Domain Of Validity Research Articles

GaiaData Release 3

Context.The third release of theGaiacatalogue contains radial velocities for 33 812 183 stars with effective temperatures ranging from 3100 K to 14 500 K. The measurements are based on the comparison of the spectra observed with the Radial Velocity Spectrometer (RVS; wavelength coverage: 846–870 nm, median resolving power: 11 500) to synthetic data broadened to the adequate along-scan line spread function. The additional line-broadening, fitted as it would only be due to axial rotation, is also produced by the pipeline and is available in the catalogue (field namevbroad).Aims.We describe the properties of the line-broadening information extracted from the RVS and published in the catalogue, and analyse the limitations imposed by the adopted method, wavelength range, and instrument.Methods.We used simulations to express the link between the line-broadening measurement provided inGaiaData Release 3 andVsini. We then compared the observed values to the measurements published by various catalogues and surveys (GALAH, APOGEE, LAMOST, etc.).Results.While we recommend caution in the interpretation of thevbroadmeasurement, we also find a reasonable general agreement of theGaiaData Release 3 line-broadening values and values in other catalogues. We discuss and establish the validity domain of the publishedvbroadvalues. The estimate tends to be overestimated at the lowerVsiniend, and atTeff > 7500 K its quality and significance degrade rapidly whenGRVS > 10. Despite all the known and reported limitations, theGaiaData Release 3 line-broadening catalogue contains measurements obtained for 3 524 677 stars withTeffranging from 3500 to 14 500 K, andGRVS < 12. It gathers the largest stellar sample ever considered for the purpose, and allows a first mapping of theGaialine-broadening parameter across the Hertzsprung-Russel diagram.

Machine Learning-Assisted Estimation of the Photoantioxidant Activities of Bare, Mg, Cu, and Mg/Cu Dual-Doped ZnO

Green-synthesized pure zinc oxide (ZnO), Mg-doped ZnO, Cu-doped ZnO, and Mg/Cu dual-doped ZnO using aqueous leaf extract of Ziziphus mauritiana were analyzed for their antioxidant activities. In this study, the data-driven approach has been used to estimate the photoantioxidant activities of ZnO, Mg-doped ZnO, Cu-doped ZnO, and Mg/Cu dual-doped ZnO based on the experimental data and synthetic data generated through simulations. Three different machine learning models, including artificial neural network, extreme gradient boosting, and automated machine learning, were explored and compared for both data sets. These models were validated by using external validation and applicability domain methods based on the values of coefficient of determination, root mean square, and mean absolute errors. The performance of the machine learning techniques showed that photoantioxidant activities could be predicted accurately from the input variables such as types of dopants, percentage of dopants, average crystallite size, lighting condition, and concentration of antioxidants (photocatalyst). Doping and the lighting condition were found to have a more significant impact on the values of photoantioxidant activities of the ZnO, Mg-doped ZnO, Cu-doped ZnO, and Mg/Cu dual-doped ZnO in comparison to other variables. Based on three artificial neural network models, the variables for Mg doping and the lighting condition had weights with values ranging between 1.1 and 2.9.

Legitimizing the game: how gamers' personal experiences shape the emergence of grassroots collective action in esports

PurposeThis paper studies early stages of actor mobilization for institutional change within Swedish esports.Design/methodology/approachThe authors employ interpretative phenomenological analysis.FindingsThe authors’ findings explain how actors become motivated to act in critical reflections linked to conflicting legitimacy judgments and emotionally charged personal struggles. Moreover, the findings show how, as actors get activated in collective action, they identify efficacy lines around valid domains and experience emotionally charged collective endeavors. Furthermore, the findings explain how particularities in early experiences project legitimacy aspirations that orient collective action toward validity ends and particular values and ideals shaping actors' grassroots movements.Originality/valueThis study adds to legitimacy and institutional change theory through individual actors' perspectives, providing key insights into how they are motivated, activated, and oriented. This study is the first to investigate grassroots activists' personal stories in esports.

