Power-law Model Research Articles

Effect of chitosan molecular weight and protein to polysaccharide ratio on the rheological and physicochemical properties of milk proteins–chitosan complex coacervate

The small amplitude oscillatory shear (SAOS) rheological properties of complex coacervate of milk proteins with high (HMC), medium (MMC), and low (LMC) molecular weight chitosan in the optimal ratios of milk proteins to chitosan (15:1, 10:1, and 5:1, respectively) were measured. In addition, the morphological (SEM), structural (XRD), and thermal (DSC) properties of the complex coacervates were investigated in comparison with the milk protein concentrate. Complex coacervates showed the shear-thinning behavior due to a linear decrease of complex viscosity with increasing frequency. Furthermore, the highest complex modulus and the more compact structure under optimal conditions, in terms of the ratio of protein to chitosan and pH, revealed strong electrostatic bonding between proteins and chitosan. All coacervates showed a G′ > G″ (Tanδ<1), indicating the formation of an interconnected gel-like structure that was described by the power law model. The maximum fracture stress was obtained at optimum conditions (R = 15:1, pH =6.7 for HMC; R = 10:1, pH =5.5 for MMC and R = 5:1, pH =4.6 for LMC), indicating the highest intermolecular interaction between milk proteins and chitosan. The coacervates had a completely amorphous structure similar to MPC, and according to DSC results, the ionic bonds between milk proteins and chitosan were not destroyed up to 300 °C. Coacervation leads to purified milk proteins at a low cost. In addition, the coacervates can be used for the encapsulation of heat-sensitive compounds, and also as a stabilizer to improve the texture of food.

The Thermal Emission in Short Gamma-Ray Bursts with Extended Emission Observed by Fermi/GBM

Short gamma-ray bursts (SGRBs) with extended emission (EE) are composed of initial main emission (ME) with a short hard spike, followed by a long-lasting EE. Whether the ME and EE originated from the same origin or not, as well as the jet composition, remains an open question. In this paper, we present a systematic analysis of 36 gamma-ray bursts (GRBs) in our sample, which are identified as the category of SGRBs with EE as observed by Fermi/Gamma-ray Burst Monitor. By extracting time-integrated spectra of ME and EE with cutoff power-law or Band models for our sample, we find that 20 out of 36 SGRBs have α values that exceed the death line (e.g., −2/3) of synchrotron emission within either ME or EE phases, and we suggest that the quasi-thermal component should exist in the prompt emission. Then, we extract the time-resolved spectra of our samples, but only four GRBs are bright enough to extract the time-resolved spectra. We find that both thermal and nonthermal emissions do exist in the prompt emission of those four bright GRBs, which suggests that a hybrid jet (e.g., matter and Poynting-flux outflow) in GRBs should exist. Moreover, strong positive correlations (e.g., F tot–Γ and F tot–kT) in the time-resolved spectra of ME and EE for those four GRBs have been discovered. This indicates that the spectral evolution of both ME and EE seem to share similar behavior, possibly from the same physical origin.

Triggering the Untriggered: The First Einstein Probe-detected Gamma-Ray Burst 240219A and Its Implications

The Einstein Probe (EP) achieved its first detection and localization of a bright X-ray flare, EP240219a, on 2024 February 19, during its commissioning phase. Subsequent targeted searches triggered by the EP240219a alert identified a faint, untriggered gamma-ray burst (GRB) in the archived data of Fermi Gamma-ray Burst Monitor (GBM), Swift Burst Alert Telescope (BAT), and Insight-HXMT/HE. The EP Wide-field X-ray Telescope (WXT) light curve reveals a long duration of approximately 160 s with a slow decay, whereas the Fermi/GBM light curve shows a total duration of approximately 70 s. The peak in the Fermi/GBM light curve occurs slightly later with respect to the peak seen in the EP/WXT light curve. Our spectral analysis shows that a single cutoff power-law (PL) model effectively describes the joint EP/WXT–Fermi/GBM spectra in general, indicating coherent broad emission typical of GRBs. The model yielded a photon index of ∼–1.70 ± 0.05 and a peak energy of ∼257 ± 134 keV. After detection of GRB 240219A, long-term observations identified several candidates in optical and radio wavelengths, none of which was confirmed as the afterglow counterpart during subsequent optical and near-infrared follow-ups. The analysis of GRB 240219A classifies it as an X-ray-rich GRB (XRR) with a high peak energy, presenting both challenges and opportunities for studying the physical origins of X-ray flashes, XRRs, and classical GRBs. Furthermore, linking the cutoff PL component to nonthermal synchrotron radiation suggests that the burst is driven by a Poynting flux-dominated outflow.

