Two-component Model Research Articles

On the 3D Transport of Low-energy Galactic Cosmic-ray and Jovian Electrons in the Inner Heliosphere in the Presence of a Fisk-type Heliospheric Magnetic Field

Modeling the transport of low-energy (1−10 MeV) cosmic-ray electrons can lead to valuable insights as to the behavior of the heliospheric magnetic field (HMF), due to the fact that the mean free path (MFP) of these particles parallel to the HMF is significantly larger than their perpendicular MFP, and that these particles experience little in the way of drift due to gradients/curvatures in the HMF and along the heliospheric current sheet. Jovian electrons are particularly suitable for such an endeavour, as they originate from a decentral source in the inner heliosphere. To this end, the transport of these electrons is studied using a 3D, ab initio particle transport code that incorporates theoretical expressions for electron diffusion coefficients, and utilizes as inputs for these transport coefficients turbulence quantities calculated using a two-component turbulence transport model. The effects of a novel Fisk-type field on the transport of these Jovian electrons are investigated and compared with the effects of a standard Parker field.

Estimation of a Generalized Treatment Effect in a Control Group versus Treatment Group Design

A control group versus treatment group design is considered where the responses in the treatment group are modeled as a two-component mixture model that accounts for the possibility that only a fraction of the patients in the treated group will respond to the treatment. In this setting, the treatment effect is generalized to include both the fraction of treated patients that respond to the treatment and the magnitude of the response. Two alternative correlated and biased estimators are combined to yield an estimator that is preferable to either one of the estimators individually. The combined estimator is demonstrated on an illustrative blood pressure data set.

On plutonium-241 and americium in the two-component nuclear energy system

The paper deals with the influence of the strategy for using separated plutonium from spent fuel of thermal and fast reactors, as well as homogeneous burning of americium in the BN reactor core on the balance of americium in the Russian nuclear fuel cycle throughout the 21st century. The assessment is carried out with the use of mathematical modeling of nuclear materials movement including nuclide transformations throughout the nuclear energy system based on the CYCLE code. Scenario modeling of the americium and Pu-241 accumulation was carried out in Russia’s two-component nuclear energy system model with thermal (VVER) and fast (BN) reactors. In so doing, spent nuclear fuel (SNF) reprocessing was simulated in 2 options: as priority reprocessing of SNF of VVER reactors (1) or SNF of BN reactors (2). In addition to americium accumulation in the system without burning, the accumulation of this actinide was studied taking into account its homogeneous burning in the MOX-fuel of fast reactors at the level of its equilibrium content of ~1%. It has been shown that the priority reprocessing of VVER spent fuel makes it possible to reduce the americium accumulation by the end of the century by ~8 tons, and the effect is achieved by using freshly separated plutonium with short-term cooling, thus, by priority the americium source is eliminated, without directly handling it. Homogeneous addition of americium to the fuel of fast reactors of the BN-1200 type at a level of ~1% makes it possible to stop accumulation of americium in a two-component energy system by 2070, stabilizing it at a level of ~40 tons in the scenario with priority reprocessing of VVER SNF and ~50 tons in the scenario with priority reprocessing of BN SNF.

Equilibrium dynamical models in the inner region of the Large Magellanic Cloud based on Gaia DR3 kinematics

