Geometry Data Research Articles

Experimental and theoretical study on spectral features, reactivity, solvation, topoisomerase I inhibition and in vitro cytotoxicity in human HepG2 cells of guadiscine and guadiscidine aporphine alkaloids

In this study, guadiscine (G1) and guadiscidine (G2), 7,7-dimethylaporphine alkaloids from Guatteria friesiana, have they geometric paramaters, vibrational behavior and quantum chemical properties (HOMO-LUMO, MEP, ALIE and Fukui indices) analyzed through a theoretical view, by density functional theory (DFT), using the Becker's three-parameter hybrid exchange functional combined with the Lee–Yang–Parr correlation functional (B3LYP) and 6–311G(2d,p) and 6–311G++(2df,3p) basis sets. The obtained geometry data were compared with x-ray data for (−)-N-acetyl-anonaine, showing close values. Vibrational analysis, together with potential energy distribution (PED) calculations, revealed several characteristic vibrations that characterize the 7,7 dimethylaporphine skeleton, besides enabling the observation of intermolecular H-bonds through dimers formation. Molecular dynamic simulations were carried out, allowing to evaluate the solvation free energies of G1 and G2 in water, methanol and ethanol, as well as H-bonds formation between G1 and G2 and the tested solvents. The antineoplastic potential of the title molecules was evaluated via molecular docking calculations with topoisomerase I complexed with DNA. Guadiscine and guadiscidine showed, respectively, binding free energies of -8.0 and -8.5 kcal/mol, while topotecan, a DNA topoisomerase I inhibitor, showed a binding free energy value of -12 kcal/mol, indicating that the studied molecules are good topoisomerase I inhibitors. In vitro cytotoxicity assay with HepG2 cell line were performed, revealing significant antitumor potential for G2.

A Simple Model to Identify Dryout Location: Validation and Computational Fluid Dynamics Predictions

Prediction of dryout location is essential to identify reliable heat flux margins for the safe operation of different thermal systems. The present study proposes a simple model to predict the dryout type critical heat flux location in a circular tube and an annulus. Based on the flow topology, the annular flow boiling regime is demarcated into two zones viz., vapor flow in the core region and liquid film flow in the annular gap between the vapor core and the wall surface. An expression is derived for the dryout location which is purely a function of operating conditions and fluid properties. The dryout location and quality predictions of the present model are found to be in very good agreement and within 10% error margin against the experimental data for tube and annulus geometries. The present study is extended to investigate the effect of eccentricity on the dryout location and the inner wall temperature. It is observed that the eccentricity results in early occurrence of dryout in the narrow gap region of an eccentric annulus. Furthermore, the predictions from the present model are compared with the look-up table data, subchannel analysis and computational fluid dynamics simulation predictions.

Computer-assisted beam modeling for particle therapy.

PurposeTo develop a computer‐driven and thus less user‐dependent method, allowing for a simple and straightforward generation of a Monte Carlo (MC) beam model of a scanned proton and carbon ion beam delivery system.MethodsIn a first step, experimental measurements were performed for proton and carbon ion energies in the available energy ranges. Data included depth dose profiles measured in water and spot sizes in air at various isocenter distances. Using an automated regularization‐based optimization process (AUTO‐BEAM), GATE/Geant4 beam models of the respective beam lines were generated. These were obtained sequentially by using least square weighting functions with and without regularization, to iteratively tune the beam parameters energy, energy spread, beam sigma, divergence, and emittance until a user‐defined agreement was reached. Based on the parameter tuning for a set of energies, a beam model was semi‐automatically generated. The resulting beam models were validated for all centers comparing to independent measurements of laterally integrated depth dose curves and spot sizes in air. For one representative center, three‐dimensional dose cubes were measured and compared to simulations. The method was applied on one research as well as four different clinical beam lines for proton and carbon ions of three different particle therapy centers using synchrotron or cyclotron accelerator systems: (a) MedAustron ion therapy center, (b) University Proton Therapy Dresden, and (c) Center Antoine Lacassagne Nice.ResultsParticle beam ranges in the MC beam models agreed on average within 0.2 mm compared to measurements for all energies and beam lines. Spot sizes in air (full‐width at half maximum) at all positions differed by less than 0.4% from the measurements. Dose calculation with the beam model for the clinical beam line at MedAustron agreed better than 1.7% in absolute dose for a representative clinical case treated with protons. For protons, beam model generation, including geometry creation, data conversion, and validation, was possible within three working days. The number of iterations required for the optimization process to converge, was found to be similar for all beam line geometries and particle types.ConclusionThe presented method was demonstrated to work independently of the beam optics behavior of the different beam lines, particle types, and geometries. Furthermore, it is suitable for non‐expert users and requires only limited user interaction. Beam model validation for different beam lines based on different beam delivery systems, showed good agreement.

