scholarly journals Prediction of Wide Range Two-Dimensional Refractivity Using an IDW Interpolation Method from High-Altitude Refractivity Data of Multiple Meteorological Observatories

2021 ◽  
Vol 11 (4) ◽  
pp. 1431
Author(s):  
Sungsik Wang ◽  
Tae Heung Lim ◽  
Kyoungsoo Oh ◽  
Chulhun Seo ◽  
Hosung Choo
Keyword(s):  
High Altitude ◽  
Korean Peninsula ◽  
Interpolation Method ◽  
Atmospheric Condition ◽  
Propagation Path ◽  
Two Dimensional ◽  
Data Set ◽  
Wide Range ◽  
Atmospheric Data ◽  
Terrain Surface

This article proposes a method for the prediction of wide range two-dimensional refractivity for synthetic aperture radar (SAR) applications, using an inverse distance weighted (IDW) interpolation of high-altitude radio refractivity data from multiple meteorological observatories. The radio refractivity is extracted from an atmospheric data set of twenty meteorological observatories around the Korean Peninsula along a given altitude. Then, from the sparse refractive data, the two-dimensional regional radio refractivity of the entire Korean Peninsula is derived using the IDW interpolation, in consideration of the curvature of the Earth. The refractivities of the four seasons in 2019 are derived at the locations of seven meteorological observatories within the Korean Peninsula, using the refractivity data from the other nineteen observatories. The atmospheric refractivities on 15 February 2019 are then evaluated across the entire Korean Peninsula, using the atmospheric data collected from the twenty meteorological observatories. We found that the proposed IDW interpolation has the lowest average, the lowest average root-mean-square error (RMSE) of ∇M (gradient of M), and more continuous results than other methods. To compare the resulting IDW refractivity interpolation for airborne SAR applications, all the propagation path losses across Pohang and Heuksando are obtained using the standard atmospheric condition of ∇M = 118 and the observation-based interpolated atmospheric conditions on 15 February 2019. On the terrain surface ranging from 90 km to 190 km, the average path losses in the standard and derived conditions are 179.7 dB and 182.1 dB, respectively. Finally, based on the air-to-ground scenario in the SAR application, two-dimensional illuminated field intensities on the terrain surface are illustrated.

scholarly journals Atmospheric condition identification in multivariate data through a metric for total variation

2020 ◽  
Vol 13 (2) ◽  
pp. 1019-1032 ◽  
Author(s):  
Nicholas Hamilton
Keyword(s):  
Total Variation ◽  
Model Validation ◽  
Multivariate Data ◽  
Atmospheric Condition ◽  
Plant Design ◽  
Atmospheric Conditions ◽  
Real Time Control ◽  
Data Set ◽  
Atmospheric Data ◽  
Stationary Conditions

Abstract. Identification of atmospheric conditions within a multivariable atmospheric data set is a necessary step in the validation of emerging and existing high-fidelity models used to simulate wind plant flows and operation. Atmospheric conditions relevant for wind energy research include stationary conditions, given the need for well-converged statistics for model validation, as well as conditions observed less frequently, such as extreme atmospheric events, which are used in wind turbine and wind plant design. Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of atmospheric conditions. Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation set the stage for more advanced model validation and the development of real-time control and operational strategies. The current work explores a single metric for variation in a multivariate data sample that quantifies variability within each channel as well as covariance between channels. The total variation is used to identify conditions of interest that conform to desired objective functions, such as stationary conditions, ramps or waves of wind speed, and changes in wind direction. Total variation is somewhat sensitive to the presence of outliers in the input data, and the method is best complemented by quality-control procedures to ensure reliable results. The direct detection and classification of events or conditions of interest within atmospheric data sets is vital to developing our understanding of wind plant response and to the formulation of forecasting and control models.

Two-Dimensional Stress-Strain Relationship for Canine Pericardium

1990 ◽  
Vol 112 (2) ◽  
pp. 153-159 ◽  
Author(s):  
Hwa Soon Choi ◽  
R. P. Vito
Keyword(s):  
Constitutive Model ◽  
Lateral Displacement ◽  
A Priori ◽  
Lateral Force ◽  
Two Dimensional ◽  
Data Set ◽  
Material Constants ◽  
Wide Range ◽  
Strain Relationship

Two-dimensional pseudoelastic mechanical properties of the canine pericardium were investigated in vitro. The pericardium was assumed to be orthotropic. The material symmetry axis was determined a priori and aligned with the stretching axis. Various biaxial stretching tests were then performed and a set of data covering a wide range of strains was constructed. This complete data set was fitted to a new exponential type constitutive model, and a set of true material constants was determined for each specimen. Using the constitutive model and the true material constants, the results from constant lateral force tests and constant lateral displacement tests were predicted and compared with experiment.

