Real-time mechanoluminescence sensing of the amplitude and duration of impact stress

The present paper reports the real-time sensing of the amplitude and duration of impact stress using mechanoluminescence (ML) of the films such as ZnS:Mn and SrAl₂O₄:Eu. After the impact of a small ball from a low height onto the film, initially the elastico mechanoluminescence (EML) intensity increases with time, attains a peak value and then it decreases with time, initially at a fast rate and later on at a slow rate. The fast decay time of the EML intensity is related to the rate constant for the rise of impact stress and the slow decay time of EML is equal to the lifetime of electrons in the shallow traps lying in the normal piezoelectric region of the crystals, which get filled during the detrapping of thermally stable traps at the time of the increase of pressure. Both the peaks of EML intensity and total EML intensity increase linearly with the height through which the ball is dropped onto the films. The EML spectra are similar to the corresponding photoluminescence and electroluminescence spectra. On the basis of the localized piezoelectrically induced electron detrapping model, expressions are derived for different parameters of the impact stress-induced EML of the films, whereby a good agreement is found between the experimental and theoretical results. As the EML intensity depends on the impact stress, the impact stress can be sensed by measuring the EML intensity. Furthermore, the duration of stress is related to the time t_m corresponding to the peak of the EML intensity versus time curve; hence, the pulse duration of the impact stress can be monitored by measuring the value of time t_m.     

Gravitational radiation in ultrarelativistic collisions

Classical ultrarelativistic gravitational bremsstrahlung in particle collisions is studied in the ADD model with d extra dimensions. The main goal in this consideration concerns trans-Planckian energies. The radiation efficiency ?? ?? E _rad /E _initial is computed in terms of the Schwarzschild radius r _S (E_collision), the impact parameter b and the center-of-mass Lorentz factor ?? _cm and is found to be ?? = C _d (r _S /b)^3d+3 times ?? _cm in some d-dependent power, larger than the previous estimates by powers of ?? _cm ? 1. The cubic graviton vertex is consistently taken into account, and the approximation is reliable for impact parameters in the range r _S < b < b _c , with b _c marking (for d ?? 0) the loss of the notion of classical trajectories. It follows that gravitational bremsstrahlung leads to extreme damping in trans-Planckian collisions, and the radiation reaction should be included in the analysis of black hole production.     

Estimation of the proportion of true null hypotheses in high-dimensional data under dependence

In multiple testing, a challenging issue is to provide an accurate estimation of the proportion π₀ of true null hypotheses among the whole set of tests. Besides a biological interpretation, this parameter is involved in the control of error rates such as the False Discovery Rate. Improving its estimation can result in more powerful/less conservative methods of differential analysis. Various methods for π₀ estimation have been previously developed. Most of them rely on the assumption of independent p-values distributed according to a two-component mixture model, with a uniform distribution for null p-values. In a general factor analytic framework, the impact of dependence on the properties of the estimation procedures is first investigated and exact expressions of bias and variance are provided in case of dependent data. A more accurate factor-adjusted estimator of π₀ is finally presented, which shows large improvements with respect to the standard procedures.     

Effect of imbalance and intracluster correlation coefficient in cluster randomized trials with binary outcomes

Cluster randomization trials are increasingly popular among healthcare researchers. Intact groups (called ‘clusters’) of subjects are randomized to receive different interventions, and all subjects within a cluster receive the same intervention. In cluster randomized trials, a cluster is the unit of randomization, and a subject is the unit of analysis. Variation in cluster sizes can affect the sample size estimate or the power of the study. [Guittet, L., Ravaud, P., Giraudeau, B., 2006. Planning a cluster randomized trial with unequal cluster sizes: Practical issues involving continuous outcomes. BMC Medical Research Methodology 6 (17), 1-15] investigated the impact of an imbalance in cluster size on the power of trials with continuous outcomes through simulations. In this paper, we examine the impact of cluster size variation and intracluster correlation on the power of the study for binary outcomes through simulations. Because the sample size formula for cluster randomization trials is based on a large sample approximation, we evaluate the performance of the sample size formula with small sample sizes through simulation. Simulation study findings show that the sample size formula (m_p) accounting for unequal cluster sizes yields empirical powers closer to the nominal power than the sample size formula (m_a) for the average cluster size method. The differences in sample size estimates and empirical powers between m_a and m_p get smaller as the imbalance in cluster sizes gets smaller.     

