Fitting Procedure Research Articles

Influence of species kinetics on discharge characteristics in oxygen helicon plasma

Abstract Oxygen (O2) helicon plasmas in multiple wave modes were excited by a right-helical antenna with an upper metal endplate at low pressure. Mode transitions were observed at increasing input power or magnetic field, characterized by obvious jumps of plasma parameters. Blue Core appears at high magnetic fields (~700 G) and input powers (~1700 W), with a large radial gradient of plasma density, ion line intensity, and electron temperature. Emission spectra demonstrate that the blue lights originate from O II lines. We found that the intensity ratio of O II to O I of Blue Core in O2 is lower by one order than that in N2 or Ar despite their similar ionization rates and plasma densities in Blue Core area. A high-temperature B-dot probe together with a waveform fitting procedure was used to present the measured oscillating waveforms of m =+1 helicon waves, showing distinct wave structures of different eigenmodes. Cavity mode resonance is suggested to be responsible for the formation of standing waves of discrete eigenmodes. A pressure balance model was developed to estimate the species densities around the central area in different modes, showing massive dissociation of O2 molecules and high density of O atoms locally, so that O2 helicon plasma behaves a species feature of monatomic gas discharge. The obviously low intensity of O II lines compared to O I lines of Blue Core in O2 is related to the quite high excitation threshold of O+ ions (~30 eV) although electron density and temperature are relatively high. The combined effects of dispersed reaction energy distribution, massive molecule dissociation and negative ion creation are considered to be the main causes for requirement of much higher RF power and magnetic field for Blue Core formation in O2 helicon plasma than that in Ar. The calculated radial profile of power deposition and the captured plasma morphology confirm that the dominant central electron heating is the essential reason for the large radial gradients of plasma density and electron temperature which contributes to the serious neutral depletion and Blue Core formation.

Proton quantal delocalization and H/D translocations in (MeOH)nH+ (n = 2, 3).

In this study, we present results from path integral molecular dynamics simulations that describe the characteristics of the quantum spatial delocalizations of protons participating in OH bonds in (MeOH)2H+ and in (MeOH)3H+. The characterization was carried out by examining the overall structures of the corresponding isomorphic polymers. To introduce full flexibility in the force treatment, we have adopted a neural network fitting procedure based on second-order Møller-Plesset perturbation theory predictions. For the dimer case, we found that the spatial extent of the shared connective proton can be portrayed in terms of a prolate-like structure with typical dimensions of ∼0.1 Å. On the other hand, the dangling polymers lie confined within a thin spherical layer, spread over length scales of the order of ∼0.25 Å. In contrast, connective protons in (MeOH)3H+ exhibit larger delocalizations along the O-H bond and more localized ones along perpendicular directions, compared to their dangling counterparts. We also examined the characteristics of the relative propensities of H and D isotopes to be localized in dangling and connective positions. Physical interpretations of the different thermodynamic trends are provided in terms of the local geometrical characteristics and of the strengths of the corresponding intermolecular connectivities.

EVALUATING THE LEARNING CURVE OF A NOVICE OPTOMETRY STUDENT IN SCLERAL LENS FITTING: A PROSPECTIVE QUANTITATIVE STUDY USING DELIBERATE PRACTICE AND CUMULATIVE SUMMATION (LC-CUSUM)

