Ratio Maps Research Articles

Combined and optimized 2-steps ratio map for shadow detection in aerial images

Combined and optimized 2-steps ratio map for shadow detection in aerial images

Reliability of task-evoked neural activation during face-emotion paradigms: Effects of scanner and psychological processes.

Assessing and improving test–retest reliability is critical to efforts to address concerns about replicability of task‐based functional magnetic resonance imaging. The current study uses two statistical approaches to examine how scanner and task‐related factors influence reliability of neural response to face‐emotion viewing. Forty healthy adult participants completed two face‐emotion paradigms at up to three scanning sessions across two scanners of the same build over approximately 2 months. We examined reliability across the main task contrasts using Bayesian linear mixed‐effects models performed voxel‐wise across the brain. We also used a novel Bayesian hierarchical model across a predefined whole‐brain parcellation scheme and subcortical anatomical regions. Scanner differences accounted for minimal variance in temporal signal‐to‐noise ratio and task contrast maps. Regions activated during task at the group level showed higher reliability relative to regions not activated significantly at the group level. Greater reliability was found for contrasts involving conditions with clearly distinct visual stimuli and associated cognitive demands (e.g., face vs. nonface discrimination) compared to conditions with more similar demands (e.g., angry vs. happy face discrimination). Voxel‐wise reliability estimates tended to be higher than those based on predefined anatomical regions. This work informs attempts to improve reliability in the context of task activation patterns and specific task contrasts. Our study provides a new method to estimate reliability across a large number of regions of interest and can inform researchers' selection of task conditions and analytic contrasts.

A reconstruction approach for proton computed tomography by modeling the integral depth dose of the scanning proton pencil beam.

To present a proton computed tomography (pCT) reconstruction approach that models the integral depth dose (IDD) of the clinical scanning proton beam into beamlets. Using a multilayer ionization chamber (MLIC) as the imager, the proposed pCT system and the reconstruction approach can minimize extra ambient neutron dose and simplify the beamline design by eliminating an additional collimator to confine the proton beam. Monte Carlo simulation was applied to digitally simulate the IDDs of the exiting proton beams detected by the MLIC. A forward model was developed to model each IDD into a weighted sum of percentage depth doses of the constituent beamlets separated laterally by 1mm. The water equivalent path lengths (WEPLs) of the beamlets were determined by iteratively minimizing the squared L2-norm between the forward projected and simulated IDDs. The final WEPL values were reconstructed to pCT images, that is, proton stopping power ratio (SPR) maps, through simultaneous algebraic reconstruction technique with total variation regularization. The reconstruction process was tested with a digital cylindrical water-based phantom and an ICRP adult reference computational phantom. The mean of SPR within regions of interest (ROIs) and the WEPL along a 4mm-wide beam ( ) were compared with the reference values. The spatial resolution was analyzed at the edge of a cortical insert of the cylindrical phantom. The percentage deviations from reference SPR were within±1% in all selected ROIs. The mean absolute error of the reconstructed SPR was 0.33%, 0.19%, and 0.27% for the cylindrical phantom, the adult phantom at the head and lung region, respectively. The corresponding percentage deviations from reference were 0.48±0.64%, 0.28±0.48%, and 0.22±0.49%. The full width at half maximum of the line spread function (LSF) derived from the radial edge spread function (ESF) of a cortical insert was 0.13cm. The frequency at 10% of the modulation transfer function (MTF) was 6.38cm-1 . The mean signal-to-noise ratio (SNR) of all the inserts was 2.45. The mean imaging dose was 0.29 and 0.25cGy at the head and lung region of the adult phantom, respectively. A new pCT reconstruction approach was developed by modeling the IDDs of the uncollimated scanning proton beams in the pencil beam geometry. SPR accuracy within±1%, spatial resolution of better than 2mm at 10% MTF, and imaging dose at the magnitude of mGy were achieved. Potential side effects caused by neutron dose were eliminated by removing the extra beam collimator.