Numerical simulation of microcystin distribution in Liangxi River, downstream of Taihu Lake

AbstractMicrocystins (MCs), the algal toxins produced by cyanobacteria, raised a worldwide concern in recent decades. Limited monitoring stations for MCs make it hard to map the MC spatial distribution in certain areas. To tackle such problems, we selected Liangxi River as our research area and developed an integrated model to get spatial continuous MC data without too many sampling sites, which integrates a hydro‐environment model and an artificial neural network algorithm (ANN). The ANN algorithm can estimate concentration MCs via environmental factors. In this paper, we selected chl‐a, TN, TP, , , NH3‐N, and as stressors. The ANN model we established showed good performances both in train (R2 = 0.8407) and test set (R2 = 0.7543). In the hydro‐environment model, by inputting river geometry and model boundary data, the spatial continuous water quality data could be simulated. The water quality data returned from the hydro‐environmental model were used as input variables of the well‐trained ANN model; the continuous MC data were derived. To evaluate this model on geo‐mapping the MC distribution in Liangxi River, we compared the performance of this model and spatial interpolation on the test set, it turns out the integrated model showed a better performance. © 2020 Water Environment FederationPractitioner points The cost of microcystin (MC) detection is too high for routine monitoring. We integrated regression method and hydro‐environment model to predict MCs. Results derived from spatial interpolation are not robust in unmonitored area. The new integration model can minimize the drawback of spatial interpolation.

Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations

Spectral aerosol optical depth (AOD) estimation from satellite-measured top of atmosphere (TOA) reflectances is challenging because of the complicated TOA-AOD relationship and a nexus of land surface and atmospheric state variations. This task is usually undertaken using a physical model to provide a first estimate of the TOA reflectances which are then optimized by comparison with the satellite data. Recently developed deep neural network (DNN) models provide a powerful tool to represent the complicated relationship statistically. This study presents a methodology based on DNN to estimate AOD using Himawari-8 Advanced Himawari Imager (AHI) TOA observations. A year (2017) of AHI TOA observations over the Himawari-8 full disk collocated in space and time with Aerosol Robotic Network (AERONET) AOD data were used to derive a total of 14,154 training and validation samples. The TOA reflectance in all six AHI solar bands, three TOA reflectance ratios derived based on the dark-target assumptions, sun-sensor geometry, and auxiliary data are used as predictors to estimate AOD at 500 nm. The DNN AOD is validated by separating training and validation samples using random k-fold cross-validation and using AERONET site-specific leave-one-station-out validation, and is compared with a random forest regression estimator and Japan Meteorological Agency (JMA) AOD. The DNN AOD shows high accuracy: (1) RMSE = 0.094, R2 = 0.915 for k-fold cross-validation, and (2) RMSE = 0.172, R2 = 0.730 for leave-one-station-out validation. The k-fold cross-validation overestimates the DNN accuracy as the training and validation samples may come from the same AHI pixel location. The leave-one-station-out validation reflects the accuracy for large-area applications where there are no training samples for the pixel location to be estimated. The DNN AOD has better accuracy than the random forest AOD and JMA AOD. In addition, the contribution of the dark-target derived TOA ratio predictors is examined and confirmed, and the sensitivity to the DNN structure is discussed.

