功能性小麦品种的概念、类别和发展前景（网络首发、推荐阅读）

结合全球倡导的营养导向型农业和功能性食品的内容，首次提出“功能性小麦品种”的概念，将其定义为“含有对人体健康有益的活性成分，可调节人体有益代谢，能给人体健康带来某种益处或满足特定人群的特殊需求，同时可以作为日常食物的口感正常、无毒副作用的小麦品种类型”；结合疫情警示和我国进入后工业时代后，人们需求必将由“吃得饱”、“吃得好”向“吃得健康”转变，因而提出继高产品种、优质品种之后培育“功能性小麦品种”的育种目标。根据多年关于小麦淀粉、蛋白、酯类和其他成分的功能研究结果，介绍新育成的“麦黄酮”、“高色素”、“高抗性淀粉”、“富锌”、“低醇溶蛋白”和“低植酸”等功能性小麦新品种（系）的营养特性和农艺产量状况；根据“健康中国2030”规划等国家战略，进行“功能性品种培育是解决我国功能性食品‘卡脖子’的关键基础，一种功能性品种可以形成一类功能性食品，多种功能性品种可以形成我国功能性面制品产业，推动我国整个食品工业的发展”的前景展望；根据功能性品种及其食品的稳定性和可靠性是产品和市场的“生命线”，从对消费者负责的高度，提出关于“功能性农作物品种审定导向和组建功能性成分检测机构；编制有关功能性品种和食品的国家或行业标准，设立功能性食品和功能性农作物品种的商业标志，保证我国功能性农作物品种及其食品健康发展”等方面的具体建议。     

KSUTraffic: A Microscopic Traffic Simulator for Traffic Planning in Smart Cities

Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number of incidents. Unfortunately, employing simulation to provide effective traffic management for local scenarios in Saudi Arabia is limited to a number of commercial products in both public and private sectors. Commercial simulators are usually expensive, closed source and inflexible as they allow limited functionalities. In this project, we developed a local traffic simulator “KSUtraffic” for traffic modeling, planning and analysis with respect to different traffic control strategies and considerations. We modeled information specified by GIS and real traffic data. Furthermore, we designed experiments that manipulate simulation parameters and the underlying area. KSUTraffic visualizes traffic and provides statistical results on the simulated traffic which would help to improve traffic management and efficiency.     

A fast genetic algorithm for a critical protection problem in biomedical supply chain networks

In this paper, we present a new bilevel model for a biomedical supply chain network with capacity and budget constraint due to the protection and interdiction operations. The components considered in this model are biomedical devices, distribution centers (DCs), medical suppliers (MSs), and hospitals and patients as the demand points. On the other hand, two levels of decisions in the network planning is suggested: (1) the defender’s decision about protection operations of MSs and DCs, the assignment of clients to the DCs, and quantity of products shipped to DCs from MSs to minimize the demand-weighted traveling costs and transport costs and (2) the attacker’s decision about interdiction operations of MSs and DCs to maximize the capacity or service reduction and losses. Because of nondeterministic polynomial time (NP)-hardness of the problem under consideration, an efficient and fast approach based on a genetic algorithm and a fast branch and cut method (GA–FBC) was developed to solve the proposed model. Also, the efficiency via the comparison of results with the genetic algorithm based on CPLEX (GA-CPLEX) and decomposition method (DM) is investigated. In order to assess the performance of the presented GA–FBC, a set of 27 instances of the problem is used. Comprehensive analysis indicates that the proposed approach significantly solves the problem. In addition, the benefits and advantages of preference with running times and its accuracy is shown numerically. Simulation results clearly demonstrate that the defender’s objective effectively reduced and CPU time also within the large-sized instances of the problem in comparison with the GA-CPLEX and DM.     

The Art of Masonry

Brick masonry is not only a question of building physics, building construction and durability, i.e. sustainability, but has much to do with aesthetics and making sense, which may have been forgotten in modern architecture with its absolute lack of décor. Masonry as an art form has been scarce since the era of brick expressionism. Recently, there have been some exceptions – and thoroughly welcome. The ”Fjordenhus“ in Vejle, Denmark, is an astonishing example.     

