Sustainable Development of Agriculture and Animal Husbandry in Tibet Based on "Resource Saving and Environment Friendly"

During the ＂13th five-year＂ period,Tibet is building a well-off society in an all-round way and constructing a harmonious socialist new countryside. The pace of economic construction in the west is advanced step by step,and all kinds of economic construction subjects show obvious increasing trend. As one of the regions with rich agriculture and animal husbandry resources,it is inevitable to face the problems that wild resources are gradually consumed,and environmental pollution is severe in Tibet. While developing the economy,it must not damage the environment. To a certain extent,the resource and environment infrastructure is the material basis for economic development. With the gradual progress of economic construction,improvement of residents＇ living standards,and updating of consumption structure,it needs to build,produce and live in the environment of ＂ beautiful Tibet with clean water,blue sky and green＂. In this paper,based on resource-saving and environment-friendly angle,it sufficiently understands the importance and urgency of accelerating sustainable development of agriculture and animal husbandry in Tibet from the global and strategic heights. It should accelerate Tibet agriculture and animal husbandry taking ＂ resource-saving and environment-friendly＂,put the sustainable development of agriculture and animal husbandry in an important historical development opportunity,and impel large economic development of plateau agriculture and animal husbandry.

Environmental risks of shale gas exploitation and solutions for clean shale gas production in China

Shale gas is a relatively clean-burning fossil fuel,produced by hydraulic fracturing.This technology may be harmful to the environment;therefore,environmentally friendly methods to extract shale gas have attracted considerable attention from researchers.Unlike previous studies,this study is a comprehensive investigation that uses systematic analyses and detailed field data.The environmental challenges associated with shale gas extraction,as well as measures to mitigate environmental impacts from the source to end point are detailed,using data and experience from China’s shale gas production sites.Environmental concerns are among the biggest challenges in practice,mainly including seasonal water shortages,requisition of primary farmland,leakage of drilling fluid and infiltration of flowback fluid,oil-based drill cuttings getting buried underground,and induced seismicity.China’s shale gas companies have attempted to improve methods,as well as invent new materials and devices to implement cleaner processes for the sake of protecting the environment.Through more than 10-year summary,China’s clean production model for shale gas focuses on source pollution prevention,process control,and end treatment,which yield significant results in terms of resource as well as environmental protection,and can have practical implications for shale gas production in other countries,that can be duplicated elsewhere.

Adaptive Data-Driven Wideband Compressive Spectrum Sensing for Cognitive Radio Networks

This paper presents a novel adaptive wide-band compressed spectrum sensing scheme for cognitive radio(CR)networks.Compared to the traditional CSS-based CR scenarios,the proposed approach reconstructs neither the received signal nor its spectrum during the compressed sensing procedure.On the contrary,a precise estimation of wide spectrum support is recovered with a fewer number of compressed measurements.Then,the spectrum occupancy is determined directly from the reconstructed support vector.To carry out this process,a data-driven methodology is utilized to obtain the mini-mum number of necessary samples required for support reconstruction,and a closed-form expression is obtained that optimally estimates the number of desired samples as a function of the sparsity level and number of channels.Following this phase,an adjustable sequential framework is developed where the first step predicts the optimal number of compressed measurements and the second step recovers the sparse support and makes sensing decision.Theoretical analysis and numerical simulations demonstrate the improvement achieved with the proposed algorithm to significantly reduce both sampling costs and average sensing time without any deterioration in detection performance.Furthermore,the remainder of the sensing time can be employed by secondary users for data transmission,thus leading to the enhancement of the total throughput of the CR network.