Quantitative Interpretation Research Articles

Objective interpretation of ultraviolet-induced luminescence for characterizing pictorial materials

Ultraviolet-induced Luminescence (UVL) is the property of some materials of emitting light once illuminated by a source of UV radiation. This feature is characteristic of some mediums and pigments, such as some red lakes, widely used for the realisation of works of art. On the one hand, UVL represents a like strike for a researcher in the cultural heritage field: in fact, UVL allows to characterise the state of conservation of the paintings and, in some cases, to recognize at glance some of the materials used by the artists. On the other hand, the contribution of UVL to the study of the artefacts is almost always limited to qualitative observation, while any speculation about the cause of the luminescence emission relies on the observer’s expertise. The aim of this paper is to overcome this paradigm, moving a step toward a more quantitative interpretation of the luminescence signal. The obtained results concern the case study of pictorial materials by Giuseppe Pellizza da Volpedo (1868–1907, Volpedo, AL, Italy) including his iconic masterpiece Quarto Stato (1889–1901), but the method has general validity and can be applied whenever the appropriate experimental conditions occur. Once designed an appropriate set-up, the statistical comparison between the acquisitions performed on Quarto Stato, on a palette belonged to the master, on drafts made by the author himself and on a set of ad hoc prepared samples both with commercial contemporary pigments and prepared with the traditional recipe, shed some light on which materials have been employed by the artist, where they have been applied and support some intriguing speculations on the use of the industrial lakes in the Quarto Stato painting.

Understanding the formation process of negative customer engagement behaviours: a quantitative and qualitative interpretation

The development of mobile internet has made it easier for negative emotions, cognitions and behaviours expressed by customers to be spread, and the damage caused by negative customer engagement behaviours (NCEBs) to the company's brand value and reputation has gradually been amplified. Therefore, this study aims to explore the formation process of NCEBs in online brand community by combining qualitative method with quantitative method. Xiaomi Community was selected as the data source platform, using Python programming language to crawl users’ comments in ‘11Ultra circle’ and machine learning methods to obtain negative emotional polarity comments. The text coding and classification of negative emotion polarity comments are mainly based on manual coding and supplemented by machine learning. Perform binary logistic regression on the classified data to obtain the impact of various factors on NCEBs. The results showed that there were differences in the impact of different factors on NCEBs. This article obtains a different result from existing literature, that is, cognition and emotion are no longer necessary factors for the generation of NCEBs. Company managers should start with pricing, users’ cognition mining, and identifying and solving key issues reported by users to suppress the occurrence of NCEBs.

Reconstructing subglacial lake activity with an altimetry-based inverse method

Abstract Subglacial lake water-volume changes produce ice-elevation anomalies that provide clues about water flow beneath glaciers and ice sheets. Significant challenges remain in the quantitative interpretation of these elevation-change anomalies because the surface expression of subglacial lake activity depends on basal conditions, rate of water-volume change, and ice rheology. To address these challenges, we introduce an inverse method that reconstructs subglacial lake activity from altimetry data while accounting for the effects of viscous ice flow. We use a linearized approximation of a Stokes ice-flow model under the assumption that subglacial lake activity only induces small perturbations relative to a reference ice-flow state. We validate this assumption by accurately reconstructing lake activity from synthetic data that are produced with a fully nonlinear model. We then apply the method to estimate the water-volume changes of several active subglacial lakes in Antarctica by inverting data from NASA's Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) laser altimetry mission. The results show that there can be substantial discrepancies (20% or more) between the inversion and traditional estimation methods due to the effects of viscous ice flow. The inverse method will help refine estimates of subglacial water transport and further constrain the role of subglacial hydrology in ice-sheet evolution.

