Exponential Patterns Research Articles

High UV Excitation Intensity Induces Photoconversion of DAPI During Wide-Field Microscopy

Background: Multi-color fluorescence microscopy is dependent on the spectral specificity of the dyes and probes used for localization. One of the most commonly used fluorescent DNA dyes is DAPI, which is usually excited by UV light to emit in the blue visible light range. Herein, we describe a pattern of decreasing DAPI fluorescence upon extended UV exposure, closely followed by an increase in emission maxima in the green range.
 Methods: UV-induced photo-conversion of DAPI to green-fluorescing photoproducts was studied on Chinese hamster ovary cells using wide-field fluorescence microscopy, at different UV exposure times and intensities. Imaging was done in repetitive cycles, by alternating between a DAPI and FITC filter cube and following this with a 1 second UV excitation time. The effect of differing UV light intensities on the photo- conversion process was not previously described in the literature.
 Results: Upon image analysis from a large sample of cells, the rate of photo-conversion was shown to be dependent on both the duration of UV excitation and the intensity of the UV light source. Both the process of DAPI depletion and photo-product growth showed biphasic exponential patterns of change. Furthermore, the level of DAPI fluorescence intensity was found to be negatively correlated with the green fluorescence of the photo-product.
 Limitations: This study did not examine the effect of differing mounting media or a variation in DAPI concentration on the rate of DAPI photo-conversion. Also, the exact light dosage to the system was not measured from the 100W Hg bulb. Photo-bleaching of green fluorescence in cells not stained with DAPI was not measured to control for bleaching of endogenous cell molecules.
 Conclusion: Based on our findings, a set of recommendations was formulated in order to help reduce the effects of UV-induced DAPI photo-conversion.

A Comparison of Climate Signal Trend Detection Uncertainty Analysis Methods

Abstract Two climate signal trend analysis methods are the focus of this paper. The uncertainty of trend estimate from these two methods is investigated using Monte Carlo simulation. Several theoretically and randomly generated series of white noise, first-order autoregressive and second-order autoregressive, are explored. The choice of method that is most appropriate for the time series of interest depends upon the autocorrelation structure of the series. If the structure has its autocorrelation coefficients decreased with increasing lags (i.e., an exponential decay pattern), then the method of Weatherhead et al. is adequate. If the structure exhibits a decreasing sinusoid pattern of coefficient with lags (or a damped sinusoid pattern) or a mixture of both exponential decay and damped sinusoid patterns, then the method of Leroy et al. is recommended. The two methods are then applied to the time series of monthly and globally averaged top-of-the-atmosphere (TOA) irradiances for the reflected solar shortwave and emitted longwave regions, using radiance observations made by Clouds and the Earth’s Radiant Energy System (CERES) instruments during March 2000 through June 2011. Examination of the autocorrelation structures indicates that the reflected shortwave region has an exponential decay pattern, while the longwave region has a mixture of exponential decay and damped sinusoid patterns. Therefore, it is recommended that the method of Weatherhead et al. is used for the series of reflected shortwave irradiances and that the method of Leroy et al. is used for the series of emitted longwave irradiances.

PD15-11 EXPONENTIAL PSA KINETIC PATTERN DURING OFF-TREATMENT PERIOD IS A POOR OUTCOMES RISK FACTOR IN INTERMITENT ANDROGEN DEPRIVATION THERAPY FOR PROSTATE CANCER

