Potential Parameters Research Articles

Dispersive optical-model potential parameters for neutron scattering on 197Au up to 200 MeV

In this study, dispersive optical model (DOM) potential parameters were derived for the 197Au target nucleus up to an incident neutron energy of 200 MeV. The procedure involved fitting the theoretical total cross sections σtot with the experimental ones and thereby determining the valid free potential parameters at the lowest value of χ2/M. The contribution of compound nuclei mechanism at low energies was also incorporated in the calculations. The theoretical results obtained using the derived potential were compared to the experimental data for both the angular differential cross-section and the elastic cross-section. While there was a good agreement with the experimental values for the total cross section, a satisfactory agreement was achieved for the angular cross section. The obtained potential is useful for describing the n+197Au scattering system and its outputs over an extensive energy spectrum.

Single Transit Detection in Kepler with Machine Learning and Onboard Spacecraft Diagnostics

Exoplanet discovery at long orbital periods requires reliably detecting individual transits without additional information about the system. Common techniques, like phase folding of light curves and periodogram analysis of radial velocity data, are more sensitive to planets with shorter orbital periods, leaving a dearth of planet discoveries at long periods. We present a novel technique using an ensemble of convolutional neural networks incorporating the onboard spacecraft diagnostics of Kepler to classify transits within a light curve. We create a pipeline to recover the location of individual transits, and the period of the orbiting planet, which possesses an accuracy of >80% in the long orbital period regime (50 ≤ P ≤ 800 days). Our neural network pipeline has the potential to discover additional planets in the Kepler data set, and crucially, within the η-Earth regime. We report our first candidate from this pipeline, KOI-1271.02. KOI-1271.01 is known to exhibit strong transit timing variations (TTVs), and so we jointly model the TTVs and transits of both transiting planets to constrain the orbital configuration and planetary parameters and conclude with a series of potential parameters for KOI-1271.02, as there are not enough data currently to uniquely constrain the system. We conclude that KOI-1271.02 has a radius of 5.32 ± 0.20 R ⊕ and most likely a mass of 28.94−0.470.23 M ⊕. Future constraints on the nature of KOI-1271.02 require measuring additional TTVs of KOI-1271.01 or observing a second transit of KOI-1271.02.

Emergence of inflaton potential from asymptotically safe gravity

The Asymptotic Safety Hypothesis for gravity relies on the existence of an interacting fixed point of the Wilsonian renormalization group flow, which controls the microscopic dynamics, and provides a UV completion of the theory. Connecting such UV completion to observable physics has become an active area of research in the last decades. In this work we show such connection within the framework of scalar-tensor models. More specifically, we found that cosmological inflation naturally emerges from the integration of the RG flow equations, and that the predicted parameters of the emergent effective potentials provide a slow-roll model of inflation compatible with current observations. Furthermore, the RG evolution of the effective action starting at the UV fixed point, provides a prediction for the initial value of the inflaton field.

Evaluation of five different species of Pleurotus for their yield potential and growth parameters under Tripura’s conditions of North East India

Evaluation of five different species of Pleurotus for their yield potential and growth parameters under Tripura’s conditions of North East India

Application of TCM network pharmacology and experimental verification to explore the mechanism of kaempferol against epilepsy

BackgroundKaempferol (KF), the main active ingredient in identifying the authenticity of safflower, has a variety of pharmacological activities and neuroprotective effects. However, the mechanism of KF in the treatment of epilepsy remains unclear. This study aimed to investigate the protective effects of KF on epilepsy and its related mechanisms. MethodsNetwork pharmacology was used to explore the targets and mechanisms of safflower antiepileptic action. The protective effect of KF on epilepsy was assessed in the behavior and tissues of epileptic mice. Additionally, the impact of KF on the excitability and calcium transients of rat cortical neurons and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionicacid receptor (AMPAR) were investigated using patch clamp and calcium imaging techniques. ResultsNetwork pharmacology indicated safflower could be involved in calcium signaling pathways and calcium channel inhibitor activity. Experimental validation demonstrated that KF delayed seizure onset and mitigated neuronal damage in the prefrontal cortex of mice. It also reduced neuronal excitability, as indicated by action potential parameters, and suppressed Glutamate (Glu)-induced calcium transients. In tsA201 cells, KF inhibited AMPAR-mediated currents, suggesting a role in regulating [Ca2+]i homeostasis. ConclusionThese results indicate that KF's anticonvulsant properties may arise from its neuroprotection against cell injury, edema, and necrosis, its reduction of neuronal hyperexcitability, and its prevention of calcium-induced cytotoxicity, potentially involving AMPAR modulation. This study positions KF as a promising candidate for epilepsy therapy, offering a scientific foundation for its clinical investigation.

