Fitting Procedure Research Articles

Determining the Sparking Voltage of Working Electrolytes

Sparking voltage is one of the vital parameters of the working electrolytes for aluminum electrolytic capacitors, which determines the operating voltage of the capacitors. However, the existing methods for measuring the sparking voltage suffer from low accuracy, bad reproducibility, high artificial error, etc. In this paper, we reported a versatile approach to determining the sparking voltage of the electrolytes. By a linear fitting procedure, the voltage-time data acquired from the test experiments were transformed into a correlation coefficient-time curve. Since the abrupt correlation coefficient change due to the occurrence of sparking could be more readily identified in the correlation coefficient-time curve, the limit voltage of the electrolyte was accurately determined. Thus, this voltage was subtracted from the IR drop in the solution to get the true sparking voltage of the electrolyte. This method prevented artificial errors arising from the direct observation or listening of sparking features, by which reliable and reproducible results can be gained by a computer program. This study provided active support for the development of high-performance working electrolytes.

AugmentA: Patient-specific augmented atrial model generation tool.

Digital twins of patients' hearts are a promising tool to assess arrhythmia vulnerability and to personalize therapy. However, the process of building personalized computational models can be challenging and requires a high level of human interaction. We propose a patient-specific Augmented Atria generation pipeline (AugmentA) as a highly automated framework which, starting from clinical geometrical data, provides ready-to-use atrial personalized computational models. AugmentA identifies and labels atrial orifices using only one reference point per atrium. If the user chooses to fit a statistical shape model to the input geometry, it is first rigidly aligned with the given mean shape before a non-rigid fitting procedure is applied. AugmentA automatically generates the fiber orientation and finds local conduction velocities by minimizing the error between the simulated and clinical local activation time (LAT) map. The pipeline was tested on a cohort of 29 patients on both segmented magnetic resonance images (MRI) and electroanatomical maps of the left atrium. Moreover, the pipeline was applied to a bi-atrial volumetric mesh derived from MRI. The pipeline robustly integrated fiber orientation and anatomical region annotations in 38.4±5.7s. In conclusion, AugmentA offers an automated and comprehensive pipeline delivering atrial digital twins from clinical data in procedural time.

Measurements and calculations of CO2-broadening and shift coefficients of water vapor transitions in the 5150–5550 cm−1 spectral region

The high-resolution H2O absorption spectra induced by CO2 pressure have been recorded using a Bruker IFS 125 HR FTIR spectrometer at room temperature in the 5150–5550 cm–1 spectral region. A multispectrum fitting procedure has been applied to these spectra to recover the spectral line parameters using the speed-dependent Voigt profile. The water vapor line broadening and shift coefficients for lines of two vibrational bands ν2+ν3 and ν1+ν2 were obtained. An uncertainty of the broadening coefficients for the unblended H2O absorption lines was estimated to be 2–3%. The calculations of line-broadening and line-shifting parameters were performed using the semi-empirical method which is based on the impact theory and enables a realistic prediction modified by introducing additional parameters obtained by using empirical data. The root mean square deviations of measured and calculated line widths and shifts were 0.0086 and 0.0053 cm−1 atm−1, respectively.

Multifrequency bioimpedance device based on the Analog Discovery 2: performance and characterization

Abstract Bioimpedance spectroscopy can be used to investigate the composition and monitor the human body, organs, tissues, or cell cultures by measuring the voltage developed by the injection of small alternating currents at different frequencies. These currents are injected sequentially through a frequency sweep and a with a Howland current source or one of its modifications. However, the frequency sweep is not time efficient and introduces problems with data coherence in the case of bioinstability. On the other hand, the Howland current source requires high precision matching between its components. In this contribution we developed a custom-made device for bioimpedance measurements based on a multisine current waveform and on a negative-feedback topology for the current source. Measurements on passive elements showed that the device had less than 1Ω and 0.05∘ uncertainty in the frequency range between 500 Hz and 200 kHz for impedance between 1 kΩ and 10 kΩ. The measurements were affected by an inductive artifact connected with the limited common-mode rejection at high frequencies. Nevertheless, we could characterize the artifacts through a fitting procedure to recover the expected value of the targeted impedance.

