Engaging Consumers with Advergames: An Experimental Evaluation of Interactivity, Fit and Expectancy

Advergames are increasingly popular for online advertising campaigns. However, few IS studies have investigated the effectiveness of this unique advertising strategy. This study sheds light on the effectiveness of advergames by studying three design factors of advergame: interactivity, fit, and expectancy. We use multiple dependent variables (e.g., attitude toward advergames, attitude toward brand, and purchase intention) to evaluate the effectiveness of advergames. Based on work from human-computer interaction research and the transportation theory, we propose two-way interaction effects of interactivity, fit, and expectancy on attitudes toward advergame, and also their main effects on attitude toward brand. A positive mediating relationship from attitude toward advergame to attitude toward brand, and to purchase intention is also hypothesized. We conducted a 2*2*2 factorial design experiment in an online 3D virtual world environment to test our hypotheses. The results show that, in the high fit condition, both high interactivity and low expectancy lead to a more favorable attitude toward advergames. However, in the low interactivity condition, low expectancy generates a more positive attitude toward advergames. Interactivity and attitude toward advergames have significant positive effects on attitude toward brand, which, in turn, positively impacts purchase intention

Coupled Kinetic Analysis of Cleavage of DNA by Esperamicin and Calicheamicin

A coupled kinetic analysis of esperamicin, calicheamicin, and DNase I cleavage of covalently closed circular PM2 DNA has been carried out. Analysis of the optical density data derived from agarose gel electrophoresis experiments shows that esperamicin A,, like the hydrolytic enzyme DNase I, produces mainly single-strand breaks in DNA. These agents cause covalently closed circular form I DNA to be initially converted to nicked circular form I1 DNA. However, the ratio of the rate constant for this process (k,\u27) to that associated with conversion of form I1 to linear form I11 DNA ( k i ) is not consistent with completely random nicking, and some double-strand cleavage may occur. The values of k , \u27 / k i found for DNase I and esperamicin A, were 5.4 nd 3.9, respectively. The behavior of these agents sharply contrasts with that of esperamicin C and calicheamicin, for which double-strand cleavage of DNA is deduced from the analysis. Although the rate constant for introducing the first break in DNA for calicheamicin is lower than the corresponding rate constant for esperamicin C, the second break (in the opposing strand) is fast for calicheamicin, making it the better double-strand cleaving agent. These drugs are unique among antitumor agents in that a single activation event on the warhead portion produces a double-strand break in DNA without the need to posttreat the DNA with other agents in order to induce a cleavage. The cleavage kinetics are discussed in terms of the structural differences in these unusual anticancer drugs

Characterising the interactions between unicast and broadcast in IEEE 802.11 ad hoc networks

This paper investigates the relative performance of unicast and broadcast traffic traversing a one-hop ad hoc network utilising the 802.11 DCF. An extended Markov model has been developed and validated through computer simulation, which successfully predicts the respective performance of unicast and broadcast in a variety of mixed traffic scenarios. Under heavy network traffic conditions, a significant divergence is seen to develop between the performance of the two traffic classes - in particular, when network becomes saturated, unicast traffic is effectively given higher precedence over broadcast. As a result, the network becomes dominated by unicast frames, leading to poor rates of broadcast frame delivery

Exploratory Study on Gasification of Pelletized Grassy Biomass

Renewable energy offers a great potential for the world to reduce its dependency on fossil fuels, which can lead to a cleaner environment, better preservation of natural resources, and more economic opportunities for communities. Herbaceous biomass – such as switchgrass – is a major source of renewable energy available in the Midwest. For this project, switchgrass pellets were successfully co-gasified with wood chips. Characteristics of solid fuel mix of 50% wood chips and 50% switchgrass pellets were examined in terms of their gasification behavior, in reference to wood chips and wood pellets. Chemical kinetic studies were conducted to investigate the effect of gasification temperature on the production of hydrogen, carbon monoxide, and carbon dioxide in syngas. Within the operation temperature range studied (650-850°C), it was observed that hydrogen and carbon monoxide contents increased with gasification temperature (as gauged by the temperature at the top of the reaction zone). The mix of 50% wood chips and 50% switchgrass pellets remained relatively uniform in the gasifier chamber, even though some segregation between the two fuels was observed at the top part of the gasifier. Degradation of switchgrass pellets was observed within the gasifier; feeding bucket; and the pyrolysis, combustion, and reduction zones. A significant amount of clinkers were observed, especially toward the bottom of the reactor. Due to its chemical composition, switchgrass will inherently cause the formation of clinkers in the gasification and combustion process. Clinkers are a major technical challenge for extensive applications of grassy biomass as a renewable energy source. Further study on the ash fusion behavior for the purpose of clinker reduction is needed in order to effectively use herbaceous biomass as a renewable energy source.Illinois Sustainable Technology Center, Prairie Research Institute, University of Illinois at Urbana-Champaign; Grant Number HWR13230Ope

Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets

The recent development of reinforcement learning (RL) has boosted the adoption of online RL for wireless radio resource management (RRM). However, online RL algorithms require direct interactions with the environment, which may be undesirable given the potential performance loss due to the unavoidable exploration in RL. In this work, we first investigate the use of \emph{offline} RL algorithms in solving the RRM problem. We evaluate several state-of-the-art offline RL algorithms, including behavior constrained Q-learning (BCQ), conservative Q-learning (CQL), and implicit Q-learning (IQL), for a specific RRM problem that aims at maximizing a linear combination {of sum and} 5-percentile rates via user scheduling. We observe that the performance of offline RL for the RRM problem depends critically on the behavior policy used for data collection, and further propose a novel offline RL solution that leverages heterogeneous datasets collected by different behavior policies. We show that with a proper mixture of the datasets, offline RL can produce a near-optimal RL policy even when all involved behavior policies are highly suboptimal.Comment: This paper is the camera ready version for Asilomar 202

An automated growth enclosure for metabolic labeling of Arabidopsis thaliana with 13C-carbon dioxide - an in vivo labeling system for proteomics and metabolomics research

<p>Abstract</p> <p>Background</p> <p>Labeling whole <it>Arabidopsis (Arabidopsis thaliana) </it>plants to high enrichment with ¹³C for proteomics and metabolomics applications would facilitate experimental approaches not possible by conventional methods. Such a system would use the plant's native capacity for carbon fixation to ubiquitously incorporate ¹³C from ¹³CO₂gas. Because of the high cost of ¹³CO₂it is critical that the design conserve the labeled gas.</p> <p>Results</p> <p>A fully enclosed automated plant growth enclosure has been designed and assembled where the system simultaneously monitors humidity, temperature, pressure and ¹³CO₂concentration with continuous adjustment of humidity, pressure and ¹³CO₂levels controlled by a computer running LabView software. The enclosure is mounted on a movable cart for mobility among growth environments. <it>Arabidopsis </it>was grown in the enclosure for up to 8 weeks and obtained on average >95 atom% enrichment for small metabolites, such as amino acids and >91 atom% for large metabolites, including proteins and peptides.</p> <p>Conclusion</p> <p>The capability of this labeling system for isotope dilution experiments was demonstrated by evaluation of amino acid turnover using GC-MS as well as protein turnover using LC-MS/MS. Because this 'open source' <it>Arabidopsis </it>¹³C-labeling growth environment was built using readily available materials and software, it can be adapted easily to accommodate many different experimental designs.</p