The paper reports on geodiversity assessments of three national parks in Poland, performed independently by experts and volunteers. Each national park selected for the study represents one of three ...morphogenetically different landscape types: mountains, uplands, and plains. The expert and volunteer assessment data sets were separately processed with two spatial multicriteria methods: Weighted Linear Combination (WLC) - also referred to in the paper as the global version of WLC, and Local Weighted Linear Combination (L-WLC) resulting in two geodiversity maps for each of the parks – one based on WLC and the other on L-WLC output data. The maps were qualitatively evaluated for their efficacy of capturing spatial heterogeneity and differentiating between high and low geodiversity of specific areas within the national parks. The expert-based maps were compared with the volunteer-based maps using statistical measures of association and similarity. The results show that L-WLC is more suitable for geodiversity mapping of mountainous areas characterized by high morphogenetic and morphometric diversity whereas WLC yields better results in less diverse areas such as uplands and lowlands. The use of data originating from volunteer-based assessment requires meeting internal and external data quality standards and should be treated with caution.
It is well-known that the research of linear combination of composition operators has become a topic of increasing interest. Recently, Choe, Koo and Wang proved that the compactness of combinations ...composition operators induced by the symbols satisfying the condition (CNC) implies that each difference is compact on the weighted Bergman space. Motivated by that work, in this paper, we discuss which difference is compact on the weighted Bergman space when the coefficients do not satisfy the condition (CNC).
Short‐TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as a linear combination of metabolite basis spectra. This large‐scale multi‐site study ...compares the levels of the four major metabolite complexes in short‐TE spectra estimated by three linear‐combination modeling (LCM) algorithms. 277 medial parietal lobe short‐TE PRESS spectra (TE = 35 ms) from a recent 3 T multi‐site study were preprocessed with the Osprey software. The resulting spectra were modeled with Osprey, Tarquin and LCModel, using the same three vendor‐specific basis sets (GE, Philips and Siemens) for each algorithm. Levels of total N‐acetylaspartate (tNAA), total choline (tCho), myo‐inositol (mI) and glutamate + glutamine (Glx) were quantified with respect to total creatine (tCr). Group means and coefficient of variations of metabolite estimates agreed well for tNAA and tCho across vendors and algorithms, but substantially less so for Glx and mI, with mI systematically estimated as lower by Tarquin. The cohort mean coefficient of determination for all pairs of LCM algorithms across all datasets and metabolites was
R2¯= 0.39, indicating generally only moderate agreement of individual metabolite estimates between algorithms. There was a significant correlation between local baseline amplitude and metabolite estimates (cohort mean
R2¯= 0.10).
While mean estimates of major metabolite complexes broadly agree between linear‐combination modeling algorithms at group level, correlations between algorithms are only weak‐to‐moderate, despite standardized preprocessing, a large sample of young, healthy and cooperative subjects, and high spectral quality. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.
Three linear‐combination algorithms (Osprey, Tarquin and LCModel) were used to quantify the levels of tNAA, tCho, mI, and Glx in 277 short‐TE PRESS. Group means and CVs of metabolite estimates agreed well for tNAA and tCho, but substantially less so for Glx and mI, with a cohort mean correlation coefficient of
R2¯= 0.39, indicating moderate agreement between algorithms. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.
