Full Map Research Articles

A possible thermodynamic definition and equation of state for a model of political election cycles.

This work demonstrates how a simulation of political discourse can be formulated using variables of the agents' behaviors in a simulation, as thermodynamic variables. With these relations the methodology provides an approach to create a correspondence between the variables of an agent based social system and those of a thermodynamic system. Extended from this observation, diagrams akin to a P-V diagram for gases can be created for this social system. The basic thermodynamic variables of temperature, pressure and volume are defined from a system of agents with political and non-political actions engaged in simulated political discourse. An equation of state is defined for the simulated political phenomenon. Through this equation of state the full thermodynamic map of the system is presented under a P-V diagram with isothermal and isentropic lines, which is able to represent the political situation of the system at each point of time. The classic election cycle that takes place can be represented on this thermodynamic map (corresponding to an Otto cycle). This provides a possibility for researching macroscopic social cycles as a thermodynamic/informational cycle as the traces on the thermodynamic map show similarities to an Otto cycle. Such a formulation reinforces the endeavours of social physics to view social phenomena with physical principles.

Analysis and Improvement of Geographic Information Systems for Problem Solving and Decision Making

The complexity of our way of life has increased due to the numerous parts of life developing quickly, which results in ongoing issues. To address these issues and respond to these rapid changes in the environment, solutions that were practical, quick, and easy to implement were needed. The use of geographic information tools, a contemporary innovation, allows for the implementation of difficult issues by enhancing users' abilities to comprehend problems thoroughly through the analysis of spatial data and the creation of digital maps. This allows decision-makers to save time, effort, and money by making informed choices that will result in the best possible solution to the issue at hand. In addition to a significant urban expansion, an increase in the number of people using vehicles, and a significant emigration of people from rural and small towns, the traffic jams that have recently engulfed much of the world, particularly in the major capitals and cities, are a result of these factors for transportation, have contributed to a complex problem in modern times. The goal of this study is to examine proposed elements and gauge their impact on the issue of traffic bottlenecks. It then suggests both long- and short-term remedies for this issue based on the study's findings, which are generally not found in the pertinent departments. In order to create a unique surface for these components and provide a comprehensive picture of the research region, it also makes satellite photos of the area available. geographical database for each of them, evaluate each layer's influence on the traffic jam independently by analyzing it, and then merge these levels to create full map that shows their location and the extent to which they affect the study problems. This process was done in order to arrive at the aforementioned solution.

Self-Prompting Tracking: A Fast and Efficient Tracking Pipeline for UAV Videos

In the realm of visual tracking, remote sensing videos captured by Unmanned Aerial Vehicles (UAVs) have seen significant advancements with wide applications. However, there remain challenges to conventional Transformer-based trackers in balancing tracking accuracy and inference speed. This problem is further exacerbated when Transformers are extensively implemented at larger model scales. To address this challenge, we present a fast and efficient UAV tracking framework, denoted as SiamPT, aiming to reduce the number of Transformer layers without losing the discriminative ability of the model. To realize it, we transfer the conventional prompting theories in multi-model tracking into UAV tracking, where a novel self-prompting method is proposed by utilizing the target’s inherent characteristics in the search branch to discriminate targets from the background. Specifically, a self-distribution strategy is introduced to capture feature-level relationships, which segment tokens into distinct smaller patches. Subsequently, salient tokens within the full attention map are identified as foreground targets, enabling the fusion of local region information. These fused tokens serve as prompters to enhance the identification of distractors, thereby avoiding the demand for model expansion. SiamPT has demonstrated impressive results on the UAV123 benchmark, achieving success and precision rates of 0.694 and 0.890 respectively, while maintaining an inference speed of 91.0 FPS.

Coumarin Derivatives: The Influence of Cycloalkyl Groups at the C-3 Position on Intermolecular Interactions—Synthesis, Structure and Spectroscopy

In this study, we explore the synthesis and solid-state characterization of four coumarin-3-carboxylic acid esters, each modified at the C-3 position with different cycloalkyl groups: cyclohexyl, menthyl, and iso-pulegyl. We conducted a detailed analysis of these compounds utilizing a variety of techniques such as a single-crystal X-ray diffraction, nuclear magnetic resonance (NMR), and Fourier-transform infrared (FTIR) spectroscopy. Additionally, we calculated the dipole moments for these molecules. Our findings include a thorough structural assessment, highlighting the role of noncovalent interactions through Full Interaction Maps and Hirshfeld surface analysis. This study reveals the critical influence of the weak C-H…O hydrogen bonds in determining the solid-state architecture of these esters, whereas π-π stacking interactions appear to be negligible among the studied derivatives.