An Extended Tree-Width Notion for Directed Graphs Related to the Computation of Permanents

It is well known that permanents of matrices of bounded tree-width are efficiently computable. Here, the tree-width of a square matrix M=(m _ij ) with entries from a field \(\mathbb{K}\) is the tree-width of the underlying graph G _M having an edge (i,j) if and only if the entry m _ij ≠0. Though G _M is directed this does not influence the tree-width definition. Thus, it does not reflect the lacking symmetry when m _ij ≠0 but m _ji =0. The latter however might have impact on the computation of the permanent. In this paper we introduce and study an extended notion of tree-width for directed graphs called triangular tree-width. We give examples where the latter parameter is bounded whereas the former is not. As main result we show that permanents of matrices of bounded triangular tree-width are efficiently computable. This result is shown to hold as well for the Hamiltonian Cycle problem.     

Simulating the impact of discrete-return lidar system and survey characteristics over young conifer and broadleaf forests

We present a model-based investigation of the effect of discrete-return lidar system and survey characteristics on the signal recorded over young forest environments. A Monte Carlo ray tracing (MCRT) model of canopy scattering was used to examine the sensitivity of model estimates of lidar-derived canopy height, h_lidar to signal triggering method, canopy structure, footprint size, sampling density and scanning angle, for broadleaf and conifer canopies of varying density. Detailed 3D models of Scots pine (Pinus sylvestris) and Downy birch (Betula pubescens) were used to simulate lidar response, with minimal assumptions about canopy structure. Use of such models allowed the impact of lidar parameters on canopy height retrieval to be tested under a range of conditions typically not possible in practice. Retrieved h_lidar was generally found to be an underestimate of ‘true’ canopy height, h_canopy, but with exceptions. Choice of signal triggering method caused h_lidar to underestimate h_canopy by ∼ 4% for birch and ∼ 7% for pine (up to 66% in extreme cases). Variations in canopy structure resulted on average in underestimation of h_canopy by 13% for birch and between 29 and 48% for pine depending on age, but with over-estimates in some cases of up to 10%. Increasing footprint diameter from 0.1 to 1 m increased retrieved h_lidar from significant underestimates of h_canopy to values indistinguishable from h_canopy. Increased sampling density led to slightly increased values of h_lidar to close to h_canopy, but not significantly. Increasing scan angle increased h_lidar by up to 8% for birch, and 19% for pine at a scan angle of 30°. The impact of scan angle was greater for conifers as a result of large variation in crown height. Results showed that interactions between physically modelled (hypothetical) within canopy returns are similar to findings made in other studies using actual lidar systems, and that these modelled returns can depend strongly on the type of canopy and the lidar acquisition characteristics, as well as interactions between these properties. Physical models of laser pulse/canopy interactions may provide additional information on pulse interactions within the canopy, but require validation and testing before they are applied to actual survey planning and logistics.     

