An aerodynamic load criterion for airships

A simple aerodynamic bending moment envelope is derived for conventionally shaped airships. This criterion is intended to be used, much like the Naval Architect's standard wave, for preliminary estimates of longitudinal strength requirements. It should be useful in tradeoff studies between speed, fineness ratio, block coefficient, structure weight, and other such general parameters of airship design

2D Saturable Absorbers for Fibre Lasers

© 2015.Two-dimensional (2D) nanomaterials are an emergent and promising platform for future photonic and optoelectronic applications. Here, we review recent progress demonstrating the application of 2D nanomaterials as versatile, wideband saturable absorbers for Q-switching and mode-locking fibre lasers. We focus specifically on the family of few-layer transition metal dichalcogenides, including MoS2, MoSe2 and WS2

Benchmarking the Returns to Venture

We describe a new index of the current and historical returns to venture-type capital. The conceptual basis for the index is the value of a continuously reinvested value-weighted portfolio of all venture-backed and similar pre-public companies. It provides a metric for private equity comparable to the S&P 500 for public equity. We build the index from valuations revealed in episodic transactions in the companies' shares - private placements of new rounds of equity funding, IPOs, acquisitions, and liquidations. Our approach to dealing with the episodic nature of the data is similar to the one used in constructing indexes of real-estate value from transaction data for individual properties. We have extended earlier sources of data to deal with selection bias - we tracked down unfavorable valuations that were less likely to be reported in the earlier data. We also use econometric techniques to handle the remaining selection bias. The resulting index has important uses in marking venture portfolios to market and in assessing the performance of venture investments.

Stable gauged maps

We give an introduction to moduli stacks of gauged maps satisfying a stability conditition introduced by Mundet and Schmitt, and the associated integrals giving rise to gauged Gromov-Witten invariants. We survey various applications to cohomological and K-theoretic Gromov-Witten invariants.Comment: Survey for the 2015 AMS Summer Institute on Algebraic Geometry. Split off from the more technical paper "Properness for scaled gauged maps" [arXiv:1606.01383]. There is still substantial overlap between the two papers. This version has minor correction

The Incentives to Start New Companies: Evidence from Venture Capital

The standard venture-capital contract rewards entrepreneurs only for creating successful companies that go public or are acquired on favorable terms. As a result, entrepreneurs receive no help from venture capital in avoiding the huge idiosyncratic risk of the typical venture-backed startup. Entrepreneurs earned an average of $9 million from each company that succeeded in attracting venture funding. But entrepreneurs are generally specialized in their own companies and bear the burden of the idiosyncratic risk. Entrepreneurs with a coefficient of relative risk aversion of two would be willing to sell their interests for less than$1 million at the outset rather than face that risk. The standard financial contract provides entrepreneurs capital supplied by passive investors and rewards entrepreneurs for successful outcomes. We track the division of value for a sample of the great majority of U.S. venture-funded companies over the period form 1987 through 2005. Venture capitalists received an average of $5 million in fee revenue from each company they backed. The outside investors in venture capital received a financial return substantially above that of publicly traded companies, but that the excess is mostly a reward for bearing risk. The pure excess return measured by the alpha of the Capital Asset Pricing Model is positive but may reflect only random variation.

Knowledge source preferences as determinants of strategic entrepreneurial orientation

In the knowledge intensive context, firms’ capacity to integrate external and internal sources of knowledge becomes an important competitive advantage and may distinguish entrepreneurial from conservative firms. This paper explores the proposition that differences in strategic entrepreneurial orientation (EO) across firms may be significantly determined by differences in firms’ preferences regarding knowledge sources. Our research is based on 208 firms operating in knowledge intensive industries in six Central and East European countries (CEEC). We identified three types of firms in terms of patterns of sources of knowledge: external R&D knowledge based firms, in-house knowledge based firms and value chain dependent firms. By using different proxies or different dimensions of EO, we have found that the EO is strongest in firms based on external knowledge. Firms with inhouse based knowledge have an intermediate strength of the EO, and firms dependent on value chains are the least entrepreneurially oriented. We have also found moderate support for grouping different proxies of EO into three dimensions identified in literature – innovativeness, pro-activeness and risk-taking. Value chain firms are not pro-active, have the lowest innovativeness, and are the most risk averse. External knowledge based firms are the most active in all three dimensions of EO, while inhouse knowledge based firms are in an intermediate position. Our results point to strong systemic features of entrepreneurial activities; i.e., EO is inherently different in different sub-populations of firms depending on their patterns of sources of knowledge. It seems that these patterns operate as a moderating factor between performance and the EO, which explains mixed results from the literature

Performance modelling of a multiple threshold RED mechanism for bursty and correlated Internet traffic with MMPP arrival process

Access to the large web content hosted all over the world by users of the Internet engage many hosts, routers/switches and faster links. They challenge the internet backbone to operate at its capacity to assure e±cient content access. This may result in congestion and raises concerns over various Quality of Service (QoS) issues like high delays, high packet loss and low throughput of the system for various Internet applications. Thus, there is a need to develop effective congestion control mechanisms in order to meet various Quality of Service (QoS) related performance parameters. In this paper, our emphasis is on the Active Queue Management (AQM) mechanisms, particularly Random Early Detection (RED). We propose a threshold based novel analytical model based on standard RED mechanism. Various numerical examples are presented for Internet traffic scenarios containing both the burstiness and correlation properties of the network traffic

Towards 'smart lasers': self-optimisation of an ultrafast pulse source using a genetic algorithm

Short-pulse fibre lasers are a complex dynamical system possessing a broad space of operating states that can be accessed through control of cavity parameters. Determination of target regimes is a multi-parameter global optimisation problem. Here, we report the implementation of a genetic algorithm to intelligently locate optimum parameters for stable single-pulse mode-locking in a Figure-8 fibre laser, and fully automate the system turn-on procedure. Stable ultrashort pulses are repeatably achieved by employing a compound fitness function that monitors both temporal and spectral output properties of the laser. Our method of encoding photonics expertise into an algorithm and applying machine-learning principles paves the way to self-optimising `smart' optical technologies

Genetic algorithm-based control of birefringent filtering for self-tuning, self-pulsing fiber lasers

Polarization-based filtering in fiber lasers is well-known to enable spectral tunability and a wide range of dynamical operating states. This effect is rarely exploited in practical systems, however, because optimization of cavity parameters is non-trivial and evolves due to environmental sensitivity. Here, we report a genetic algorithm-based approach, utilizing electronic control of the cavity transfer function, to autonomously achieve broad wavelength tuning and the generation of Q-switched pulses with variable repetition rate and duration. The practicalities and limitations of simultaneous spectral and temporal self-tuning from a simple fiber laser are discussed, paving the way to on-demand laser properties through algorithmic control and machine learning schemes.Comment: Accepted for Optics Letters, 12th June 201