Potential Interactions Research Articles

ROBUSTNESS EVALUATION OF MACHINE LEARNING ALGORITHMS FOR NEUROCOMPUTER INTERFACE SOFTWARE USING DISTRIBUTED AND PARALLEL COMPUTING

This article highlights the field of information technology for brain-computer interaction, and the main goal is to use it to determine patterns of human brain activity using electroencephalography (EEG) data. During the execution of the article, machine learning methods were used, namely such classifiers as Random Forest, Multi-Layer Perceptron (MLP), and Logistic Regression. The investigation begins with real-world experiments recording EEG signals during finger movement tasks, providing valuable insight into the complex dynamics of brain operation and interaction. Utilizing 10-fold cross-validation, the performance of each classifier is rigorously evaluated across various metrics, including accuracy, f1_weighted та roc_auc_ovr_weighted. Through this process, the robustness and consistency of classifier performance are assessed, with dispersion values computed to gauge variability across iterations. The findings reveal nuanced differences among the classifiers, with MLP demonstrating the highest robustness, followed by Logistic Regression and Random Forest. The main goal of the article was to find out the importance of such a classifier performance parameter as robustness. Software robustness is a key characteristic, especially in medical applications, where consistent and reliable performance of information technology is paramount. Neural interfaces offer many avenues for solving various limb problems, spinal cord injuries, and neurological diseases in humans. These devices contribute to improving the quality of life by minimizing these problems in people, which leads to increased mobility and functional capabilities of people. The article also emphasizes the potential associated with the transformation of neurointerface technologies in expanding human capabilities and revolutionizing human-machine interaction. In conclusion, the research contributes to advancing the field of brain-computer interaction by leveraging machine learning algorithms to decode neural signals and uncover hidden patterns within EEG data. By identifying the most stable classifier, the study lays the groundwork for the development of robust neurointerface technologies with practical applications in healthcare, rehabilitation, and beyond. Through interdisciplinary collaboration and innovative methodologies, the journey towards unlocking the full potential of brain-computer interaction continues, promising new horizons in human augmentation and technological innovation.

Discovering dynamic laws from observations: The case of self-propelled, interacting colloids.

Active matter spans a wide range of time and length scales, from groups of cells and synthetic self-propelled colloids to schools of fish and flocks of birds. The theoretical framework describing these systems has shown tremendous success in finding universal phenomenology. However, further progress is often burdened by the difficulty of determining forces controlling the dynamics of individual elements within each system. Accessing this local information is pivotal for the understanding of the physics governing an ensemble of active particles and for the creation of numerical models capable of explaining the observed collective phenomena. In this work, we present ActiveNet, a machine-learning tool consisting of a graph neural network that uses the collective motion of particles to learn active and two-body forces controlling their individual dynamics. We verify our approach using numerical simulations of active Brownian particles, active particles undergoing underdamped Langevin dynamics, and chiral active Brownian particles considering different interaction potentials and values of activity. Interestingly, ActiveNet can equally learn conservative or nonconservative forces as well as torques. Moreover, ActiveNet has proven to be a useful tool to learn the stochastic contribution to the forces, enabling the estimation of the diffusion coefficients. Therefore, all coefficients of the equationof motion of Active Brownian Particles are captured. Finally, we apply ActiveNet to experiments of electrophoretic Janus particles, extracting the active and two-body forces controlling colloids' dynamics. On the one side, we have learned that the active force depends on the electric field and area fraction. On the other side, we have also discovered a dependence of the two-body interaction with the electric field that leads us to propose that the dominant force between active colloids is a screened electrostatic interaction with a constant length scale. We believe that the proposed methodological tool, ActiveNet, might open a new avenue for the study and modeling of experimental suspensions of active particles.

