Resource access needs and capabilities as mediators of the relationship between VC firm size and syndication

Drawing from the resource-based view and transaction costs economics, we develop a theoretical framework to explain why small and large firms face different levels of resource access needs and resource access capabilities, which mediate the relationship between firm size and hybrid governance. Employing a sample of 317 venture capital firms, drawn across six European countries, we empirically assess our framework in the context of venture capital syndication. We estimate a path model using structural equation modeling and find, consistent with our theoretical framework, mediating effects of different types of resource access needs and resource access capabilities between VC firm size and syndication frequency. These findings advance the small business literature by highlighting the trade-offs that size imposes on firms that seek to manage their access to external resources through hybrid governance strategies.

Hybrid cluster state proposal for a quantum game

We propose an experimental implementation of a quantum game algorithm in a hybrid scheme combining the quantum circuit approach and the cluster state model. An economical cluster configuration is suggested to embody a quantum version of the Prisoners' Dilemma. Our proposal is shown to be within the experimental state of the art and can be realized with existing technology. The effects of relevant experimental imperfections are also carefully examined.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

Imperfect assessment and limited information preclude optimal strategies in male-male fights in the orb-weaving spider Metellina mengei

Agonistic behaviour between male orb-web spiders Metellina mengei competing for access to female webs was examined in field experiments to test the major predictions of game theory. Winners of fights were significantly larger than losers, particularly with respect to the length of the first pair of legs, which are sexually dimorphic in this species and used extensively in agonistic encounters. The size of the winning male had no influence on contest intensity or duration, and neither did relative size. However, fight intensity and duration were both positively correlated with the size of the losing male. Resident males won significantly more contests than intruders. Winning intruders were significantly larger than winning residents and it was these winning intruders that tended to produce the longer fights. Female weight and hence reproductive value had a marked influence on fight intensity and duration of fights won by the intruder but not those won by the resident. This indicates that only the resident obtains information about the female. These data are discussed with reference to the discrepancy with theory and a failure of some contestants to obtain information on resource value and relative contestant size necessary to optimize fight strategy.

An automated hybrid procedure for capturing mode-jumping in postbuckling composite stiffened structures

This paper presents a robust finite element procedure for modelling the behaviour of postbuckling structures undergoing mode-jumping. Current non-linear implicit finite element solution schemes, found in most finite element codes, are discussed and their shortcomings highlighted. A more effective strategy is presented which combines a quasi-static and a pseudo-transient routine for modelling this behaviour. The switching between these two schemes is fully automated and therefore eliminates the need for user intervention during the solution process. The quasi-static response is modelled using the are-length constraint while the pseudo-transient routine uses a modified explicit dynamic routine, which is more computationally efficient than standard implicit and explicit dynamic schemes. The strategies for switching between the quasi-static and pseudo-transient routines are presented

Local Conventions in Game Play in an Evolving Dual Social Network Framework

People usually perform economic interactions within the social setting of a small group, while they obtain relevant information from a broader source. We capture this feature with a dynamic interaction model based on two separate social networks. Individuals play a coordination game in an interaction network, while updating their strategies using information from a separate influence network through which information is disseminated. In each time period, the interaction and influence networks co-evolve, and the individuals’ strategies are updated through a modified naive learning process. We show that both network structures and players’ strategies always reach a steady state, in which players form fully connected groups and converge to local conventions. We also analyze the influence exerted by a minority group of strongly opinionated players on these outcomes.