Control of an Industrial Distillation Column Using a Hybrid Model with Adaptation of the Range of Validity and an ANN‐based Soft Sensor

AbstractAdvanced control schemes such as model predictive control can be used to minimize the use of resources while guaranteeing the specified product quality. In this paper, we consider an industrial mother liquor distillation column varying flow rate and composition of the feed. There are specifications of the composition for all product streams. To address this challenging control problem, we employ a nonlinear model‐predictive controller using a hybrid model, which consists of a simple phenomenological model augmented by a data‐based component to compensate the plant‐model mismatch. The trustworthiness of the data‐based model is addressed using a domain of validity of the data‐based model, which is estimated using a one‐class support vector machine. During operation, it may turn out that the model is also reliable in a wider range, therefore, data of recently visited operating points is recorded and the domain of validity is extended if the model is sufficiently accurate. To improve the performance of the controller, an artificial neural network model is used to estimate the product composition from available measurements.

Should physical symmetries guide metaphysics? Two reasons why they should maybe not

Symmetry-based inferences have permeated many discussions in philosophy of physics and metaphysics of science. It is claimed that symmetries in our physical theories would allow us to draw metaphysical conclusions about the world, a view that I call ‘symmetry inferentialism’. This paper is critical to this view. I claim that (a) it assumes a philosophically questionable characterization of the relevant validity domain of physical symmetries, and (b) it overlooks a distinction between two opposing ways through which relevant physical symmetries become established. My conclusion is that symmetry inferentialism loses persuasive force when these two points are taken into consideration.

Experimental measurement and expression of atmospheric ice Young's modulus according to its density

Ice properties are hard to define and vary significantly in literature. While some of this variation can be attributed to different testing methods, the authors believe that most of this variation comes from the nature of the ice accretion itself. To address the problematic of scattering in mechanical properties values, a new approach is proposed which consists of expressing the behavior of atmospheric ice according to its density. Thanks to a hybrid experimental/numerical approach, the accurate measurement of the Young's modulus of atmospheric ice can be done. Ice samples are generated in both cold room and wind tunnel and at many different test conditions. The results obtained in this study confirm the validity of this new approach and gives a concrete relationship between the Young's modulus and the ice density. Finally, the relevance of using porous material hypothesis to explain the relation and the results domain of validity are discussed.

Event‐triggered control of Takagi‐Sugeno fuzzy systems under deception attacks

AbstractThis article handles the problem of periodic event‐triggered control co‐design for the stabilization of Takagi‐Sugeno fuzzy models subject to stochastic deception attacks whose occurrence follows a given Bernoulli distribution. A novel delay‐dependent condition is presented to simultaneously design the event‐triggering mechanism and the state‐feedback controller to ensure the local mean‐square asymptotic stability of the closed‐loop system. The co‐design condition is derived as linear matrix inequalities by considering Lyapunov–Krasovskii stability arguments. In addition, an optimization procedure is provided to estimate an enlarged set of admissible initial conditions and the corresponding ultimate bound within the validity domain of the fuzzy model. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.

Charged-particle transport models for global models

This work analyses the influence of different charged-particle transport models on the global modeling of low-temperature plasmas. The simulations use the LisbOn KInetics simulation tool, calculating the charged-particle loss frequency due to transport with various formulations, categorized into two large groups: ambipolar-based and h-factor transport models. The models are applied to the description of (i) a DC discharge in oxygen (as example of an electronegative multi-ion plasma), at low to intermediate pressures, adopting a validated kinetic scheme as reference model; (ii) a microwave discharge in helium (as example of an electropositive multi-ion plasma), from low to atmospheric pressures, proposing and validating an updated kinetic scheme that bridges two previous models, adjusted separately for low to intermediate pressures and for atmospheric pressure. The analysis shows that using different charged-particle transport models can result in uncertainties of 20%–60% and 8%–115% in the discharge characteristics of oxygen and helium, respectively, with larger dispersion at low pressure and low electron density. The spreading in the results is observed also in the densities of the main plasma species, corresponding to uncertainties up to and within 50%–150% in oxygen and helium, respectively. Since transport accounts for more than of total charge losses, this mechanism should always be part of the quantitative sensitivity analysis of a kinetic scheme, considering several models with different validity domains, according to the electro-positive/-negative single-/multi-ion plasma under study and the low/high pressure conditions considered.