You have accessJournal of UrologyProstate Cancer: Staging I1 Apr 2014PD15-11 EXPONENTIAL PSA KINETIC PATTERN DURING OFF-TREATMENT PERIOD IS A POOR OUTCOMES RISK FACTOR IN INTERMITENT ANDROGEN DEPRIVATION THERAPY FOR PROSTATE CANCER Alexandre Ingels, Rafael Sanchez-Salas, Fabien Olivier, Dominique Prapotnich, Mehdi Fhima, José Dancausa, Stephane David, Fernando Secin, Eric Barret, Marc Galiano, Francois Rozet, and Xavier Cathelineau Alexandre IngelsAlexandre Ingels More articles by this author , Rafael Sanchez-SalasRafael Sanchez-Salas More articles by this author , Fabien OlivierFabien Olivier More articles by this author , Dominique PrapotnichDominique Prapotnich More articles by this author , Mehdi FhimaMehdi Fhima More articles by this author , José DancausaJosé Dancausa More articles by this author , Stephane DavidStephane David More articles by this author , Fernando SecinFernando Secin More articles by this author , Eric BarretEric Barret More articles by this author , Marc GalianoMarc Galiano More articles by this author , Francois RozetFrancois Rozet More articles by this author , and Xavier CathelineauXavier Cathelineau More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.1300AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Significance of PSA kinetics patterns during intermittent androgen deprivation (IAD) therapy off-treatment period for prostate cancer (PC) is not clearly established. To define relevant PSA kinetics patterns, to quantify them and to determine their prognostic value in IAD. METHODS Between 1992 and 2012, 735 patients underwent IAD at our institution. ON-Treatment Period: three months of gonadotropin-releasing hormone (GnRH) agonist combined with daily oral androgen receptor antagonist. Off-treatment Period was indicated when PSA was < 4 ng/ml. Hormonal therapy was restarted when PSA > 20 ng/ml or for clinical symptoms. Follow-up consisted in a 3-month PSA monitoring. Inclusion criteria to implement off-treatment period (OFTP) in analysis: increase between two consecutive PSA measurements >0.3 ng/ml; minimum four consecutive measurements; sequence followed by a treatment. Matching criteria was set ≤10%. Kaplan-Meier curves with Uni- and multivariate Cox regression model to estimate kinetics patterns impact on Time to Continuous Androgen Deprivation (TCAD), Time to Castration-Resistant PC (TCRPC) and Cancer Specific Survival (CSS). RESULTS 493 patients were selected based on inclusion criteria. A set of 1173 OFTPs was analyzed. OFTP PSA kinetics fitted with 3 patterns: exponential (PSA(t)=λ.eα.t), linear (PSA(t)=a.t), power law (PSA(t)= a.tc) or were classified as “other”. Only 45% of OFTPs (33% for 1st OFTP) matched with an exponential pattern. Linear and power law-like PSA kinetics represented respectively 7.5 and 7.7% of selected OFTPs. Remainder of the cohort had more complex kinetics. On multivariate analysis, exponential kinetic pattern on 1st OFTP was related with significantly worse CSS (p<0.0001, HR=2.9), shorter TCAD (p<0.0001, HR=2.3) and TCRPC (p=0.0003, HR=2.0) and happened to be the most robust factor to predict these outcomes. Figure 1: Survival curves for TCAD (a), CRPC (b) and CSS (c) comparing exponential (black) vs non-exponential (red) patterns CONCLUSIONS Although it is assumed to be the general pattern for PSA kinetics in PC, less than 50% of OFTPs analyzed fitted an exponential model, it appeared to be a risk factor for shorter IAD durations, time before castration-resistance PC and CSS. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e420 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Alexandre Ingels More articles by this author Rafael Sanchez-Salas More articles by this author Fabien Olivier More articles by this author Dominique Prapotnich More articles by this author Mehdi Fhima More articles by this author José Dancausa More articles by this author Stephane David More articles by this author Fernando Secin More articles by this author Eric Barret More articles by this author Marc Galiano More articles by this author Francois Rozet More articles by this author Xavier Cathelineau More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Failure mechanisms of load-sharing complex systems

We investigate the failure mechanisms of load-sharing complex systems. The system is composed of multiple nodes or components whose failures are determined based on the interaction of their respective strengths and loads (or capacity and demand, respectively) as well as the ability of a component to share its load with its neighbors when needed. We focus on two distinct mechanisms to model the interaction between components' strengths and loads. The failure mechanisms of these two models demonstrate temporal scaling phenomena, phase transitions, and multiple distinct failure modes excited by extremal dynamics. For critical ranges of parameters the models demonstrate power-law and exponential failure patterns. We identify the similarities and differences between the two mechanisms and the implications of our results for the failure mechanisms of complex systems in the real world.

