Key influences on motivations for utility cycling (cycling for transport to and from places)

Issue addressed: 

A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model

Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP.

Oral treatment with Cu(II)(atsm) increases mutant SOD1 in vivo but protects motor neurons and improves the phenotype of a transgenic mouse model of amyotrophic lateral sclerosis

Mutations in the metallo-protein Cu/Zn-superoxide dismutase (SOD1) cause amyotrophic lateral sclerosis (ALS) in humans and an expression level-dependent phenotype in transgenic rodents. We show that oral treatment with the therapeutic agent diacetyl-bis(4-methylthiosemicarbazonato)copper(II) [Cu(II)(atsm)] increased the concentration of mutant SOD1 (SOD1G37R) in ALS model mice, but paradoxically improved locomotor function and survival of the mice. To determine why the mice with increased levels of mutant SOD1 had an improved phenotype, we analyzed tissues by mass spectrometry. These analyses revealed most SOD1 in the spinal cord tissue of the SOD1G37R mice was Cu deficient. Treating with Cu(II)(atsm) decreased the pool of Cu-deficient SOD1 and increased the pool of fully metallated (holo) SOD1. Tracking isotopically enriched (65)Cu(II)(atsm) confirmed the increase in holo-SOD1 involved transfer of Cu from Cu(II)(atsm) to SOD1, suggesting the improved locomotor function and survival of the Cu(II)(atsm)-treated SOD1G37R mice involved, at least in part, the ability of the compound to improve the Cu content of the mutant SOD1. This was supported by improved survival of SOD1G37R mice that expressed the human gene for the Cu uptake protein CTR1. Improving the metal content of mutant SOD1 in vivo with Cu(II)(atsm) did not decrease levels of misfolded SOD1. These outcomes indicate the metal content of SOD1 may be a greater determinant of the toxicity of the protein in mutant SOD1-associated forms of ALS than the mutations themselves. Improving the metal content of SOD1 therefore represents a valid therapeutic strategy for treating ALS caused by SOD1.

A new model to imitate the foraging behavior of Physarum polycephalum on a nutrient-poor substrate

Researches on Physarum polycephalum show that methods inspired by the primitive unicellular organism can construct an efficient network and solve some complex problems in graph theory. Current models simulating the intelligent behavior of Physarum are mainly based on Hagen-Poiseuille Law and Kirchhoff Law, reaction-diffusion, Cellular Automaton and multi-agent approach. In this paper, based on an assumption that the plasmodium of Physarum forages for food along the gradient of chemo-attractants on a nutrient-poor substrate, a new model is proposed to imitate its intelligent foraging behavior. The key point of the model is that the growth of Physarum is determined by the simple particle concentration field relating the distance to food source and the shape of food source on a nutrient-poor substrate. To verify this model, numerical experiments are conducted according to Adamatzky[U+05F3]s experiment. Results in spanning tree construction by this model are almost the same as those of Physarum and Oregonator model. The proposed model can also imitate Physarum to avoid repellents. Furthermore, the Euclidean Spanning tree built by this model is similar to its corresponding Minimal Euclidean Spanning tree.

Polymer architecture effect on sodium ion transport in PSTFSI-based ionomers: a molecular dynamics study

In this study, we investigated the effect of polymer architecture on the ion dynamics and local structure to understand the factors that might lead to the design of highly conductive and mechanically robust polyelectrolytes. Molecular dynamic simulations were undertaken on the sodium poly[(4-styrenesulfonyl) (trifluoromethanesulfonyl) imide] P(STFSINa) homopolymer and its copolymers with either ether or styrene spacer groups to investigate the spacer length and polarity dependence of Na-ion transport. Using a scaled charge model, we observed a continuous ion aggregate network in the homopolymer, which facilitates the fast ion dynamics despite the rigid polymer matrix. The longest spacer groups disrupt this percolating ionic network differently, with the ether group being more disruptive than the styrene group, and leading to more discrete ionic aggregates. The copolymer with the ether spacer was also found to result in an alternative Na-ion diffusion mechanism.