Design of multi-band frequency selective surfaces using multi-periodicity combined elements

Traditional multi-band frequency selective surface （FSS） approaches are hard to achieve a perfect resonance response in a wide band due to the limit of the onset grating lobe frequency determined by the array. To solve this problem, an approach of combining elements in different period to build a hybrid array is presented. The results of series of numerical simulation show that multi-periodicity combined element FSS, which are designed using this approach, usually have much weaker grating lobes than the traditional FSS. Furthermore, their frequency response can be well predicted through the properties of their member element FSS. A prediction method for estimating the degree of expected grating lobe energy loss in designing multi-band FSS using this approach is provided.

Simulation of methane adsorption in diverse organic pores in shale reservoirs with multi-period geological evolution

In shale reservoirs,the organic pores with various structures formed during the thermal evolution of organic matter are the main storage site for adsorbed methane.However,in the process of thermal evolution,the adsorption characteristics of methane in multi type and multi-scale organic matter pores have not been sufficiently studied.In this study,the molecular simulation method was used to study the adsorption characteristics of methane based on the geological conditions of Longmaxi Formation shale reservoir in Sichuan Basin,China.The results show that the characteristics of pore structure will affect the methane adsorption characteristics.The adsorption capacity of slit-pores for methane is much higher than that of cylindrical pores.The groove space inside the pore will change the density distribution of methane molecules in the pore,greatly improve the adsorption capacity of the pore,and increase the pressure sensitivity of the adsorption process.Although the variation of methane adsorption characteristics of different shapes is not consistent with pore size,all pores have the strongest methane adsorption capacity when the pore size is about 2 nm.In addition,the changes of temperature and pressure during the thermal evolution are also important factors to control the methane adsorption characteristics.The pore adsorption capacity first increases and then decreases with the increase of pressure,and increases with the increase of temperature.In the early stage of thermal evolution,pore adsorption capacity is strong and pressure sensitivity is weak;while in the late stage,it is on the contrary.

Synergic Effect of Reworking for Imperfect Quality Items with the Integration of Multi-Period Delay-in-Payment and Partial Backordering in Global Supply Chains

In intercontinental trade and economics goods are bought from a global supplier.On occasion,the expected lot may include a fraction of defective items.These imperfect items still have worth and can be sold to customers after repair.It is cost-effective and sustainable to rework such items in nearby repair workshops rather than return them.The reworked items can be returned from the workshop to the buyer when shortages are equal to the quantity of imperfect items.In the meantime,the supplier correspondingly deals a multi-period delay-in-payments strategy with purchaser.The entire profit has been maximized with paybacks for interim financing.This study aims to develop a synergic inventory model to get the most profit by making an allowance for reworking,multi-period delay-in-payments policy,and shortages.The findings of the proposed model augment inventory management performance by monitoring cycle time as well as fraction of phase with optimistic inventory for a supply chain.The results demonstrate that profit is smaller if the permitted period given by supplier to buyer is equal to or greater than the cycle time,and profit is greater if the permitted period is smaller than the cycle time.The algebraic method is engaged to make a closed system optimum solution.The mathematical experiment of this study is constructed to provide management insights and tangible practices.

Carbon storage dynamics of subtropical forests estimated with multi-period forest inventories at a regional scale:the case of Jiangxi forests

Temperate and high-latitude forests are carbon sinks and play pivotal roles in offsetting greenhouse gas emissions of CO2.However,uncertainty still exists for subtropical forests,especially in monsoon-prevalent eastern Asia.Earlier studies have depended on remote sensing,ecosystem modeling,carbon fluxes,or single period forest surveys to estimate carbon sequestration capacities,and the results vary significantly.This study was designed to utilize multi-period forest survey data to explore spatial-dynamics of biomass storage in subtropical forests of China.Jiangxi province,a region with over 60%subtropical forest cover,was selected as the case study site and is located in central east China.Based on forest inventory data 1984-2013,and the stock-difference and biomass expansion factor methods,the carbon storage and density,of arboreal forests,economic forests,bamboo forests,woodlands and shrubberies were estimated.The results show that carbon storage increased from 159.1 Tg C in 1988 to 276.1 TgC in 2013,making up 3.1-3.8%of carbon stored throughout China.Among the four types of forests,the amount of carbon stored was as follows:arboreal forest>economic forest>bamboo forest>woodland and shrubbery.Arboreal forests accounted for 64.0-79.4%of the total.Forest carbon density increased from 21.2 Mg C ha-1 in 1984 to26.2 Mg C ha-1 in 2013,equal to 61.2-70.2%of the average carbon density of China’s forests in the same period.Forest carbon storage in Jiangxi will reach 355.5 Tg C and 535.8 Tg C in 2020 and 2030,respectively,and forest carbon density is predicted to be 31.9 Mg C ha-1and 46.4 Mg C ha-1,respectively.As one of the few studies using multi-period data tracking biomass dynamics in Jiangxi province,the findings of this study may be used as a reference for other research.Using Jiangxi as a case study underlies the fact that subtropical forests in China have great carbon sequestration potential and have fundamental significance to offset global environmental change effects.