Probing broadband spectral energy distribution and variability of Mrk 501 in the low flux state

We conducted a multi-wavelength analysis of the blazar Mrk501, utilizing observations from AstroSat (SXT, LAXPC), Swift-UVOT, and Fermi-LAT during the period August 15, 2016 to March 27, 2022. The resulting multi-wavelength light curve revealed relatively low activity of the source across the electromagnetic spectrum. Notably, logparabola and broken power-law models provided a better fit to the joint X-ray spectra from AstroSat-SXT/LAXPC instruments compared to the power-law model. During the low activity state, the source showed the characteristic “harder when brighter” trend at the X-ray energies. To gain insights into underlying physical processes responsible for the broadband emission, we performed a detailed broadband spectral analysis using the convolved one-zone leptonic model with different forms of particle distributions such as logparabola (LP), broken power-law (BPL), power-law model with maximum energy (ξmax), and energy-dependent acceleration (EDA) models. Our analysis revealed similar reduced-χ2 values for the four particle distributions. The LP and EDA models exhibited the lowest jet powers. The correlation analyses conducted for the LP and BPL models revealed that there is a positive correlation between jet power and bulk Lorentz factor. Specifically, in the LP model, jet power proved independent of γmin, whereas in the broken power-law model, jet power decreased with an increase in γmin. The jet power in the LP/EDA particle distribution is nearly 10 percent of the Eddington luminosity of a 107 M⊙ black hole. This result suggests that the jet could potentially be fueled by accretion processes.

Field cycling imaging to characterise breast cancer at low and ultra-low magnetic fields below 0.2 T

BackgroundThis prospective feasibility study explores Field-Cycling Imaging (FCI), a new MRI technology that measures the longitudinal relaxation time across a range of low magnetic field strengths, providing additional information about the molecular properties of tissues. This study aims to assess the performance of FCI and investigate new quantitative biomarkers at low fields within the context of breast cancer.MethodsWe conducted a study involving 9 people living with breast cancer (10 tumours in total, mean age, 54 ± 10 years). FCI images were obtained at four magnetic field strengths (2.3 mT to 200 mT). FCI images were processed to generate T1 maps and 1/T1 dispersion profiles from regions of tumour, normal adipose tissue, and glandular tissue. The dispersion profiles were subsequently fitted using a power law model. Statistical analysis focused on comparing potential FCI biomarkers using a Mann-Whitney U or Wilcoxon signed rank test.ResultsWe show that low magnetic fields clearly differentiate tumours from adipose and glandular tissues without contrast agents, particularly at 22 mT (1/T1, median [IQR]: 6.8 [3.9–7.8] s−1 vs 9.1 [8.9–10.2] s−1 vs 8.1 [6.2–9.2] s−1, P < 0.01), where the tumour-to-background contrast ratio was highest (62%). Additionally, 1/T1 dispersion indicated a potential to discriminate invasive from non-invasive cancers (median [IQR]: 0.05 [0.03–0.09] vs 0.19 [0.09–0.26], P = 0.038).ConclusionsTo the best of our knowledge, we described the first application of in vivo FCI in breast cancer, demonstrating relevant biomarkers that could complement diagnosis of current imaging modalities, non-invasively and without contrast agents.

