Interaction Radius Research Articles

4D-based Robot Navigation Using Relativistic Image Processing

Machine perception is an important prerequisite for safe interaction and locomotion in dynamic environments. This requires not only the timely perception of surrounding geometries and distances but also the ability to react to changing situations through predefined, learned but also reusable skill endings of a robot so that physical damage or bodily harm can be avoided. In this context, 4D perception offers the possibility of predicting one’s own position and changes in the environment over time. In this paper, we present a 4D-based approach to robot navigation using relativistic image processing. Relativistic image processing handles the temporalrelated sensor information in a tensor model within a constructive 4D space. 4D-based navigation expands the causal understanding and the resulting interaction radius of a robot through the use of visual and sensory 4D information.

Transparent mechanism of salted egg (white) hierarchically and synergistically driven by NaCl, NaOH and thermal treatment: Based on empirical data and molecular simulation

Currently, it is a challenge that the yolk in salted preserved egg tends to preserved egg yolk due to extreme NaOH treatment. Therefore, NaCl, NaOH and thermal were successfully used to prepare a new translucent salted quail egg (T-SQE), which combined advantages of preserved egg white with transparent appearance and salted egg yolk with unique texture and odour. Moreover, transparency of opaque gel (Transmittance: 0.09 %) subjected to NaCl and thermal was demonstrated to be improved under the synergistic effect of NaOH (8.55 %) via empirical data and molecular simulation. The disordered and dense network in opaque T-SQE induced by NaCl and thermal tended to form an ordered, porous and transparent structure in presence of NaOH, with more immobilized water that was poorly bonded to protein, larger radius of gyration and lower hydrophobic interaction. This research provides new insight into understanding the influence of hierarchy and synergism on transparency of egg products.

Collective motion of binary chiral particle mixtures with environmental complex noise.

The strategies for demixing and sorting mixed-chirality particles are crucial in the biochemical and pharmaceutical industries. However, whether chiral mixed particles can effectively separate in more complex spatial environments remains unresolved. In this paper, we explore the collective motion of binary chiral particle mixtures with environmental complex noise in the binary chiral Vicsek model (BCVM). We discover that the noisy region ratio, λ, significantly influences the separation behavior and spatial distribution of binary mixtures, unveiling system states not observed in uniform environments. Additionally, varying the chirality of particles reveals four distinct phases in our model. In the Vicsek bands phase (small chirality), an increase in λ can, under certain conditions, promote segregation rather than consistently hindering the demixing process. Conversely, for large chirality, localized dynamics and a homogeneous phase emerge, reducing the impact of λ on separation behavior. Notably, when chirality and activity are comparable, macrodrops and microflock phases appear, with a mixed-segregated state transition occurring at a critical λ_{c}. For λ<λ_{c}, chiral separation occurs with particles confined to the noise-free region. However, when λ>λ_{c}, particles gradually migrate to the noisy region, disrupting the separation. Further, we discuss the effects of multiple factors, including chirality, velocity, noise magnitude, particle number, and system size on λ_{c}. We also identify an optimal interaction radius at which λ_{c} reaches its peak value. Our findings may inspire strategies for achieving spontaneous demixing and spatial migration of mixed-chirality particles in complex environments.

Numerical analysis of a class of penalty discontinuous Galerkin methods for nonlocal diffusion problems

