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https://www.readbyqxmd.com/read/28425426/production-of-red-tilapia-oreochromis-spp-in-floating-cages-in-the-mekong-delta-vietnam-mortality-and-health-management
#1
Annette S Boerlage, Tu Thanh Dung, Tran Thi Hoa, Jeffrey Davidson, Henrik Stryhn, K Larry Hammell
The Mekong Delta in Vietnam is one of the most productive aquaculture regions in the world, in which the red tilapia (Oreochromis spp.) industry is a small-scale industry that mainly supplies local markets in the delta region. Little is known about the frequency of mortality events and health management in this sector. We describe red tilapia floating cage production systems in the Mekong Delta, Vietnam, for the purposes of quantifying mortality and associated production factors, and describing practices that may influence pathogen introduction and spread to and from farms...
April 20, 2017: Diseases of Aquatic Organisms
https://www.readbyqxmd.com/read/28370082/big-data-challenges-of-high-dimensional-continuous-time-mean-variance-portfolio-selection-and-a-remedy
#2
Mei Choi Chiu, Chi Seng Pun, Hoi Ying Wong
Investors interested in the global financial market must analyze financial securities internationally. Making an optimal global investment decision involves processing a huge amount of data for a high-dimensional portfolio. This article investigates the big data challenges of two mean-variance optimal portfolios: continuous-time precommitment and constant-rebalancing strategies. We show that both optimized portfolios implemented with the traditional sample estimates converge to the worst performing portfolio when the portfolio size becomes large...
March 30, 2017: Risk Analysis: An Official Publication of the Society for Risk Analysis
https://www.readbyqxmd.com/read/28364677/forecasting-stochastic-neural-network-based-on-financial-empirical-mode-decomposition
#3
Jie Wang, Jun Wang
In an attempt to improve the forecasting accuracy of stock price fluctuations, a new one-step-ahead model is developed in this paper which combines empirical mode decomposition (EMD) with stochastic time strength neural network (STNN). The EMD is a processing technique introduced to extract all the oscillatory modes embedded in a series, and the STNN model is established for considering the weight of occurrence time of the historical data. The linear regression performs the predictive availability of the proposed model, and the effectiveness of EMD-STNN is revealed clearly through comparing the predicted results with the traditional models...
March 18, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28345444/budgetary-impact-of-cabazitaxel-use-after-docetaxel-treatment-for-metastatic-castration-resistant-prostate-cancer
#4
Kyle Flannery, Ed Drea, Louis Hudspeth, Shelby Corman, Xin Gao, Mei Xue, Raymond Miao
BACKGROUND: With the approval of several new treatments for metastatic castration-resistant prostate cancer (mCRPC), budgetary impact is a concern for health plan decision makers. Budget impact models (BIMs) are becoming a requirement in many countries as part of formulary approval or reimbursement decisions. Cabazitaxel is a second-generation taxane developed to overcome resistance to docetaxel and is approved for the treatment of patients with mCRPC previously treated with a docetaxel-containing regimen...
April 2017: Journal of Managed Care & Specialty Pharmacy
https://www.readbyqxmd.com/read/28316618/an-evolutionary-method-for-financial-forecasting-in-microscopic-high-speed-trading-environment
#5
Chien-Feng Huang, Hsu-Chih Li
The advancement of information technology in financial applications nowadays have led to fast market-driven events that prompt flash decision-making and actions issued by computer algorithms. As a result, today's markets experience intense activity in the highly dynamic environment where trading systems respond to others at a much faster pace than before. This new breed of technology involves the implementation of high-speed trading strategies which generate significant portion of activity in the financial markets and present researchers with a wealth of information not available in traditional low-speed trading environments...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28314980/ex-post-assessment-of-genetically-modified-low-level-presence-in-canadian-flax
#6
Helen M Booker, Eric G Lamb, Stuart J Smyth
Canada is the world's largest producer and exporter of flaxseed. In 2009, DNA from deregistered genetically modified (GM) CDC Triffid was detected in a shipment of Canadian flaxseed exported to Europe, causing a large decrease in the amount of flax planted in Canada and a major shift in export markets. The flax industry in Canada undertook major changes to ensure the removal of transgenic flax from the supply chain. To demonstrate compliance, Canada adopted a protocol involving testing grain samples (post-harvest) using an RT-PCR test for the construct found in CDC Triffid...