Quantitative and qualitative interpretation of community partitions by map overlaying and calculating the distribution of related geographical features

Abstract Applying community detection algorithms in spatial interaction networks constructed from modern human communication records is an essential means of evaluating urban territorial subdivisions. Previous studies have usually involved qualitative rather than quantitative interpretations of community detection results. This article proposes a method of quantitatively and qualitatively interpreting community partition results by map overlaying the spatial regions corresponding to the detected communities with the related geographical features and by calculating the distribution of the geographical features contained in the regions and the entropy value of each distribution. The interpretation of the communities detected from the spatial interaction networks is carried out from the perspective of multi-temporal and multi-spatial scales and multi-geographical features. Extensive experiments were conducted with Milan, Italy, as the study area. The spatial interaction records reflected by telephone calls, land use, and point of interest (POI) data were used as the experimental data. Experimental results demonstrated the effectiveness of our method, and the specific results include: (1) Qualitative interpretation of multi-spatial resolution scale communities detected from the long-term aggregated spatial interaction network. The cohesiveness, homogeneity, and heterogeneity of the detected communities were qualitatively interpreted by the spatial distribution patterns of the land use dataset and the POI dataset. (2) Quantitative interpretation of multi-spatial resolution scale communities detected from the long-term aggregated spatial interaction network. The low spatial resolution scale community partitions and the high spatial resolution scale community partitions were interpreted through the statistical distribution of the land use dataset and the POI dataset, respectively. (3) Qualitative interpretation of the stable and active regions discovered from the community time series. Regardless of the community partitions’ spatial resolution scales, the stable and active regions were distinguished with the statistical distributions of the land use dataset and the POI dataset.

Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images

Reliable detection and characterization of water ice on the Martian surface is pivotal to not only understand its present and past climate, but to also provide valuable information on in-situ resource availability and distribution for future human exploration missions. Ice-rich features are currently identified with visible/near-IR (VNIR), thermal IR and radar data. However, their coarse spatial scale sometimes limits confident characterization of small (i.e., meter-scale) icy exposures resulting from recent activity like new impacts. Water ice bearing materials possess weaker spectral characteristics at wavelengths shorter than ∼1030 nm that may be resolved by VNIR imaging instruments like the High Resolution Imaging Science Experiment (HiRISE) and the Colour and Stereo Surface Imaging System (CaSSIS). Our study assesses the spectral capability of HiRISE colour observations to help distinguish high purity water ice exposures from ice-poor materials. We report detailed methodologies for reliable colour characterization of icy surface using unfiltered HiRISE images. We present the first quantitative approach to uniquely characterize high-purity ice-rich materials through spectral shape and spectral parameterization methods at high spatial resolution (∼50 cm/pixel). We also present three spectral parameters to aid detection of pure water ice features, while also providing statistical constraints to enable a quantitative interpretation scheme. Our methods are observed to work well in characterizing and separating ice-rich features uniquely from ice-poor and ferrous materials. However, we do observe that these methods have a lower grain size detection limit of ∼250–300 μm, and may not be able to uniquely separate frosts from ground ice exposures. We also apply these methods to better constrain the composition of bright materials exposed by recent impacts identified in previous surveys, where substantial evidence for ice-bearing materials was previously unavailable. Overall, our work proposes HiRISE colour-based methods as a novel approach for high-resolution multispectral characterization of ice-rich features on the Martian surface, which is of particular value since the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has ceased operations.

Application of Vertical Electrical Sounding (VES) for the Determination of Water-Bearing Zone in Karaworo, Lokoja Kogi State, Nigeria

