Dynamics between patent latent variables and patent price

This paper focuses on studying the relationship between patent latent variables and patent price. From the existing literature, seven patent latent variables, namely age, generality, originality, foreign filings, technology field, forward citations, and backward citations were identified as having an influence on patent value. We used Ocean Tomo's patent auction price data in this study. We transformed the price and the predictor variables (excluding the dummy variables) to its logarithmic value. The OLS estimates revealed that forward citations and foreign filings were positively correlated to price. Both the variables jointly explained 14.79% of the variance in patent pricing. We did not find sufficient evidence to come up with any definite conclusions on the relationship between price and the variables such as age, technology field, generality, backward citations and originality. The Heckman two-stage sample selection model was used to test for selection bias. (C) 2011 Elsevier Ltd. All rights reserved.

Reservoir Operation with Fuzzy State Variables for Irrigation of Multiple Crops

This paper presents the development and application of a stochastic dynamic programming model with fuzzy state variables for irrigation of multiple crops. A fuzzy stochastic dynamic programming (FSDP) model is developed in which the reservoir storage and soil moisture of the crops are considered as fuzzy numbers, and the reservoir inflow is considered as a stochastic variable. The model is formulated with an objective of minimizing crop yield deficits, resulting in optimal water allocations to the crops by maintaining storage continuity and soil moisture balance. The standard fuzzy arithmetic method is used to solve all arithmetic equations with fuzzy numbers, and the fuzzy ranking method is used to compare two or more fuzzy numbers. The reservoir operation model is integrated with a daily-based water allocation model, which results in daily temporal variations of allocated water, soil moisture, and crop deficits. A case study of an existing Bhadra reservoir in Karnataka, India, is chosen for the model application. The FSDP is a more realistic model because it considers the uncertainty in discretization of state variables. The results obtained using the FSDP model are found to be more acceptable for the case study than those of the classical stochastic dynamic model and the standard operating model, in terms of 10-day releases from the reservoir and evapotranspiration deficit. (C) 2015 American Society of Civil Engineers.

Cybernetic Modeling Revisited: A Method for Inferring the Cybernetic Variables u(i) from Experimental Data

The cybernetic modeling framework for the growth of microorganisms provides for an elegant methodology to account for the unknown regulatory phenomena through the use of cybernetic variables for enzyme induction and activity. In this paper, we revisit the assumption of limited resources for enzyme induction (Sigma u(i) = 1) used in the cybernetic modeling framework by presenting a methodology for inferring the individual cybernetic variables u(i) from experimental data. We use this methodology to infer u(i) during the simultaneous consumption of glycerol and lactose by Escherichia coli and then model the fitness trade-offs involved in the recently discovered predictive regulation strategy of microorganisms.