The Large Magellanic Cloud (LMC) contains complex dynamics driven by both internal and external processes. The external forces are due to tidal interactions with the Small Magellanic Cloud and the Milky Way, while internally its dynamics mainly depend on the stellar, gas, and dark matter mass distributions. Despite this complexity, simple physical models often provide valuable insights into the primary driving factors. We used Gaia Data Release 3 (DR3) to explore how well equilibrium dynamical models based on the Jeans equations and the Schwarzschild orbit superposition method are able to describe the LMC's five-dimensional phase-space distribution and line-of-sight (LOS) velocity distribution, respectively. In the Schwarzschild model, we incorporated a triaxial bar component for the first time and derived the LMC's bar pattern speed. We fit comprehensive Jeans dynamical models to all Gaia DR3 stars with proper motion and LOS velocity measurements found in the footprint of the VISTA near-infrared survey of the Magellanic System using a discrete maximum likelihood approach. These models are very efficient at discriminating genuine LMC member stars from Milky Way foreground stars and background galaxies. They constrain the shape, orientation, and enclosed mass of the galaxy under the assumption of axisymmetry. We used the Jeans model results as a stepping stone to more complex two-component Schwarzschild models, which include an axisymmetric disc and a co-centric triaxial bar, which we fit to the LMC Gaia DR3 LOS velocity field using a $ minimisation approach. The Jeans models describe the rotation and velocity dispersion of the LMC disc well, and we find an inclination angle of $ circ circ $, line of nodes orientation of $ circ circ $, and an intrinsic thickness of the disc of $q_0^d = b a (minor to major axis ratio). However, bound to axisymmetry, these models fail to properly describe the kinematics in the central region of the galaxy dominated by the LMC bar. We used the derived disc orientation and the Gaia DR3 density image of the LMC to obtain the intrinsic shape of the bar. Using these two components as input to our Schwarzschild models, we performed orbit integration and weighting in a rotating reference frame fixed to the bar, deriving an independent measurement of the LMC bar pattern speed of $ Both the Jeans and Schwarzschild models predict the same enclosed mass distribution within a radius of $6.2$\,kpc of $ Msun.

Polymer-Interface-Tissue Model to Estimate Leachable Release from Medical Devices.

The ability to predict clinically relevant exposure to potentially hazardous compounds that can leach from polymeric components can help reduce testing needed to evaluate the biocompatibility of medical devices. In this manuscript, we compare two physics-based exposure models: 1) a simple, one-component model that assumes the only barrier to leaching is the migration of the compound through the polymer matrix and 2) a more clinically relevant, two-component model that also considers partitioning across the polymer-tissue interface and migration in the tissue away from the interface. Using data from the literature, the variation of the model parameters with key material properties were established, enabling the models to be applied to a wide range of combinations of leachable compound, polymer matrix and tissue type. Exposure predictions based on the models suggest that the models are indistinguishable over much of the range of clinically relevant scenarios. However, for systems with low partitioning and/or slow tissue diffusion, the two-component model predicted up to three orders of magnitude less mass release over the same time period. Thus, despite the added complexity, in some scenarios it can be beneficial to use the two-component model to provide more clinically relevant estimates of exposure to leachable substances from implanted devices.

A thermal performance study on magnetic dipole based viscoplastic nanomaterial deploying distinct rheological aspects

Magnetic nanoliquids stand inimitable when compared with conventional liquids as their distinctive magnetic attributes can be regulated utilizing magnetic fields. For this reason, heat transference can be stimulated or regulated subjected to externally imposed magnetic fields. Magnetic nanoliquids are useful in comparison to orthodox or non-magnetic nanoliquids. These encompasses, energy conversion, electronics, hydraulics, thermal engineering and bioengineering. This study elaborates the magnetic dipole impact on convectively heated rheological nanomaterial confined by stretchy surface. Mathematical modeling is based on thermally radiative viscoplastic (Casson) model. Porous medium features are scrutinized through Darcian Forchheimer (DF) relation. Two-component Buongiorno nanomaterial model which captures Brownian diffusive together with thermophoretic diffusion is under consideration. Energy and solutal transportation expressions capture thermal source and chemical reaction effects. The dimensionalized nanomaterial flow model for stretching flow is obtained by deploying similarity variables. Numerical solutions are computed through Bvp4c scheme. The physical outcomes are elucidated graphically and arithmetically on dimensionless quantities (i.e., Nusselt number, temperature, skin-friction, velocity, Sherwood number and concentration streams). A benchmark is reported to authenticate the acquired numeric solutions. It is further visualized that nanomaterial temperature escalates subject to higher estimations of thermal Biot number, Curie temperature factor, radiation factor, thermophoresis parameter, heat source, ferrohydrodynamic interaction factor and Brownian diffusive parameter while it diminishes with Prandtl number and dissipation factor.