Unveiling the Evolutionary State of Three B Supergiant Stars: PU Gem, ϵ CMa, and η CMa

We aim to combine asteroseismology, spectroscopy, and evolutionary models to establish a comprehensive picture of the evolution of Galactic blue supergiant stars (BSG). To start such an investigation, we selected three BSG candidates for our analysis: HD 42087 (PU Gem), HD 52089 (ϵ CMa), and HD 58350 (η CMa). These stars show pulsations and were suspected to be in an evolutionary stage either preceding or succeding the red supergiant (RSG) stage. For our analysis, we utilized the 2-min cadence TESS data to study the photometric variability, and we obtained new spectroscopic observations at the CASLEO observatory. We used non-LTE radiative transfer models calculated with CMFGEN to derive their stellar and wind parameters. For the fitting procedure, we included CMFGEN models in the iterative spectral analysis pipeline XTgrid to determine their CNO abundances. The spectral modeling was limited to changing only the effective temperature, surface gravity, CNO abundances, and mass-loss rates. Finally, we compared the derived metal abundances with prediction from Geneva stellar evolution models. The frequency spectra of all three stars show stochastic oscillations and indications of one nonradial strange mode, fr= 0.09321 d−1 in HD 42087 and a rotational splitting centred in f2= 0.36366 d−1 in HD 52089. We conclude that the rather short sectoral observing windows of TESS prevent establishing a reliable mode identification of low frequencies connected to mass-loss variabilities. The spectral analysis confirmed gradual changes in the mass-loss rates, and the derived CNO abundances comply with the values reported in the literature. We were able to achieve a quantitative match with stellar evolution models for the stellar masses and luminosities. However, the spectroscopic surface abundances turned out to be inconsistent with the theoretical predictions. The stars show N enrichment, typical for CNO cycle processed material, but the abundance ratios did not reflect the associated levels of C and O depletion. We found HD 42087 to be the most consistent with a pre-RSG evolutionary stage, HD 58350 is most likely in a post-RSG evolution and HD 52089 shows stellar parameters compatible with a star at the TAMS.

Low-Scaling Algorithm for the Random Phase Approximation Using Tensor Hypercontraction with k-point Sampling.

We present a low-scaling algorithm for the random phase approximation (RPA) with k-point sampling in the framework of tensor hypercontraction (THC) for electron repulsion integrals (ERIs). The THC factorization is obtained via a revised interpolative separable density fitting (ISDF) procedure with a momentum-dependent auxiliary basis for generic single-particle Bloch orbitals. Our formulation does not require preoptimized interpolating points or auxiliary bases, and the accuracy is systematically controlled by the number of interpolating points. The resulting RPA algorithm scales linearly with the number of k-points and cubically with the system size without any assumption on sparsity or locality of orbitals. The errors of ERIs and RPA energy show rapid convergence with respect to the size of the THC auxiliary basis, suggesting a promising and robust direction to construct efficient algorithms of higher order many-body perturbation theories for large-scale systems.

Atomic cluster expansion for Pt–Rh catalysts: From ab initio to the simulation of nanoclusters in few steps

Insight into structural and thermodynamic properties of nanoparticles is crucial for designing optimal catalysts with enhanced activity and stability. In this work, we present a semi-automated workflow for parameterizing the atomic cluster expansion (ACE) from ab initio data. The main steps of the workflow are the generation of training data from accurate electronic structure calculations, an efficient fitting procedure supported by active learning and uncertainty indication, and a thorough validation. We apply the workflow to the simulation of binary Pt–Rh nanoparticles that are important for catalytic applications. We demonstrate that the Pt–Rh ACE is able to reproduce accurately a broad range of fundamental properties of the elemental metals as well as their compounds while retaining an outstanding computational efficiency. This enables a direct comparison of atomistic simulations to high-resolution experiments.Graphical abstract

Fractional Modeling of Cancer with Mixed Therapies.

