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At least 523 records · Page 29

Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution

This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Flexible and scalable methods for quantifying stochastic variability in the era of massive time-domain astronomical data sets

We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placing them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.

79 ASTRONOMY AND ASTROPHYSICS↗

Energy density functional analysis of shape coexistence in {sup 44}S

The structure of low-energy collective states in the neutron-rich nucleus {sup 44}S is analyzed using a microscopic collective Hamiltonian model based on energy density functionals (EDFs). The calculated triaxial energy map, low-energy spectrum and corresponding probability distributions indicate a coexistence of prolate and oblate shapes in this nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Copula cosmology: Constructing a likelihood function

To estimate cosmological parameters from a given data set, we need to construct a likelihood function, which sometimes has a complicated functional form. We introduce the copula, a mathematical tool to construct an arbitrary multivariate distribution function from one-dimensional marginal distribution functions with any given dependence structure. It is shown that a likelihood function constructed by the so-called Gaussian copula can reproduce very well the n-dimensional probability distribution of the cosmic shear power spectrum obtained from a large number of ray-tracing simulations. This suggests that the Copula likelihood will be a powerful tool for future weak lensing analyses, instead of the conventional multivariate Gaussian likelihood.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sensitivity Analysis of Passive Heat Removal Capability of FHR Based on Efficient Surrogate Model and GenFlow

Code Scaling, Applicability and Uncertainty Evaluation Methodology (CSAU) is used for quantifying reactor safety margins and works as an alternative method for licensing nuclear power plant. In the framework of CSAU, sensitivity and uncertainty analysis (SA and UA) should be performed. However, for large-scale complicated thermal hydraulics analysis simulated by code (e.g. RELAP5, CFD and subchannel analysis, the sensitivity and uncertainty analysis is really time-consuming. Furthermore, sometimes it is not feasible to perform SA and UA. Specifically, the computation time for Monte Carlo sampling or advanced LHS sampling can be neglected, but the computation time for thermal hydraulics code makes up main part of time during SA and UA process. In order to accelerate the speed of SA and UA, thermal hydraulics code can be improved based on advanced mathematic algorithm or using parallel method. However, the development for new mathematic method needs long time and strict verification and validation process is needed for a new code, which usually takes a couple of years or even longer time to have an approved code that can be used in nuclear industry. An alternative way to improve the speed of SA and UA is using surrogate model. The surrogate model is derived from the input as well as output data of the original code, assuming the code as a black box. The most common method is using response surface method (RSM) as a surrogate for the code, the input parameters are then sampled from their assumed distribution and the corresponding value of the response surface function is calculated. However, a couple of input parameters need hundreds or even thousands of original code calculations. The large number of runs is an obvious disadvantage of this method. Besides, the second disadvantage is an appropriate response surface function must be selected (e.g. quadratic, cubic, quartic, with or without cross product terms, or using a non-polynomial form) to avoid the overfit and underfit problem. This process is time consuming and expensive. Polynomial chaos expansion method is a reasonably fast and attractive alternative, stochastic model. The chaos expansion provides an efficient high-order method of including non-linear effects in stochastic analysis. Usually, the information about the model parameters and their probability distribution is limited and the dependence between them is not known. However, if arbitrary polynomial chaos is used, instead of assuming probability distribution for input parameters which may introduces additional subjectivity into the analysis, the available information can directly and most purely be used in stochastic analysis based on arbitrary data distribution. Thus, it is not necessary to know the exact probability density functions to perform SA and UA based on arbitrary polynomial chaos (aPC). The aPC has been applied for uncertainty quantification in many fields (e.g. in solid mechanics, fluid flows, thermal sciences), and become widely used in nuclear industry recently. Mk1 PB-FHR is a small modular fluoride-salt-cooled, high-temperature reactors (FHRs) that is a concept design by University of California, Berkeley (UCB). It has inherently safe features like natural-circulation-driven systems (e.g. direct reactor auxiliary cooling system (DRACS)) to passively remove decay heat from the reactor core during design basis and beyond design. It is necessary to perform SA and UA, since the licensing process of this new kind of reactor is under way and there are many design parameters that have not been fixed. Current nuclear commercial codes, such as RELAP5, have mainly been developed for light water reactors, which require the use of comprehensive two-phase flow models. This capability is not required to simulate single-phase flow phenomena in FHRs, whose baseline coolant, flibe, remains liquid up to 1430 deg. C at atmospheric pressure. The FHR advanced natural circulation analysis (FANCY) code has been developed specifically for FHR technology modeling and validation work has been performed by using CIET data in UCB. The code has been renamed General Flow (GenFlow) because it has been further developed to have the capability to model complicated pipework system based on object-oriented concept for user friendly purpose. Besides, it can be used to simulate both the force circulation as well as natural circulation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