Classifying basin‐scale stratigraphic geometries from subsurface formation tops with machine learning

AbstractPresented here is a transfer‐learning model for classifying basin‐scale stratigraphic geometries from subsurface formation tops. Support vector, decision trees, random forests, AdaBoost and K‐nearest neighbour classification models are evaluated to support this challenge. Each model is trained on labelled synthetic stratigraphic geometry data generated in Python using observable geological principles and concepts. Accuracy is measured using a weighted Jaccard similarity coefficient score, and certainty of each prediction is quantified using margin sampling. The random forest classifier has the highest initial accuracy, and the optimal hyperparameters for the model that yield 88.4% accuracy and 72.8% mean certainty via five‐fold cross‐validation and active learning are documented on a real‐world subsurface dataset. The random forest classifier with optimised hyperparameters is then used to make predictions on the real‐world subsurface formation tops dataset. The dataset consists of formation tops for the Upper Cretaceous and Palaeocene strata of the Eastern Greater Green River Basin in south‐central Wyoming. Results from model predictions include an area of truncation in the Lance Formation across the basin, and an area of onlap and truncation on the nose of the Rock Springs Uplift that previous studies in the region corroborate. It is believed that this model is most useful for guided interpretation, and identifying regions that warrant further inquiry by domain experts.

Approximate Bayesian computation for railway track geometry parameter estimation

The quality of track geometry is directly linked to vehicle safety, reliability and ride quality. The performance of track is therefore considerably hindered when track geometry indicators deviate from the specified and approved limits due to loads and continuous usage. Information obtained from the analysis of track geometry data can inform the prompt application of preventive and corrective maintenance measures like tamping, to increase the lifespan of the track and provide higher train speeds, optimizing track performance. Recently, there has been the application of Bayesian statistical methods in track degradation models. However, most models rely heavily on likelihood functions which are intractable. The aim of this paper is to apply Approximate Bayesian Computation (ABC), also known as the likelihood-free method, in estimating Track Quality Indices (TQIs) which are essential for track degradation modeling. ABC is applied using methods like the rejection algorithm and Markov Chain Monte Carlo (MCMC). In ABC, it is essential that summary statistics are computed from the observed data followed by the simulation of summary statistics for different parameter values. Two ABC-MCMC algorithms were used for parameter estimation in this paper. Models were developed using 200 ft. TQIs and 150 ft. TQIs with different priors and model choice was performed with the aid of Bayes Factors.

MODIS aerosol optical depth retrieval based on random forest approach

ABSTRACT Despite significant improvement in Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrieval, high-resolution–high-accuracy AOD retrieval remains a challenging task. This study utilizes machine learning for AOD retrieval of MODIS data. The global long-time-series data of AERONET sites and corresponding MODIS data in time and space were used as sample training data for aerosol retrieval via use of the random forest (RF) approach. The accuracy and stability of retrieval were ensured by processing AERONET site data, performing time–space matching between different data types, and determining related parameters in the RF model. MODIS data use bands 1–7 of the top-of-atmosphere reflectance (TOA) – extending from the visible to near-infrared radiation spectra – along with the corresponding observation geometry data, global land surface satellite (GLASS) albedo dataset, and normalized difference vegetation index (NDVI) data. The proposed method facilitates realizationthe of high-accuracy aerosol retrieval. Furthermore, significant enhancement in the efficiency of aerosol inversion is an added advantage.

Generating axial compressor maps to zero speed

Gas turbine performance models typically rely on component maps to characterize engine component performance throughout the operational regime. For the sub-idle case, the lack of reliable rig test data or inability to run design codes far from design conditions entails that component maps have to be generated from the extrapolation of existing data at higher speeds. This undermines the accuracy of whole-engine sub-idle performance models, at times impacting engine development and certification of aviation engines and the accuracy of start-up performance prediction in industrial gas turbines. One of the main components driving this issue is the core compression system, which can present operability concerns during light-up and which also sets the combustor airflow required for ignition. This paper presents, discusses, and draws on previous approaches to describe a method enabling the creation of sub-idle compressor maps from analytical and physical grounds. The method relies on the calculation of zero-speed and torque-free lines to generate a map down to zero speed along with analytical interpolation. A method for the interpolation process is described. A sensitivity study is carried out to assess the effects that different elements of the map generation process may have on the accuracy of the resulting performance calculation. Overall, a method for the generation of accurate, consistent maps from limited geometry data is identified.

