministic responses elicited by the task are superimposed. Moreover, evidence in the literature tentatively suggests that this VLF activity may not be present in the data as distinct, independent source(s) per se, but rather as a mechanism that modulates and perhaps even governs underlying brain processes. Here, we use electrophysiology to investigate the intertrial variability observed in magnetoencephalographic (MEG) event-related field (ERF) components, and to examine whether this variability exhibits a VLF time signature in order to indirectly infer information about the underlying slow waves. The focus is on the visual component, the M100, understood to be regulated by attention. We also explored whether individual differences in the M100 VLF pattern varies as a function of attention deficit/hyperactivity disorder (ADHD) by comparing 11 cases against 11 controls. The M100 component was extracted from the data using a recently introduced blind-source separation technique – space-time independent component analysis (ST-ICA) – which allowed trial-by-trial analysis to be performed on the M100 for proper assessment of VLF modulation. Our results demonstrate, for the first time, the ability of this signal-processing method to isolate relevant components from multidimensional, noisy, ERF data recorded from a highly dense 148-channel MEG system. The intertrial variability in the amplitude and latency of the M100 responses exhibits a slow wave pattern (&lt; 0.1 Hz). However, there was no evidence that the degree of VLF modulation was different in ADHD participants. The role of this VLF activity in brain function is discussed.

Three-Step Method for Stiffness Identification of Inter-Story Shearing Structures Under Ambient Excitation

This paper presents a three-step method for the stiffness identification of inter-story shearing structures under ambient excitation. The transition from structural random response to deterministic response is realized by the natural excitation technique (NExT). The parameter-decoupled free vibration equation of inter-story shearing structures is deduced, which can simplify the procedure of identification and reduce the amount of calculation. Through the effective combination of the NExT, the parameter-decoupled method, and the extended Kalman filter (EKF) algorithm, a good scheme is presented for stiffness identification of inter-story shearing structures under ambient excitation. Using inter-story shearing structures with six-degree-of-freedom and ten-degree-of-freedom as examples, the scheme is tested by numerical simulation and experiment. The result shows that the maximum of identification error is 7.82%, and it can reach the requirement of engineering application basically.

Mass Sensing Based on Deterministic and Stochastic Responses of Elastically Coupled Nanocantilevers

Coupled nanomechanical systems and their entangled eigenstates offer unique opportunities for the detection of ultrasmall masses. In this paper we show theoretically and experimentally that the stochastic and deterministic responses of a pair of coupled nanocantilevers provide different and complementary information about the added mass of an analyte and its location. This method allows the sensitive detection of minute quantities of mass even in the presence of large initial differences in the active masses of the two cantilevers. Finally, we show the fundamental limits in mass detection of this sensing paradigm.

A Realistic Assessment of the Indicator Potential of Butterflies and Other Charismatic Taxonomic Groups

Charismatic groups of animals and plants often are proposed as sentinels of environmental status and trends. Nevertheless, many claims that a certain taxonomic group can provide more-general information on environmental quality are not evaluated critically. To address several of the many definitions of indicator species, we used butterflies to explore in some detail the attributes that affect implementation of indicators generically. There probably are few individual species, or sets of species, that can serve as scientifically valid, cost-effective measures of the status or trend of an environmental phenomenon that is difficult to measure directly. Nevertheless, there are species with distributions, abundances, or demographic characteristics that are responsive to known environmental changes. In this context, single or multiple species can serve as indicators when targets are defined explicitly, ecological relationships between the target and the putative indicators are well understood, and data are sufficient to differentiate between deterministic and stochastic responses. Although these situations exist, they are less common than might be apparent from an extensive and often confounded literature on indicators. Instead, the public appeal of charismatic groups may be driving much of their acclaim as indicators. The same taxon may not be appropriate for marketing a general conservation mission and for drawing strong inference about specific environmental changes. To provide insights into the progress of conservation efforts, it is essential to identify scientific and practical criteria for selection and application of indicators and then to examine whether a given taxonomic group meets those criteria.

Bifurcation structure and noise‐assisted transitions in the Pleistocene glacial cycles

The glacial cycles are attributed to the climatic response of the orbital changes in the irradiance to the Earth. These changes in the forcing are too small to explain the observed climate variations as simple linear responses. Nonlinear amplifications of the orbital forcing are necessary to account for the glacial cycles. Here an empirical model of the nonlinear response is presented. From the model it is possible to assess the role of stochastic noise in comparison to the deterministic orbital forcing of the ice ages. The model is based on the bifurcation structure derived from the climate history. It indicates the dynamical origin of the mid‐Pleistocene transition from the “41 ka world” to the “100 ka world.” The dominant forcing in the latter is still the 41 ka obliquity cycle, but the bifurcation structure of the climate system is changed. The model suggests that transitions between glacial and interglacial climate are assisted by internal stochastic noise in the period prior to the last five glacial cycles, while the last five cycles are deterministic responses to the orbital forcing.