Regional green finance development and local green innovation:Evidence from a quasi-natural experiment of green bond issuance in China

Based on provincial panel data in China from 2008 to 2019, this research takes the issuance of China's green bond as a quasi-natural experiment to explore whether China's regional green finance development promotes local green innovation by using the multi-period DID model. The results show that the regional green financial development can promote local green innovation, and the rapid growth of the green bond market driven by policy does improve environmental sound technology innovation. The promotion of regional green finance development to local green innovation is related to the funds allocation of green credit,but not to the issuance scale of green bonds, according to further analysis, because China's development pattern can lead to a lack of endogenous market power and low credit resource allocation efficiency. In addition, the issuance of green bonds can effectively promote the allocation of green credit funds, thus enhancing the local green innovation level, but it can't reduce local carbon emissions through promoting green innovation. Therefore, the government should strengthen the green finance implementation assessment mechanism, taking into account the heterogeneity of regions and enterprises, complete the green finance monitoring and disclosure system, and increase the rate of green technology conversion.

Geologic Characteristics of Gas Reservoirs in West Sichuan Foreland Basin

The foreland basin in West Sichuan is a tectonic unit that has undergone multi-periods tectonic movements of Indosinian-Yanshanian-Himalayan. Since late Triassic, it has been in a passive subsidence environment controlled by basin margin mountain systems and by the compression with abundant sediment sources. With the complex geologic setting, the main geologic characteristics of natural gas reservoir are listed as following： （1） Source rocks are coal-bearing mud and shale series with high to over maturity, and long and progressive hydrocarbon generation-displacement period. The key accumulation period is middle-late Yanshanian epoch. （2） There are three gas-bearing systems vertically, each of which has different reservoir mechanism, main-controlled factors and distribution law, so the exploration thoughts and techniques are also different. （3） Undergoing multi-period generation-migration-accumulation, oil and gas have encountered multi-period modification or destruction, and gas accumulation overpass multiple tectonic periods. So the trap type is complicated and dominated by combination traps. Because the main accumulation period of natural gas is early and the reservoir encountered the modification of strong Himalayan movement, there is great difference in the fullness degree of gas reservoirs and complicated gas-water relation. （4） Reservoir is tight to very tight, but reservoirs of relatively high quality developed under the super tight setting. （5） The key techniques for oil and gas exploration in west Sichuan foreland basin are the prediction of relatively favorable reservoirs, fractures and gas bearing; and the key techniques for oil and gas development are how to improve the penetration rate, reservoir protection and modification.

Hydrocarbon enrichment characteristics and difference analysis in the TZ1-TZ4 well block of the Tarim Basin

The reservoirs in the TZ1-TZ4 well block of the Tarim Basin are complex, and the hydrocarbon enrichment shows differences. The three Carboniferous oil layers are characterized by ＂oil in the upper and lower layers and gas in the middle＂ in profile and ＂oil in the west and gas in the east＂ in plane view. In order to discuss the complex reservoir accumulation mechanisms, based on the petroleum geology and reservoir distribution, we studied the generation history of source rocks, the fault evolution and sealing, the accumulation periods and gas washing, and reconstructed the accumulation process of the TZ1-TZ4 well block. It is concluded that the hydrocarbon enrichment differences of oil layers CIII, CII and CI were caused by multiple sources and multi-period hydrocarbon charging and adjustment. The CII was closely related to CIII, but CI was formed by reservoir adjustment during the Yanshan period and was not affected by gas washing after it was formed. During the Himalayan period, different degrees of gas washing in the east and west led to hydrocarbon enrichment differences on the plane. The Carboniferous accumulation process of two-stage charging and one-stage adjustment is summarized： oil charging during the late Hercynian period is the first accumulation period of CIII and CII; oil reservoirs were adjusted into CI in the Yanshan period; finally gas washing in the Himalayan period is the second accumulation period of CIII and CII, but CI was not affected by gas washing. This complex accumulation process leads to the hydrocarbon enrichment differences in the TZ1-TZ4 well block.

Risk measures with comonotonic subadditivity or convexity on product spaces

In this paper, by an axiomatic approach, we propose the concepts of comonotonic subadditivity and comonotonic convex risk measures for portfolios, which are extensions of the ones introduced by Song and Yan （2006）. Representation results for these new introduced risk measures for portfolios are given in terms of Choquet integrals. Links of these newly introduced risk measures to multi-period comonotonic risk measures are represented. Finally, applications of the newly introduced comonotonic coherent risk measures to capital allocations are provided.