Causes for overestimation of the moisture recycling in an alpine meadow ecosystem of the Shule River Basin, Tibetan Plateau, China

Terrestrial moisture recycling is an essential hydrological component and a significant source of the atmosphere’s humidity budget in arid and semi-arid inland regions. Investigations on moisture recycling using the stable hydrogen and oxygen isotopes is currently a focal point in hydrologic research. However, the direct quantification of recycling ratio based on isotopic composition of evapotranspiration vapor is lacking. So, this causes challenges to compare studies, based in the same region and time period but with different methodologies. In this study, we measured the isotopic compositions of evapotranspiration vapor (δ18OET/δDET) from June to September 2018 in an alpine meadow ecosystem at the Shule River Basin by combining the Keeling plot model and in-situ chamber measurement. Using this data, the moisture recycled rate (mrr) was assessed based on the two-component (Model A) and three-component isotopic mixing models (Model B), respectively. Based on Model A and δ18OET, the analysis revealed that the mean recycled rate for the entire observation period was 35 %, while it was 26 % during the westerly period (the months dominated by the north branch of prevailing westerlies) and 44 % during the monsoon period (when subtropical moisture from the Indian monsoon penetrated the region). The recycled rate based on Model A and δDET was slightly larger with a mean value of 41 % during the entire observation period. The recycled rate based on Model B was also significantly higher in comparison with Model A, while the causes for this difference could be the assumption of substituting xylem water for transpiration vapor and the plant water source δD offset. The contribution of recycled moisture was notable lower for heavy rainfall comparing with light rainfall. Our findings provided a new perspective for the investigations of alpine meadow ecosystem hydrological processes.

Model Development and Experimental Application on Rewetting Characteristics of Cured Tobacco Leaves

Accurately predicting the moisture rewetting process of cured tobacco leaves is crucial for maintaining tobacco quality, storage stability, and preventing damage. In this study, a rewetting model for cured tobacco leaves was developed based on the two-component heterogeneity of leaf blades and main veins. The established model was compared with the model based on one-component homogeneity. The impact of different temperature and relative humidity (RH) conditions on the rewetting process of cured tobacco leaves was investigated, and predictions are made for the rewetting process on sunny and rainy days. In the results, the simulated value by the two-component heterogeneity model exhibited a highly consistent with the corresponding experimental data, with a maximum deviation of less than 9.74%. The rewetting rate increased with increasing temperature and RH, but the increased temperature also reduced the final moisture content. Compared to 20 °C and 80% RH, the rewetting time at 40 °C and 80% RH was reduced by 80.95%. The rewetting time at 20 °C and 90% RH was reduced by 81.25% compared to that at 20 °C and 70% RH. The rewetting rate of cured tobacco leaves was higher at night compared to daytime. In addition, the rewetting was faster on rainy days than sunny days. On rainy days (11.4–21.8 °C, 76.5%–95.4% RH), it took 13 h for cured tobacco leaves to reach the target moisture content (16% dry basis, d.b.) during rewetting, while on sunny days (20.3–29.5 °C, 46.1%–66.5% RH), it took more than 24 h. The findings of this study provided a helpful information for accurately predicting the moisture rewetting process of cured tobacco leaves.

Investigating the Role of Inward Alfvén Waves and Structures in the Slow Solar Wind

The solar wind dynamics are thought to be governed by counter-propagating Alfvén waves. Alfvén waves generate a turbulent cascade through nonlinear couplings between shearing wave packets. However, imbalances, structures, and intermittency complicate the solar wind’s magnetohydrodynamic (MHD) turbulence. Simulations and theories have suggested that dynamic alignment, or the tendency for velocity and magnetic fluctuations to become more correlated as a function of scale, may dictate the turbulent cascade. Observations have hinted at dynamic alignment at large scales but remain inconclusive at small scales. To investigate the nature of dynamically aligning fluctuations in the solar wind, we examine slow wind intervals from the Helios 2 spacecraft. We develop a two-component model of solar wind turbulence consisting of Alfvénic and non-Alfvénic contributions. We assume that only counter-propagating Alfvén waves experience dynamic alignment, and the non-Alfvénic structures do not participate in the alignment process. Our model allows us to constrain the relative contribution of inward Alfvén waves and non-Alfvénic structures with respect to the amplitude of outward Alfvén waves in the slow solar wind as a function of scale under the assumption of dynamic alignment. We show that the power ratio of inward to outward Alfvén fluctuations decreases as a function of scale. At the same time, the non-Alfvénic structures to outward Alfvén fluctuations increase with decreasing scale. Increasing structures provide a possible explanation for no dynamic alignment at small scales. Our study implies the need for new theoretical models to fully account for the solar wind’s compressibility, intermittency, and imbalanced nature.