Evaluation of the effect of viscosity on blood flow using viscosity models

The study of blood hemodynamics and rheological properties, particularly blood viscosity, is essential for understanding and treating certain cardiovascular conditions. Blood is a non-Newtonian fluid, meaning its viscosity varies with shear rate, a behavior driven by the aggregation and deformation of red blood cells (RBCs). Accurate modeling of blood viscosity is therefore critical for simulating blood flow in both physiological and pathological states. In this work, various viscosity models were assessed to identify the most suitable that represents the blood’s behavior in relation to shear rate. Although the Newtonian model is simple, it fails to capture the non-Newtonian characteristics of blood, particularly at varying shear rates. In comparison, the Power Law, Walburn-Schneck, and Carreau-Yasuda models offer more detailed and complex approaches to modeling blood viscosity. The Effect of blood viscosity on the overall blood flow was evaluated based on the four viscosity models. The work was carried out in a MATLAB Simulation Environment. The Volumetric blood flow rate was evaluated from the Poiseuille’s equation using three viscosity models whose values were defined by shear rates ranging from (217.5 – 226.5)s−1 . The percentage change in the blood volume resulting from changes in the viscosity was examined for each model. The two viscosity models (Power and Carreau models) concurrently reported equal percentage change of blood flux variation with the corresponding variation of the viscosity due to change in shear rate. This shows that any of the two models can be used to study the variation of blood flow to the viscosity with respect to cardiovascular complications.

Power-Law Modeling for Swift Viscoelastic Assessment in Biological Soft Tissues

In addressing the viscoelastic behavior of biological soft tissues, the precise and expeditious measurement methodologies hold paramount significance, given the intrinsic softness and heightened aqueous content of such substrates. We have introduced an expeditious modality for the characterization of viscoelasticity in biological soft tissues, hinged upon a power-law model. This method has been rigorously validated through ramp–hold tests conducted on mechanically stable hydrogels. Notably, during the Ramp phase, the viscoelastic parameters of the material can be readily extracted. Furthermore, we applied unconfined compression stress-relaxation/creep tests with three different ramp–strain rates, namely [Formula: see text], on both white and gray matter to enable rapid quantification. The results indicate that the predicted curves during the Hold phase exhibit notable consistency with experimental data. Moreover, under quasi-static loading conditions, an increase in strain rate significantly enhances the predictive adaptability. Nonetheless, it is crucial to be mindful of the sensitivity to initial stress conditions. This study offers a promising avenue for the expeditious characterization of soft tissue viscoelasticity. It underscores the feasibility of mechanical characterization metrics from a phenomenological model for the assessment of physiological variations and pathological mechanisms in tissue states.

On the Complex Flow Dynamics of Shear Thickening Fluids Entry Flows

Due to their nature, using shear thickening fluids (STFs) in engineering applications has sparked an interest in developing energy-dissipating systems, such as damping devices or shock absorbers. The Rheinforce technology allows the design of customized energy dissipative composites by embedding microfluidic channels filled with STFs in a scaffold material. One of the reasons for using microfluidic channels is that their shape can be numerically optimized to control pressure drop (also known as rectifiers); thus, by controlling the pressure drop, it is possible to control the energy dissipated by the viscous effect. Upon impact, the fluid is forced to flow through the microchannel, experiencing the typical entry flow until it reaches the fully developed flow. It is well-known for Newtonian fluid that the entrance flow is responsible for a non-negligible percentage of the total pressure drop in the fluid; therefore, an analysis of the fluid flow at the entry region for STFs is of paramount importance for an accurate design of the Rheinforce composites. This analysis has been numerically performed before for shear-thickening fluids modeled by a power-law model; however, as this constitutive model represents a continuously growing viscosity between end-viscosity plateau values, it is not representative of the characteristic viscosity curve of shear-thickening fluids, which typically exhibit a three-region shape (thinning-thickening-thinning). For the first time, the influence of these three regions on the entry flow on an axisymmetric pipe is analyzed. Two-dimensional numerical simulations have been performed for four STFs consisting of four dispersions of fumed silica nanoparticles in polypropylene glycol varying concentrations (7.5–20 wt%).