COSMOLOGICAL EVOLUTION OF ATOMIC GAS AND IMPLICATIONS FOR 21 cm H I ABSORPTION

Galaxy disks are shown to contain a significant population of atomic clouds of 100 pc linear size which are self-opaque in the 21 cm transition. These objects have H I column densities as high as 10{sup 23} cm{sup -2} and contribute to a global opacity correction factor of 1.34 {+-} 0.05 that applies to the integrated 21 cm emission to obtain a total H I mass estimate. High-resolution, opacity-corrected images of the nearest external galaxies have been used to form a robust redshift zero distribution function of H I, f(N{sub HI}, X, z = 0), the probability of encountering a specific H I column density along random lines of sight per unit comoving distance. This is contrasted with previously published determinations of f(N{sub HI}, X) at z = 1 and 3. A systematic decline of moderate column density (18 < log(N{sub H)} < 21) H I is observed with decreasing redshift that corresponds to a decline in surface area of such gas by a factor of five since z = 3. The number of equivalent Damped Lyman Alpha absorbers (log(N{sub HI})>20.3) has also declined systematically over this redshift interval by a similar amount, while the cosmological mass density in such systems has declined by only a factor of two to its current, opacity-corrected value of {Omega}{sup DLA}{sub HI}(z = 0) = 5.4 {+-} 0.9 Multiplication-Sign 10{sup -4}. We utilize the tight but strongly nonlinear dependence of 21 cm absorption opacity on column density at z = 0 to transform our high-resolution H I images into ones of 21 cm absorption opacity. These images are used to calculate distribution and pathlength functions of integrated 21 cm opacity. We suggest that that this z = 0 calibration may also apply at higher redshift. In this case, the incidence of deep 21 cm absorption systems is predicted to show very little evolution with redshift, while that of faint absorbers should decline by a factor of 5 between z = 3 and the present. We explicitly consider the effects of H I absorption against background sources that are extended relative to the 100 pc intervening absorber size scale. Extended background sources result in dramatically altered distribution and pathlength functions which are insensitive to the predicted redshift evolution. Future surveys of 21 cm absorption will require very high angular resolution, of about 15 mas, for their unambiguous interpretation.

79 ASTRONOMY AND ASTROPHYSICS↗

Large-eddy simulations of wind-farm wake characteristics associated with a low-level jet

Here, we performed a suite of flow simulations for a 12-wind-turbine array with varying inflow conditions and lateral spacings, and compared the impacts of the flow on velocity deficit and wake recovery. We imposed both laminar inflow and turbulent inflows, which contain turbulence for the Ekman layer and a low-level jet (LLJ) in the stable boundary layer. To solve the flow through the wind turbines and their wakes, we used a large-eddy simulation technique with an actuator-line method. We compared the time series for the velocity deficit at the first and rear columns to observe the temporal change in velocity deficit for the entire wind farm. The velocity deficit at the first column for LLJ inflow was similar to that for laminar inflow. However, the magnitude of velocity deficit at the rear columns for the case with LLJ inflow was 11.9% greater because of strong wake recovery, which was enhanced by the vertical flux of kinetic energy associated with the LLJ. In order to observe the spatial transition and characteristics of wake recovery, we performed statistical analyses of the velocity at different locations for both the laminar and LLJ inflows. These studies indicated that strong wake recovery was present, and a kurtosis analysis showed that the probability density function for the streamwise velocity followed a Gaussian distribution. In a quadrant analysis of the Reynolds stress, we found that the ejection and sweep motions for the LLJ inflow case were greater than those for the laminar inflow case.