Background and Objective: To evaluate the learning curve of a novice optometry student in scleral lens fitting through deliberate practice and to objectively quantify the learning process using the LearningCurve-Cumulative Summation (LC-CUSUM) test, ensuring accurate and unbiased results. Method: The complexity of scleral contact lens fittings was assessed by categorizing subjects into regular and irregular cornea groups. A student enrolled in the Master of Optometry program conducted the fittings using a dedicated scleral lens record form (rubrics) designed to quantify the lens management approach. Prior to performing fittings independently, the student received four weeks of training from a contact lens expert, who also served as her guide for the study. This training period and the subsequent fittings were structured based on the principles of deliberate practice, with the student performing repeated diagnostic trials. A maximum of three diagnostic trials were performed for each subject to achieve the optimal fit. After each trial, the student completed a self-efficacy scale questionnaire to assess her perceived diffi-culty and clinical judgement skills, recording “FIRST trial scores” following the initial trial and ‘LAST trial scores’ after achieving the optimal fit. The guide consistently provided verbal feedback after each case throughout the fitting process as part of the deliberate practice methodology to enhance the student’s understanding of the fitting procedure while keeping the scores confidential to ensure unbiased self-as-sessment. Following the complete supervision of the fitting procedure, the guide evaluated the student’s clinical skills using a specially designed observation scale questionnaire, referred to as the ‘GUIDE scores.’ A seven-point Likert scale was used to rate the judgement for both the self-efficacy scale and observation scale questionnaire. The student’s LAST trial scores were subsequently compared with the GUIDE scores. Results: A total of 80 scleral lens fittings were evaluated. The Intraclass Correlation Coefficient (ICC) demonstrated excellent agreement between student-reported self-efficacy scores and guide-reported observation scores. The difference in self-efficacy scores between the initial and final lens fittings was statistically significant (p < 0.05), as determined by the Wilcoxon signed-rank test. The Learning Curve-Cumulative Summation (LC-CUSUM) chart revealed that learning stabilized after 26 fittings, marking a consolidation phase where minimal further improvement was observed beyond this point, and additional practice primarily helped to maintain proficiency. The average number of trials required per eye was higher in patients with irregular corneas than those with regular corneas. Conclusion: This study evaluated the learning curve of a novice optometry student in scleral lens fitting through deliberate practice, utilizing the LC-CUSUM test to quantify progress and assess skill acquisition objectively. Proficiency was achieved after 26 fittings, with additional trials needed for irregular corneas, underscoring the influence of patient characteristics on learning. These findings emphasize the importance of structured training, personalized feedback, and self-assessment in developing clinical competence. The insights contribute to advancing education and research in contact lens science by providing practical guid-ance for designing effective programs focused on planning, teaching, and learning about scleral lens fittings.

Testing the molecular cloud paradigm for ultra-high-energy gamma ray emission from the direction of SNR G106.3+2.7

Context. Supernova remnants (SNRs) are believed to be capable of accelerating cosmic rays (CRs) to PeV energies. SNR G106.3+2.7 is a prime PeVatron candidate. It is formed by a head region, where the pulsar J2229+6114 and its boomerang-shaped pulsar wind nebula are located, and a tail region containing SN ejecta. The lack of observed gamma ray emission from the two regions of this SNR has made it difficult to assess which region would be responsible for the PeV CRs. Aims. We aim to characterize the very-high-energy (VHE, 0.1–100 TeV) gamma ray emission from SNR G106.3+2.7 by determining the morphology and spectral energy distribution of the region. This is accomplished using 2565 days of data and improved reconstruction algorithms from the High Altitude Water Cherenkov (HAWC) Observatory. We also explore possible gamma ray production mechanisms for different energy ranges. Methods. Using a multi-source fitting procedure based on a maximum-likelihood estimation method, we evaluate the complex nature of this region. We determine the morphology, spectrum, and energy range for the source found in the region. Molecular cloud information is also used to create a template and evaluate the HAWC gamma ray spectral properties at ultra-high-energies (UHE, > 56 TeV). This will help probe the hadronic nature of the highest-energy emission from the region. Results. We resolve one extended source coincident with all other gamma ray observations of the region. The emission reaches above 100 TeV and its preferred log-parabola shape in the spectrum shows a flux peak in the TeV range. The molecular cloud template fit on the higher energy data reveals that the SNR’s energy budget is fully capable of producing a purely hadronic source for UHE gamma rays. Conclusions. The HAWC observatory resolves one extended source between the head and the tail of SNR G106.3+2.7 in the VHE gamma ray regime. The template fit suggests the highest energy gamma rays could come from a hadronic origin. However, the leptonic scenario, or a combination of the two, cannot be excluded at this time.

