Continuous-Domain Real-Time Distributed ADMM Algorithm for Aggregator Scheduling and Voltage Stability in Distribution Network
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Realizing the full potential of genome editing for crop improvement has been slow due to inefficient methods for reagent delivery and the reliance on tissue culture for creating gene-edited plants. RNA viral vectors offer an alternative approach for delivering gene engineering reagents and bypassing the tissue culture requirement. Viruses, however, are often excluded from the shoot apical meristem, making virus-mediated gene editing inefficient in some species. Here, we developed effective approaches for generating gene-edited shoots in Cas9-expressing transgenic tomato plants using RNA virus-mediated delivery of single-guide RNAs (sgRNAs). RNA viral vectors expressing sgRNAs were either delivered to leaves or sites near axillary meristems. Trimming of the apical and axillary meristems induced new shoots to form from edited somatic cells. To further encourage the induction of shoots, we used RNA viral vectors to deliver sgRNAs along with the cytokinin biosynthesis gene, isopentenyl transferase. Abundant, phenotypically normal, gene-edited shoots were induced per infected plant with single and multiplexed gene edits fixed in the germline. The use of viruses to deliver both gene editing reagents and developmental regulators overcomes the bottleneck in applying virus-induced gene editing to dicotyledonous crops such as tomato and reduces the dependency on tissue culture.
Abstract Background and Objective Activated potassium channels were found to be strongly correlated with gingival overgrowth (GO) phenotype as we reviewed syndromic hereditary gingival fibromatosis (HGF). Nevertheless, the functional roles of potassium channels in gingival fibrosis or gingival overgrowth remained uncovered. The aim of the present study was to explore the pathogenic role of aberrantly activated potassium channel in Hereditary Gingival Fibromatosis (HGF). Methods Gingival tissues were collected from 9 HGF patients and 15 normal controls. Expression of KCNQ1 was detected by immunohistochemistry. Gingival fibroblasts were isolated, and outward K + currents were detected by whole‐cell patch‐clamp analysis, transmembrane potential was determined by flow cytometry. Normal human gingival fibroblasts (NHGFs) were transfected with KCNQ1 adenovirus or treated with KCNQ1 selective agonist ML277 and antagonist chromanol 293B. Accumulation of Extracellular Matrix (ECM) was measured by Western blotting and Sircol Soluble Collagen Assay. Content of secreted TGF‐β1 was measured by ELISA. Active RAS pull‐down assay and cell immunofluorescence were utilized to verify RAS activation. Results KCNQ1 was upregulated in gingival tissues derived from HGF patients and HGF gingival fibroblasts presented increased outward K + currents than NHGFs. Overexpression of KCNQ1, or KCNQ1 agonist ML277, promoted fibrotic responses of NHGFs. TGF‐β1 and KCNQ1 channels formed a positive feed‐back loop. ML277 generated lateral clustering and activation of Ras on plasma membrane, followed by augmented MAPK/AP‐1 signaling pathway output. JNK or ERK1/2 inhibitors suppressed ML277‐induced AP‐1 and ECM upregulation. Conclusion Activation of KCNQ1 potassium channel promoted fibrogenic responses in NHGFs via Ras/MAPK/AP‐1 signaling.
Adopting an effective top coal caving method is the key to enhancing coal recovery and reducing gangue content for the fully mechanized top coal caving working face with extra‐thick coal seams. In this study, the movement of coal particles generated during top coal caving is considered to follow a normal distribution. Then, the caving body and coal‐rock settlement along the working face during the caving process are studied based on both the random media theory and probability theory. Accordingly, the optimal caving interval and caving sequences are determined, and a novel interval symmetrical coal caving method is proposed. The proposed method is systematically verified with results from physical similarity tests, and different caving methods are assessed by field tests. The results show the following: (1) The coal‐rock settlement and the caving body demonstrate clear axial symmetrical features along the working face; the size of the caving body increases as the caving height grows and its shape turns progressively from semicircular to semielliptical with a lower foot of the coal‐rock settlement. (2) The caving interval is derived using the sum of the radii of the coal‐rock settlement curves formed by the two largest caving bodies. (3) The symmetrical caving approach provides a symmetrical space for the subsequent movement of the broken top coal, which enables a uniform development of the caving body. (4) Compared with the traditional sequential coal caving method with the same number of supports, the interval symmetrical caving method results in a 21.7% of coal production increase, 17% caving rate promotion, and a shortened caving time by 23.4%. (5) The interval symmetrical caving method is found to improve the controllability of the caving process at the fully mechanized top coal caving working face. In general, this work presents a theoretical approach to select the optimal caving methods for the fully mechanized caving working face in extra‐thick coal seams for an improved production efficiency of the work face. The results of this study can also provide theoretical significance and referencing value for quantitative analyses of the coal caving methods for work faces with similar geological conditions.