17 WIND ENERGY↗

Hypofractionation Results in Reduced Tumor Cell Kill Compared to Conventional Fractionation for Tumors With Regions of Hypoxia

Purpose: Tumor hypoxia has been observed in many human cancers and is associated with treatment failure in radiation therapy. The purpose of this study is to quantify the effect of different radiation fractionation schemes on tumor cell killing, assuming a realistic distribution of tumor oxygenation. Methods and Materials: A probability density function for the partial pressure of oxygen in a tumor cell population is quantified as a function of radial distance from the capillary wall. Corresponding hypoxia reduction factors for cell killing are determined. The surviving fraction of a tumor consisting of maximally resistant cells, cells at intermediate levels of hypoxia, and normoxic cells is calculated as a function of dose per fraction for an equivalent tumor biological effective dose under normoxic conditions. Results: Increasing hypoxia as a function of distance from blood vessels results in a decrease in tumor cell killing for a typical radiotherapy fractionation scheme by a factor of 10{sup 5} over a distance of 130 {mu}m. For head-and-neck cancer and prostate cancer, the fraction of tumor clonogens killed over a full treatment course decreases by up to a factor of {approx}10{sup 3} as the dose per fraction is increased from 2 to 24 Gy and from 2 to 18 Gy, respectively. Conclusions: Hypofractionation of a radiotherapy regimen can result in a significant decrease in tumor cell killing compared to standard fractionation as a result of tumor hypoxia. There is a potential for large errors when calculating alternate fractionations using formalisms that do not account for tumor hypoxia.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Quantitative x ray phase contrast imaging of oblique shock wave–interface interactions

Oblique shock wave–interface interactions of gases and liquids have been extensively studied in shock tubes using optical methods to measure equation-of-state (EOS) parameters. However, this is difficult with solids due to their opaqueness to visible light. X ray phase contrast imaging (XPCI) has the penetrative strength to probe solids while still being sensitive to mass density and enhancing the visibility of material boundaries. We investigate the accuracy and repeatability of measuring the mean value of the average mass density (areal density divided by thickness) over region S (B S ) and flow deflection angle (θ) from XPCI images of a sample. To that end, a Hough transform-based method for measuring θ is developed. To measure B S , the XPCI image intensity probability density function (PDF) is modeled accounting for the spatial distribution of x ray energy, scintillator response, and pulse-to-pulse variation in the x ray intensity. In addition, a Monte Carlo-based algorithm for computing the B S PDF is developed. Both methods are validated on an impact-generated oblique shock wave interacting at a solid polymer-to-polymer interface. Furthermore this is accomplished through a comparison to hydrodynamic simulations using well-established EOS. Under the modeling framework for the XPCI image intensity, B S is computed with an accuracy of < 0.1% and precision of 3%–5%, while θ has an uncertainty of 0.2°, respectively. This shows that the XPCI-based model that is developed here could be an invaluable tool for high-fidelity testing of hydrodynamic models in shock polar configurations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spiky electric and magnetic field structures in flux rope experiments

