A Study of the Production Process Simulation System Based on Workflow Management

The paper presents a method for designing a production process simulation system using workflow management technique, which consists of three parts: process model, organization resource model and workflow engine. Based on this method, we put forward a production process simulation system structure, and discuss the function of the key modules in detail. At last we present a sample in practical application

Relationship Between A Diffusion Model and A Transport Model For Softwood Drying

Transfer equations in a transport model for wood drying are rearranged to give equations that have similar form to those of Luikov's drying model. In this way the transport coefficients in these equations are derived from the transport model and are functions of moisture content, temperature, wood properties (density, permeability, and bound water diffusivity), and properties of moisture (liquid density and viscosity, vapor density, and viscosity).The above-derived equations are used to examine the relationship between the transport model and the simple diffusion model. It is shown that the diffusion model can be regarded as a simplified form of the transport model when the effect of temperature gradient is neglected. The diffusion model is applicable to cases where the temperature gradient is flat or the coefficient for the temperature gradient is small compared to that for the moisture content gradient. In other cases, or where the wood temperature is of concern, the transport drying model should be employed

The Effect of Parental Involvement on Online Learning Performance of Secondary Students: A Report on the Survey of Primary and Secondary School Online Teaching in Jiangsu Province

This paper was published in the Journal of East China Normal University. Affected by the Covid-19 Pandemic, China’s education system has experienced a nation-wide practice of online teaching and learning. The online learning performance of primary and secondary school students and their adaptability to the new operation has become a social concern. Families are more involved in child learning process than ever before. Based on a large-scale survey of online teaching in primary and secondary schools commissioned by the Jiangsu Provincial Department of Education, this study explores how middle school students perform in online learning and how parental involvement affects secondary school students’ online learning performance

Transitional Flow and Heat Transfer Characteristics in a Rectangular Duct with Stagger-arrayed Short Pin Fins

AbstractThis article describes an experimental study on friction and heat transfer performances of a transitional airflow in a rectangular channel with stagger-arrayed short pin fins. Friction factors, average Nusselt numbers and overall thermal performances of the transitional flow are obtained. The experimental study has showed that the pin fins enhance the heat transfer performance significantly, however increasing the flow frictional resistance considerably. After comparing the experimental results with the published data in references, it can be concluded that, in the transitional flow region, the pin fin channels of the proposed geometrical configuration could lead to a significant improvement of an overall thermal performance; for instance, the convective heat transfer performance is increased by at least 68%. By contrast, in the fully turbulent flow region, the ability of the proposed pin fin channels to increase heat transfer performances decreases as the Reynolds number increases. When Re > 6 000, the overall thermal performance becomes lower than the others

Improved Tissue-Based Analytical Test Methods for Orellanine, a Biomarker of Cortinarius Mushroom Intoxication.

Orellanine (OR) toxin is produced by mushrooms of the genus Cortinarius which grow in North America and in Europe. OR poisoning is characterized by severe oliguric acute renal failure, with a mortality rate of 10%-30%. Diagnosis of OR poisoning currently hinges on a history of ingestion of Cortinarius mushrooms and histopathology of renal biopsies. A key step in the diagnostic approach is analysis of tissues for OR. Currently, tissue-based analytical methods for OR are nonspecific and lack sensitivity. The objectives of this study were: (1) to develop definitive HPLC and LC-MS/MS tissue-based analytical methods for OR; and (2) to investigate toxicological effects of OR in mice. The HPLC limit of quantitation was 10 µg/g. For fortification levels of 15 µg/g to 50 µg/g OR in kidney, the relative standard deviation was between 1.3% and 9.8%, and accuracy was within 1.5% to 7.1%. A matrix-matched calibration curve was reproduced in this range with a correlation coefficient (r) of 0.97-0.99. The limit of detection was 20 ng/g for LC-MS/MS. In OR-injected mice, kidney OR concentrations were 97 ± 51 µg/g on Day 0 and 17 ± 1 µg/g on termination Day 3. Splenic and liver injuries were novel findings in this mouse model. The new tissue-based analytical tests will improve diagnosis of OR poisoning, while the mouse model has yielded new data advancing knowledge on OR-induced pathology. The new tissue-based analytical tests will improve diagnosis of OR poisoning, while the mouse model has yielded new data advancing knowledge on OR-induced pathology

Efficient double-quenching of electrochemiluminescence from CdS:Eu QDs by hemin-graphene-Au nanorods ternary composite for ultrasensitive immunoassay

A novel ternary composite of hemin-graphene-Au nanorods (H-RGO-Au NRs) with high electrocatalytic activity was synthesized by a simple method. And this ternary composite was firstly used in construction of electrochemiluminescence (ECL) immunosensor due to its double-quenching effect of quantum dots (QDs). Based on the high electrocatalytic activity of ternary complexes for the reduction of H(2)O(2) which acted as the coreactant of QDs-based ECL, as a result, the ECL intensity of QDs decreased. Besides, due to the ECL resonance energy transfer (ECL-RET) strategy between the large amount of Au nanorods (Au NRs) on the ternary composite surface and the CdS:Eu QDs, the ECL intensity of QDs was further quenched. Based on the double-quenching effect, a novel ultrasensitive ECL immunoassay method for detection of carcinoembryonic antigen (CEA) which is used as a model biomarker analyte was proposed. The designed immunoassay method showed a linear range from 0.01 pg mL(−1) to 1.0 ng mL(−1) with a detection limit of 0.01 pg mL(−1). The method showing low detection limit, good stability and acceptable fabrication reproducibility, provided a new approach for ECL immunoassay sensing and significant prospect for practical application

Forecasting stock market return with nonlinearity: a genetic programming approach

The issue whether return in the stock market is predictable remains ambiguous. This paper attempts to establish new return forecasting models in order to contribute on addressing this issue. In contrast to existing literatures, we first reveal that the model forecasting accuracy can be improved through better model specification without adding any new variables. Instead of having a unified return forecasting model, we argue that stock markets in different countries shall have different forecasting models. Furthermore, we adopt an evolutionary procedure called Genetic programming (GP), to develop our new models with nonlinearity. Our newly-developed forecasting models are testified to be more accurate than traditional AR-family models. More importantly, the trading strategy we propose based on our forecasting models has been verified to be highly profitable in different types of stock markets in terms of stock index futures trading

Bilateral Network with Residual U-blocks and Dual-Guided Attention for Real-time Semantic Segmentation

When some application scenarios need to use semantic segmentation technology, like automatic driving, the primary concern comes to real-time performance rather than extremely high segmentation accuracy. To achieve a good trade-off between speed and accuracy, two-branch architecture has been proposed in recent years. It treats spatial information and semantics information separately which allows the model to be composed of two networks both not heavy. However, the process of fusing features with two different scales becomes a performance bottleneck for many nowaday two-branch models. In this research, we design a new fusion mechanism for two-branch architecture which is guided by attention computation. To be precise, we use the Dual-Guided Attention (DGA) module we proposed to replace some multi-scale transformations with the calculation of attention which means we only use several attention layers of near linear complexity to achieve performance comparable to frequently-used multi-layer fusion. To ensure that our module can be effective, we use Residual U-blocks (RSU) to build one of the two branches in our networks which aims to obtain better multi-scale features. Extensive experiments on Cityscapes and CamVid dataset show the effectiveness of our method