Evaluation of methods to detect circular RNAs from single-end RNA-sequencing data

BackgroundCircular RNA (circRNA), a class of RNA molecule with a loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers of human diseases. Most of the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize the mapping information of paired-end (PE) reads to eliminate false positives. However, much of the practical RNA-Seq data such as cross-linking immunoprecipitation sequencing (CLIP-Seq) data usually contain single-end (SE) reads. It is not clear how well these tools perform on SE RNA-Seq data.ResultsIn this study, we present a systematic evaluation of six advanced RNA-based methods and two CLIP-Seq based methods for detecting circRNAs from SE RNA-Seq data. The performances of the methods are rigorously assessed based on precision, sensitivity, F1 score, and true discovery rate. We investigate the impacts of read length, false positive ratio, sequencing depth and PE mapping information on the performances of the methods using simulated SE RNA-Seq simulated datasets. The real datasets used in this study consist of four experimental RNA-Seq datasets with ≥100bp read length and 124 CLIP-Seq samples from 45 studies that contain mostly short-read (≤50bp) RNA-Seq data. The simulation study shows that the sensitivities of most of the methods can be improved by increasing either read length or sequencing depth, and that the levels of false positive rates significantly affect the precision of all methods. Furthermore, the PE mapping information can improve the method’s precision but can not always guarantee the increase of F1 score. Overall, no method is dominant for all SE RNA-Seq data. The RNA-based methods perform better for the long-read datasets but are worse for the short-read datasets. In contrast, the CLIP-Seq based methods outperform the RNA-Seq based methods for all the short-read samples. Combining the results of these methods can significantly improve precision in the CLIP-Seq data.ConclusionsThe results provide a systematic evaluation of circRNA detection methods on SE RNA-Seq data that would facilitate researchers’ strategies in circRNA analysis.

Single-camera stereoscopic 3D multiplexed structured image capture for quantitative fuel-to-air ratio mapping

A single-camera three-dimensional Multiplexed Structured Image Capture (3D-MUSIC) based stereoscopic imaging system is demonstrated to obtain a three-dimensional fuel-to-air ratio (FAR) map of a methane-air Bunsen flame at standard atmosphere conditions. Images of the C2* (500nm) and CH* (430nm) emissions are spatially modulated and captured through two optical paths and combined into a single image on the camera. The C2* / CH* ratio is computationally recovered by low-pass filtering in the spatial frequency domain and exhibits a linear trend to a FAR map of the flame. Each channel's unique FAR map is fused to generate a line-of-sight three-dimensional FAR map by triangulating points from each channel's perspective. As an imaging technique, the 3D MUSIC is capable of obtaining multi-spectral multi-view 3D images using spatial modulation and recovery in one camera without any special illumination. It may be extended for applications in combustion, biomedical, and other key diagnostics.

T1w/FLAIR ratio standardization as a myelin marker in MS patients

IntroductionCalculation of a T1w/T2w ratio was introduced as a proxy for myelin integrity in the brain of multiple sclerosis (MS) patients. Since nowadays 3D FLAIR is commonly used for lesion detection instead of T2w images, we introduce a T1w/FLAIR ratio as an alternative for the T1w/T2w ratio. ObjectivesBias and intensity variation are widely present between different scanners, between subjects and within subjects over time in T1w, T2w and FLAIR images. We present a standardized method for calculating a histogram calibrated T1w/FLAIR ratio to reduce bias and intensity variation in MR sequences from different scanners and at different time-points. Material and methods207 Relapsing Remitting MS patients were scanned on 4 different 3 T scanners with a protocol including 3D T1w, 2D T2w and 3D FLAIR images. After bias correction, T1w/FLAIR ratio maps and T1w/T2w ratio maps were calculated in 4 different ways: without calibration, with linear histogram calibration as described by Ganzetti et al. (2014), and by using 2 methods of non-linear histogram calibration. The first nonlinear calibration uses a template of extra-cerebral tissue and cerebrospinal fluid (CSF) brought from Montreal Neurological Institute (MNI) space to subject space; for the second nonlinear method we used an extra-cerebral tissue and CSF template of our own subjects. Additionally, we segmented several brain structures such as Normal Appearing White Matter (NAWM), Normal Appearing Grey Matter (NAGM), corpus callosum, thalami and MS lesions using Freesurfer and Samseg. ResultsThe coefficient of variation of T1w/FLAIR ratio in NAWM for the no calibrated, linear, and 2 nonlinear calibration methods were respectively 24, 19.1, 9.5, 13.8. The nonlinear methods of calibration showed the best results for calculating the T1w/FLAIR ratio with a smaller dispersion of the data and a smaller overlap of T1w/FLAIR ratio in the different segmented brain structures. T1w/T2w and T1w/FLAIR ratios showed a wider range of values compared to MTR values. ConclusionsCalibration of T1w/T2w and T1w/FLAIR ratio maps is imperative to account for the sources of variation described above. The nonlinear calibration methods showed the best reduction of between-subject and within-subject variability. The T1w/T2w and T1w/FLAIR ratio seem to be more sensitive to smaller changes in tissue integrity than MTR. Future work is needed to determine the exact substrate of T1w/FLAIR ratio and to obtain correlations with clinical outcome.

