Strategic Alliances in the Global Airline Industry

Strategic alliances are common to any industry. Their presence is felt quite significantly in the airline industry. Starting in the US in 1978 deregulation of airline industry has since brought about sea changes in functioning of the industry. This paper attempts to understand the developments and strategic alliances that have occurred in the airline industry since deregulation. These strategic alliances exist in various forms and differ widely in scope and no consensus on classification was found. The advantages and disadvantages of strategic alliances with respect to the airline industry have been discussed. It is felt that the industry is getting increasingly concentrated. However, no conclusive remarks can be made about consumer welfare.

Use of bamboo fiber in oil water separation

One of the environmental issues facing the society is the separation of oil from water in emulsions. Oily wastewater enters into the environment through many ways such as oil spill as well as from the industry. Natural fibers are a viable alternative to synthetic fibers in separating oil from the water. The oil physical characteristics and sorbents made from the fiber influences the sorption of oil onto the fiber. This work uses the naturally available bamboo fibers for separation of oil from water. Very high adsorption capacities were obtained for vegetable oil. Furthermore, recovery of oil was also tested and 90% recovery was obtained. Bamboo fiber has thus great advantage in treating oil-water mixture

Causes of Corruption:History, Geography, and Government

Corruption, which remains a serious problem in many countries, has prompted considerable research in recent years. This paper adds to the extant literature with insights on factors influencing corrupt activity. Using cross-country data for about 100 nations, the roles of national history, geography, and government are examined to see how they affect conditions for corruption, both qualitatively and quantitatively. The innovative aspects of this research include use of a wide set of historical, geographical, and governmental determinants of corruption, as well as detailed assessment of several previously considered determinants. The main issues addressed are the effects of the size and scope of government on the incidence of corruption across countries, and the significance of historical and geographic factors in corruption. Regarding the first question, the authors find the size and scope of government can significantly affect corruption. On the second, it is shown that historical institutional inertia in older countries and new rent-seeking opportunities in younger nations can encourage corruption, while certain geographic factors can mitigate corruption. The paper ends with discussion aimed at the policymaker.corruption; bribery; government size; government scope; rent-seeking; history; geography

When Hashes Met Wedges: A Distributed Algorithm for Finding High Similarity Vectors

Finding similar user pairs is a fundamental task in social networks, with numerous applications in ranking and personalization tasks such as link prediction and tie strength detection. A common manifestation of user similarity is based upon network structure: each user is represented by a vector that represents the user's network connections, where pairwise cosine similarity among these vectors defines user similarity. The predominant task for user similarity applications is to discover all similar pairs that have a pairwise cosine similarity value larger than a given threshold $\tau$. In contrast to previous work where $\tau$ is assumed to be quite close to 1, we focus on recommendation applications where $\tau$ is small, but still meaningful. The all pairs cosine similarity problem is computationally challenging on networks with billions of edges, and especially so for settings with small $\tau$. To the best of our knowledge, there is no practical solution for computing all user pairs with, say $\tau = 0.2$ on large social networks, even using the power of distributed algorithms. Our work directly addresses this challenge by introducing a new algorithm --- WHIMP --- that solves this problem efficiently in the MapReduce model. The key insight in WHIMP is to combine the "wedge-sampling" approach of Cohen-Lewis for approximate matrix multiplication with the SimHash random projection techniques of Charikar. We provide a theoretical analysis of WHIMP, proving that it has near optimal communication costs while maintaining computation cost comparable with the state of the art. We also empirically demonstrate WHIMP's scalability by computing all highly similar pairs on four massive data sets, and show that it accurately finds high similarity pairs. In particular, we note that WHIMP successfully processes the entire Twitter network, which has tens of billions of edges

Attitudes of the Youth towards Entrepreneurs and Entrepreneurship: A Cross-cultural Comparison of India and China

This study argues that social support is an important enabler in entrepreneurial activity in a country or a region. One untested assumption in policy making on entrepreneurship development has been that all regions are equally desirous of entrepreneurial activity and one policy could address issues in all regions. It was argued that societal attitudes towards entrepreneurs and entrepreneurship are important determinants for future entrepreneurial activity. These attitudes would be impacted by the family background of an individual and entrepreneurial development in the region an individual comes from. It was hypothesized that more positive attitude would be seen in (i) people form entrepreneurial backgrounds, and (ii) entrepreneurially more developed regions. These hypotheses were tested on more than 5,000 respondents in India and China. The results for family background’s influence on attitudes found strong support in both India and China. Regional development showed stronger influence on attitude in India than in China. The findings and implications for studying attitudes and policy making are discussed.

Lectin based glycoprotein analysis

Many of the biopharmaceutical therapeutics entering the market and currently in clinical trails are recombinant glycoprotein molecules, the glycan moieties of which have a significant impact on efficacy and immunogenicity. The cell culture techniques required to produce these glycoproteins often result in products that are heterogeneous with respect to glycan content. This inconsistency ultimately leads to increased production costs and restricts patient accessibility to these therapeutics. To overcome these difficulties novel analytical platforms facilitating rapid in-process monitoring and product quality control are essential. Work undertaken within the Centre for Bioanalytical Sciences (CBAS) seeks to exploit the microbial world as a source of novel biorecognition elements to produce such platforms

Diamagnetic Susceptibilities of Some Cyclic Dialkylsilylamidoximes

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Cascades: A view from Audience

Cascades on online networks have been a popular subject of study in the past decade, and there is a considerable literature on phenomena such as diffusion mechanisms, virality, cascade prediction, and peer network effects. However, a basic question has received comparatively little attention: how desirable are cascades on a social media platform from the point of view of users? While versions of this question have been considered from the perspective of the producers of cascades, any answer to this question must also take into account the effect of cascades on their audience. In this work, we seek to fill this gap by providing a consumer perspective of cascade. Users on online networks play the dual role of producers and consumers. First, we perform an empirical study of the interaction of Twitter users with retweet cascades. We measure how often users observe retweets in their home timeline, and observe a phenomenon that we term the "Impressions Paradox": the share of impressions for cascades of size k decays much slower than frequency of cascades of size k. Thus, the audience for cascades can be quite large even for rare large cascades. We also measure audience engagement with retweet cascades in comparison to non-retweeted content. Our results show that cascades often rival or exceed organic content in engagement received per impression. This result is perhaps surprising in that consumers didn't opt in to see tweets from these authors. Furthermore, although cascading content is widely popular, one would expect it to eventually reach parts of the audience that may not be interested in the content. Motivated by our findings, we posit a theoretical model that focuses on the effect of cascades on the audience. Our results on this model highlight the balance between retweeting as a high-quality content selection mechanism and the role of network users in filtering irrelevant content