The importance of water in our various communities and the difficulties faced so far to get good and clean water for both domestic consumption and industrial purposes can never be overemphasized. For these purposes to be accomplished, it is necessary to survey the area of study to know more about the geology of the area, which is characterized by the Lokoja Formation, Patti Formation, and Agbaja Ironstone and the possible reasons why there is a lack of water in the area. The geoelectric survey was conducted at Karaworo with the objective of determining the sedimentary formation's geoelectrical features and analyzing the potential of the groundwater in the study area. The most frequently used type of array for Vertical Electrical Sounding (VES) is the Schlumberger array, which needs a lot of space at both ends to yield deeper subsurface information. The Schlumberger configuration was used for data acquisition. About fifteen (15) VES points were acquired at different locations within the study area. For the different VES positions, the maximum AB/2 is within 100m to 180m. Partial curve matching was used to determine the layer parameters as part of the quantitative interpretation of the VES curves. The IP2WIN software was used in the final data analysis. The depth sounding interpretation revealed subsurface layers which comprises of topsoil/clay with a resistivity range between 1.42 ohm-m to 81.0ohm-m and a thickness of 0.253 m to 70.4 m, lateritic clay with a resistivity range between 01.06ohm-m to 1730 ohm-m and a thickness of 0.236 m to 19.2 m, siltstone with resistivity range between 0.423 ohm-m to 5069 ohm-m and a thickness of 4.09 m to 28 m and sandstone with resistivity range between 0.664 ohm-m to 137 ohm-m with the thickness at infinity. Sandstone constituted the aquiferous zone. In conclusion, different types of curves which include HA-type, H-type, KH-type, QH-type and HAK-type characterize the area and hence it is suggested that boreholes be placed in low resistivity zones and considerable depth and thickness as revealed in VES 4 and VES 8 but those with low resistivity without considerable depth, for example, VES 2, VES 5, VES 6, VES 7, etc. can be developed into a hand dug well.

Quantitative and Qualitative Exploration of Meaningful Change on the Vineland Adaptive Behavior Scales (Vineland™-II) in Children and Adolescents with Autism Without Intellectual Disability Following Participation in a Clinical Trial.

The VinelandTM Adaptive Behavior Scale is often used in autism spectrum disorder (ASD) trials. The Adaptive Behavior Composite Score (VABS-ABC) is the standardized overall score (the average of the Socialization, Communication and Daily Living skills domains), and the standardized 2-Domain Composite Score (VABS-2DC) is a novel outcome measure (average of the Socialization and Communication domains). A within-person meaningful change threshold (MCT) has not been established for the VABS-2DC. This paper presents a quantitative and qualitative interpretation of what constitutes a meaningful change in these scores to individuals with ASD without Intellectual Disability (ID; IQ≥70) and their families, as reported by their study partners (SPs). Data were obtained from the aV1ation clinical trial in children and adolescents with ASD and associated exit interviews. The intent-to-treat (ITT) clinical trial population included 308 individuals with autism (85.4% male; average age: 12.4 years [standard deviation (SD)=2.97]); 124 in the child cohort (aged 5 to 12 years; average age: 9.4 years [SD=1.86]), and 184 in the adolescent cohort (aged 13 to 17 years; average age: 14.5 years [SD=1.39]). Study partners of 86 trial participants were included in the Exit Interview Population (EIP): participants represented were 83.7% male, average age: 12.3 years [SD=2.98]). Anchor and distribution-based methods were used to estimate within-person change to support a responder definition, to aid interpretation of the clinical trial data; qualitative data were used to contextualize the meaning of changes observed. A within-person MCT range of 4 to 8 points was proposed for both VABS-ABC and VABS-2DC, which was associated with at least a 1-point improvement on 4 different anchors. Evidence for this within-person MCT was further supported by qualitative data, which suggested any change was considered meaningful to the individual with ASD, as reported by their SP, no matter what the magnitude. A change in standardized score of 4 to 8 points constitutes a within-person MCT on both VABS-ABC and novel VABS-2DC in those with ASD and no ID. A change of this, or more, was reported by the SPs in this trial to be meaningful and highly impactful upon the individuals with ASD and their family.