Evaluation of classical correlation functions from 2/3D images on CPU and GPU architectures: Introducing CorrelationFunctions.jl

Correlation functions are becoming one of the major tools for quantification of structural information that is usually represented as 2D or 3D images. In this paper we introduce ▪ open-source package developed in Julia and capable of computing all classical correlation functions based on imaging input data. Images include both binary and multi-phase representations. Our code is capable of evaluating two-point probability S2, phase cross-correlation ρij, cluster C2, lineal-path L2, surface-surface Fss, surface-void Fsv, pore-size P and chord-length p distribution functions on both CPU and GPU architectures. Where possible, we presented two types of computations: full correlation map (correlations of each point with other points on the image, that also allows obtaining ensemble averaged CF) and directional correlation functions (currently in major orthogonal and diagonal directions). Such an implementation allowed for the first time to assemble a completely free solution to evaluate correlation functions under any operating system with well documented application programming interface (API). Our package includes automatic tests against analytical solutions that are described in the paper. We measured execution times for all CPU and GPU implementations and as a rule of thumb full correlation maps on GPU are faster than other methods. However, full maps require more RAM and, thus, are limited to available RAM resources. On the other hand, directional CFs are memory efficient and can be evaluated for huge datasets – this way they are the first candidates for structural data compression of feature extraction. The package itself is available through Julia package ecosystem and on GitHub, the latter source also contains documentation and additional helpful resources such as tutorials. We believe that a single powerful computational tool such as ▪ presented in this paper will significantly facilitate the usage of correlation functions in numerous areas of structural description and research of porous materials, as well as in machine learning applications. We also present some examples as applied to ceramic, soil composite and oil-bearing rock samples based on their 3D X-ray tomography and 2D scanning electron microscope images. Finally, we conclude our paper with discussion of possible ways to further improve presented computational framework. Program summaryProgram Title: CorrelationFunctions.jlCPC Library link to program files:https://doi.org/10.17632/6gb9gfm3dw.1Developer's repository link:https://github.com/fatimp/CorrelationFunctions.jlLicensing provisions: MITProgramming language: JuliaSupplementary material: Numerous Jupiter notebooks with examples are available on the GitHub pageNature of problem: Correlation functions are invaluable universal statistical descriptors of structures used in numerous scientific fields such as astronomy, material science, rock and soil physics, hydrology and biology, to name just a handful of examples. While computational approaches are available in the literature for some functions, they are fragmented and are usually implemented in proprietary interpreted languages for CPU architecture alone.Solution method: We contribute an open source and cross-platform solution with well documented API for computation of all classical correlation functions from both 2D and 3D images on CPU and GPU architectures. The package computes correlation functions using two approaches: computation of correlation maps and computation along predefined directions. These two approaches can be thought of as an execution time - memory trade-off, but the choice may also depend on the application. The computations are based on a) fast Fourier transform with preprocessing steps such as cluster labeling or edge detection, and b) linear scan approach to evaluate correlation functions along predefined directions. Where justified, the algorithms can be executed on both CPU and GPU which results in high execution speed on modern hardware.

Effects of changing ions on the crystal design, non-covalent interactions, antimicrobial activity, and molecular docking of Cu(II) complexes with a pyridoxal-hydrazone ligand.

The present work reports the influence of the presence of different ions (Cl-, Br-, NO3 -, or SO4 2-) on the formation and proprieties of Cu(II) complexes with pyridoxal-benzoylhydrazone (PLBHZ). Four new complexes were successfully synthesized, [CuCl2(PLBHZ)] (1), [CuBr2(PLBHZ)] (2), [CuCl(PLBHZ)H2O]⋅NO3⋅H2O (3), and [CuSO4(PLBHZ)H2O]⋅3H2O (4), and characterized by spectroscopic and physicochemical methods. A single-crystal X-ray study reveals the Schiff base coordinated to the metal center tridentate by the ONS-donor system, resulting in distorted square pyramidal coordination geometries. Noncovalent interactions were investigated by 3D Hirshfeld surface analysis by the d norm function, 2D fingerprint plots, and full interaction maps. The ion exchange is important in forming three-dimensional networks with π⋅⋅⋅π stacking interactions and intermolecular hydrogen bonds. The in vitro biological activity of the free ligand and metal complexes was evaluated against Gram-positive and Gram-negative bacterial strains and the free pyridoxal-hydrazone ligand showed higher activity than their Cu(II) complexes. Molecular docking was used to predict the inhibitory activity of the ligand and complexes against Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli bacteria.