A NACA 0018 airfoil in freestream velocity is oscillated in longitudinal, transverse, and angle-of-attack directions with respect to the freestream velocity, known as surge, plunge, and pitch. The lift-based equivalence method introduces phase shifts between these three motions to construct in-phase sinusoidal components for maximum lift, waveform construction. Lift cancellation is also determined with the exact negative pitch and plunge motion amplitudes found from the equivalence method to achieve out-of-phase wave destruction. Lift cancellation occurs when a combination of these motions is sought to obtain a constant lift magnitude throughout the oscillation cycle. To achieve both equivalence and cancellation of lift, a prescribed pure pitch amplitude through the Theodorsen theory equates the corresponding equivalent plunge amplitude and pitch–plunge phase shift. These Theodorsen, linear superposition findings of pitch–plunge are leveraged toward the Greenberg theory to determine a closed-form, surge–pitch–plunge solution through the addition of a surge–plunge phase shift and optimal surge amplitude for lift cancellation. The lift cancellation surge–pitch–plunge amplitudes define the equivalence amplitude investigated here and theoretically limit the experiment to combinations of the first lift harmonic of the Greenberg theory. The analytical results are then compared with experimental lift force measurements and dye visualization. Finally, the normalized lift differences due to unsteady wake and boundary-layer behavior are examined to explore the extents of the Greenberg theory for these cases of lift-based equivalence and cancellation.
The performance of Ru/CeO 2 catalysts under CO 2 hydrogenation conditions was studied using in situ X-ray absorption fine structure (XAFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) to understand the structural evolution and chemical nature of each component under reaction conditions. The catalysts were prepared using a reverse microemulsion method that maximized the dispersion of RuOx particles on ceria. A RuO x → Ru transformation was observed upon exposure of the RuO x /CeO 2 systems to H 2 at 250 °C. For a sample with 5% molar Ru, two-dimensional clusters (2-4 atoms) of Ru formed on top of the ceria support. An increase in the loading of ruthenium to 20% molar led to the formation of nanoplates of the metal 2-3 atomic layers thick. Both Ru structures were highly dispersed on ceria. They were oxidized after exposure to CO 2 at 250 °C. However, under CO 2 /H 2 mixture, they remained in a metallic state as two-dimensional clusters and nanoplates. In situ DRIFTS studies, the 5% and 20% Ru/CeO 2 catalysts showed distinct reaction intermediates when exposed to CO 2 or CO 2 /H 2 (1/4) reaction mixtures. Normalized to the Ru molar percentage, the 5% Ru/CeO 2 system was the most active catalyst exhibiting a selectivity of ~ 60% CH 4 and 40% CO at 250 °C. On the other hand, under the same reaction conditions, the 20% Ru/CeO 2 system was less active but had a CH 4 selectivity close to 80%. In conclusion, these results highlight the importance of the structure of the metallic Ru particles as a factor that determines the catalytic performance.
We study the three-point form factor of the length-three half-BPS operator (Tr ϕ 3 ) in planar $\mathcal{N}$ = 4 Super-Yang-Mills theory, using analyticity and integrability methods. We find that the functions describing the form factor in perturbation theory live in the same restrictive space of multiple polylogarithms as the one describing the form factor of the stress-tensor operator (Tr ϕ 2 ). Furthermore, we find that the leading-order data in the collinear limit provided by the form factor operator product expansion (FFOPE) is enough to fix the form factor uniquely, at least through six loops. We perform various tests of our results using the subleading FFOPE corrections. We also analyze the form factor in the Regge limit where two Mandelstam invariants are large; we obtain a compact representation for the form factor in this limit which is valid to all orders in the coupling.
