Dispersive Model Research Articles

Neutron skins: A perspective from dispersive optical models

An overview of neutron skin predictions obtained using an empirical nonlocal dispersive optical model (DOM) is presented. The DOM links both scattering and bound-state experimental data through a subtracted dispersion relation which allows for fully consistent, data-informed predictions for nuclei where such data exist. Large skins were predicted for both 48Ca (Rskin48=0.25±0.023 fm in 2017) and 208Pb (Rskin208=0.25±0.05 fm in 2020). Whereas the DOM prediction in 208Pb is within 1σ of the subsequent PREX-2 measurement, the DOM prediction in 48Ca is over 2σ larger than the thin neutron skin resulting from CREX. From the moment it was revealed, the thin skin in 48Ca has puzzled the nuclear-physics community as no adequate theories simultaneously predict both a large skin in 208Pb and a small skin in 48Ca. The DOM is unique in its ability to treat both structure and reaction data on the same footing, providing a unique perspective on this Rskin puzzle. It appears vital that more neutron data be measured in both the scattering and bound-state domain for 48Ca to clarify the situation.

First test beam of the DMAPS-based proton tracker at the pMBRT facility at the Curie Institute

Objective.Proton radiotherapy's efficacy relies on an accurate relative stopping power (RSP) map of the patient to optimise the treatment plan and minimize uncertainties. Currently, a conversion of a Hounsfield Units map obtained by a common x-ray computed tomography (CT) is used to compute the RSP. This conversion is one of the main limiting factors for proton radiotherapy. To bypass this conversion a direct RSP map could be obtained by performing a proton CT (pCT). The focal point of this article is to present a proof of concept of the potential of fast pixel technologies for proton tracking at clinical facilities.Approach.A two-layer tracker based on the TJ-Monopix1, a depleted monolithic active pixel sensor (DMAPS) chip initially designed for the ATLAS, was tested at the proton minibeam radiotherapy beamline at the Curie Institute. The chips were subjected to 100 MeV protons passing through the single slit collimator (0.4×20mm2) with fluxes up to1.3×107p s-1 cm-2. The performance of the proton tracker was evaluated with GEANT4 simulations.Main results.The beam profile and dispersion in air were characterized by an opening of 0.031 mm cm-1, and aσx=0.172mm at the position of the slit. The results of the proton tracking show how the TJ-Monopix1 chip can effectively track protons in a clinical environment, achieving a tracking purity close to 70%, and a position resolution below 0.5 mm; confirming the chip's ability to handle high proton fluxes with a competitive performance.Significance.This work suggests that DMAPS technologies can be a cost-effective alternative for proton imaging. Additionally, the study identifies areas where further optimization of chip design is required to fully leverage these technologies for clinical ion imaging applications.

Larval dispersal and physical connectivity of Pheronema carpenteri populations in the Azores

The study of larval dispersal and connectivity between deep-sea populations is essential for the effective conservation and management of deep-sea environments and the design and implementation of Marine Protected Areas. Dense sponge aggregations, known as “sponge grounds”, are a key component of marine benthic ecosystems, by increasing the structural complexity of the sea floor and providing structure and habitat for many other species. These aggregations are characteristic of the Azores deep-sea environment. These sessile organisms rely primarily on larval dispersal for their reproduction. Connectivity between specific Pheronema carpenteri sponge aggregations in the Azores was studied using a 3-D biophysical dispersal model. Different biological trait scenarios were analyzed, considering spawning seasonality and pelagic larval duration. Model results indicate that regional circulation patterns drive larval dispersion, shaping population connectivity of P. carpenteri sponge aggregations in the Azores, particularly among aggregations in the Central Group of Azorean islands. Some areas present high retention rates, receiving larvae from several sponge aggregations while also being important larval source aggregations. In contrast, aggregations from the Eastern Group may be isolated from the others. Larval dispersal and connectivity patterns were analyzed concerning the current configuration of Marine Protected Areas (MPAs) in the Azores. The results underscored the importance of maintaining protection efforts in existing MPAs and identified stepping-stone locations and specific sites where additional measures could enhance species connectivity in the Azores.

