The Adoption and Disadoption of Recombinant Bovine Somatotropin in the U.S. Dairy Industry

The use of recombinant bovine somatotropin (rbST) has been a source of much controversy ever since its commercial introduction in 1993. In spite of initial predictions that it would revolutionize the dairy industry, the reality is that more and more producers are choosing to discontinue using rbST. This paper contributes to the existing literature by addressing the disadoption decision. Using data from a nationally representative survey of U.S. dairy producers, this paper examines the reasons dairy producers have disadopted rbST and identifies the key variables that are correlated with adoption and disadoption. The results show that the use of complementary dairy technologies is associated with a higher probability of adopting rbST, a higher intensity of adoption and a lower probability of disadopting rbST.Livestock Production/Industries,

Technology Adoption and Product Differentiation: Market-Level Effects

The focus of the microeconomic technology adoption literature has been on the adoption and diffusion of new innovations: who adopts, and when they adopt. Implicit in the literature is that consumers will embrace the product that results from the use of the new technology. If producers have reason to believe that adopting a new technology may lead consumers to perceive differentiated products, then the decision of whether or not to adopt needs to consider not only the effectiveness of the new technology but also the consumer response to it. That is, producers have to incorporate the impact of consumer-driven market-level effects into their technology choice decisions. In these situations, producers considering the adoption of a new agricultural biotechnology have a more complex learning problem than the technology adoption literature generally addresses, because producers need to consider the interaction of demand and supply effects from the adoption of any new technology. We motivate our analysis with the case of recombinant bovine somatotropin (rbST). In order to address some of these issues, we construct an analytical model of technology adoption that considers a market with differentiated goods. We develop a multi-period economic model of a representative farmer’s technology choice decision and integrate it into a market-level analysis that links the industry’s use of the technology to the structure of consumer demand. The focus of the microeconomic technology adoption literature has been on the adoption and diffusion of new innovations: who adopts, and when they adopt. Implicit in the literature is that consumers will embrace the product that results from the use of the new technology. If producers have reason to believe that adopting a new technology may lead consumers to perceive differentiated products, then the decision of whether or not to adopt needs to consider not only the effectiveness of the new technology but also the consumer response to it. That is, producers have to incorporate the impact of consumer-driven market-level effects into their technology choice decisions. In these situations, producers considering the adoption of a new agricultural biotechnology have a more complex learning problem than the technology adoption literature generally addresses, because producers need to consider the interaction of demand and supply effects from the adoption of any new technology. We motivate our analysis with the case of recombinant bovine somatotropin (rbST). In order to address some of these issues, we construct an analytical model of technology adoption that considers a market with differentiated goods. We develop a multi-period economic model of a representative farmer’s technology choice decision and integrate it into a market-level analysis that links the industry’s use of the technology to the structure of consumer demand.Marketing, Research and Development/Tech Change/Emerging Technologies,

Fabrication and functionalization of PCB gold electrodes suitable for DNA-based electrochemical sensing

The request of high specificity and selectivity sensors suitable for mass production is a constant demand in medical research. For applications in point-of-care diagnostics and therapy, there is a high demand for low cost and rapid sensing platforms. This paper describes the fabrication and functionalization of gold electrodes arrays for the detection of deoxyribonucleic acid (DNA) in printed circuit board (PCB) technology. The process can be implemented to produce efficiently a large number of biosensors. We report an electrolytic plating procedure to fabricate low-density gold microarrays on PCB suitable for electrochemical DNA detection in research fields such as cancer diagnostics or pharmacogenetics, where biosensors are usually targeted to detect a small number of genes. PCB technology allows producing high precision, fast and low cost microelectrodes. The surface of the microarray is functionalized with self-assembled monolayers of mercaptoundodecanoic acid or thiolated DNA. The PCB microarray is tested by cyclic voltammetry in presence of 5 mM of the redox probe K3Fe(CN6) in 0.1 M KCl. The voltammograms prove the correct immobilization of both the alkanethiol systems. The sensor is tested for detecting relevant markers for breast cancer. Results for 5 nM of the target TACSTD1 against the complementary TACSTD1 and non-complementary GRP, MYC, SCGB2A1, SCGB2A2, TOP2A probes show a remarkable detection limit of 0.05 nM and a high specificity

