What we discovered when we implemented Discovery

The presentation describes the technical aspects of the customisation of its discovery interface, which uses EBSCO Discovery Service software. The customisation required close collaboration with EBSCO software engineers and involved a high level of technical expertise.

Changes in use of types of tobacco products by pack sizes and price segments, prices paid and consumption following the introduction of plain packaging in Australia

Objectives: To describe changes among smokers in use of various types of tobacco products, reported prices paid and cigarette consumption following the standardisation of tobacco packaging in Australia.
Methods: National cross-sectional telephone surveys of adult smokers were conducted from April 2012 (6 months before transition to plain packaging (PP) to March 2014 (15 months afterwards). Multivariable logistics regression assessed changes in products, brands and pack types/sizes; multivariable linear regression examined changes in inflation-adjusted prices paid and reported cigarette consumption between the pre-PP and three subsequent periods – the transition phase, PP year 1 and PP post-tax (post a 12.5% tax increase in December 2013).
Results: The proposition of current smokers using roll-your-own (RYO) products fluctuated over the study period. Proportions using value brands of factory-made (FM) cigarettes increased from pre-PP (21.4%) to PP year 1 (25.5%; p=0.002) and PP post-tax (27.8%; p<0.001). Inflation-adjusted prices paid increased in the PP year 1 and PP post-tax phases; the largest increases were among premium FM brands, the smallest among value brands. Consumption did not change in PP year 1 among daily, regular or current smokers declined significantly in PP post-tax (mean=14.0, SE=0.33) compared to PP year 1 (mean=14.8, SE=0.17; p=0.037).
Conclusions: Introduction of PP was associated with an increase in use of value brands, likely due to increased numbers available and smaller increases in prices for value relative to premium brands. Reported consumption declined following the December 2013 tax increase.

Influence of price discounts and skill-building strategies on purchase and consumption of healthy food and beverages: outcomes of the Supermarket Healthy Eating for Life randomized controlled trial

BACKGROUND: Fiscal strategies are increasingly considered upstream nutrition promotion measures. However, few trials have investigated the effectiveness or cost effectiveness of pricing manipulations on diet in real-world settings. OBJECTIVE: We assessed the effects on fruit, vegetable, and beverage purchasing and consumption of a 20% price-reduction intervention, a tailored skills-based behavior-change intervention, and a combined intervention compared with a control condition. DESIGN: The Supermarket Healthy Eating for Life trial was a randomized controlled trial conducted over 3 mo [baseline (time 1) to postintervention (time 2) with a 6-mo follow-up (time 3)]. Female primary household shoppers in Melbourne, Australia, were randomly assigned to a 1) skill-building (n = 160), 2) price-reduction (n = 161), 3) combined skill-building and price-reduction (n = 160), or 4) control (n = 161) group. Supermarket transaction data and surveys were used to measure the following study outcomes: fruit, vegetable, and beverage purchases and self-reported fruit and vegetable consumption at each time point. RESULTS: At 3 mo (time 2), price reduction-alone participants purchased more total vegetables and frozen vegetables than did controls. Price reduction-alone and price reduction-plus-skill-building participants purchased more fruit than did controls. Relative to controls, in the price-reduction group, total vegetable consumption increased by 233 g/wk (3.1 servings or 15% more than at baseline), and fruit purchases increased by 364 g/wk (2.4 servings; 35% more than at baseline). Increases were not maintained 6 mo postintervention (time 3). Price reduction-alone participants showed a tendency for a slight increase in fruit consumption at time 2 (P = 0.09) that was maintained at time 3 (P = 0.014). No intervention improved purchases of bottled water or low-calorie beverages. CONCLUSIONS: A 20% price reduction in fruit and vegetables resulted in increased purchasing per household of 35% for fruit and 15% for vegetables over the price-reduction period. These findings show that price modifications can directly increase produce purchases. The Supermarket Healthy Eating for Life trial was registered at Current Controlled Trials Registration as ISRCTN39432901.

Lying about the price? Ultimatum bargaining with messages and imperfectly observed offers

We introduce the taxicab game, related to the ultimatum game and Gehrig et al.'s (2007) yes/no game. The proposer makes an offer, and simultaneously sends a cheap talk message indicating (possibly falsely) the amount of the offer. The responder observes the message with certainty and the offer with probability p before accepting or rejecting the offer. We investigate versions with p=. 0 and p=. 0.5 along with the ultimatum game as a baseline. Intuition and a model comprising both standard economic agents and others who dislike inequity, lies and lying provide clear predictions that our experimental results support. As the likelihood increases of offers being seen, the offers themselves increase, messages over-state them less, and responders are more likely to accept (even when the offer is unseen). Also, responders are more likely to accept after truthful messages than after lies or when no message is sent.

Toward Omics-Based, Systems Biomedicine, and Path and Drug Discovery Methodologies for Depression-Inflammation Research.