Exploring slip flow and heat transfer of power-law fluid past an induced magnetic stretching regime subject to Cattaneo-Christov flux theory

This work investigates the heat transmission and boundary layer (BL) slip flow of a power-law fluid induced by stretching surfaces. The power-law fluid, induced magnetic field, and finite thermal relaxation have significant applications in a variety of industrial settings, including thin-layer growth, cooling systems, the extrusion process, and coating and shaping operations in a heat transfer mechanism. With these significant industrial applications, the current study explores BL flow and heat transfer in the context of the of the Cattaneo-Christov theory against the backdrop of an induced magnetic field over a stretching surface. The shear-thinning and thickening features are captured by the power-law fluid model, while the Cattaneo-Christov theory solves the deficiencies of Fourier's law. The BVP4c technique is used to construct and solve BL equations numerically. The surface drag and heat transmission rates at the wall are studied using statistical multi-regression analysis. The findings clarify that the magnetic and power law indices have a favorable effect on the Nusselt number, while their influence on skin friction is conflicting. A lower heat transmission is predicted with thermal relaxation as compared to Fourier's law in the energy equation. The accumulated thermal relaxation parameter produces a non-equilibrium state, delaying the internal thermal processes.

Impact of Fluid Rheology and Density Ratio in Droplet Collision: A Numerical Investigation

Abstract This research delves into the intricate interplay of fluid rheology, characterized by the power-law model, and density ratio ρr=ρlρg in the context of droplet collision dynamics. The power-law index (n) is systematically varied within the range of 0.5 to 1.5, while the density ratio spans two orders of magnitude, ranging from 101-103. Comprehensive investigations are conducted across various impact parameters (B = 0 - 0.75) and Weber numbers (We = 40 - 160). A noteworthy finding is the cessation of droplet coalescence at elevated Weber numbers (We = 160), revealing a critical threshold beyond which coalescence is no longer sustained. The impact of fluid rheology on internal fluid flow dynamics within the complex droplet structure is substantial. The variation in viscous dissipation with (n) contributes to observable changes in the critical wavelength of the complex droplet rim structure, consequently influencing the size of child droplets. Furthermore, the density ratio is a pivotal factor influencing the deformation rate during collision events. A decrease in density ratio correlates with a reduction in the deformation ratio, shedding light on the significant role of density ratio in shaping the dynamics of droplet collisions.

Effect of porous defects on mechanical behavior of functionally graded materials

Porous defects in functionally graded materials (FGMs) significantly change their mechanical behavior, in particular, affecting the displacement of the neutral plane and stress distribution. Defects such as porosity reduce material bending strength while enhancing compression strength and can lead to significant transverse effects. The purpose of this study is to clarify the influence of porosity on transverse effects based on new kinematic model. This research consider in detail a particular case of this model, that allows take into account two Poisson`s effects separately. This study examines the influence of porosity on FGM, highlighting the critical role of changes in Poisson’s ratio through thickness. The theory used for analytical solution satisfies the nullity of the shear stresses at the upper and lower surfaces of the plate without using the shear correction factor. The network of pores proposed to be empty or filled with low-pressure air and material properties graded by thickness according to power-law and exponential models. Navier solution method is used to solve the governing differential equations of equilibrium. The concentration of porosity at the center of the plate or in separate layers results in a reduction in normal tensile stresses along the longitudinal coordinate, suggesting that strategic placement of porosity can be used to reduce stress concentrations, potentially enhancing the structural integrity and performance of functionally graded materials under mechanical loading.