A Quantitative Structure-Activity Relationship for Human Plasma Protein Binding: Prediction, Validation and Applicability Domain.

The purpose of this study was to develop a robust and externally predictive in silico QSAR-neural network model for predicting plasma protein binding of drugs. This model aims to enhance drug discovery processes by reducing the need for chemical synthesis and extensive laboratory testing. A dataset of 277 drugs was used to develop the QSAR-neural network model. The model was constructed using a Filter method to select 55 molecular descriptors. The validation set's external accuracy was assessed through the predictive squared correlation coefficient Q2 and the root mean squared error (RMSE). The developed QSAR-neural network model demonstrated robustness and good applicability domain. The external accuracy of the validation set was high, with a predictive squared correlation coefficient Q2 of 0.966 and a root mean squared error (RMSE) of 0.063. Comparatively, this model outperformed previously published models in the literature. The study successfully developed an advanced QSAR-neural network model capable of predicting plasma protein binding in human plasma for a diverse set of 277 drugs. This model's accuracy and robustness make it a valuable tool in drug discovery, potentially reducing the need for resource-intensive chemical synthesis and laboratory testing.

On-farm evaluation of multiparametric models to predict subacute ruminal acidosis in dairy cows

This research aimed: (i) to evaluate on-farm (FARM data) multiparametric models developed under controlled experiment (INRAE data) and based on non-invasive indicators to detect subacute ruminal acidosis (SARA) in dairy cows. We also aimed to recover high discrimination capacity, if needed, by (ii) building new models with combined INRAE and FARM data; and (iii) enriching the models increasing from 2 to 5 indicators per model. For model enrichment, we focused on indicators determinable on-farm by quick and inexpensive routine analysis. Fifteen commercial dairy farms were selected to cover a wide range of SARA risk. In each farm, four Holstein early-lactating healthy primiparous cows were selected based on their last on-farm recording of milk yield and somatic cell count analysis. Cows were equipped with a reticulo-rumen pH sensor. The pH kinetics were analysed over a subsequent 7-day period. Relative pH indicators were used to classify cows with or without SARA. Milk, blood, faeces, and urine were collected for analysis of the indicators included in the models developed by Villot et al. (2020) on INRAE data that were externally evaluated using FARM data. Then, new models based on the same indicators were developed combining INRAE and FARM data to test whether a possible loss in performance was due to a limited validity domain of model by Villot et al (2020). Finally, the models developed combining INRAE and FARM data were adapted to the on-farm application and enriched by increasing indicators from 2 to 5 per model using linear discriminant analysis and leave-one-out cross-validation. The sensitivities (true-positive rate) in external evaluation on FARM data were substantially lower than those from cross-validation by Villot et al. (2020) (range: 0.1–0.75 vs 0.79–0.96, respectively), and the specificities (true-negative rate) showed a larger range with lower minimum values (range: 0.18–1.0 vs 0.62–0.97, respectively). The sensitivities of new models developed combining INRAE and FARM data ranged from 0.63 to 0.77. Models involving blood cholesterol, β-hydroxybutyrate, haptoglobin, milk and blood urea, and models involving milk fat/protein ratio, dietary starch proportion, and milk fatty acids had the highest performances, whereas models including sieved faecal residues and urine pH had the lowest. Enriching models to three indicators per model improved sensitivity and specificity, but the inclusion of more indicators was less or not effective. Larger field trials are required to validate our results and to increase variability and validity domain of models.