Nuclear fusion science is an example of a scientific field with a rich history of expert involvement and scientific publications, which together, form an expert-knowledge base. One example of a nuclear fusion formalism is the utilization of published reaction rates from a variety of authors. Investigators for Deuterium- Tritium (D-T) ion fusion can choose from using frequently cited methods: the Bosch and Hal reactivity, thermonuclear reaction rates from Caughlan and Fowler, and the reactivity evaluation from Miley, Towner & Ivich which forms the basis of the Naval Research Lab (NRL) formulary. There are other choices available. Each of the reactivity formulations considered here, are based upon the Maxwell-Boltzmann velocity distribution for D-T fusion ion reactants. Numerical methods for computer codes simulating hot, energetic plasmas, include tabulations of the reactivity, and the first moment of energy. This report continues the step toward building understanding of nuclear fusion reactivity formalisms. It is part of a series of reports with the same goal, [5-10] and is the continuation of the Part I paper for defining the mathematical relationship of the first moment of D-T fusion ion kinetic energy, <$E$>, with the fusion cross-section, fusion reactivity and its derivative with ion-temperature. In Part I, three variants of the first moment <$E$> were analytically developed and explored: 1) constant cross-section, 2) a normalized first moment, and 3) a particular function of the first moment from Brysk. In Part II, attention is given to the definition of <$K$>, originally described as a ratio of moments from Brysk, and its relationship to the first moment definitions from Part I. One measure of the progress made in these documents is the identification that Brysk’s ratio of the second moment to the first moment ratio, <$K$>, does not correspond to his provided solution of the first moment of energy. Another measure of (our) progress from this work is the comparison of first moment variants. That comparison includes confirming the importance of cross sections defined in terms of energy. The analytical relationships we have developed among important physics quantities are useful tools in validation and verification (V&V). For example, we can calculate the kinetic energy as a mean or as a first moment, or as a function of the first moment. These analytically-determined values can be compared directly with numerically-determined values, supplied to the authors, representing <$E$>.
The integration of thermal energy storage into a concentrating solar power system allows for mitigating some of the risk associated with uncertain solar irradiance and uncertain energy prices. We solve a 48 h dispatch optimization model with continually updated conditional point forecasts of both direct normal irradiance (DNI) and electricity prices with a rolling-horizon scheme at hourly resolution over the course of a year. Joint, conditional forecasts for DNI and prices are formed using an autoregressive moving-average time series model with exogenous weather predictors. We guide dispatch using a mixed-integer programming model, but in order to evaluate performance we use the System Advisor Model (SAM) of the National Renewable Energy Laboratory. SAM is a techno-economic simulation model that accounts for plant thermodynamics with higher fidelity. Our conditional DNI forecasts improve annual revenue by 4%–12% over using historical forecasts based on data from previous years. Conditional price forecasts improve annual revenue by 6%–19% in the real-time market over analogous historical forecasts. Updating these forecasts every six hours, rather than every 24 h, further improves annual revenue by 5%–6%. Here, we also investigate a method that values terminal inventory in our dispatch optimization model, again when used in a rolling-horizon scheme.
Cancer is one of the diseases with the highest mortality rate worldwide. Although PDT has recently produced encouraging outcomes, there are still many areas that need to be improved. The first of these is the negative consequences faced by patients treated with the PDT method when exposed to sunlight. For this reason, a new PDT method has been developed in recent years, and it is aimed at using photosensitizer molecules that can be active in acidic conditions. Since the pH values of tumor tissues are more acidic than normal tissues, preparing molecules that act effectively in acidic conditions will allow for more effective results in treating cancer with PDT. In this context, within the scope of this study, 3‐(4‐propionylphenoxy)phthalonitrile ( 1 ) and its non‐peripheral tetra‐substituted phthalocyanine derivatives [( 2 ), ( 3 ), and ( 4 )] were prepared. With these phthalocyanine derivatives, the novel compounds ( 5 ), ( 6 ), and ( 7 ) were synthesized for the first time. The aggregation tendencies of newly synthesized phthalocyanines ( 5–7 ) were investigated in solvent media. The effects of pH changes upon UV–Vis and fluorescence spectra were performed. The electronic and emission spectra of synthesized phthalocyanine derivatives are highly sensitive to pH changes. Formation constant (Log K) values of mono‐ and di‐protonated phthalocyanine forms were calculated by the Henderson–Hasselback equation. The mono‐ and di‐protonated species' equilibrium constants (logK 1 and logK 2 ) were calculated as ~5.0. This value may be promising for pH‐sensitizing photosensitizers. Also, the photophysical and photochemical properties of synthesized metallophthalocyanine derivatives ( 2 ) and ( 5 ) were studied at different pH values. The singlet oxygen quantum yield of ( 2 ) and ( 5 ) was calculated to be 0.78 and 0.81 in DMSO, respectively. When pH = 6.4, that is, tumor‐pH‐values, this value for ( 5 ) has increased to 0.92. The newly synthesized phthalocyanines are suitable photosensitizers for PDT applications, especially with high singlet oxygen quantum yield at pH 6.4.
