Ecological network analysis reveals complex responses of tree species life stage interactions to stand variables

Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.

Molecular dynamics simulations on the interactions between nucleic acids and a phospholipid bilayer

Recently,lipid nanoparticles(LNPs)have been extensively investigated as non-viral carriers of nucleic acid vaccines due to their high transport efficiency,safety,and straightforward production and scalability.However,the molecular mechanism underlying the interactions between nucleic acids and phospholipid bilayers within LNPs remains elusive.In this study,we employed the all-atom molecular dynamics simulation to investigate the interactions between single-stranded nucleic acids and a phospholipid bilayer.Our findings revealed that hydrophilic bases,specifically G in single-stranded RNA(ssRNA)and single-stranded DNA(ssDNA),displayed a higher propensity to form hydrogen bonds with phospholipid head groups.Notably,ssRNA exhibited stronger binding energy than ssDNA.Furthermore,divalent ions,particularly Ca2+,facilitated the binding of ssRNA to phospholipids due to their higher binding energy and lower dissociation rate from phospholipids.Overall,our study provides valuable insights into the molecular mechanisms underlying nucleic acidphospholipid interactions,with potential implications for the nucleic acids in biotherapies,particularly in the context of lipid carriers.

Strong metal-support interactions between highly dispersed Cu^(+) species and ceria via mix-MOF pyrolysis toward promoted water-gas shift reaction

The modulation of metal-support interfacial interaction is significant but challenging in the design of high-efficiency and high-stability supported catalysts.Here,we report a synthetic strategy to upgrade Cu-CeO_(2)interfacial interaction by the pyrolysis of mixed metal-organic framework(MOF)structure.The obtained highly dispersed Cu/CeO_(2)-MOF catalyst via this strategy was used to catalyze water-gas shift reaction(WGSR),which exhibited high activity of 40.5μmolCOgcat^(-1).s^(-1)at 300℃and high stability of about 120 h.Based on comprehensive studies of electronic structure,pyrolysis strategy has significant effect on enhancing metal-support interaction and then stabilizing interfacial Cu^(+)species under reaction conditions.Abundant Cu^(+)species and generated oxygen vacancies over Cu/CeO_(2)-MOF catalyst played a key role in CO molecule activation and H2O molecule dissociation,respectively.Both collaborated closely and then promoted WGSR catalytic performance in comparison with traditio nal supported catalysts.This study shall offer a robust approach to harvest highly dispersed catalysts with finely-tuned metal-support interactions for stabilizing the most interfacial active metal species in diverse heterogeneous catalytic reactions.

Effects of layer interactions on instantaneous stability of finite Stokes flows

The stability analysis of a finite Stokes layer is of practical importance in flow control. In the present work, the instantaneous stability of a finite Stokes layer with layer interactions is studied via a linear stability analysis of the frozen phases of the base flow. The oscillations of two plates can have different velocity amplitudes, initial phases, and frequencies. The effects of the Stokes-layer interactions on the stability when two plates oscillate synchronously are analyzed. The growth rates of two most unstable modes when δ < 0.12 are almost equal, and δ = δ*/h*, where δ*and h*are the Stokes-layer thickness and the half height of the channel, respectively. However, their vorticities are different. The vorticity of the most unstable mode is symmetric, while the other is asymmetric. The Stokes-layer interactions have a destabilizing effect on the most unstable mode when δ < 0.68, and have a stabilizing effect when δ > 0.68. However, the interactions always have a stabilizing effect on the other unstable mode. It is explained that one of the two unstable modes has much higher dissipation than the other one when the Stokes-layer interactions are strong. We also find that the stability of the Stokes layer is closely related to the inflectional points of the base-flow velocity profile. The effects of inconsistent velocity-amplitude, initial phase, and frequency of the oscillations on the stability are analyzed. The energy of the most unstable eigenvector is mainly distributed near the plate of higher velocity amplitude or higher oscillation frequency. The effects of the initial phase difference are complicated because the base-flow velocity is extremely sensitive to the initial phase.