Multi-Objective Production Planning Using Lexicographic Procedure

This paper presents a multi-objective production planning model for a factory operating under a multi-product, and multi-period environment using the lexicographic (pre-emptive) procedure. The model objectives are to maximize the profit, minimize the total cost, and maximize the Overall Service Level (OSL) of the customers. The system consists of three potential suppliers that serve the factory to serve three customers/distributors. The performance of the developed model is illustrated using a verification example. Discussion of the results proved the efficacy of the model. Also, the effect of the deviation percentages on the different objectives is discussed.

Internal Transactions for Multiple Risky Assets

Most of the articles about insider trading assume that there is only one risky asset in the market. On the basis of these papers, this thesis is mainly divided into three parts to study the situation of multiple risky assets in the market. In the first part, the situation of multiple risky assets in the market when two transactions are in progress is studied and then, the equilibrium when the market requires the internal traders to disclose the trading volume after each transaction is analyzed. In the second part, the equilibrium of multi-period based on the two phases of transaction is derived. The third part is the summary of the paper.

The Impact of General Correlation Under Multi-Period Mean-Variance Asset-Liability Portfolio Management

This paper studies the multi-period mean-variance(MV)asset-liability portfolio management problem(MVAL),in which the portfolio is constructed by risky assets and liability.It is worth mentioning that the impact of general correlation is considered,i.e.,the random returns of risky assets and the liability are not only statistically correlated to each other but also correlated to themselves in different time periods.Such a model with a general correlation structure extends the classical multiperiod MVAL models with assumption of independent returns.The authors derive the explicit portfolio policy and the MV efficient frontier for this problem.Moreover,a numerical example is presented to illustrate the efficiency of the proposed solution scheme.

A Multi-Period Constrained Multi-Objective Evolutionary Algorithm with Orthogonal Learning for Solving the Complex Carbon Neutral Stock Portfolio Optimization Model

Financial market has systemic complexity and uncertainty.For investors,return and risk often coexist.How to rationally allocate funds into different assets and achieve excess returns with effectively controlling risk are main problems to be solved in the field of portfolio optimization(PO).At present,due to the influence of modeling and algorithm solving,the PO models established by many researchers are still mainly focused on single-stage single-objective models or single-stage multiobjective models.PO is actually considered as a multi-stage multi-objective optimization problem in real investment scenarios.It is more difficult than the previous single-stage PO model for meeting the realistic requirements.In this paper,the authors proposed a mean-improved stable tail adjusted return ratio-maximum drawdown rate(M-ISTARR-MD)PO model which effectively characterizes the real investment scenario.In order to solve the multi-stage multi-objective PO model with complex multi-constraints,the authors designed a multi-stage constrained multi-objective evolutionary algorithm with orthogonal learning(MSCMOEA-OL).Comparing with four well-known intelligence algorithms,the MSCMOEA-OL algorithm has competitive advantages in solving the M-ISTARR-MD model on the proposed constructed carbon neutral stock dataset.This paper provides a new way to construct and solve the complex PO model.

Multi-Period Optimal Distribution Model of Energy Medium and Its Application

A mathematical model of optimal energy medium distribution in steelmaking process is formulated. In this model, three kinds of important energy mediums including byproduct gases, steam and electricity are considered, and the objective function accounts for both the change of generation and consumption of the byproduct gases and the demand of low （or middle） pressure steam and electricity for each period to maximize the benefit of products cost and minimize the consumption of energy. The results indicate that the optimal distribution scheme of byproduct gases, middle pressure steam, low pressure steam and electricity is achieved and case study shows that 6% of operation cost is reduced by using the proposed model comparing with the previous model.

Time Consistent Multi-period Worst-Case Risk Measure in Robust Portfolio Selection

In this paper,we first construct a time consistent multi-period worst-case risk measure,which measures the dynamic investment risk period-wise from a distributionally robust perspective.Under the usually adopted uncertainty set,we derive the explicit optimal investment strategy for the multi-period robust portfolio selection problem under the multi-period worst-case risk measure.Empirical results demonstrate that the portfolio selection model under the proposed risk measure is a good complement to existing multi-period robust portfolio selection models using the adjustable robust approach.

The effect of the multi-period on the properties of deep-ultraviolet transparent conductive Ga_2O_3/ITO alternating multilayer films

Ga2O3/ITO alternating multilayer films were deposited on quartz glass substrates by rnagnetron sputtering. The effect of the multi-period on the structural, optical and electrical properties of Ga2O3/ITO alternating multilayer films was investigated by an X-ray diffractometer, a double beam spectrophotometer and the Hall system, respectively. A low sheet resistance of 225.5 Ω/□ and a high transmittance of more than 62.9% at a 300 nm wavelength were obtained for the two-period alternating multilayer film with a thickness of 72 nm.