In this paper, we consider a class of discontinuous Galerkin (DG) methods for one-dimensional nonlocal diffusion (ND) problems. The nonlocal models are integral equations that are widely used in describing many physical phenomena with long-range interactions. The ND problem is the nonlocal analog of the classic diffusion problem, and the nonlocality disappears as the interaction radius (horizon) vanishes, then the ND problem recovers the classic diffusion problem. Under certain conditions, the exact solution to the ND problem may contain discontinuities, and this is one of the properties of the ND problem that sets it apart from the classic diffusion problem. It is natural to adopt the DG method to compute the ND problems since the DG method shows its great advantages in resolving problems with discontinuities in the computational fluid dynamics in the past several decades. Based on \cite{DuCAMC2020}, we construct the DG methods with different penalty terms, and the proposed DG methods have their local counterparts as the horizon vanishes. This indicates the proposed methods will converge to the existing DG schemes as the horizon vanishes, which is crucial to obtain the {\it asymptotic compatibility}. Rigorous proofs are provided to demonstrate the stability, error estimates, and asymptotic compatibility of the proposed DG schemes. To see the nonlocal diffusion effect, we also consider the time-dependent convection-diffusion problems with nonlocal diffusion. We conduct several numerical experiments, including accuracy tests and Burgers' equation with nonlocal diffusion, and various horizons are taken to show the good performance of the proposed algorithm and validate the theoretical findings.

Solubility of 2,5-Furandicarboxylic Acid in Pure and Mixed Organic Solvent Systems at 293 K Predicted Using Hansen Solubility Parameters.

Central to the production of polyethylene furanoate (PEF), a bioplastic that could potentially replace petroleum-derived plastics, is 2,5-furandicarboxylic acid (FDCA). FDCA is a chemical derived from biomass that has low solubility in traditionally used solvents such as water. Thus, identifying solvents that can solubilize significant amounts of FDCA could allow for lower PEF production costs. In this study, FDCA solubility was investigated in nine pure solvents including H2O, acetonitrile (ACN), γ-valerolactone (GVL), γ-butyrolactone (GBL), ethanol (EtOH), methanol (MeOH), dimethyl sulfoxide (DMSO), sulfolane (SULF), and tetrahydrofuran (THF), eight binary, and three ternary solvent blends at 293 K. For all binary systems excluding DMSO and MeOH, the solubility of FDCA increased 1.5-65 times compared to the pure organic solvent, and the FDCA solubility was at least 10 times higher when compared to pure water. Specifically, the 20/80 w/w H2O/DMSO system solubilized 23.1 wt % FDCA, the highest of any binary blend studied, and 190 times more solubility than in pure water. In 20/80 w/w H2O/THF, the FDCA solubility was 60 times higher than pure water. In ternary blends that included DMSO, H2O, and either GVL, THF, or SULF, solubility increased by at least 6.6 times relative to the pure secondary organic component and 54 times relative to pure water. Using Hansen solubility parameters (HSPs), the radius of interaction (R i,j ) was found to be more strongly correlated to FDCA solubility than individual HSPs or the total solubility parameter. A MATLAB-based optimization code was developed and successful in minimizing the R i,j of a solvent blend to maximize FDCA solubility in binary and ternary aqueous solvents.

Production of D(*)D¯(*) near the thresholds in e+e− annihilation

It is shown that the nontrivial energy dependencies of DD¯, DD¯*, and D*D¯* pair production cross sections in e+e− annihilation are well described within the approach based on an account of the final-state interaction of produced particles. This statement is valid for the production of charged and neutral particles. Interaction of D(*) and D¯(*) is taken into account using the effective potential method. Its applicability is based on the fact that for near-threshold resonance the characteristic width of peak in the wave function is much larger than the interaction radius. The transition amplitudes between all three channels play an important role in the description of cross sections. These transitions are possible since all channels have the same quantum numbers JPC=1−−. Published by the American Physical Society 2024

Opinion formation on evolving network: the DPA method applied to a nonlocal cross-diffusion PDE-ODE system

Abstract We study a system of nonlocal aggregation cross-diffusion PDEs that describe the evolution of opinion densities on a network. The PDEs are coupled with a system of ODEs that describe the time evolution of the agents on the network. Firstly, we apply the Deterministic Particle Approximation (DPA) method to the aforementioned system in order to prove the existence of solutions under suitable assumptions on the interactions between agents. Later on, we present an explicit model for opinion formation on an evolving network. The opinions evolve based on both the distance between the agents on the network and the ’attitude areas’, which depend on the distance between the agents’ opinions. The position of the agents on the network evolves based on the distance between the agents’ opinions. The goal is to study radicalisation, polarisation and fragmentation of the population while changing its open-mindedness and the radius of interaction.

