Thomson backscattering in combined two laser and magnetic field

The Thomson backscattering of an electron moving in combined fields is studied by a dynamically assisted mechanism. The combined fields are composed of two co-propagating laser fields and a magnetic field, where the first laser field is strong and low-frequency while the second is weak and high-frequency, relatively. The dependence of fundamental frequency of emission on the ratio of incident laser high-to-low frequency is presented and the spectrum of backscattering is obtained. It is found that, with a magnetic field, the peak of the spectrum and the corresponding radiation frequency are significantly larger in case of two-laser than that in case of only one laser. They are also improved obviously as the frequency of the weak laser field. Another finding is the nonlinear correlation between the emission intensity of the backscattering and the intensity of the weak laser field. These results provide a new possibility to adjust and control the spectrum by changing the ratios of frequency and intensity of the two laser fields.Comment: 13 pages, 4 figure

Study of Scalar Mesons at BES-II

Recent results from BES-II experiment on hadron spectroscopy using \jpsi and $\psi^\prime$ data samples collected in $e^+e^-$ annihilation are presented, including study of the scalar particles in \jpsi radiative and hadronic decays, the observation of X(1810) in $J/\psi \to \gamma \phi \omega$, as well as pair productions of scalars in $\chi_{c0}$ hadronic decays.Comment: Talk on "Hadron spectroscopy at BES" at "From Phi to Psi" Workshop February 27 - March 2, 2006, Novosibirsk, Russi

A dynamic truck dispatching problem in marine container terminal

In this paper, a dynamic truck dispatching problem of a marine container terminal is described and discussed. In this problem, a few containers, encoded as work instructions, need to be transferred between yard blocks and vessels by a fleet of trucks. Both the yard blocks and the quay are equipped with cranes to support loading/unloading operations. In order to service more vessels, any unnecessary idle time between quay crane (QC) operations need to be minimised to speed up the container transfer process. Due to the unpredictable port situations that can affect routing plans and the short calculation time allowed to generate one, static solution methods are not suitable for this problem. In this paper, we introduce a new mathematical model that minimises both the QC makespan and the truck travelling time. Three dynamic heuristics are proposed and a genetic algorithm hyperheuristic (GAHH) under development is also described. Experiment results show promising capabilities the GAHH may offer

Evolution of spatial and temporal patterns of railway container transportation: A case study of China cities

The healthy development of railway container transport is an important part of railway freight transport and is key for promoting the green transformation of China's transport and supporting a new pattern of transport development. In this study, railway container handling station (RCHS) data, kernel density analysis, standard deviation ellipse, Herfindahl–Hirschman index (HHI), trend surface analysis (TSA), and R index were applied to examine the evolution characteristics of container transport patterns after the market-oriented reform of China's railway freight transport in 2013. The results are as follows: First, the overall scale growth trend is obvious, and the double-center effect of transport scale on the Bohai Rim region and Chengdu–Chongqing Economic Zone is evident, with the transport center of gravity moving northward. Second, the amount of attraction/occurrence is consistent in spatial distribution, and the aggregation effect of both is similar, essentially exhibiting a tendency of being high in the northwest and low in the southeast. Third, the pattern of “export-oriented in the north and import-oriented in the south” has taken shape; nearly half of cities in China have stable traffic functions, stable traffic supply, and demand relationships, and the change of functions shows that the industrial structure is constantly upgrading. This study elucidates the pattern of railway container transport in cities in China and provides empirical guidance for adjusting the functions of urban freight transport, thereby promoting the healthy development of urban freight transport and optimizing urban transport planning

Spatiotemporal features of microsporogenesis in the cycad species Macrozamia communis

Plant Biology, Ecology and Evolutio

Drones and Blockchain Integration to Manage Forest Fires in Remote Regions

Central management of fire stations and traditional optimization strategies are vulnerable to response time, a single point of failure, workload balancing, and cost problems. This is further intensified by the absence of modern communication systems and a comprehensive management framework for firefighting operations. These problems motivate the use of new technologies such as unmanned aerial vehicles (UAVs) with the capability to transport extinguishing materials and reach remote zones. Forest fire management in remote regions can also benefit from blockchain technology (BC) due to the facilitation of decentralization, tamper-proofing, immutability, and mission recording in distributed ledgers. This study proposed an integrated drone-based blockchain framework in which the network users or nodes include drones, drone controllers, firefighters, and managers. In this distributed network, all nodes can have access to data; therefore, the flow of data exchange is smooth and challenges on spatial distance are minimized. The research concluded with a discussion on constraints and opportunities in integrating blockchain with other new technologies to manage forest fires in remote regions

Cooperative Double-Layer Genetic Programming Hyper-Heuristic for Online Container Terminal Truck Dispatching

In a marine container terminal, truck dispatching is a crucial problem that impacts on the operation efficiency of the whole port. Traditionally, this problem is formulated as an offline optimisation problem, whose solutions are, however, impractical for most real-world scenarios primarily because of the uncertainties of dynamic events in both yard operations and seaside loading–unloading operations. These solutions are either unattractive or infeasible to execute. Herein, for more intelligent handling of these uncertainties and dynamics, a novel cooperative double-layer genetic programming hyper-heuristic (CD-GPHH) is proposed to tackle this challenging online optimisation problem. In this new CD-GPHH, a novel scenario genetic programming (GP) approach is added on top of a traditional GP method that chooses among different GP heuristics for different scenarios to facilitate optimised truck dispatching. In contrast to traditional arithmetic GP (AGP) and GP with logic operators (LGP) which only evolve on one population, our CD-GPHH method separates the scenario and the calculation into two populations, which improved the quality of solutions in multi-scenario problems while reducing the search space. Experimental results show that our CD-GPHH dominates AGP and LGP in solving a multi-scenario function fitting problem as well as a truck dispatching problem in container terminal