A methodology to assess the influence of local wind conditions and building orientation on the convective heat transfer at building surfaces

Information on the statistical mean convective heat transfer coefficient (CHTC_SM) for a building surface, which represents the temporally-averaged CHTC over a long time span (e.g. the lifetime of the building), could be useful for example for the optimisation of the performance of solar collectors and ventilated photovoltaic arrays or for preservation analysis of cultural heritage sites. A methodology is proposed to estimate the CHTC_SM for a building surface, by combining local wind climate information and information on the CHTC, namely CHTC-U₁₀ correlations, where U₁₀ is the mean wind speed at a height of 10 m above the ground. This methodology is applied to a cubic building for a specific wind climate, where the CHTC-U₁₀ correlations are obtained by means of CFD simulations (CFD code Fluent 6.3, realizable k-? turbulence model). It is shown that the CHTC_SM varied significantly with the orientation of the building surface due to the rather anisotropic wind conditions, where high values are found for surfaces oriented towards the prevailing wind directions, thus for windward conditions. Moreover, the evaluation of the CHTC_SM for other wind climates clearly shows that the local wind conditions also can have a significant impact on the overall magnitude of the CHTC_SM, where differences up to a factor 4 are found in this study. Different levels of complexity for determining the CHTC_SM value are also evaluated and it is found that the required number of CFD simulations can be reduced significantly by using more simplified methods to calculate the CHTC_SM, without compromising its accuracy. The applicability of the proposed methodology for other building-related applications is also discussed, for example to assess statistical mean pressure coefficients, wind-driven ventilation rates or convective mass transfer coefficients.     

Semi-physical mean-value NOx model for diesel engine control

A semi-physical model has been developed to predict nitrogen oxide (NO_x) emissions produced by diesel engines. This model is suitable for online NO_x estimation and for model-based engine control. It is derived from a zero-dimensional thermodynamic model which was simplified by only retaining main phenomena contributing to NO_x formation. The crank angle evolution of the burned gas temperature, which has a strong impact on NO_x formation rate, is described by a semi-empirical model whose key variable is the maximum burned gas temperature. This variable presents a good correlation with the molar fraction of NO_x at the end of combustion and can be expressed as a function of the intake burned gas ratio and the start of combustion. The maximum burned gas temperature sub-model is then coupled to an averaged NO_x formation kinetic model (based on the Zeldovich mechanism) to form a mean-value model for NO_x computation. This latter model was validated using data sets recorded in two diesel engines for steady-state operating conditions as well as for several driving cycles including parametric variations of the engine calibration.     

Estimating model prediction error: Should you treat predictions as fixed or random?

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP_fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP_uncertain(X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP_uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP_uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.     

Applying rough set theory in the function group analysis for phenolic amide compounds

This research synthesized and assayed 15 phenolic amide compounds for antioxidant activity. The principle approach was based on the antioxidant activity (IC₅₀) values of various R₁-R₅ in the phenolic amide compound backbones for investigating the impact in functional groups. Through the analysis and calculation by rough set mathematics, it was determined that R₅ was responsible for the most significant impact on antioxidant activity. This finding indicated that the functional group at the para-position in the phenethylamine backbone was the most influential, followed by R₂ and R₄, indicating the critical role of the functional group at the meta-position. This result was consistent with the actual circumstance. In the future, functional groups at different positions should be synthesized to increase the number of compounds followed by integrating the mathematics model and computer toolbox to validate the accuracy and rationality.     

Cardinality Networks: a theoretical and empirical study

We introduce Cardinality Networks, a new CNF encoding of cardinality constraints. It improves upon the previously existing encodings such as the sorting networks of Eén and Sörensson (JSAT 2:1–26, 2006) in that it requires much less clauses and auxiliary variables, while arc consistency is still preserved: e.g., for a constraint x ₁?+?...?+?x _n ?≤?k, as soon as k variables among the x _i ’s become true, unit propagation sets all other x _i ’s to false. Our encoding also still admits incremental strengthening: this constraint for any smaller k is obtained without adding any new clauses, by setting a single variable to false. Here we give precise recursive definitions of the clause sets that are needed and give detailed proofs of the required properties. We demonstrate the practical impact of this new encoding by careful experiments comparing it with previous encodings on real-world instances.     

