An Experimental Study of Information Revelation Policies in Sequential Auctions

Theoretical models of information asymmetry have identied a tradeoff between the desire to learn and the desire to prevent an opponent from learning private information. This paper reports a laboratory experiment that investigates if actual bidders account for this tradeoff, using a sequential procurement auction with private cost information and varying information revelation policies. Specically, the Complete Information Policy, where all submitted bids are revealed between auctions, is compared against the Incomplete Information Policy, where only the winning bid is revealed. The experimental results are largely consistent with the theoretical predictions. For example, bidders pool with other types to prevent an opponent from learning signicantly more often under a Complete Information Policy. Also as predicted, the procurer pays less when employing an Incomplete Information Policy only when the market is highly competitive. Bids are usually more aggressive than the risk neutral quantitative prediction, which is usually consistent with risk aversion.Complete and Incomplete Information Revelation Policies, Laboratory Study, Procurement Auction, Multistage Game

Analyzing video compression for transporting over wireless fading channels

Wireless video communication is becoming increasingly popular these days with new applications such as TV on mobile and video phones. Commercial success of these applications requires superior video quality at the receiver. So it is imperative to analyze the effect of a wireless channel on a video transmission. The aim of this research is to analyze the video transmission over Rayleigh fading channels for various bit error rates (BER), signal to noise ratios (Eb/N0) and Doppler rates, and to suggest which source coding scheme is best at which BER, Eb/N0 and Doppler rates. Alternative schemes such as hybrid (digital/analog) schemes were considered and their performances were compared with pure digital communication. It is also shown that the combination of digital and analog video communication does not yield any better performance compared to pure digital video communication

A Computational Approach to Compare Information Revelation Policies

Revelation policies in an electronic marketplace differ in terms of the level of competitive information disseminated to participating sellers. Since sellers who repeatedly compete against one another learn based on the information revealed and alter their future bidding behavior, revelation policies affect welfare parameters—consumer surplus, producer surplus, and social welfare—of the market. Although different revelation policies are adopted in several traditional and Web-based marketplaces, prior work has not studied the implications of these policies on the performance of a market. In this paper, we study and compare a set of revelation policies using a computational marketplace. Specifically, we study this in the context of a reverse-market where each seller’s decision problem of choosing an optimal bid is modeled as an MDP (Markov decision process). Results and analysis presented in this paper are based on market sessions executed using the computational marketplace. The computational model, which employs a machine-learning technique proposed in this paper, ties the simulation results to the model developed using the game-theoretic models. In addition to this, the computational model allows us to relax assumptions of the game-theoretic models and study the problem under a more realistic scenario. Insights gained from this paper will be useful in guiding the buyer in choosing the appropriate policy

When Reward Meets Donation: A Paradoxical Dilemma

Reward-based crowdfunding platforms are increasingly incorporating donation options, allowing backers to financially support campaigns without receiving any tangible rewards in return. Although this option seems to create a novel fundraising channel, our quasi-natural experimental study highlights the potential negative impacts of individual donation occurrences, which ultimately lead to reduced total raised funds, as substantiated by robust empirical evidence. We explore two primary mechanisms responsible for the adverse effect. First, the bystander effect, where prior donations discourage potential backers from supporting the campaign, causing them to either forgo reward purchases or decrease their contribution amounts. Second, the social conformity effect, in which prior donations shape backers\u27 perceptions of social norms and consequently lower their support levels. By offering a comprehensive understanding of behavioral dynamics in crowdfunding, our study enriches the literature on the design and management of crowdfunding platforms and provides valuable insights for industry practitioners