COVMOS: A new Monte Carlo approach for galaxy clustering analysis

We validate the COVMOS method introduced in our previous study allowing for the fast simulation of catalogues of different cosmological field tracers (e.g. dark matter particles, halos, galaxies, etc.). The power spectrum and one-point probability distribution function of the underlying tracer’s density field are set as inputs of the method and arbitrarily chosen by the user. To evaluate the validity domain of COVMOS at the level of the produced two-point statistics covariance matrix, we chose to target these two input statistical quantities from realistic N-body simulation outputs. We performed this cloning procedure based on the ΛCDM as well as on a massive neutrino cosmology, for five redshifts in the range of z ∈ [0, 2]. First, we validated the output real-space two-point statistics (both in the configuration and Fourier space) and estimated over 5000 COVMOS realisations per redshift and per cosmology, with a volume of 1 [Gpc/h]3 and 108 particles each. This validation was performed against the corresponding N-body measurements, estimated from 50 simulations. We found the method to be valid up to k ∼ 0.2h Mpc−1 for the power spectrum and down to r ∼ 20 Mpc h−1 for the correlation function. Then, we extended the method by proposing a new modelling of the peculiar velocity distribution, aimed at reproducing the redshift-space distortions both in the linear and mildly non-linear regimes. After validating this prescription, we finally compared and validated the resulting redshift-space two-point statistics covariance matrices in the same range of scales. We released the Python code associated with this method on a public repository, which allows for the production of tens of thousands of realisations in record time. In particular, COVMOS is intended for any study involving large-scale galaxy-survey science that requires a large number of mock realisations.

The SZ flux-mass (Y–M) relation at low-halo masses: improvements with symbolic regression and strong constraints on baryonic feedback

ABSTRACT Feedback from active galactic nuclei (AGNs) and supernovae can affect measurements of integrated Sunyaev–Zeldovich (SZ) flux of haloes (YSZ) from cosmic microwave background (CMB) surveys, and cause its relation with the halo mass (YSZ–M) to deviate from the self-similar power-law prediction of the virial theorem. We perform a comprehensive study of such deviations using CAMELS, a suite of hydrodynamic simulations with extensive variations in feedback prescriptions. We use a combination of two machine learning tools (random forest and symbolic regression) to search for analogues of the Y–M relation which are more robust to feedback processes for low masses ($M\lesssim 10^{14}\, \mathrm{ h}^{-1} \, \mathrm{ M}_\odot$); we find that simply replacing Y → Y(1 + M*/Mgas) in the relation makes it remarkably self-similar. This could serve as a robust multiwavelength mass proxy for low-mass clusters and galaxy groups. Our methodology can also be generally useful to improve the domain of validity of other astrophysical scaling relations. We also forecast that measurements of the Y–M relation could provide per cent level constraints on certain combinations of feedback parameters and/or rule out a major part of the parameter space of supernova and AGN feedback models used in current state-of-the-art hydrodynamic simulations. Our results can be useful for using upcoming SZ surveys (e.g. SO, CMB-S4) and galaxy surveys (e.g. DESI and Rubin) to constrain the nature of baryonic feedback. Finally, we find that the alternative relation, Y–M*, provides complementary information on feedback than Y–M.

Measurement properties of 72 movement biomarkers aiming to discriminate non‑specific chronic low back pain patients from an asymptomatic population

The identification of relevant and valid biomarkers to distinguish patients with non-specific chronic low back pain (NSCLBP) from an asymptomatic population in terms of musculoskeletal factors could contribute to patient follow-up and to evaluate therapeutic strategies. Several parameters related to movement impairments have been proposed in the literature in that respect. However, most of them were assessed in only one study, and only 8% were evaluated in terms of reliability, validity and interpretability. The aim of this study was to consolidate the current knowledge about movement biomarkers to discriminate NSCLBP patients from an asymptomatic population. For that, an experimental protocol was established to assess the reliability, validity and interpretability of a set of 72 movement biomarkers on 30 asymptomatic participants and 30 NSCLBP patients. Correlations between the biomarkers and common patient reported outcome measures were also analysed. Four biomarkers reached at least a good level in reliability (ICC ≥ 0.75) and validity (significant difference between asymptomatic participants and NSCLBP patients, p ≤ 0.01) domains and could thus be possibly considered as valuable biomarkers: maximal lumbar sagittal angle, lumbar sagittal angle range of motion, mean lumbar sagittal angular velocity, and maximal upper lumbar sagittal angle during trunk sagittal bending. These four biomarkers demonstrated typically larger values in asymptomatic participants than in NSCLBP patients. They are in general weakly correlated with patient reported outcome measures, arguing for a potential interest in including related musculoskeletal factors in the establishment of a valuable diagnosis and in guiding treatment response.