This study primarily focuses on examining the impact that geometric structure has on thermal conductivity of multi-phase constructs in different 3D-printed poly(lactic acid), PLA, samples. The investigated structures are inspired by morphologies formed by diblock copolymers: lamellae, hexagonally packed cylinders, and gyroid. This research also investigates how volume percentage and material combination influence the thermal conductivity of these structures. Further, the samples can be tailored to simulate various thermal management structures observed in practical applications, such as thermal interface materials in electronic devices. Thermal conductivity ratio is controlled using air, the least conductive material at 0.026 W/(m K), PLA at 0.136 W/(m K), and thermal paste at 5.11 W/(m K). Different models were tested against thermal conductivity measurements in order to capture the effect of material type (PLA-Air versus PLA-Thermal Paste), volume percentage, structure, and orientation. Simple, effective medium models were good predictions of thermal conductivity in lamellar structures, but it was necessary to develop models for conduction through cylindrical and gyroid structures. Finally, all results were normalized to find a universal model that is independent of structure and material. This approach provides a simple method to predict how to reduce or enhance transport properties and heat management capabilities of 3D printed objects.
Nuclear fusion science is an example of a scientific field with a rich history of expert involvement and scientific publications, which together, form an expert-knowledge base. One example of this history is the utilization of published reaction rates from a variety of authors. Investigators for Deuterium-Tritium (D-T) ion fusion can choose from using frequently cited methods: the Bosch and Hale reactivity, thermonuclear reaction rates from Caughlan and Fowler, and the reactivity evaluation from Miley, Towner & Ivich which forms the basis of the Naval Research Lab (NRL) formulary. There are other choices available. Each of the reactivity formulations considered here, are based upon the Maxwell- Boltzmann velocity distribution for D-T fusion ion reactants. Numerical methods for computer codes simulating hot, energetic plasmas, include tabulations of the reactivity, and the first moment of energy. The purpose of this study is to answer the question: what is the first moment of energy, and how has it been formulated? This report is part of a series of reports by the authors on D-T fusion-reaction formalism. The present focus is on defining the mathematical relationship of the first moment of D-T fusion ion kinetic energy, $\langle$E$\rangle$, with the fusion crosssection, fusion reactivity and its derivative with respect to ion-temperature. Three variants of the first moment $\langle$E$\rangle$ are analytically developed and explored: 1) constant cross-section, 2) a normalized first moment, and 3) a particular function of the first moment. Much of the mathematical development is relegated to the Appendices, for a concise presentation of topics and results. A research component of this discussion is our comparison of some of the reactivity and its derivative results between evaluations (1) versus (2) and (3), which the authors have not found in any other publication to date. This investigation is useful for validation, verification (V&V) and uncertainty quantification (UQ) as it compares the work of several authors.
Heterojunction Si solar cells exhibit notable performance degradation. Here, we modeled this degradation by electronic defects getting generated by thermal activation across energy barriers over time. To analyze the physics of this degradation, we developed the SolDeg platform to simulate the dynamics of electronic defect generation. First, femtosecond molecular dynamics simulations were performed to create a-Si/c-Si stacks, using the machine learning-based Gaussian approximation potential. Second, we created shocked clusters by a cluster blaster method. Third, the shocked clusters were analyzed to identify which of them supported electronic defects. Fourth, the distribution of energy barriers that control the generation of these electronic defects was determined. Fifth, an accelerated Monte Carlo method was developed to simulate the thermally activated time-dependent defect generation across the barriers. Our main conclusions are as follows. (1) The degradation of a-Si/c-Si heterojunction solar cells via defect generation is controlled by a broad distribution of energy barriers. (2) We developed the SolDeg platform to track the microscopic dynamics of defect generation across this wide barrier distribution and determined the time-dependent defect density N(t) from femtoseconds to gigaseconds, over 24 orders of magnitude in time. (3) We have shown that a stretched exponential analytical form can successfully describe the defect generation N(t) over at least 10 orders of magnitude in time. (4) We found that in relative terms, Voc degrades at a rate of 0.2%/year over the first year, slowing with advancing time. (5) We developed the time correspondence curve to calibrate and validate the accelerated testing of solar cells. We found a compellingly simple scaling relationship between accelerated and normal times t normal ∝ t accel T(accel)/T(normal) . (6) We also carried out experimental studies of defect generation in a-Si:H/c-Si stacks. We found a relatively high degradation rate at early times that slowed considerably at longer time scales.