Unlocking Discovery Potential for Decaying Dark Matter and Faint X-Ray Sources with XRISM

Astrophysical emission lines arising from particle decays can offer unique insights into the nature of dark matter (DM). Using dedicated simulations with background and foreground modeling, we comprehensively demonstrate that the recently launched X-Ray Imaging and Spectroscopy Mission (XRISM) space telescope with powerful X-ray spectroscopy capabilities is particularly well suited to probe decaying DM, such as sterile neutrinos and axion-like particles, in the mass range of a few to tens of keV. We analyze and map XRISM’s DM discovery potential parameter space by considering the Milky Way Galactic DM halo, including establishing an optimal line-of-sight search, as well as dwarf galaxies, where we identify Segue 1 as a remarkably promising target. We demonstrate that with only 100 ks exposure, the XRISM/Resolve instrument is capable of probing the underexplored DM parameter window around a few keV and testing DM couplings with a sensitivity that exceeds by two orders existing Segue 1 limits. Further, we demonstrate that XRISM/Xtend instrument sensitivity enables discovery of the nature of faint astrophysical X-ray sources, especially in Segue 1, which could shed light on star formation history. We discuss implications for decaying DM searches with improved detector energy resolution in future experiments.

Seasonal remodelling of the fish heart alters sensitivity to petrochemical pollutant, 3-methylphenanthrene

Exploitation of offshore oil reserves, heightened traffic in marine transportation routes, and the release of petrochemicals from the thawing of permafrost and glaciers is increasing the bioavailability of polycyclic aromatic hydrocarbons (PAHs) to aquatic organisms. This availability may also change with the seasons as temperature changes accessibility of Arctic transport routes and the degree of land- and ice-melt and thus run-off into coastal ecosystems. Seasonal temperature change also remodels the ion channels in the heart of fish to facilitated preserved cardiac function across a range of temperatures. How this seasonal cardiac remodelling impacts vulnerability to pollutants is currently unknown. In this study we accessed the electrical activity of navaga cod (Eleginus nawaga) ventricular cardiomyocytes under the dual influence of seasonal change and varying concentrations of a pervasive PAH pollutant, 3-methylphenanthrene (3-MP). We used whole-cell patch-clamp to elucidate the effect of various doses of 3-MP on action potential (AP) parameters and the main ion currents (IKr, IK1, INa, ICa) in ventricular cardiomyocytes isolated from navaga cod in winter and summer at the White Sea, close to the Russian Arctic circle. Navaga cod ventricular cardiomyocytes were particularly vulnerable to 3-MP during the winter season. Exposure to 300 nM 3-MP resulted in significant changes in AP duration in winter-acclimatized fish, whereas no such changes were observed in summer-acclimatized fish. The IKr current was the most sensitive to 3-MP, with a winter IC50 of 49.7 nM and a summer IC50 of 53 μM. The INa current also exhibited seasonal shifts in sensitivity to 3-MP, with IC50 values of 2.39 μM in winter-acclimatized fish and 7.73 μM in summer-acclimatized fish. No significant differences were observed in the effect of 3-MP on the peak ICa current, although 3 μM of 3-MP caused a pronounced decrease in charge transferred by ICa (e.g. QCa) in both seasons. The IK1 current was insensitive to 3-MP in both winter and summer fish. These findings highlight how remodelling of the fish heart with changing season alters the potency of PAH pollution. This paper lays the groundwork for future research on the molecular mechanisms that drive the altered seasonal potency of pollutants in navaga cod and other species.

Dynamic contrast‑enhanced MRI combined with intravoxel incoherent motion in quantitative evaluation for preoperative risk stratification of resectable rectal adenocarcinoma.

