Ex post demand information sharing between differentiated suppliers and a common retailer

We consider ex post demand information sharing in a two-echelon supply chain in which two suppliers sell differentiated products through a common retailer. We model three scenarios of information sharing to characterise the conditions under which information sharing may benefit or hurt different players: (1) no supplier is informed; (2) only one supplier is informed; and (3) both suppliers are informed. We find that the retailer may voluntarily share the low demand information when the product differentiation and demand magnitude satisfy certain conditions. In contrast, the retailer has no incentive to share the high demand information, even though this information benefits the suppliers. To achieve information sharing, we propose a side payment mechanism, which allows benefitted players to subsidise hurtful players. Finally, we extend our model by considering a situation where the suppliers have limited capacity and may invest to ramp up production capacity to satisfy a high demand.     

Data envelopment analysis based on team reasoning

Existing approaches to data envelopment analysis focus mainly on the derivation of the efficiency of the individual decision‐making unit (DMU) or on the calculation of the weights of multiple inputs or outputs, but pay little attention to the team interest of all the DMUs. Motivated by the idea of team reasoning, in which the benefit of the team is of higher importance than that of each individual, this paper considers all the DMUs as a team and introduces the team indexes including the overall efficiencies, variance, boundaries of all the DMUs, and relationships between DMUs. Several models are first developed to estimate values of the team indexes based on which decision makers can provide their preferences regarding them. Then, models are established to obtain the interval efficiencies of individual DMUs under the condition that the team indexes are satisfied. Several examples are given to illustrate the proposed approaches and verify their applicability.     

Milk from cows fed a diet with a high forage:concentrate ratio improves inflammatory state,oxidative stress,and mitochondrial function in rats

Excessive energy intake may evoke complex biochemical processes characterized by inflammation, oxidative stress, and impairment of mitochondrial function that represent the main factors underlying noncommunicable diseases. Because cow milk is widely used for human nutrition and in food industry processing, the nutritional quality of milk is of special interest with respect to human health. In our study, we analyzed milk produced by dairy cows fed a diet characterized by a high forage:concentrate ratio (high forage milk, HFM). In view of the low n-6:n-3 ratio and high content of conjugated linoleic acid of HFM, we studied the effects of this milk on lipid metabolism, inflammation, mitochondrial function, and oxidative stress in a rat model. To this end, we supplemented for 4 wk the diet of male Wistar rats with HFM and with an isocaloric amount (82 kJ, 22 mL/d) of milk obtained from cows fed a diet with low forage:concentrate ratio, and analyzed the metabolic parameters of the animals. Our results indicate that HFM may positively affect lipid metabolism, leptin:adiponectin ratio, inflammation, mitochondrial function, and oxidative stress, providing the first evidence of the beneficial effects of HFM on rat metabolism.     

天然橡胶期货市场回顾及后市展望

2019年天然橡胶期货市场起起落落,沪胶价格继续低位震荡。2020年天然橡胶供大于求的局面仍不会发生根本性改变,由极端天气引发的天然橡胶市场行情变动可能会减小,汽车行业可能会在政策支持下再次振兴,尤其重型卡车市场会成为亮点,轮胎企业继续寻求扩大出口。2020年上半年,天然橡胶期货市场可能还会受到2019年异常天气和病害等的余波作用,胶价会达到一个相对的高点,价格底部抬升,但很难出现持续性上涨的市场行情。2020年下半年,随着天然橡胶产量的季节性增长,胶价可能会再次回落。     

Optimal design of Raman fibre amplifier based on terminal value optimization strategy and shuffled frog leaping algorithm

This paper introduces an evolutionary algorithm, Shuffled Frog Leaping Algorithm (SFLA), to solve the optimization problem in designing the multi-pumped Raman Fibre Amplifier (RFA). SFLA is a powerful optimizer tool because of its efficient mathematical expressions and global search capability. We utilize SFLA to determine the optimal pump wavelengths and pump powers by minimizing the gain ripple of RFA. To accelerate calculations, a terminal value optimization strategy (TVOS) is incorporated into the evolution of SFLA. This proposed strategy takes the terminal power values of pumps as the decision variables in optimization. Then, the optimal original power values of the pumps are obtained by solving the Power Coupled Equations once, without using the traditional method of repetitive guesses.The combination of SFLA and TVOS enhances the efficiency of optimization and accelerates calculation, while satisfying the design requirements of RFA.The simulation results show that nearly 65% of computational time has been saved compared with the traditional average power analysis. The 4-pumped C+L band of backward multi-pumped RFA with the average net gain of 0 dB, 1 dB and 2 dB are designed individually, where the gain ripple is less than 0.64 dB. The combination of SFLA and TVOS enhance the optimization efficiency and improve the performance of RFA with good gain profile.     