Phenomenological R-matrix has been a standard framework for the evaluation of resolved resonance cross section data in nuclear physics for many years. It is a powerful method for comparing different types of experimental nuclear data and combining the results of many different experimental measurements in order to gain a better estimation of the true underlying cross sections. Yet a practical challenge has always been the estimation of the uncertainty on both the cross sections at the energies of interest and the fit parameters, which can take the form of standard level parameters. Frequentist (χ 2 -based) estimation has been the norm. In this work, a Markov Chain Monte Carlo sampler, emcee, has been implemented for the R-matrix code AZURE2, creating the Bayesian R-matrix Inference Code Kit (BRICK). Bayesian uncertainty estimation has then been carried out for a simultaneous R-matrix fit of the 3 He (α,γ) 7 Be and 3 He (α,α) 3 He reactions in order to gain further insight into the fitting of capture and scattering data. Both data sets constrain the values of the bound state α-particle asymptotic normalization coefficients in 7 Be. The analysis highlights the need for low-energy scattering data with well-documented uncertainty information and shows how misleading results can be obtained in its absence.
Active millimeter and microwave imaging techniques can be used to create a high-resolution 3D image volume of a target’s reflectivity. Millimeter-wave imaging is commonly used for personnel security screening and numerous other applications. Backprojection based image reconstruction techniques form a 3D complex-valued volume. The complex-valued volume is commonly reduced to a real-valued volume by taking the magnitude. For anomaly detection and cross image registration of an object it is beneficial to generate an accurate representation of an object’s surface. Extracting a smooth and accurate surface from a magnitude only image is challenging. One difficulty is the magnitude image has limited resolution in the depth direction which normally limits precision to a moderate fraction of the depth resolution. Another difficulty is that the magnitude of the image depends heavily on the geometry and orientation of the object being imaged. The phase information in a complex-valued image volume provides a means to decouple the magnitude of the image from the geometry of an object and provide precision much finer than the depth resolution would indicate. This enables the generation of a smooth and accurate point cloud representation of the surface of an imaged object. A method to extract a point cloud from the phase information in a 3D complex-valued millimeter-wave image volume is developed and results with simulated and experimental data are presented.
The U.S. DOE has designed four spent nuclear fuel (SNF) dry storage canisters for storing DOE standardized SNFs. The DOE standard canisters are cylindrical shells with a diameter of 24 inches (610 m) or 18 inches (457 m), a wall thickness of 0.5 inches (12.7 m) or 0.375 inches (9.53 m), and a length of 15 feet (4.57 m) or 10 feet (3.05 m). These DOE canister geometries are completely different from commercial canisters. The latter may experience chloride-induced stress cracking corrosion (CI-SCC) because they are stored near coastal regions. The former may not experience CI-SCC but face different challenges because they are stored in the SNF storage facilities. Because of large residual stresses, mechanical flaws may occur in the DOE canisters during long-distance transportation or lifting handling. To date, only limited structural integrity analyses were carried out through drop tests on the DOE canisters, but a more general flaw tolerance assessment has not been performed. Therefore, the failure assessment diagram (FAD)-based fracture mechanics method, as codified by the latest API 579-1/ASME FFS-1-2021 Edition, is adopted in this work to assess surface flaw tolerance for DOE canisters under operation loading and welding residual stresses (WRS), where the new code-recommended WRS distributions are used. To more adequately consider the transverse distribution of WRS, an equivalent WRS distribution is proposed to account for the WRS reduction with distance from the weld centerline. Moreover, the closed-form solutions of stress intensity factor K, which serves as the crack driving force during subcritical crack growth, are developed from the tabular data of the K factors provided in API 579-1/ASME FFS-1 and used to determine more accurate flaw sizes at flaw instability. Subsequently, the Level 2 assessment procedures with 12 assessment steps, as codified and detailed in API 579-1 and ASME FFS-1, are followed to assess the flaw tolerance for the surface flaws in the DOE standard canisters with consideration of normal or accident operation loads combined with WRS. The assessment results show that the four designs of DOE standard canisters can tolerate all surface flaws that meet the code permitted maximum sizes of a flaw length of 8 inches (i.e., 200 mm) and a flaw depth of 80% wall thickness. This demonstrates that all designs of DOE standard canisters are robust and reliable.