An optically dark merging system at z ∼ 6 detected by JWST

Context. Near- to mid-infrared observations (from Spitzer and JWST) have revealed a hidden population of galaxies at redshift z = 3 − 6 called optically dark objects, which are believed to be massive and dusty star-formers. They contribute substantially to the cosmic star-formation rate (SFR) density at z ∼ 4 − 5 (up to 30 − 40%). Aims. While optically dark sources are widely recognized as a significant component of the stellar mass function, the history of their stellar mass assembly (and the evolution of their interstellar medium) remains unexplored. However, they are thought to be the progenitors of the more massive early-type galaxies found in present-day groups and clusters. It is thus important to examine the possible connection between dark sources and merging events in order to understand the environment in which they live. Methods. Here, we report our search for close companions in a sample of 19 optically-dark objects identified in the SMACS0723 JWST deep field. They were selected in the NIRCam F444W band and undetected below 2 μm. We restricted our analysis to the reddest (i.e., F277W–F444W > 1.3) and brightest (F444W < 26 mag) objects. Results. We identified KLAMA, an optically dark source showing a very close companion (angular distance < 0.5″). The spatially resolved SED fitting procedure indicates that all components lying within 1.5″ of who is it the dark source are indeed at z ∼ 5.7. Tidal features (leading to a whale-shaped morphology) corroborate the hypothesis that KLAMA is the most massive (log(M⋆/M⊙) > 10.3) and dusty (AV ∼ 3 at the core) system of an ongoing merger with a mass ratio of ∼10. Thus, around ten similar merger events would be required to double the stellar mass of KLAMA. Merging systems with properties similar to KLAMA are identified in the SERRA simulations, allowing us to reconstruct their stellar-mass assembly history and predict their molecular gas properties (in particular, the [CII] emission for the simulated system). Conclusions. The discovery of mergers within dark galaxies at the end of the Epoch of Reionization highlights the importance of conducting a statistical search for additional candidates in deep NIRCam fields. Such research will aid in our understanding of the significance of merging processes during the obscured phase of stellar-mass accumulation.

Robust, fast and accurate mapping of diffusional mean kurtosis

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Robust, fast and accurate mapping of diffusional mean kurtosis.

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Porous material characterization with Bayesian and machine learning method

Two main classes of characterization methods are usually employed for acoustic parameters of porous media, namely the analytical inversion method or the numerical fitting procedure. While analytical inverse methods suffer from a high sensivity to the operator, the numerical fitting methods can lead to non physical sets of parameters. The fitting procedure can be bounded by the analytical inversion. The Bayesian method, which is presented in this work, is the appropriate tool to couple these methods. It enables to carry out a numerical fitting procedure using the analytical inversion as prior estimation while increasing the confidence in the resulting uncertainties. In a second part, machine learning method and data mining are used as an alternative characterization method which could be a good prior estimation for the Bayesian method. Results and performances will be shown for various porous media.

A two-step self consistent algorithm for extracting magnetic anisotropy constants from angle-dependent ferromagnetic resonance measurements

To infer anisotropy parameters of magnetic materials from experimental measurements of ferromagnetic resonance (FMR) (with data comprising resonant frequencies and corresponding resonant magnetic fields), a fitting procedure to the theoretical model is essential. The governing equation for this fitting process is the Smit–Beljers equation (SB equation), which links FMR frequencies to resonant magnetic field values and anisotropy parameters nonlinearly, and through the equilibrium magnetization angle values, which also depend on the same anisotropy parameters and magnetic field values. Obtaining an analytical expression for this equation is rarely possible. In this paper, we address the challenges posed by the Smit–Beljers equation and propose a two-step self-consistent algorithm to extract the relevant parameters efficiently.