Structural Model of Two-Fraction Ceramic Dispersions

Structural Model of Two-Fraction Ceramic Dispersions

The magicity, the radii of neutron orbits 1<i>f</i><sub>7/2</sub>, 2<i>p</i><sub>3/2</sub> and halo-like structure of <sup>52,54</sup>Ca nuclei

The evolution of neutron single-particle spectra of isotones with N = 32 and 34 new magic neutron numbers in the region 16 ≤ Z ≤ 32 was calculated in the dispersive optical model. It was shown that the minimum of the difference between the Fermi energy and the half-sum of the energy levels of the last predominantly occupied state and the first predominantly unoccupied state is achieved in the magic isotones with N = 32 and 34. The calculated root-mean-square radius of the neutron halo-like state 2p3/2 in double magic 52Ca nucleus exceeded the radius of the underlying 1f7/2 state by 0.8 fm. It is consistent with the recent experimental data and theoretical predictions that explain ‟unexpectedly” large root-mean-square charge radius of this nucleus.

Computations of energetic nearshore waves: Are weakly dispersive phase-resolving models telling the same story?

Three phase-resolving weakly dispersive wave models are used for 2DH (2D depth-integrated) computations of large-scale wave-by-wave processes induced by highly energetic sea/swell (SS) forcing near Haleʻiwa on the North Shore of Oʻahu, Hawaiʻi. The computed model results are compared to observations obtained over a nearshore cross-reef transect and from the basin of a small boat harbor. The level of agreement between the model results and observations in complex coastal environments under highly energetic wave forcing, along with the qualitative consistency among the three models, makes these models good candidates for operational applications in nearshore environments exposed to energetic wave forcing conditions.Spectral analyses inside the harbor and over the reef indicate that all three models generally account for infragravity (IG) spatial modal structures that are consistent with observations and the theory of edge and leaky waves. Over the reef, auto- and cross-spectral analyses reveal that the dominant waveforms are qualitatively reproduced by all three models, as indicated through: (i) the growth of IG wave amplitudes from deeper water to the shallow reef sites; (ii) the agreement of power spectral density peaks at the nearshore locations; and (iii) the remarkable similarity of spatial coherence functions among the models and between the models and observations. The computations of swell entering the small boat harbor at Haleʻiwa demonstrate that the models can successfully reproduce the variability in the narrow IG frequency bands that are spatially dependent and often subject to resonant amplifications.

Toolbox for nonreciprocal dispersive models in circuit quantum electrodynamics

Toolbox for nonreciprocal dispersive models in circuit quantum electrodynamics

Propagation dynamics of a nonlocal dispersal Zika transmission model with general incidence

In this paper, we are interested in propagation dynamics of a nonlocal dispersal Zika transmission model with general incidence. When the threshold is greater than one, we prove that there is a wave speed such that the model has a traveling wave solution with speed , and there is no traveling wave solution with speed less than . When the threshold is less than or equal to one, we show that there is no nontrivial traveling wave solution. The approaches we use here are Schauder's fixed point theorem with an explicit construction of a pair of upper and lower solutions, the contradictory approach, and the two‐sided Laplace transform.

Using the reactive/transport dispersive models to simulate a monolithic anion exchanger: Experimental parameter determination, simultaneous model evaluation, and validation.

Selecting an adequate model to represent the mass transfer mechanisms occurring in a chromatographic process is generally complicated, which is one of the reasons why monolithic chromatography is scarcely simulated. In this study, the chromatographic separation of model proteins bovine serum albumin (BSA), β-lactoglobulin-A, and β-lactoglobulin-B on an anion exchange monolith was simulated based on experimental parameter determination, simultaneous model testing, and validation under three statistical criteria: retention time, dispersion accuracies, and Pearson correlation coefficient. Experimental characterization of morphologic, physicochemical, and kinetic parameters was performed through volume balances, pressure drop analysis, breakthrough curve analysis, and batch adsorptions. Free Gibbs energy indicated a spontaneous adsorption process for proteins and counterions. Dimensionless numbers were estimated based on height equivalent to a theoretical plate analysis, finding that pore diffusion controlled β-lactoglobulin separation, whereas adsorption/desorption kinetics was the dominant mechanism for BSA. The elution profiles were modeled using the transport dispersive model and the reactive dispersive model coupled with steric mass action (SMA) isotherms because these models allowed to consider most of the mass transport mechanisms that have been described. RDM-SMA presented the most accurate simulations at pH 6.0 and at low (250mM) and high (400mM) NaCl concentrations. This simulation will be used as reference to forecast the purification of these proteins from bovine whey waste and to extrapolate this methodology to other monolith-based separations using these three statistical criteria that have not been used previously for this purpose.