The Commonality and Individuality of Human Brains When Performing Tasks.

It is imperative to study individual brain functioning toward understanding the neural bases responsible for individual behavioral and clinical traits. The complex and dynamic brain activity varies from area to area and from time to time across the entire brain, and BOLD-fMRI measures this spatiotemporal activity at large-scale systems level. We present a novel method to investigate task-evoked whole brain activity that varies not only from person to person but also from task trial to trial within each task type, offering a means of characterizing the individuality of human brains when performing tasks. For each task trial, the temporal correlation of task-evoked ideal time signal with the time signal of every point in the brain yields a full spatial map that characterizes the whole brain's functional co-activity (FC) relative to the task-evoked ideal response. For any two task trials, regardless of whether they are the same task or not, the spatial correlation of their corresponding two FC maps over the entire brain quantifies the similarity between these two maps, offering a means of investigating the variation in the whole brain activity trial to trial. The results demonstrated a substantially varied whole brain activity from trial to trial for each task category. The degree of this variation was task type-dependent and varied from subject to subject, showing a remarkable individuality of human brains when performing tasks. It demonstrates the potential of using the presented method to investigate the relationship of the whole brain activity with individual behavioral and clinical traits.

Mapping a Lower Limit on the Mass Fraction of the Cold Neutral Medium Using Fourier-transformed H i 21 cm Emission Line Spectra: Application to the DRAO Deep Field from DHIGLS and the HI4PI Survey

We develop a new method for spatially mapping a lower limit on the mass fraction of the cold neutral medium by analyzing the amplitude structure of Tˆb(kv) , the Fourier transform of T b (v), the spectrum of the brightness temperature of the H i 21 cm line emission with respect to the radial velocity v. This advances a broader effort exploiting 21 cm emission line data alone (without absorption line data, τ) to extract integrated properties of the multiphase structure of the H i gas and to map each phase separately. Using toy models, we illustrate the origin of interference patterns seen in Tˆb(kv) . Building on this, a lower limit on the cold gas mass fraction is obtained from the amplitude of Tˆb at high k v . Tested on a numerical simulation of thermally bi-stable turbulence, the lower limit from this method has a strong linear correlation with the “true” cold gas mass fraction from the simulation for a relatively low cold gas mass fraction. At a higher mass fraction, our lower limit is lower than the “true” value, because of a combination of interference and opacity effects. Comparison with absorption surveys shows a similar behavior, with a departure from linear correlation at N H I ≳ 3–5 × 1020 cm−2. Application to the DRAO Deep Field from DHIGLS reveals a complex network of cold filaments in the Spider, an important structural property of the thermal condensation of the H i gas. Application to the HI4PI survey in the velocity range −90 < v < 90 km s−1 produces a full sky map of a lower limit on the mass fraction of the cold neutral medium at 16.′2 resolution. Our new method has the ability to extract a lower limit on the cold gas mass fraction for massive amounts of emission line data alone with low computing time and memory, pointing the way to new approaches suitable for the new generation of radio interferometers.

Two-component Supramolecular Adduct based on Hydroxyl Substituted Triptycene with 4,4’-bipyridine: Crystal Structure Analysis

A new cocrystal solvate possessing 2,7,14-trihydroxytriptycene (THT) and 4,4′-bipyridine (bpy) was grown from a MeOH solution by solvent evaporation to form THT·0.5bpy·MeOH·H2O (1).The crystal structure of 1 was determined by single-crystal X-ray diffraction in the monoclinic space group C2/c. In the new cocrystal solvate (1), the asymmetric unit consists of one unit of THT, a half unit of disordered bpy, one unit of a water molecule and one MeOH molecule. A 2D supramolecular architecture is observed in (1) linking THT, bpy and solvent water molecules via classical O-H···N and O-H···O hydrogen bonds. The MeOH and water molecules entrapped in (1) form stabilizing hydrogen bondswith the surrounding “trimeric cocrystals.” Furthermore, we investigated whether these hydrogen bonds stabilize the crystal packing. The calculations were carried out using Hydrogen Bond Statistics and Full Interaction Maps packages, and the results exhibit common bonding behaviour in terms of bond distances and strength.