Metallicity calibrations based on auroral lines from PHANGS-MUSE data

We present a chemical analysis of selected regions from the PHANGS-MUSE nebular catalogue. Our intent is to empirically re-calibrate strong-line diagnostics of gas-phase metallicity, applicable across a wide range of metallicities within nearby star-forming galaxies. To ensure reliable measurements of auroral line fluxes, we carried out a new spectral fitting procedure whereby only restricted wavelength regions around the emission lines of interest are taken into account: this assures a better fit for the stellar continuum. No prior cuts to nebulae luminosity were applied to limit biases in auroral line detections. Ionic abundances of O$^+$ $, N$^+$, S$^+$, and S$^ $ were estimated by applying the direct method. We integrated the selected PHANGS-MUSE sample with other existing auroral line catalogues, appropriately re-analysed to obtain a homogeneous dataset. This was used to derive strong-line diagnostic calibrations that span from 12+log(O/H) = 7.5 to 8.8. We investigate their dependence on the ionisation parameter and conclude that it is likely the primary cause of the significant scatter observed in these diagnostics. We apply our newly calibrated strong-line diagnostics to the total sample of regions from the PHANGS-MUSE nebular catalogue, and we exploit these indirect metallicity estimates to study the radial metallicity gradient within each of the 19 galaxies of the sample. We compare our results with the literature and find good agreement, validating our procedure and findings. With this paper, we release the full catalogue of auroral and nebular line fluxes for the selected regions from the PHANGS-MUSE nebular catalogue. This is the first catalogue of direct chemical abundance measurements carried out with PHANGS-MUSE data.

High resolution analysis of the CD[formula omitted] deuterated methane: Extended investigation of the pentad region

A highly accurate rotational–vibrational analysis of Fourier transform infrared spectra of the 12CD4 molecule is presented. The high resolution infrared spectra were measured with a IFS125 HR Fourier transform interferometer from Bruker at an optical resolution of 0.003 cm−1 and analyzed in the 1750–2400 cm−1 region. Here the 2ν2, ν2+ν4, 2ν4, ν1 and ν3 bands (altogether, nine sub-bands of different symmetry) of the pentad are located. The number of 1213/1993/1576/77/1582 transitions with the Jmax = 23/23/23/14/32 were assigned to the 2ν2, ν2+ν4, 2ν4, ν1 and ν3 bands of 12CD4. The obtained experimental data were used for the determination of the upper ro-vibrational energy values. To provide more correct values of the upper energies, more than 7800 highly accurate “hot” transitions from the dyad region were additionally processed. In general, 4088 upper ro-vibrational energies of the pentad (for comparison, 2525 upper ro-vibrational energies with the value of Jmax=20 are known in the modern literature up to now) were determined, which were used then in the weighted fit procedure with a goal to determine the spectroscopic parameters (band centers, rotational, centrifugal distortion, tetrahedral splitting and resonance interaction parameters) of the effective Hamiltonian. The obtained drms value is 5.5×10−4 cm−1 which is almost one hundred times better than the reproduction of the same set of experimental data by the parameters known in the earlier literature.

Simultaneous assessment of NAD(P)H and flavins with multispectral fluorescence lifetime imaging microscopy at a single excitation wavelength of 750nm.