Physical and Chemical Stability of Nanoparticles in Ferrofluid Before and After Impregnation: Implications for Magnetic Pore Fabric Studies

AbstractMagnetic pore fabrics (MPFs) are a promising approach to explore the 3D pore space of rocks. There exist empirical relationships between the orientation, degree, and shape of MPF with pore space geometry and permeability anisotropy. Nevertheless, the precise nature of these relationships remains elusive. A common assumption in MPF studies is that ferrofluid uniformly fills the pore space, establishing a constant nanoparticle density and magnetic properties in space and time. However, this assumption is challenged by observations of particle sedimentation and time‐dependent magnetic properties, which render the quantitative interpretation of MPFs challenging. This study explores the physical and chemical stability of ferrofluid, mobility of particles after impregnation, and the magnetic properties of impregnated rocks over time. Water‐based ferrofluids are physically more stable than oil‐based ferrofluids, though with higher magnetic variability. In impregnated rock, magnetic nanoparticles display a certain degree of mobility, resulting in changes in MPF degree and shape. When ferrofluid is mixed with epoxy, particles are less mobile, though some changes were observed both during polymerization and aging. The susceptibility of ferrofluid‐epoxy mixtures is lower than for ferrofluid and carrier liquid at the same concentration. Interestingly, the susceptibility of impregnated rock increases over time, regardless of the ferrofluid used for the impregnation. Understanding and controlling these processes will enhance the reliability of MPF interpretations and increase the applicability of the method.

A Workflow for Interpretation of Fracture Characteristics Based on Digital Outcrop Models: A Case Study on Ebian XianFeng Profile in Sichuan Basin

Abstract Collecting information about fracture attributes through outcrops measurement is crucial for analyzing the scale, distribution, orientation, and spatial arrangement of fractures. The emergence of digital outcrop models (DOMs) provides a new technology for quantitative interpretation of fractures. However, large-scale DOMs pose additional challenges to the practical application, particularly in the interpretation of geological elements (e.g. fractures). This research proposes a workflow for fracture characteristics interpretation based on DOMs. First, DOMs are generated using light detection and ranging scanning technology. Then, a 3D visualization platform is developed based on OpenSceneGraph. We use level-of-detail technology to reconstruct DOMs for multiscale fast visualization of large-scale models. Finally, in order to realize the quantitative interpretation of fractures, we propose the best-plane fitting and the feature information (orientation, length, spacing, etc.) extraction methods for two types of fractures (exposed fracture walls and fracture traces). The proposed methods are applied to extract attributes of fractures in Dengying Formation (second member), Ebian, Xianfeng, southwest Sichuan Basin, China. The results provide the basis for reservoir evaluation in this area.

Deriving mineral moduli of the noncarbonate fraction in a marly chalk reservoir using petrophysical logging data and an isoframe model

Knowledge of the elastic properties of clays and clay-rich sediments is essential when performing quantitative seismic interpretation and geomechanical modeling of reservoirs where they are present. Such is the case for the marly chalk reservoirs of Lower Cretaceous age in the Danish North Sea. We develop a new method to derive the elastic properties of the clay-rich insoluble residue (IR) fraction in marly chalks, using petrophysical logs and rock physical modeling. We calculate compressional ( M), shear ( G), and bulk ( K) moduli of the formation along the borehole using the density and sonic (shear and compressional) logs and model the elastic properties of minerals using the isoframe (IF) rock-physics model. In our model, the marly chalk is composed of two materials: calcite, with well-known elastic properties, and the IR fraction, whose elastic properties are the sought variable. We systematically vary the assumed elastic properties of the IR fraction, each time achieving equality between the measured and modeled elastic moduli solving for the IF values of calcite ([Formula: see text]) and IR fraction ([Formula: see text]) for each of the three elastic parameters one at a time, deriving the modeled values for the other two. We add up the error between the modeled and logged values for each set of assumed elastic properties of the IR fraction. We adopt the values of [Formula: see text] and [Formula: see text] that minimize the compound error as the actual elastic properties of the IR fraction. We run the algorithm in the Boje-2C and Valdemar-2H wells in different stratigraphic units of the Lower Cretaceous: the Fanø Formation and the marly chalk of the Tuxen and Sola formations. Elastic properties derived for the IR fraction compare well to data for wet clays from ultrasonic velocity laboratory tests. In a clean chalk section (almost 100% calcite), the model outputs values similar to calcite.