Rectal adenocarcinoma is a common malignant tumor of the digestive tract. However, it is difficult to obtain tumor microstructural information using conventional magnetic resonance imaging (MRI). Dynamic contrast-enhanced (DCE)-MRI and intravoxel incoherent motion (IVIM) have been used in tumor research. The present study aimed to explore the application of DCE-MRI and IVIM in the risk stratification of resectable rectal adenocarcinoma. To achieve this, 75 patients with rectal adenocarcinoma confirmed via postoperative pathological examination who underwent high-resolution MRI, IVIM and DCE-diffusion-weighted imaging before surgery were retrospectively enrolled and divided into very low-risk (19 cases), low-risk (29 cases) and medium-risk (27 cases) groups. The quantitative parameters of DCE-MRI and IVIM were obtained using the GenIQ and Medical Imaging Interaction Toolkit software, respectively. One-way analysis of variance or the Kruskal-Wallis H test were used to analyze the differences in the measured parameters between the different risk groups. Receiver operating characteristic curves were used to analyze the diagnostic efficacy of each parameter. The differences in rate constant (Kep), perfusion fraction (f) and false diffusion coefficient (D*) between the different risk stratification groups were statistically significant (P<0.05). When the very low- and low-risk groups were compared, f + D* had the highest diagnostic efficiency [area under the curve (AUC)=0.719], with a sensitivity and specificity of 100 and 51.70%, respectively. When the low- and medium-risk groups were compared, Kep had the highest diagnostic efficiency (AUC=0.602), with a sensitivity and specificity of 72.41 and 55.56%, respectively. When the very low-risk and medium-risk groups were compared, Kep + f + D* had the highest diagnostic efficiency (AUC=0.887), with a sensitivity and specificity of 100 and 70.4%, respectively. Thus, DCE-MRI and IVIM can aid the prognostic risk stratification of resectable rectal adenocarcinoma, and Kep, f and D* are potential quantitative imaging parameters for the risk stratification of rectal adenocarcinoma.

Laser-Assisted Scattering With Screened Diatomic Potential

This study explores the differential cross section (DCS) for laser-assisted scattering of diatomic molecules, considering various polarization conditions (linear, circular, elliptical) and potential parameters. The primary objective is to understand how polarization, screening effects, and potential parameters influence the scattering behavior. Utilizing a model that incorporates the Morse potential with screening effects, the analysis treats the laser field classically as a time-dependent, spatially homogeneous electric field, while the electron dynamics are described quantum mechanically using the Schrödinger equation. The Volkov wavefunction is derived, and the first-Born S-matrix element is computed to evaluate the scattering process. The results show that the DCS decreases with increasing screening parameters, with linear polarization yielding higher values than circular or elliptical polarization. Specifically, at an initial momentum of 8 MeV and a final momentum of 9 MeV, the DCS for elliptical polarization is notably higher. The DCS also varies with potential strength and well width, showing a peak at 0.14 Å for potential well width. The findings suggest that linear polarization is most effective for scattering studies under varying potential strengths. It is recommended to focus on linear polarization for enhanced scattering efficiency and to carefully adjust screening parameters and potential well widths for optimal results.

Relativistic bound state solutions and quantum information theory in D dimensions under exponential-type plus Yukawa potentials

The bound-state solution of the radial Klein-Gordon equation has been obtained under the interaction of an exponential-type and Yukawa potential functions. The Greene-Aldrich approximation has been used to overcome the centrifugal barrier and enable the analytical solutions of the energy and wave functions in closed form. The momentum space wave function in D dimensions has been constructed using the Fourier transform. The mean values have been conjectured for the position and momentum spaces using two equivalent equations. The effects of the potential parameters on the expectation values and quantum information measurement have been investigated. For the 1D case, the results obey the Heisenberg uncertainty principle, Fisher, Shannon, Onicescu, and the Rényi entropic inequalities. Other information complexities measures, such as Shannon Power, Fisher-Shannon, and Lopez-Ruiz-Mancini-Calbet, have been verified. For the ground state, the 1D momentum expectation value \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle p^{2} \\rangle_{00}$$\\end{document} coincides with the 3D \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle p^{2} \\rangle_{000}$$\\end{document} values, which is an indication of degeneracy. The total energy of a particle in both 1D and 3D space may be degenerate due to the inter-dimensional degeneracy of the quantum numbers. However, in this present result, the degeneracy in 1D and 3D occurred for fixed quantum states at different momentum intervals. Thus, in 1D, a particle may transit an entire space (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:-\\infty\\:<p<\\infty\\:)$$\\end{document} with a certain kinetic energy, which must be equal to its kinetic energy if it moves through the interval \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:0<p<\\infty\\:$$\\end{document} in 3D space. This may have implications for kinetic energy degeneracy in higher dimensions.