Cancer is the biggest cause of mortality globally, with approximately 10 million fatalities expected by 2020, or about one in every six deaths. Breast, lung, colon, rectum, and prostate cancers are the most prevalent types of cancer. In this work, fractional modeling is presented which describes the dynamics of cancer treatment with mixed therapies (immunotherapy and chemotherapy). Mathematical models of cancer treatment are important to understand the dynamical behavior of the disease. Fractional models are studied considering immunotherapy and chemotherapy to control cancer growth at the level of cell populations. The models consist of the system of fractional differential equations (FDEs). Fractional term is defined by Caputo fractional derivative. The models are solved numerically by using Adams-Bashforth-Moulton method. For all fractional models the reasonable range of fractional order is between β = 0.6 and β = 0.9. The equilibrium points and stability analysis are presented. Moreover, positivity and boundedness of the solution are proved. Furthermore, a graphical representation of cancerous cells, immunotherapy and chemotherapy is presented to understand the behaviour of cancer treatment. At the end, a curve fitting procedure is presented which may help medical practitioners to treat cancer patients.

The impact of COVID-19 lockdowns on urban photochemistry as inferred from TROPOMI

Movement restrictions were imposed in 2020 to mitigate the spread of Covid-19. These lock-down episodes provide a unique opportunity to study the sensitivity of urban photochemistry to temporary emission reductions and test air quality models. This study uses Tropospheric Monitoring Instrument (TROPOMI) nitrogen dioxide/carbon monoxide (NO2/CO) ratios in urban plumes in combination with an exponential fitting procedure to infer changes in the NOx lifetime (τNOx) during Covid-19 lock-downs in the cities of Denver, Chicago, New York, Riyadh, Wuhan and Sao Paulo compared with the year before.The strict lockdown policy in Wuhan led to a 65–80% reduction in NO2, compared to 30–50% in the other cities that were studied. In New York and Wuhan, CO concentration was reduced by 10–15%, whereas over Riyadh, Denver, Chicago, and Sao Paulo the CO background concentration increased by 2–5 ppb. τNOx has been derived for calm (0.0 < U (m/s) < 3.5) and windy (5.0 < U (m/s) < 8.5) days to study the influence of wind speed. We find reductions in τNOx during Covid-19 lockdowns in all six megacities during calm days. The largest change in τNOx during calm days is found for Sao-Paulo (31.8 ± 9.0%), whereas the smallest reduction is observed over Riyadh (22 ± 6.6%). During windy days, reductions in τNOx are observed during Covid-19 lockdowns in New York and Chicago. However, over Riyadh τNOx is almost similar for windy days during the Covid-19 lockdown and the year before.Ground-based measurements and the Chemistry Land-surface Atmosphere Soil Slab (CLASS) model have been used to validate the TROPOMI-derived results over Denver. CLASS simulates an enhancement of ozone (O3) by 4 ppb along with reductions in NO (38.7%), NO2 (25.7%) and CO (17.2%) during the Covid-19 lockdown in agreement with the ground-based measurements. In CLASS, decreased NOx emissions reduce the removal of OH in the NO2 + OH reaction, leading to higher OH concentrations and decreased τNOx. The reduction in τNOx inferred from TROPOMI (28 ± 9.0%) is in agreement with CLASS. These results indicate that TROPOMI derived NO2/CO ratios provide useful information about urban photochemistry and that changes in photochemical lifetimes can successfully be detected.

