Taste perception and purchase intent of oil‐in‐water spreads: effects of oil types and salt (NaCl or KCl) concentrations

Associations of sodium intake with heart‐related problems are creating awareness towards reducing sodium. Potassium chloride (KCl), a substitute for sodium chloride (NaCl), has the disadvantage of imparting bitterness at high concentrations. We evaluated physical characteristics, taste perception and purchase intent of KCl and NaCl in oil‐in‐water spreads/emulsions composed by olive, rice bran and soya bean oils. Consumers (N = 300) evaluated saltiness/bitterness of emulsions prepared with 65% oil, and NaCl (0.5% and 1.0%) or KCl (0.75% and 1.5%). Olive oil spreads (104.07–107.43 Pa s) had higher viscosity compared to other spreads (59.16–74.96 Pa s). Type of oil had significant effects on bitterness, overall taste liking and viscosity. Taste liking decreased due to bitterness of olive oil spreads (mean drop=1.72–2.43). Purchase intent was positively associated with saltiness and pH and increased with oil claims (increase = 1.3%–22.1%) compared to sodium claims (increase = 0.0%–12.9%). These findings are useful for understanding taste perception of emulsions.     

Holistic environmental soil-landscape modeling of soil organic carbon

In environmental soil-landscape modeling (ESLM), the selection of predictive variables is commonly contingent on the researchers' domain expertise on soil–environment processes. This variable selection strategy may suffer bias or even fail in regions where the process knowledge is insufficient. To overcome this problem, this study demonstrates a holistic ESLM framework which consists of five components: model conceptualization, data compilation, process identification, parsimonious model calibration, and model validation. Based on the STEP-AWBH conceptual model, a comprehensive pool of 210 potential environmental variables that exhaustively cover pedogenic and environmental factors was constructed. This was followed by strategic variable selection and development of parsimonious prediction models using machine learning techniques. The all-relevant variable selection successfully identified the major and minor factors relevant to the SOC variation, showing that the major factors important for explaining SOC variation in Florida were vegetation and soil water gradient. Topography and climate showed moderate effects on SOC variation. Parsimonious SOC models developed using four minimal-optimal variable selection techniques and simulated annealing yielded optimal predictive performance with minimal model complexity. The holistic ESLM framework not only provides a new view of selecting and utilizing variables for predicting soil properties but can also assist in identifying the underlying processes of soil-environment systems of interest. Due to the flexibility of the framework to incorporate various types of variable selection and modeling techniques, the holistic environmental modeling strategy can be generalized to other environmental modeling domains for both prediction and process identification.     

Subspace recycling accelerates the parametric macro‐modeling of MEMS

A fast computational technique that speeds up the process of parametric macro‐model extraction is proposed. An efficient starting point is the technique of parametric model order reduction (PMOR). The key step in PMOR is the computation of a projection matrix V, which requires the computation of multiple moment matrices of the underlying system. In turn, for each moment matrix, a linear system with multiple right‐hand sides has to be solved. Usually, a considerable number of linear systems must be solved when the system includes more than two free parameters. If the original system is of very large size, the linear solution step is computationally expensive. In this paper, the subspace recycling algorithm outer generalized conjugate residual method combined with generalized minimal residual method with deflated restarting (GCRO‐DR), is considered as a basis to solve the sequence of linear systems. In particular, two more efficient recycling algorithms, G‐DRvar1 and G‐DRvar2, are proposed. Theoretical analysis and simulation results show that both the GCRO‐DR method and its variants G‐DRvar1 and G‐DRvar2 are very efficient when compared with the standard solvers. Furthermore, the presented algorithms overcome the bottleneck of a recently proposed subspace recycling method the modified Krylov recycling generalized minimal residual method. From these subspace recycling algorithms, a PMOR process for macro‐model extraction can be significantly accelerated. Copyright © 2013 John Wiley & Sons, Ltd.     

Cycle time-oriented mid-term production planning for semiconductor wafer fabrication

Wafers are produced in an environment with uncertain demand and failure-prone machines. Production planners have to react to changes of both machine availability and target output, and revise plans appropriately. The scientific community mostly proposes WIP-oriented mid-term production planning to solve this problem. In such approaches, production is planned by defining targets for throughput rates and buffer levels of selected operations. In industrial practice, however, cycle time-oriented planning is often preferred over WIP-oriented planning. We therefore propose a new linear programming formulation, which facilitates cycle time-oriented mid-term production planning in wafer fabrication. This approach plans production by defining release quantities and target cycle times up to selected operations. It allows a seamless integration with the subordinate scheduling level. Here, least slack first scheduling translates target cycle times into lot priorities. We evaluate our new methodology in a comprehensive simulation study. The results suggest that cycle time-oriented mid-term production planning can both increase service level and reduce cycle time compared to WIP-oriented planning. Further, it requires less modelling effort and generates plans, which are easier to comprehend by human planners.     