Topographical effect of high embankments on resistivity investigation of the underlying permafrost table

AbstractInvestigation of resistivity has been effectively used in assessing the risks of embankmentation and failure. A two‐dimensional (2D) approximation of the surveyed object is commonly assumed for a survey line on the road surface. However, this approximation may not be met when resistivity investigations are conducted over a raised high embankment; under these conditions, regular inversions might yield erroneous results. This study explored the topographical effect of a high embankment on resistivity measurements by forward and inverse modeling of a 3D high embankment model. The results show that a 2D approximation of the survey lines on the road surface significantly increases the apparent resistivity within the depth of the raised embankment. Maximum relative errors reached 21% and 11% for the road shoulder and midline survey lines, respectively. The biased apparent resistivity resulted in an inverted resistivity that was higher than the true values, although resistivity contrasts can still identify interfaces between layers. A geometric factor was used to correct the biased apparent resistivity to eliminate the high embankment topographical effect. Inversion results of the corrected apparent resistivity agreed well with the forward model. The method was then verified by field application. The apparent resistivity of the field data collected on a high embankment in permafrost regions on the Qinghai–Tibet Plateau was corrected before inversion. The permafrost table derived from the inverted resistivity was verified based on borehole temperatures. These findings indicate that the topographical influence of high embankments on resistivity measurements needs to be considered. Correction of the apparent resistivity is indispensable for quantitative interpretation of the inverted resistivity.

Amphetamine pretreatment blunts dopamine-induced D2/D3-receptor occupancy by an arrestin-mediated mechanism: A PET study in internalization compromised mice

While all reversible receptor-targeting radioligands for positron emission tomography (PET) can be displaced by competition with an antagonist at the receptor, many radiotracers show limited occupancies using agonists even at high doses. [11C]Raclopride, a D2/D3 receptor radiotracer with rapid kinetics, can identify the direction of changes in the neurotransmitter dopamine, but quantitative interpretation of the relationship between dopamine levels and radiotracer binding has proven elusive. Agonist-induced receptor desensitization and internalization, a homeostatic mechanism to downregulate neurotransmitter-mediated function, can shift radioligand-receptor binding affinity and confound PET interpretations of receptor occupancy. In this study, we compared occupancies induced by amphetamine (AMP) in drug-naive wild-type (WT) and internalization-compromised β-arrestin-2 knockout (KO) mice using a within-scan drug infusion to modulate the kinetics of [11C]raclopride. We additionally performed studies at 3 h following AMP pretreatment, with the hypothesis that receptor internalization should markedly attenuate occupancy on the second challenge, because dopamine cannot access internalized receptors. Without prior AMP treatment, WT mice exhibited somewhat larger binding potential than KO mice but similar AMP-induced occupancy. At 3 h after AMP treatment, WT mice exhibited binding potentials that were 15 % lower than KO mice. At this time point, occupancy was preserved in KO mice but suppressed by 60 % in WT animals, consistent with a model in which most receptors contributing to binding potential in WT animals were not functional. These results demonstrate that arrestin-mediated receptor desensitization and internalization produce large effects in PET [11C]raclopride occupancy studies using agonist challenges.

Role of speckle-tracking echocardiography in diagnosis and further prognosis of coronary heart disease

