CONSUMER PREFERENCE AND DEMAND FOR ORGANIC FOOD: EVIDENCE FROM A VERMONT SURVEY

While organic farming has been identified as an effective way to improve food safety and environment quality, the adoption of organic production and processing is highly determined by the market demand for organic food products. To assess the market potential for organic apples and milk, a conjoint analysis is conducted in the state of Vermont to examine consumer evaluation of major product attributes and their tradeoffs. Results suggest that there is likely a significant niche market for organic apples and milk and many consumers, especially people who have purchased organic food products, are willing to pay more for organic apples and milk produced locally and certified by NOFA.Environmental Economics and Policy, Food Consumption/Nutrition/Food Safety,

Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework

In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design - the Wholesale Power Market Platform (WPMP) ï¾– for common adoption by all U.S. wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, and the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. Annotated pointers to related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/AMESMarketHome.htm

Testing financial and real market operations in restructured electricity systems: four theoretical and empirical studies

To facilitate the U.S. wholesale electric power restructuring process and promote competitive market outcomes, in April 2003 the U.S. Federal Energy Regulatory Commission (FERC) proposed a complicated market design called the Wholesale Power Market Platform (WPMP) for common adoption by all U.S. wholesale power markets. Despite the fact that versions of the WPMP have been widely implemented in many states, strong opposition to the WPMP persists among some industry stakeholders due largely to a perceived lack of adequate performance testing. In this dissertation, I apply analytical, statistical and agent-based computational simulation tools to analyze and test financial and real power market operations under the current WPMP design. The overall dissertation objective is to better understand how and to what extent the WPMP design facilitates to produce orderly, fair and efficient market outcomes. Four related studies have been undertaken to address four different issues at four different levels. Specifically, my first paper is a theoretical study of financial transmission right (FTR) markets. My second paper is an empirical study on the Midwest FTR market using statistical estimation tools. My third paper is an agent-based computational wholesale power market simulation study for systematic market design tests and market structure analyses. And my fourth paper is an optimization study in which I develop a Java-based DC OPF solver

Testing Institutional Arrangements Via Agent-Based Modeling: A U.S. Electricity Market Example

Many critical goods and services in modern-day economies are produced and distributed through complex institutional arrangements. Agent-based computational economics (ACE) modeling tools are capable of handling this degree of complexity. In concrete support of this claim, this study presents an ACE test bed designed to permit the exploratory study of restructured U.S. wholesale power markets with transmission grid congestion managed by locational marginal prices (LMPs). Illustrative findings are presented showing how spatial LMP cross-correlation patterns vary systematically in response to changes in the price responsiveness of wholesale power demand when wholesale power sellers have learning capabilities. These findings highlight several distinctive features of ACE modeling: namely, an emphasis on process rather than on equilibrium; an ability to capture complicated structural, institutional, and behavioral real-world aspects (micro-validation); and an ability to study the effects of changes in these aspects on spatial and temporal outcome distributions.Institutional Design; agent-based computational economics; U.S. Electricity Market; Locational marginal pricing; Spatial Cross-Correlations; AMES Test Bed

Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets

This study uses an agent-based test bed ("AMES") to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/AMESMarketHome.htmRestructured wholesale power markets; multi-agent learning; demand-bid price sensitivity; AMES Wholesale Power Market Test Bed; agent-based modeling; locational marginal prices (LMPs); LMP separation; LMP volatility; supply-offer price caps

U.S. Financial Transmission Rights: Theory and Practice

This paper reviews both theoretical and empirical studies of financial transmission rights (FTRs) in the major U.S. wholesale power markets. Although the current literature hold more negative views about FTRs, this paper presents a simple illustrative 2-stage model to study the competitive behaviors of electricity generators and load serving entities (LSEs) and analyzes the welfare effects of FTRs in the restructuring U.S. wholesale power market framework. The analysis focuses on a competitive two-node electricity network model where there is one generator and one LSE in each node with linear marginal cost and demand function, supervised by an independent system operator (ISO). In the first-stage of modelling, a no-rights benchmark model is developed to solve for the optimal quantity of power production and consumption and derive the locational marginal price for each node, which serve as the building blocks to solve for the optimal FTR hedge positions in the second-stage model. Once a stochastic parameter shock is introduced, the second-stage model shows that the acquisition of optimal FTRs by the risk averse generators and LSEs increases and in general strictly increases the social welfare compared with the case where there is no FTRs available. This result provides a counterexample to the somewhat negative views about FTRs held by other economists in the literature and provides some economic explanations to the fact that FTRs are widely adopted as a financial hedge instrument in the major U.S. wholesale power markets.financial transmission rights; locational marginal price; security-constrained economic dispatch; independent system operator; congestion rent