Relationship between aboveground biomass and measures of structure and species diversity in tropical forests of Vietnam

Tropical forests play an important role in storing carbon through aboveground biomass (AGB) and are considered the highest biodiversity ecosystem on earth. However, the quantitative relationship between AGB and structure–species diversity is poorly understood. Twenty-eight 1-ha plots from old-growth tropical evergreen broadleaf forests and dry dipterocarp deciduous forests, distributed in six ecological regions throughout Vietnam, were used for large tree census (diameter at breast height⩾10cm). Measures of biodiversity (species richness, Shannon index, and evenness) and of structure–species diversity (biomass–species and abundance–biomass–species diversities) were used to determine the patterns and strengths of relationship between each measure and AGB. The linear, logarithmic, and exponential patterns were found, however the former dominated. Negative linear and exponential patterns represented relationship between evenness and AGB, while positive linear and logarithmic relationships were most suitable for others. In general, site – specific relationships (R2>0.6) were much stronger than inter – site relationships (R2<0.6). Meanwhile, relationships between measures of biodiversity and AGB (the lowest R2=0.14) were generally weaker than that between measures of structure–species diversity and AGB (the lowest R2=0.31). This finding indicates that structure–species diversity is a sound index representing the role of tropical forest in storing biomass and may suggest that uneven-aged and multistoried plantations should be encouraged for carbon sequestration.

Time-Series Analysis of Supergranule Characteristics at Solar Minimum

Sixty days of Doppler images from the Solar and Heliospheric Observatory (SOHO) / Michelson Doppler Imager (MDI) investigation during the 1996 and 2008 solar minima have been analyzed to show that certain supergranule characteristics (size, size range, and horizontal velocity) exhibit fluctuations of three to five days. Cross-correlating parameters showed a good, positive correlation between supergranulation size and size range, and a moderate, negative correlation between size range and velocity. The size and velocity do exhibit a moderate, negative correlation, but with a small time lag (less than 12 hours). Supergranule sizes during five days of co-temporal data from MDI and the Solar Dynamics Observatory (SDO) / Helioseismic Magnetic Imager (HMI) exhibit similar fluctuations with a high level of correlation between them. This verifies the solar origin of the fluctuations, which cannot be caused by instrumental artifacts according to these observations. Similar fluctuations are also observed in data simulations that model the evolution of the MDI Doppler pattern over a 60-day period. Correlations between the supergranule size and size range time-series derived from the simulated data are similar to those seen in MDI data. A simple toy-model using cumulative, uncorrelated exponential growth and decay patterns at random emergence times produces a time-series similar to the data simulations. The qualitative similarities between the simulated and the observed time-series suggest that the fluctuations arise from stochastic processes occurring within the solar convection zone. This behavior, propagating to surface manifestations of supergranulation, may assist our understanding of magnetic-field-line advection, evolution, and interaction.

Long-term GDP forecasts and the prospects for growth

The growth of GDP is considered as a natural-growth process amenable to description by the logistic-growth equation. The S-shaped logistic pattern provides good descriptions and forecasts for both nominal and real GDP per capita in the US over the last 80years. This enables the calculation of a long-term forecast for inflation, which is to enter a declining trend not so far in the future. The two logistics are well advanced, more so for nominal GDP. The assumption for logistic growth works even better for Japan whose nominal GDP per capita has already completed tracing out an entire logistic trajectory. The economic woes of industrialized countries could be attributed to the saturation of growth there, as if a niche in nature had been filled to capacity. In contrast, GDP growth in China and India is in the very early stages of logistic growth still indistinguishable from exponential patterns. The ceiling of these logistics can be anywhere between 5 and 10 times today's levels.