Autofluorescence characteristics of the reduced nicotinamide adenine dinucleotide and oxidized flavin cofactors are important for the evaluation of the metabolic status of the cells. The approaches that involve a detailed analysis of both spectral and time characteristics of the autofluorescence signals may provide additional insights into the biochemical processes in the cells and biological tissues and facilitate the transition of spectral fluorescence lifetime imaging into clinical applications. We present the experiments on multispectral fluorescence lifetime imaging with a detailed analysis of the fluorescence decays and spectral profiles of the reduced nicotinamide adenine dinucleotide and oxidized flavin under a single excitation wavelength aimed at understanding whether the use of multispectral detection is helpful for metabolic imaging of cancer cells. We use two-photon spectral fluorescence lifetime imaging microscopy. Starting from model solutions, we switched to cell cultures treated by metabolic inhibitors and then studied the metabolism of cells within tumor spheroids. The use of a multispectral detector in combination with an excitation at a single wavelength of 750nm allows the identification of fluorescence signals from three components: free and bound NAD(P)H, and flavins based on the global fitting procedure. Multispectral data make it possible to assess not only the lifetime but also the spectral shifts of emission of flavins caused by chemical perturbations. Altogether, the informative parameters of the developed approach are the ratio of free and bound NAD(P)H amplitudes, the decay time of bound NAD(P)H, the amplitude of flavin fluorescence signal, the fluorescence decay time of flavins, and the spectral shift of the emission signal of flavins. Hence, with multispectral fluorescence lifetime imaging, we get five independent parameters, of which three are related to flavins. The approach to probe the metabolic state of cells in culture and spheroids using excitation at a single wavelength of 750nm and a fluorescence time-resolved spectral detection with the consequent global analysis of the data not only simplifies image acquisition protocol but also allows to disentangle the impacts of free and bound NAD(P)H, and flavin components evaluate changes in their fluorescence parameters (emission spectra and fluorescence lifetime) upon treating cells with metabolic inhibitors and sense metabolic heterogeneity within 3D tumor spheroids.

The goodness-of-fit of models for fracture trace length distribution: Does the power law provide a good fit?

Fracture trace length distributions are often assumed to follow a power law, which implies that the distribution is scale-independent. The present study tests this assumption by evaluating the goodness-of-fit of three statistical models—the power law, piecewise power law, and lognormal distribution—upon a dataset of 57 trace maps that cover a range of fracture modes, host rock types, network scales, and topologies. The goodness-of-fit was assessed through the unbiased Kolmogorov-Smirnov (KS) test, which accounts for the fitting procedure and the degrees of freedom of each model. The results show that the power law provides a poor fit to trace length distributions, being rejected in 24 trace maps at a significance level of 0.05. In contrast, the piecewise power law and lognormal distribution demonstrated better fits across the fracture networks, with the piecewise power law performing the best overall. The poor fit of the power law can be attributed to mechanical and chemical controls on fracture growth, mainly fracture abutment, as well as stress shadowing and cementation, which affect growth rate at different length scales and result in scale-dependent trace length distributions. The consistent poor fit of the power law across various fracture networks suggests that these controls are prevalent in natural systems. While the power law remains a simple and effective model for trace length distribution, it should be recognized that it overlooks such controls that can influence the mechanical and hydraulic properties of fracture networks. Meanwhile, the fit of the piecewise power-law suggests the existence of a characteristic length where a transition in fracture growth occurs.

Analytical potential energy functions for CO in its ground and excited electronic states.

Accurate functions to analytically represent the potential energy interactions of CO diatomic system in , , and electronic states are proposed. The new functions depend upon only four parameters directly obtained from experimental data, without any fitting procedure. These functions have been developed from the modified generalized potential proposed by Araújo and Ballester. The function for the electronic state represents a significant improvement to the previously proposed model. To quantify the accuracy of the potential energy functions, the Lippincont test is used. The novel potential was also compared with the classical Morse potential and with the recently proposed Improved Generalized Pöschl-Teller potential. Furthermore, the main spectroscopic constants and vibrational energy levels are calculated and compared for all potentials. The present results agree excellently with the experiment Rydberg-Klein-Rees (RKR) potentials. The rovibrational energy levels of the proposed diatomic potentials were asserted by solving radial the Schrödinger equation of the nuclear motion with the aid of the LEVEL program.