Free vibration analysis of structural-acoustic coupled system using hybrid impedance and mobility approach

The present paper discusses impedance and mobility approach integrated with finite element method (FEM) for free vibration analysis of structural-acoustic coupled systems for irregular geometry. In this method, coupled natural frequencies of any irregular geometry with flexible surfaces with different boundary conditions can be estimated. The proposed hybrid method helps to understand the underlying physics of structural-acoustic coupling in complex geometries. The formulation being in impedance and mobility form, gives more insight in understanding coupled modes of the complex geometries. It is for three dimensional irregular geometries, so it can be used in most of the practical applications where coupled natural frequencies play a vital role. The proposed method is demonstrated for regular and irregular geometry with one wall flexible configuration. The results are corroborated with existing literature data for regular geometry and numerical models for irregular geometry.

Integrated outcrop and subsurface geomodeling of the Turonian Wall Creek Member of the Frontier Formation, Powder River Basin, Wyoming, USA

Inter-well heterogeneities influencing fluid migration in deltaic reservoirs are controlled by lateral lithofacies changes and vertical complexities such as low permeability thin-beds (i.e. mudstones). Subsurface tools cannot adequately predict the spatial and stratigraphic organization of these architectural elements, nor their influence on effective reservoir properties and connectivity. Our outcrop-based geomodeling study of the Turonian Wall Creek Member of the Frontier Formation in the Powder River Basin, Wyoming, USA, integrates subsurface production and flow simulation data to quantify the impact of multi-scale stratigraphic heterogeneity on analogous reservoir behavior and horizontal well design. The upscaled representation of thin-bed complexity in our 500 m × 715 m x 15 m geomodel is derived through flow simulation of internally nested, facies specific, centimeter-scale models (basic depositional element models or BDEMs). These BDEMs are populated with quantitative data of mudstone thin-bed geometries directly derived from digital outcrop measurements and measurements in the field, and aided by subsurface (core) petrophysical properties. Reservoir simulations are performed using various landing zone and completion configurations, and under both single-phase and multi-phase flow conditions history matched to subsurface production data.Results from our workflow demonstrate that, in heterolithic settings, the permeability of mudstone thin-beds impart the most significant impacts toward upscaled reservoir behavior, and deliver unique Kv/Kh flow anisotropies dependent on the governing depositional environment. Thin, laterally continuous and planar mudstone beds in the wave-and river-dominated distal delta front setting have the greatest negative effect on Kv and a minimal impact on Kh, promoting laterally continuous and vertically baffled flow units. Conversely, the more curvilinear and intersecting architectures of mudstone beds in the tidal dune facies maintain better vertical connectivity but decreased Kh compared to the wave-influenced facies. Reservoir flow is only sensitive to changes in engineering design (landing zone, well orientation, completion size) where thin-beds act as complete barriers rather than baffles to flow. Layer cake subsurface models failing to account for high-resolution stratigraphic architectures are likely to overestimate reservoir production where thin-beds act as barriers capable of appreciable reservoir compartmentalization, which in our models is more characteristic of the distal delta front setting. Synthesized results of this study are immediately applicable toward development planning in similar tight sandstone reservoirs.

Experimental Study on Deteriorated Performance, Vibration, and Geometry Changes of an Electrical Submersible Pump Under Sand Water Flow Condition