Spectroscopy of Gossans and associated lithology and its implication in geo exploration- A Case Study in the Parts of Rajpura-Dariba Group, Rajasthan, India

The gossan exposures are sparsely distributed in the Dariba area and for detection and mapping of gossan and its associated lithology, spectral signatures have been used. Spectral reflectance and absorption features in VNIR-SWIR (visible and near-infrared - shortwave infrared) domain provide the scope for delineating the mineralogy of rocks. In the study, a few spectral mapping methods like Spectral angle mapper, Spectral information divergence and Band ratio indices were applied to ASTER (Advanced Space borne Thermal Emission Reflection Radiometer) calibrated data for delineating the lithology. These mapping methods could delineate boundaries for gossan and its associated rocks of Dariba; but above out of all mapping methods, spectral angle mapper spatial map has been validated with base detailed geological map in quantitatively and accuracy much better than spectral information divergence indices. The band ratio can demarcate the boundaries for gossans in the 4/2 ratio map, in the same way for associated rocks of Carbonates were well delineated in the (7+9)/8 ratio map and Quartzite 4/6 ratio map. Finally, the overextended boundaries of Dariba gossans and associated units found in the above validated spatial map, can be confirmed with field evidence can be helpful to update the base map of Dariba

Correlated MR spectroscopic imaging of breast cancer to investigate metabolites and lipids: acceleration and compressed sensing reconstruction.

The main objective of this work was to detect novel biomarkers in breast cancer by spreading the MR spectra over two dimensions in multiple spatial locations using an accelerated 5D EP-COSI technology. The 5D EP-COSI data were non-uniformly undersampled with an acceleration factor of 8 and reconstructed using group sparsity-based compressed sensing reconstruction. Different metabolite and lipid ratios were then quantified and statistically analyzed for significance. Linear discriminant models based on the quantified metabolite and lipid ratios were generated. Spectroscopic images of the quantified metabolite and lipid ratios were also reconstructed. The 2D COSY spectra generated using the 5D EP-COSI technique showed differences among healthy, benign, and malignant tissues in terms of their mean values of metabolite and lipid ratios, especially the ratios of potential novel biomarkers based on unsaturated fatty acids, myo-inositol, and glycine. It is further shown the potential of choline and unsaturated lipid ratio maps, generated from the quantified COSY signals across multiple locations in the breast, to serve as complementary markers of malignancy that can be added to the multiparametric MR protocol. Discriminant models using metabolite and lipid ratios were found to be statistically significant for classifying benign and malignant tumor from healthy tissues. Accelerated 5D EP-COSI technique demonstrates the potential to detect novel biomarkers such as glycine, myo-inositol, and unsaturated fatty acids in addition to commonly reported choline in breast cancer, and facilitates metabolite and lipid ratio maps which have the potential to play a significant role in breast cancer detection. This study presents the first evaluation of a multidimensional MR spectroscopic imaging technique for the detection of potentially novel biomarkers based on glycine, myo-inositol, and unsaturated fatty acids, in addition to commonly reported choline. Spatial mapping of choline and unsaturated fatty acid ratios with respect to water in malignant and benign breast masses are also shown. These metabolic characteristics may serve as additional biomarkers for improving the diagnostic and therapeutic evaluation of breast cancer.