Solute segregation in a moving grain boundary: a phase-field approach

We present a phase-field approach for investigating monolayer and multilayer type solute segregation in a moving Grain boundary (GB). In this model, we introduce an expression for the GB solute interaction potential which allows for easy modification of the shape of the solute segregation profile at the GB. As a consequence, our phase-field simulations capture various segregation profiles in both stationary and migrating GB that agree with Cahn’s solute drag theory. Furthermore, we explore how different segregation profiles evolve at varying GB velocities owing to the inequality of the atomic flux of solute between the front and back faces of the moving GB. At a low-velocity regime, we observe that multilayer segregation results in significantly increased drag force compared to monolayer segregation. At a high-velocity regime, the opposite holds. Our simulation results also provide valuable insights for predicting grain growth in polycrystalline materials in the presence of solute segregation.

Dispersion Energies with the i-DMFT Method.

The recently proposed i-DMFT method [Wang and Baerends, Phys. Rev. Lett. 128, 013001 (2022)] has been proven to be ideally suited to recover strong static correlation in dissociating covalent bonds. Here, the application to van der Waals bonding is investigated using the prototype van der Waals systems triplet H2 and ground-state He2. It is demonstrated that the i-DMFT orbitals are in this case essentially different from the natural orbitals, and the i-DMFT occupations differ substantially from the NO occupations. This is shown to lead to rather deficient interaction potential curves, even if a reasonable well depth may be obtained by fitting of parameters. If the basis set is extended, however, it may no longer be possible to generate van der Waals bonding at all. The linear behavior of the two-electron cumulant energy Ecum as a function of the "entropy" S along a dissociation coordinate, which was the basis of i-DMFT, is distinctly poorer in the case of van der Waals bonding than for covalent bonding.

Deliberate Starvation: Hunger Artists in Kafka, Różewicz, and Sinking Ship

How can a negative action, the decision to abstain from food, be enacted on stage? Examining hunger as a conscious choice to avoid food for spectacle rather than an unwanted need arising from lack of basic nourishment, this article illustrates several ways to make hunger visible in performance. Through the critical lens of actor-network theory (ANT), hunger’s apparently scarce dramatic action is shown to be framed by and networked with the performance of several other human and non-human actors. Case studies chart a process of “translation” of the typical hunger artist performance from its historical examples to its contemporary theatre-within-the-theatre adaptations. In the West, self-inflicted starvation became a form of entertainment more distinctly in the late nineteenth century, when living skeletons and hunger artists were shown at circuses, fairs, and amusement parks, and produced income for themselves and their impresarios. Franz Kafka’s short story “Ein Hungerkünstler” (“A Hunger Artist,” 1922) looked back at the history of the profession, identifying the main components of the spectacle of hunger. Polish playwright Tadeusz Różewicz turned the short story into a play, Odejście głodomora (The Hunger Artist Departs, 1977), exploring the potential for dialogic interactions at the textual level and developing side-characters only implied by Kafka. By contrast, the contemporary NYC-based company Sinking Ship created A Hunger Artist (2017), an adaptation that expanded the short story’s theatricality around a single performer who plays multiple characters with the aid of all the resources of theatre, from puppets to audience members “enrolled” in the show.

The breakdown of the direct relation between the density scaling exponent and the intermolecular interaction potential for molecular systems with purely repulsive intermolecular forces

In this work, we question the generally accepted statement that the character of intermolecular interactions can be directly determined from the scaling exponent. We show that the scaling exponent evidently differs on the molecular architecture for pure inverse power law systems. Since these systems are characterized by a well-defined dependency between the intermolecular virial and potential energy, the results contradict theoretical predictions and previous reports. Moreover, we suggest that the recently proposed “molecular force” method also returns the value that varies from the one scaling the dynamics. Finally, the obtained result allows us to conclude that the value of the density scaling exponent for real liquids depends on intramolecular interactions.