FLOCKING OF A THERMODYNAMIC CUCKER-SMALE MODEL WITH LOCAL VELOCITY INTERACTIONS

In this paper, we study the flocking behavior of a thermodynamic Cucker–Smale model with local velocity interactions. Using the spectral gap of a connected stochastic matrix, together with an elaborate estimate on perturbations of a linearized system, we provide a sufficient framework in terms of initial data and model parameters to guarantee flocking. Moreover, it is shown that the system achieves a consensus at an exponential rate.

T cell interactions with microglia in immune-inflammatory processes of ischemic stroke

The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.

Opinion consensus incorporating higher-order interactions in individual-collective networks

In the current information society, the dissemination mechanisms and evolution laws of individual or collective opinions and their behaviors are the research hot topics in the field of opinion dynamics. First, in this paper, a two-layer network consisting of an individual-opinion layer and a collective-opinion layer is constructed, and a dissemination model of opinions incorporating higher-order interactions(i.e. OIHOI dissemination model) is proposed. Furthermore, the dynamic equations of opinion dissemination for both individuals and groups are presented. Using Lyapunov's first method,two equilibrium points, including the negative consensus point and positive consensus point, and the dynamic equations obtained for opinion dissemination, are analyzed theoretically. In addition, for individual opinions and collective opinions,some conditions for reaching negative consensus and positive consensus as well as the theoretical expression for the dissemination threshold are put forward. Numerical simulations are carried to verify the feasibility and effectiveness of the proposed theoretical results, as well as the influence of the intra-structure, inter-connections, and higher-order interactions on the dissemination and evolution of individual opinions. The main results are as follows.(i) When the intra-structure of the collective-opinion layer meets certain characteristics, then a negative or positive consensus is easier to reach for individuals.(ii) Both negative consensus and positive consensus perform best in mixed type of inter-connections in the two-layer network.(iii) Higher-order interactions can quickly eliminate differences in individual opinions, thereby enabling individuals to reach consensus faster.

Multiparameter Numerical Investigation of Two Types of Moving Interactions Between the Deep-Sea Mining Vehicle Track Plate and Seabed Soil:Digging and Rotating Motions

To ensure the safe performance of deep-sea mining vehicles(DSMVs),it is necessary to study the mechanical characteristics of the interaction between the seabed soil and the track plate.The rotation and digging motions of the track plate are important links in the contact between the driving mechanism of the DSMV and seabed soil.In this study,a numerical simulation is conducted using the coupled Eulerian–Lagrangian(CEL)large deformation numerical method to investigate the interaction between the track plate of the DSMV and the seabed soil under two working conditions:rotating condition and digging condition.First,a soil numerical model is established based on the elastoplastic mechanical characterization using the basic physical and mechanical properties of the seabed soil obtained by in situ sampling.Subsequently,the soil disturbance mechanism and the dynamic mechanical response of the track plate under rotating and digging conditions are obtained through the analysis of the sensitivity of the motion parameters,the grouser structure,the layered soil features and the soil heterogeneity.The results indicate that the above parameters remarkably influence the interaction between the DSMV and the seabed soil.Therefore,it is important to consider the rotating and digging motion of the DSMV in practical engineering to develop a detailed optimization design of the track plate.

Assessment of the potential interactions between favipiravir and radiocontrast agents

BACKGROUND In cases of coronavirus disease 2019(COVID-19),favipiravir is commonly included to the therapy regimen.Drug interactions between favipiravir and other COVID-19 therapy drugs are frequently researched.However,no research on possible drug interactions between Favipiravir and radiocontrast agents,which have become almost crucial in diagnostic processes while not being part of the treatment,has been found.AIM To determine potential medication interactions between Favipiravir and radiocontrast agents.METHODS The study comprised patients who were taking Favipiravir for COVID-19 therapy and underwent a contrast-enhanced computed tomography(CT)or magnetic resonance imaging(MRI)test while taking the medicine.The computerized patient files of the cases included in the study,as well as the pharmacovigilance forms in the designated hospital,were evaluated for this purpose.RESULTS The study included the evaluation of data from 1046 patients.The study sample's mean age was 47.23±9.48 years.The mean age of cases with drug interactions was statistically significant greater than that of cases with no drug interactions(P=0.003).When evaluated with logistic regression analysis,a 1-year raises in age increases the risk of developing drug interactions by 1.63 times(P=0.023).There was no statistically significant difference in the occurrence of medication interactions between the sexes(P=0.090).Possible medication interactions were discovered in 42 cases(4%).CONCLUSION The findings of this study revealed that the most notable findings as a result of the combined use of contrast agents and favipiravir were increased creatinine and transaminase values,as well as an increase in the frequency of nausea and vomiting.The majority of drug interactions discovered were modest enough that they were not reflected in the clinic.Drug interactions become more common as people get older.