Persymmetric Adaptive Target Detection With Dual-Polarization in Compound Gaussian Sea Clutter With Inverse Gamma Texture

This paper investigates the dual-polarimetric target detection problem in non-Gaussian sea clutter. The compound Gaussian model with inverse Gamma texture is adopted to describe the real sea clutter of which characteristics are time-varying and heterogeneous. Three novel polarimetric detectors are proposed based on the two-step maximum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> (MAP) generalized likelihood ratio test (GLRT), MAP Rao, and MAP Wald criteria. Specifically, we assume the polarimetric clutter covariance matrix (PCCM) and the inverse Gamma textures are known in the first step, and the test statistics of the proposed polarimetric detectors are derived. In the second step, we take advantage of the proposed polarimetric persymmetric property and MAP criterion to estimate the PCCM and inverse Gamma textures, respectively. The fully adaptive persymmetric polarimetric detectors are obtained by substituting the estimates into the test statistics of the proposed detectors. Then the proposed detectors are proved to have the constant false alarm rate (CFAR) properties with respect to the real PCCM. The performance assessments are evaluated by contrasting the proposed detectors with their counterparts on the simulated and measured sea clutter data. The numerical results verify the performance of the proposed persymmetric polarimetric detectors.

Radio Map Assisted Path Planning for UAV Anti-Jamming Communications

The communications quality of unmanned aerial vehicle (UAV) has been brought into focus increasingly, which can be severely affected by other users, as well as complex topography. In this letter, we propose a path planning algorithm for UAV anti-jamming communications with the joint assistance of two kinds of radio maps—signal power map and signal to interference plus noise ratio (SINR) map, which contain the abundant information of path loss caused by the topography and interference from jammers. We show how to generate these maps from real topographic data, and provide the optimal UAV path planning by adopting the power and the SNR maps to the heuristic and graphic based A* algorithm. Simulations with various settings for areas with complex topography in real world, show that the proposed algorithm can considerably improve the efficiency by minimizing the UAV flying distance for anti-jamming communications.

Eye fatigue estimation using blink detection based on Eye Aspect Ratio Mapping(EARM)

With the advent of the information society, the eyes' health is threatened all over the world. Rules and systems have been proposed to avoid these problems, but most users do not use them due to the physical and time constraints and costs involved and the lack of awareness of eye health. In this paper, we estimate the eye fatigue sensitivity by detecting spontaneous blinks with high accuracy. The experimental results show that the proposed Eye Aspect Ratio Mapping can classify blinks with high accuracy at a low cost. We also found a strong correlation between the median SBR (Spontaneous Blink Rate) and the time between the objective estimation of eye fatigue and the subject's awareness of eye fatigue.

Individual variability in the cortical distribution of elevated 18F‐flortaucipir uptake in posterior cortical atrophy

AbstractBackgroundAccumulating evidence supports the relevance of the localization of tau pathology, as measured with 18F‐flortaucipir (FTP) PET imaging, for characterizing clinical phenotypes of Alzheimer’s disease (AD), including posterior cortical atrophy (PCA). The present study investigated the degree to which the cortical distribution of elevated FTP uptake varies across individual patients with PCA, with the goal to identify regions of heightened vulnerability to tau pathology in this population. Based on available PET imaging evidence and using a systems neuroscience approach, we hypothesized that the majority of PCA patients would exhibit elevated FTP uptake in the visual and dorsal attention networks of the brain, consistent with impairments in basic and higher‐order visual processing characteristic of this syndrome.Method15 patients with PCA underwent FTP PET imaging. Individual FTP standardized uptake value ratio (SUVR) maps were partial volume corrected and projected to template cortical surface space. These individual SUVR maps were converted to Z‐score maps using data obtained from 24 age‐matched healthy control subjects, then binarized at Z &gt; 1.5. Percent overlap maps were created based on the individual binarized Z‐score maps. A parcellation of the cerebral cortex into seven canonical intrinsic functional networks was used to characterize the spatial topography of elevated FTP uptake.Result100% of PCA patients showed elevated FTP uptake in brain regions including bilateral superior parietal lobule, area MT, and importantly, bilateral frontal eye fields, which are key nodes of the dorsal attention network. In more than 80% of patients, elevated signal was also observed bilaterally in the occipital, parietal, and temporal areas that are nodes of the visual, frontoparietal, and default mode networks, with more circumscribed and variable involvement of prefrontal cortex.ConclusionThe results support the hypothesis that tau pathology in PCA universally affects the key nodes of the dorsal attention network consistent with visuospatial and visuomotor deficits commonly observed in PCA, including oculomotor apraxia (impaired voluntary control of eye movements). In addition to the nearly universal involvement of visual association networks, key nodes of default mode and frontoparietal control networks likely subserve other cognitive deficits that are common but more variable in PCA.