Accurately Estimating the State of a Geophysical System with Sparse Observations: Predicting the Weather

Utilizing the information in observations of a complex system to make accurate predictions through a quantitative model when observations are completed at time $T$, requires an accurate estimate of the full state of the model at time $T$. When the number of measurements $L$ at each observation time within the observation window is larger than a sufficient minimum value $L_s$, the impediments in the estimation procedure are removed. As the number of available observations is typically such that $L \ll L_s$, additional information from the observations must be presented to the model. We show how, using the time delays of the measurements at each observation time, one can augment the information transferred from the data to the model, removing the impediments to accurate estimation and permitting dependable prediction. We do this in a core geophysical fluid dynamics model, the shallow water equations, at the heart of numerical weather prediction. The method is quite general, however, and can be utilized in the analysis of a broad spectrum of complex systems where measurements are sparse. When the model of the complex system has errors, the method still enables accurate estimation of the state of the model and thus evaluation of the model errors in a manner separated from uncertainties in the data assimilation procedure

Heavy metal bioaccumulation and biomarkers of oxidative stress in the wild African tiger frog, Hoplobatrachus occipitalis

Human activities can have dramatic effects on animal populations around urban areas with heavy metal contamination being a primary cause of harm. Amphibians, as residents of aquatic systems and with their semi-permeable skin are especially susceptible to heavy metal contamination. To better understand the effect of heavy metals on Wild African Tiger frogs (Hoplobatrachus occipitalis) and the resulting production of oxidative stress enzymes, the concentrations of the heavy metals, cadmium (Cd), copper (Cu), iron (Fe), zinc (Zn), lead (Pb) and nickel (Ni) were investigated in the tissues of H. occipitalis as well as in water and sediment samples collected from five different locations in Lagos State, Nigeria. The activities of superoxide dismutase (SOD), reduced glutathione (GSH) and level of lipid peroxidation product, malondialdehyde (MDA) were analyzed in the liver of the sampled frogs. Most measured physicochemical characteristics of the water varied significantly across the sampling locations (P<0.05). The levels of metals (mg/kg dry weight) in muscle tissues also varied significantly across the locations (P<0.05) and ranged as follows: Cd: 0.21-5.03, Cu: 0.74-13.40, Fe: 3.19-109.10, Zn: 3.70-120.20, Pb: 0.12-18.24 and Ni: 3.20-7.28. Zn was the most accumulated metal, followed by Fe, Cu and Ni, while Pb was the least. The mean of SOD and reduced GSH in the frogs indicate some responses to oxidative stress which varied significantly among sampling areas (P<0.05). MDA values however did not consistently correlate with either oxidative stress or heavy metal concentrations in the frogs. The water-sediment-tissue analysis for heavy metals demonstrated that the sediment concentrated more heavy metals than water, while the frog tissues accumulated these metals articularly in more polluted areas.Key words: Heavy metal pollution, bioaccumulation, Hoplobatrachus occipitalis, biomarkers, oxidative stress

Path deviations outperform approximate stability in heterogeneous congestion games

We consider non-atomic network congestion games with heterogeneous players where the latencies of the paths are subject to some bounded deviations. This model encompasses several well-studied extensions of the classical Wardrop model which incorporate, for example, risk-aversion, altruism or travel time delays. Our main goal is to analyze the worst-case deterioration in social cost of a perturbed Nash flow (i.e., for the perturbed latencies) with respect to an original Nash flow. We show that for homogeneous players perturbed Nash flows coincide with approximate Nash flows and derive tight bounds on their inefficiency. In contrast, we show that for heterogeneous populations this equivalence does not hold. We derive tight bounds on the inefficiency of both perturbed and approximate Nash flows for arbitrary player sensitivity distributions. Intuitively, our results suggest that the negative impact of path deviations (e.g., caused by risk-averse behavior or latency perturbations) is less severe than approximate stability (e.g., caused by limited responsiveness or bounded rationality). We also obtain a tight bound on the inefficiency of perturbed Nash flows for matroid congestion games and homogeneous populations if the path deviations can be decomposed into edge deviations. In particular, this provides a tight bound on the Price of Risk-Aversion for matroid congestion games