Ab Initio DFT and MD Simulations Serving as an Anchor for Correcting Melting Curves Reported by DAC and SW Experiments—Some Transition Metals as Illustrative Examples

The pressure–temperature scales in DAC and shock wave (SW) experiments should be corrected by taking into account the thermal pressure shifts. In the present contribution, it is further claimed that first-principle ab initio DFT and MD simulations should serve as an anchor for correcting the pressures and temperatures reported by DAC and SW experiments. It was concluded that upon deriving the actual pressure sensed by the explored sample, the thermal pressure and the temperature shifts must be taken into account when constructing melting curves. Therefore, melting curves measured by diamond anvil cells for 3d elements do not contribute to a better understanding of the geophysical Earth’s inner core. In addition, the advantage of the Lindemann–Gilvarry vs. Simon–Glatzel fitting procedure of melting curves is shown.

Modeling the Migration Behavior of Extractables from Mono- and Multilayer Polyolefin Films to Mathematically Predict the Concentration of Leachable Impurities in Pharmaceutical Drug Products. Part 2: Conservative Diffusion and Partition Coefficient Determinations.

In the development of a pharmaceutical drug product packaging, an important step is to demonstrate acceptable levels of leachable impurities migrating from the packaging material into the drug product during its shelf life and therapeutic use. Such migration processes can be quantified either by analytical methods (which is often challenging and labor intensive) or (in many cases) through theoretical modeling, which is a reliable, quick, and cost-effective method to forecast the level of leachable impurities in the packaged drug when the diffusion and partition coefficients are known. In the previous part, it was shown how these parameters can be determined experimentally, and subsequent theoretical fitting of the results for a series of low- and high-molecular-weight organic compounds (known leachables) in a series of polyolefin materials was performed. One of the interpretations of these results is that a theoretical calculation can be made only for organic compounds and materials whose diffusion/partition/solubility coefficients were determined experimentally and theoretical fitting was achieved. However, in practice, there will be situations in which other leachable compounds may have to be investigated. In such cases, strictly speaking, it would be necessary to perform the whole experimental and fitting procedure for the new compound before a proper theoretical modeling is possible. But this would make the theoretical calculation of a leaching process from a pharmaceutical packaging material a cumbersome and cost intensive procedure. To address this problem, the pools of diffusion and partition coefficients were used to develop an approach that allows the estimation, without any additional experimentation, of so-called "conservative" diffusion and partition coefficients for a much wider range of potential leachables in the polyolefin pharmaceutical packaging materials and aqueous solutions investigated previously.

A Systematic Review of the Audiological Efficacy of Cartilage Conduction Hearing Aids and the Factors Influencing Their Clinical Application.

This systematic review evaluates the efficacy and benefit of cartilage conduction hearing aids (CC-HAs) and that factors that influence purchasing decisions. The hearing thresholds and functional gain following CC-HA wear were synthesised. A one-way analysis of variance compared the differences in the hearing thresholds and functional gain at individual frequencies and in patients with a variety of pathological changes. The synchronised aided hearing threshold and functional gain at 2.0 kHz were significantly better than at 0.5, 1.0, and 4.0 kHz. There was no significant difference in the synchronised unaided hearing thresholds across individual frequencies between 0.5 and 4.0 kHz. The synchronised functional gain in patients with atresia was significantly greater than in patients with aural atresia or stenosis and middle ear pathologies with normal ear canals. The acceptability of CC-HAs in terms of purchase decision is influenced by the condition of the external auditory meatus and severity of hearing loss, with the highest purchase rate seen in patients with aural atresia or stenosis. CC-HAs' fitting procedure advantages and cosmetic considerations make these devices a viable and preferred choice for individuals with microtia and aural atresia. Additional research to evaluate the benefits towards emotional well-being is crucial to gain insights into the psychological impact of CC-HA use.

