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Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.

The purpose of this paper is to elucidate the influences of the animal fat and fatty acid type on the formation of polycyclic aromatic hydrocarbons (PAHs) and to propose a formation mechanism of PAHs in fat during electric roasting, which is a method of non-direct-contact-flame heating.

The effects of animal fats and model fat on the formation of PAHs were valued on the basis of the ultra high-performance liquid chromatography data. The corresponding products of the FAME pyrolysis were detected by TG-FTIR. The proposal formation mechanism of PAHs was based on the summary of the literature.

Contrary to the International Agency for Research on Cancer, DF had higher risk with 280.53 ng/g of concentration after being roasted than the others animal fats of red meat in terms of PAHs formation. This research also ensured the importance of fat on PAHs formation, the concentration of PAHs in pure fats was higher after being electric roasted than that in meat patties and juice which made from corresponding animal fat. What is more, during pure animal fats and meat products being processed, less PAHs formed in the fat with lower extent of unsaturation and lower content of linolenate. In the same way, methyl linolenate demonstrated the significant increasement to PAHs formation compared to the other fatty acids. And, the number of carbon atom and the extent of unsaturation in fatty acid affects the formation of PAHs during roasting. The detection of alkene and alkane allows to propose a formation mechanism of PAHs during model fat being heated. Further study is required to elucidate the confirm moleculars during the formation of PAHs.

This work studied the effect of the carbon atom number and the unsaturation extent of fats and model fats on the formation of PAHs. This work also assure the important of alkene and alkane on the pyrolysis of model fats. This study also researched the formation and distribution of PAHs in pure fats and meat products after being heated.

This study aims to investigate the effects of different surface-to-jet velocity ratios (Rsj) on the flow structure and the heat transfer of the floatation nozzle under different ratios (h/w) of the separation distance (h) to the slot width (w) and the differences of the flow structure and the heat transfer between the floatation nozzle and the slot nozzle.

The Nusselt number (Nu) and the pressure distribution of the floatation nozzle with a stationary wall are measured. Then the experimental results are used to validate the numerical model. Finally, a series of numerical simulations is carried out to achieve the purpose of this study.

The flow structure and heat transfer differences between the floatation nozzle and the slot nozzle are clarified. The floatation nozzle has more than 18 times the floatation ability of the unconfined slot nozzle. The Nu and pressure distributions of the floatation nozzle are experimentally measured. The effects of wall motion on the Nu and pressure distributions are identified.

The effects of the wall motion on the flow structure and the heat transfer of the floatation nozzle, and the differences between the floatation nozzle and the slot nozzle are first obtained. Therefore, it is valuable for engineers in engineering design of the floatation nozzle.

The numerical simulation of dispersed-phase evolution in injection molding process of polymer blends is of great significance in both adjusting material microstructure and improving performances of the final products. This paper aims to present a numerical strategy for the simulation of dispersed-phase evolution for immiscible polymer blends in injection molding.

First, the dispersed-phase modeling is discussed in detail. Then the Maffettone–Minale model, affine deformation model, breakup model and coalescence statistical model are chosen for the dispersed-phase evolution. A general coupled model of microscopic morphological evolution and macroscopic flow field is constructed. Besides, a stable finite element simulation strategy based on pressure-stabilizing/Petrov–Galerkin/streamline-upwind/Petrov–Galerkin method is adopted for both scales.

Finally, the simulation results are compared and evaluated with the experimental data, suggesting the reliability of the presented numerical strategy.

The coupled modeling of dispersed-phase and complex flow field during injection molding and the tracing and simulation of droplet evolution during the whole process can be achieved.

This study aims to prepare a low-formaldehyde and environmentally friendly glucose-lignin-based phenolic resin.

The authors directly used lignin to substitute formaldehyde to prepare lignin-based phenolic resin (LPF) with urea as formaldehyde absorbent. To improve the performance of the adhesive, the biobased glucose was introduced and the modified glucose-LPF (GLPF) was obtained.

The results showed that when the replacing amount of lignin to formaldehyde reached 15 Wt.%, the physical properties of the prepared LPF met the Chinese national standard, and the bonding strength increased by 21.9%, from 0.75 to 0.96 MPa, compared with PF. The addition of glucose boost the performance of wood adhesive, for example, the free phenol content of the obtained GLPF was significantly reduced by 79.11%, from 5.60% to 1.17%, the bonding strength (1.19 MPa) of GLPF increased by 19.3% in comparison to LPF and the curing temperature of GLPF decreased by 13.08%.