Data-driven identification of differential equations is an interesting but challenging problem, especially when the given data are corrupted by noise. When the governing differential equation is a linear combination of various differential terms, the identification problem can be formulated as solving a linear system, with the feature matrix consisting of linear and nonlinear terms multiplied by a coefficient vector. This product is equal to the time derivative term, and thus generates dynamical behaviors. The goal is to identify the correct terms that form the equation to capture the dynamics of the given data. We propose a general and robust framework to recover differential equations using a weak formulation with two new mechanisms, narrow-fit and trimming, for both ordinary and partial differential equations (ODEs and PDEs). The weak formulation facilitates an efficient and robust way to handle noise, and two new mechanisms, narrow-fit and trimming, improve the coefficient support and value recoveries respectively. For each sparsity level, Subspace Pursuit is utilized to find an initial set of support from the large dictionary. Then, we focus on highly dynamic regions (rows of the feature matrix), and error normalize the feature matrix in the narrow-fit step. The support is further updated via trimming the terms that contribute the least. Finally, the support set of features with the smallest Cross-Validation error is chosen as the result. A comprehensive set of numerical experiments are presented for both systems of ODEs and PDEs with various noise levels. The proposed method gives a robust recovery of the coefficients, and a significant denoising effect which can handle up to 100% noise-to-signal ratio for some equations. We compare the proposed method with several state-of-the-art algorithms for the recovery of differential equations.
Galaxy evolution has been studied by interpreting the spectral energy distribution of galaxies using spectral synthesis codes. This method has been crucial in discovering different pillars of modern galaxy evolution theories. However, this analysis was mostly carried out using spectral synthesis codes that are purely stellar, that is, they assume that the nebular contribution to the total continuum is negligible. The code FADO is the first publicly available population spectral synthesis tool that treats the contribution from ionised gas to the observed emission self-consistently. This is expected to have a particularly strong effect in star-forming (SF) galaxies. We study the impact of the nebular contribution on the determination of the star formation rate (SFR), stellar mass, and consequent effect on the star-forming main sequence (SFMS) at low redshift. We applied FADO to the spectral database of the SDSS to derive the physical properties of galaxies. As a comparison, we used the data in the MPA-JHU catalogue, which contains the properties of SDSS galaxies derived without the nebular contribution. We selected a sample of SF galaxies with Hα and Hβ flux measurements, and we corrected the fluxes for the nebular extinction through the Balmer decrement. We then calculated the Hα luminosity to estimate the SFR. Then, by combining the stellar mass and SFR estimates from FADO and MPA-JHU, the SFMS was obtained. The Hα flux estimates are similar between FADO and MPA-JHU. Because the Hα flux was used as tracer of the SFR, FADO and MPA-JHU agree in their SFR. The stellar mass estimates are slightly higher for FADO than for MPA-JHU on average. However, considering the uncertainties, the differences are negligible. With similar SFR and stellar mass estimates, the derived SFMS is also similar between FADO and MPA-JHU. Our results show that for SDSS normal SF galaxies, the additional modelling of the nebular contribution does not affect the retrieved fluxes and consequentially also does not influence SFR estimators based on the extinction-corrected Hα luminosity. For the stellar masses, the results point to the same conclusion. These results are a consequence of the fact that the vast majority of normal SF galaxies in the SDSS have a low nebular contribution. However, the obtained agreement might only hold for local SF galaxies, but higher-redshift galaxies might show different physical properties when FADO is used. This would then be an effect of the expected increased nebular contribution.