Realizability of Iso-g2g_2 Processes via Effective Pair Interactions

An outstanding problem in statistical mechanics is the determination of whether prescribed functional forms of the pair correlation function $g_2(r)$ [or equivalently, structure factor $S(k)$] at some number density $\rho$ can be achieved by $d$-dimensional many-body systems. The Zhang-Torquato conjecture states that any realizable set of pair statistics, whether from a nonequilibrium or equilibrium system, can be achieved by equilibrium systems involving up to two-body interactions. In light of this conjecture, we study the realizability problem of the nonequilibrium iso-$g_2$ process, i.e., the determination of density-dependent effective potentials that yield equilibrium states in which $g_2$ remains invariant for a positive range of densities. Using a precise inverse methodology that determines effective potentials that match hypothesized functional forms of $g_2(r)$ for all $r$ and $S(k)$ for all $k$, we show that the unit-step function $g_2$, which is the zero-density limit of the hard-sphere potential, is remarkably numerically realizable up to the packing fraction $\phi=0.49$ for $d=1$. For $d=2$ and 3, it is realizable up to the maximum ``terminal'' packing fraction $\phi_c=1/2^d$, at which the systems are hyperuniform, implying that the explicitly known necessary conditions for realizability are sufficient up through $\phi_c$. For $\phi$ near but below $\phi_c$, the large-$r$ behaviors of the effective potentials are given exactly by the functional forms $\exp[-\kappa(\phi) r]$ for $d=1$, $r^{-1/2}\exp[-\kappa(\phi) r]$ for $d=2$, and $r^{-1}\exp[-\kappa(\phi) r]$ (Yukawa form) for $d=3$, where $\kappa^{-1}(\phi)$ is a screening length, and for $\phi=\phi_c$, the potentials at large $r$ are given by the pure Coulomb forms in the respective dimensions, as predicted by Torquato and Stillinger [\textit{Phys. Rev. E}, 68, 041113 1-25 (2003)]

Multi-behaviors coordination controller design with enzymatic numerical P systems for robots

Membrane computing models are parallel and distributed natural computing models. These models are often referred to as P systems. This paper proposes a novel multi-behaviors coordination controller model using enzymatic numerical P systems for autonomous mobile robots navigation in unknown environments. An environment classifier is constructed to identify different environment patterns in the maze-like environment and the multi-behavior coordination controller is constructed to coordinate the behaviors of the robots in different environments. Eleven sensory prototypes of local environments are presented to design the environment classifier, which needs to memorize only rough information , for solving the problems of poor obstacle clearance and sensor noise. A switching control strategy and multi-behaviors coordinator are developed without detailed environmental knowledge and heavy computation burden, for avoiding the local minimum traps or oscillation problems and adapt to the unknown environments. Also, a serial behaviors control law is constructed on the basis of Lyapunov stability theory aiming at the specialized environment, for realizing stable navigation and avoiding actuator saturation. Moreover, both environment classifier and multi-behavior coordination controller are amenable to the addition of new environment models or new behaviors due to the modularity of the hierarchical architecture of P systems. The simulation of wheeled mobile robots shows the effectiveness of this approach

Application of Fuzzy Reasoning Spiking Neural P Systems to Fault Diagnosis

This paper discusses the application of fuzzy reasoning spiking neural P systems with trapezoidal fuzzy numbers (tFRSN P systems) to fault diagnosis of power systems, where a matrix-based fuzzy reasoning algorithm based on the dynamic firing mechanism of neurons is used to develop the inference ability of tFRSN P systems from classical reasoning to fuzzy reasoning. Some case studies show the effectiveness of the presented method. We also briefly draw comparisons between the presented method and several main fault diagnosis approaches from the perspectives of knowledge representation and inference process

