Kinetic Studies and Mechanism of Hydrogen Peroxide Catalytic Decomposition by Cu(II) Complexes with Polyelectrolytes Derived from L-Alanine and Glycylglycine

The catalytic decomposition of hydrogen peroxide by Cu(II) complexes with polymers bearing L-alanine (PAla) and glycylglycine (PGlygly) in their side chain was studied in alkaline aqueous media. The reactions were of pseudo-first order with respect to [H2O2] and [L-Cu(II)] (L stands for PAla or PGlygly) and the reaction rate was increased with pH increase. The energies of activation for the reactions were determined at pH 8.8, in a temperature range of 293–308 K. A suitable mechanism is proposed to account for the kinetic data, which involves the Cu(II)/Cu(I) redox pair, as has been demonstrated by ESR spectroscopy. The trend in catalytic efficiency is in the order PGlygly>PAla, due to differences in modes of complexation and in the conformation of the macromolecular ligands

Novelty search for soft robotic space exploration

The use of soft robots in future space exploration is still a far-fetched idea, but an attractive one. Soft robots are inherently compliant mechanisms that are well suited for locomotion on rough terrain as often faced in extra-planetary environments. Depending on the particular application and requirements, the best shape (or body morphology) and locomotion strategy for such robots will vary substantially. Recent developments in soft robotics and evolutionary optimization showed the possibility to simultaneously evolve the morphology and locomotion strategy in simulated trials. The use of techniques such as generative encoding and neural evolution were key to these findings. In this paper, we improve further on this methodology by introducing the use of a novelty measure during the evolution process. We compare fitness search and novelty search in different gravity levels and we consistently find novelty-based search to perform as good as or better than a fitness-based search, while also delivering a greater variety of designs. We propose a combination of the two techniques using fitness-elitism in novelty search to obtain a further improvement. We then use our methodology to evolve the gait and morphology of soft robots at different gravity levels, finding a taxonomy of possible locomotion strategies that are analyzed in the context of space-exploration

SLA-mechanisms for electricity trading under volatile supply and varying criticality of demand (Extended Abstract)

The increasing adoption of renewable power generation makes volatile quantities of electricity available, the delivery of which cannot be guaranteed, if sold. However, if not sold, the electricity might need to be curtailed, thus foregoing potential profits. In this paper we adapt service level agreements (SLAs) for the future smart electricity grid, where generation will primarily depend on volatile and istributed renewable power sources, and where buyers' ability to cope with uncertainty may vary significantly. We propose a contracting framework through SLAs to allocate uncertain power generation to buyers of varying preferences. These SLAs comprise quantity, reliability and price. We define a characterization of the value degradation of tolerant and critical buyers with regards to the uncertainty of electricity delivery (generalizing the Value of Lost Load, VoLL). We consider two mechanisms (sequential second-price auction and VCG) that allocate SLAs based on buyer bids. We further study the incentive compatibility of the proposed mechanisms, and show that both mechanisms ensure that no buyer has an incentive to misreport its valuation. We experimentally compare their performance and demonstrate that VCG dominates alternative allocations, while vastly improves the efficiency of the proposed system when compared to a baseline allocation considering only the VoLL. This article lays the ground work for distributed energy trading under uncertainty, thereby contributing an essential component to the future smart grid

A multi-scale energy demand model suggests sharing market risks with intelligent energy cooperatives

In this paper, we propose a multi-scale model of energy demand that is consistent with observations at a macro scale, in our use-case standard load profiles for (residential) electric loads. We employ the model to study incentives to assume the risk of volatile market prices for intelligent energy cooperatives at different aggregation scales of energy consumption. Next to scale, we investigate the benefits of demand response, more precisely intelligent scheduling of time-shiftable electric processes, and virtual storage intraday and between days. Results show that the increasing electrification and introduction of flexibilities (electric vehicles, thermal applications, storage, etc.) is going to make market participation viable for smaller groups of consumers. Retailers may thus introduce innovative tariffs for intelligent energy cooperatives to share the risk of volatility in wholesale markets for electricity