Four series of Pb(Mg1/3Nb2/3)O3–Pb(In1/2Nb1/2)O3–PbZrO3–PbTiO3 (PMN–PIN–PZ–PT) quaternary ceramics with compositions located at the morphotropic phase boundary (MPB) regions were prepared. The ...MPBs of the multicomponent system were predicted using a linear combination rule and experimentally confirmed by X-ray powder diffraction and electrical measurement. The positions of MPBs in multicomponent systems were found in linear correlation with the tolerance factor and ionic radii of non-PT end-members. The phase structure, piezoelectric coefficient, electromechanical coupling coefficient, unipolar strains, and dielectric properties of as-prepared ceramics were systematically investigated. The largest d 33s were obtained at S36.8, L37.4, M39.6, and N35.8, with the corresponding values of 580, 450, 420, and 530 pC/N, respectively, while the largest k ps were found at S34.8, L37.4, M39.6, and N35.8, with the respective values of 0.54, 0.50, 0.47, and 0.53. The largest unipolar strain S max and high-field piezoelectric strain coefficients d 33* were also observed around the respective MPB regions. The rhombohedral-to-tetragonal phase transition temperature T rt increased with increasing PIN and PZ contents. Of particular importance is that high T rt of 140–197 °C was achieved in the M series with PZ and PIN contents being around 0.208 and 0.158, which will broaden the temperature usage range.
Landslides are a common hazard in the highly urbanized hilly areas in Chittagong Metropolitan Area (CMA), Bangladesh. The main cause of the landslides is torrential rain in short period of time. This ...area experiences several landslides each year, resulting in casualties, property damage, and economic loss. Therefore, the primary objective of this research is to produce the Landslide Susceptibility Maps for CMA so that appropriate landslide disaster risk reduction strategies can be developed. In this research, three different Geographic Information System-based Multi-Criteria Decision Analysis methods—the Artificial Hierarchy Process (AHP), Weighted Linear Combination (WLC), and Ordered Weighted Average (OWA)—were applied to scientifically assess the landslide susceptible areas in CMA. Nine different thematic layers or landslide causative factors were considered. Then, seven different landslide susceptible scenarios were generated based on the three weighted overlay techniques. Later, the performances of the methods were validated using the area under the relative operating characteristic curves. The accuracies of the landslide susceptibility maps produced by the AHP, WLC_1, WLC_2, WLC_3, OWA_1, OWA_2, and OWA_3 methods were found as 89.80, 83.90, 91.10, 88.50, 90.40, 95.10, and 87.10 %, respectively. The verification results showed satisfactory agreement between the susceptibility maps produced and the existing data on the 20 historical landslide locations.
Slope failure along highways is a crucial problem in hilly regions. Landslide hazard maps are very efficient and effective tools for planning and management of landslide disasters. Aim of this study ...is to prepare a landslide hazard map along national highway 5 (197.600–283.200 Km) using analytic hierarchy process (AHP) model. The different causative factors of landslides considered in this study are slope, aspect, curvature, relative relief, fault density, drainage density, geology, topographic wetness index (TWI), distance from road and lithology. The causative factors are divided into sub-factors and weightage are assigned according to analytic hierarchy process (AHP). The causative factor layers are overlaid using weighted linear combination (WLC) technique and a landslide hazard map is prepared. A landslide inventory of 215 landslides is used for validation of the landslide hazard map. The map shows a prediction rate of 0.825 on area under curve (AUC) technique. The study can be used by the construction planners and decision makers.
J‐difference‐edited spectroscopy is a valuable approach for the in vivo detection of γ‐aminobutyric‐acid (GABA) with magnetic resonance spectroscopy (MRS). A recent expert consensus article ...recommends linear combination modeling (LCM) of edited MRS but does not give specific details regarding implementation. This study explores different modeling strategies to adapt LCM for GABA‐edited MRS. Sixty‐one medial parietal lobe GABA‐edited MEGA‐PRESS spectra from a recent 3‐T multisite study were modeled using 102 different strategies combining six different approaches to account for co‐edited macromolecules (MMs), three modeling ranges, three baseline knot spacings, and the use of basis sets with or without homocarnosine. The resulting GABA and GABA+ estimates (quantified relative to total creatine), the residuals at different ranges, standard deviations and coefficients of variation (CVs), and Akaike information criteria, were used to evaluate the models' performance. Significantly different GABA+ and GABA estimates were found when a well‐parameterized MM3co basis function was included in the model. The mean GABA estimates were significantly lower when modeling MM3co, while the CVs were similar. A sparser spline knot spacing led to lower variation in the GABA and GABA+ estimates, and a narrower modeling range—only including the signals of interest—did not substantially improve or degrade modeling performance. Additionally, the results suggest that LCM can separate GABA and the underlying co‐edited MM3co. Incorporating homocarnosine into the modeling did not significantly improve variance in GABA+ estimates. In conclusion, GABA‐edited MRS is most appropriately quantified by LCM with a well‐parameterized co‐edited MM3co basis function with a constraint to the nonoverlapped MM0.93, in combination with a sparse spline knot spacing (0.55 ppm) and a modeling range of 0.5–4 ppm.