Universal ontogenetic growth without fitted parameters: implications for life history invariants and population growth

Since the work of von Bertalanffy (Q Rev Boil 32:217–231, 1957), several models have been proposed that relate the ontogenetic scaling of energy assimilation and metabolism to growth, which are able to describe ontogenetic growth trajectories for living organisms and collapse them onto a single universal curve (West et al. in Nature 413:628–631, 2001; Barnavar et al. in Nature 420:626, 2002). Nevertheless, all these ontogenetic growth models critically depend on fitting parameters and on the allometric scaling of the metabolic rate. Using a new metabolic rate relation (Escala in Theor Ecol 12(4):415–425, 2019) applied to a Bertalanffy-type ontogenetic growth equation, we find that ontogenetic growth can also be described by a universal growth curve for all studied species, but without the aid of any fitting parameters (i.e., no fitting procedure is performed on individual growth curves). We find that the inverse of the heart frequency mathrm f_H, rescaled by the ratio of the specific energies for biomass creation and metabolism, defines the characteristic timescale for ontogenetic growth. Moreover, our model also predicts a generation time and lifespan that explain the origin of several “Life History Invariants’ (Charnov in Oxford University Press, Oxford, 1993) and predict that the Malthusian parameter should be inversely proportional to both the generation time and lifespan, in agreement with the data in the literature (Duncan et al. in Ecology 88:324–333 2007; Dillingham et al. in Paper 535, 2016; Hatton et al. in PNAS 116(43):21616–21622 2019). In our formalism, several critical timescales and rates (lifespan, generation time, and intrinsic population growth rate) are all proportional to the heart frequency mathrm f_H, and thus, their allometric scaling relations come directly from the allometry of the heart frequency, which is typically mathrm f_H propto M^{-0.25} under basal conditions.

Inshore Ship Detection Based on Multi-Modality Saliency for Synthetic Aperture Radar Images

Synthetic aperture radar (SAR) ship detection is of significant importance in military and commercial applications. However, a high similarity in intensity and spatial distribution of scattering characteristics between the ship target and harbor facilities, along with a fuzzy sea-land boundary due to the strong speckle noise, result in a low detection accuracy and high false alarm rate for SAR ship detection with complex inshore scenes. In this paper, a new inshore ship detection method based on multi-modality saliency is proposed to overcome these challenges. Four saliency maps are established from different perspectives: an ocean-buffer saliency map (OBSM) outlining more accurate coastline under speckle noises; a local stability saliency map (LSSM) addressing pixel spatial distribution; a super-pixel saliency map (SPSM) extracting critical region-based features for inshore ship detection; and an intensity saliency map (ISM) to highlight target pixels with intensity distribution. By combining these saliency maps, ship targets in complex inshore scenes can be successfully detected. The method provides a novel interdisciplinary perspective (surface metrology) for SAR image segmentation, discovers the difference in spatial characteristics of SAR image elements, and proposes a novel robust CFAR procedure for background clutter fitting. Experiments on a public SAR ship detection dataset (SSDD) shows that our method achieves excellent detection performance, with a low false alarm rate, in offshore scenes, inshore scenes, inshore scenes with confusing metallic port facilities, and large-scale scenes. The results outperform several widely used methods, such as CFAR-based methods and super-pixel methods.

Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations

LiteBIRD is a planned JAXA-led cosmic microwave background (CMB) B-mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, δr, down to δr &lt; 0.001. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust spectral energy distribution, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compared the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the High-Frequency Telescope (HFT) frequency range was shifted logarithmically toward higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measured the tensor-to-scalar ratio r uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on r after foreground cleaning may be reduced by as much as 30–50% by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to higher residuals when fitting an incorrect dust model, but also it is easier to discriminate between models through higher χ2 sensitivity. Even in the case in which the fitting procedure does not correspond to the underlying dust model in the sky, and when the highest frequency data cannot be modeled with sufficient fidelity and must be excluded from the analysis, the uncertainty on r increases by only about 5% for a 500 GHz configuration compared to the baseline.