Capturing the non-equilibrium state in light–matter–free-electron interactions through ultrafast transmission electron microscopy

Ultrafast transmission electron microscope(UTEM) with the multimodality of time-resolved diffraction, imaging,and spectroscopy provides a unique platform to reveal the fundamental features associated with the interaction between free electrons and matter. In this review, we summarize the principles, instrumentation, and recent developments of the UTEM and its applications in capturing dynamic processes and non-equilibrium transient states. The combination of the transmission electron microscope with a femtosecond laser via the pump–probe method guarantees the high spatiotemporal resolution, allowing the investigation of the transient process in real, reciprocal and energy spaces. Ultrafast structural dynamics can be studied by diffraction and imaging methods, revealing the coherent acoustic phonon generation and photoinduced phase transition process. In the energy dimension, time-resolved electron energy-loss spectroscopy enables the examination of the intrinsic electronic dynamics of materials, while the photon-induced near-field electron microscopy extends the application of the UTEM to the imaging of optical near fields with high real-space resolution. It is noted that light–free-electron interactions have the ability to shape electron wave packets in both longitudinal and transverse directions, showing the potential application in the generation of attosecond electron pulses and vortex electron beams.

Growth and Interactions of Multi-Source Perturbations in Convection-Allowing Ensemble Forecasts

This study investigated the growth of forecast errors stemming from initial conditions(ICs),lateral boundary conditions(LBCs),and model(MO)perturbations,as well as their interactions,by conducting seven 36 h convectionallowing ensemble forecast(CAEF)experiments.Two cases,one with strong-forcing(SF)and the other with weak-forcing(WF),occurred over the Yangtze-Huai River basin(YHRB)in East China,were selected to examine the sources of uncertainties associated with perturbation growth under varying forcing backgrounds and the influence of these backgrounds on growth.The perturbations exhibited distinct characteristics in terms of temporal evolution,spatial propagation,and vertical distribution under different forcing backgrounds,indicating a dependence between perturbation growth and forcing background.A comparison of the perturbation growth in different precipitation areas revealed that IC and LBC perturbations were significantly influenced by the location of precipitation in the SF case,while MO perturbations were more responsive to convection triggering and dominated in the WF case.The vertical distribution of perturbations showed that the sources of uncertainties and the performance of perturbations varied between SF and WF cases,with LBC perturbations displaying notable case dependence.Furthermore,the interactions between perturbations were considered by exploring the added values of different source perturbations.For the SF case,the added values of IC,LBC,and MO perturbations were reflected in different forecast periods and different source uncertainties,suggesting that the combination of multi-source perturbations can yield positive interactions.In the WF case,MO perturbations provided a more accurate estimation of uncertainties downstream of the Dabie Mountain and need to be prioritized in the research on perturbation development.

Parallelization strategies for resolved simulations of fluid-structure-particle interactions

Fluid-structure-particle interactions in three spatial dimensions happen in many environmental and engineering flows.This paper presents the parallel algorithms for the hybrid diffuse and sharp interface immersed boundary(IB)method developed in our previous work.For the moving structure modeled using the sharp interface IB method,a recursive box method is developed for efficiently classifying the background grid nodes.For the particles modeled using the diffuse interface IB method,a‘master-slave’approach is adopted.For the particle-particle interaction(PPI)and particle-structure interaction(PSI),a fast algorithm for classifying the active and inactive Lagrangian points,which discretize the particle surface,is developed for the‘dry’contact approach.The results show that the proposed recursive box method can reduce the classifying time from 52seconds to 0.3 seconds.Acceptable parallel efficiency is obtained for cases with different particle concentrations.Furthermore,the lubrication model is utilized when a particle approaches a wall,enabling an accurate simulation of the rebounding phenomena in the benchmark particle-wall collision problem.At last,the capability of the proposed computational framework is demonstrated by simulating particle-laden turbulent channel flows with rough walls.