Meta-analyses confirm that depression is accompanied by signs of inflammation including increased levels of acute phase proteins, e.g., C-reactive protein, and pro-inflammatory cytokines, e.g., interleukin-6. Supporting the translational significance of this, a meta-analysis showed that anti-inflammatory drugs may have antidepressant effects. Here, we argue that inflammation and depression research needs to get onto a new track. Firstly, the choice of inflammatory biomarkers in depression research was often too selective and did not consider the broader pathways. Secondly, although mild inflammatory responses are present in depression, other immune-related pathways cannot be disregarded as new drug targets, e.g., activation of cell-mediated immunity, oxidative and nitrosative stress (O&NS) pathways, autoimmune responses, bacterial translocation, and activation of the toll-like receptor and neuroprogressive pathways. Thirdly, anti-inflammatory treatments are sometimes used without full understanding of their effects on the broader pathways underpinning depression. Since many of the activated immune-inflammatory pathways in depression actually confer protection against an overzealous inflammatory response, targeting these pathways may result in unpredictable and unwanted results. Furthermore, this paper discusses the required improvements in research strategy, i.e., path and drug discovery processes, omics-based techniques, and systems biomedicine methodologies. Firstly, novel methods should be employed to examine the intracellular networks that control and modulate the immune, O&NS and neuroprogressive pathways using omics-based assays, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, immunoproteomics and metagenomics. Secondly, systems biomedicine analyses are essential to unravel the complex interactions between these cellular networks, pathways, and the multifactorial trigger factors and to delineate new drug targets in the cellular networks or pathways. Drug discovery processes should delineate new drugs targeting the intracellular networks and immune-related pathways.

Stock price comovement: Evidence from India

We examine the extent to which stock prices comove in an emerging economy, India. We first document that stocks listed on the National Stock Exchange (NSE) comove. Further, we find that synchronicity is positively associated with growth and earnings volatility and negatively associated with business group affiliation and leverage.

Equity market price interactions between China and the other markets within the Chinese states equity markets

This study examines the cointegrating and long-term causal relationships of equity market prices in equity markets of Chinese states namely, Shanghai, Shenzhen, Hong Kong, Taiwan and Singapore. I cover the period between October 5, 1992 and March 20, 2006, taking into account both the Asian financial crisis and the opening-up of China’s equity markets in recent years. First, I analysis the cointegration by utilizing Johansen’s (1988) cointegration tests. I find that a long-term equilibrium relationship measured by cointegration has been established among Shanghai, Shenzhen, Hong Kong and Taiwanese markets and, to a lesser degree, between these markets and the Singapore market since 1998. Secondly, this study examines causality by exploring the bootstrapped Toda-Yamamoto non-causality tests. I find that there is strong evidence of a bi-directional causality between Shanghai and Shenzhen markets after 1998. Furthermore, I also find that there are more causal linkages between the Chinese states equity markets: two mainland Chinese markets, Hong Kong, Taiwan, and Singapore became more dependent on each other. The robustness of the above findings is confirmed by the use of a bootstrap test employed to test the validity of my results.

Genomics based biomarker discovery in oral squamous cell carcinoma

 The present thesis showed signaling mechanisms and pathways essential for oral cancer progression through genomics approach. It has identified markers that are of diagnostic, prognostic and therapeutic importance. It has also shown that aspirin is a potential drug in oral cancer treatment.

Information discovery in multi-dimensional autonomous wireless sensor networks

 The thesis proposed four novel algorithms of information discovery for Multidimensional Autonomous Wireless Sensor Networks (WSNs) that can significantly increase network lifetime and minimize query processing latency, resulting in quality of service improvements that are of immense benefit to Multidimensional Autonomous WSNs are deployed in complex environments (e.g., mission-critical applications).

The use of mixed methods in drug discovery: integrating qualitative methods into clinical trials

Contemporary methods in clinical trials are pivoted around hypothesis confirmation, not generation. This is a problem for new drug discovery, since the pharmacokinetic or receptor profile of most novel agents do not link to pathophysiology, which is very poorly understood. Therefore, it is difficult to impute the therapeutic potential of a candidate agent. Most psychotropic agents were discovered serendipitously, either through careful clinical observation or by researchers finding unexpected associations in datasets. Methods that increase the ability to detect latent signals in data are needed. These include mixed methods that incorporate qualitative methods into randomized controlled trials.

This chapter proposes a methodology for the integration of mixed methods in clinical trials, fusing qualitative and quantitative methods, and presents an exemplar using this approach.

Mixed methods show potential for signal detection, hypothesis generation, and associations that may be otherwise undetected in traditional clinical trials.

Continuous discovery of co-location contexts from Bluetooth data

The discovery of contexts is important for context-aware applications in pervasive computing. This is a challenging problem because of the stream nature of data, the complexity and changing nature of contexts. We propose a Bayesian nonparametric model for the detection of co-location contexts from Bluetooth signals. By using an Indian buffet process as the prior distribution, the model can discover the number of contexts automatically. We introduce a novel fixed-lag particle filter that processes data incrementally. This sampling scheme is especially suitable for pervasive computing as the computational requirements remain constant in spite of growing data. We examine our model on a synthetic dataset and two real world datasets. To verify the discovered contexts, we compare them to the communities detected by the Louvain method, showing a strong correlation between the results of the two methods. Fixed-lag particle filter is compared with Gibbs sampling in terms of the normalized factorization error that shows a close performance between the two inference methods. As fixed-lag particle filter processes a small chunk of data when it comes and does not need to be restarted, its execution time is significantly shorter than that of Gibbs sampling.