The role of grain size in active galactic nuclei torus dust models

Context. Active galactic nuclei (AGN) are surrounded by dust within the central parsecs. The dusty circumnuclear structures, referred to as the torus, are mainly heated by radiation from the AGN and emitted at infrared wavelengths, producing the emergent dust continuum and silicate features. Fits to the infrared spectra from the nuclear regions of AGN can place constraints on the dust properties, distribution, and geometry by comparison with models. However, none of the currently available models fully describe the observations of AGN currently available. Aims. Among the aspects least explored, here we focus on the role of dust grain size. We offer the community a new spectral energy distribution (SED) library which is based on the two-phase torus model developed before with the inclusion of the grain size as a model parameter, parameterized by the maximum grain size Psize or equivalently the mass-weighted average grain size ⟨P⟩. Methods. We created 691 200 SEDs using the SKIRT code, where the maximum grain size can vary within the range Psize = 0.01 − 10.0 μm (⟨P⟩ = 0.007 − 3.41 μm). We fit this new library and several existing libraries to a sample of 68 nearby and luminous AGN with Spitzer/IRS spectra dominated by AGN-heated dust. Results. We find that the GoMar23 model can adequately reproduce up to ∼85–88% of the spectra. The dust grain size parameter significantly improves the final fit in up to 90% of these spectra. Statistical tests indicate that the grain size is the third most important parameter in the fitting procedure (after the size and half opening angle of the torus). The requirement of a foreground extinction by our model is lower compared to purely clumpy models. We find that ∼41% of our sample requires that the maximum dust grain size is as large as Psize ∼ 10 μm (⟨P⟩∼3.41 μm). Nonetheless, we also remark that disk+wind and clumpy torus models are still required to reproduce the spectra of a nonnegligible fraction of objects, suggesting the need for several dust geometries to explain the infrared continuum of AGN. Conclusions. This work provides tentative evidence for dust grain growth in the proximity of the AGN.

Comparison of neural closure models for discretised PDEs

Neural closure models have recently been proposed as a method for efficiently approximating small scales in multiscale systems with neural networks. The choice of loss function and associated training procedure has a large effect on the accuracy and stability of the resulting neural closure model. In this work, we systematically compare three distinct procedures: "derivative fitting", "trajectory fitting" with discretise-then-optimise, and "trajectory fitting" with optimise-then-discretise. Derivative fitting is conceptually the simplest and computationally the most efficient approach and is found to perform reasonably well on one of the test problems (Kuramoto-Sivashinsky) but poorly on the other (Burgers). Trajectory fitting is computationally more expensive but is more robust and is therefore the preferred approach. Of the two trajectory fitting procedures, the discretise-then-optimise approach produces more accurate models than the optimise-then-discretise approach. While the optimise-then-discretise approach can still produce accurate models, care must be taken in choosing the length of the trajectories used for training, in order to train the models on long-term behaviour while still producing reasonably accurate gradients during training. Two existing theorems are interpreted in a novel way that gives insight into the long-term accuracy of a neural closure model based on how accurate it is in the short term.

Effective Dipole Moment Model for Axially Symmetric C3v Molecules: Application to the Precise Study of Absolute Line Strengths of the ν6 Fundamental of CH335Cl.

