Vibration characteristics of a cylinder partially filled with liquid with an attached elastic drain pipe

Liquid and ullage gas effects of partially filled cylinder with attached elastic drain pip

Estimating offsets for avian displacement effects of anthropogenic impacts

Biodiversity offsetting, or compensatory mitigation, is increasingly being used in temperate grassland ecosystems to compensate for unavoidable environmental damage from anthropogenic developments such as transportation infrastructure, urbanization, and energy development. Pursuit of energy independence in the United States will expand domestic energy production. Concurrent with this increased growth is increased disruption to wildlife habitats, including avian displacement from suitable breeding habitat. Recent studies at energy-extraction and energy-generation facilities have provided evidence for behavioral avoidance and thus reduced use of habitat by breeding waterfowl and grassland birds in the vicinity of energy infrastructure. To quantify and compensate for this loss in value of avian breeding habitat, it is necessary to determine a biologically based currency so that the sufficiency of offsets in terms of biological equivalent value can be obtained. We describe a method for quantifying the amount of habitat needed to provide equivalent biological value for avifauna displaced by energy and transportation infrastructure, based on the ability to define five metrics: impact distance, impact area, pre-impact density, percent displacement, and offset density. We calculate percent displacement values for breeding waterfowl and grassland birds and demonstrate the applicability of our avian-impact offset method using examples for wind and oil infrastructure. We also apply our method to an example in which the biological value of the offset habitat is similar to the impacted habitat, based on similarity in habitat type (e.g., native prairie), geographical location, land use, and landscape composition, as well as to an example in which the biological value of the offset habitat is dissimilar to the impacted habitat. We provide a worksheet that informs potential users how to apply our method to their specific developments and a framework for developing decision-support tools aimed at achieving landscape-level conservation goals

Financing SME growth in the UK: meeting the challenges after the global financial crisis

In the aftermath of the Global Financial Crisis new forms of SME finance are emerging in the place of traditional banking and equity finance sources. This Special Issue has its origins in a conference organised in June 2014 by the Centre for Enterprise and Economic Development Research (CEEDR) at Middlesex University Business School, where all but the final two papers were presented. The Conference was designed to provide a timely forum for leading academics, practitioners and policy makers to disseminate current research and practitioner knowledge exploring finance gaps and how best to address the financing needs of small high growth potential businesses

The transformation of the business angel market: empirical evidence and research implications

Business angel investing – a key source of finance for entrepreneurial businesses – is rapidly evolving from a fragmented and largely anonymous activity dominated by individuals investing on their own to one that is increasingly characterised by groups of investors investing together through managed angel groups. The implications of this change have been largely ignored by scholars. The paper examines the investment activity and operation of angel groups in Scotland to highlight the implications of this change for the nature of angel investing. It goes on to argue that this transformation challenges both the ongoing relevance of prior research on business angels and current methodological practices, and raises a set of new research questions

The evaluation criteria used by venture capitalists:evidence from a UK fund

GRAHAM BOOCOCK AND MARGARET WOODS are Lecturers in Banking and Finance, and Financial Management, respectively, at Loughborough University Business School, England. The paper examines how venture fund managers select their investee companies, by exploring the evaluation criteria and the decision-making process adopted at one United Kingdom regional venture fund (henceforth referred to as the Fund). The analysis confirms that relatively consistent evaluation criteria are applied across the industry and corroborates previous models which suggest that the venture capitalist's decision-making consists of several stages. With the benefit of access to the Fund's internal records, however, this paper adds to the current literature by differentiating the evaluation criteria used at each successive stage of the decision-making process. The paper presents a model of the Fund's activities which demonstrates that the relative importance attached to the evaluation criteria changes as applications are systematically processed. Proposals have to satsfy different criteria at each stage of the decision-making process before they receive funding. In the vast majority of cases, applications are rejected by the fund managers. In addition, the length of time taken by the fund managers in appraising propositions can lead to withdrawal of applications at an advanced stage

Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping

We present an autoencoder-based semi-supervised approach to classify perceived human emotions from walking styles obtained from videos or motion-captured data and represented as sequences of 3D poses. Given the motion on each joint in the pose at each time step extracted from 3D pose sequences, we hierarchically pool these joint motions in a bottom-up manner in the encoder, following the kinematic chains in the human body. We also constrain the latent embeddings of the encoder to contain the space of psychologically-motivated affective features underlying the gaits. We train the decoder to reconstruct the motions per joint per time step in a top-down manner from the latent embeddings. For the annotated data, we also train a classifier to map the latent embeddings to emotion labels. Our semi-supervised approach achieves a mean average precision of 0.84 on the Emotion-Gait benchmark dataset, which contains both labeled and unlabeled gaits collected from multiple sources. We outperform current state-of-art algorithms for both emotion recognition and action recognition from 3D gaits by 7%--23% on the absolute. More importantly, we improve the average precision by 10%--50% on the absolute on classes that each makes up less than 25% of the labeled part of the Emotion-Gait benchmark dataset.Comment: In proceedings of the 16th European Conference on Computer Vision, 2020. Total pages 18. Total figures 5. Total tables

Financial Markets and Online Advertising: Reevaluating the Dotcom Investment Bubble

While the dotcom period is often dismissed as a false start in the history of the web’s commercial development, it is better conceived of as highly generative of modern structures of online advertising. Soaring investment markets and the developing online advertising sector entered into a pattern of mutual reinforcement that began in 1995 and intensified until the bubble collapsed in 2000, transforming the character of the web in the process. This article sketches the contours of this generative capacity, focusing on the production of demand for online advertising services. Taking the approach of critical political economy, this narrative is contextualized as an outgrowth of broader social trends, namely the increased importance and interconnection of marketing communications, media technologies, and finance within a changing capitalism

Global trends in milk quality: implications for the Irish dairy industry

The quality of Irish agricultural product will become increasingly important with the ongoing liberalisation of international trade. This paper presents a review of the global and Irish dairy industries; considers the impact of milk quality on farm profitability, food processing and human health, examines global trends in quality; and explores several models that are successfully being used to tackle milk quality concerns. There is a growing global demand for dairy products, fuelled in part by growing consumer wealth in developing countries. Global dairy trade represents only 6.2% of global production and demand currently outstrips supply. Although the Irish dairy industry is small by global standards, approximately 85% of annual production is exported annually. It is also the world's largest producer of powdered infant formula. Milk quality has an impact on human health, milk processing and on-farm profitability. Somatic cell count (SCC) is a key measure of milk quality, with a SCC not exceeding 400,000 cells/ml (the EU milk quality standard) generally accepted as the international export standard. There have been ongoing improvements in milk quality among both established and emerging international suppliers. A number of countries have developed successful industry-led models to tackle milk quality concerns. Based on international experiences, it is likely that problems with effective translation of knowledge to practice, rather than incomplete knowledge per se, are the more important constraints to national progress towards improved milk quality