Echocardiography is one of the first-line methods of detection and evaluation of coronary artery disease, which helps clinicians in the diagnostic and prognostic evaluation of this disease. However, visual assessment of abnormal left ventricular myocardial wall motion is not always appropriate in detecting less severe or transient myocardial ischemia and in making an accurate differential diagnosis. Speckle-tracking echocardiography is a widely available non-invasive tool that can easily and quickly provide clarifying information and significantly extend the standard echocardiographic study, as the method allows you to identify subtle myocardial damage and local areas of ischemia that correspond to the pattern of coronary disease, and obtain an objective report in the form of simple visual scheme, very easy to use for differential diagnosis and treatment. Therefore, this method, which is increasingly used in various manifestations of coronary insufficiency and is convenient to use both at rest and with stress echocardiography, has proved efficient results in terms of predicting coronary heart disease, quantitative interpretation of emerging or persistent ischemia, assessment of the clinical course and outcome, and left ventricular remodeling. In this review, we have attempted to reflect the currently available findings that demonstrate the significance of speckle-tracking echocardiography for the evaluation and follow-up of coronary heart disease, including some congenital anomalies of the coronary arteries, and to touch on the main achievements and discoveries in the use of two-dimensional and three-dimensional deformation parameters and their potential application for a wider introduction into clinical practice.

Quantitative interpretation of bone marrow biopsies inMPN-What's the point in a molecular age?

The diagnosis of myeloproliferative neoplasms (MPN) requires the integration of clinical, morphological, genetic and immunophenotypic findings. Recently, there has been a transformation in our understanding of the cellular and molecular mechanisms underlying disease initiation and progression in MPN. This has been accompanied by the widespread application of high-resolution quantitative molecular techniques. By contrast, microscopic interpretation of bone marrow biopsies by haematologists/haematopathologists remains subjective and qualitative. However, advances in tissue image analysis and artificial intelligence (AI) promise to transform haematopathology. Pioneering studies in bone marrow image analysis offer to refine our understanding of the boundaries between reactive samples and MPN subtypes and better capture the morphological correlates of high-risk disease. They also demonstrate potential to improve the evaluation of current and novel therapeutics for MPN and other blood cancers. With increased therapeutic targeting of diverse molecular, cellular and extra-cellular components of the marrow, these approaches can address the unmet need for improved objective and quantitative measures of disease modification in the context of clinical trials. This review focuses on the state-of-the-art in image analysis/AI of bone marrow tissue, with an emphasis on its potential to complement and inform future clinical studies and research in MPN.

Relationship Between Permeability and Resistivity of Sheared Rock Fractures: The Role of Tortuosity and Flow Path Percolation

AbstractThe fluid‐flow properties of fractures have received increasing attention regarding the role of geofluids in the genesis of slow and fast earthquakes and recent advances in geoengineering developments. Geophysical observations are promising tools to remotely estimate crustal permeability changes; however, quantitative interpretations are limited by the rock‐physical models' paucity for fractures. This study investigated changes in permeability, resistivity, and their respective relationships at elevated stress by performing numerical simulations of different fracture models with varying fracture size, roughness, and shear displacement. Numerical results and microscopic flow analysis demonstrate that permeability–resistivity relationships are controlled by percolation and are less dependent on fracture geometric characteristics. Our finding suggests that the permeability evolution of fractures can be formulated with resistivity changes independent of both fracture size and microstructure, the trends of which can be predicted using Archie's exponent. The extension to the electro‐mechanical relationship further derives the potential applications of estimating stress changes.

Interpretable machine learning model for shear wave estimation in a carbonate reservoir using LightGBM and SHAP: a case study in the Amu Darya right bank

The shear wave velocity (Vs) is significant for quantitative seismic interpretation. Although numerous studies have proved the effectiveness of the machine learning method in estimating the Vs using well-logging parameters, the real-world application is still hindered because of the black-box nature of machine learning models. With the rapid development of the interpretable machine learning (ML) technique, the drawback of ML can be overcome by various interpretation methods. This study applies the Light Gradient Boosting Machine (LightGBM) to predict the Vs of a carbonate reservoir and uses the Shapley Additive Explanations (SHAP) to interpret the model. The application of ML in Vs estimation normally involves using conventional well-log data that are highly correlated with Vs to train the model. To expand the model’s applicability in wells that lack essential logs, such as the density and neutron logs, we introduce three geologically important features, temperature, pressure, and formation, into the model. The LightGBM model is tuned by the automatic hyperparameter optimization framework; the result is compared with the Xu-Payne rock physics model and four machine learning models tuned with the same process. The results show that the LightGBM model can fit the training data and provide accurate predictions in the test well. The model outperforms the rock physics model and other ML models in both accuracy and training time. The SHAP analysis provides a detailed explanation of the contribution of each input variable to the model and demonstrates the variation of feature contribution in different reservoir conditions. Moreover, the validity of the LightGBM model is further proved by the consistency of the deduced information from feature dependency with the geological understanding of the carbonate formation. The study demonstrates that the newly added features can effectively improve model performance, and the importance of the input feature is not necessarily related to its correlation with Vs