Robot-Mediated Intergenerational Childcare: Experimental Study Based on Health-Screening Task in Nursery School

Intergenerational interactions between children and older adults are gaining broader recognition because of their mutual benefits. However, such interactions face practical limitations owing to potential disease transmission and the poor health of older adults for face-to-face interactions. This study explores robot-mediated interactions as a potential solution to address these issues. In this study, older adults remotely controlled a social robot to perform a health-screening task for nursery school children, thereby overcoming the problems associated with face-to-face interactions while engaging in physical interactions. The results of this study suggested that the children responded favorably to the robot, and the rate of positive response increased over time. Older adults also found the task generally manageable and experienced a significant positive shift in their attitude toward children. These findings suggest that robot-mediated interactions can effectively facilitate intergenerational engagement and provide psychosocial benefits to both the parties to the engagement. This study provides valuable insights into the potential of robot-mediated interactions in childcare and other similar settings.

Developing of a Monte Carlo calculations-based on simulation code for binary collision approximation in amorphous materials

In this work, we present a computer code developed and named MCIS (Monte Carlo Collisions In Solids) in his first version allowing the study and determination of the structure properties (arrangement, vacancies, energy losses...) during ion implantation in an amorphous solid matrix. This code is based on both the binary collisions approximation (BCA) theory and statistical Monte Carlo method within C++ Builder environment. The properties of this code can be summarized as: simulate 92 chemical elements of periodic table, the energy of projectile tuned from 1eV to few MeV, variable angle of incidence projectile, it can simulated 4 layers with a maximum of 4 elements per layer, it can use of the electronic losses of energies by choose of Firsov or Robinson approximation, various interactions potentials such as the ZBL, Moliers and C-Kr. Possibility of choose of scattering phenomenon among the Magic Formula and the Rutherford scattering. The results generated by our code are very promising when compared to those given by SRIM (Stopping and Range of Ions in Matter) code along with the advantage that our code takes into account the effect of the interaction potential which is neglected in SRIM.

GEM-based computational modeling for exploring metabolic interactions in a microbial community.

Microbial communities play fundamental roles in every complex ecosystem, such as soil, sea and the human body. The stability and diversity of the microbial community depend precisely on the composition of the microbiota. Any change in the composition of these communities affects microbial functions. An important goal of studying the interactions between species is to understand the behavior of microbes and their responses to perturbations. These interactions among species are mediated by the exchange of metabolites within microbial communities. We developed a computational model for the microbial community that has a separate compartment for exchanging metabolites. This model can predict possible metabolites that cause competition, commensalism, and mutual interactions between species within a microbial community. Our constraint-based community metabolic modeling approach provides insights to elucidate the pattern of metabolic interactions for each common metabolite between two microbes. To validate our approach, we used a toy model and a syntrophic co-culture of Desulfovibrio vulgaris and Methanococcus maripaludis, as well as another in co-culture between Geobacter sulfurreducens and Rhodoferax ferrireducens. For a more general evaluation, we applied our algorithm to the honeybee gut microbiome, composed of seven species, and the epiphyte strain Pantoea eucalypti 299R. The epiphyte strain Pe299R has been previously studied and cultured with six different phyllosphere bacteria. Our algorithm successfully predicts metabolites, which imply mutualistic, competitive, or commensal interactions. In contrast to OptCom, MRO, and MICOM algorithms, our COMMA algorithm shows that the potential for competitive interactions between an epiphytic species and Pe299R is not significant. These results are consistent with the experimental measurements of population density and reproductive success of the Pe299R strain.

Physiologically-based pharmacokinetic modeling predicts the drug interaction potential of GLS4 in co-administered with ritonavir.

GLS4 is a first-in-class hepatitis B virus (HBV) capsid assembly modulator (class I) that is co-administered with ritonavir to maintain the anticipated concentration required for the effective antiviral activity of GLS4. In this study, the first physiologically-based pharmacokinetic (PBPK) model for GLS4/ritonavir was successfully developed. The predictive performance of the PBPK model was verified using data from 39 clinical studies, including single-dose, multiple-dose, food effects, and drug-drug interactions (DDI). The PBPK model accurately described the PK profiles of GLS4 and ritonavir, with predicted values closely aligning with observed data. Based on the verified GLS4/ritonavir model, it prospectively predicts the effect of hepatic impairment (HI) and DDI on its pharmacokinetics (PK). Notably, CYP3A4 inducers significantly influenced GLS4 exposure when co-administered with ritonavir; co-administered GLS4 and ritonavir significantly influenced the exposure of CYP3A4 substrates. Additionally, with the severity of HI increased, there was a corresponding increase in the exposure to GLS4 when co-administered with ritonavir. The GLS4/ritonavir PBPK model can potentially be used as an alternative to clinical studies or guide the design of clinical trial protocols.