AbstractIn the oil and gas industry, the proppant backflow from fracturing wells severely reduces the lifespan of widely used downhole electrical submersible pumps (ESPs). In field applications, a minimal sand concentration may cause severe damage to ESPs in a short time. In order to resist the three-body abrasive sand wear, flanged tungsten carbide sleeves are used in ESPs. However, the wear-resistant performance of different pump geometry is not well analyzed and understood. Therefore, a 64 h pump erosion and abrasion test was conducted with water at the pump's best efficient flowrate with a sand concentration of 1 wt% to imitate the damage caused by short-term proppant backflow. The test was divided into several periods, after which the pump performance, paint-removal wear pattern, eroded pump geometries, and stage vibration were measured and recorded. The wear-rate on pump stage geometries gradually decreased at the beginning of 8–16 h. Then, the carbide sleeves started to help sustain the pump rotation. As a result, the wear-rate and pump vibration became relatively stable. Therefore, the wear mechanism in the secondary flow region (seal rings and sleeves) is believed to change from abrasive wear to the combined erosive-abrasive wear. The pump overall performance decreased by approximately 10% after the 64 h test. The performance, pump geometry, and vibration data are previous for understanding wear mechanism, predicting failures, improving pump design, and saving the well service cost.

A Computationally-Efficient Probabilistic Approach to Model-Based Damage Diagnosis

This work presents a computationally-efficient, probabilistic approach to model-based damage diagnosis. Given measurement data, probability distributions of unknown damage parameters are estimated using Bayesian inference and Markov chain Monte Carlo (MCMC) sampling. Substantial computational speedup is obtained by replacing a three-dimensional finite element (FE) model with an efficient surrogate model. While the formulation is general for arbitrary component geometry, damage type, and sensor data, it is applied to the problem of strain-based crack characterization and experimentally validated using full-field strain data from digital image correlation (DIC). Access to full-field DIC data facilitates the study of the effectiveness of strain-based diagnosis as the distance between the location of damage and strain measurements is varied. The ability of the framework to accurately estimate the crack parameters and effectively capture the uncertainty due to measurement proximity and experimental error is demonstrated. Furthermore, surrogate modeling is shown to enable diagnoses on the order of seconds and minutes rather than several days required with the FE model.

Advances in ultrafast gas-phase x-ray scattering

Recent developments of x-ray free electron lasers and pulsed electron sources have enabled ultrafast scattering to become an increasingly powerful tool for exploring molecular dynamics. This article describes our recent experimental and methodological advances in ultrafast gas-phase x-ray scattering experiments at the LCLS. A re-designed short-pathlength windowless diffractometer is coupled with careful optimization of sample density and independent normalization of x-ray intensity fluctuations to provide gas-phase scattering patterns with exceptionally high signal-to-noise ratios. These advances, coupled with careful geometry optimization and data treatment, provide both ground- and excited-state signals in excellent agreement with high level ab initio total scattering patterns.

Output-Sensitive Avatar Representations for Immersive Telepresence.

In this article, we propose a system design and implementation for output-sensitive reconstruction, transmission and rendering of 3D video avatars in distributed virtual environments. In our immersive telepresence system, users are captured by multiple RGBD sensors connected to a server that performs geometry reconstruction based on viewing feedback from remote telepresence parties. This feedback and reconstruction loop enables visibility-aware level-of-detail reconstruction of video avatars regarding geometry and texture data, and considers individual and groups of collocated users. Our evaluation reveals that our approach leads to a significant reduction of reconstruction times, network bandwidth requirements and round-trip times as well as rendering costs in many situations.

Inferring chromosome radial organization from Hi-C data

BackgroundThe nonrandom radial organization of eukaryotic chromosome territories (CTs) inside the nucleus plays an important role in nuclear functional compartmentalization. Increasingly, chromosome conformation capture (Hi-C) based approaches are being used to characterize the genome structure of many cell types and conditions. Computational methods to extract 3D arrangements of CTs from this type of pairwise contact data will thus increase our ability to analyze CT organization in a wider variety of biological situations.ResultsA number of full-scale polymer models have successfully reconstructed the 3D structure of chromosome territories from Hi-C. To supplement such methods, we explore alternative, direct, and less computationally intensive approaches to capture radial CT organization from Hi-C data. We show that we can infer relative chromosome ordering using PCA on a thresholded inter-chromosomal contact matrix. We simulate an ensemble of possible CT arrangements using a force-directed network layout algorithm and propose an approach to integrate additional chromosome properties into our predictions. Our CT radial organization predictions have a high correlation with microscopy imaging data for various cell nucleus geometries (lymphoblastoid, skin fibroblast, and breast epithelial cells), and we can capture previously documented changes in senescent and progeria cells.ConclusionsOur analysis approaches provide rapid and modular approaches to screen for alterations in CT organization across widely available Hi-C data. We demonstrate which stages of the approach can extract meaningful information, and also describe limitations of pairwise contacts alone to predict absolute 3D positions.