Measuring vaping-related expectancies in young adults: Psychometric evaluation of the Electronic Nicotine Vaping Outcomes (ENVO) scale

ObjectiveElectronic cigarettes are the most commonly used tobacco products by young adults. Measures of beliefs about outcomes of use (i.e., expectancies) can be helpful in predicting use, as well as informing and evaluating interventions to impact use. MethodsWe surveyed young adult students (N = 2296, Mean age=20.0, SD=1.8, 64 % female, 34 % White) from a community college, a historically black university, and a state university. Students answered ENDS expectancy items derived from focus groups and expert panel refinement using Delphi methods. Factor Analysis and Item Response Theory (IRT) methods were used to understand relevant factors and identify useful items. ResultsA 5-factor solution [Positive Reinforcement (consists of Stimulation, Sensorimotor, and Taste subthemes, α = .92), Negative Consequences (Health Risks and Stigma, α = .94), Negative Affect Reduction (α = .95), Weight Control (α = .92), and Addiction (α = .87)] fit the data well (CFI=0.95; TLI=0.94; RMSEA=0.05) and was invariant across subgroups. Factors were significantly correlated with relevant vaping measures, including vaping susceptibility and lifetime vaping. Hierarchical linear regression demonstrated factors were significant predictors of lifetime vaping after controlling for demographics, vaping ad exposure, and peer/family vaping. IRT analyses indicated that individual items tended to be related to their underlying constructs (a parameters ranged from 1.26 to 3.18) and covered a relatively wide range of the expectancies continuum (b parameters ranged from −0.72 to 2.47). ConclusionsA novel ENDS expectancy measure appears to be a reliable measure for young adults with promising results in the domains of concurrent validity, incremental validity, and IRT characteristics. This tool may be helpful in predicting use and informing future interventions. ImplicationsFindings provide support for the future development of computerized adaptive testing of vaping beliefs. Expectancies appear to play a role in vaping similar to smoking and other substance use. Public health messaging should target expectancies to modify young adult vaping behavior.

Use of a Caprine Model for Simulation and Training of Endoscopic Ear surgery.

The objective of this study was to evaluate the utility of a caprine model in endoscopic ear surgical education using the index procedures of tympanoplasty and ossiculoplasty. Specifically, this study assessed the face and content validity of the caprine model, and the potential impact of anatomical differences on trainee understanding of human middle ear anatomy. Twelve otolaryngology trainees attended a 3-hour endoscopic ear surgery course utilizing the caprine model in which they completed canalplasty, tympanoplasty, and ossiculoplasty. Prior to the course, the trainees completed a self-reported needs assessment and knowledge assessment of human middle ear anatomy. Following the course, the trainees repeated the knowledge assessment and completed evaluation and validation questionnaires. Five-point Likert scores were used for the needs assessment and validation questionnaire. Of the 12 trainees, 9 participated in the study. All domains of the learner needs assessment showed an average improvement of 1 point on the post-course evaluation with 6 of 9 domains being significantly improved using the Wilcoxon signed-rank test (P< .05). The model achieved validation in the domains of face, content, and global content validity with an average Likert score > 4. Knowledge assessment scores increased by 7% (P=.23) after the course compared to before. The caprine model offers an effective surgical simulation model for endoscopic ear surgery training with good face and content validity. We find it to be readily available and affordable. We currently use it routinely to give otolaryngology residents the experience of endoscopic ear surgery before operating on patients.