Zigzag phase transition of electrons confined within a thin annulus region

We consider a semiclassical approach to study the possible stabilization of a zigzag phase for a system of interacting electrons confined within a thin annulus region with infinite inner/outer walls. The electrons are considered spinless and interact via the standard Coulomb interaction potential. The classical minimum energy configuration of the system due to the Coulomb repulsion between electrons is accurately determined by using the simulated annealing method. As the number of electrons increases we see the appearance and stabilization of a two-ring structure with zigzag patterns. Further increase of the number of electrons appears to eventually lead to the collapse of the two-ring zigzag structure. A simple quantum treatment of the nodal features of the free many-particle wave function shows the appearance of nodal domain patterns that are consistent with the zigzag features that were observed in the classical model.

Derivation of dirac exchange interaction potential from quantum plasma kinetic theory

The Dirac exchange interaction is derived from recent quantum kinetic theory for collisionless plasmas. For this purpose, the kinetic equation is written in the semiclassical and long wavelength approximations. The validity of the model for real systems is worked out, in terms of temperature and density parameters. Within the region of applicability, the correlation potential energy is shown to be always smaller than the exchange contribution. From the moments of the quantum kinetic equations, macroscopic, hydrodynamic equations are found, for an electron-ion plasma. The Dirac exchange term is explicitly derived, in the case of a completely degenerate electron gas. These results show, within quantum kinetic theory for charged particle systems, a new view of the Dirac exchange interaction frequently used in density functional theory parametrization. Finally, a simpler form of the quantum plasma exchange kinetic theory is also found.

Cellulose nanocrystal dispersions conjugated with symmetric and asymmetric dialkylamine groups

The present study discusses the effect of symmetric and asymmetric grafting on the surface of CNCs (cellulose nanocrystals) on their dispersion properties using dialkyl azetidinium salts. Three dialkylamine of different size and chain length were successfully grafted to the sulfate groups on the surface of CNCs by conjugation of azetidinium salts. The coupling process resulted in the formation of 2-hydroxypropyl-N-dialkylamine conjugated to the CNC sulfate groups abbreviated as Cn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_n$$\\end{document}-N-Cm\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_m$$\\end{document}-Prop-2-OH-CNC, where m, n are the number of carbons in the alkyl groups, each with a total of m+n=12\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$m+n=12$$\\end{document}, with (m,n)=(11,1);(9,3);(6,6)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(m,n) = (11,1); (9,3); (6,6)$$\\end{document}. Molecular dynamics simulations were used to assess the probable morphology of the grafted chains and the interaction potential between CNCs. Steady shear simultaneously combined with polarized light imaging and oscillatory shear rheological measurements were used to evaluate for the first time the impact of the CNC surface modifications on their dispersion flow and optical properties. Overall, the results show that the different linker topologies could effectively promote different types of aggregation morphologies based on the size of the linker, their flexibility and their most probable conformation.

Laser assisted embedding of Pd10Cu bimetals in ZIF-8 enabling highly selective hydrogenation of C = C in π-bond conjugation

Selective hydrogenation of vinyl groups (C = C) and carbonyl groups (C = O) is of significance to effectively convert low-value organic compounds into high-value target chemicals, while a challenge remains on the hydrogenation of C = C bond that is in π-bond conjugation with the C = O bond. Herein, we address this challenge based on a synergetic modulation strategy on electronic structure and adsorption configurations to achieve a highly selective hydrogenation of the C = C bond, achieved by laser-assisted embedding of PdxCu bimetals in the ZIF-8 bulk phase (x represents the Pd/Cu molar ratio in PdCu nanoparticles). It is revealed that laser assisted synthesis of PdxCu bimetals not only inhibits the hydrogenation of C = O and promotes the hydrogenation of C = C, but also results in an arched absorption configuration for substrate molecules that facilitates the selective hydrogenation of vinyl groups. Exemplified by cinnamaldehyde (CAL), the present work achieves 98.03 % conversion of CAL and 100 % selectivity of the hydrocinnamaldehyde (HCAL) (70 °C, 1 MPa H2, 1 h), indicating the potential of laser-matter interaction to tackle the trade-off between conversion efficiency and selectivity in thermal catalysis.