Outcome analysis of surgically managed unstable burst fracture

Background:Burst fractures are common injuries of dorsolumbar spine. In indicated cases, surgery is the treatment of choice. Significant controversy exists regarding surgical intervention for these fractures. Posterior decompression, anterior decompression and instrumentation, and combined anterior decompression and posterior instrumentation have been recommended in various studies. Here we are going to evaluate unstable burst fractures of thoracic and lumbar spine treated by isolated anterior decompression and instrumented fusion with TSM-Bone graft composite.Methods: Prospective study of thirty-six cases of unstable fracture of thoracic and lumbar spine treated in Sri Ramachandra Medical centre from January 2011 to January 2014. The inclusion criteria were burst fractures of thoracic or lumbar spine complete or incomplete neurological deficit and burst fractures of thoracic or lumbar spine without neurological deficit but with mechanical instability. The exclusion criteria were pathological fractures, chance fracture, stable burst, wedge compression and osteoporotic compression fractures. The results were analyzed during the follow-up using the Pain – Visual analogue scale, Fusion status and radiographic parameter – K-angle .For pain score were given as 3,2,1 for absent, moderate and severe pain respectively. Regarding fusion status score of 3,2,1 were given when fusion was good, fair and no sign of fusion respectively.Results:Mean pre-operative K-angle was 28o. Average loss of correction at final follow up was 3o.Mean correction of K-angle was 140.Moderate to severe loss of correction of K- angle was observed in 4 patients. Mild to moderate pain in 5 patients treated with analgesics. Average TSM subsidence was 3mm.Conclusions:Bone graft composite provides stable biomechanical support to deficient anterior column in burst fractures and allows early rehabilitation and mobilization. Neural recovery may occur after anterior decompression, stabilization and fusion with TSM-Bone graft composite in dorsolumbar burst fractures with incomplete cord injury

Antigenically intact hemagglutinin in circulating avian and swine influenza viruses and potential for H3N2 pandemic

The 2009 swine-origin H1N1 influenza, though antigenically novel to the population at the time, was antigenically similar to the 1918 H1N1 pandemic influenza, and consequently was considered to be “archived” in the swine species before reemerging in humans. Given that the H3N2 is another subtype that currently circulates in the human population and is high on WHO pandemic preparedness list, we assessed the likelihood of reemergence of H3N2 from a non-human host. Using HA sequence features relevant to immune recognition, receptor binding and transmission we have identified several recent H3 strains in avian and swine that present hallmarks of a reemerging virus. IgG polyclonal raised in rabbit with recent seasonal vaccine H3 fail to recognize these swine H3 strains suggesting that existing vaccines may not be effective in protecting against these strains. Vaccine strategies can mitigate risks associated with a potential H3N2 pandemic in humans.National Institutes of Health (U.S.) (R37 GM057073-13

A Dynamic Probabilistic Based Broadcasting Scheme for MANETs

MANET is commonly known as Mobile Ad Hoc Network in which cluster of mobile nodes can communicate with each other without having any basic infrastructure. The basic characteristic of MANET is dynamic topology. Due to the dynamic behavior nature, the topology of the network changes very frequently, and this will lead to the failure of the valid route repeatedly. Thus, the process of finding the valid route leads to notable drop in the throughput of the network. To identify a new valid path to the targeted mobile node, available proactive routing protocols use simple broadcasting method known as simple flooding. The simple flooding method broadcasts the RREQ packet from the source to the rest of the nodes in mobile network. But the problem with this method is disproportionate repetitive retransmission of RREQ packet which could result in high contention on the available channel and packet collision due to extreme traffic in the network. A reasonable number of routing algorithms have been suggested for reducing the lethal impact of flooding the RREQ packets. However, most of the algorithms have resulted in considerable amount of complexity and deduce the throughput by depending on special hardware components and maintaining complex information which will be less frequently used. By considering routing complexity with the goal of increasing the throughput of the network, in this paper, we have introduced a new approach called Dynamic Probabilistic Route (DPR) discovery. The Node’s Forwarding Probability (NFP) is dynamically calculated by the DPR mobile nodes using Probability Function (PF) which depends on density of local neighbor nodes and the cumulative number of its broadcast covered neighbors