An XML-based approach for geo-semantic data exchange from BIM to VR applications

Virtual Reality (VR) and Building Information Modelling (BIM) have been steadily growing over the past decade and found practical applications in project planning, design review and construction planning analysis particularly in the Architecture, Engineering, Construction, and Facility Management (AEC/FM) industry. However, data exchange between BIM and VR is a complex and time consuming process, which has limited VR applications in practice. To address this challenge, this research proposes a novel method that enables an efficient interoperability of BIM and VR including geometry of each element along with required semantic data of the BIM model. In this method, geometry and semantic data are extracted from BIM models through an Extensible Markup Language (XML) file, which is then optimized to be efficiently imported and recreated into the VR environment. The backward communication is performed by converting XML file to IFC, which is then imported to the BIM application. A prototype was developed to implement the proposed methodology. A building case study was used to demonstrate the capability of the method including considerably short transfer time, high quality rendering and geo-semantic data exchange for design and construction. These capabilities promote VR applications in the AEC/FM industry as the required information for design and construction plan review including Architectural parameter (e.g., material, texture and dimensions), Engineering parameters (e.g., loads, R-Value), cost, schedule and clashes can be exchanged between BIM and VR in near real time.

Standardized navigational data for situational awareness during simultaneous maritime operations

The objective of this paper is to describe a protocol for exchange of navigational data between ships operating in close proximity. The protocol supports the exchange of data needed for relative positioning and includes geometry data of the objects involved in the operation in addition to inertial and positional data. The protocol takes into account the variable and limited communication capabilities that may be available for maritime operations. The paper describes one use case where two ships perform a simultaneous operation and another use case where a ship broadcasts its intended route. A S-100 Application Schema covering the required data is presented. Examples of the message exchange and bandwidth requirements are given. The resulting protocol will be useful for autonomous systems and ships that need standardized exchange of data to support situational awareness during their passage. The paper is written as part of the H2H project [1] which is developing an open system architecture to ensure interoperability between different vendors of autonomous systems when it comes to the data exchange related to position and geometry data.

PENGOLAHAN DATA SEISMIK 2D MARINE MENGGUNAKAN ProMAX DI AREA TENGGARA PULAU SIMEULUE

PENGOLAHAN DATA SEISMIK 2D MARINE MENGGUNAKAN ProMAX DI AREA TENGGARA PULAU SIMEULUE

Assessment of the Stability of Passenger Ships in Coastal Navigation in Case of Lacking Ship Geometry Data

Ships should ensure safe navigation by meeting the stability norms defined by the International Maritime Organization (IMO) and determined by national maritime administrations. The fulfillment of these norms is becoming increasingly important, especially for passenger ships used for tourist excursions. Recently, the development of maritime tourism has greatly increased the demand for these ships most of which are converted fishing vessels. The situation described in this paper pertains to Albania and most probably differs in other countries in the region and the wider area. Ships rarely have adequate technical documentation. The Albanian Register of Shipping requires the performance of stability tests, the results of which are entered in the amended stability book to ensure the vessels’ compliance with the norms following modifications undergone and guarantee safe navigation for tourists. An examination of a variety of ship design papers helped us identify various methods and methodologies for determining approximate geometric ship elements with an acceptable degree of reliability. However, their use should be limited and reliability proven by calculating parameters such as lightship VCG, number of passengers per m2, assessing the possible range and area of navigation and weather conditions (mainly wind speed and wave forces). The calculations based on stability testing and the use of highly reliable software such as MaxSurf - Integrated Naval Architecture Software, Napa - Naval Architectural Package Autoship - Systems Operation, Orca3D – Naval Architecture Software delivered fast and reliable stability assessment results and verified conformance with the norms prescribed by the Albanian Register of Shipping.