Potential Bias Models With Bayesian Shrinkage Priors for Dynamic Borrowing of Multiple Historical Control Data

ABSTRACTWhen multiple historical controls are available, it is necessary to consider the conflicts between current and historical controls and the relationships among historical controls. One of the assumptions concerning the relationships between the parameters of interest of current and historical controls is known as the “Potential biases.” Within the “Potential biases” assumption, the differences between the parameters of interest of the current control and of each historical control are defined as “potential bias parameters.” We define a class of models called “potential biases model” that encompass several existing methods, including the commensurate prior. The potential bias model incorporates homogeneous historical controls by shrinking the potential bias parameters to zero. In scenarios where multiple historical controls are available, a method that uses a horseshoe prior was proposed. However, various other shrinkage priors are also available. In this study, we propose methods that apply spike‐and‐slab, Dirichlet–Laplace, and spike‐and‐slab lasso priors to the potential bias model. We conduct a simulation study and analyze clinical trial examples to compare the performances of the proposed and existing methods. The horseshoe prior and the three other priors make the strongest use of historical controls in the absence of heterogeneous historical controls and reduce the influence of heterogeneous historical controls in the presence of a few historical controls. Among these four priors, the spike‐and‐slab prior performed the best for heterogeneous historical controls.

Characterizing juvenile blacktip shark (Carcharhinus limbatus) nursery areas in the Galapagos: new methods and understandings.

New approaches to abundance surveying utilizing unoccupied aerial vehicles (UAVs) are proving to be effective tools in marine and terrestrial environments. We explored UAV efficacy for surveys in the Galapagos Marine Reserve (GMR), where relative abundance patterns of juvenile sharks and subsequent classifications of putative nursery areas based on environmental drivers are lacking. The UAV method allowed greater temporal and spatial coverage. We expanded classification of shark nursery habitat through monthly drone surveys and environmental data collection at 14 sites around San Cristobal Island (GMR) from November 2018 to July 2019. In the period of surveying, 56 flights identified 453 juvenile Carcharhinus limbatus (blacktip shark). Classification of nurseries followed three criteria, necessitating higher density, short-term residency, and annual site fidelity in target locations. We developed preliminary generalized linear models to elucidate potential environmental parameters influencing the perceived abundance and habitat preference of juveniles. Four sites were identified as either potential nurseries or nursery areas for the target species based on previous excursions. An averaged model was subsequently created from the models found to best explain deviance patterns (R2 = 0.10-0.44) in perceived shark abundance and habitat preference. Relative variable importance (RVI) values further clarified the parameters most associated with higher juvenile presence. This approach provides a systematic method of abundance surveying while simultaneously beginning the process of defining when and where we expect to find higher abundance through environmental modelling of most influential parameters to perceived abundance in this environment.

Compartmental modeling of CO2 absorption in a rotating packed bed

Capturing carbon dioxide (CO2), i.e., the primary greenhouse gas that contributes to climate change, from CO2 containing gas mixtures in various industrial sectors, e.g., natural gas processing and treating refinery off-gases, is necessary. Rotating packed beds (RPBs) have shown great efficiency in CO2 capture from flue gases with an appreciable intensification in the absorber size compared to the conventional packed bed absorbers. Successful commercialization of an RPB technology requires a comprehensive understanding of its performance under various operating conditions, process configurations, and for different solvents. In this study, we presented a mathematical model describing the performance of an RPB absorber for CO2 capture by aqueous amine solutions. We established the compartmental model based on two plug-flow reactors for gas and liquid phases. We validated this model adopting two sets of experimental data from literature. We considered reaction rates of all compounds in the system in the model. We, subsequently, employed the validated model to highlight the potential parameters in enhancing the overall CO2 recovery by an RPB absorber. The developed model takes advantage of acquired knowledge and data from literature based on years of numerical studies on RPBs. We studied the effects of operating conditions, such as inlet gas and liquid flow rates, amine fraction, rotating speed, and inlet liquid and gas temperatures on the performance of an RPB by the validated model. Although we initially developed the model for the CO2-monoethanolamine (MEA) solvent, we also studied the effect of changing the solvent to methyl diethanolamine (MDEA) and piperazine (PZ) on the overall absorption performance of an RPB absorber. We further adopted the developed model as a design tool to assist us in replacing a pilot- and an industrial-scale packed bed absorber with corresponding single RPB absorbers.