Cerebrospinal Fluid Homovanillic and 5-Hydroxyindoleacetic Acids in a Large Pediatric Population; Establishment of Reference Intervals and Impact of Disease and Medication.

Cerebrospinal fluid (CSF) homovanillic (HVA), and 5-hydroxyindoleacetic acids (5-HIAA) are biomarkers of neurological diseases affecting the dopaminergic and serotoninergic pathways. Establishing reference intervals for these metabolites faces the challenges of a lack of healthy controls and a negative correlation with age, making stratified intervals unrealistic. We propose a pipeline to determine continuous reference intervals for HVA and 5-HIAA using an indirect method. We also studied the confounding effects of different variables and explored the impact of antiepileptic and neuroleptic treatments on HVA and 5-HIAA values. The study used least squares regression to fit age-concentration curves from a cohort of pediatric patients (n = 1533), where the residuals represent metabolite values excluding age effect. Presuming that HVA and 5-HIAA primary deficiencies characterize a distinct subpopulation, we fitted a two-component finite mixture model in age-normalized data and set reference intervals at the central 95% of the nondeficient population. Patients with primary genetic deficiencies of HVA and/or 5-HIAA consistently fall outside the proposed continuous reference intervals. Using the new continuous reference intervals reduces the number of secondary deficiencies detected compared with using stratified values. No correlations were observed between CSF HVA and 5-HIAA values across the studied drug categories (antiseizure and neuroleptic medications). In addition, biopterin values positively influenced both metabolite concentrations. The proposed continuous reference intervals caused a substantial reduction in the number of secondary deficiencies detected, most of which demonstrated no conclusive correlations between the diseases and altered HVA and 5-HIAA values.

The story of SN 2021aatd: A peculiar 1987A-like supernova with an early-phase luminosity excess

Context. There is a growing number of peculiar events that cannot be assigned to any of the main classes. SN 1987A and a handful of similar objects, thought to be explosive outcomes of blue supergiant stars, is one of them: while their spectra closely resemble those of H-rich (IIP) SNe, their light curve (LC) evolution is very different. Aims. Here we present the detailed photometric and spectroscopic analysis of SN 2021aatd, a peculiar Type II explosion. While its early-time evolution resembles that of the slowly evolving double-peaked SN 2020faa (although at a lower luminosity scale), after ∼40 days its LC shape becomes similar to that of SN 1987A-like explosions. Methods. In addition to comparing LCs, color curves, and spectra of SN 2021aatd to those of SNe 2020faa, 1987A, and other objects, we compared the observed spectra with our own SYN++ models and with the outputs of published radiative transfer models. We also carried out a detailed modeling of the pseudo-bolometric LCs of SNe 2021aatd and 1987A with a self-developed semi-analytical code, assuming a two-component ejecta (core + shell), and involving the rotational energy of a newborn magnetar in addition to radioactive decay. Results. We find that the photometric and the spectroscopic evolution of SN 2021aatd can be well described with the explosion of a ∼15 M⊙ blue supergiant star. Nevertheless, SN 2021aatd shows higher temperatures and weaker Na I D and Ba II 6142 Å lines than SN 1987A, which is instead reminiscent of IIP-like atmospheres. With the applied two-component ejecta model (accounting for decay and magnetar energy), we can successfully describe the bolometric LC of SN 2021aatd, including the first ∼40-day phase showing an excess compared to 87A-like SNe, but being strikingly similar to that of the long-lived SN 2020faa. Nevertheless, finding a unified model that also explains the LCs of more luminous events (e.g., SN 2020faa) is still a matter of debate.

