Annual Report: 2013

I submit herewith the annual reports from the Agricultural and Forestry Experiment Station, School of Natural Resources and Agricultural Sciences, University of Alaska Fairbanks, for the period ending December 31, 2013. This is done in accordance with an act of Congress, approved March 2, 1887, entitled, “An act to establish agricultural experiment stations, in connection with the agricultural college established in the several states under the provisions of an act approved July 2, 1862, and under the acts supplementary thereto,” and also of the act of the Alaska Territorial Legislature, approved March 12, 1935, accepting the provisions of the act of Congress. The research reports are organized according to our strategic plan and by broad subject, focusing on geography, high-latitude agriculture, forest sciences, and the interaction of humans and the environment. Research conducted by our graduate and undergraduate students plays an important role in these grants and the impact they make on Alaska.Financial Statement -- Funding & Grants -- Students -- Research at SNRAS & AFES -- Publications -- Facult

Corporate competition: A self-organized network

A substantial number of studies have extended the work on universal properties in physical systems to complex networks in social, biological, and technological systems. In this paper, we present a complex networks perspective on interfirm organizational networks by mapping, analyzing and modeling the spatial structure of a large interfirm competition network across a variety of sectors and industries within the United States. We propose two micro-dynamic models that are able to reproduce empirically observed characteristics of competition networks as a natural outcome of a minimal set of general mechanisms governing the formation of competition networks. Both models, which utilize different approaches yet apply common principles to network formation give comparable results. There is an asymmetry between companies that are considered competitors, and companies that consider others as their competitors. All companies only consider a small number of other companies as competitors; however, there are a few companies that are considered as competitors by many others. Geographically, the density of corporate headquarters strongly correlates with local population density, and the probability two firms are competitors declines with geographic distance. We construct these properties by growing a corporate network with competitive links using random incorporations modulated by population density and geographic distance. Our new analysis, methodology and empirical results are relevant to various phenomena of social and market behavior, and have implications to research fields such as economic geography, economic sociology, and regional economic development.Organizational networks; Interfirm competition; Economic geography; Social networks; Spatial networks; Network dynamics; Firm size dynamics

Intense, ultrashort light and dense, hot matter

This article presents an overview of the physics and applications of the interaction of high intensity laser light with matter. It traces the crucial advances that have occurred over the past few decades in laser technology and nonlinear optics and then discusses physical phenomena that occur in intense laser fields and their modeling. After a description of the basic phenomena like multiphoton and tunneling ionization, the physics of plasma formed in dense matter is presented. Specific phenomena are chosen for illustration of the scientific and technological possibilities - simulation of astrophysical phenomena, relativistic nonlinear optics, laser wakefield acceleration, laser fusion, ultrafast real time X-ray diffraction, application of the particle beams produced from the plasma for medical therapies etc. A survey of the Indian activities in this research area appears at the end

Activity archetypes in question-and-answer (Q8A) websites—A study of 50 Stack Exchange instances

Millions of users on the Internet discuss a variety of topics on Question-and-Answer (Q&A) instances. However, not all instances and topics receive the same amount of attention, as some thrive and achieve self-sustaining levels of activity, while others fail to attract users and either never grow beyond being a small niche community or become inactive. Hence, it is imperative to not only better understand but also to distill deciding factors and rules that define and govern sustainable Q&A instances. We aim to empower community managers with quantitative methods for them to better understand, control and foster their communities, and thus contribute to making the Web a more efficient place to exchange information. To that end, we extract, model and cluster user activity-based time series from $50$ randomly selected Q&A instances from the Stack Exchange network to characterize user behavior. We find four distinct types of user activity temporal patterns, which vary primarily according to the users' activity frequency. Finally, by breaking down total activity in our 50 Q&A instances by the previously identified user activity profiles, we classify those 50 Q&A instances into three different activity profiles. Our parsimonious categorization of Q&A instances aligns with the stage of development and maturity of the underlying communities, and can potentially help operators of such instances: We not only quantitatively assess progress of Q&A instances, but we also derive practical implications for optimizing Q&A community building efforts, as we e.g. recommend which user types to focus on at different developmental stages of a Q&A community

Financial cycles, credit networks and macroeconomic fluctuations: multi-scale stochastic models and wavelet analysis

This project focuses on the macroeconomics of financial cycles. Usually defined in terms of self-reinforcing interactions between perceptions of value and risk, attitudes towards risk and financing constraints, which translate into booms followed by bust, the recent empirical literature has recurred to two approaches \u2013 turning point analysis and frequency-based filters - applied to measures of credit and asset prices to pose a number of stylized facts. First, financial cycles tend to display a greater amplitude and a lower frequency in comparison to business cycles, with peaks associated with systemic crises. Second, financial cycles depend on policy regimes and on the pace of financial innovations, leading to a wide cross-country heterogeneity and a time-varying degree of global synchronization. The latter point is clearly related to the structural transformations occurred in financial systems over the last three decades, like the cumulative integration of traditional banking with capital market developments and the increasing degree of interconnections among financial institutions. However, to date very little is known about determinants and mechanisms behind financial cycles, and on how they interact with business cycles and medium-to-long-run macroeconomic performance. In this project we plan to research along three dimensions: i) measurement issues, in order to provide a comprehensive assessment of the evolution of co-movements between financial and real variables across a sample of financial developed countries, both over time and at different frequencies; ii) theoretical issues, aimed at exploring under what circumstances the network of interconnections among financial intermediaries and between intermediaries and non-financial borrowers might evolve cyclically, contributing this way to regulate the incentives agents have in taking risks, and to set the importance of credit and financial frictions in accounting for time-varying misallocations of resources; iii) policy issues, given the role assigned by international supervisory bodies to a proper characterization and knowledge of the financial cycle as a prerequisite for the macro-prudential regulation of banks, and the scope of monetary policy in promoting financial stability in addition to the typical mandate of price stability. Our task requires the employment of a new approach to macroeconomic analysis, diverse analytical tools and one unifying economic principle. As regards the latter, our focal point is the notion of risk externalities, across financial institutions and between the financial sector and the real economy. The set of tools we plan to employ spans from wavelets methods to multi-scale models in continuous time, and from strategic network formation to agent-based computational techniques. All these tools are instrumental in building and estimating macroeconomic models characterized by interrelated markets operating at different time scales