QSAR model and microscopic mechanism analysis of dye removal by coagulation of aluminum chloride under alkaline conditions

Introduction: The inorganic coagulant AlCl3 is used in the traditional coagulation method for the decolorization of industrial dye wastewater. We studied its effectiveness in 41 kinds of dye with different structures, including azo, anthraquinone, arylmethane, and indigo dyes.Discussion: The optimal conditions for the removal of dye in the AlCl3 coagulation system were alkaline &amp;gt; neutral &amp;gt; acidic conditions. Under alkaline conditions, the hydrolysis colloid of AlCl3 is positively charged and easily combined with negatively charged anionic dyes by electrostatic adsorption. Therefore, the relationships between the dye removal behavior and molecular parameters under alkaline conditions were analyzed.Methods: Quantitative structure–activity relationship (QSAR) models were built for the color removal rates (Rexp) of 41 dyes and 46 molecular parameters computed by the density functional theory (DFT). Internal validation, external validation, statistical tests, Y-randomization, and applicability domain tests indicated that the optimal models are stable, accurate, reliable, and predictive.Results: The optimal QSAR model showed that surface area (approx.) (SAA) and molecular weight (MW) are two key molecular parameters. Moreover, electrostatic forces and hydrogen bonding are the predominant adsorption forces in this coagulation process.

Systematic literature review of quality-of-life questionnaires in Waldenström macroglobulinaemia-need for a disease-specific tool.

Systematic literature review of quality-of-life questionnaires in Waldenström macroglobulinaemia-need for a disease-specific tool.

Phase transitions in de Sitter spacetimes: Quantum Corrections

We investigate the decay rate of a false vacuum state in de Sitter space at high Hubble rates, using two methods: the Hawking-Moss instanton method which is fully quantum mechanical but relies on the saddle-point approximation, and the Starobinsky-Yokoyama stochastic approach which is nonperturbative but does not include quantum effects. We use the flux over population method to compute the Hawking-Moss decay rate at one-loop order, and demonstrate that in its domain of validity, it is reproduced by the stochastic calculation using the one-loop constraint effective potential. This suggests that the stochastic approach together with the constraint effective potential can be used to accurately describe vacuum decay beyond the saddle-point approximation.

Asymptotic analysis of boundary layer flow of a fluid with temperature-dependent viscosity

In this work, we study boundary layer flows for thermo-dependent Newtonian fluids. We first show that the governing equations admit a self-similar solution. Furthermore, an asymptotic model is used to obtain correlations on heat transfer and the skin-friction coefficient. In addition, the numerical study of the complete problem enables us to specify the domain of validity of these correlations. Finally, the obtained numerical results are used to analyze the influence of the Prandtl number on the profiles of the stream function and the temperature field, and also on parameters such as the local Nusselt number and the thickness of the boundary layer.

The cost of an ALP solution to the neutral B-anomalies

The neutral anomalies in B decays are analysed in terms of the tree-level exchange of an axion-like-particle (ALP), within the effective field theory framework. The complete two-dimensional parameter space for ALP couplings to electrons and muons is explored. The solutions to RK and to the two energy bins of {R}_{K^{ast }} are confronted with the impact of ALP exchange on other observables (meson oscillations, leptonic and semileptonic decays of B mesons including searches for new resonances, astrophysical constraints), as well as with the theoretical domain of validity of the effective theory. Solutions based on ALPs heavier than B mesons, or lighter than twice the muon mass, are shown to be excluded. In contrast, the exchange of on-shell ALPs provides solutions to RK and/or {R}_{K^{ast }} within 2σ sensitivity which are technically compatible with those constraints. Furthermore, a “golden ALP mass” is identified at the frontier between the two energy bin windows of {R}_{K^{ast }} , which could simultaneously explain these two {R}_{K^{ast }} anomalies together with RK; this calls for the convenience of different energy binning which would easily clear up this (unlikely) possibility. The impact of smearing on data analysis is also discussed. When loop effects are taken into account, the solutions found can be in addition compatible with the data on the g − 2 of the electron but not simultaneously with those on the g − 2 of the muon. Furthermore, loop effects may require fine-tunings of some coupling values.