Magnetic flux ropes are structures that are common in the corona of the sun and presumably all stars. They can be thought of as the building blocks of solar structures. They have been observed in Earth’s magnetotail and near Mars and Venus. When multiple flux ropes are present magnetic field line reconnection, which converts magnetic energy to other forms, can occur when they collide. The structure of multiple magnetic ropes, the interactions between multiple ropes, and their topological properties such as helicity and writhing have been studied theoretically and in laboratory experiments. In this paper, we report on spiky potential and magnetic fields associated with the ropes. We show that the potential structures are chaotic for a range of their temporal half-widths and the probability density function (PDF) of their widths resembles the statistical distribution of crumpled paper. The spatial structure of the magnetic spikes is revealed using a correlation counting method. Computer simulation suggests that the potential structures are the nonlinear end result of an instability involving relative drift between ions and electrons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Reactivity of heterogeneous surfaces: Modeling precursor–surface interaction using absorbing Markov chains

Heterogeneous reactive surfaces involving a spatial distribution of reactive sites are ubiquitous in thin film growth, from defect nucleation to step flow growth. In this work, the interaction of gas phase species with heterogeneous reactive surfaces was explored using a model combining absorbing Markov chains and local balance equations. Through this model, single particle statistics can be extracted of the adsorption-diffusion-desorption/reaction process even beyond the transport-limited regime, where the surface coverage of adsorbates, and hence adsorbate-adsorbate interaction, is not negligible, and local rates can be connected with macroscopic quantities, such as the sticking probability and desorption rates. In the transport-limited regime, a similarity law was identified for the sticking probability for both step flow growth and nucleation on randomly distributed reactive sites in which the sticking probability is a function of the product of the local diffusion and reaction probabilities. Lastly, the model can be applied to extract local reactivity maps providing the probability that a particle adsorbing on a given site reacts with the surface. This allows one to explore the development of capture zones and the impact of site-blocking and desorption on the local sticking probabilities.

36 MATERIALS SCIENCE↗

Revealing minijet dynamics via centrality dependence of double parton interactions in proton–nucleus collisions

One of the main challenges hampering an accurate measurement of the double parton scattering (DPS) cross sections is the difficulty in separating the DPS from the leading twist (LT) contributions. We argue that such a separation can be achieved, and cross section of DPS measured, in proton–nucleus scattering by exploiting the different centrality dependence of DPS and LT processes. We developed a Monte Carlo implementation of the DPS processes which includes realistic nucleon–nucleon (NN) correlations in nuclei, an accurate description of transverse geometry of both hard and soft NN collisions as well as fluctuations of the strength of interaction of nucleon with nucleus (color fluctuation effects). Our method allows the calculation of probability distributions of single and double dijet events as a function of centrality, also distinguishing double hard scatterings originating from a single target nucleon and from two different nucleons. We present numerical results for the rate of DPS as a function of centrality, following the model developed by the ATLAS collaboration which relates the distribution over the number of wounded nucleons to the distribution over the sum of transverse energies of hadrons produced at large negative (along the nucleus direction) rapidities, which is experimentally measurable. We suggest a new quantity which allows to test the geometry of DPS and we argue that it is a universal function of centrality for different DPS processes. This quantity can be tested by analyzing existing LHC data. The method developed in this work can be extended to the search for triple parton interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tunable Geometries in Sparse Clifford Circuits

We investigate the emergence of different effective geometries in stochastic Clifford circuits with sparse coupling. By changing the probability distribution for choosing two-site gates as a function of distance, we generate sparse interactions that either decay or grow with distance as a function of a single tunable parameter. Tuning this parameter reveals three distinct regimes of geometry for the spreading of correlations and growth of entanglement in the system. We observe linear geometry for short-range interactions, treelike geometry on a sparse coupling graph for long-range interactions, and an intermediate fast scrambling regime at the crossover point between the linear and treelike geometries. This transition in geometry is revealed in calculations of the subsystem entanglement entropy and tripartite mutual information. We also study emergent lightcones that govern these effective geometries by teleporting a single qubit of information from an input qubit to an output qubit. These tools help to analyze distinct geometries arising in dynamics and correlation spreading in quantum many-body systems.

