8,410 research outputs found
Farming Shrimp for the Future: A Sustainability Analysis of Shrimp Farming in China.
The intensification of the shrimp farming industry has generated much concern over its environmental, social and economic sustainability. The objective of this dissertation was to conduct a comprehensive sustainability analysis for Chinese shrimp farming. My results could be utilized to evaluate and improve shrimp production systems in terms of environmental sustainability, economic profitability, and social acceptability.
Life cycle assessment was conducted to evaluate environmental performance of different shrimp farming systems. Intensive systems had higher environmental impacts per unit production than semi-intensive. The grow-out stage contributed on average 95% of the overall impacts, mainly caused by feed production, electricity use and effluents. To produce 1 tonne live-weight of shrimp in China, 38.3±4.3 GJ of energy and 40.4±1.7 tonnes of net primary productivity were required, and 23.1±2.6 kg of SO2 equivalents (eq), 36.9±4.3 kg of PO4 eq, and 3.1±0.4 tonnes of CO2 eq were generated. Changes in feed composition, farm management, electricity generating sources, and effluent treatment may result in future improvement.
Mathematical models were developed to study nutrient dynamics and the effects of management strategies on nutrient dynamics and discharge. Management strategies had significant impacts on nutrient dynamics. Nutrient loading increased with farm intensity. On average, approximately 701 kg N ha-1 cycle-1 (100 days/cycle) and 176 kg P ha-1 cycle-1 were unutilized and wasted. Of them, 120 kg N ha-1 cycle-1 in dissolved form and 62 kg P ha-1 cycle-1 were discharged with effluents. Moderate stocking density and reduced water exchange could minimize environmental impacts of pond effluents and achieve high production.
A socioeconomic survey of 100 shrimp farms was conducted to evaluate system profitability, disease risk, and changes in quality of life. Production costs per kilogram of shrimp were highest in intensive systems (2.10) and polyculture (9,500 ha-1 crop-1) than the other two systems (< $7,300 ha-1 crop-1). If disease occurred, an average of 78% and 36% of shrimp would die in the worst and most probable cases, respectively. Disease had highest influence on the intensive systems. Quality of life of farmers was significantly improved by shrimp farming.Ph.D.Natural Resources and EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91554/1/caoling_1.pd
Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image
As a new machine learning approach, extreme learning machine (ELM) has
received wide attentions due to its good performances. However, when directly
applied to the hyperspectral image (HSI) classification, the recognition rate
is too low. This is because ELM does not use the spatial information which is
very important for HSI classification. In view of this, this paper proposes a
new framework for spectral-spatial classification of HSI by combining ELM with
loopy belief propagation (LBP). The original ELM is linear, and the nonlinear
ELMs (or Kernel ELMs) are the improvement of linear ELM (LELM). However, based
on lots of experiments and analysis, we found out that the LELM is a better
choice than nonlinear ELM for spectral-spatial classification of HSI.
Furthermore, we exploit the marginal probability distribution that uses the
whole information in the HSI and learn such distribution using the LBP. The
proposed method not only maintain the fast speed of ELM, but also greatly
improves the accuracy of classification. The experimental results in the
well-known HSI data sets, Indian Pines and Pavia University, demonstrate the
good performances of the proposed method.Comment: 13 pages,8 figures,3 tables,articl
Signature of Pseudo Nambu-Goldstone Higgs boson in its Decay
If the Higgs boson is a pseudo Nambu-Goldstone boson (PNGB), the
contact interaction induced by the invariants of the
non-linear sigma model is free from its nonlinearity effects. The process
can be used to eliminate the universal effects of heavy
particles, which can fake the nonlinearity effects of the PNGB Higgs boson in
the process (,\ ). We demonstrate that the
ratio of the signal strength of and
is good to distinguish the signature of the PNGB Higgs boson from Higgs
coupling deviations
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