Exactly Solvable Two-Parameter Models of Relativistic δ′s -Sphere Interactions in Quantum Mechanics

We make a systematic study of two-parameter models of δ ′ s -sphere interaction and δ ′ s -sphere plus a Coulomb interaction. Where δ ′ s interaction denotes the δ ′ -sphere interaction of the second kind. We provide the mathematical definitions of Hamiltonians and obtain new results for both models, in particular the resolvents equations, spectral properties and some scattering quantities.

Biological Interaction and Imaging of Ultrasmall Gold Nanoparticles

Ultrasmall gold nanoparticles(AuNPs)typically includes atomically precise gold nanoclusters(AuNCs)and AuNPs with a core size below 3 nm.Serving as a bridge between small molecules and traditional inorganic nanoparticles,the ultrasmall AuNPs show the unique advantages of both small molecules(e.g.,rapid distribution,renal clearance,low non-specific organ accumulation)and nanoparticles(e.g.,long blood circulation and enhanced permeability and retention effect).The emergence of ultrasmall AuNPs creates significant opportunities to address many challenges in the health field including disease diagnosis,monitoring and treatment.Since the nano–bio interaction dictates the overall biological applications of the ultrasmall AuNPs,this review elucidates the recent advances in the biological interactions and imaging of ultrasmall AuNPs.We begin with the introduction of the factors that influence the cellular interactions of ultrasmall AuNPs.We then discuss the organ interactions,especially focus on the interactions of the liver and kidneys.We further present the recent advances in the tumor interactions of ultrasmall AuNPs.In addition,the imaging performance of the ultrasmall AuNPs is summarized and discussed.Finally,we summarize this review and provide some perspective on the future research direction of the ultrasmall AuNPs,aiming to accelerate their clinical translation.

Study of the Relationship Between New Ionic Interaction Parameters and Salt Solubility in Electrolyte Solutions Based on Molecular Dynamics Simulation

Studying the relationship between ionic interactions and salt solubility in seawater has implications for seawater desalination and mineral extraction.In this paper,a new method of expressing ion-to-ion interaction is proposed by using molecular dynamics simulation,and the relationship between ion-to-ion interaction and salt solubility in a simulated seawater water-salt system is investigated.By analyzing the variation of distance and contact time between ions in an electrolyte solution,from both spatial and temporal perspectives,new parameters were proposed to describe the interaction between ions:interaction distance(ID),and interaction time ratio(ITR).The best correlation between characteristic time ratio and solubility was found for a molar ratio of salt-to-water of 10:100 with a correlation coefficient of 0.96.For the same salt,a positive correlation was found between CTR and the molar ratio of salt and water.For type 1-1,type 2-1,type 1-2,and type 2-2 salts,the correlation coefficients between CTR and solubility were 0.93,0.96,0.92,and 0.98 for a salt-to-water molar ratio of 10:100,respectively.The solubility of multiple salts was predicted by simulations and compared with experimental values,yielding an average relative deviation of 12.4%.The new ion-interaction parameters offer significant advantages in describing strongly correlated and strongly hydrated electrolyte solutions.

Interatomic Interaction Models for Magnetic Materials:Recent Advances

Atomistic modeling is a widely employed theoretical method of computational materials science.It has found particular utility in the study of magnetic materials.Initially,magnetic empirical interatomic potentials or spinpolarized density functional theory(DFT)served as the primary models for describing interatomic interactions in atomistic simulations of magnetic systems.Furthermore,in recent years,a new class of interatomic potentials known as magnetic machine-learning interatomic potentials(magnetic MLIPs)has emerged.These MLIPs combine the computational efficiency,in terms of CPU time,of empirical potentials with the accuracy of DFT calculations.In this review,our focus lies on providing a comprehensive summary of the interatomic interaction models developed specifically for investigating magnetic materials.We also delve into the various problem classes to which these models can be applied.Finally,we offer insights into the future prospects of interatomic interaction model development for the exploration of magnetic materials.