Prediction of penetration depth in a plunging water jet using soft computing approaches

The flow characteristics of the plunging water jets can be defined as volumetric air entrainment rate, bubble penetration depth, and oxygen transfer efficiency. In this study, the bubble penetration depth is evaluated based on four major parameters that describe air entrainment at the plunge point: the nozzle diameter (D _N), jet length (L _j), jet velocity (V _N), and jet impact angle (θ). This study presents artificial neural network (ANN) and genetic expression programming (GEP) model, which is an extension to genetic programming, as an alternative approach to modeling of the bubble penetration depth by plunging water jets. A new formulation for prediction of penetration depth in a plunging water jets is developed using GEP. The GEP-based formulation and ANN approach are compared with experimental results, multiple linear/nonlinear regressions, and other equations. The results have shown that the both ANN and GEP are found to be able to learn the relation between the bubble penetration depth and basic water jet properties. Additionally, sensitivity analysis is performed for ANN, and it is found that D _N is the most effective parameter on the bubble penetration depth.     

Evaluating environmental influences of zoning in urban ecosystems with remote sensing

The influence of zoning on Normalized Difference Vegetation Index (NDVI) and radiant surface temperature (T_s) measurements is investigated in the City of Indianapolis, IN, USA using data collected by the Enhanced Thematic Mapper Plus (ETM+) remote sensing system. Analysis of variance indicates statistically significant differences in mean T_s and NDVI values associated with different types of zoning. Multiple comparisons of mean T_s and NDVI values associated with specific pairings of individual zoning categories are also shown to be significantly different. An inverse relationship between T_s and NDVI was observed across the city as a whole and within all but one zoning category. A range of environmental influences on sensible heat flux and urban vegetation was detected both within and between individual zoning categories. Examples for implementing these findings in urban planning applications to find examples of high and low impact development are demonstrated.     

A delay optimal coterie on the k-dimensional folded Petersen graph

Coteries are an effective tool for enforcing mutual exclusion in distributed systems. Communication delay is an important metric to measure the performance of a coterie. The topology of the interconnection network in a distributed system also has an impact on its performance. The k-dimensional folded Petersen graph, a graph with 10^k nodes and diameter 2k, qualifies as a good network topology for large distributed systems. In this paper, we present a delay optimal coterie on the k-dimensional folded Petersen graph, FP_k. For any positive integer k, the coterie has message complexity 4^k and delay k. Moreover, this coterie is not vote-assignable.     

Spectral unmixing model to assess land cover fractions in Mongolian steppe regions

The land cover fractions (LCFs) and spectral reflectance of photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and bare soil were measured at 58 sites in semi-arid and arid regions of Mongolia in the summers of 2005 and 2006. These data sets allowed a detailed assessment of the impact of measurement geometry as represented by the solar zenith angle θ_s, sensor view zenith angle θ_v and azimuth view angle ? in the estimation of LCF values by means of the spectral unmixing model (SUM). The bidirectional distribution function (BRDF) was fitted to the reflectance data and then used to produce reflectance at various measurement geometries. LCFs from these reflectance data for a given combination of θ_s, θ_v, and ? were compared with visually determined LCFs. It was found that θ_s in the range of 30-45° produced a better agreement of LCFs. For θ_v, the agreement is not very sensitive to the choice of angle for the range 30-70°, although θ_v = 50° showed a slightly better performance. The azimuth view angle does not have strong influences to the LCF estimation, except for the case of ? = 180° (view toward the sun), which does not allow precise fitting of BRDF function over a tall vegetation site. Overall, this study verified the results of earlier studies obtained mostly for the American continents that SUM is capable of producing LCF estimates accurately and also found that its accuracy was, in general, much better than that by the more traditional approach of the supervised classification method (SCM) applied to images of a digital camera.     