March 17, 2017: Transgenic Research
https://www.readbyqxmd.com/read/28298880/h7n9-and-h5n1-avian-influenza-suitability-models-for-china-accounting-for-new-poultry-and-live-poultry-markets-distribution-data
#7
Jean Artois, Shengjie Lai, Luzhao Feng, Hui Jiang, Hang Zhou, Xiangping Li, Madhur S Dhingra, Catherine Linard, Gaëlle Nicolas, Xiangming Xiao, Timothy P Robinson, Hongjie Yu, Marius Gilbert
In the last two decades, two important avian influenza viruses infecting humans emerged in China, the highly pathogenic avian influenza (HPAI) H5N1 virus in the late nineties, and the low pathogenic avian influenza (LPAI) H7N9 virus in 2013. China is home to the largest population of chickens (4.83 billion) and ducks (0.694 billion), representing, respectively 23.1 and 58.6% of the 2013 world stock, with a significant part of poultry sold through live-poultry markets potentially contributing to the spread of avian influenza viruses...
2017: Stochastic Environmental Research and Risk Assessment: Research Journal
https://www.readbyqxmd.com/read/28241832/the-malaria-testing-and-treatment-market-in-kinshasa-democratic-republic-of-the-congo-2013
#8
Godéfroid Mpanya, Antoinette Tshefu, Joris Losimba Likwela
BACKGROUND: The Democratic Republic of Congo (DRC) is one of the two most leading contributors to the global burden of disease due to malaria. This paper describes the malaria testing and treatment market in the nation's capital province of Kinshasa, including availability of malaria testing and treatment and relative anti-malarial market share for the public and private sector. METHODS: A malaria medicine outlet survey was conducted in Kinshasa province in 2013...
February 28, 2017: Malaria Journal
https://www.readbyqxmd.com/read/28231255/confidence-and-self-attribution-bias-in-an-artificial-stock-market
#9
Mario A Bertella, Felipe R Pires, Henio H A Rego, Jonathas N Silva, Irena Vodenska, H Eugene Stanley
Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index-both generated by our model-are cointegrated and that stock price affects confidence index but confidence index does not affect stock price...
2017: PloS One
https://www.readbyqxmd.com/read/28220717/merger-acquisition-and-capital-expenditure-in-health-care
#10
Wenjing Ouyang, Peter E Hilsenrath
Investment, especially through merger and acquisition (M&A), is a leading topic of concern among health care managers. In addition, the implications of this activity for organization and market concentration are of great interest to policy makers. Using a sample of 2256 firm-year observations in the health care industry during the period from 1985 to 2011, this article provides novel evidence that managers learn from financial markets in making capital expenditure (CAPEX) and M&A investment decisions. Within the industry, managers in the Drugs subsector are most likely to do so, whereas managers in the Medical Equipment and Supplies are least likely to do so...
January 2017: Inquiry: a Journal of Medical Care Organization, Provision and Financing
https://www.readbyqxmd.com/read/28190972/object-view-in-spatial-system-dynamics-a-grassland-farming-example
#11
REVIEW
Christian Neuwirth, Barbara Hofer, Andreas Schaumberger
Spatial system dynamics (SSD) models are typically implemented by linking stock variables to raster grids while the use of object representations of human artefacts such as buildings or ownership has been limited. This limitation is addressed by this article, which demonstrates the use of object representations in SSD. The objects are parcels of land that are attributed to grassland farms. The model simulates structural change in agriculture, i.e., change in the size of farms. The aim of the model is to reveal relations between structural change, farmland fragmentation and variable farmland quality...
July 2, 2016: Journal of Spatial Science
https://www.readbyqxmd.com/read/28159017/global-health-workforce-labor-market-projections-for-2030
#12
Jenny X Liu, Yevgeniy Goryakin, Akiko Maeda, Tim Bruckner, Richard Scheffler
BACKGROUND: In low- and middle-income countries, scaling essential health interventions to achieve health development targets is constrained by the lack of skilled health professionals to deliver services. METHODS: We take a labor market approach to project future health workforce demand based on an economic model based on projected economic growth, demographics, and health coverage, and using health workforce data (1990-2013) for 165 countries from the WHO Global Health Observatory...