Non-Newtonian fluids effects on the steady-state performance of two-lobe journal bearings

This research aims to investigate the behavior of non-Newtonian fluid obeying the power law model in a laminar flow regime for a two-lobe journal bearing. The investigation involves calculating the static characteristics in terms; of load-carrying capacity, attitude angle, friction coefficient, friction force, and side leakage, for various values of the power law index and different eccentricity ratios. To determine the static characteristics, the pressure distributions are obtained by the numerical solution of the modified Reynolds equation considering the effect of non-Newtonian behavior of the fluids using the finite difference method. This study reveals that increasing both the eccentricity ratio and power law index produce an increase in the load-carrying capacity, friction force, and side leakage while lead to a decrease in the attitude angle and friction coefficient for the two-lobe journal bearing. In addition, compared to Newtonian fluid the results show that the using of non-Newtonian fluids as lubricants improves the static characteristics of the two-lobe journal bearing especially for the shear-thickening lubricants.

Developing a machine learning-based methodology for optimal hyperparameter determination—A mathematical modeling of high-pressure and high-temperature drilling fluid behavior

Drilling fluids exhibit complex rheological behavior due to a non-linear response to shear rate variations and high sensitivity to changes in temperature, time, and pressure conditions. The prediction of drilling fluid rheological behavior is crucial for the success of oil well drilling, and it directly impacts the fluid's performance. The dataset used in this study was obtained from extensive rheometric tests of water-based and olefin-based drilling fluids in steady-state flow curves. The optimal hyperparameters were guided by performance metrics and compared with alternative models such as Power-law and Herschel-Bulkley rheological models. Different configurations with different hidden layers, using neuron sequences of 16, 32, and 64, learning rates of 0.001 and 0.01, and the ReLU activation function were used to improve the model's performance. Additionally, the paper delved into the impact of the number of training epochs on the accuracy of shear stress predictions. Finding this equilibrium was identified as a crucial factor in achieving precise results. The neural network model demonstrated remarkable accuracy when using the ML-C3 configuration, with MAE values of 0.535 and R2 of 0.987 in predicting the steady-state flow curves of drilling fluids, establishing itself as a powerful tool for forecasting the rheological behavior of these fluids under diverse operational conditions. The present research significantly contributes to the field of drilling fluid rheology and provides valuable insights for optimizing drilling operations in HPHT environments.

Power or speed: Which metric is more accurate for modelling endurance running performance on track?

This study aimed to compare the accuracy of the power output, measured by a power meter, with respect to the speed, measured by an inertial measurement unit (IMU) and a global navigation satellite system (GNSS) sport watch to determine the critical power (CP) and speed (CS), work over CP (W') and CS (D'), and long-duration performance (i.e., 60 min). Fifteen highly trained athletes randomly performed seven time trials on a 400m track. The CP/CS and W'/D' were defined through the inverse of time model using the 3, 4, 5, 10, and 20 min trials. The 60 min performance was estimated through the power law model using the 1, 3, and 10 min trials and compared with the actual performance. A lower standard error of the estimate was obtained when using the power meter (CP: 2.7 [2.1-3.3] % and W': 13.8 [10.4-17.3] %) compared to the speed reported by the IMU (CS: 3.4 [2.5-4.3] %) and D': 20.7 [16.6-24.7] %) and GNSS sport watch (CS: 3.4 [2.5-4.3] % and D': 20.6 [16.7-24.7] %). A lower coefficient of variation was also observed for the power meter (4.9 [3.7-6.1] %) Regarding the speed reported by the IMU (10.9 [7.1-14.8] %) and GNSS sport watch (10.9 [7.0-14.7] %) in the 60 min performance estimation, the power meter offered lower errors than the IMU and GNSS sport watch for modelling endurance performance on the track.