Constraining seasonal and spatial ambient and urban groundwater contributions to streamflow across a mixed land-use regional-scale Precambrian Shield watershed

Groundwater-surface water (GW-SW) interactions are complex phenomena that vary naturally over space and time and are being influenced by environmental change. The Whitson River watershed is a mixed land-use Precambrian shield watershed located in Northeastern Ontario, Canada in which groundwater is a source of municipal water supply and in which groundwater and surface waters are at risk of potential impacts from urban runoff, ongoing municipal drainage projects, periodic flooding, and climate change. This study used watershed-scale synoptic surveys of stable isotopes (δ18O and δ2H) and geochemistry, and corresponding mixing-model approaches (two-component and three-component) to quantify the seasonal and spatial variation in surface water, ambient, and urban groundwater contributions to streamflow. Multiple mixing models were generated based on isotope and geochemical source water identification, and the performance of these models was compared. Mixing-model analyses showed that groundwater contributes a critical, sustaining source to streamflow (> 50 % or more) during summer baseflow conditions, dropping to ∼ 15 % in fall when connection to shield lakes and wetlands dominate. Three-component mixing models showed similar results to the two-component models, refining groundwater contributions into ambient and urban groundwater sources. Estimated urban groundwater contributed 30 % or more to summer baseflow, dropping to ∼ 4 % in the fall. Baseflow estimates derived from graphical hydrograph separation were similar to mixing model groundwater estimates in the summer but suggest this approach overestimates groundwater contributions during the fall. These results demonstrate the complexity of source water contributions to streamflow and the challenges in their determination in mixed-land-use Precambrian Shield landscapes where communities are largely located. Assessment of source water contributions to streamflow across the Whitson River sub-watershed has generated a region-specific conceptualization (e.g. urban versus ambient groundwater) of a basin that is experiencing increased urban development, providing information that will be of value for long term management.

Two-component off-axis jet model for radio flares of tidal disruption events

Two-component off-axis jet model for radio flares of tidal disruption events

Probing the energy and luminosity-dependent spectro-timing properties of RX J0440.9+4431 with AstroSat

ABSTRACT The Be/X-ray binary pulsar RX J0440.9+4431 went through a giant outburst in December 2022 with a peak flux of $\sim$2.3 Crab in 15–50 keV. We studied the broad-band timing and spectral properties of RX J0440.9+4431 using four AstroSat observations, where the source transited between subcritical and supercritical accretion regimes. Pulsations were detected significantly above 100 keV. The pulse profiles were found to be highly luminosity- and energy-dependent. A significant evolution in the pulse profile shape near the peak of the outburst indicates a possible change in the accretion mode and beaming patterns of RX J0440.9+4431. The rms pulsed fraction was luminosity- and energy-dependent, with a concave-like feature around 20–30 keV. The depth of this feature varied with luminosity, indicating changes in the accretion column height and proportion of reflected photons. The broad-band continuum spectra were best fitted with a two-component Comptonization model with a blackbody component or a two-blackbody component model with a thermal Comptonization component. A quasi-periodic oscillation (QPO) at 60 mHz was detected at a luminosity of $2.6 \times 10^{37}$ erg s$^{-1}$, which evolved into 42 mHz at $1.5 \times 10^{37}$ erg s$^{-1}$. The QPO rms were found to be energy dependent with an overall increasing trend with energy. For the first time, we found the QPO frequency varying with photon energy in an X-ray pulsar, which poses a challenge in explaining the QPO with current models such as the Keplarian and beat frequency model. Hence, more physically motivated models are required to understand the physical mechanism behind the mHz QPOs.

Fractionation by Spatially Heterogeneous Diffusion: Experiments and the Two-Component Random Walk Model.

The fundamental question regarding the fractionation phenomenon is whether diffusion alone is responsible for it or whether an additional advection dynamic is involved. We studied the fractionation by diffusion of particles in spatially heterogeneous environments. By experimentally observing the time-sequential fractionation patterns of dye particles diffusing across a solid-solid interface of varying polyacrylamide gel densities, we found that the two-component diffusion model accurately captures the observed fractionation dynamics. In contrast, single-component diffusion models by Fick, Wereide, and Chapman do not. Our results indicate that diffusion alone can explain the fractionation phenomenon and that additional advection dynamics are not involved. The underlying physics in the fractionation phenomenon is discussed by using a two-component random walk model.

