Look Who's Talking: Bipartite Networks as Representations of a Topic Model of New Zealand Parliamentary Speeches

Quantitative methods to measure the participation to parliamentary debate and discourse of elected Members of Parliament (MPs) and the parties they belong to are lacking. This is an exploratory study in which we propose the development of a new approach for a quantitative analysis of such participation. We utilize the New Zealand government's digital Hansard database to construct a topic model of parliamentary speeches consisting of nearly 40 million words in the period 2003-2016. A Latent Dirichlet Allocation topic model is implemented in order to reveal the thematic structure of our set of documents. This generative statistical model enables the detection of major themes or topics that are publicly discussed in the New Zealand parliament, as well as permitting their classification by MP. Information on topic proportions is subsequently analyzed using a combination of statistical methods. We observe patterns arising from time-series analysis of topic frequencies which can be related to specific social, economic and legislative events. We then construct a bipartite network representation, linking MPs to topics, for each of four parliamentary terms in this time frame. We build projected networks (onto the set of nodes represented by MPs) and proceed to the study of the dynamical changes of their topology, including community structure. By performing this longitudinal network analysis, we can observe the evolution of the New Zealand parliamentary topic network and its main parties in the period studied.Comment: 28 pages, 12 figures, 3 table

Neural correlates of visuospatial working memory in the ‘at-risk mental state’

Background. Impaired spatial working memory (SWM) is a robust feature of schizophrenia and has been linked to the risk of developing psychosis in people with an at-risk mental state (ARMS). We used functional magnetic resonance imaging (fMRI) to examine the neural substrate of SWM in the ARMS and in patients who had just developed schizophrenia. Method. fMRI was used to study 17 patients with an ARMS, 10 patients with a first episode of psychosis and 15 agematched healthy comparison subjects. The blood oxygen level-dependent (BOLD) response was measured while subjects performed an object–location paired-associate memory task, with experimental manipulation of mnemonic load. Results. In all groups, increasing mnemonic load was associated with activation in the medial frontal and medial posterior parietal cortex. Significant between-group differences in activation were evident in a cluster spanning the medial frontal cortex and right precuneus, with the ARMS groups showing less activation than controls but greater activation than first-episode psychosis (FEP) patients. These group differences were more evident at the most demanding levels of the task than at the easy level. In all groups, task performance improved with repetition of the conditions. However, there was a significant group difference in the response of the right precuneus across repeated trials, with an attenuation of activation in controls but increased activation in FEP and little change in the ARMS. Conclusions. Abnormal neural activity in the medial frontal cortex and posterior parietal cortex during an SWM task may be a neural correlate of increased vulnerability to psychosis

Real Exchange Rates in the Long and Short Run: A Panel Co-Integration Approach

The empirical literature on long-run real exchange rate behavior has shown mixed evidence due to problems involving the lack of long time series data and the low power of time-series unit root tests in small samples. The main objective of the present paper is to tackle these empirical issues by applying the recently developed panel cointegration techniques to the long-run real exchange rate equation implied by our model. Using annual data for 67 countries over the 1966-97, we find that the cointegrating relationship between the real exchange rate, the ratio of net foreign assets to GDP, the relative Home to Foreign productivity of the traded and non-traded sector, and the terms of trade is valid in the long run. This result holds for all sub-sample of countries (whether they are classified by income per capita or capital controls). Furthermore, our coefficient estimates are consistent with the theoretical values implied by the calibrated parameters of preferences and technology in Stockman and Tesar (1995). Robustness checks reveal that: (i) “pooling” the data to obtain a common long-run equilibrium relationship across countries is valid for the samples of countries with high income and low capital controls, (ii) the oil shock crisis in 1973 represents a structural change for these sub-samples. Finally, deviations from the equilibrium are large and persistent with half-life estimates (between 2.8 and 5) consistent with the consensus interval of 2.5-5 found in the literature (Murray and Papell, 2002).