Actuator fault tolerant control using adaptive RBFNN fuzzy sliding mode controller for coaxial octorotor UAV

In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial octorotor helicopter control is proposed in presence of actuator faults. Radial Base Function Neural Network (RBFNN), Fuzzy Logic Control approach (FLC) and Sliding Mode Control (SMC) technique are used to design a controller, named Fault Tolerant Control (FTC), for each subsystem of the octorotor helicopter. The proposed FTC scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller, and guaranteeing the stability and the robustness of the system. The simulation results show that the proposed FTC can greatly alleviate the chattering effect, good tracking in presence of actuator faults.     

Identification of nonlinear Wiener-Hammerstein systems by a novel adaptive algorithm based on cost function framework

This paper investigates parameter identification of nonlinear Wiener-Hammerstein systems by using filter gain and novel cost function. Taking into account the system information is corrupted by noise, the filter gain is exploited to extract the system data. By using several auxiliary filtered variables, an extended estimation error vector is developed. Then, based on the discount term of the extended estimation error and the penalty term on the initial estimate, a novel cost function is developed to obtain the optimal parameter adaptive law. Compared with the conventional cost function which is composed of the square sum of output error, the proposed algorithm based on the cost function of this paper can provide faster convergence rate and higher estimation accuracy. Furthermore, the convergence analysis of the proposed scheme indicates that the parameter estimation error can converge to zero. The effectiveness and practicality of the proposed scheme are validated through the simulation example and experiment on the turntable servo system.     

某型发动机自反馈调节阀动态仿真分析

基于FLUENT软件提供的计算方法和物理模型，利用动网格技术及用户自定义函数（User-define Function，UDF），对发动机预燃室调节阀的自反馈调节过程进行动态数值模拟，并分析阻尼参数对调节效果的影响。结果表明：自反馈机构可实现对不同压力扰动的及时响应，具有稳定流量的效果，改变阻尼参数可对调节响应速度和流量稳定性进行优化，其中摩擦力对调节影响最显著。     

Domestic demand-side response with heat pumps: controls and tariffs

ABSTRACT

Electric heat pumps feature prominently in projected energy transitions in the UK and elsewhere. Owing to their high electricity consumption, heat pumps are viewed as important targets for demand-side response (DSR). Findings are presented from a field trial of a new control system that aims to optimize heat pump performance, including under time-varying tariff conditions. The trial involved monitoring 76 properties with heat pumps, but without dedicated heat storage; 31 of these received the control system. Interviews were conducted with a subsample of 12 participants. The controller successfully evened out electricity demand over the day (reducing the evening peak), but this was associated with increased late night and daytime temperatures. Interview participants reported some disturbance owing to overnight heating and noise, as well as usability issues with the controller interface and hardware. These issues present risks to the future acceptability of such systems. While the system delivered short-term demand reductions successfully, longer-term demand shifting risked causing unacceptable disturbance to occupants. Future control systems could overcome some of the issues identified in this pioneering trial through more effective zoning, using temperature caps or installing dedicated heat storage, but these may either limit the available flexibility or be challenging to achieve.     

Oil Demand and Stocks

Current data of world oil demand. This includes international bunkers and refinery fuel. Updated on a monthly basis. Current data of oil demand from counties such as Canada, the United States of America, Japan, OECD Europe, Belgium, France, Germany, Italy, Netherlands, Spain, Sweden, the United Kingdom, Australia, Mexico, Republic of Korea, and Turkey. Updated on a monthly basis. Current data for crude oil and refined product stocks in Canada, Chile, Mexico, the United States (Western Hemisphere), France, Germany, Italy, Netherlands, Spain, the United Kingdom and Other Europe (Europe), Japan, Republic of Korea, Other Pacific (Asia-Pacific), and Total OECD (Table 12.1) Current data for refined product stocks in the OECD Western Hemisphere, OECD Europe, OECD Asia-Pacific and Total OECD. Products include gasoline, diesel and gasoil, and heavy fuel oil. Updated on a monthly basis (Table 12.2).