Myo-regressor Deep Informed Neural NetwOrk (Myo-DINO) for fast MR parameters mapping in neuromuscular disorders

Magnetic Resonance (MR) parameters mapping in muscle Magnetic Resonance Imaging (mMRI) is predominantly performed using pattern recognition-based algorithms, which are characterised by high computational costs and scalability issues in the context of multi-parametric mapping.Deep Learning (DL) has been demonstrated to be a robust and efficient method for rapid MR parameters mapping. However, its application in mMRI domain to investigate Neuromuscular Disorders (NMDs) has not yet been explored. In addition, data-driven DL models suffered in interpretation and explainability of the learning process. We developed a Physics Informed Neural Network called Myo-Regressor Deep Informed Neural NetwOrk (Myo-DINO) for efficient and explainable Fat Fraction (FF), water-T2 (wT2) and B1 mapping from a cohort of NMDs.A total of 2165 slices (232 subjects) from Multi-Echo Spin Echo (MESE) images were selected as the input dataset for which FF, wT2,B1 ground truth maps were computed using the MyoQMRI toolbox. This toolbox exploits the Extended Phase Graph (EPG) theory with a two-component model (water and fat signal) and slice profile to simulate the signal evolution in the MESE framework. A customized U-Net architecture was implemented as the Myo-DINO architecture. The squared L2 norm loss was complemented by two distinct physics models to define two ‘Physics-Informed’ loss functions: Cycling Loss 1 embedded a mono-exponential model to describe the relaxation of water protons, while Cycling Loss 2 incorporated the EPG theory with slice profile to model the magnetization dephasing under the effect of gradients and RF pulses. The Myo-DINO was trained with the hyperparameter value of the 'Physics-Informed' component held constant, i.e. λmodel = 1, while different hyperparameter values (λcnn) were applied to the squared L2 norm component in both the cycling loss. In particular, hard (λcnn=10), normal (λcnn=1) and self-supervised (λcnn=0) constraints were applied to gradually decrease the impact of the squared L2 norm component on the ‘Physics Informed’ term during the Myo-DINO training process.Myo-DINO achieved higher performance with Cycling Loss 2 for FF, wT2 and B1 prediction. In particular, high reconstruction similarity and quality (Structural Similarity Index > 0.92, Peak Signal to Noise ratio > 30.0 db) and small reconstruction error (Normalized Root Mean Squared Error < 0.038) to the reference maps were shown with self-supervised weighting of the Cycling Loss 2. In addition muscle-wise FF, wT2 and B1 predicted values showed good agreement with the reference values. The Myo-DINO has been demonstrated to be a robust and efficient workflow for MR parameters mapping in the context of mMRI. This provides preliminary evidence that it can be an effective alternative to the reference post-processing algorithm. In addition, our results demonstrate that Cycling Loss 2, which incorporates the Extended Phase Graph (EPG) model, provides the most robust and relevant physical constraints for Myo-DINO in this multi-parameter regression task. The use of Cycling Loss 2 with self-supervised constraint improved the explainability of the learning process because the network acquired domain knowledge solely in accordance with the assumptions of the EPG model.

Topology Control of Covalent Organic Frameworks with Interlaced Unsaturated 2D and Saturated 3D Units for Boosting Electrocatalytic Hydrogen Peroxide Production.

Modulating the electronic state of multicomponent covalent organic framework (COF) electrocatalysts is crucial for enhancing catalytic activity. However, the effect of dimensionality on their physicochemical functionalities is still lacking. Herein, we report an interlaced unsaturated 2D and saturated 3D strategy to develop multicomponent-regulated COFs with tunable gradient dimensionality for high selectivity and activity electrocatalysis. Compared with the two-component 2D and 3D model COFs, the 2D/3D framework interlaced COFs with locally irregular dimensions and electronic structures are more practical in optimizing the intrinsic electrode surface reaction and mass transfer. Remarkably, the unsaturated 2D-inserted 3D TAE-COF regulates the adsorption mode of OOH* species to supply a favorable dynamic pathway for the H2O2 process, thereby achieving an excellent production rate of 8.50 mol gcat -1 h-1. Moreover, utilizing theoretical calculation and in situ ATR-FTIR experiment, we found that the central carbon atom of the tetraphenyl-based unit (site-1 and site-6) are potential active sites. This strategy of operating the adsorption ability of reactants with dimensionality-interconnected building blocks provides an idea for designing durable and efficient electrocatalysts.