Development of fracture diagnostic methods for fluid distribution based on quantitative interpretation of distributed acoustic sensing and distributed temperature sensing

Multistage hydraulic fracturing design on horizontal wells has significantly evolved with larger fluid volume, more fracturing stages, and tighter perforation cluster spacing to efficiently stimulate unconventional reservoirs. From the published field observations, the recent fracturing design results in complex fracture networks or swarm of fractures. Fracture treatment evaluation is extremely challenging in such a case because of the large amount of variables in well completion and stimulation design. Combined measurements from different technologies can help in fracture diagnosis. Fluid distribution, either during fracture injection or during production, directly relates to the stimulation efficiency at the cluster level and at the stage level. Because it is unlikely in the real world to distribute the injected fluid uniformly among all the clusters, we need diagnostic techniques to generate the flow profile along a lateral. Fiber-optic measurements, such as distributed acoustic sensing (DAS) and distributed temperature sensing (DTS), are currently used to diagnose downhole flow conditions. This technology allows us to qualitatively confirm the fluid flow profile and other issues occurring downhole during fracturing such as leakage through plugs. For optimizing a fracturing design, we also need to understand how the design parameters are correlated with the stimulation efficiency. In this study, we combine two sets of models of DAS and DTS data interpretation for injected fluid volume distribution. The DAS is interpreted based on an empirical correlation between fluid flow rates and frequency band energy from the acoustic signals. The DTS is interpreted by performing temperature history match-based thermal energy conservation. Because of the completely different physics behind the interpretations, the confirmation of two interpretations provides confidence in fluid distribution.

Cognitive Research Methods in Linguistics: Conceptual-Inferential Analysis

In studying language modern linguistics takes into account the users’ personality and their role as interpreters, arguing that language does not only convey a person’s knowledge of the world in one format or another, but also interprets it in a certain way. The leading role of the anthropocentric factor in linguistic research, as well as focusing on the cognitive and linguistic mechanisms of meaning construction makes the problem be discussed in the study up-to-date and significant one within the framework of the cognitive-discursive paradigm. The authors put forward an idea of conceptualinferential analysis as a new research method which can be effectively applied to language data within the framework of a cognitive study of language. The aim of this article is to substantiate the possibility of using this method in modelling the processes of interpretation and representation of world knowledge in language. The application of the method of conceptual-inferential analysis is illustrated by the example of quantitative interpretation of quality in language as a complex mental processing of quantitative-qualitative relations in the world. Based on the analysis of the linguistic means of the quantity concept representation, the article gives a deeper insight into processes of quantitative interpretation of quality, describes the repertoire of potential inferenced qualitative meanings and demonstrates their dependence on the cognitive context. In addition to the proposed method, the authors also use other research methods and techniques of conceptual analysis and conceptual-definition analysis. The evidence data (12000 examples) is retrieved from the works by modern authors. The integrated application of conceptual-inferential and conceptual-definition analysis methods reveals a high interpretive potential of quantitative meanings in representing quality in language. It also helps identify cognitive mechanisms of the quantitative-qualitative meanings construction, and to detect various types of knowledge available to an individual as an interpreter of quantitative-qualitative relations and their representation in language.