DTI Values in Key White Matter Tracts from Infancy through Adolescence

DTI is an advanced neuroimaging technique that allows in vivo quantification of water diffusion properties as surrogate markers of the integrity of WM microstructure. In our study, we investigated normative data from a large number of pediatric and adolescent participants to examine the developmental trends in DTI during this conspicuous WM maturation period. DTI data in 202 healthy pediatric and adolescent participants were analyzed retrospectively. Fractional anisotropy and mean diffusivity values in the corpus callosum and internal capsule were fitted to an exponential regression model to delineate age-dependent maturational changes across the WM structures. The DTI metrics demonstrated characteristic exponential patterns of progression during development and conspicuous age-dependent changes in the first 36 months, with rostral WM tracts experiencing the highest slope of the exponential function. In contrast, the highest final FA and lowest MD values were detected in the splenium of the corpus callosum and the posterior limb of the internal capsule. Our analysis shows that the more caudal portions of the corpus callosum and internal capsule begin the maturation process earlier than the rostral regions, but the rostral regions develop at a more accelerated pace, which may suggest that rostral regions rely on development of more caudal brain regions to instigate their development. Our normative DTI can be used as a reference to study normal spatiotemporal developmental profiles in the WM and help identify abnormal WM structures in patient populations.

The RARE model: A generalized approach to random relaxation processes in disordered systems

This paper introduces and analyses a general statistical model, termed the RAndom RElaxations (RARE) model, of random relaxation processes in disordered systems. The model considers excitations that are randomly scattered around a reaction center in a general embedding space. The model's input quantities are the spatial scattering statistics of the excitations around the reaction center, and the chemical reaction rates between the excitations and the reaction center as a function of their mutual distance. The framework of the RARE model is versatile and a detailed stochastic analysis of the random relaxation processes is established. Analytic results regarding the duration and the range of the random relaxation processes, as well as the model's thermodynamic limit, are obtained in closed form. In particular, the case of power-law inputs, which turn out to yield stretched exponential relaxation patterns and asymptotically Paretian relaxation ranges, is addressed in detail.

Design and management of high-performance, reliable and thermal-aware 3D networks-on-chip

Increasing the number of cores over a 2D plane is not efficient in hyper-core systems due to long interconnects. As a viable alternative over the 2D planar chip, 3D integrated technology offers greater device integration and shorter interlayer interconnects. 3D networks-on-chip (NoC)–bus hybrid mesh architecture, which is a hybrid between packet-switched network and a bus, was proposed to take advantage of the intrinsic attributes of 3D ICs. Even though this architecture was proposed as a feasible one to provide both performance and area benefits, the challenges of combining both media (NoC and bus) to design 3D NoCs have not been addressed. In this study, an efficient 3D NoC architecture is proposed to optimise performance, power consumption and reliability of 3D NoC–bus hybrid mesh system. The mechanism benefits from a congestion-aware and bus failure tolerant routing algorithm called ‘AdaptiveZ’ for vertical communication. In addition, the authors propose thermal-aware scheduling strategy in order to mitigate temperature by herding most of the switching activity closer to the heatsink. To estimate the efficiency of the proposed architecture, the system has been simulated using uniform, hotspot 10% and negative exponential distribution traffic patterns. In addition, a videoconference encoder has been used as a real application for system analysis. Compared with a typical stacked mesh 3D NoC, our extensive simulations demonstrate significant power, performance and peak temperature improvements.

The Assessment of Non-Linear Effects in Clinical Research

Background: Novel models for the assessment of non-linear data are being developed for the benefit of making better predictions from the data. Objective: To review traditional and modern models. Results, and Conclusions: 1) Logit and probit transformations are often successfully used to mimic a linear model. Logistic regression, Cox regression, Poisson regression, and Markow modeling are examples of logit transformation; 2) Either the x- or y-axis or both of them can be logarithmically transformed. Also Box Cox transformation equations and ACE (alternating conditional expectations) or AVAS (additive and variance stabilization for regression) packages are simple empirical methods often successful for linearly remodeling of non-linear data; 3) Data that are sinusoidal, can, generally, be successfully modeled using polynomial regression or Fourier analysis; 4) For exponential patterns like plasma concentration time relationships exponential modeling with or without Laplace transformations is a possibility. Spline and Loess are computationally intensive modern methods, suitable for smoothing data patterns, if the data plot leaves you with no idea of the relationship between the y- and x-values. There are no statistical tests to assess the goodness of fit of these methods, but it is always better than that of traditional models.