UltraSOUND-based characterization of ventricular tachycardia SCAR and arrhythmogenic substrate: The SOUNDSCAR study

BackgroundIntracardiac echocardiography (ICE) represents a valuable image integration technique, with the unique advantage of dynamic real-time scar characterization. ObjectivesThe goals of this study were to assess the correlation between ICE-defined and electroanatomic mapping (EAM)–defined scar in patients with ischemic cardiomyopathy and to define the outcomes of ICE-guided ventricular tachycardia (VT) ablation. MethodsThirty-eight patients with ischemic cardiomyopathy (SOUNDSCAR cohort) underwent full left ventricular (LV) ICE imaging and EAM. ICE-defined scar parameters (end-diastolic and end-systolic wall diameter [EDWD and ESWD], end-systolic wall thickening [percentage difference between EDWD and ESWD with respect to EDWD], slope [end-diastole to end-systole wall thickening], and American Heart Association wall motion scoring) were correlated with EAM-defined scar (voltage <1.5 mV). In a separate cohort (n = 21), outcomes of an ICE-guided VT ablation approach (EAM focused to ICE-defined scar regions) were compared with those of conventional ablation (full left ventricular mapping with EAM only; n = 21). ResultsIn the 38 SOUNDSCAR patients (mean age 67 ± 11 years; 35 male [92%]; left ventricular ejection fraction 31% ± 10%; 2474 ICE segments; 524 ICE sectors), all ICE-defined parameters strongly predicted EAM-defined scar (area under the curve: American Heart Association score 0.873; ESWD 0.880; EDWD 0.827; slope 0.855; percentage difference between EDWD and ESWD with respect to EDWD, 0.851). All ICE-defined parameters had large effect sizes for predicting EAM-defined scar (logistic regression, P < .001). A detailed topographical comparison of ICE-defined (slope) and EAM-defined scar was possible in 25 patients and demonstrated 88% ± 10% overlap. Compared with conventional VT ablation, ICE-guided ablation was associated with shorter procedure times and comparable VT-free survival (ICE-guided vs conventional: procedure time 240 ± 20 minutes vs 298 ± 39 minutes; P < .001; VT recurrence 3 [14%] vs 7 [31%]; P = .19). ConclusionICE-defined scar demonstrates a strong correlation with EAM-defined scar. ICE-guided VT ablation is associated with enhanced procedural efficiency.

Navigating Nonlinear Analysis and Artificial Intelligence Frontiers for Revolutionary Technology Solutions

The intersection of nonlinear analysis and artificial intelligence (AI) presents a promising frontier in the rapidly changing field of technology, with the potential to yield ground-breaking solutions in a multitude of fields. In order to investigate how different disciplines may work together to transform technological progress, this study explores the synthesis of these fields. Deeper comprehension of complicated patterns and behaviours is made possible by the intersection of AI and nonlinear analysis, which can both model complex systems and events. This combination has the potential to go beyond conventional linear thinking and open doors to solve complex problems. Through the utilisation of AI's learning skills to augment nonlinear models, a novel approach to problem-solving is revealed. The purpose of the paper is to examine the applications of this synergy in various disciplines. The combination of nonlinear analysis and AI holds the potential to transform a number of industries, from banking and predictive analytics to biological systems research and autonomous vehicle development. This investigation also includes the societal and ethical ramifications of using such cutting-edge technologies. It aims to provide a thorough understanding of the factors necessary for the ethical integration of these advances into our lives by delving into concerns of privacy, prejudice, and responsible use. This study tries to give academics, engineers, and innovators a full road map by looking at recent advances and possible future possibilities. It seeks to stimulate novel research directions, interdisciplinary teamwork, and the advancement of ground-breaking technical innovations that have the potential to fundamentally alter our understanding of and interactions with the environment around us.

Strain Measurement with Optic Fibers for Structural Health Monitoring of Woven Composites: Comparison with Strain Gauges and Digital Image Correlation Measurements.