Optimization of Supercritical CO2 Fracturing Based on Random Forest-Particle Swarm Optimization Model and Pre-existing Fracture Network

Summary On a global scale, shale oil/gas has become an important alternative energy source for conventional oil and gas. The potential advantages of supercritical CO2 (ScCO2) make it an ideal alternative to hydraulic fracturing, used for shale reservoir transformation and production increase while also promoting the geological storage of CO2, which is in-line with today’s carbon capture, utilization, and storage technology and helps to address the challenges of global climate change. To further study the fracture propagation and optimization of a complex fracture network (CFN) in ScCO2 fracturing under complex geological conditions using the cohesive module of ABAQUS to establish a fluid structure coupling model and completing indoor and field experimental verification, we introduce the global embedded cohesion zone model (CZM) combined with Python to generate two natural-fracture (NF) distribution models, conjugate and power law, to establish a dispersed mesh model. Based on this model, we studied the fracture propagation problem of ScCO2 fracturing under different engineering and geological conditions. The simulation results will be used as data-driven data to establish an optimization model of the random forest-particle swarm optimization algorithm (RF-PSO) and optimize the CFN. Research has shown that (1) ScCO2 is more inclined to pass through NFs and propagate in the rock matrix, and hydraulic fractures (HFs) combine better with NFs. Compared with hydraulic fracturing, ScCO2 fracturing has significant advantages (only the fracture width is lower than hydraulic fracturing, its initiation pressure and fracture length are much better than hydraulic fracturing, and there are more small fractures, making it easier to form a CFN). (2) During the process of fracture propagation, once dominant fractures form, the trend of the “Matthew effect” is inevitable. The process of fracture propagation is influenced by multiple factors, especially the distribution of NFs; the larger the reservoir filtration coefficient is, the more ScCO2 fracturing fluid that is lost, which is more unfavorable for fracturing construction. While maintaining the same amount of fracturing fluid injection, as the displacement increases, the fracture complexity increases, and the fracturing control range expands. Compared with other parameters, the effect of fracturing fluid temperature (FFT) on the expansion of ScCO2 fracturing fractures is not significant. (3) The established RF-PSO optimization model has an error of 2.89%, which can well adapt to CFN optimization problems under complex NF conditions and reduce uncertainty. We propose in this article a research method for fracture network optimization from fracture modeling, dynamic simulation, and optimization modeling. By combining numerical simulation and machine learning, the CFN optimization design of ScCO2 fracturing under CFN conditions is achieved, providing a research approach for the optimization of fracturing in fractured reservoirs.

Barau's petrel, Pterodroma baraui, as a bioindicator of plastic pollution in the South-West Indian Ocean: A multifaceted approach

Marine plastic pollution is well described by bioindicator species in temperate and polar regions but remains understudied in tropical oceans. We addressed this gap by evaluating the seabird Barau's petrel as bioindicator of plastic pollution in the South-West Indian Ocean. We conducted a multifaceted approach including necropsies of birds to quantify plastic ingestion; GPS tracking of breeding adults to identify their foraging areas; manta trawling of plastic debris to measure plastic pollution at sea and modelling of plastic dispersal. We developed a spatial risk index of seabird exposure to plastic ingestion. Seventy-one percent of the analysed birds had ingested plastic. GPS tracking coupled with manta trawling and dispersal modelling show that adults consistently foraged at places with high level of plastic concentration. The highest ingestion risk occurred in the northwest of Reunion Island and at latitude 30°S. Our findings confirm that Barau's petrel is a reliable bioindicator of plastic pollution in the region.