Parametric investigations on dynamic responses of porous functionally graded al/al2o3 plates: effects of homogenization models and material distributions

This study presents a numerical analysis of the dynamic responses exhibited by functionally graded Al/Al2O3 plates that incorporate porosity. It explores the influence of critical parameters such as the thickness-to-span ratio and the porosity coefficient on the non-dimensional fundamental frequencies. Various micromechanical homogenization models, including Voigt, Mori-Tanaka, LRVE, Tamura, and Reuss, are utilized in conjunction with different material volume fraction distribution profiles: Power-law, Viola-Tornabene four-parameter, and Trigonometric. The research considers four distinct porosity variation patterns: uniform, non-uniform, logarithmic non-uniform, and mass-density. The governing equations are addressed using the Navier solution technique. The findings indicate that the Viola-Tornabene model results in the highest fundamental frequencies, succeeded by the Power-law and Trigonometric models. Among the porosity patterns, mass-density porosity yields the maximum frequencies, whereas uniform porosity leads to the lowest. Furthermore, an increase in the porosity coefficient typically raises the frequencies, with the exception of uniform porosity, while an increase in the thickness-to-span ratio results in a reduction of frequencies across all models. These insights are essential for the optimization of designs for functionally graded porous plates.

Bouncing universe scenarios in an extended gravitational framework involving curvature-matter coupling

Exploration of bouncing cosmic models in modified theories has gained much popularity in modern cosmology. This paper explores the Lagrangian function of a new theory namely F(R,Lm,T) framework by taking four renowned cosmic bouncing models, i.e., the exponential bounce, oscillatory bounce scenario, power law, and matter bouncing. Our primary objective is to fix the form of F(R,Lm,T) function for each model and investigate which kinds of reconstructed Lagrangian function have potential of regenerating bouncing scenario in terms of analytical form. It is seen that except power law model, the analytical solutions are conceivable only for certain cases of these bouncing models. For power law bounce, different cases of Lagrangian function may be rebuilt analytically while for some other bouncing scenarios, it is found that particular solutions are not always attainable and hence only the complimentary solutions can be explored. Further, we examine the behavior of energy constraints and stability of these analytically formed bouncing solutions. Additionally, we determine that the dark energy phase in F(R,Lm,T) gravity is compatible with the experimental data of BAO+Sne-Ia+CMB+H(z) and it is shown that cosmic bounce can be produced with dark energy eras in this gravity. We also present some constraints on the model parameters with Hubble parameter values and ΛCDM to determine the best-fit values of model via least square and reduced chi-squares methods. It is concluded that matter bounce model is the best fitted with the observational data set as well as ΛCDM model because it has least value of χm2.

Tunable diameter of electrospun fibers using empirical scaling laws of electrospinning parameters

This study introduces a new semi-empirical power-law model for predicting electrospun fiber diameter (D), addressing key processing parameters. Polycaprolactone (PCL) fibers were produced using a solvent mixture of Trichloromethane (TCM), Dimethyl Formamide (DMF), and ethanol (EtOH). Systematic experiments validated an existing theoretical model and led to the development of a novel model: D ∼ (c1/2η1/3Q1/5X2/3)/(U2/3ω1/4I1/5). This model incorporates seven crucial parameters: viscosity (η), concentration (c), voltage (U), spinning distance (X), flow–rate (Q), current (I) and collector wheel rotation speed (ω). The model was validated through a partial factorial design experiment, proving to be a valuable and reliable tool for predicting fiber diameters and optimizing electrospinning processes. The ability to control fiber diameter is essential for tailoring electrospun fibers for various applications, including biomedicine, filtration, sensors, and lightweight materials.