Particle swarm intelligence promotes cooperation by adapting interaction radii in co-evolutionary games

Particle swarm optimization (PSO), a population-based optimization algorithm inspired by swarm behaviors, has been applied extensively to simulate social behaviors such as migration, urban planning, or resource utilization. It capitalizes on the inherent principles of social cooperation, adaptability and learning from peers to help individuals in a population search for optima. In this work, we propose a novel co-evolutionary game model in which individuals adapt their interaction radii by applying the PSO algorithm and study how the learning factor ω in the algorithm shapes the cooperation dynamics. We find that the adaptive interaction radii based on PSO could significantly enhance cooperation, especially in the scenario with strong social dilemma. By studying the snapshots of strategy pattern and the distributions of interaction radii in the population, we further reveal that the PSO-based adapting mechanism can protect cooperators by shrinking the interaction radii in a severe environment with an appropriate ω. Nevertheless, when cooperation is favorable, the adaptation leads to a relatively wide distribution of interaction radii to facilitate the spread of cooperation. The results of this work highlight the potential of the PSO algorithm to resolve social dilemmas when combined with the evolutionary dynamics.

Collective motion of chiral particles in complex noise environments.

Collective motion of chiral particles in complex noise environments is investigated based on the Vicsek model. In the model, we added chirality, along with complex noise, affecting particles clustering motion. Particles can only avoid noise interference in a specific channel, and this consideration is more realistic due to the complexity of the environment. Via simulations, we find that the channel proportion, p, critically influences chiral particle synchronization. Specifically, we observe a disorder-order transition at critical [Formula: see text], only when [Formula: see text], the system can achieve global synchronization. Combined with our definition of spatial distribution parameter and observation of the model, the reason is that particles begin to escape from the noise region under the influence of complex noise. In addition, the value of [Formula: see text] increases linearly with velocity, while it decreases monotonically with the increase in chirality and interaction radius. Interestingly, an appropriate noise amplitude minimizes [Formula: see text]. Our findings may inspire novel strategies to manipulate self-propelled particles of distinct chirality to achieve desired spatial migration and global synchronization.

Two birds, one stone: Simultaneous removal of saccharides and metal ions from ionic liquid solution by selective electrodialysis

The efficient and cost-effective elimination of saccharides and metal ions solving in the ionic liquid spinning solution produced in the regenerated cellulose fibers (RCFs) manufacture is highly desirable in view of the RCF quality and IL recycling. Herein, the ‘two birds and one stone’ strategy was proposed for simultaneous removal of saccharides and metal ions solving in [Emim]Dep spinning solution by selective electrodialysis (SED). Benefiting from the electric neutrality of saccharides, the differences of IL and metal ions (Mg2+ and Ca2+) in electrostatic interaction and hydration radius, the permeation ratio of IL (PIL), removal ratios of saccharides (Rs), Mg2+ (RMg2+) and Ca2+ (RCa2+) could reach up to 96.0 %, 94.8 %, 95.0 % and 95.0 %, respectively in the practical ionic liquid spinning solution. The structure of [Emim]Dep after SED process was similar to that of pristine, indicating the stability during the SED process. Interestingly, the presence of saccharides was beneficial to the removal of metal ions because of the complexation. Moreover, the membrane fouling process and mechanism were also investigated by the determination of ion exchange capacity and the characterization of morphology and structure. Along this line, the corresponding cleaning strategy was raised and the performance of the membrane did not change notably within 5-times recycle. Thus, this work put forward a facile and cost-effective method for one-step removal of saccharides and metal ions and the purification of ionic liquids, which could be popularized in the fields of biomass pretreatment and dissolution using ILs.