In Vivo 18 F-APN-1607 Tau Positron Emission Tomography Imaging in MAPT Mutations: Cross-Sectional and Longitudinal Findings.

Frontotemporal lobar degeneration with tauopathy caused by MAPT (microtubule-associated protein tau) mutations is a highly heterogenous disorder. The ability to visualize and longitudinally monitor tau deposits may be beneficial to understand disease pathophysiology and predict clinical trajectories. The aim of this study was to investigate the cross-sectional and longitudinal 18 F-APN-1607 positron emission tomography/computed tomography (PET/CT) imaging findings in MAPT mutation carriers. Seven carriers of MAPT mutations (six within exon 10 and one outside of exon 10) and 15 healthy control subjects were included. All participants underwent 18 F-APN-1607 PET/CT at baseline. Three carriers of exon 10 mutations received follow-up 18 F-APN-1607 PET/CT scans. Standardized uptake value ratio (SUVR) maps were obtained using the cerebellar gray matter as the reference region. SUVR values observed in MAPT mutation carriers were normalized to data from healthy control subjects. A regional SUVR z score ≥ 2 was used as the criterion to define positive 18 F-APN-1607 PET/CT findings. Although the seven study patients had heterogenous clinical phenotypes, all showed a significant 18 F-APN-1607 uptake characterized by high-contrast signals. However, the anatomical localization of tau deposits differed in patients with distinct clinical symptoms. Follow-up imaging data, which were available for three patients, demonstrated worsening trends in patterns of tau accumulation over time, which were paralleled by a significant clinical deterioration. Our data represent a promising step in understanding the usefulness of 18 F-APN-1607 PET/CT imaging for detecting tau accumulation in MAPT mutation carriers. Our preliminary follow-up data also suggest the potential value of 18 F-APN-1607 PET/CT for monitoring the longitudinal trajectories of frontotemporal lobar degeneration caused by MAPT mutations. © 2021 International Parkinson and Movement Disorder Society.

Integrating magnetic susceptibility, hydrogeochemical, and isotopic data to assess the seawater invasion in coastal aquifers of Digha, West Bengal, India.

Seawater intrusion in coastal aquifers is a major concern due to geogenic and anthropogenic activities leading to declining groundwater quality. The present study focuses on deciphering the sea water intruded zones and its extent in the Quaternary alluvial aquifer system in the coastal belt of Digha, West Bengal, India. In this study, 36 groundwater samples were collected during pre-monsoon (2020). Subsequently, an integrated approach of hydrogeological, hydrogeochemistry, bulk magnetic susceptibility, isotopic, multivariate statistical, and geochemical modeling is adopted. Spatial distribution maps of hydrological parameters (salinity, conductivity, TDS) and major ion concentration (Na+, K+, Ca2+, Mg2+, Cl-, SO42-, F-, and Br-) suggest that the northern, south-west, and eastern parts of the study area are largely affected by saltwater intrusion and are corroborated with seawater mixing index (SMI). Based on sodium adsorption ratio (SAR), sodium percentage (Na%), and Permeability index (PI) distribution maps, the same locations are identified under critical condition for the suitability of groundwater for irrigation. The order of concentration of cations and anions in the water samples are Na+ > Ca2+ > Mg2+ > K+ and HCO3- > SO4- > Cl- > Br- > F- respectively. Piper diagram shows three principal hydrochemical water types with water composition changes from fresh (86%) to saline water mix (14%). The hydrochemical facies evolution diagram depicts 81% of water samples are in the freshening phase, and 19% are in the intrusion phase. The various bivariate plots revealed that ion exchange, reverse ion exchange, silicate weathering, seawater mixing, and anthropogenic inputs are the governing factors that control groundwater evolution. R-mode factor analysis, principal component analysis (PCA), and agglomerative hierarchical cluster (AHC) also indicate the influence on groundwater from seawater mixing and/or seawater intrusion. The superlativeness of bulk magnetic susceptibility (χ) analysis of water samples in delineating seawater intruded zones is elaborated. Saturation index (SI) shows that groundwater is saturated (> 0) with calcite, dolomite, and aragonite, plausibly due to seawater ingression. Stable isotopic analysis of δ2H (- 53.979 to - 16.9578‰) and δ18O (- 7.00183 to - 1.37 ‰) suggests precipitation recharge/paleo-water at some locations and evaporation enrichment of groundwater. It is recommended to increase groundwater recharge, reduce groundwater extraction at critically affected locations, and have regular monitoring and management to control seawater intrusion.

