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A virtual enterprise (VE) is always in an environment with unpredictable change and dynamic markets. Therefore, a VE is more susceptible to risks. Minimizing risk in the operation of a project and ensuring success are major issues to concern in VEs. This paper develops a novel three-level dynamic risk-management planning model for VEs focusing on project organization mode and dynamic features of risk with the objective to maximize the completion probability under the constraints of cost, due date, and quality. The first level adopts non-linear integer programming techniques, the second level is about risk evaluation for the whole project based on network analysis, and the third level is on a Markov process based single process risk evaluation. An algorithm of integrated genetic algorithm plus simulated annealing/critical path method/Markov (GA---SA/CPM/Markov) is then designed to solve the problem and compared with GA and SA respectively. Experimental results show that the proposed algorithm is effective and the three-level model can deal with dynamic risks for VEs.

Heterosis (or hybrid vigor) is a natural phenomenon whereby hybrid offspring of genetically diverse individuals display improved physical and functional characteristics relative to their parents. Heterosis has been increasingly applied in crop production for nearly a century, with the aim of developing more vigorous, higher yielding and better performing cultivars. In this review we present and compare three categories of crop heterosis utilization: intraspecific heterosis, intersubspecific heterosis and wide-hybridization heterosis, with particular focus on polyploid species. Different pollination-control systems used to breed for heterosis are also comparatively analyzed. Finally, we highlight problems involved in heterosis research and crop improvement. We aim to provide insight into best practices for amplifying heterosis potential.

Constant looper height and small tension control is a basic characteristic of modern hot rolling mill. The control quality of looper system affects directly performances in the width and thickness of a product. A looper system has the features of nonlinearity, strong coupling, uncertainty, and multi-constraints. In this paper, a dynamic mathematical model of looper system is set up based on 1700ASP. In addition, multiple-input multiple-output (MIMO) space model at the vicinity of working point has been deduced. A new control strategy-fuzzy sliding mode control is introduced to decouple the system by using two filters to smooth control signal and to suppress output noise, respectively. Simulation results show that the algorithm is effective and has better control effect in resisting disturbance and weakening chattering after this system is decoupled.

Risk exists in the course of a project operation. Hence, selecting a good risk management strategy is essential for project success. In this paper, a two-phase evaluating method is proposed focusing on the characteristics of dynamic risk and multi attributes. Considering dynamic risk in a project, Markov process is used to evaluate risk in the first phase. And then, this paper explores how to select risk management strategy based on technique for order preference by similarity to ideal solution (TOPSIS) in view of completion time, cost, quality and success probability factors. Finally, a numerical example shows that this method is effective for decision making in project risk management.

A project consists of many subprojects with precedence. Subprojects' completion times are often uncertain due to many factors from inside and outside environment, which makes the project's completion time uncertain. In such case, the project cannot be delivered on time leading to tardiness risk. To address this uncertainty, we provide a risk measure-value at risk (VaR). A model with the objective to minimizing VaR is built to describe and quantify the tardiness risk. The proposed model is compared to Monte Carlo simulation. Comparison results show that this proposed method can replace Monte Carlo simulation in measuring tardiness risk.

Considering the features of coupling, multivariable, and nonlinearity in thickness and tension system for cold-rolling, this paper proposes a dynamic coupling model. Furthermore, a new compound decoupling control algorithm is designed based on diagonal recurrent neural network combined with PID(DRNN-PID) for decoupling control. Simulation results show the proposed algorithm has stronger adaptive tracking, faster response, and better anti-interference than PID. The performances can meet the requirement of practical rolling and effectively enhance the control accuracy of thickness and tension.

Heterosis (or hybrid vigor) refers to a natural phenomenon whereby hybrid offspring of genetically diverse individuals out-perform their parents in multiple traits including yield, adaptability and resistances to biotic and abiotic stressors. Innovations in technology and research continue to clarify the mechanisms underlying crop heterosis, however the intrinsic relationship between the biological basis of heterosis remain unclear. In this review, we aim to provide insight into the molecular genetic basis of heterosis by presenting recent advances in the 'omics' of heterosis and the role of non-coding regions, particularly in relation to energy-use efficiency. We propose that future research should focus on integrating the expanding datasets from different species and hybrid combinations, to mine key heterotic genes and unravel interactive 'omics' networks associated with heterosis. Improved understanding of heterosis and the biological basis for its manipulation in agriculture should help to streamline its use in enhancing crop productivity.

With the emergence of global economy and in order to respond fast to the constantly changing market demand, virtual enterprises arise at this historic moment. Risk management of virtual enterprise draws attentions of researchers. This paper proposes a three-level model to deal with the dynamic risk of virtual enterprise, based on nonlinear integer programming, network analysis, and Markov process. The model focuses on project organization mode and dynamic features of risk in virtual enterprise. It helps to determine the completion time of each process with the objectives of maximizing the minimum completion probability of all processes under the constraints of project investment, customers' due dates, and process quality. Furthermore, an algorithm of integrated GA/CPM/Markov is designed to solve the problem and its efficiency is shown by instances analysis.

Generally, more than 120 ultrasonic sensors are necessary in a non-destructive testing (NDT) system for wide and thick steel plates. With the increase of the numbers of sensors, the system becomes more complex. It means that much higher automatization level is required in the parameters setting and much higher efficiency is demanded on data transmission in the network. This paper presents a novel ultrasonic NDT system based on the Ethernet network. The system accommodates 196 sensors and can detect plates with 4.8-meter width. The solution solves the data communication problem successfully. New technologies on hardware and software are introduced to improve the automatization level. All endeavors we have made ensure the new detection system can set parameters, adjust parameters automatically and complete the whole detection task automatically. In this paper, the network topology, network configuration and measures on real-time data transmission are also discussed. It is proved that the system is feasible in practice.

With the emergence of global market economy and in order to respond fast to the constantly changing market demand, virtual enterprises arise at this historic moment. Risk management of virtual enterprise draws attentions of researchers. This paper proposes a three-level programming model to deal with the dynamic risk of virtual enterprise, based on non-linear integer programming, network analysis, and Markov Process. The model focuses on project organization mode and dynamic features of risk in virtual enterprise. It helps to determine the completion time of each process with the objectives of maximizing the minimum completion probability of all processes under the constraints of project investment, customers' due dates, and process quality. Furthermore, an algorithm of integrated SA/CPM/Markov is designed to solve the problem and its efficacy is shown by instances.