Klein–Gordon equation in the presence of a vector generalized Yukawa and a scalar generalized Hulthen potentials in the rotating cosmic string space–time

In this paper, we explore the relativistic quantum dynamics of spin-0 oscillator fields within the framework of a rotating cosmic string space–time, taking into account the presence of scalar and vector potentials. We solve the Klein–Gordon oscillator equation in this curved space–time, incorporating generalized versions of the Yukawa and Hulthen potentials as vector and scalar potentials, respectively. The analytical solution of the quantum system yields the energy eigenvalue and corresponding eigenfunction, which is expressed in terms of confluent Heun functions. The resulting energy spectrum is shown to depend on various parameters associated with the cosmic string space–time and the confining potentials. We graphically illustrate how the energy spectrum varies with changes in both the potential parameters and the cosmic string parameters.

Development of Multiscale Force Field for Actinide (An3+) Solutions.

A multiscale force field (FF) is developed for an aqueous solution of trivalent actinide cations An3+ (An = U, Np, Pu, Am, Cm, Bk, and Cf) by using a 12-6-4 Lennard-Jones type potential considering ion-induced dipole interaction. Potential parameters are rigorously and automatically optimized by the meta-multilinear interpolation parametrization (meta-MIP) algorithm via matching the experimental properties, including ion-oxygen distance (IOD) and coordination number (CN) in the first solvation shell and hydration free energy (HFE). The water solvent models incorporate an especially developed polar coarse-grained (CG) water scheme named PW32 and three widely used all-atom (AA) level SPC/E, TIP3P, and TIP4P water schemes. Each PW32 is modeled as two bonded beads to represent three neighboring water molecules, the simulation efficiency of which is 1 to 2 orders of magnitude higher than that of AA waters. The newly developed FF shows high accuracy and transferability in reproducing the IOD, CN, and HFE of An3+. The molecular structure and water exchange dynamics of the first An3+ hydration shell and the ionic (van der Waals) radii are reinvestigated in this work. Moreover, the new FF can readily be transferred to other popular FFs, as it has practicably predicted the permeability of An3+ in a graphene oxide filter within the framework of optimized potentials for liquid simulations (OPLS)-AA FF. It holds promise for applications in exploring actinide aqueous solutions with multiscale computational overhead.

Effects of conical singularity and Wu-Yang magnetic monopole on thermodynamic properties of harmonic oscillator interacting with potential

Abstract This paper investigates the thermodynamic properties of the harmonic oscillator system in a conical singularities background. Moreover, we incorporate a Wu-Yang magnetic monopole (WYMM) and inverse square potential into the quantum system and analyze the resulting effects. Using analytical methods, we derive the energy eigenvalues and study the thermodynamic properties, such as the partition function, Helmholtz free energy, Gibbs's free energy and specific heat capacity at finite temperature $T \neq 0$. Our findings demonstrate that these physical parameters are influenced by the topological parameter, strength of WYMM and potential parameters. These results provide valuable insights into the interplay between thermodynamic properties of a quantum mechanical problem and the gravitational effects.

The comparative role of physical system processes in Hudson Strait ice stream cycling: a comprehensive model-based test of Heinrich event hypotheses

Abstract. Despite their recognized significance on global climate and extensive research efforts, the mechanism(s) driving Heinrich events remain(s) a subject of debate. Here, we use the 3D thermomechanically coupled glacial systems model (GSM) to examine the Hudson Strait ice stream surge cycling and the role of three factors previously hypothesized to play a critical role in Heinrich events: ice shelves, glacial isostatic adjustment, and sub-surface ocean temperature forcings. In contrast to all previous modeling studies examining HEs, the GSM uses a transient last glacial cycle climate forcing, global viscoelastic glacial isostatic adjustment model, and sub-glacial hydrology model. The results presented here are based on a high-variance sub-ensemble retrieved from North American history matching for the last glacial cycle. Over our comparatively wide sampling of the potential parameter space (52 ensemble parameters for climate forcing and process uncertainties), we find two modes of Hudson Strait ice streaming: classic binge–purge versus near-continuous ice streaming with occasional shutdowns and subsequent surge onset overshoot. Our model results indicate that large ice shelves covering the Labrador Sea during the last glacial cycle only occur when extreme calving restrictions are applied. The otherwise minor ice shelves provide insignificant buttressing for the Hudson Strait ice stream. While sub-surface ocean temperature forcing leads to minor differences regarding surge characteristics, glacial isostatic adjustment does have a significant impact. Given input uncertainties, the strongest controls on ice stream surge cycling are the poorly constrained deep geothermal heat flux under Hudson Bay and Hudson Strait and the basal drag law. Decreasing the geothermal heat flux within available constraints and/or using a Coulomb sliding law instead of a Weertman-type power law leads to a shift from the near-continuous streaming mode to the binge–purge mode.