Search for a New Internucleon Interaction Using Neutron Powder Diffraction

The application of neutron powder diffraction to search for a new internucleon Yukawa-like interaction is considered. The essence of the method is in the investigation of dependency of the neutron scattering amplitude on the momentum transfer. The possible contributions to the scattering amplitude and to the integrated intensity of diffraction maxima were analyzed. The neutron diffraction experiment with silicon powder at D20 diffractometer of the ILL reactor (Grenoble, France) was performed. From the data obtained constraints on the coupling constant of the considered interaction were made. It is shown that in the interaction radius range of λ = 10–13–10—11 m they improve the values already existing in the literature. The result obtained is limited by imperfections of the experimental setup. Eliminating the instrumental contribution may allow increasing the sensitivity of the method by at least an order of magnitude.

Determination of carbon nanoparticle dispersion solubility parameters using the classic Hansen and the DiPEVa method

Hansen's three-dimensional Solubility Parameter (3DSP) are widely recognized for assessing the compatibility of a dispersed phase with a continuous phase. A modified approach, known as the DiPEVa method, has recently emerged in the literature. This method refines 3DSP by incorporating surface tension considerations. Given the presence of these two similar methodologies, the objective of this study is to conduct a comparative analysis between the two approaches, employing carbon nanoparticles, including graphene oxide, carbon quantum dots (produced via microwave pyrolysis of Spirulina microalgae, and the reaction between citric acid and ethylenediamine), graphene nanoplatelets, and carbon nanotubes as the focal subjects. To achieve this, assessing solubility parameters involved dispersing these nanoparticles in 32 organic solvents with well-established solubility parameters. Subsequently, the collected data underwent a genetic algorithm optimization, facilitating the computation of the Hansen 3D dispersibility sphere. This process included the calculation of the 3DSP for the sphere's central point and its interaction radius (R0). Quality-of-fit metrics, such as DataFit values and the percentage of outliers, were computed to assess the accuracy of the models. As a result, it was evident that the DiPEVa method outperformed the Hansen method in most cases, except for carbon quantum dot dispersion obtained through Spirulina pyrolysis, where both methods yielded comparable results.

Study on Community Detection Method for Morning and Evening Peak Shared Bicycle Trips in Urban Areas: A Case Study of Six Districts in Beijing

Examining the clustering characteristics and fluctuations within urban areas during peak hours through the lens of bike-sharing is of utmost importance in the optimization of bike-sharing systems and urban transportation planning. This investigation adopts the principles of urban spatial interaction network construction and employs streets as the fundamental units of analysis to model bike-sharing activities during morning and evening peak hours within Beijing’s six central districts. Subsequent to this, a comprehensive analysis of the network’s structural attributes was carried out. A Walktrap method, rooted in modularity analysis, was introduced to discern and scrutinize the clustering patterns and characteristics of communities within the network across different temporal intervals. Empirical findings reveal a predominant usage pattern of shared bicycles for short-distance travel during both morning and evening peak hours. Notably, distinctive community structures manifest during these periods, characterized by two large communities and multiple smaller ones during the morning peak, while the evening peak showcases a single large community alongside several medium-sized and smaller ones. Moreover, the extended interaction radius points to an expanded geographic range of interactions among streets. These findings bear significant implications for the management of urban transportation, bike-sharing enterprises, and urban residents, proffering valuable insights for the optimization of bike-sharing schemes and transportation strategies. These research findings not only contribute to enhancing urban transportation planning and bike-sharing systems but also provide robust guidance for advancing more efficient and sustainable urban transportation solutions, thereby fostering the sustainable development of cities.

Unraveling the Functional Significance of Unstructured Regions in G Protein-Coupled Receptors.