Arrival-angle effects on two-receiver measurements of phase velocity

2019 ◽  
Vol 220 (3) ◽  
pp. 1838-1844
Author(s):  
Fabrizio Magrini ◽  
Giovanni Diaferia ◽  
Lapo Boschi ◽  
Fabio Cammarano
Keyword(s):  
Ambient Noise ◽  
Western Mediterranean ◽  
Propagation Path ◽  
Data Set ◽  
Arrival Angle ◽  
Phase Velocities ◽  
Angle Correction ◽  
Wide Range ◽  
Cross Correlations ◽  
Teleseismic Events

SUMMARY We compile a data set of Rayleigh-wave phase velocities between pairs of stations, based on teleseismic events located on the same great circle as the two stations. We validate our observations against dispersion estimates based on ambient-noise cross correlations at the same station pairs. Discrepancies between the results of the two methods can in principle be explained by deviations in the wave propagation path between earthquake and receivers, due to lateral heterogeneity in the Earth’s structure, but the latter effect has, so far, not been precisely quantified nor corrected for. We implement an algorithm to measure the arrival angle of earthquake-generated surface waves and correct the dispersion measurements accordingly. Application to a data set from the Central-Western Mediterranean shows that the arrival-angle correction almost entirely accounts for the discrepancy in question, decreasing significantly the velocity bias for a wide range of periods.

scholarly journals Novel approaches for large-scale two-dimensional hydrodynamic modelling of rivers

2018 ◽  
Vol 40 ◽  
pp. 05040
Author(s):  
Mohamed F.M. Yossef ◽  
J. S. de Jong ◽  
A. Spruyt ◽  
M. Scholten
Keyword(s):  
Large Scale ◽  
Scale Model ◽  
Calibration Data ◽  
Hydrodynamic Modelling ◽  
Two Dimensional ◽  
Data Set ◽  
Wide Range ◽  
Recent Developments ◽  
Model Setup ◽  
Using Data

For decades, the decision-making process for water management in the Netherlands makes full utilisation of state of the art models. For rivers, two-dimensional hydrodynamic models are considered essential for a wide range of questions. Every five years, there is a major model revision that includes software updates, improved physical processes, new modelling strategy, and a new calibration. 2017 marked the setup and calibration of the first river model in the sixth generation of these models. In this paper, we discuss the most recent developments in two-dimensional hydrodynamic modelling of rivers. We give an overview of the process followed to agree on the functional design of the model and address the use of the recently developed Delft3D Flexible Mesh suite. We address, in some details: i) a mesh independent approach for model setup; ii) the utilisation of a new calibration technique, which is automated using data assimilation and includes spatial and discharge dependencies; and iii) the use of a novel operational module to control hydraulic structures. The first river model within the 6th generation of models is that of the Meuse River, where the new approaches are being successfully applied. In conclusion: the mesh independent modelling approach offers great flexibility and facilitates that the same data set can be used for multiple versions of the model (e.g. different grid resolution; or different model extent). The automated calibration approach makes it possible to utilise a comprehensive calibration data set for a large-scale model in a reproducible way. The increased complexity of modelling has become possible over the last decade due to the availability of large datasets and increased computational power. This paper is particularly relevant for modellers and decision makers alike.

Aromatic Volatile Composition of Celery and Celeriac Cultivars

HortScience ◽  
1990 ◽  
Vol 25 (5) ◽  
pp. 556-559 ◽  
Author(s):  
Fredy Van Wassenhove ◽  
Patrick Dirinck ◽  
Georges Vulsteke ◽  
Niceas Schamp
Keyword(s):  
Volatile Compounds ◽  
Chromatographic Method ◽  
Apium Graveolens ◽  
Volatile Components ◽  
Two Dimensional ◽  
Qualitative Composition ◽  
Volatile Composition ◽  
Wide Range ◽  
Gas Chromatographic Method ◽  
Identification And Quantification

A two-dimensional capillary gas chromatographic method was developed to separate and quantify aromatic volatiles of celery in one analysis. The isolation, identification, and quantification of the volatile compounds of four cultivars of blanching celery (Apium graveolens L. var. dulce) and six cultivars of celeriac (Apium graveolens L. var. rapaceum) are described. The qualitative composition of Likens-Nickerson extracts of both cultivars is similar. The concentration of terpenes and phthalides, the key volatile components, found in various cultivars of both celery and celeriac varied over a wide range.