Dispersion, Dynamics, and Mechanics of Polymer Nanocomposites Filled with Rigid-Soft Janus Nanoparticles via Molecular Dynamics Simulation.

The introduction of nanoparticles (NPs) presents boundless possibilities for enhancing the performance of polymer nanocomposites (PNCs). Consequently, the design of novel NPs becomes of paramount significance for PNCs. In our study, we employ the dumbbell two-component model of Janus nanoparticles (JNPs) and design rigid-soft JNPs as fillers. Using coarse-grained molecular dynamics simulations, we systematically investigate the dispersion, dynamics, and mechanical properties of these novel PNCs. First, we determine the optimal dispersion conditions by studying rcutoff and εnp. The simulation indicates that when the interaction between polymer chains and JNPs is a repulsive potential, the JNPs tend to aggregate together, forming a cluster with soft NPs inside and rigid NPs outside. Conversely, under attractive interactions, JNPs show superior dispersion uniformity compared to the repulsive system, and as εnp increases, the dispersion improves. Then, the mean square displacement (MSD) indicates that JNPs effectively impede the mobility of polymer chains, with the degree of hindrance increasing as εnp grows; this effect is more pronounced in attractive systems. Comparing JNPs of different particle sizes, we find that smaller JNP systems exhibit higher temperature sensitivity. Furthermore, there exists a critical particle size (Dnp ≈ 5σ) under a constant filling fraction at which the NPs exert the most pronounced restriction effect on the polymer. Next, upon examining the mechanical behavior, we find that the rigid-soft JNPs demonstrate notable elasticity and variability compared to traditional NPs. This observation is confirmed through measurements of the bond orientation and mean square radius of gyration of the soft segments of JNPs. In summary, this research provides a comprehensive understanding of the intricate interplay among various factors, offering valuable insights for optimizing JNP dispersion and enhancing the mechanical properties of PNCs.

Statistical Framework for Modeling Asymmetrical Data with Dual Peaks

Objectives: To create a comprehensive framework that effectively identifies the most suitable model for asymmetrical data based on its unique characteristics. Methods: This study proposed a new model named Gompertz-Gumbel distribution (GGD) based on the results from the framework which utilizes various statistical tools, as well as information criteria. A dip test is used to check the modality of the data. To propose a new model, the finite mixture model concept was employed. The location, scale, shape, and weight parameters of the GGD were estimated using the maximum likelihood estimation method. Findings: The suggested framework exhibits superior performance in developing a suitable model for the asymmetrical data with dual peaks, resulting in the best fit for the data. To validate the effectiveness of the proposed model, it has been compared with various models like Gaussian models and two-component mixture models. The GGD's properties have also been determined. The various shapes of the GGD were also analyzed. Novelty: A novel framework is proposed to identify the appropriate model for the asymmetrical data with dual peaks that outperform the existing models. It shows the significance of the framework. Keywords: Lifetime distributions, Mixture models, Information Criteria, Goodness of fit, Asymmetrical data

Microscopic Study on Superexchange Dynamics of Composite Spin-1 Bosons.

We report on an experimental simulation of the spin-1 Heisenberg model with composite bosons in a one-dimensional chain based on the two-component Bose-Hubbard model. Exploiting our site- and spin-resolved quantum gas microscope, we observed faster superexchange dynamics of the spin-1 system compared to its spin-1/2 counterpart, which is attributed to the enhancement effect of multi-bosons. We further probed the nonequilibrium spin dynamics driven by the superexchange and single-ion anisotropy terms, unveiling the linear expansion of the spin-spin correlations, which is limited by the Lieb-Robinson bound. Based on the superexchange process, we prepared and verified the entangled qutrits pairs with these composite spin-1 bosons, potentially being applied in qutrit-based quantum information processing.