Rapid sloshing-free transport of liquids in arbitrarily shaped containers

AbstractWe present a model-based feedforward control strategy suitable for designing swift rest-to-rest maneuvers for liquids in arbitrarily shaped containers. We employ the commonly used equivalent pendulum model to represent the sloshing dynamics and suggest a novel parameter identification scheme suitable for arbitrary container shapes and any number of sloshing modes. By computing natural modes and fluid reaction forces and torques for imposed harmonic container motions via a finite element model, we obtain data for the identification scheme. A fitting procedure then yields highly accurate parameters for a physical pendulum model, where each pendulum represents one sloshing mode. We also provide a thorough analysis of parameter identifiability and guidelines for obtaining robust parameter estimates. The proposed feedforward control method uses a virtual tray pendulum on which we place the container (in the form of its equivalent pendulum model). Designing the virtual tray such that the fluid’s dominant sloshing mode cannot be excited by horizontally moving the tray pendulum pivot effectively zeros out any sloshing motion in this mode. We then exploit the flatness property of the resulting system to design rest-to-rest maneuvers where any residual sloshing motion (in higher modes) can be exactly stopped at the end of the maneuver. The effectiveness of the proposed method is demonstrated through extensive simulations and experimental results using a Martini cocktail glass, whose shape is challenging in terms of sloshing. The experimental results show the successful, accurate suppression of sloshing, validating the efficacy of the proposed concept.

The reverse-DADI method: Computation of frequency-dependent atomic polarizabilities for carbon and hydrogen atoms in hydrocarbon structures

A specific method, combining some ingredients of the well-known DDA and PDI approaches, has been developed in our group since many years to calculate the absorption cross-sections of carbonaceous nanoparticles based on their atomistic details. This method, here named the Dynamic Atomic Dipole Interaction (DADI) model, requires the knowledge of the position and frequency-dependent polarizability of each atom constituting the nanoparticles. While the atomic positions can be quite easily obtained, for example as the results of molecular dynamics simulations, obtaining the frequency-dependent atomic polarizabilities is a trickier task. Here, a fitting procedure, named the reverse-DADI method, has been applied to calculate the frequency-dependent atomic polarizability values for carbon and hydrogen atoms involved in aromatic cycles or in aliphatic chains, on the basis of frequency-dependent molecular polarizabilities of various PAH and alkane molecules, calculated with the TD-DFT theory, in the UV–Visible range. Then, using these frequency-dependent atomic polarizabilities as input parameters in the DADI model has been shown to lead to an accurate representation of the absorption cross-sections of various PAH and alkane molecules with respect to the corresponding values obtained at the TD-DFT level, with however the great advantage of a much shorter time of calculations. Furthermore, these results are indications of a good transferability of the frequency-dependent atomic polarizability values obtained here to any C or H atom of any PAH or alkane molecule. This opens the way for building large databases of optical properties for carbonaceous species of atmospheric or astrophysical interests.

Fitting x-ray diffraction peaks by a genetic algorithm and Monte Carlo Markov Chain procedure

A fitting procedure based on the use of the Genetic algorithms (GA) and the Markov Chain Monte Carlo (MCMC) bayesian technique is proposed for the modelization of the x-ray diffraction peaks by using the usual standard bell-type functions (pseudo-Voigt, Voigt, etc). The method has been tested with simulated Voigt-shaped profiles at different overlapping degrees and the results have been compared with those obtained by means of the classical Levenberg-Marquardt algorithm, showing its reliability.

Dehydration of tomato peels and seeds as affected by the temperature

SummaryAn empirical model was developed for dehydrating tomato's peels and seeds (TPS) at three different temperatures (i.e. 50 °C, 60 °C and 70 °C). The model assumes that there is an initial constant drying rate period (first stage) followed by a decreasing drying rate period (second stage). To assess the goodness of fitting procedure, the mean relative deviation modulus was calculated. Results indicate that the model can adequately describe the dehydration data. The robustness of the model was further tested by evaluating the dependence of model parameters on the temperature, using an Arrhenius‐type equation. Recorded findings show that model parameters changed with the temperature, thus confirming that the proposed model can be advantageously used to describe the dehydration kinetic of TPS. The influence of TPS dehydration on temperature was also assessed by calculating the dehydration rate as function of TPS water content. Results demonstrate that the dehydration rate increases as the testing temperature increases too. In both drying stages, the difference between the dehydration rate at 50 °C and the one at the other two temperatures is more marked.