基于stackelberg多步博弈的无人机协同搜索路径规划

考虑到现有无人机搜索问题研究中无人机、移动目标仅有一方具有远距离探测能力的设定，已经无法体现出战场环境下双方的博弈关系。针对这一不足，基于stackelberg均衡策略，结合多步预测的思想，提出了stackelberg多步博弈策略，实现了无人机、目标都具有远距离探测能力的博弈搜索。通过建立无人机、目标各自的路径收益函数，使双方能够根据不同时刻的博弈状态选择相对应的函数，实现无人机的动态路径规划。仿真结果表明所提出策略完全适用于该博弈模型，比贪婪策略具有更高的搜索效率，大大提高了目标捕获率。     

Generation-expansion planning with linearized primary frequency response constraints

As renewable energy resources increasingly penetrate the electric grid, the inertia capability of power systems has become a developmental bottleneck. Nevertheless, the importance of primary frequency response (PFR) when making generation-expansion plans has been largely ignored. In this paper, we propose an optimal generation-expansion planning framework for wind and thermal power plants that takes PFR into account. The model is based on the frequency equivalent model. It includes investment, startup/shutdown, and typical operating costs for both thermal and renewable generators. The linearization constraints of PFR are derived theoretically. Case studies based on the modified IEEE 39-bus system demonstrate the efficiency and effectiveness of the proposed method. Compared with methods that ignore PFR, the method proposed in this paper can effectively reduce the cost of the entire planning and operation cycle, improving the accommodation rate of renewable energy.     

An analysis of adaptive planning capacity: The case of chilean water utilities

New long-term planning approaches capable of coping with uncertainties such as climate change, rapid urbanization, and changing societal values, have been put forward as a way of producing more robust and sustainable plans for the future. But is the planning practice ready for their adoption? This paper takes four key propositions from the adaptive planning literature and tests the existing capacity for adopting those propositions in the context of Chilean water utilities. We will then propose how existing capacities could be enhanced, and propose alternatives for current planning practices, highlighting the importance of implementation through experimentation.     

Team O2AS at the world robot summit 2018: an approach to robotic kitting and assembly tasks using general purpose grippers and tools

ABSTRACT

In this article, we propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger grippers to grasp and hold tools to perform subtasks such as screwing and suctioning. A third gripper is used as a precision picking and centering tool, and uses in-built passive compliance to compensate for small position errors and uncertainty. A novel grasp point detection for bin picking is described for the kitting task, using a single depth map. Using the proposed system we competed in the Assembly Challenge of the Industrial Robotics Category of the World Robot Challenge at the World Robot Summit 2018, obtaining 4th place and the SICE award for lean design and versatile tool use. We show the effectiveness of our approach through experiments performed during the competition.     

In Silico Study on Tumor-Size-Dependent Thermal Profiles inside an Anthropomorphic Female Breast Phantom Subjected to Multi-Dipole Antenna Array

Electromagnetic hyperthermia as a potent adjuvant for conventional cancer therapies can be considered valuable in modern oncology, as its task is to thermally destroy cancer cells exposed to high-frequency electromagnetic fields. Hyperthermia treatment planning based on computer in silico simulations has the potential to improve the localized heating of breast tissues through the use of the phased-array dipole applicators. Herein, we intended to improve our understanding of temperature estimation in an anatomically accurate female breast phantom embedded with a tumor, particularly when it is exposed to an eight-element dipole antenna matrix surrounding the breast tissues. The Maxwell equations coupled with the modified Pennes’ bioheat equation was solved in the modelled breast tissues using the finite-difference time-domain (FDTD) engine. The microwave (MW) applicators around the object were modelled with shortened half-wavelength dipole antennas operating at the same 1 GHz frequency, but with different input power and phases for the dipole sources. The total input power of an eight-dipole antenna matrix was set at 8 W so that the temperature in the breast tumor did not exceed 42 °C. Finding the optimal setting for each dipole antenna from the matrix was our primary objective. Such a procedure should form the basis of any successful hyperthermia treatment planning. We applied the algorithm of multi for multi-objective optimization for the power and phases for the dipole sources in terms of maximizing the specific absorption rate (SAR) parameter inside the breast tumor while minimizing this parameter in the healthy tissues. Electro-thermal simulations were performed for tumors of different radii to confirm the reliable operation of the given optimization procedure. In the next step, thermal profiles for tumors of various sizes were calculated for the optimal parameters of dipole sources. The computed results showed that larger tumors heated better than smaller tumors; however, the procedure worked well regardless of the tumor size. This verifies the effectiveness of the applied optimization method, regardless of the various stages of breast tumor development.