Performance Evaluation of DFTB1 and DFTB2 Methods in reference to the Crystal Structures and Molecular Energetics of Siloxaalkane Molecular Compass

In the lately developed computational paradigms and state-of-art theoretical analyses, the density-functional based tight-binding (DFTB) scheme and its profound theoretical features extended to address the crystalline molecular systems stand as the most versatile quantum mechanical method. Being its computational parser codes extremely efficient and even assessable directly as a low-cost scheme despite hosting ab initio functionalities comprising mathematical formulations, the “non-self-consistent-charge” (DFTB1) and “self-consistent-charge" (DFTB2) approaches are extensively applied to the wide ranged molecular systems under both crystalline (PBC) and non-crystalline conditions. The "dispersion energy corrections (DECs)" features of it further add an additional value to their rational applications. Herewith, the intensive evaluations on their performances are carried out based on the results they produced for the experimentally synthesized amphidynamic type molecular crystal with macroscopic compass like supramolecular assembly possessing central dipolar difluorophenylene rotator (compass needle), axial Si-C bond spin axis, and peripheral -Si- & -Si-O- made siloxaalkane stator. It is found that the DFTB2 performed far better than the DFTB1 in reference to its datasets: (a) lengths for the bonds associated with rotator, stator, and spin axis, (b) free-volume unit around the rotator, (c) rotational energy barriers, viz. = 5.99 kcal/mol, & 5.52 kcal/mol under PBC with and without DECs, and (d) locations of the 1p-flipped (rotator) degenerate equilibrium structures, viz. at f = 0.505p & 1.493p (Expt. f = 0.56p & 1.56p) radians. Besides this, the dispersion constants for the F atom; cutoff =3.8Å, polarizability =3.4Å3, and effective nuclear charge =3.5au determined by DFTB2, and the precise unit-cell geometries derived by undertaking these numeral values further exemplified its superiority over DFTB1. It is believed that all the justifications and quantitative interpretations conferred throughout this article put considerable demands on the accuracy of DFTB2 for investigating crystal structures and molecular energetics explicitly.

BITS: A Bayesian Isotope Turnover and Sampling model for strontium isotopes in proboscideans and its potential utility in movement ecology

Abstract Strontium isotope ratios (87Sr/86Sr) of incrementally grown tissues have been widely used to study movement ecology and migration of animals. However, the time scale of 87Sr/86Sr incorporation from the environment into tissue and how it may influence data interpretation are still poorly understood. Using the relocation of a zoo elephant (Loxodonta africana) named Misha, we characterise and model the 87Sr/86Sr turnover process using high‐resolution measurements of its tusk dentine. We seek to develop a framework that can improve quantitative interpretation of 87Sr/86Sr data in tissues. The 87Sr/86Sr transition associated with the relocation is measured using laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) on a prepared tusk slab. We develop a turnover model (BITS), with a rapidly exchanging central pool and a slowly exchanging peripheral pool, in a Bayesian statistical framework. The measured dentine data are first used to calibrate model parameters. The parameters are then used to estimate possible 87Sr/86Sr input time series from two datasets via model inversion: a fidelity test using Misha's dentine data and a case study using published dentine measurements from an Alaskan Woolly Mammoth (Mammuthus primigenius). The LA‐ICP‐MS data are consistent with a two‐compartment turnover process with equivalent half‐lives of 41 days for the central pool and 170 days for the peripheral pool. The model inversion shows good fidelity when estimating the intake 87Sr/86Sr time series associated with Misha's relocation. In the case study, the model suggests an abrupt pattern of change in, and a much wider range of, intake 87Sr/86Sr values than expressed in the woolly mammoth dentine data themselves. Our framework bridges the gap between environmental 87Sr/86Sr variation and data measured in tusk dentine or other incrementally grown tissues. It could be coupled with movement models and additional isotope tracers to study seasonal residency or the spatial and temporal patterns of movement/migration. The generic turnover processes can be adapted to other isotope systems, additional incremental tissues, or other organisms, thus expanding our modelling toolkit to investigate niche partitioning, life history traits and behavioural patterns in conservation biology, archaeology and paleoecology.