Monitoring root-zone soil moisture through the assimilation of a thermal remote sensing-based soil moisture proxy into a water balance model

Two types of Soil Vegetation Atmosphere Transfer (SVAT) modeling approaches can be applied to monitor root-zone soil moisture in agricultural landscapes. Water and Energy Balance (WEB) SVAT modeling is based on forcing a prognostic root-zone water balance model with observed rainfall and predicted evapotranspiration. In contrast, thermal Remote Sensing (RS) observations of surface radiometric temperature (T_R) are integrated into purely diagnostic RS-SVAT models to predict the onset of vegetation water stress. While RS-SVAT models do not explicitly monitor soil moisture, they can be used in the calculation of thermal-based proxy variables for the availability of soil water in the root zone. Using four growing seasons (2001 to 2004) of profile soil moisture, micro-meteorology, and surface radiometric temperature measurements at the United States Department of Agriculture (USDA) Optimizing Production Inputs for Economic and Environmental Enhancements (OPE³) study site in Beltsville, MD, prospects for improving WEB-SVAT root-zone soil water predictions via the assimilation of diagnostic RS-SVAT soil moisture proxy information are examined. Results illustrate the potential advantages of such an assimilation approach relative to the competing approach of directly assimilating T_R measurements. Since T_R measurements used in the analysis are tower-based (and not obtained from a remote platform), a sensitivity analysis demonstrates the potential impact of remote sensing limitations on the value of the RS-SVAT proxy. Overall, results support a potential role for RS-SVAT modeling strategies in improving WEB-SVAT model characterization of root-zone soil moisture.     

Analysis of the impact of space vector modulation techniques on the operation of ultrahigh speed induction machines

The paper investigates the impact of different space vector modulation (SVM) techniques on the operation of ultrahigh speed induction machines (USIMs), where the m_f frequency ratio is low owing to the necessarily high fundamental frequency f₁. Three different sampling techniques, the Regular Sampled, Naturally Sampled and the Oversampled are studied by simulation. It is found that the SVM is proned to generate DC current in the stator windings. Furthermore subharmonic flux and current components with considerable amplitudes can also be generated in USIM. In the paper it is revealed that both the DC and the subharmonic components could lead to extremely large additional losses in the USIM enhanced by its special parameters.     

PM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region

The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM₁₀ over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM₁₀ observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (r_SEV∼ 0.7, r_MOD∼ 0.6) with regard to daily averaged PM₁₀. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM₁₀ assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.     

Sports ball aerodynamics: A numerical study of the erratic motion of soccer balls

The application of the commercial CFD code, FLUENT, to sports ball aerodynamics was assessed and a validated 3D analysis technique was established for balls that have been scanned with a 3D laser scanner or drawn in CAD. The technique was used to examine the effects of surface geometry on the aerodynamic behaviour of soccer balls by comparing the flow around different balls and predicting the aerodynamic force coefficients. The validation process included performing CFD studies on 3D smooth spheres and various soccer balls, and comparing the results to wind tunnel tests and flow visualisation. The CFD technique used a surface wrapping meshing method and the Reynolds Averaged Navier-Stokes approach with the realizable k-ε turbulence model, which was found to be able to predict the drag, lift and side force coefficients (C_D, C_L and C_S) reliably, to compare the wake behaviour, and to give good pressure distributions near the stagnation point. The main limitations of the technique with the available computational resources were its inability to accurately predict boundary layer transition or growth, but despite this, several conclusions could be drawn regarding soccer ball aerodynamics. C_D was not significantly different between balls. C_L and C_S were found to be significantly affected by the orientation of the ball relative to its direction of travel, meaning that balls kicked with low amounts of spin could experience quasi-steady lift and side forces and move erratically from side-to-side or up and down through the air. For different balls, C_D, C_L and C_S were predicted and their variation with orientation entered into a modified trajectory simulation program. The erratic nature of this type of kick was found to vary with details of the surface geometry including seam size, panel symmetry, number, frequency and pattern, as well as the velocity and spin applied to the ball by the player. Exploitation of this phenomenon by players and ball designers could have a significant impact on the game.