Reconstruction of human dispersal during Aurignacian on pan-European scale

The Aurignacian is the first techno-complex related with certainty to Anatomically Modern Humans in Europe. Studies show that they appeared around 43-42 kyr cal BP and dispersed rapidly in Europe during the Upper Palaeolithic. However, human dispersal is a highly convoluted process which is until today not well understood. Here, we provide a reconstruction of the human dispersal during the Aurignacian on the pan-European scale using a human dispersal model, the Our Way Model, which combines archaeological with paleoclimate data and uses the human existence potential as a unifying driver of human population dynamics. Based on the reconstruction, we identify the different stages of the human dispersal and analyse how human demographic processes are influenced by climate change and topography. A chronology of the Aurignacian human groups in Europe is provided, which is verified for locations where archaeological dating records are available. Insights into highly debated hypotheses, such as human dispersal routes, are provided.

Repeated migration, interbreeding and bottlenecking shaped the phylogeography of the selfing grass Brachypodium stacei.

Brachypodium stacei is the most ancestral lineage in the genus Brachypodium, a model system for grass functional genomics. B. stacei shows striking and sometimes contradictory biological and evolutionary features, including a high selfing rate yet extensive admixture, an ancient Miocene origin yet with recent evolutionary radiation, and adaptation to different dry climate conditions in its narrow distribution range. Therefore, it constitutes an ideal system to study these life history traits. We studied the phylogeography of 17 native circum-Mediterranean B. stacei populations (39 individuals) using genome-wide RADseq SNP data and complete plastome sequences. Nuclear SNP data revealed the existence of six distinct genetic clusters, low levels of intra-population genetic diversity and high selfing rates, albeit with signatures of admixture. Coalescence-based dating analysis detected a recent split between crown lineages in the Late Quaternary. Plastome sequences showed incongruent evolutionary relationships with those recovered by the nuclear data, suggesting interbreeding and chloroplast capture events between genetically distant populations. Demographic and population dispersal coalescent models identified an ancestral origin of B. stacei in the western-central Mediterranean islands, followed by an early colonization of the Canary Islands and two independent colonization events of the eastern Mediterranean region through long-distance dispersal and bottleneck events as the most likely evolutionary history. Climate niche data identified three arid niches of B. stacei in the southern Mediterranean region. Our findings indicate that the phylogeography of B. stacei populations was shaped by recent radiations, frequent extinctions, long-distance dispersal events, occasional interbreeding, and adaptation to local climates.

Pointwise estimates on the fundamental solution to nonlocal diffusion equation

In this article we study the pointwise behavior of the fundamental solution S ( t , x ) to the nonlocal diffusion model u t = D ( J ∗ u − u ) on R , S ( t , x ) can be written as e − Dt δ ( x ) + S 0 ( t , x ) , where S 0 ( t , x ) is called the regularizing part. Under some conditions on J and its Fourier transform J ^ , we obtain some new pointwise estimates on S 0 ( t , x ) . Then we apply our results to study the spatial dynamics of the nonlocal diffusion population model in a shifting environment considered in Li et al. [Spatial dynamics of a nonlocal dispersal population model in a shifting environment. J Nonlinear Sci. 2018;28:1189–1219]. In our study the convolution kernel J can be assumed to be more general, i.e. not necessarily of compact support, also the proof is greatly simplified. It is our believe that these pointwise estimates possess their own interest in further studying nonlocal diffusion models.