Resistive field generation in intense proton beam interaction with solid targets

The Brown-Preston-Singleton(BPS)stopping power model is added to our previously developed hybrid code to model ion beam-plasma interaction.Hybrid simulations show that both resistive field and ion scattering effects are important for proton beam transport in a solid target,in which they compete with each other.When the target is not completely ionized,the self-generated resistive field effect dominates over the ion scattering effect.However,when the target is completely ionized,this situation is reversed.Moreover,it is found that Ohmic heating is important for higher current densities and materials with high resistivity.The energy fraction deposited as Ohmic heating can be as high as 20%-30%.Typical ion divergences with half-angles of about 5°-10°will modify the proton energy deposition substantially and should be taken into account.

Dynamical nonlinear excitations induced by interaction quench in a two-dimensional box-trapped Bose-Einstein condensate

Manipulating nonlinear excitations,including solitons and vortices,is an essential topic in quantum many-body physics.A new progress in this direction is a protocol proposed in[Phys.Rev.Res.2043256(2020)]to produce dark solitons in a one-dimensional atomic Bose–Einstein condensate(BEC)by quenching inter-atomic interaction.Motivated by this work,we generalize the protocol to a two-dimensional BEC and investigate the generic scenario of its post-quench dynamics.For an isotropic disk trap with a hard-wall boundary,we find that successive inward-moving ring dark solitons(RDSs)can be induced from the edge,and the number of RDSs can be controlled by tuning the ratio of the after-and before-quench interaction strength across different critical values.The role of the quench played on the profiles of the density,phase,and sound velocity is also investigated.Due to the snake instability,the RDSs then become vortex–antivortex pairs with peculiar dynamics managed by the initial density and the after-quench interaction.By tuning the geometry of the box traps,demonstrated as polygonal ones,more subtle dynamics of solitons and vortices are enabled.Our proposed protocol and the discovered rich dynamical effects on nonlinear excitations can be realized in near future cold-atom experiments.

Effect of electron-electron interaction on polarization process of exciton and biexciton in conjugated polymer

By using one-dimensional tight-binding model modified to include electron-electric field interaction and electron-electron interaction,we theoretically explore the polarization process of exciton and biexciton in cis-polyacetylene.The dynamical simulation is performed by adopting the non-adiabatic evolution approach.The results show that under the effect of moderate electric field,when the strength of electron-electron interaction is weak,the singlet exciton is stable but its polarization presents obvious oscillation.With the enhancement of interaction,it is dissociated into polaron pairs,the spin-flip of which can be observed through modulating the interaction strength.For the triplet exciton,the strong electron-electron interaction restrains its normal polarization,but it is still stable.In the case of biexciton,the strong electron-electron interaction not only dissociate it,but also flip its charge distribution.The yield of the possible states formed after the dissociation of exciton and biexciton is also calculated.

Silica-modified Pt/TiO_(2) catalysts with tunable suppression of strong metal-support interaction for cinnamaldehyde hydrogenation

Tuning Strong Metal-support Interactions(SMSI)is a key strategy to obtain highly active catalysts,but conventional methods usually enable TiO encapsulation of noble metal components to minimize the exposure of noble metals.This study demonstrates a catalyst preparation method to modulate a weak encapsulation of Pt metal nanoparticles(NPs)with the supported TiO_(2),achieving the moderate suppression of SMSI effects.The introduction of silica inhibits this encapsulation,as reflected in the characterization results such as XPS and HRTEM,while the Ti4+to Ti3+conversion due to SMSI can still be found on the support surface.Furthermore,the hydrogenation of cinnamaldehyde(CAL)as a probe reaction revealed that once this encapsulation behavior was suppressed,the adsorption capacity of the catalyst for small molecules like H_(2) and CO was enhanced,which thereby improved the catalytic activity and facilitated the hydrogenation of CAL.Meanwhile,the introduction of SiO_(2) also changed the surface structure of the catalyst,which inhibited the occurrence of the acetal reaction and improved the conversion efficiency of C=O and C=C hydrogenation.Systematic manipulation of SMSI formation and its consequence on the performance in catalytic hydrogenation reactions are discussed.