Glass Substrate Dust Removal Using 233 fs Laser-Generated Shockwave.

Eliminating dust is gaining importance as a critical requirement in the display panel manufacturing process. The pixel resolution of display panels is increasing rapidly, which means that even small dust particles on the order of a few micrometers can affect them. Conventional surface cleaning methods such as ultrasonic cleaning (USC), CO2 cleaning, and wet cleaning may not be sufficiently efficient, economical, or environment friendly. In this study, a laser shockwave cleaning (LSC) method with a 233 fs pulsed laser was developed, which is different from the laser ablation cleaning method. To minimize thermal damage to the glass substrate, the effect of the number of pulses and the gap distance between the focused laser beam and the glass substrate were studied. The optimum number of pulses and gap distance to prevent damage to the glass substrate was inferred as 500 and 20 μm, respectively. With the optimal pulse number and gap distance, cleaning efficiency was tested at a 95% removal ratio regardless of the density of the particles. The effective cleaning area was measured using the removal ratio map and compared with the theoretical value.

Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy.

Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based method to synthesize DECT images from SECT image for proton radiotherapy. The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model to focus on the difference between DECT images and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 70 head-and-neck cancer patients whose DECT and SECT scans were acquired simultaneously. The model was trained to generate both a high and low energy DECT image based on a SECT image. The generated synthetic low and high DECT images were evaluated against the true DECT images using leave-one-out cross-validation. To evaluate our method in the context of a practical application, we generated SPR maps from synthetic DECT (sDECT) using a dual-energy based stoichiometric method and compared the SPR maps to those generated from DECT. A dosimetric comparison for dose obtained from DECT was performed against that derived from sDECT. The mean of mean absolute error, peak signal-to-noise ratio and normalized cross-correlation for the synthetic high and low energy CT images was 36.9 HU, 29.3 dB, 0.96 and 35.8 HU, 29.2 dB, and 0.96, respectively. The corresponding SPR maps generated from synthetic DECT showed an average normalized mean square deviation of about 1% with reduced noise level and artifacts than those from original DECT. Dose-volume histogram (DVH) metrics for the clinical target volume agree within 1% between the DECT and sDECT calculated dose. Our method synthesized accurate DECT images and showed a potential feasibility for proton SPR map generation. This study investigated a learning-based method to synthesize DECT images from SECT image for proton radiotherapy.

A robust, multi-solution framework for well placement and control optimization

Field development and control optimization aim to maximize the economic profit of oil and gas production while considering several sources of uncertainty. This results in a high-dimensional optimization problem with a computationally demanding and uncertain objective function based on the simulated reservoir model. The limitations of many current robust optimization methods are: 1) it is single-level optimization (e.g. optimization of well locations/placement only; or of well production/injection control variables only) that ignores interference between the control variables from different levels; and 2) they provide a single optimal solution, whereas operational problems often add unexpected constraints likely to reduce that optimal, inflexible solution to a sub-optimal scenario. This paper presents a robust, multi-solution framework based on sequential iterative optimization of control variables at multiple levels using the Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm. A systematic realization selection process, tailored to the objective of the subsequent optimization stage, is used to select a small representative ensemble of reservoir model realizations to be used for calculating the expected objective value. The estimated gradients are calculated using a 1:1 ratio mapping ensemble of control variables perturbations at each iteration onto the ensemble of selected reservoir model realizations to reduce the computational cost. An ensemble of close-to-optimum solutions is then chosen from each level (e.g. from the well placement optimization level) and transferred to the next level of optimization (e.g. where the control settings are optimized), and this loop continues until no significant improvement is observed in the expected objective value. Fit-for-purpose clustering techniques are developed to systematically select an ensemble of solutions, with maximum differences in control variables but close-to-optimum objective values, at each optimization level. The proposed framework has been tested on a benchmark case study (Brugge field). Multiple solutions are obtained with different well locations and control settings but close-to-optimum objective values. We show that suboptimal solutions from an early optimization level can approach and even outdo the optimal one at the next level(s). Results demonstrate the advantage of the developed framework in more efficient exploration of the search space and providing the much-needed operational flexibility to field operators.