In this work, the strains measured with optic fibers and recorded during tensile tests performed on carbon/epoxy composite specimens were compared to those recorded by strain gauges and by Digital Image Correlation (DIC). The work aims at investigating the sensitivity of embedded and glued optic sensors for structural health monitoring applications in comparison with strain gauges and the full field strain map of the DIC. Acrylate, polyimide optic fibers, and three strain gauge sizes are considered to compare the three techniques. Results show hard polyimide-coated sensors are more sensitive to the material pattern than soft acrylate-coated fibers, which also require extensive adhesion length. The work shows a comparable size of strain gauges and material meso-structure is also critical for properly assessing material properties. The Young's modulus computed with the three different techniques is used to define a strategy that supports the selection and the proper size of the adopted strain measuring system for structural health monitoring of composite materials.

Generating Seed Mappings for Machine Learning-Based Code-to-Architecture Mappers Using InMap

Software architecture consistency checking (SACC) is a popular method to detect architecture degradation. Most SACC techniques require software engineers to manually map a subset of entities of a system's implementation onto elements of its intended software architecture. Manually creating such a "seed mapping" for complex systems is a time-consuming activity. The objective of this paper is to investigate if creating seed mappings semi-automatically based on mapping recommendations for training automatic, machine learning-based mappers can reduce the effort for this task. To this end, we applied InMap, a highly accurate, interactive code-to-architecture mapping approach, to create seed mappings for five opensource systems with known architectures and mappings. Three different machine learning-based mappers were trained with these seed mappings and analysed regarding their predictive performance. We then compared the manual effort involved in using the combination of InMap and the most accurate automatic mapper and the manual effort of mapping the systems solely with InMap. The results suggest that InMap, with a minor adaption, can be used to seed an accurate mapper at a size of 20--25% based on Naive Bayes. A full mapping with only InMap though turns out to involve slightly less manual effort on average; this is, however, not consistent across all systems. These results give evidence that more advanced ways of combining automatic mappers with InMap may further reduce that effort.

The FALCON double-detector Laue diffractometer add-on for grain mapping at POLDI

Laue 3D neutron diffraction tomography (Laue 3DNDT) is a novel tomographic approach that enables non-destructive resolution of the 3D microstructure of polycrystalline materials, utilizing a high-intensity white beam of neutrons, resulting in high experimental efficiency. This article describes the functionality of the fast-acquisition Laue camera for neutrons (FALCON), a double-detector system setup used for Laue 3DNDT experiments at the pulse-overlap diffractometer (POLDI) at the SINQ neutron source of the Paul Scherrer Institute. The reported commissioning includes standard experimental protocols, strategies for acquiring data and a detailed characterization of the measurement system. Finally, single-crystal measurements for calibration and a full grain map of a CoNiGa oligocrystalline sample, extracted from a pilot study, are presented. A detailed understanding of the performance of the FALCON instrumentation is vital for the future advancement of the Laue 3DNDT algorithm, including, but not limited to, improved morphology reconstructions and strain mapping.

Seismic attributes and quantitative inverse dynamical simulations for characterization of late Cretaceous classical fluvial meander channelized stratigraphic traps system, onshore Indus, Pakistan: Implications for hydrocarbon exploration