Ensemble-Based Estimates of the Predictability of Wind-Driven Coastal Ocean Flow over Topography

AbstractThe predictability of coastal ocean circulation over the central Oregon shelf, a region of strong wind-driven currents and variable topography, is studied using ensembles of 50-day primitive equation ocean model simulations with realistic topography, simplified lateral boundary conditions, and forcing from both idealized and observed wind time series representative of the summer upwelling season. The main focus is on the balance, relevant to practical predictability, between deterministic response to known or well-predicted forcing, uncertainty in initial conditions, and sensitivity to instabilities and topographic interactions. Large ensemble and single-simulation variances are found downstream of topographic features, associated with transitions between along-isobath and cross-isobath flow, which are in turn related both to the time-integrated amplitude of upwelling-favorable wind forcing and to the formation of small-scale eddies. Simulated predictability experiments are conducted and model forecasts are verified by standard statistics including anomaly correlation coefficient, and root-mean-square error. A new variant of relative entropy, the forecast relative entropy, is introduced to quantify the predictive information content in the forecast ensemble, relative to the initial ensemble. The results suggest that, even under conditions of relatively weak wind forcing, the deterministic response is stronger than instability growth over the 3–7-day forecast intervals considered here. Consequently, important elements of the coastal circulation should be accessible to predictive, dynamical forecasts on the nominal 7-day predictability time scale of the atmospheric forcing, provided that sufficiently accurate initializations are available. These results on predictability are consistent with inferences drawn from recent modeling studies of coastal ocean circulation along the central Oregon shelf, and should have general validity for other, similar regions.

Parametric estimation of spike train statistics

We consider the evolution of a network of neurons, focusing on the asymptotic behavior of spikes dynamics instead of membrane potential dynamics. The spike response is not sought as a deterministic response in this context, but as a conditional probability: Reading the consists in inferring such a probability. This probability is computed from empirical raster plots, by using the framework of thermodynamic formalism in ergodic theory. This provides us a parametric statistical model where the probability has the form of a Gibbs distribution. In this respect, this approach generalizes the seminal and profound work of Schneidman and collaborators . A minimal presentation of the formalism is reviewed here, while a general algorithmic estimation method is proposed, minimizing the relative entropy, yielding fast convergent implementations. It is also made explicit how several spike observables (entropy, rate, synchronizations, correlations) are given in closed-form from the parametric estimation. This paradigm does not only allow us to estimate the spike statistics, given a design choice, but also to compare different models, thus answering comparative questions about the neural code such as : are correlations (or time synchrony or a given set of spike patterns, ..) significant with respect to rate coding ? A numerical validation of the method is proposed and the perspectives regarding spike-train code analysis are also discussed.

Brownian vortexes

Mechanical equilibrium at zero temperature does not necessarily imply thermodynamic equilibrium at finite temperature for a particle confined by a static but nonconservative force field. Instead, the diffusing particle can enter into a steady state characterized by toroidal circulation in the probability flux, which we call a Brownian vortex. The circulatory bias in the particle's thermally driven trajectory is not simply a deterministic response to the solenoidal component of the force but rather reflects interplay between advection and diffusion in which thermal fluctuations extract work from the nonconservative force field. As an example of this previously unrecognized class of stochastic heat engines, we consider a colloidal sphere diffusing in a conventional optical tweezer. We demonstrate both theoretically and experimentally that nonconservative optical forces bias the particle's fluctuations into toroidal vortexes whose circulation can reverse direction with temperature or laser power.

A null-model analysis of the spatio-temporal distribution of earthworm species assemblages in Colombian grasslands

Abstract:Earthworm assemblages are usually spatio-temporally structured in mosaics of patches with different species composition. We re-analysed results of past research carried out in Eastern Colombia to explore how interspecific competition accounts for this pattern. In three sown pastures and three native savannas, density data matrices were obtained from spatially explicit samplings at several successive dates, and spatio-temporal patterns of species assemblages were described through partial triadic analyses and geostatistics. This first analysis detected assemblage patchiness in the six plots at spatial scales ranging from 6 to 33 m. Species richness ranged from 5 to 6 species per plot. Null models were further used to analyse niche overlap and morphometric distribution patterns at two different scales, i.e. at the ‘plot level’ and the ‘patch level’. Seasonal and vertical niche overlaps were higher than expected by chance at both scales, indicating high environmental constraints on assemblage membership. Within-patch overlaps were lower than plot-scale overlaps. Biometric niche overlap was random at the plot level and was weakly lower than that expected by chance in patches. Body weight was significantly overdispersed and constant whatever the scale, while body length and diameter showed a similar trend within patches. These results suggest that earthworms form distinct assemblages within patches, mainly driven by deterministic responses to competition: ecologically similar species avoid competition through spatial segregation, whereas a minimal level of ecological segregation is required to allow co-existence in a given patch.

Real-time control architecture using Xenomai for intelligent service robots in USN environments

This paper describes the implementation of a dual-kernel software architecture, based on standard Linux and real-time embedded Linux, for real-time control of service robots in ubiquitous sensor network environments. Mobile robots are used in active service for the assisted living of elderly people, monitoring their mental and physiological data with wireless sensor nodes. The data collected from sensor nodes are routed back to a sink node through multi-hop communication. The moving sink node installed on the main controller of the robot collects data and transmits it to the main controller. To be able to handle emergency situations, the robot needs to satisfy real-time requirements when processing the data collected, and invoking tasks to execute. This paper realizes a multi-hop sensor network and proposes real-time software architecture based on Xenomai. The real-time tasks were implemented, with priority, to rapidly respond to urgent sensor data. In order to validate the deterministic response of the proposed system, the performance measurements for the delay in handling the sensed data transmission and the trajectory control with a feedback loop were evaluated on the non real-time standard Linux.