Exploring the CIEDE2000 thresholds for lightness, chroma, and hue differences in dentistry

ObjectiveTo evaluate the perceptibility and acceptability CIEDE2000 (KL:KC:KH) thresholds for lightness, chroma and hue differences in dentistry. MethodA Python-based program was developed to conduct a psychophysical experiment based on visual assessments of computer-simulated images of human teeth. The experiment was performed on a calibrated display. A 40-observer panel: dentists and laypersons (male and female; n=10), evalu- ated three subsets of simulated human teeth: the lightness subset (%∆L00 ≥ 98 %), the chroma subset (%∆C00 ≥ 98 %) and the hue subset (%∆H00 ≥ 98 %), using ∆E00 ≥ 5 units. A Takagi-Sugeno-Kang Fuzzy Approximation model was used as fitting procedure, and 50:50 % lightness, chroma and hue CIEDE2000 (1:1:1) and CIEDE2000 (2:1:1) perceptibility (PT00) and accept- ability (AT00) thresholds were calculated. Data was statistically analyzed using t-test (p < 0.05). ResultsThe 50:50 % PT00 for KL=1 were ∆L00=1.04, ∆C00=1.58 and ∆E00=1.01; and for KL=2 were ∆L00=0.51, ∆C00=1.58 and ∆E00=0.71. The 50:50 % AT00 for KL=1 were ∆L00=2.82, ∆C00=3.04 and ∆E00=2.66; and for KL=2 were ∆L00=1.40, ∆C00=3.04 and ∆E00=1.78. PT00 and AT00 ∆H00 may be considered no computable. A significant difference was found between CIEDE2000(1:1:1) and CIEDE2000(2:1:1), between lightness and chroma metrics, and between observer groups. No differences for lightness and chroma PT00 were found between male and female groups. ConclusionsIt is important to use PT00 and AT00 for lightness, chroma and hue specific to evaluate perceptual sensitivity for color changes in the tooth color space. AT00 for lightness and chroma are influenced by the observer's experience and gender. Males and laypersons show more tolerance for changes in chroma (∆C00) and in lightness (∆L00). SignificanceHue and chroma mismatch are more difficult to be accepted in dental color space.

Comprehensive measurement of three-dimensional thermal conductivity tensor using a beam-offset square-pulsed source (BO-SPS) approach

Accurately measuring the three-dimensional thermal conductivity tensor is essential for understanding and engineering the thermal behavior of anisotropic materials. Existing methods often struggle to isolate individual tensor elements, leading to large measurement uncertainties and time-consuming iterative fitting procedures. In this study, we introduce the Beam-Offset Square-Pulsed Source (BO-SPS) method for comprehensive measurements of three-dimensional anisotropic thermal conductivity tensors. This method uses square-pulsed heating and precise temperature rise measurements to achieve high signal-to-noise ratios, even with large beam offsets and low modulation frequencies, enabling the isolation of thermal conductivity tensor elements. We demonstrate and validate the BO-SPS method by measuring X-cut and AT-cut quartz samples. For X-cut quartz, with a known relationship between in-plane and cross-plane thermal conductivities, we can determine the full thermal conductivity tensor and heat capacity simultaneously. For AT-cut quartz, assuming a known heat capacity, we can determine the entire anisotropic thermal conductivity tensor, even with finite off-diagonal elements. Our results yield consistent principal thermal conductivity values for both quartz types, demonstrating the method's reliability and accuracy. This research highlights the BO-SPS method's potential to advance the understanding of thermal behavior in complex materials.