Revisiting the effect of lens mass models in cosmological applications of strong gravitational lensing

Abstract Strong gravitational lens system catalogues are typically used to constrain a combination of cosmological and empirical power-law lens mass model parameters, often introducing additional empirical parameters and constraints from high resolution imagery. We investigate these lens models using Bayesian methods through a novel alternative that treats spatial curvature via the non-FLRW timescape cosmology. We apply Markov Chain Monte Carlo methods using the catalogue of 161 lens systems of Chen et al. (2019) in order to constrain both lens and cosmological parameters for: (i) the standard ΛCDM model with zero spatial curvature; and (ii) the timescape model. We then generate large mock data sets to further investigate the choice of cosmology on fitting simple power-law lens models. In agreement with previous results, we find that in combination with single isothermal sphere parameters, models with zero FLRW spatial curvature fit better as the free parameter approaches an unphysical empty universe, ΩM0 → 0. By contrast, the timescape cosmology is found to prefer parameter values in which its cosmological parameter, the present void fraction, is driven to fv0 → 0.73 and closely matches values that best fit independent cosmological data sets: supernovae Ia distances and the cosmic microwave background. This conclusion holds for a large range of seed values fv0 ∈ {0.1, 0.9}, and for timescape fits to both timescape and FLRW mocks. Regardless of cosmology, unphysical estimates of the distance ratios given from power-law lens models result in poor goodness of fit. With larger datasets soon available, separation of cosmology and lens models must be addressed.

Novel optimized models to enhance performance forecasting of grid-connected PERC PV string operating under semi-arid climate conditions

This study focuses on modeling and forecasting the performance of a grid-connected photovoltaic (PV) string, aiming to enhance the accuracy of output power prediction, which is crucial for the effective management and stability of the electrical grid. While previous research has extensively examined PV modules, there is a notable lack of studies specifically targeting PV string behaviors, especially in harsh climates prevailing in semi-arid regions. This study addresses this gap by investigating the modeling and performance prediction of a Passivated Emitter Rear Cell (PERC) PV string under semi-arid climate conditions using analytical and predictive approaches based on both implicit and explicit models as Single Diode Model (SDM), Das Model (DM), Boutana et al. Model (BM) and Power Law Model (PLM). New mathematical models of DM and BM shape parameters versus temperature and irradiance along with novel analytical formulas giving DM shape parameters as a function of PV metrics have been introduced. The proposed approaches are validated using real measurements of a PERC PV string incorporating 12 JKM405M-72H PV modules operating at Green Energy Park (GEP) research facility in Morocco. The reliability of these approaches is assessed by comparing I-V curves, P-V curves and peak power generated and predicted by SDM, DM, BM and PLM to actual measurements. The comparison reveals that generated and predicted outcomes align well with measured data, with an average value of Normalized Root Mean Square Error (NRMSE) not exceeding 4.16 % for all models throughout the day. The findings indicate that the proposed approaches effectively predict the performance of the PERC PV string, accounting for climatic influences and providing insights into optimizing PV system performance, thereby contributing to improved grid stability in semi-arid regions.

Observational Constraints and Cosmographic Analysis of f(T,TG) Gravity and Cosmology

We perform observational confrontation and cosmographic analysis of f(T,TG) gravity and cosmology. This higher-order torsional gravity is based on both the torsion scalar, as well as on the teleparallel equivalent of the Gauss–Bonnet combination, and gives rise to an effective dark-energy sector which depends on the extra torsion contributions. We employ observational data from the Hubble function and supernova Type Ia Pantheon datasets, applying a Markov chain Monte Carlo sampling technique, and we provide the iso-likelihood contours, as well as the best-fit values for the parameters of the power-law model, an ansatz which is expected to be a good approximation of most realistic deviations from general relativity. Additionally, we reconstruct the effective dark-energy equation-of-state parameter, which exhibits a quintessence-like behavior, while in the future the Universe enters into the phantom regime, before it tends asymptotically to the cosmological constant value. Furthermore, we perform a detailed cosmographic analysis, examining the deceleration, jerk, snap, and lerk parameters, showing that the transition to acceleration occurs in the redshift range 0.52≤ztr≤0.89, as well as the preference of the scenario for quintessence-like behavior. Finally, we apply the Om diagnostic analysis to cross-verify the behavior of the obtained model.