Using Chemistry To Recreate the Complexity of the Extracellular Matrix: Guidelines for Supramolecular Hydrogel-Cell Interactions.

Hydrogels have emerged as a promising class of extracellular matrix (ECM)-mimicking materials in regenerative medicine. Here, we briefly describe current state-of-the-art of ECM-mimicking hydrogels, ranging from natural to hybrid to completely synthetic versions, giving the prelude to the importance of supramolecular interactions to make true ECM mimics. The potential of supramolecular interactions to create ECM mimics for cell culture is illustrated through a focus on two different supramolecular hydrogel systems, both developed in our laboratories. We use some recent, significant findings to present important design principles underlying the cell-material interaction. To achieve cell spreading, we propose that slow molecular dynamics (monomer exchange within fibers) is crucial to ensure the robust incorporation of cell adhesion ligands within supramolecular fibers. Slow bulk dynamics (stress-relaxation─fiber rearrangements, τ1/2 ≈ 1000 s) is required to achieve cell spreading in soft gels (<1 kPa), while gel stiffness overrules dynamics in stiffer gels. Importantly, this resonates with the findings of others which specialize in different material types: cell spreading is impaired in case substrate relaxation occurs faster than clutch binding and focal adhesion lifetime. We conclude with discussing considerations and limitations of the supramolecular approach as well as provide a forward thinking perspective to further understand supramolecular hydrogel-cell interactions. Future work may utilize the presented guidelines underlying cell-material interactions to not only arrive at the next generation of ECM-mimicking hydrogels but also advance other fields, such as bioelectronics, opening up new opportunities for innovative applications.

Simple and modified chitosan gel beads from a natural source as a bio-sorbent for water defluoridation: Experimental and computational perspectives

Water contaminated with fluoride (F -) is widely acknowledged as a major global issue that poses serious health and environmental risks. Adsorption is one of the many fluoride removal treatment methods that has been widely and successfully investigated. In this work, we describe a simple process for making both cross-linked and uncross-linked chitosan gel beads from shrimp waste. SEM, FTIR, XRD and TGA analysis confirmed the successful synthesis of the non-cross-linked chitosan gel beads (Cs beads) and cross-linked chitosan gel (Cs-Ech beads) whose swelling behavior, stability and fluoride removal efficiency were studied. The adsorption conditions were also optimised. An adsorption capacity of 16.59 mg/g was achieved after just 30 min and at pH = 6.8, 10 mg/L and T = 25 °C. It was shown that chitosan gel beads cross-linked with epichlorohydrin removed more fluoride than non-cross-linked chitosan gel beads. The rate of adsorption of fluoride ions is determined by the pseudo-first order kinetic equation. On the other hand, equilibrium data was best described by Langmuir adsorption isotherms. Density functional theory calculations (DFT) based on quantitative analyses were used to explore the interfacial interaction mechanisms, offering valuable perspectives on the inter- and intra-molecular interactions. Further studies on weak interaction were conducted, focusing on the binding contribution of electrostatic interaction and vdW potential. DFT results confirmed the strong adsorption capacity and coordination behavior of F - ions on the cross-linked Cs-Ech, suggesting that the Ech group offers preferred adsorption sites.