97 MATHEMATICS AND COMPUTING↗

A COUPLED 2 × 2D BABCOCK–LEIGHTON SOLAR DYNAMO MODEL. II. REFERENCE DYNAMO SOLUTIONS

In this paper we complete the presentation of a new hybrid 2 × 2D flux transport dynamo (FTD) model of the solar cycle based on the Babcock–Leighton mechanism of poloidal magnetic field regeneration via the surface decay of bipolar magnetic regions (BMRs). This hybrid model is constructed by allowing the surface flux transport (SFT) simulation described in Lemerle et al. to provide the poloidal source term to an axisymmetric FTD simulation defined in a meridional plane, which in turn generates the BMRs required by the SFT. A key aspect of this coupling is the definition of an emergence function describing the probability of BMR emergence as a function of the spatial distribution of the internal axisymmetric magnetic field. We use a genetic algorithm to calibrate this function, together with other model parameters, against observed cycle 21 emergence data. We present a reference dynamo solution reproducing many solar cycle characteristics, including good hemispheric coupling, phase relationship between the surface dipole and the BMR-generating internal field, and correlation between dipole strength at cycle maximum and peak amplitude of the next cycle. The saturation of the cycle amplitude takes place through the quenching of the BMR tilt as a function of the internal field. The observed statistical scatter about the mean BMR tilt, built into the model, acts as a source of stochasticity which dominates amplitude fluctuations. The model thus can produce Dalton-like epochs of strongly suppressed cycle amplitude lasting a few cycles and can even shut off entirely following an unfavorable sequence of emergence events.

79 ASTRONOMY AND ASTROPHYSICS↗

Open EFTs, IR effects & late-time resummations: systematic corrections in stochastic inflation

Though simple inflationary models describe the CMB well, their corrections are often plagued by infrared effects that obstruct a reliable calculation of late-time behaviour. Here we adapt to cosmology tools designed to address similar issues in other physical systems with the goal of making reliable late-time inflationary predictions. The main such tool is Open EFTs which reduce in the inflationary case to Stochastic Inflation plus calculable corrections. We apply this to a simple inflationary model that is complicated enough to have dangerous IR behaviour yet simple enough to allow the inference of late-time behaviour. We find corrections to standard Stochastic Inflationary predictions for the noise and drift, and we find these corrections ensure the IR finiteness of both these quantities. The late-time probability distribution, P(Φ), for super-Hubble field fluctuations are obtained as functions of the noise and drift and so these too are IR finite. We compare our results to other methods (such as large-N models) and find they agree when these models are reliable. In all cases we can explore in detail we find IR secular effects describe the slow accumulation of small perturbations to give a big effect: a significant distortion of the late-time probability distribution for the field. But the energy density associated with this is only of order H 4 at late times and so does not generate a dramatic gravitational back-reaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Characterizing Peatland Microtopography Using Gradient and Microform-Based Approaches

Abstract Peatlands represent an important component of the global carbon cycle, storing 180–621 Gt of carbon (C). Small-scale spatial variations in elevation, frequently referred to as microtopography, influence ecological processes associated with the peatland C cycle, including Sphagnum photosynthesis and methane flux. Microtopography can be characterized with measures of topographic variability and by using conceptual classes (microforms) linked to function: most commonly hummocks and hollows. However, the criteria used to define these conceptual classes are often poorly described, if at all, and vary between studies. Such inconsistencies compel development of explicit quantitative methods to classify microforms. Furthermore, gradient-based characterizations that describe spatial variability without the use of microforms are lacking in the literature. Therefore, the objectives of this study were to (1) calculate peatland microtopographical elevation gradients and measures of spatial variability, (2) develop three microform classification methods intended for specific purposes, and (3) evaluate and contrast classification methods. Our results suggest that at spatial scales much larger than microforms, elevation distributions are unimodal and are well approximated with parametric probability density functions. Results from classifications were variable between methods and years and exhibited significant differences in mean hollow areal coverages of a raised ombrotrophic bog. Our results suggest that the conceptualization and classification of microforms can significantly influence microtopographic structural metrics. The three explicit methods for microform classification described here may be used and built upon for future applications.