High activity and Lévy searches: jellyfish can search the water column like fish

Over-fishing may lead to a decrease in fish abundance and a proliferation of jellyfish. Active movements and prey search might be thought to provide a competitive advantage for fish, but here we use data-loggers to show that the frequently occurring coastal jellyfish (Rhizostoma octopus) does not simply passively drift to encounter prey. Jellyfish (327 days of data from 25 jellyfish with depth collected every 1 min) showed very dynamic vertical movements, with their integrated vertical movement averaging 619.2 m d(-1), more than 60 times the water depth where they were tagged. The majority of movement patterns were best approximated by exponential models describing normal random walks. However, jellyfish also showed switching behaviour from exponential patterns to patterns best fitted by a truncated Lévy distribution with exponents (mean μ=1.96, range 1.2-2.9) close to the theoretical optimum for searching for sparse prey (μopt≈2.0). Complex movements in these 'simple' animals may help jellyfish to compete effectively with fish for plankton prey, which may enhance their ability to increase in dominance in perturbed ocean systems.

Distance-decay patterns of nutrient loading at watershed scale: Regression modeling with a special spatial aggregation strategy

The effect of distance-decay on nutrient flux usually plays an important role in nutrient retention from non-point sources to surface waters. However, the distance-decay effect has been inappropriately neglected in many studies that adopted regression modeling method to quantify the relationship between watershed landscape and in-stream nutrient loading level. The goal of this study was to develop non-linear regression models that better quantify the role of distance on non-point source nutrient loads in rivers by using simulation results of a spatially-explicit model applied to the watersheds in the Upper Chattahoochee River Basin, Georgia. Because a detailed spatially-explicit modeling approach typically simulates the nutrient flux across the entire watershed, it provides opportunities to examine the nutrient decay patterns at watershed scale. The simulation results confirmed that regarding the effect of flow distance on nutrient loading, the exponential decay setting in the spatially-explicit model performs well. Other heterogeneous factors including slope and soil conditions do affect the decay results but not strongly enough to change the general exponential patterns. The nutrient contribution from areas that were greater than 300 meters to the river network was negligible. It was also found that the decay rate for urban lands is lower than that for other land-covers. Based on these findings, a spatial aggregation strategy in the lateral dimension of the river network was adopted and eight non-linear regression models which explicitly addressed the effects of distance-decay were designed to estimate the nutrient annual average loads. The model validation results showed that three of them can well estimate the nutrient loads. This study shows the usage of stream-lateral-dimension aggregation strategy in addressing nutrient distance-decay patterns and developing simple regression models of nutrient loading. This study also illustrates the advantages of using comprehensive spatially-explicit models to design and configure simpler regression models for improving our understanding of nutrient export from land to water.

Adding Meaning to Regression

In any data analysis we should look for ability to predict and for connections to a broader comparative context. Our equations must not predict absurdities, even under extreme circumstances, if we want to be taken seriously as scientists. Poorly done linear regression analysis often does lead to absurd predictions. Fixed exponent and exponential patterns seem more prevalent in social nature than linear patterns. Before applying regression to two variables, graph them against each other, showing the borders of the conceptually allowed space and possible logical anchor points. Transform the data until anchor points and data points do fit a straight line which does not pierce conceptual ceilings or floors. During regression, consider symmetric regression, because Ordinary Least Squares y-on-x and x-on-y differ from each other and their slopes depend on the degree of scatter. After regression, look at the numerical values of parameters and ask what they tell us in a comparative context. When considering multivariable regression, pay more than lip service to Occam's Razor.