Structure Guided Molecular Docking Assisted Alignment Dependent 3DQSAR Study on Steroidal Aromatase Inhibitors (SAIs) as Anti-breast Cancer Agents

2019 ◽  
Vol 16 (7) ◽  
pp. 808-817 ◽  
Author(s):  
Laxmi Banjare ◽  
Sant Kumar Verma ◽  
Akhlesh Kumar Jain ◽  
Suresh Thareja
Keyword(s):  
Breast Cancer ◽  
Molecular Docking ◽  
Aromatase Inhibitors ◽  
Direct Synthesis ◽  
3D Qsar ◽  
Chemotherapeutic Agents ◽  
Modeling Tools ◽  
Data Set ◽  
Wide Range ◽  
Steroidal Aromatase Inhibitors

Background: In spite of the availability of various treatment approaches including surgery, radiotherapy, and hormonal therapy, the steroidal aromatase inhibitors (SAIs) play a significant role as chemotherapeutic agents for the treatment of estrogen-dependent breast cancer with the benefit of reduced risk of recurrence. However, due to greater toxicity and side effects associated with currently available anti-breast cancer agents, there is emergent requirement to develop target-specific AIs with safer anti-breast cancer profile. Methods: It is challenging task to design target-specific and less toxic SAIs, though the molecular modeling tools viz. molecular docking simulations and QSAR have been continuing for more than two decades for the fast and efficient designing of novel, selective, potent and safe molecules against various biological targets to fight the number of dreaded diseases/disorders. In order to design novel and selective SAIs, structure guided molecular docking assisted alignment dependent 3D-QSAR studies was performed on a data set comprises of 22 molecules bearing steroidal scaffold with wide range of aromatase inhibitory activity. Results: 3D-QSAR model developed using molecular weighted (MW) extent alignment approach showed good statistical quality and predictive ability when compared to model developed using moments of inertia (MI) alignment approach. Conclusion: The explored binding interactions and generated pharmacophoric features (steric and electrostatic) of steroidal molecules could be exploited for further design, direct synthesis and development of new potential safer SAIs, that can be effective to reduce the mortality and morbidity associated with breast cancer.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

scholarly journals A Self-Spatial Adaptive Weighting Based U-Net for Image Segmentation

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 348
Author(s):  
Choongsang Cho ◽  
Young Han Lee ◽  
Jongyoul Park ◽  
Sangkeun Lee
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Feature Maps ◽  
Data Set ◽  
Feature Map ◽  
Adaptive Weighting ◽  
Spatially Adaptive ◽  
Wide Range ◽  
Decoder Architecture

Semantic image segmentation has a wide range of applications. When it comes to medical image segmentation, its accuracy is even more important than those of other areas because the performance gives useful information directly applicable to disease diagnosis, surgical planning, and history monitoring. The state-of-the-art models in medical image segmentation are variants of encoder-decoder architecture, which is called U-Net. To effectively reflect the spatial features in feature maps in encoder-decoder architecture, we propose a spatially adaptive weighting scheme for medical image segmentation. Specifically, the spatial feature is estimated from the feature maps, and the learned weighting parameters are obtained from the computed map, since segmentation results are predicted from the feature map through a convolutional layer. Especially in the proposed networks, the convolutional block for extracting the feature map is replaced with the widely used convolutional frameworks: VGG, ResNet, and Bottleneck Resent structures. In addition, a bilinear up-sampling method replaces the up-convolutional layer to increase the resolution of the feature map. For the performance evaluation of the proposed architecture, we used three data sets covering different medical imaging modalities. Experimental results show that the network with the proposed self-spatial adaptive weighting block based on the ResNet framework gave the highest IoU and DICE scores in the three tasks compared to other methods. In particular, the segmentation network combining the proposed self-spatially adaptive block and ResNet framework recorded the highest 3.01% and 2.89% improvements in IoU and DICE scores, respectively, in the Nerve data set. Therefore, we believe that the proposed scheme can be a useful tool for image segmentation tasks based on the encoder-decoder architecture.