The effective dipole moment model for molecules of axial C3v symmetry is derived on the basis of the symmetry properties of a molecule which, on the one hand, is of the same order of efficiency (but much simpler and clearer in applications) as the analogous models derived on the basis of the irreducible tensorial sets theory, and, on the other hand, mathematically more correct in comparison with concepts like the Herman-Walles function used in the models. As an application of the general results obtained, we discuss high-resolution infrared spectra of CH335Cl, recorded with the Zürich prototype ZP2001 (Bruker IFS125 HR) Fourier transform infrared spectrometer at a resolution of 0.001 cm-1 and analyzed in the region of 880-1190 cm-1 (ν6 bending fundamental centered at ν0 = 1018.070790 cm-1). Absolute strengths of more than 2800 transitions (2081 lines) were obtained from the fit of their shapes both with Voigt and Hartmann-Tran profiles, and parameters of the effective dipole moment of the ν6 band were determined by the computer code SYMTOMLIST (SYMmetric TOp Molecules: LIne STrengths), created on the basis of a derived theoretical model. As the first step of the analysis of the experimental data, assignments of the recorded lines were made. A total of 5124 transitions with Jmax = 68, Kmax = 21 were assigned to the ν6 band. The weighted fit of 2077 upper energy values obtained from the experimentally recorded transitions was made with a Hamiltonian which takes into account different types of ro-vibrational effects in doubly degenerate vibrational states of the C3v-symmetric molecule. As the result, a set of 25 fitted parameters was obtained which reproduces the initial 2077 upper "experimental" ro-vibrational energy values with a root mean square deviation drms=4.7×10-5 cm-1. At the second step of the analysis, the computer code SYMTOMLIST was used for determination of the parameters of the derived effective dipole moment model. Six effective dipole moment parameters were obtained from the weighted fit procedure which reproduces absolute experimental strengths of the 2804 initial experimental transitions with a relative drms=3.4%.

Dark energy–matter equivalence by the evolution of cosmic equation of state

We consider a model-independent approach to constrain the equivalence redshift, zeq, at which dark energy and the total matter (cold dark matter and baryonic) equate their magnitudes. To this aim, in the context of a homogeneous and isotropic universe, we first consider a generic model where the dark energy contribution is provided by an unknown function of barotropic fluids. Afterwards, we compute the deceleration and jerk parameters, evaluating at our epoch, namely z=0, and at z=zeq. Thus, by Taylor expanding around current time the Hubble rate, luminosity and angular distances, we substitute the theoretical expressions obtained from the aforementioned generic dark energy model, defining a correspondence between quantities evaluated at z=0 and z=zeq. In so doing, we directly fit these quantities by means of current data sets, involving the most recent Pantheon type Ia supernovae, baryonic acoustic oscillation and Hubble rate points. We consider two hierarchies in our fitting procedures and compare our findings in the spatially-flat universe first and including spatial curvature, later. We assess constraints on the overall equation of state of the universe and its first derivative. We compare our results with those predicted by the standard ΛCDM paradigm. Specifically, our findings are in agreement at the 2σ confidence level, assuming a constant dark energy term. However, our analysis does not rule out the possibility of a slight evolution of dark energy, indicating a small deviation from the scenario of a pure cosmological constant. In particular, the possible departures appear consistent with a phenomenological ωCDM model, rather than more complicated dark energy parameterizations.

Non-Contact and Self-Calibrated Photopyroelectric Method for Complete Thermal Characterization of Porous Materials.

A general theory of a photopyroelectric (PPE) configuration, based on an opaque sample and transparent pyroelectric sensor, backing and coupling fluids is developed. A combined back-front detection investigation, based on a frequency scan of the phase of the PPE signals, followed by a self-normalization of the phases' behavior, leads to the possibility of simultaneously measuring both thermal effusivity and diffusivity of a solid sample. A particular case of this configuration, with no coupling fluid at the sample/backing interface and air instead of coupling fluid at the sample/sensor interface (non-contact method) is suitable for simultaneous measurement ofboth thermal diffusivity and effusivity (in fact complete thermal characterization) of porous solids. Compared with the already proposed configurations for investigations of porous materials, this novel configuration makes use of a fitting procedure with only one fitting parameter, in order to guarantee the uniqueness of the solution. The porous solids belong to a class of materials which are by far not easy to be investigated using PPE. To the best of our knowledge, porous materials represent the only type of compounds, belonging to condensed matter, which were not taken into consideration (until recently) as potential samples for PPE calorimetric investigations. Consequently, the method proposed in this paper complete the area of applications of the PPE method. Applications on some porous building materials and cellulose-based samples validate the theory.