The Demand for Beef in Indonesia: Implications for Australian Agribusiness

Meat consumption and socio-demographic data from the 1990, 1993 and 1996 SUSENAS Household Food Expenditure and Consumption Surveys were employed to estimate the demand for meats in Indonesia. The focus was on the Provinces of DKI Jakarta and West Java where about one-fourth of the Indonesian population reside. Statistical and econometric procedures were used to aggregate the 16 meat types recorded in the SUSENAS into four Meat Groups. They were then used to estimate the Linear Approximation of the Almost Ideal Demand System (LA/AIDS) model, taking into account zero observations and the restrictions on budget shares. The demand for Meat Group 1 (with the dominant meat, beef) is income-inelastic, whereas for Meat Group 2 (with the dominant meat, commercial and native chicken) it is income-elastic. These two groups comprise nearly 95 per cent of all meat purchases. The estimated own-price elasticity of the beef group is -0.92, while that for the chicken group is -1.09. The cross-price elasticities indicate that all the meat groups are substitute goods, as expected. The results suggest that the current focus of the Indonesian government on strengthening the domestic poultry industry is well placed, as the demand for chicken is likely to respond more quickly to income growth than the demand for beef. Further, consumers seem more likely to adapt their chicken consumption patterns to price changes than they do for beef. However, these differences are relatively minor and there is still a major opportunity for Australian agribusiness firms in the cattle and beef sectors to take advantage of the projected rapid growth in Indonesian beef demand.beef demand, almost ideal demand system, commodity aggregation, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries,

Another Look at the Null of Stationary RealExchange Rates. Panel Data with Structural Breaks and Cross-section Dependence

This paper re-examines the null of stationary of real exchange rate for a panel of seventeen OECD developed countries during the post-Bretton Woods era. Our analysis simultaneously considers both the presence of cross-section dependence and multiple structural breaks that have not received much attention in previous panel methods of long-run PPP. Empirical results indicate that there is little evidence in favor of PPP hypothesis when the analysis does not account for structural breaks. This conclusion is reversed when structural breaks are considered in computation of the panel statistics. We also compute point estimates of half-life separately for idiosyncratic and common factor components and find that it is always below one year.Purchasing power parity, Half-lives, Panel unit roottests, Multiple structural breaks, Cross-section dependence.

Study protocol for the Anesthesiology Control Tower—Feedback Alerts to Supplement Treatments (ACTFAST-3) trial: A pilot randomized controlled trial in intraoperative telemedicine [version 1; referees: 2 approved]

Background: Each year, over 300 million people undergo surgical procedures worldwide. Despite efforts to improve outcomes, postoperative morbidity and mortality are common. Many patients experience complications as a result of either medical error or failure to adhere to established clinical practice guidelines. This protocol describes a clinical trial comparing a telemedicine-based decision support system, the Anesthesiology Control Tower (ACT), with enhanced standard intraoperative care. Methods: This study is a pragmatic, comparative effectiveness trial that will randomize approximately 12,000 adult surgical patients on an operating room (OR) level to a control or to an intervention group. All OR clinicians will have access to decision support software within the OR as a part of enhanced standard intraoperative care. The ACT will monitor patients in both groups and will provide additional support to the clinicians assigned to intervention ORs. Primary outcomes include blood glucose management and temperature management. Secondary outcomes will include surrogate, clinical, and economic outcomes, such as incidence of intraoperative hypotension, postoperative respiratory compromise, acute kidney injury, delirium, and volatile anesthetic utilization. Ethics and dissemination: The ACTFAST-3 study has been approved by the Human Resource Protection Office (HRPO) at Washington University in St. Louis and is registered at clinicaltrials.gov (NCT02830126). Recruitment for this protocol began in April 2017 and will end in December 2018. Dissemination of the findings of this study will occur via presentations at academic conferences, journal publications, and educational materials

Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the {citation vector}, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action

Grand Valley Magazine, vol. 5, no. 2 Winter 2006

Grand Valley Magazine is a quarterly publication about Grand Valley State University produced by University Communications since 2001.https://scholarworks.gvsu.edu/gv_magazine/1014/thumbnail.jp