Validation and parametric study of FFRD model in DRACCAR code

The recent revision of Emergency Core Cooling System (ECCS) regulations in Korea has necessitated the consideration of Fuel Fragmentation, Relocation, and Dispersal (FFRD) phenomena in nuclear reactor safety analyses. Consequently, the Korea Atomic Energy Research Institute (KAERI) has developed and integrated the FFRD model into the domestically licensed safety analysis code, SPACE. Globally, US NRC’s FRAPTRAN and IRSN’s DRACCAR are available for evaluating FFRD phenomena. The FRAPTRAN code incorporates the FFR model, developed by Quantum Technology, while the fuel dispersal model is currently not included. In contrast, the DRACCAR code functions as an integrated analysis platform capable of modeling multi-dimensional thermal, hydraulic, mechanical, and chemical phenomena during a Loss of Coolant Accident (LOCA). This study conducts a thorough examination of the FFRD model in the DRACCAR code and validates its applicability through analysis using the Halden IFA-650 tests. The results demonstrate satisfactory predictive capabilities. Furthermore, a parametric study of key FFRD model parameters enhances the understanding of the FFRD model in the DRACCAR code. The development of detailed physical models in the FFRD model could significantly enhance the performance of the DRACCAR code, warranting the establishment of a comprehensive framework for these advancements. In the future, code-to-code comparisons between the DRACCAR code and other domestically developed integrated analysis platforms will be conducted to investigate various phenomena in depth.

Dispersivity calculation in digital twins of multiscale porous materials using the micro-continuum approach

The micro-continuum method is a novel approach to simulate flow and transport in multiscale porous materials. For such materials, the domain can be divided into three sub-domains depending on the local porosity ε: fully resolved solid phase, for which ε = 0, fully resolved pores, for which ε = 1.0, and unresolved pores, for which 0 < ε < 1.0. For such domains, the flow can be solved using the Darcy-Brinkman-Stokes (DBS) equation, which offers a seamless transition between unresolved pores, where flow is described by Darcy’s law, and resolved pores, where flow is described by the Stokes equations. Species transport can then be modelled using a volume-averaged equation. In this work, we present a derivation of the closure problem for the micro-continuum approach. Effective dispersivity tensors can then be calculated through a multi-stage process. First, high resolution images are chosen for characterizing the structure of the unresolved pores. Porosity, permeability and effective dispersivity for the unresolved parts are calculated by solving a closure problem based on Direct Numerical Simulation (DNS) in the high-resolution images. The effective dispersivity is then expressed as a function of the Péclet number, which describes the ratio of advective to diffusive transport. This relationship, along with porosity and permeability, is then integrated into the multiscale domain and the effective dispersivity tensor for the full image is calculated. Our novel method is validated by comparison with the numerical solution obtained for a fully-resolved simulation in a multiscale 2D micromodel. It is then applied to obtain an effective dispersivity model in digital twins for two multiscale materials: hierarchical ceramic foams and microporous carbonate rocks.

Effects of stochastic intraspecific seed dispersal variation on dispersal distance predictions in a temperate forest in Japan

The incorporation of seed dispersal models into conservation practices plays a pivotal role in predicting future ecosystems. Seed dispersal significantly influences plant population dynamics; however, our understanding of its implications at a landscape scale remains limited. We investigated how different seed dispersal processes impact the distributions of individual species within a 20 km × 20 km plot centered around a temperate old-growth forest reserve in Japan. We hypothesized that random variation in seed dispersal (i.e., stochastic processes) and variation mediated by distance (i.e., deterministic processes) would explain landscape-scale species distributions more effectively than deterministic seed dispersal processes alone. We evaluated 16 tree species with different seed dispersal modes by simulating seed dispersal processes. Stochastic simulations predicted higher dispersal distances for the majority of species. The findings of this study suggest that stochastic simulations are a more reliable tool for identifying dispersal restrictions in the context of climate change and biodiversity loss, highlighting the significance of using stochastic simulations for analyzing seed dispersal patterns in temperate forests, rather than more conventional deterministic methods.

Comparison of in situ black-lipped oyster spat collection and larval dispersal modelling results in semi-closed pearl-farming lagoons of the Tuamotu Archipelago

Spat collection of the pearl oyster Pinctada margaritifera in atoll lagoons of French Polynesia is the fundamental sustain of black pearl farming. Spat collection has always yielded variable results in space and time, but obvious signs of steady decreases, even collapses, have emerged in several lagoons. Spat collection materializes the ecological connectivity pathways between wild spawning populations and the location of artificial larval settlement substrates. To assess if oyster larval dispersal modelling could capture such pathways, we compared four six-week long spat collector deployment periods with dispersal simulations in two different lagoons. Spat collectors displayed wide spatial and temporal variations. Numerical modelling and field experiments were generally not in agreement. Although both methods have limitations, they can still approximate each other. But the accuracy of model simulations cannot be ascertained with spat collection data only. Using a SWOT (Strength-Weakness-Opportunities-Threats) analysis, we emphasize the complementarity of both approaches for management decisions.

