Effect of High Se and Co Alfalfa Forage on Animal Production

Total and available selenium (Se) and cobalt (Co) concentrations are low in Chinese soils, especially those found in mainly in temperate humid sub-humid conditions in the northeast to the southwest band across China (Tan et al. 2002). The levels of Se and Co are marginally deficit in the brown soil of the Yellow River region which causes lower production level and quality in forage and crop plants. Application of Se and Co fertilizers to arable lands is essential to produce high Se and Co forages. Henan is a Province where produce high-quality grass forages are used to support dairy farming. The province is mainly spread along the Yellow River where soils are sandy and deficient in Se and Co (Lu et al. 2003). Se deficiency in forages not only limits livestock production, but also affects the quality and safety of food products (Rotruck et al. 2003). Since rabbits and dairy cows are especially sensitive to low Se levels in feed, we chose these as our test animals. The objective of this study was to analyze effect of high Se and Co alfalfa forage on animal production and feed conversion efficiency in order to establish a set of effective technical ways to solve trace element gaps of animal diets, i.e. by basal fertilization of Se and Co fertilizers in soil. This study was conducted as a series of field trials and animal experiments from 2007 to 2008

Effects of Se and Co Combined Fertilizer on Production of Alfalfa

Selenium(Se) and cobalt (Co) are important essential trace elements for forage and animal production (Yang et al. 1998, Arvy 1993). The supplementation of Se in animal diet significantly increases Se-Glutathione peroxidase (GSH-Px ) activities in the liver, testes, spermatozoa and seminal plasma (Abdelrahman et al.1998), Selenium is also a key component of a number of functional seleno-proteins. GSH-Px is the best characterized of the family of selenoproteins. In Henan Province, the fine grass and green milk production zones are mainly distributed along the riverbank of the Yellow River where soils are sandy and sterile with lower Se and Co contents (Lu et al. 2003). Deficiency of Se and Co in soils affects local forage and animal production level, as well as the qualities and securities of fodder and animal products (Rotruck et al. 2003). This experiment was carried out to determine the impacts of the application combined Se and Co on the quality of alfalfa hay

Dynamic Flow-Adaptive Spectrum Leasing with Channel Aggregation in Cognitive Radio Networks

Cognitive radio networks (CRNs), which allow secondary users (SUs) to dynamically access a network without affecting the primary users (PUs), have been widely regarded as an effective approach to mitigate the shortage of spectrum resources and the inefficiency of spectrum utilization. However, the SUs suffer from frequent spectrum handoffs and transmission limitations. In this paper, considering the quality of service (QoS) requirements of PUs and SUs, we propose a novel dynamic flow-adaptive spectrum leasing with channel aggregation. Specifically, we design an adaptive leasing algorithm, which adaptively adjusts the portion of leased channels based on the number of ongoing and buffered PU flows. Furthermore, in the leased spectrum band, the SU flows with access priority employ dynamic spectrum access of channel aggregation, which enables one flow to occupy multiple channels for transmission in a dynamically changing environment. For performance evaluation, the continuous time Markov chain (CTMC) is developed to model our proposed strategy and conduct theoretical analyses. Numerical results demonstrate that the proposed strategy effectively improves the spectrum utilization and network capacity, while significantly reducing the forced termination probability and blocking probability of SU flows.publishedVersio

2-(2,4,6-Trichloro­phen­oxy)ethyl bromide

In the title compound, C8H6BrCl3O, there is a weak intra­molecular C—H⋯Cl hydrogen bond involving the O bound methylene group. Intermolecular Cl⋯Cl contacts [3.482 (2) Å] are present in the crystal structure

Thermodynamic Properties of Nano-Silver and Alloy Particles

Non

Enabling controlling complex networks with local topological information

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulflling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired fnal state in fnite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefned state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efciently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.The work was partially supported by National Science Foundation of China (61603209), and Beijing Natural Science Foundation (4164086), and the Study of Brain-Inspired Computing System of Tsinghua University program (20151080467), and Ministry of Education, Singapore, under contracts RG28/14, MOE2014-T2-1-028 and MOE2016-T2-1-119. Part of this work is an outcome of the Future Resilient Systems project at the Singapore-ETH Centre (SEC), which is funded by the National Research Foundation of Singapore (NRF) under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. (61603209 - National Science Foundation of China; 4164086 - Beijing Natural Science Foundation; 20151080467 - Study of Brain-Inspired Computing System of Tsinghua University program; RG28/14 - Ministry of Education, Singapore; MOE2014-T2-1-028 - Ministry of Education, Singapore; MOE2016-T2-1-119 - Ministry of Education, Singapore; National Research Foundation of Singapore (NRF) under Campus for Research Excellence and Technological Enterprise (CREATE) programme)Published versio

Author correction: Enabling controlling complex networks with local topological information

Correction to: Scientific Reports https://doi.org/10.1038/s41598-018-22655-5, published online 15 March 2018. The Acknowledgements section in this Article is incomplete.The work was partially supported by National Science Foundation of China (61603209, 61327902), and Beijing Natural Science Foundation (4164086), and the Study of Brain-Inspired Computing System of Tsinghua University program (20151080467), and SuZhou-Tsinghua innovation leading program 2016SZ0102, and Ministry of Education, Singapore, under contracts RG28/14, MOE2014-T2-1-028 and MOE2016-T2-1-119. Part of this work is an outcome of the Future Resilient Systems project at the Singapore-ETH Centre (SEC), which is funded by the National Research Foundation of Singapore (NRF) under its Campus for Research Excellence and Technological Enterprise (CREATE) program. (61603209 - National Science Foundation of China; 61327902 - National Science Foundation of China; 4164086 - Beijing Natural Science Foundation; 20151080467 - Study of Brain-Inspired Computing System of Tsinghua University program; 2016SZ0102 - SuZhou-Tsinghua innovation leading program; RG28/14 - Ministry of Education, Singapore; MOE2014-T2-1-028 - Ministry of Education, Singapore; MOE2016-T2-1-119 - Ministry of Education, Singapore; National Research Foundation of Singapore (NRF) under its Campus for Research Excellence and Technological Enterprise (CREATE) program)Published versio