Unstructured regions in functional proteins have gained attention in recent years due to advancements in informatics tools and biophysical methods. G protein-coupled receptors (GPCRs), a large family of cell surface receptors, contain unstructured regions in the form of the i3 loop and C-terminus. This review provides an overview of the functional significance of these regions in GPCRs. GPCRs transmit signals from the extracellular environment to the cell interior, regulating various physiological processes. The i3 loop, located between the fifth and sixth transmembrane helices, and the C-terminus, connected to the seventh transmembrane helix, are determinant of interactions with G proteins and with other intracellular partners such as arrestins. Recent studies demonstrate that the i3 loop and C-terminus play critical roles in allosterically regulating GPCR activation. They can act as autoregulators, adopting conformations that, by restricting G protein access, modulate receptor coupling specificity. The length and unstructured nature of the i3 loop and C-terminus provide unique advantages in GPCR interactions with intracellular protein partners. They act as "fishing lines", expanding the radius of interaction and enabling GPCRs to tether scaffolding proteins, thus facilitating receptor stability during cell membrane movements. Additionally, the i3 loop may be involved in domain swapping between GPCRs, generating novel receptor dimers with distinct binding and coupling characteristics. Overall, the i3 loop and C-terminus are now widely recognized as crucial elements in GPCR function and regulation. Understanding their functional roles enhances our comprehension of GPCR structure and signaling complexity and holds promise for advancements in receptor pharmacology and drug development.

Quantum hydrodynamic representation of the exchange interaction in the theory of description of magnetically ordered media

Ferromagnets, multiferroics and other magnetically ordered materials are described by various models of the evolution of the magnetization of the medium. In this paper, we develop the method of many-particle quantum hydrodynamics for such media. We use the Heisenberg Hamiltonian and derive an equation for the evolution of macroscopic magnetization, corresponding to the non-dissipative version of the Landau-Lifshitz equation for particles with spin 1/2. It is shown that the well-known form of the contribution of the exchange interaction to the Landau-Lifshitz equation arises in the third order in terms of the interaction radius. The possibilities of the systematic generalization of the result obtained are discussed when considering the fifth order in the interaction radius or when considering particles with a large spin.

In Silico and In Vitro Potential of FDA-Approved Drugs for Antimalarial Drug Repurposing against Plasmodium Serine Hydroxymethyltransferases.

Malaria has spread in many countries, with a 12% increase in deaths after the coronavirus disease 2019 pandemic. Malaria is one of the most concerning diseases in the Greater Mekong subregion, showing increased drug-resistant rates. Serine hydroxymethyltransferase (SHMT), a key enzyme in the deoxythymidylate synthesis pathway, has been identified as a promising antimalarial drug target due to its conserved folate binding pocket. This study used a molecular docking approach to screen 2509 US Food and Drug Administration (FDA)-approved drugs against seven Plasmodium SHMT structures. Eight compounds had significantly lower binding energies than the known SHMT inhibitors pyrazolopyran(+)-86, tetrahydrofolate, and antimalarial drugs, ranging from 4 to 10 kcal/mol. Inhibition assays testing the eight compounds against Plasmodium falciparum SHMT (PfSHMT) showed that amphotericin B was a competitive inhibitor of PfSHMT with a half-maximal inhibitory concentration (IC50) of 106 ± 1 μM. Therefore, a 500 ns molecular dynamics simulation of PfSHMT/PLS/amphotericin B was performed. The backbone root-mean-square deviation of the protein-ligand complex indicated the high complex stability during simulations, supported by its radius of gyration, hydrogen-bond interactions, and number of atom contacts. The appreciable binding affinity of amphotericin B for PfSHMT was indicated by their solvated interaction energy (-11.15 ± 0.09 kcal/mol) and supported by strong ligand-protein interactions (≥80% occurrences) with its essential residues (i.e., Y78, K151, N262, F266, and V365) predicted by pharmacophore modeling and per-residue decomposition free energy methods. Therefore, our findings identify a promising new PfSHMT inhibitor, albeit with less inhibitory activity, and suggest a core structure that differs from that of previous SHMT inhibitors, thus being a rational approach for novel antimalarial drug design.

Boundary regularity of an isotropically censored nonlocal operator

In a bounded domain, we consider a variable range nonlocal operator, which is maximally isotropic in the sense that its radius of interaction equals the distance to the boundary. We establish C^{1,alpha } boundary regularity and existence results for the Dirichlet problem.