Permeability of Concrete with Recycled Concrete Aggregate and Pozzolanic Materials under Stress.

The research reported herein studied the permeability of concrete containing recycled-concrete aggregate (RA), superfine phosphorous slag (PHS), and ground granulated blast-furnace slag (GGBS) with and without stress. Test results showed that the chloride diffusion coefficient of RA concrete (RAC) without external loads decreased with time, and the permeability of RAC is much lower than that of the reference concrete due to the on-going hydration and the pozzolanic reaction provided by the PHS and GGBS additives in the RAC mixture. The permeability of chloride under flexural load is much more sensitive than that under compressive load due to the differences in porosity and cracking pattern. At low compressive stress levels, the permeability of chloride decreased by the closing of pores and microcracks within RAC specimens. However, in a relatively short time the chloride diffusion coefficient and the chloride content increased rapidly with the increase of compressive stress when it exceeded a threshold stress level of approximate 35% of the ultimate compressive strength. Under flexural stress, the chloride transport capability increased with the increase of stress level and time. At high compressive and flexural stress levels, creep had a significant effect on the permeability of chloride in the RAC specimens due to the damage from the nucleation and propagation of microcracks over time. It is apparent that mortar cracking has more of a significant effect on the chloride transport in concrete than cracking in the interfacial transition zone (ITZ)

RFWD3 acts as a tumor promotor in the development and progression of bladder cancer

Background. Bladder cancer is one of the most commonly diagnosed malignancies of the urinary system with relatively poor prognosis and insufficient treatment strategies. RFWD3 is an E3 ligase whose function is rarely investigated in malignant tumors. Methods. A tissue microarray was used for evaluating RFWD3 expression in clinical samples and its correlation with tumor characteristics and patients’ prognosis. RFWD3 knockdown and overexpression cell models were constructed for conducting loss-of-function and gain-of-function assays. qPCR and western blotting were used for detecting mRNA and protein levels of RFWD3, respectively. MTT assay, colony formation assay, flow cytometry, wound-healing assay and transwell assay were carried out to demonstrate the change of cell phenotypes upon RFWD3 knockdown. Results. RFWD3 expression was relatively higher in bladder cancer tissues than in normal tissues, which is correlated with higher N stage and poorer prognosis of patients. Knockdown of RFWD3 in bladder cancer cells significantly inhibited cell proliferation, colony formation, promote cell apoptosis and restrained cell migration. Overexpression of RFWD3 induced the opposite effects. Conclusions. It was illustrated that RFWD3 possesses excellent tumor-promoting ability in bladder cancer. Accordingly, RFWD3 may be a promising therapeutic target in the targeted therapy of bladder cancer, which is worth further research

Discovery of Points of Interest with Different Granularities for Tour Recommendation Using a City Adaptive Clustering Framework

Increasing demand for personalized tours for tourists travel in an urban area motivates more attention to points of interest (POI) and tour recommendation services. Recently, the granularity of POI has been discussed to provide more detailed information for tour planning, which supports both inside and outside routes that would improve tourists' travel experience. Such tour recommendation systems require a predefined POI database with different granularities, but existing POI discovery methods do not consider the granularity of POI well and treat all POIs as the same scale. On the other hand, the parameters also need to be tuned for different cities, which is not a trivial process. To this end, we propose a city adaptive clustering framework for discovering POIs with different granularities in this article. Our proposed method takes advantage of two clustering algorithms and is adaptive to different cities due to automatic identification of suitable parameters for different datasets. Experiments on two real-world social image datasets reveal the effectiveness of our proposed framework. Finally, the discovered POIs with two levels of granularity are successfully applied on inner and outside tour planning