Magnetic and spectrometric studies of Al-Gor area, Southwestern Sinai, Egypt

Al-Gor area is a part of Southwestern Sinai of Egypt. It is considered as one of the most promising areas for mineralization in Egypt, being rich in many mineral deposits of: manganese, iron, copper, zinc, lead, cobalt, nickel, silver, gibbsite, and uranium. Besides, some industrial ore minerals such as kaolin and glass sand,… etc. are also found in this area. The area was studied by Gama-ray spectrometry to trace the radioactive anomalies, their concentrations and their relationship to the existing rocks, and by magnetic survey to study the relationship of radioactive anomalies and their trends with the trends of geological structures. The gamma-ray spectrometric maps show different levels over the surveyed area, which reflect contrasting radioelement contents for the exposed various rock types. The highest radiospectrometric levels are located in the northwest southeast direction and some scattered parts all over the study area. They are mainly associated with Um-Bogma Formation, bearing gibbsite. The study area possesses radiospectrometric ranging between 0.6 and 110.9 Ur as a total-count, 0.1 to 1.8 % for K, 0.1 to 99 ppm for eU and 0.1 to 23 ppm for eTh. The qualitative analyses of magnetic data show the existences of a number of different magnetic anomalies, with different amplitudes and frequencies as well as trends. From the application of spectral analyses of magnetic data, the regional and residual depths of magnetic anomalies can be computed. The first depth represents the regional (deep-seated) anomalies, at about 75 m and the residual (shallow-seated) anomalies, at about 20 m. The trends of the structures as derived from the spectrometric and ratio maps correspond to those inferred from the residual-component magnetic map, which reflects the effect of structures on the concentration of radioactive elements and, consequently mineralization.

Lunar Surface Composition Constraints from Maturity-corrected Far-ultraviolet Reflectance Maps

Abstract Far-ultraviolet (FUV) observations by the Lunar Reconnaissance Orbiter Lyman Alpha Mapping Project (LAMP) have shown that the lunar surface reflectance in the ultraviolet is sensitive to changes in both composition and maturity at wavelengths &gt;170 nm. This can lead to uncertainties in the interpretation of features that appear in maps created using LAMP data from this wavelength range. Here we utilize a correction based on the optical maturity parameter to remove large-scale immaturity features from LAMP spectral slope and band ratio maps. After performing the correction, the LAMP maps more accurately represent the FUV lunar surface in the context of composition. Corrected LAMP maps show good correlation with lunar FeO, plagioclase, and bulk silicate abundance maps for moderate- to high-iron regions, indicating a sensitivity in the LAMP data to differences in mineral composition in those regions. These maps represent a unique view into a relatively unexplored region of the spectrum and showcase the ability to perform compositional mapping and mineral identification using FUV remote-sensing measurements.

Impact of the dog population and household environment for the maintenance of natural foci of Leishmania infantum transmission to human and animal hosts in endemic areas for visceral leishmaniasis in Sao Paulo state, Brazil.

When it comes to visceral leishmaniasis (VL) in Brazil, one of the main targets of public health policies of surveillance is the control of domestic canine reservoirs of Leishmania infantum. This paper aims to evaluate the effect of the dog population and household environment for the maintenance of natural foci in the transmission to human and animal hosts in an endemic city for VL, Bauru, in Brazil. We collected 6,578 blood samples of dogs living in 3,916 households from Nov.2019 to Mar.2020 and applied geospatial models to predict the disease risk based on the canine population. We used Kernel density estimation, cluster analysis, geostatistics, and Generalized Additive Models (GAM). To validate our models, we used cross-validation and created a receiver operating characteristic (ROC) curve. We found an overall canine VL (CVL) seroprevalence of 5.6% for the sampled dogs, while for the households, the positivity rate was 8.7%. Odds ratios (OR) for CVL increased progressively according to the number of canines for >2 dogs (OR 2.70); households that already had CVL in the past increased the chances for CVL currently (OR 2.73); and the cases of CVL increase the chances for human VL cases (OR 1.16). Our models were statistically significant and demonstrated a spatial association between canine and human disease cases, mainly in VL foci that remain endemic. Although the Kernel density ratio map had the best performance (AUC = 82), all the models showed high risk in the city’s northwest area. Canine population dynamics must be considered in public policies, and geospatial methods may help target priority areas and planning VL surveillance in low and middle-income countries.