54 ENVIRONMENTAL SCIENCES↗

Representation of Arctic Mixed-Phase clouds and the Wegener-Bergeron-Findeisen Process in Climate Models: Perspectives from a Cloud-Resolving Study

Two types of Arctic mixed-phase clouds observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional cloud-resolving model (CRM) with size-resolved cloud microphysics. The modeled cloud properties agree reasonably well with aircraft measurements and surface-based retrievals. Cloud properties such as the probability density function (PDF) of vertical velocity (w), cloud liquid and ice, the regime of ice growth at the expense of liquid water (i.e., Wegener-Bergeron-Findeisen (WBF) process), and the inherent relationships among cloud properties/processes in the mixed-phase layers are examined to gain insights for improving the representation of the mixed-phase processes in General Circulation Models (GCMs). We find that, the WBF process only occurs in about 50% of the mixed-phase regime with the vast majority occurring in the downdrafts. In updrafts both liquid and ice grow simultaneously. But in GCMs, it is not necessary to treat the WBF process at the subgrid scale. Our CRM results produce a w distribution well represented by a Gaussian normal function, validating, at least for arctic clouds, the subgrid treatment used in GCMs. Our CRM results also support the assumption frequently used in GCMs that mixed phase clouds maintain water vapor very near liquid saturation. A Gamma function with a fixed variance does not accurately represent the subgrid variability of cloud liquid. The PDFs of cloud liquid and cloud ice can be fitted with Gamma functions, and a normal function can be used for total water, but the variance should not be fixed. The relationship between the ice depositional growth rate and cloud ice strongly depends on the capacitance of ice particles. The assumption for the capacitance of ice particles (e.g., 1.0 for spheres) used in GCMs could lead to a large deviation in ice depositional growth. At large sales, the maximum overlap assumption looks appropriate.

54 ENVIRONMENTAL SCIENCES↗

SU-E-T-520: Four-Dimensional Dose Calculation Algorithm Considering Variations in Dose Distribution Induced by Sinusoidal One-Dimensional Motion Patterns

Purpose: To investigate quantitatively the variations in dose-distributions induced by motion by measurements and modeling. A four-dimensional (4D) motion model of dose distributions that accounts for different motion parameters was developed. Methods: Variations in dose distributions induced by sinusoidal phantom motion were measured using a multiple-diode-array-detector (MapCheck2). MapCheck2 was mounted on a mobile platform that moves with adjustable calibrated motion patterns in the superior-inferior direction. Various plans including open and intensity-modulated fields were used to irradiate MapCheck2. A motion model was developed to predict spatial and temporal variations in the dose-distributions and dependence on the motion parameters using pencil-beam spread-out superposition function. This model used the superposition of pencil-beams weighted with a probability function extracted from the motion trajectory. The model was verified with measured dose-distributions obtained from MapCheck2. Results: Dose-distribution varied considerably with motion where in the regions between isocenter and 50% isodose-line, dose decreased with increase of the motion amplitude. Dose levels increased with increase in the motion amplitude in the region beyond 50% isodose-line. When the range of motion (ROM=twice amplitude) was smaller than the field length both central axis dose and the 50% isodose-line did not change with variation of motion amplitude and remained equal to the dose of stationary phantom. As ROM became larger than the field length, the dose level decreased at central axis dose and 50% isodose-line. Motion frequency and phase did not affect the dose distributions which were delivered over an extended time longer than few motion cycles, however, they played an important role for doses delivered with high-dose-rates within one motion cycle . Conclusion: A 4D-dose motion model was developed to predict and correct variations in dose distributions induced by one-dimensional sinusoidal motion. This model was verified with measured dose-distributions and can be expanded to consider complicated patient motion patterns.

07 ISOTOPE AND RADIATION SOURCES↗