Modeling and Solving a Multi-Period Inventory Fulfilling and Routing Problem for Hazardous Materials

Any potential damage may be severe once an accident occurs involving hazardous materials.It is therefore important to consider the risk factor concerning hazardous material supply chains,in order to make the best inventory routing decisions.This paper addresses the problem of hazardous material multi-period inventory routing with the assumption of a limited production capacity of a given manufacturer.The goal is to achieve the manufacturer's production plan,the retailer's supply schedule and the transportation routes within a fixed period.As the distribution of hazardous materials over a certain period is essentially a multiple travelling salesmen problem,the authors formulate a loadingdependent risk model for multiple-vehicle transportation and present an integer programming model to maximize the supply chain profit.An improved genetic algorithm considering two dimensions of chromosomes that cover the aforementioned period and supply quantity is devised to handle the integer programming model.Numerical experiments carried out demonstrate that using the proposed multiperiod joint decision-making can significantly increase the overall profit of the supply chain as compared to the use of single period decision repeatedly,while effectively reducing its risk.

Survey on Multi-period Mean-Variance Portfolio Selection Model

Due to the non-separability of the variance term,the dynamic mean-variance(MV)portfolio optimization problem is inherently difficult to solve by dynamic programming.Li and Ng(Math Finance 10(3):387-406,2000)and Zhou and Li(Appl Math Optim 42(1):19-33,2000)develop the pre-committed optimal policy for such a problem using the embedding method.Following this line of research,researchers have extensively studied the MV portfolio selection model through the inclusion of more practical investment constraints,realistic market assumptions and various financial applications.As the principle of optimality no longer holds,the pre-committed policy suffers from the time-inconsistent issue,i.e.,the optimal policy computed at the intermediate time t is not consistent with the optimal policy calculated at any time before time t.The time inconsistency of the dynamic MV model has become an important yet challenging research topic.This paper mainly focuses on the multi-period mean–variance(MMV)portfolio optimization problem,reviews the essential extensions and highlights the critical development of time-consistent policies.

Time-consistent investment and reinsurance strategies for insurers under multi-period mean-variance formulation with generalized correlated returns

The existing literature on investment and reinsurance is limited to the study of continuous-time problems,while discrete-time problems are always ignored by re-searchers.In this study,we first discuss a multi-period investment and reinsurance opti-mization problem under the classical mean-variance framework.When the asset returns with a serially correlated structure,the time-consistent investment and reinsurance strategies are acquired via backward induction.In addition,we propose an alternative time-consistent mean-variance optimization model that contrasts with the classical mean-variance model,and the corresponding optimal strategy and value function are also derived.We find that the investment and reinsurance strategies are both independent of the current wealth for the above two optimization problems,which coincides with the conclusion presented in the continuous-time problems.Most importantly,the above in-vestment strategies with serially correlated structures are both conditional mean-based strategies,rather than unconditional ones.Finally,we compare the investment and rein-surance strategies suggested above based on the simulation approach,to shed light on which investment-reinsurance strategies are more suitable for insurers.

A New Risk Measure MMVaR:Properties and Empirical Research

The paper presents the properties of an alternative method,which measures market risk over time-horizon exceeding one day:Mark to market value at risk(MMVaR).Relying on the minimal returns during the time interval,this method not only considers the non-normality of data and information about sample size,but also meets the requirement of increasing the minimal capital ratio in BaselⅢ,basically.The authors theoretically prove the translation invariance,monotonicity and subadditivity of MMVaR as a risk measure under some conditions,and study its finite sample properties through Monte Carlo simulations.The empirical analysis shows that MMVaR can measure multi-period risk accurately.

Hybrid Physics and Data-driven Contingency Filtering for Security Operation of Micro Energy-water Nexus

This paper investigates a novel engineering problem,i.e.,security-constrained multi-period operation of micro energywater nexuses.This problem is computationally challenging because of its high nonlinearity,nonconvexity,and large dimension.We propose a two-stage iterative algorithm employing a hybrid physics and data-driven contingency filtering(CF)method and convexification to solve it.The convexified master problem is solved in the first stage by considering the base case operation and binding contingencies set(BCS).The second stage updates BCS using physics-based data-driven methods,which include dynamic and filtered data sets.This method is faster than existing CF methods because it relies on offline optimization problems and contains a limited number of online optimization problems.We validate effectiveness of the proposed method using two different case studies:the IEEE 13-bus power system with the EPANET 8-node water system and the IEEE 33-bus power system with the Otsfeld 13-node water system.