CFD analysis on the catalyst layer breakage failure of an SCR-DeNOx system for a 350 MW coal-fired power plant

Selective catalytic reduction as one of the secondary NO_x control technologies is widely used in industrial sources including coal-fired power plants and large boilers. The performance of an SCR-DeNO_x system is sensitive to the installment of its components such as turning vanes and hybrid grids. In this work, three-dimensional CFD simulations are carried out to analyze the breakage failure of an SCR-DeNO_x system for a certain 350 MW coal-fired power plant. Research results are consistent with the phenomena that occur in the industrial application. It reveals that the breakage failure in the industrial application is likely to be caused by the inappropriate installation of the turning vane 3 locating closest to the catalyst, especially the angle of the turning vane 3. The analysis further shows that the lifetime or the breakage of the catalyst layers depends highly on the gas velocity, the fly ash distribution and its particle velocity.     

Influence of Na2 CO3 as Additive on Direct Reduction of Boron-bearing Magnetite Concentrate

Boron-bearing magnetite concentrate is typically characterized by low grade of iron and boron (wTFe=51%-54%,wB2 O3=6%-8%),as well as the close intergrowth of ascharite phase and magnetite phase.A promising technology was proposed to separate iron and boron by coupling the direct reduction of iron oxides and Na activation of boron minerals together.The influence of Na2 CO3 as additive on the direct reduction of boron-bearing magnetite was studied by chemical analysis,kinetic analysis,XRD analysis and SEM analysis.The results showed that the ad-dition of Na2 CO3 not only activated boron minerals,but also reduced the activation energy of the reaction and pro-moted the reduction of iron oxides.Besides,the addition of Na2 CO3 changed the composition and melting point of non-ferrous phase,and then promoted the growth and aggregation of iron grains,which was conducive to the subse-quent magnetic separation.Thus,the coupling of the two processes is advantageous.     

Numerical analysis of carbon saving potential in a top gas recycling oxygen blast furnace

Aiming at the current characteristics of blast furnace(BF)process,carbon saving potential of blast furnace was investigated from the perspective of the relationship between degree of direct reduction and carbon consumption.A new relationship chart between carbon consumption and degree of direct reduction,which can reflect more real situation of blast furnace operation,was established.Furthermore,the carbon saving potential of hydrogen-rich oxygen blast furnace(OBF)process was analyzed.Then,the policy implications based on this relationship chart established were suggested.On this basis,the method of improving the carbon saving potential of blast furnace was recycling the top gas with removal of CO_2 and H_2O or increasing hydrogen in BF gas and full oxygen blast.The results show that the carbon saving potential in traditional blast furnace(TBF)is only 38-56kg·t~(-1) while that in OBF is 138kg·t~(-1).Theoretically,the lowest carbon consumption of OBF is 261kg·t~(-1)and the corresponding degree of direct reduction is 0.04.In addition,the theoretical lowest carbon consumption of hydrogen-rich OBF is 257kg·t~(-1).The modeling analysis can be used to estimate the carbon savings potential in new ironmaking process and its related CO_2 emissions.     

Efficient Electron Transfer Processes and Enhanced Electrocatalytic Activity of Cobalt(II) Porphyrin Anchored on Graphene Oxide

We investigated the electronic perturbation between graphene oxide and cobalt porphyrin to reveal the origin of the enhanced electrocatalytic activity of a hybrid complex using time-resolved spectroscopic measurements and theoretical calculations. The impulsively generated charge-separated state, GO⁻-(Co^IIAPFP)⁺, undergoes fast charge recombination (<10 ps) between GO⁻ and (Co^IIAPFP)⁺ moieties. This fast charge recombination is directly related to the quick neutralization of (Co^IIAPFP)⁺, which shortens the dead time of inactive Co^IIIAPFP after the electrocatalytic reduction reaction. The fast transformation of inactive Co^IIIAPFP to active Co^IIAPFP is an important factor in the enhanced electrocatalytic activity of the hybrid complex.     

全国碳市场建设现状及水泥行业应对措施探讨

建材行业二氧化碳量排放的65%～67%来自水泥制造业,工艺环节的排放又占到水泥制造业二氧化碳排放的60%以上,面对全国碳市场即将于今年启动,水泥熟料作为首批纳入行业,基准值确定与碳配额的分配将直接关系到企业的履约成本。企业通过转变原料、能源消费方式,加大节能减排新技术的推行力度,结合碳资产的有效管理,不仅可以消除碳交易制度带来的影响,先进企业还可以做到在碳市场中有所盈利。