One hundred and two strategies to model GABA‐edited MRS with linear combination modeling were evaluated to quantify GABA and GABA+ in Osprey. Significantly different GABA and GABA+ estimates were found when a well‐parameterized macromolecule at 3 ppm was included. The findings suggest that linear combination modeling needs to be adapted for quantification of GABA‐edited MRS.
•Osprey is an open-source analysis toolbox for magnetic resonance spectroscopy data.•Includes pre-processing, linear-combination modelling, and quantification.•Includes a graphical user interface for ...visualization of each analysis step.
Processing and quantitative analysis of magnetic resonance spectroscopy (MRS) data are far from standardized and require interfacing with third-party software. Here, we present Osprey, a fully integrated open-source data analysis pipeline for MRS data, with seamless integration of pre-processing, linear-combination modelling, quantification, and data visualization.
Osprey loads multiple common MRS data formats, performs phased-array coil combination, frequency-and phase-correction of individual transients, signal averaging and Fourier transformation. Linear combination modelling of the processed spectrum is carried out using simulated basis sets and a spline baseline. The MRS voxel is coregistered to an anatomical image, which is segmented for tissue correction and quantification is performed based upon modelling parameters and tissue segmentation. The results of each analysis step are visualized in the Osprey GUI. The analysis pipeline is demonstrated in 12 PRESS, 11 MEGA-PRESS, and 8 HERMES datasets acquired in healthy subjects.
Osprey successfully loads, processes, models, and quantifies MRS data acquired with a variety of conventional and spectral editing techniques.
Osprey is the first MRS software to combine uniform pre-processing, linear-combination modelling, tissue correction and quantification into a coherent ecosystem. Compared to existing compiled, often closed-source modelling software, Osprey’s open-source code philosophy allows researchers to integrate state-of-the-art data processing and modelling routines, and potentially converge towards standardization of analysis.
Osprey combines robust, peer-reviewed data processing methods into a modular workflow that is easily augmented by community developers, allowing the rapid implementation of new methods.
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Modelling the rheological properties and chemical characteristics of asphalt material has been a hotspot. In this study, 20/40 and 60/80 pen grade asphalt binders named binder A and ...binder B were used to blend eleven binder samples. After that, a novel column chromatography was applied to collect sufficient SARA (Saturates, Aromatics, Resins and Asphaltenes). The Dynamic Shear Rheometer (DSR) test was used to develop the viscoelastic master curves for binders and their subsets. The Fourier Transform Infrared Spectroscopy (FTIR) test was conducted to identify and semi-quantitatively analyze the notable functional groups. Linear combination models were conducted between rheological model parameters and chemical components. It was found that the contents of Asphaltenes and Saturates increased, while those of Resins and Aromatics decreaed with the addition of binder A, resulting in the increased colloidal instability index (CII) values. In addition, the Saturates had constant value of phase angle, while the phase angle master curves of Aromatics and Resins showed plateau values of 80°. Resins containing more aromatic structures had a lower frequency (high temperature) value at this plateau value. Furthermore, the main findings were that ICC and ICH of Aromatics as well as ICH and ISO of Resins had significant relationships with binder A content. Statistically, several parameters such as CResins, CAsphaltenes, CII, ICC of Aromatics, ICH of Aromatics, ICH of Resins, and ISO of Resins had significant effects to develop multiple linear regression model on asphalt rheological properties.