Meandering channel systems and point bars (PBRL) of the fluvial depositional system (FDPS) globally form primary stratigraphic traps (PST). These ultra-thin-bedded and sub-seismic features are developed during rising sea-levels (transgressive) and standstill (aggradational parasequences) inside the transgressive system tract (TST). The aggradational parasequences of TST have coarse-grained sandstone-filled PSTs, which have specific thickness, density, velocity, angle of the sedimentary reserves, and depositional and erosional characteristics for the development of seismic reflection configurations. All these implications are the key controlling factors for developing the aggrading parasequence sets of TST throughout a sea-level standstill, which is not feasible to predict using the full spectrum-based time and depth mapping tools. The full spectrum-based amplitude volumes lack the tuning frequency content for achieving the above-addressed implications. They require sophisticated tuned-frequency amplitudes, which are responsible to resolve these PSTs when they are filled with porous (Ps) and gas-saturated (Sgas) sedimentary facies, and hence, they show unique seismic-based expressions (velocity and density). Therefore, all these implications are achieved in this study by operating the spectral attributes and the instantaneous spectral decomposition-based velocity and density reservoir simulations (SVDRS) on a hydrocarbons-producing arena, onshore Indus, Pakistan. The tuning thickness for this FDPS was 8.75 m. The 42-Hz spectral attribute shows ∼13 m parallel and wavy seismic reflection configurations, but failed in predicting the horizontally deposited PST, simulated density and velocity, shelf or basin plain, and lateral distribution of Sgas and Ps point bars along the subsidence zones. SVDRS have predicted the ∼86–95% Sgas; ∼31–35% Ps; 14–16 m thick (on inverted density simulation); 2453–2500 m/s velocity; inside the 2.2–2.3 g/c.c densely-fractured and inclined (<3°) aggradational parasequences with parallel reflection configurations for high sinuosity index (S.I) > 2.2 PBRLs, which implicates the presence of a meandering channelized reservoir stream. These stratigraphic configurations implicate the low-risk and highly rewarding hydrocarbon prospecting zones due to no spilling out of the hydrocarbon from the PST during the sea-level standstills. These hydrocarbon-bearing PBRLs have a lateral extent of >2 km, which is an appreciable signature of velocity and densities to develop these traps as the future stratigraphic prospect. These PBRLs with >90% Sgas and >32% Ps of PST are completely embedded within the topmost and horizontal regions with transgressive shales facies (seal) of TST and low-Ps shaly-sandstones, which implicates the landward shifting of shoreline during the sea-level rising events. The uncertainty analysis for simulated velocity and density validates a strong R2>0.85% and 0.90% along the high sinuosity index (S.I.)>2.2 implicates the presence of meandering channel streams., which have implicated the presence of non-Ps and water-statured (Sw) retrogradational parasequences. This workflow has developed this FDPS into a pure stratigraphic trap, and hence, the presented scheme of exploration may serve to explore the remaining reserves from the exploration zones for global FDPS.

Io’s polar volcanic thermal emission indicative of magma ocean and shallow tidal heating models

The distribution of Io’s volcanic activity probably reflects the position and magnitude of internal tidal heating, but full mapping of the moon has not been possible due to a lack of polar coverage. Here we use new observations of Io’s polar regions by the Juno spacecraft Jovian Infrared Auroral Mapper to complete near-infrared coverage, revealing the global distribution and magnitude of thermal emission from Io’s currently erupting volcanoes. We show that the distribution of volcanic heat flow from 266 active hot spots is consistent with the presence of a global magma ocean and/or shallow asthenospheric heating. We find that Io’s polar volcanoes are less energetic but approximately the same in number per unit area than those at lower latitudes. We also find that volcanic heat flow in the north polar cap is greater than that in the south. The low volcanic advection seen at Io’s poles is therefore at odds with measurements of background temperature, showing that Io’s poles are anomalously warm. We suggest that the differences in volcanic thermal emission from Io’s poles compared with those at lower latitudes are indicative of lithospheric dichotomies that inhibit volcanic advection towards Io’s poles, particularly in the south polar region.

A Comparative Azeotropic Research on Combustion of Common Ternary Systems

Methyl Tertiary Butyl Ether (MTBE) and Methanol are effective fuel oxygenate that boost octane number, improve fuel performance, combustion behavior and minimize environmental pollutant emissions. In the petroleum business, however, their high-water solubility restricts their use in terms of fuel homogeneity loss. This work presents a full investigation map for the status of the phase diagram for the tertiary system of MTBE-methanol-water at different temperatures; 0, 40, and 70oC, and different pressures; 1.0 and 3.0 atm, based on different compositions. Furthermore, the thermodynamic coefficient, UNIFAC-LL, was linked to the Aspen plus Version 9. After validation of the software by the real experimental data, the software was used to complete the full map at all missing conditions. Pressure does not influence the occurrence of phase transitions, but the temperature has a minor effect on the LLE. The methanol concentration at which phase separation occurred dropped from 43% to 31.2% when the temperature was lowered from 70 to 40°C. With the use of simulation, the compositions at which phase separation occurs were also discovered. Last but not least, it was observed that the thermodynamic model (UNIFAC-LL) properly predicted the behavior of the methanol-water–MTBE ternary system with less than 3% inaccuracy in the binodal curve points. Consequently, a validated phase diagram is developed to accurately predict the physical state of the MTBE-methanol-water system at ant temperature, pressure, and mole fraction of each component. Hence, it guarantees the feasibility of using this tertiary system, as an effective octane booster additive, under severe working conditions.