Dispersal and connectivity modelling simulations for invertebrate larvae passing through the Strait of Gibraltar

Abstract The link between the northeastern Atlantic and Mediterranean Sea created by the Strait of Gibraltar and the adjacent Iberian and Moroccan coasts marks remarkable transition areas between distinct environments that harbour a diverse mixture of species. The area is interesting regarding marine connectivity and the transport of pelagic invertebrate larvae, crucial knowledge to manage over-exploited populations, and minimize the impacts of climate change and anthropogenic activities. Biophysical models were developed, combining oceanic and particle-tracking Lagrangian simulations with in situ zooplankton distribution data. The conditions driving the larval exchange between the sub-basins and the connectivity throughout the region were explored, using crustacean decapod larvae as biological references. The potential exchange between both sub-basins was confirmed, although specific larval traits revealed contrasting scenarios. The simulations showed that slope-dwelling and mesopelagic larvae have advantage when crossing from the Alboran into the Atlantic, in comparison with shelf-dwelling and epipelagic larvae. Transport pathways and retention areas were identified, and passive drifts were shown to increase the dispersal range of the simulations. The spatial origin of the larval release, larval duration, vertical distribution, and the interaction of larvae with the oceanic features are presented as the main factors impacting the effective larval input into the Atlantic or Mediterranean basins.

Neuronal expression of herpes simplex virus-1 VP16 protein induces pseudorabies virus escape from silencing and reactivation.

Alpha herpesvirus (α-HV) particles enter their hosts from mucosal surfaces and efficiently maintain fast transport in peripheral nervous system (PNS) axons to establish infections in the peripheral ganglia. The path from axons to distant neuronal nuclei is challenging to dissect due to the difficulty of monitoring early events in a dispersed neuron culture model. We have established well-controlled, reproducible, and reactivateable latent infections in compartmented rodent neurons by infecting physically isolated axons with a small number of viral particles. This system not only recapitulates the physiological infection route but also facilitates independent treatment of isolated cell bodies or axons. Consequently, this system enables study not only of the stimuli that promote reactivation but also the factors that regulate the initial switch from productive to latent infection. Adeno-associated virus (AAV)-mediated expression of herpes simplex-1 (HSV-1) VP16 alone in neuronal cell bodies enabled the escape from silencing of incoming pseudorabies virus (PRV) genomes. Furthermore, the expression of HSV VP16 alone reactivated a latent PRV infection in this system. Surprisingly, the expression of PRV VP16 protein supported neither PRV escape from silencing nor reactivation. We compared transcription transactivation activity of both VP16 proteins in primary neurons by RNA sequencing and found that these homolog viral proteins produce different gene expression profiles. AAV-transduced HSV VP16 specifically induced the expression of proto-oncogenes including c-Jun and Pim2. In addition, HSV VP16 induces phosphorylation of c-Jun in neurons, and when this activity is inhibited, escape of PRV silencing is dramatically reduced.IMPORTANCEDuring latency, alpha herpesvirus genomes are silenced yet retain the capacity to reactivate. Currently, host and viral protein interactions that determine the establishment of latency, induce escape from genome silencing or reactivation are not completely understood. By using a compartmented neuronal culture model of latency, we investigated the effect of the viral transcriptional activator, VP16 on pseudorabies virus (PRV) escape from genome silencing. This model recapitulates the physiological infection route and enables the study of the stimuli that regulate the initial switch from a latent to productive infection. We investigated the neuronal transcriptional activation profiles of two homolog VP16 proteins (encoded by HSV-1 or PRV) and found distinct gene activation signatures leading to diverse infection outcomes. This study contributes to understanding of how alpha herpesvirus proteins modulate neuronal gene expression leading to the initiation of a productive or a latent infection.