February 3, 2017: Human Resources for Health
https://www.readbyqxmd.com/read/28157288/envisioning-nano-release-dynamics-in-a-changing-world-using-dynamic-probabilistic-modeling-to-assess-future-environmental-emissions-of-engineered-nanomaterials
#13
Tian Yin Sun, Denise M Mitrano, Nikolaus A Bornhöft, Martin Scheringer, Konrad Hungerbühler, Bernd Nowack
The need for an environmental risk assessment for engineered nanomaterials (ENM) necessitates the knowledge about their environmental emissions. Material flow models (MFA) have been used to provide predicted environmental emissions but most current nano-MFA models consider neither the rapid development of ENM production nor the fact that a large proportion of ENM are entering an in-use stock and are released from products over time (i.e., have a lag phase). Here we use dynamic probabilistic material flow modeling to predict scenarios of the future flows of four ENM (nano-TiO2, nano-ZnO, nano-Ag and CNT) to environmental compartments and to quantify their amounts in (temporary) sinks such as the in-use stock and ("final") environmental sinks such as soil and sediment...
February 16, 2017: Environmental Science & Technology
https://www.readbyqxmd.com/read/28147491/new-approach-of-financial-volatility-duration-dynamics-by-stochastic-finite-range-interacting-voter-system
#14
Guochao Wang, Jun Wang
We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system...
January 2017: Chaos
https://www.readbyqxmd.com/read/28145494/topological-characteristics-of-the-hong-kong-stock-market-a-test-based-p-threshold-approach-to-understanding-network-complexity
#15
Ronghua Xu, Wing-Keung Wong, Guanrong Chen, Shuo Huang
In this paper, we analyze the relationship among stock networks by focusing on the statistically reliable connectivity between financial time series, which accurately reflects the underlying pure stock structure. To do so, we firstly filter out the effect of market index on the correlations between paired stocks, and then take a t-test based P-threshold approach to lessening the complexity of the stock network based on the P values. We demonstrate the superiority of its performance in understanding network complexity by examining the Hong Kong stock market...
February 1, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28137850/seafood-prices-reveal-impacts-of-a-major-ecological-disturbance
#16
Martin D Smith, Atle Oglend, A Justin Kirkpatrick, Frank Asche, Lori S Bennear, J Kevin Craig, James M Nance
Coastal hypoxia (dissolved oxygen ≤ 2 mg/L) is a growing problem worldwide that threatens marine ecosystem services, but little is known about economic effects on fisheries. Here, we provide evidence that hypoxia causes economic impacts on a major fishery. Ecological studies of hypoxia and marine fauna suggest multiple mechanisms through which hypoxia can skew a population's size distribution toward smaller individuals. These mechanisms produce sharp predictions about changes in seafood markets. Hypoxia is hypothesized to decrease the quantity of large shrimp relative to small shrimp and increase the price of large shrimp relative to small shrimp...
February 14, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28129333/dynamic-portfolio-strategy-using-clustering-approach
#17
Fei Ren, Ya-Nan Lu, Sai-Ping Li, Xiong-Fei Jiang, Li-Xin Zhong, Tian Qiu
The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion...
2017: PloS One
https://www.readbyqxmd.com/read/28076383/time-varying-transition-probability-matrix-estimation-and-its-application-to-brand-share-analysis
#18
Tomoaki Chiba, Hideitsu Hino, Shotaro Akaho, Noboru Murata
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions...
2017: PloS One
https://www.readbyqxmd.com/read/28074782/the-need-for-a-life-cycle-based-aging-paradigm-for-nanomaterials-importance-of-real-world-test-systems-to-identify-realistic-particle-transformations
#19
Denise M Mitrano, Bernd Nowack
Assessing the risks of manufactured nanomaterials (MNM) has been almost exclusively focused on the pristine, as-produced materials with far fewer studies delving into more complex, real world scenarios. However, when considering a life-cycle perspective, it is clear that MNM released from commercial products during manufacturing, use and disposal are far more relevant both in terms of more realistic environmental fate and transport as well as environmental risk. The quantity in which the particles are released and their (altered) physical and chemical form should be identified and it is these metrics that should be used to assess the exposure and hazard the materials pose...
January 11, 2017: Nanotechnology
https://www.readbyqxmd.com/read/28070548/stock-market-index-data-and-indicators-for-day-trading-as-a-binary-classification-problem
#20
Renato Bruni
Classification is the attribution of labels to records according to a criterion automatically learned from a training set of labeled records. This task is needed in a huge number of practical applications, and consequently it has been studied intensively and several classification algorithms are available today. In finance, a stock market index is a measurement of value of a section of the stock market. It is often used to describe the aggregate trend of a market. One basic financial issue would be forecasting this trend...
February 2017: Data in Brief
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