Prodromal Dementia With Lewy Bodies: Evolution of Symptoms and Predictors of Dementia Onset

2021 ◽  
pp. 089198872110235
Author(s):  
Kathryn A. Wyman-Chick ◽  
Lauren R. O’Keefe ◽  
Daniel Weintraub ◽  
Melissa J. Armstrong ◽  
Michael Rosenbloom ◽  
...  
Keyword(s):  
Clinical Features ◽  
Dementia With Lewy Bodies ◽  
Clinical Symptoms ◽  
Neuropsychiatric Symptoms ◽  
Lewy Bodies ◽  
Rem Sleep Behavior Disorder ◽  
Data Set ◽  
Wide Range ◽  
Prodromal Dementia ◽  
Dementia Onset

Background: Research criteria for prodromal dementia with Lewy bodies (DLB) were published in 2020, but little is known regarding prodromal DLB in clinical settings. Methods: We identified non-demented participants without neurodegenerative disease from the National Alzheimer’s Coordinating Center Uniform Data Set who converted to DLB at a subsequent visit. Prevalence of neuropsychiatric and motor symptoms were examined up to 5 years prior to DLB diagnosis. Results: The sample included 116 participants clinically diagnosed with DLB and 348 age and sex-matched (1:3) Healthy Controls. Motor slowing was present in approximately 70% of participants 3 years prior to DLB diagnosis. In the prodromal phase, 50% of DLB participants demonstrated gait disorder, 70% had rigidity, 20% endorsed visual hallucinations, and over 50% of participants endorsed REM sleep behavior disorder. Apathy, depression, and anxiety were common prodromal neuropsychiatric symptoms. The presence of 1+ core clinical features of DLB in combination with apathy, depression, or anxiety resulted in the greatest AUC (0.815; 95% CI: 0.767, 0.865) for distinguishing HC from prodromal DLB 1 year prior to diagnosis. The presence of 2+ core clinical features was also accurate in differentiating between groups (AUC = 0.806; 95% CI: 0.756, 0.855). Conclusion: A wide range of motor, neuropsychiatric and other core clinical symptoms are common in prodromal DLB. A combination of core clinical features, neuropsychiatric symptoms and cognitive impairment can accurately differentiate DLB from normal aging prior to dementia onset.

scholarly journals Is contact angle a cause or an effect? – A cautionary tale

2020 ◽  
Vol 146 ◽  
pp. 03004
Author(s):  
Douglas Ruth
Keyword(s):  
Contact Angle ◽  
Solid Surface ◽  
Contact Angles ◽  
Two Dimensions ◽  
Experimental Results ◽  
Flow In Porous Media ◽  
Two Dimensional ◽  
Wide Range ◽  
Fluid Drop ◽  
Surrounding Fluid

The most influential parameter on the behavior of two-component flow in porous media is “wettability”. When wettability is being characterized, the most frequently used parameter is the “contact angle”. When a fluid-drop is placed on a solid surface, in the presence of a second, surrounding fluid, the fluid-fluid surface contacts the solid-surface at an angle that is typically measured through the fluid-drop. If this angle is less than 90°, the fluid in the drop is said to “wet” the surface. If this angle is greater than 90°, the surrounding fluid is said to “wet” the surface. This definition is universally accepted and appears to be scientifically justifiable, at least for a static situation where the solid surface is horizontal. Recently, this concept has been extended to characterize wettability in non-static situations using high-resolution, two-dimensional digital images of multi-component systems. Using simple thought experiments and published experimental results, many of them decades old, it will be demonstrated that contact angles are not primary parameters – their values depend on many other parameters. Using these arguments, it will be demonstrated that contact angles are not the cause of wettability behavior but the effect of wettability behavior and other parameters. The result of this is that the contact angle cannot be used as a primary indicator of wettability except in very restricted situations. Furthermore, it will be demonstrated that even for the simple case of a capillary interface in a vertical tube, attempting to use simply a two-dimensional image to determine the contact angle can result in a wide range of measured values. This observation is consistent with some published experimental results. It follows that contact angles measured in two-dimensions cannot be trusted to provide accurate values and these values should not be used to characterize the wettability of the system.

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