Improving Coronal Hole Detections and Open Flux Estimates

One systematic limitation of solar coronal hole (CH) detection at extreme ultraviolet (EUV) wavelengths is the obscuration of dark regions of the corona by brighter structures along the line of sight. Another problem arises when using CHs to compute the Sun’s open magnetic flux, where surface measurements of the radial magnetic field, , are situated slightly below the effective height of coronal EUV emission. In this paper, we explore these two limitations utilizing a thermodynamic magnetohydrodynamic (MHD) model of the corona for Carrington rotation (CR) 2101, where we generate CH detections from EUV 193 Å images of the corona forward-modeled from the MHD solution, and where the modeled open field is known. We demonstrate a method to combine EUV images into a full Sun map that helps alleviate CH obscuration called the minimum intensity disk merge (MIDM). We also show the variation in measured open flux and CH area that is due to the effective height differences between EUV and measurements. We then apply the MIDM method to SDO/AIA 193 Å observations from CR 2101, and conduct an analogous analysis. In this case, the MIDM method uses time-varying images, the effects of which are discussed. We show that overall, the MIDM method and an appreciation of the effective height mismatch provide a useful new way to extract a broader view of CHs, especially near the poles. In turn, they enable improved estimates of the open magnetic flux, and help facilitate comparisons between models and observations.

Perception-guided defocus blur detection based on SVD feature

Defocus blur detection aims to identify out-of-focus regions in a single image. Although defocus blur detection has attracted more and more attention in recent years, it still faces some challenges. In particular, the in-focus regions with low contrast are easily misidentified as out-of-focus regions. To address this problem, a perception-guided defocus blur detection method is proposed to estimate defocus blur amounts at edge locations from a single image based on the singular value decomposition (SVD) features. Inspired by the fact that blurring the clear region produces significant changes in SVD domain as compared with re-blurring the blurred one, new SVD features are extracted based on re-blurred singular value difference (RESVD) of the corresponding local gradient patches. Then, perceptual weight based on Just Noticeable Blur (JNB) is introduced to guide the sparse blur map estimation obtained with the SVD features. Finally, the full defocus blur map is constructed from the sparse defocus blur map by the Matting Laplace algorithm. Visual evaluations are conducted on the CUHK, DUT and CTCUG datasets, employing mean absolute error (MAE) and Fβ-measure as quantitative evaluation metrics. The experimental results demonstrate that the proposed defocus blur detection method is superior to 13 state-of-the-art methods. On the DUT dataset, the proposed method yields a high Fβ-measure (0.802) with a low MAE (0.081) compared to other methods (Fβ≤0.799, MAE ≥0.099). On the CUHK and CTCUG datasets, our method achieves the best balance between Fβ-measure and MAE. Furthermore, our method results in better visual effects than other methods regarding realism and quality.

Geobody estimation by Bhattacharyya method utilizing nonlinear inverse modeling of magnetic data in Baba-Ali iron deposit, NW Iran

One of the essential geophysical concerns is the estimation of the physical and geometrical parameters of the reserve (geobody), which is done by exploiting the nonlinear inverse modeling of magnetic data. The present study includes preparing and modeling magnetic data to suggest the Baba Ali Iron ore deposit's drilling locations in NW Iran. The area is covered with 1000 points of geomagnetic reading with an almost 5 × 10 m2 regularly spaces grid trending WE. The areal and depth extent of the iron ore geobody was unknown. The Bhattacharyya method by MATLAB software coding was employed to underestimate the misfit function and re-construct potential field data, providing the most suitable fitting with measured magnetic data. In this order, the residual calculated anomaly exhibited an excellent two-dimensional conformation with forward modeling. Furthermore, 3D modeling correctly reconstructs the anomalies' productive resources' properties. After preparing full magnetic maps, the magnetic lenses distinguished in four anomalies of surface depths, 20, 50, and deeper than 50 m for this zone. This magnetite lens for the first zone was estimated based on analytical signal filters applied on the entire magnetic map so that the lens's depth is trivial and almost zero. Due to specific gravity calculated as 4.77 t/m3, initial storage capacity is suggested to be about 95,400 tons of magnetite, pyrite, and hematite minerals at most in an area about 6 Km2. Finally, to complete the preliminary explorations of the specified area, exploratory drilling is suggested for three points by inverse modeling. Regarding this study as the first try in magnetic reconnaissance step of Iron mineral exploration in the study area, there is no geological constraints available based on drilling evidences. However, the model is well satisfies the surface anomalies considering residual magnetic property.