Patterns of larval growth and chemical composition in the Amazon River prawn, Macrobrachium amazonicum

The Amazon River prawn, Macrobrachium amazonicum (Heller, 1862), is a target species for regional fisheries in Brazil and a candidate for aquaculture. Under controlled laboratory conditions (29 °C, 10‰), the larval phase of this species shows variability in the morphology and number of successive stages (mostly 9–10, occasionally 8 to > 12). In the most commonly observed developmental pathway (9 stages, taking approximately 20–22 days from hatching to the first juvenile stage), we studied patterns of larval growth in terms of total body length (TL), carapace length (CL), dry mass (W), and elemental composition (carbon, hydrogen, nitrogen; collectively CHN). At hatching, about 12% of late embryonic W, 15–18% of C and H, but only 7% of N were lost, indicating higher losses of lipids and/or carbohydrates than proteins. Significant variability was observed in the initial biomass and elemental composition of newly hatched larvae from 20 different egg batches. This may cause variation in the endotrophic potential of the early stages, as the zoea I of this species is a non-feeding stage, and also the zoea II may still utilize internal energy stores remaining from the egg yolk. Lacking or low larval feeding activity from hatching through stage II coincided with low initial growth. Concomitantly, the proportions of C and H (in % of W) as well as the C:N ratio decreased from hatching through stage IV, indicating a utilization of stored lipids. The percentage of N showed an opposite pattern, reflecting protein synthesis associated with morphogenesis. Size growth showed maximum increments per moult in the late zoeal stages (III–VI), followed by lower increments in the subsequent decapodid stages (VII–IX). This sigmoidal growth pattern may reflect ontogenetic changes in morphometric relationships. Biomass showed exponential patterns of increase from zoeal stage III throughout later larval development and in the first two juvenile stages. Furthermore, patterns of larval growth in M. amazonicum are characterized as linear relationships between larval W in stage n and that in stage n + 1 (Hiatt diagram), between larval size (CL) and biomass (W, C), and between W and either C or N. Using CHN data, we also provide estimates of the protein and lipid contents of larval biomass (ca. 38–46% and 10–12% of W, respectively). High survival, rapid development, and predictable patterns of larval growth support the assumption that M. amazonicum should be a suitable species for production in aquaculture.

Investigation of physical sensor models for modelling SPOT 3 orbits

AbstractThis paper investigates the feasibility of modelling entire image strips, instead of individual scenes, that have been acquired from the same orbital pass through bundle adjustments. The focus differs from previous researches in the following aspects: firstly, in modelling image strips when control points are available only on a small portion of the strips and, secondly, in comparing the performance of two types of physical sensor models with various sets of adjustment parameters. The models tested were based on modified collinear equations and on satellite orbit and attitude. For each model seven adjustment parameter sets were defined and checked against two SPOT 3 strips of 420 km in length. Results showed that the accuracy of orbit modelling is highly dependent on the choice of parameters to be adjusted. Models with high‐order parameters showed exponential error patterns whereas models with low‐order parameters showed linear error patterns. Among the two types of sensor models, those based on satellite orbit and attitude yielded better orbit modelling performance. In particular, the best performance was achieved by the model that adjusts attitude biases only; a nearly constant accuracy of better than 2 pixels was maintained over the whole orbital segment of 420 km. This supports the feasibility of orbit modelling.

On window size selection in the windowed Fourier ridges algorithm

The windowed Fourier ridges (WFR) algorithm can be used to extract the frequency and phase information from an exponential or carrier fringe pattern. The selection of the window size for this algorithm is investigated in this paper. For exponential phase fringe patterns, the window size does not need to be adjusted according to the signal frequency. Hence the scaling strategy of the wavelet transform is not necessary. Instead, the window size should be selected according to the balance between the linear phase approximation error and the noise level. For carrier fringe patterns, the influence of the conjugate component should also be considered. However it can be ignored when the lowest frequency of the fringe pattern is higher than 1.5/ σ ( σ is used to represent the window size).