A review in rational design of graphene toward advanced Li–S batteries

For lithium–sulfur (Li–S) batteries, the problems of polysulfides shuttle effect, slow dynamics of sulfur species and growth of lithium dendrite during charge/discharge processes have greatly impeded its practical development. Of core importance to advance the performances of Li–S batteries lies in the selection and design of novel materials with strong polysulfides adsorption ability and enhanced redox electrocatalytic behavior. Graphene, affording high electrical conductivity, superior carrier mobility, and large surface area, has presented great potentials in improving the performances of Li–S cells. However, the properties of intrinsic graphene are far enough to achieve the multiple management toward electrochemical catalysis of energy storage systems. In addition, a general and objective understanding of its role in Li–S systems is still lacking. Along this line, we summarize the design routes from three aspects, including defect engineering, dimension adjustment, and heterostructure modulation, to perfect the graphene properties. Thus-synthesized graphene materials are explored as multifunctional electrocatalysts targeting high-efficiency and long-lifespan Li–S batteries, based on which the regulating role of graphene is comprehensively analyzed. This project provides a perspective on the effective engineering management of graphene materials to boost Li–S chemistry, meanwhile promote the practical application process for graphene materials

A Modified Membrane-Inspired Algorithm Based on Particle Swarm Optimization for Mobile Robot Path Planning

To solve the multi-objective mobile robot path planning in a dangerous environment with dynamic obstacles, this paper proposes a modified membraneinspired algorithm based on particle swarm optimization (mMPSO), which combines membrane systems with particle swarm optimization. In mMPSO, a dynamic double one-level membrane structure is introduced to arrange the particles with various dimensions and perform the communications between particles in different membranes; a point repair algorithm is presented to change an infeasible path into a feasible path; a smoothness algorithm is proposed to remove the redundant information of a feasible path; inspired by the idea of tightening the fishing line, a moving direction adjustment for each node of a path is introduced to enhance the algorithm performance. Extensive experiments conducted in different environments with three kinds of grid models and five kinds of obstacles show the effectiveness and practicality of mMPSO

A small molecule agonist of EphA2 receptor tyrosine kinase inhibits tumor cell migration in vitro and prostate cancer metastasis in vivo

10.1371/journal.pone.0042120PLoS ONE78

Genome Sequencing of Sulfolobus sp. A20 from Costa Rica and Comparative Analyses of the Putative Pathways of Carbon, Nitrogen, and Sulfur Metabolism in Various Sulfolobus Strains

The genome of Sulfolobus sp. A20 isolated from a hot spring in Costa Rica was sequenced. This circular genome of the strain is 2,688,317 bp in size and 34.8% in G+C content, and contains 2591 open reading frames (ORFs). Strain A20 shares ~95.6% identity at the 16S rRNA gene sequence level and <30% DNA-DNA hybridization (DDH) values with the most closely related known Sulfolobus species (i.e., Sulfolobus islandicus and Sulfolobus solfataricus), suggesting that it represents a novel Sulfolobus species. Comparison of the genome of strain A20 with those of the type strains of S. solfataricus, Sulfolobus acidocaldarius, S. islandicus, and Sulfolobus tokodaii, which were isolated from geographically separated areas, identified 1801 genes conserved among all Sulfolobus species analyzed (core genes). Comparative genome analyses show that central carbon metabolism in Sulfolobus is highly conserved, and enzymes involved in the Entner-Doudoroff pathway, the tricarboxylic acid cycle and the CO2 fixation pathways are predominantly encoded by the core genes. All Sulfolobus species encode genes required for the conversion of ammonium into glutamate/glutamine. Some Sulfolobus strains have gained the ability to utilize additional nitrogen source such as nitrate (i.e., S. islandicus strain REY15A, LAL14/1, M14.25, and M16.27) or urea (i.e., S. islandicus HEV10/4, S. tokodaii strain7, and S. metallicus DSM 6482). The strategies for sulfur metabolism are most diverse and least understood. S. tokodaii encodes sulfur oxygenase/reductase (SOR), whereas both S. islandicus and S. solfataricus contain genes for sulfur reductase (SRE). However, neither SOR nor SRE genes exist in the genome of strain A20, raising the possibility that an unknown pathway for the utilization of elemental sulfur may be present in the strain. The ability of Sulfolobus to utilize nitrate or sulfur is encoded by a gene cluster flanked by IS elements or their remnants. These clusters appear to have become fixed at a specific genomic site in some strains and lost in other strains during the course of evolution. The versatility in nitrogen and sulfur metabolism may represent adaptation of Sulfolobus to thriving in different habitats.Fundación Nacional de Ciencias Naturales de China/[31130003]/NSFC/ChinaUniversidad de Costa Rica/[VI 801–B0–530]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Biología Celular y Molecular (CIBCM