Design and Implementation of Intelligent Vegetable Recognition System based on MobileNet

With the rise of food safety traceability, unmanned supermarkets and autonomous shopping, the automatic identification technology of agricultural products such as vegetables in circulation and sales has become an urgent problem. This paper designs an intelligent vegetable identification system based on MobileNet to solve intelligent identification problem of vegetable sales in supermarkets. The system includes main control core, visual processing module, pressure sensor, voice broadcasting module and display module. When the system detects that there are vegetables to be weighed, the visual processing module completes the classification of vegetables, broadcasts the name, unit price and total price of vegetables by voice, and displays the weight, unit price and total price by OLED. The machine vision processing module is constructed by deep separable convolution (DSC). It realizes the separation of channels and regions, so it has high computing efficiency and is more suitable for embedded devices with low memory space. The experimental results show that the overall recognition rate of five vegetables reaches 97.33% under three kinds of illumination. The system has the advantages of stability, intelligence and convenience

Mutations in the Physcomitrium patens gene encoding Aminodeoxychorismate Synthase confer auxotrophic phenotypes

To facilitate genetic mapping of developmental mutants of Physcomitrium patens, we produced a genetic marker that combines recessive auxotrophy with dominant positive selection. We first identified the gene affected by the pabB4 auxotrophic mutation and then replaced it with a cassette that confers antibiotic resistance. This strain may be used to produce bi-parental somatic hybrids with nearly any other strain

Determining the number of new employees with learning, forgetting and variable wage with a newsvendor model in pull systems

International audienceThis paper develops a new quantitative model to find the optimal number of new employees with a Newsvendor model in a pull production system. This model allows learning, forgetting and variable wage. This paper also provides numerical results on sensitivity analysis, and compares the numerical results in three different situations: the situation with both learning and forgetting effect, that with learning effect but without forgetting effect and the situation with neither learning nor forgetting effect. The conclusions drawn from the comparison may offer theoretical insight for human resource managers to make appropriate employment decisions

Impact of Energy Conservation and Emissions Reduction Policy Means Coordination on Economic Growth: Quantitative Evidence from China

To understand the general relationship between Energy Conservation and Emissions Reduction (ECER) policy means coordination (PMC) and economic growth, this paper quantitatively investigates the impact on economic growth of differing PMCs. ECER policies from 1978 to 2013 in China are quantified across two dimensions of policy power and policy means, and then, PMC degrees are designed as independent variables and incorporated into a modified Cobb−Douglas production model. While determining the cointegration relationships by using a unit root test, a cointegration test and a stability test, cointegration equation is conducted by using quantitative data to explore the economic growth effects of PMC in China. The government’s use of PMC in China is also analyzed and ranked. The empirical results show that there is a long-term cointegration relationship among the variables from 1978 to 2013. Additionally, the effects of the different PMCs on economic growth show significant discrepancies and each PMC usage ranking is also found to be significantly different, thereby implying that the use of different PMCs by the Chinese government needs to be further perfected

Metal 3D printing technology for functional integration of catalytic system

Metal 3D printing is a very promising technology to revolutionize catalytic systems. Here the authors show that metal 3D printing products themselves can simultaneously serve as chemical reactors and catalysts for conversion of C1 molecules into high value-added chemicals

Tuning the Acid–Base Properties of Lignin-Derived Carbon Modulated ZnZr/SiO₂ Catalysts for Selective and Efficient Production of Butadiene from Ethanol

The direct selective conversion of ethanol to butadiene (ETB) is a competitive and environmentally friendly process compared to the traditional crude cracking route. The acid–base properties of catalysts are crucial for the direct ETB process. Herein, we report a rationally designed multifunctional lignin-derived carbon-modulated ZnZr/SiO2 (L-ZnZr/SiO2) catalyst with suitable acid–base properties for the direct ETB reaction. A variety of characterization techniques are employed to investigate the relationship between the acid–base properties and catalytic performance of the multifunctional lignin-modulated ZnZr/SiO2 catalysts. The results revealed that the rationally additional lignin-modulated carbon enhances both the acidity and basicity of the ZnZr/SiO2 catalysts, providing a suitable acid–base ratio that boosts the direct ETB reactivity. Meanwhile, the 1% L-ZnZr/SiO2 catalyst possessed ethanol conversion and butadiene selectivity as high as 98.4% and 55.5%, respectively, and exhibited excellent catalytic stability