Can CP be conserved in the two-Higgs-doublet model?

We study the conditions under which the CP violation in the quark mixing matrix can leak into the scalar potential of the real two-Higgs-doublet model (2HDM) via divergent radiative corrections, thereby spoiling the renormalizability of the model. We show that any contributing diagram must involve 12 Yukawa-coupling insertions and a factor of the U(1)PQ-breaking scalar potential parameter λ5, thereby requiring at least six loops; this also implies that the 2HDM with only softly broken U(1)PQ is safe from divergent leaks of CP violation to all orders. We demonstrate that additional symmetries of the six-loop diagrams in the type I and II 2HDMs guarantee that all of the divergent CP-violating contributions cancel at this order. We also show that these symmetries are violated at seven loops and enumerate the classes of diagrams that can contribute to CP-violating divergences, providing evidence that the real 2HDM is theoretically inconsistent starting at the seven-loop level. Published by the American Physical Society 2024

Statistical Analysis of Atmospheric Delay Gradient and Rainfall Prediction in a Tropical Region

In recent years, precipitable water vapor has emerged as a key atmospheric parameter in weather prediction research. However, relying on only one parameter does not always accurately predict rainfall, as other atmospheric parameters also contribute to initiating rain events. In our previous study, we explored a methodology for rainfall forecasting based on the atmospheric delay gradient at an individual station in the tropical region. Commonly referred to as the atmospheric gradient, it accounts for the delay in GNSS signals due to changes in horizontal refractivity while propagating through the troposphere to the ground station. This paper discusses the spatial and temporal correlation of the gradient with precipitation occurring over a region. We have investigated different features, such as gradient magnitude, gradient convergence, and the flux of the atmospheric gradient, to propose potential nowcasting criteria for precipitation in the tropical climatic zone. The atmospheric gradient in the surrounding region orients toward the area of precipitation as the rain event approaches. This gradient gradually alters its orientation and converges toward the region of rainfall at the time of precipitation, introducing the concept of gradient convergence. This phenomenon results in an inward gradient flux at the time of the downpour, which presents a potential parameter for rainfall prediction over an area. We also proposed investigating area sizes of 4° × 4° or 8° × 8°, depending on the gradient feature, to establish a forecasting methodology for rainfall. The weather front in the tropical region begins to initiate 12 h before the actual time of occurrence and advances toward the area where it will have an impact from a more distant location. This article presents a detailed investigation of various features of the atmospheric gradient and its potential to nowcast rainfall for a region, as well as proposes the lead time for long-term weather predictions. Furthermore, a deep neural network has been employed to predict rainfall events for the next 6 h over an area in the tropical region.

Combining graph deep learning and London dispersion interatomic potentials: A case study on pnictogen chalcohalides.

Machine-learning interatomic potential models based on graph neural network architectures have the potential to make atomistic materials modeling widely accessible due to their computational efficiency, scalability, and broad applicability. The training datasets for many such models are derived from density-functional theory calculations, typically using a semilocal exchange-correlation functional. As a result, long-range interactions such as London dispersion are often missing in these models. We investigate whether this missing component can be addressed by combining a graph deep learning potential with semiempirical dispersion models. We assess this combination by deriving the equations of state for layered pnictogen chalcohalides BiTeBr and BiTeI and performing crystal structure optimizations for a broader set of V-VI-VII compounds with various stoichiometries, many of which possess van der Waals gaps. We characterize the optimized crystal structures by calculating their x-ray diffraction patterns and radial distribution function histograms, which are also used to compute Earth mover's distances to quantify the dissimilarity between the optimized and corresponding experimental structures. We find that dispersion-corrected graph deep learning potentials generally (though not universally) provide a more realistic description of these compounds due to the inclusion of van der Waals attractions. In particular, their use results in systematic improvements in predicting not only the van der Waals gap but also the layer thickness in layered V-VI-VII compounds. Our results demonstrate that the combined potentials studied here, derived from a straightforward approach that neither requires fine-tuning the training nor refitting the potential parameters, can significantly improve the description of layered polar crystals.