The low-formaldehyde and environmentally friendly GLPF has higher bonding strength and lower curing temperature, which is profitable to industrial application.

The prepared GLPF has lower free formaldehyde and formaldehyde emission, which is cost-effective and beneficial to human health.

The joint work of lignin and glucose provides the wood adhesive with increased bonding strength, decreased free phenol content and reduced curing temperature.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this study is to investigate the research on the influence of tech-innovation behavior on tech-innovation performance for Chinese manufacturing enterprises. Environmental performance has been taken into consideration with the green manufacturing and sustainability philosophy being a hotspot.

To verify the hypotheses and assumptions, a questionnaire was designed and a semi-structured interview was conducted for data collection. In addition, structural equation modeling (SEM) is applied to verify the influence model through assessing the fitting indexes based on the 317 questionnaire responses in the form of Likert-type scale.

Tech-innovation behavior and activity from direction, mode and investment behavior dimensions show their different positive influences on tech-innovation performance. This paper has creatively taken environmental tech-innovation performance into consideration, as well as economic performance. This investigation has provided the interpretation for each individual enterprise from three dimensions when conducting tech-innovation activity.

Tech-innovation behavior, which has been a subject of extended discussion during recent decades, is the effective activity or action for tech-innovation. However, there have not been any studies on the environmental performance influence study, as well as the economic performance from these three dimensions and framework.

As this paper discusses the tech-innovation performance influence study from three dimensions, individual enterprises can choose the corresponding action for the proper tech-innovation path, especially for small- and medium-sized enterprises.

This study helps managers recognize tech-innovation activities for better tech-innovation performance based on the empirical study.

This purpose of this paper is to present a new approach of solving quantum control problem.

State‐transition‐matrix (STM) is used to solute quantum control problem.

The paper obtains the matrix representation for wave function, normalization, and some other quantum operators, and then gives the possible methods to establish the STM model and solve it.

Based on this, many tools of the widely used control theory can be adopted to denote or analyze the quantum system.

The purpose of this paper is to develop a coupled approach to solve the pressure–velocity-coupled problem efficiently in the three-dimensional injection molding simulation.

A fully coupled pressure–velocity algorithm is developed to solve the coupled problem, by treating the pressure gradient term implicitly. And, the Schur complement preconditioned FGMRES is applied to decompose the resulting coupled pressure–velocity equation into pressure and velocity subsystems. Then, BoomerAMG is adopted to solve the pressure subsystem, and block Jacobi preconditioned FGMRES is applied to the velocity subsystem.

According to the several experiments, the fully coupled pressure–velocity algorithm was demonstrated to have faster convergence than the traditional SIMPLE algorithm, and the calculating time was reduced by up to 70 per cent. And, the Schur complement preconditioned FGMRES worked more efficiently than block Gauss–Seidel preconditioned FGMRES, block-selective AMG and AMG with block ILU(0) smoother and could take at least 47.4 per cent less time. The proposed solver had good scalability for different-size problems, including various cases with different numbers of elements. It also kept good speedup and efficiency in parallel performance.

A coupled solver has been proposed to effectively solve the coupled problem in the three-dimensional injection molding simulation, which is more robust and efficient than existing methods.

This study aims to examine the effects of system and information characteristics in developing users' perceptions towards ubiquitous decision support systems (UDSS).

The research model is empirically examined with survey data from 218 mobile users who have adopted a UDSS, i.e. mobile Dianping.com. A structural equation modelling approach is employed to assess the hypotheses.

The findings demonstrate that system characteristics of wireless networks, mobile devices and mobile applications significantly predicted system quality, which in turn determined system usefulness. Localisation, immediacy and customisation of mobile word‐of‐mouth were the major predictors of information quality, which in turn determined information usefulness.

This study contributes to our current understanding of ubiquitous commerce, especially mobile word‐of‐mouth, by presenting an integrated research framework, identifying system and information characteristics that are specific to the ubiquitous era, extending system quality and system usefulness from a single system to a combination of systems, and empirically examining the crossover effects between system and information factors.