One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death I: Cell-fate arrival times

Much experimental evidence shows that the cytoskeleton is a downstream target and effector during cell death in numerous neurodegenerative diseases, including Parkinson's, Huntington's, and Alzheimer's diseases. However, recent evidence indicates that cytoskeletal dysfunction can also trigger neuronal death, by mechanisms as yet poorly understood. This is the first of two papers in which we study a mathematical model of cytoskeleton-induced neuron death. In our model, assembly control of the neuronal cytoskeleton interacts with both cellular stress levels and cytosolic free radical concentrations to trigger neurodegeneration. This trigger mechanism is further modulated by the presence of cell interactions in the form of a diffusible toxic factor released by dying neurons. We find that, consistent with empirical observations, our model produces one-hit exponential and sigmoid patterns of cell dropout. In all cases, cell dropout is exponential-tailed and described accurately by a gamma distribution. The transition between exponential and sigmoidal is gradual, and determined by a synergetic interaction between the magnitude of fluctuations in cytoskeleton assembly control and by the degree of cell coupling. We conclude that a single mechanism involving neuron interactions and fluctuations in cytoskeleton assembly control is compatible with the experimentally observed range of neuronal attrition kinetics.

Sensory-Updated Residual Life Distributions for Components With Exponential Degradation Patterns

Research on interpreting data communicated by smart sensors and distributed sensor networks, and utilizing these data streams in making critical decisions stands to provide significant advancements across a wide range of application domains such as maintenance management. In this paper, a stochastic degradation modeling framework is developed for computing and continuously updating residual life distributions of partially degraded components. The proposed degradation methodology combines population-specific degradation characteristics with component-specific sensory data acquired through condition monitoring in order to compute and continuously update remaining life distributions of partially degraded components. Two sensory updating procedures are developed and validated using real-world vibration-based degradation information acquired from rolling element thrust bearings. The results are compared with two benchmark policies and illustrate the benefits of the sensory updated degradation models proposed in this paper. Note for Practitioners-The proposed degradation-based prognostic methodology provides a comprehensive assessment of the current and future degradation states of partially degraded components by combining population-specific degradation or reliability information with real-time sensory health monitoring data. It is specifically beneficial for cases where degradation occurs in a cumulative manner and the degradation signal can be approximated by an exponential functional form. To implement this methodology, it is necessary: 1) to identify the physical phenomena associated with the evolution of the degradation process (spalling and wear herein); 2) choose the appropriate condition monitoring technology to monitor this phenomena (accelerometers); 3) identify a characteristic pattern in the sensory information to help develop a degradation signal (exponential growth); and 4) identify a failure threshold associated with the degradation signal. The first step in implementing this prognostic methodology is to obtain prior information related to stochastic parameters f the exponential model. This may require fitting some sample degradation signals with an exponential functional form and noting the values of the exponential parameters, or using subjective prior distributions. The second step is to acquire sensory information and begin updating the prior distribution. The updating frequency will dictate which expressions are used to compute the posterior distributions. Once the posterior means, variances, and correlation are computed, the truncated CDF of the residual life can be evaluated using (10) and (11). Note that the truncation is necessary to preclude negative values of the remaining life. Practitioners can implement this methodology using a simple spreadsheet. Since the residual life distributions are skewed, it is reasonable to utilize the median as a measure of the central tendency and, hence, an alternative estimate for the expected value of the remaining life

Photodissociation dynamics of CF3I investigated by two-color femtosecond laser pulses

We report an experimental study of the multiphoton dissociation dynamics of CF3I performed on a home-built femtosecond laser pump-probe system; with time-of-flight mass spectrometer. The first repulsive A band and the 5p pi(3)7s sigma v(2) = 1 Rydberg state of CF3I were accessed by one- and two-photon transitions at 267 nm, respectively; with the latter two-photon absorption followed by a further two-photon probe transition at 401 nm to the (B) over tilde state of the parent ion. The observed signals from the CF3+ and I+ fragments show similar multi-component exponential decay patterns but the former is 4 times stronger than the latter. However; the parent CF3I+ signal was observed to evolve in a very different manner; decreasing sharply when probed in the first 289 fs following excitation and subsequently rising again after 860 fs to a constant level below that measured at negative pump-probe delay times when the pump and probe pulses exchange roles. This dip observed in the parent ion profile; is very different from that previously reported at shorter pump wavelengths of 264 nm or 265 ran, and is interpreted as the competition between two different ionization channels. One from the vibrationally excited v(2) = 1 of the irradiated Rydberg state and the other from the dissociative vibrational origin of the same electronic state which is populated by internal vibrational relaxation.