Forecast-based mechanisms for demand response

We study mechanisms to incentivize demand response in smart energy systems. We assume agents that can respond (reduce their demand) with some probability if they prepare prior to the real-ization of the demand. Both preparation and response incur costs to agents. Previous work studies truthful mechanisms that select a minimal set of agents to prepare and respond such that a fixed demand reduction target is achieved with high probability. In this work we additionally consider the balancing responsibility of a retailer under a given demand forecast and imbalance price: The retailer is responsible to purchase additional reserve capacity at a high imbalance price to cover any excess in the demand. In this extended setting we study mechanisms that request only a subset of prepared agents to respond since the reduction target depends on the realization of the demand: We propose: (i) a sequential mechanism that in each round embeds a second-price auction and is truthful under some mild assumptions for the setting, and (ii) a truthful combinatorial mechanism that runs in polynomial time and uses VCG payments. We show that both mechanisms guarantee non-negative utility in expectation for both agents and the retailer (mechanism), and can further be used for simultaneous downward and upward flexibility. Last, we verify our theoretical findings in an empirical evaluation over a wide range of mechanism parameters

The acute effects of different high-intensity conditioning activities on sprint performance differ between sprinters of different strength and power characteristics

The purpose of the present study was to examine the effect of different conditioning activities (CAs) on short-term increase in sprint performance. In twelve male sprinters (21.1±2.6 years, 100 m performance: 11.5±0.6 s) their body composition, half squat maximum strength, 100 m sprinting and countermovement jump performances were evaluated. The performance of a 50 m sprint (splits at 10 m, 30 m and 50 m) was evaluated before and 5, 10 and 15 min after four postactivation performance enhancement CAs on different occasions: [1] 3 sets x 4 s maximum isometric half squat (IHF), [2] 3 sets x 3 consecutive countermovement jumps (cCMJs), [3] 3 repetitions x 30 m overspeed sprinting (OVSP) and [4] dynamic submaximal half squat (2 sets x 2 reps x 90% of 1-RM half squat; HSQ). Significant improvements of sprinting performance were found 10 and 15 min following the cCMJs, OVSP and HSQ’s interventions, in all distances (p.05). Significant inter-individual differences were found in the magnitude of sprint performance improvements as well as in the optimal time window (p<.05), with the stronger sprinters responding better after HSQs, while the more powerful sprinters after cCMJs and OVSPs. In conclusion, it seems that cCMJs, OVSP and HSQ can acutely increase sprinting performance after 10 min, but CA’s induced increases in sprinting performance are highly related to the strength and power characteristics of each sprinter

Synthesis and characterization of poly(amino acid methacrylate)-stabilized diblock copolymer nano-objects

Amino acids constitute one of Nature's most important building blocks. Their remarkably diverse properties (hydrophobic/hydrophilic character, charge density, chirality, reversible cross-linking etc.) dictate the structure and function of proteins. The synthesis of artificial peptides and proteins comprising main chain amino acids is of particular importance for nanomedicine. However, synthetic polymers bearing amino acid side-chains are more readily prepared and may offer desirable properties for various biomedical applications. Herein we describe an efficient route for the synthesis of poly(amino acid methacrylate)stabilized diblock copolymer nano-objects. First, either cysteine or glutathione is reacted with a commercially available methacrylate-acrylate adduct to produce the corresponding amino acid-based methacrylic monomer (CysMA or GSHMA). Well-defined water-soluble macromolecular chain transfer agents (PCysMA or PGSHMA macro-CTAs) are then prepared via RAFT polymerization, which are then chain-extended via aqueous RAFT dispersion polymerization of 2-hydroxypropyl methacrylate. In situ polymerization-induced self-assembly (PISA) occurs to produce sterically-stabilized diblock copolymer nano-objects. Although only spherical nanoparticles could be obtained when PGSHMA was used as the sole macro-CTA, either spheres, worms or vesicles can be prepared using either PCysMA macro-CTA alone or binary mixtures of poly(glycerol monomethacrylate) (PGMA) with either PCysMA or PGSHMA macro-CTAs. The worms formed soft free-standing thermo-responsive gels that undergo degelation on cooling as a result of a worm-to-sphere transition. Aqueous electrophoresis studies indicate that all three copolymer morphologies exhibit cationic character below pH 3.5 and anionic character above pH 3.5. This pH sensitivity corresponds to the known behavior of the poly(amino acid methacrylate) steric stabilizer chains