Vortex-pair dynamics in three-dimensional homogeneous dipolar superfluids

The static and dynamic properties of vortices in dipolar Bose-Einstein condensates (dBECs) can be considerably modified relative to their nondipolar counterparts by the anisotropic and long-ranged nature of the dipole-dipole interaction. Working in a uniform dBEC, we analyze the structure of single vortices and the dynamics of vortex pairs, investigating the deviations from the nondipolar paradigm. For a straight vortex line, we find that the induced dipolar interaction potential is axially anisotropic when the dipole moments have a nonzero projection orthogonal to the vortex line. This results in a corresponding elongation of the vortex core along this projection as well as an anisotropic superfluid phase and enhanced compressibility in the vicinity of the vortex core. Consequently, the trajectories of like-signed vortex pairs are described by a family of elliptical and oval-like curves rather than the familiar circular orbits. Similarly for opposite-signed vortex pairs their translation speeds along the binormal are found to be dipole-interaction dependent. We expect that these findings will shed light on the underlying mechanisms of many-vortex phenomena in dBECs such as quantum turbulence, vortex reconnections, and vortex lattices. Published by the American Physical Society 2024

Silica Coating of Nickel–Iron Nanocomposite by Chemical Reduction Method

The study of magnetic nanostructures is interesting because of its applications. Some of them are the development of magnetic refrigerators, ferrofluids, drug delivery systems, fabrication of devices with giant magnetoresistance effects, and high-frequency transformers. The physical and chemical properties of metal changes due to silica coating. The interaction potential can be manipulated using surface coatings and also the particle shape can be controlled. Nanoparticles with a proper surface coating are of interest for several other applications in optoelectronic devices and in the biomedical field. Thus, developing a new synthetic route for these particles and investigating the stability of magnetic materials are of great importance. Silica coating improves the chemical stability and electrical resistivity of the material. In this study, Ni3Fe (core) nanoparticles were prepared and the silica shell for this core was synthesized. The as-prepared X-ray diffraction (XRD) patterns and 300∘C annealed sample of Ni3Fe/SiO2 shows a characteristic hump in the low angle range confirming the presence of amorphous cristobalite phase of SiO2. The size of the Ni3Fe cluster in the Ni3Fe/SiO2 composite was estimated to be 8[Formula: see text]nm and 9[Formula: see text]nm, respectively, for the as-prepared and annealed samples. Vibrating sample magnetometer (VSM) measurements show the Ni3Fe to silica ratio to be 59:41. A small decrease in the coercivity value, is probably due to morphological changes associated with the coating. Scanning electron microscope (SEM) studies of the as-prepared and annealed Ni3Fe/SiO2 powder particles are of flowerlike morphology and in agglomeration. The impedance spectra were found at room temperature for the as-prepared samples.

A novel section–section potential for short-range interactions between plane beams

We derive a novel formulation for the interaction potential between deformable fibers due to short-range fields arising from intermolecular forces. The formulation improves the existing section–section interaction potential law for in-plane beams by considering an offset between interacting cross sections. The new law is asymptotically consistent, which is particularly beneficial for computationally demanding scenarios involving short-range interactions like van der Waals and steric forces. The formulation is implemented within a framework of rotation-free Bernoulli–Euler beams utilizing the isogeometric paradigm. The improved accuracy of the novel law is confirmed through thorough numerical studies. We apply the developed formulation to investigate the complex behavior observed during peeling and pull-off of elastic fibers interacting via the Lennard–Jones potential.

Navigating the Cyborg Classroom: Telepresence Robots, Accessibility Challenges, and Inclusivity in the Classroom

Telepresence robots, designed to bridge physical distances, have unique capabilities and inherent limitations when deployed in classroom environments. This study examines these aspects, focusing on how telepresence robots facilitate or hinder classroom accessibility and inclusivity. Based on field study results from participatory observations, surveys and interviews with 22 participants, we present and catalogue the operational capabilities of telepresence robots, such as mobility and interaction potential, alongside their limitations in areas like sensory perception and social presence. Our findings reveal a nuanced landscape where telepresence robots act as both enablers and barriers in the classroom. This duality raises the question of whether these robots can be considered “disabled” in certain contexts and how this perceived disability impacts remote students’ inclusion in classroom dynamics. Finally, we present use recommendations to improve classroom experience and telepresence design.