Scattering evidence of positional charge correlations in polyelectrolyte complexes

Polyelectrolyte complexation plays an important role in materials science and biology. The internal structure of the resultant polyelectrolyte complex (PEC) phase dictates properties such as physical state, response to external stimuli, and dynamics. Small-angle scattering experiments with X-rays and neutrons have revealed structural similarities between PECs and semidilute solutions of neutral polymers, where the total scattering function exhibits an Ornstein-Zernike form. In spite of consensus among different theoretical predictions, the existence of positional correlations between polyanion and polycation charges has not been confirmed experimentally. Here, we present small-angle neutron scattering profiles where the polycation scattering length density is matched to that of the solvent to extract positional correlations among anionic monomers. The polyanion scattering functions exhibit a peak at the inverse polymer screening radius of Coulomb interactions, q* ≈ 0.2 Å-1. This peak, attributed to Coulomb repulsions between the fragments of polyanions and their attractions to polycations, is even more pronounced in the calculated charge scattering function that quantifies positional correlations of all polymer charges within the PEC. Screening of electrostatic interactions by adding salt leads to the gradual disappearance of this correlation peak, and the scattering functions regain an Ornstein-Zernike form. Experimental scattering results are consistent with those calculated from the random phase approximation, a scaling analysis, and molecular simulations.

Contact interaction model of liquid and solid phases

The work implements the approach formulated by B.V. Deryagin, which states for replacing the Coulomb and molecular (dispersion) forces with a system of tensions obtained on the basis of the mechanics of continuum equations using an incompressible liquid model. Interphasal activity modeling is considered from the standpoint of the equilibrium equations of mechanics of continuum using an incompressible liquid model and representing the interfacial tension tensor as a combination of spherical and deviatoric components. Analytical expressions are obtained for the components of the tension tensor depending on the wetting conditions of a solid surface with a liquid. Intermolecular interaction is determined by the value of the internal pressure of the liquid, which is variable over the interfacial layer thickness. The anisotropy of the interfacial tension tensor in the liquid-solid interfacial layer is expressed by the representation of the spherical and deviatoric components combination, which provides the equilibrium conditions for the interfacial layer. The authors propose to consider the adhesive contact as an external force effect of a solid surface on the volume phase of a liquid, leading to the formation of an interfacial tension tensor with components that are variable over the layer thickness. The authors established the nonlinear nature of the interfacial pressure distribution over the layer thickness, due to the difference in interfacial pressures in the liquid and solid phases in the direct contact zone. It is shown that the surface phenomena specificity is due to the deformation of the liquid volume in the interfacial layer, which leads to a change in intermolecular distances in different directions, which occurs with any kind of force acting on the volume phase of the liquid. The law of intermolecular forces distribution of a liquid depending on the distance is established based on the study results of a sitting drop. Expressions are obtained for determining the long-range interaction radius of liquid molecules and the thickness of the liquid-solid interfacial layer, which give a result that fits into the known estimates of the values of these quantities.

Effect of mixed random and directional migration on cooperation in the spatial prisoner’s dilemma

The migration behavior of the population plays a significant role in the evolution of cooperation in spatial games. During the migration process, individuals may be affected by uncertain and irrational factors, and these will affect their direction of migration. In previous studies, the migration direction has been determined either entirely randomly or using entirely deterministic factors, referred to as random and directional migration, respectively. However, in real-world situations, a mixture of both random and deterministic factors will be included in individuals’ migration decisions. In this work, we examined the effects of a mixture of directional and random migration on cooperation. In our model, for the directional migration, the average migration direction of an individual’s neighbors is used. We then introduce the parameter α to adjust the proportion of directional and random migration. The results show that a small value of α and a lower speed are beneficial to cooperation. Furthermore, we find that there is always an optimal range of α that will best promote the evolution of cooperation. We explain these phenomena based on time series of the cooperation level and the order parameter, and spatial population snapshots. We also investigate the effects of the interaction radius between individuals and population density on the evolution of cooperation. The robustness of this migration mode is further verified with respect to another game model, and we find that the conclusions remain the same.