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The traditional logistics route planning method is easily affected by cargo damage and vehicle carbon emissions, which makes it difficult to obtain the optimal logistics route. To solve this problem, this paper designs a new route planning method for cross-border e-commerce logistics of agricultural products based on recurrent neural network. Firstly, by calculating the speed of logistics vehicles under different traffic flow conditions, on the basis of analyzing the travel time of cross-border e-commerce logistics route of agricultural products, combining with the ratio of the carrying capacity to the maximum carrying capacity of cross-border e-commerce logistics routes of agricultural products, the driving speed of logistics vehicles is derived. In order to select the optimal distribution path, the total fixed cost, transportation damage cost and cargo damage cost in the process of agricultural product distribution are calculated. Combined with the penalty cost, the recursive neural network is used to establish the logistics route planning model and planning process of agricultural products’ cross-border e-commerce. The experimental results show that: the route planning method for cross-border e-commerce logistics of agricultural products based on recurrent neural network can effectively resist the influence of external factors, so as to obtain the optimal route of cross-border e-commerce logistics of agricultural products.

Su, T., 2020. Research on the change of marine industrial structure in marine economic zone to marine economic growth. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 49–52. Coconut Creek (Florida), ISSN 0749-0208. With the implementation of marine strategy, the development of marine industry in China has risen to a higher level. However, the evolution of China's marine industrial structure is still not stable and uneven, so it is of great significance to study the relationship between the changes of marine industrial structure and the growth of marine economy. This paper first introduces the contribution of the three marine industries to the marine economic growth and then analyzes the factors that affect the change of the marine industrial structure, as well as the impact of the change of the marine industrial structure on the economic growth. Finally, it studies the matching relationship between the change of the industrial structure and the economic growth.

With the development of big data concept and technology, big data has an important impact on human development. This paper studies the relationship between the consumption pattern and mental health of enterprise employees under the normalization of epidemic prevention and control. Starting from the consumption structure and behavior of enterprise employees, it defines the meaning of enterprise employees’ consumption and the connotation of enterprise employees’ health psychology and analyzes the relationship between consumption behavior and consumption psychology and the elements of enterprise employees’ health psychology. Based on the change of employees’ income structure and consumption patterns, this paper speculates the relationship between employees’ consumption patterns and mental health, analyzes the correlation between employees’ consumption patterns and mental health through a questionnaire survey, and calculates the Correlation Clustering statistical results. It plays an important role in building a good enterprise staff consumption culture under the normalization of epidemic prevention and control and effectively realizes the significance of purifying the social consumption environment.

Cancer is the second leading cause of death worldwide and patients are in urgent need of therapies that can effectively target cancer with minimal off-target side effects. Exosomes are extracellular nano-shuttles that facilitate intercellular communication between cells and organs. It has been established that tumor-derived exosomes contain a similar protein and lipid composition to that of the cells that secrete them, indicating that exosomes might be uniquely employed as carriers for anti-cancer therapeutics. : We isolated exosomes from two cancer cell lines, then co-cultured each type of cancer cells with these two kinds of exosomes and quantified exosome. HT1080 or Hela exosomes were systemically injected to Nude mice bearing a subcutaneous HT1080 tumor to investigate their cancer-homing behavior. Moreover, cancer cell-derived exosomes were engineered to carry Doxil (a common chemotherapy drug), known as D-exo, were used to detect their target and therapeutic efficacy as anti-cancer drugs. Exosome proteome array analysis were used to reveal the mechanism underly this phenomenon. : Exosomes derived from cancer cells fuse preferentially with their parent cancer cells, in vitro. Systemically injected tumor-derived exosomes home to their original tumor tissues. Moreover, compared to Doxil alone, the drug-loaded exosomes showed enhanced therapeutic retention in tumor tissues and eradicated them more effectively in nude mice. Exosome proteome array analysis revealed distinct integrin expression patterns, which might shed light on the underlying mechanisms that explain the exosomal cancer-homing behavior. : Here we demonstrate that the exosomes' ability to target the parent cancer is a phenomenon that opens up new ways to devise targeted therapies to deliver anti-tumor drugs.

The objective of this study was to investigate the individual and combined contamination of aflatoxin B₁ (AFB₁), zearalenone (ZEN) and deoxynivalenol (DON) in feedstuffs from different Provinces of China between 2016 and 2017. A total of 1569 samples, including 742 feed ingredients and 827 complete pig feed samples, were collected from various regions of China for mycotoxins analysis. The results showed that individual occurrence rates of AFB₁, ZEN, and DON were more than 83.3%, 88%, and 74.5%, respectively, in all the tested samples. DON was the most prevalent contaminant, followed by ZEN and AFB₁, with the average concentrations ranging from 450.0-4381.5 μg/kg, 2.3-729.2 μg/kg, and 1.3-10.0 μg/kg, respectively. Notable, 38.2%, 10.8%, and 0.6% of complete pig feeds were contaminated with DON, ZEN, and AFB₁ over China's regulatory limits, respectively. Moreover, over 75.0% analyzed samples were co-contaminated with two or three mycotoxins. In conclusion, the current study revealed that the feedstuffs in China were severely contaminated with DON, followed by ZEN and AFB₁ during the past two years. These findings highlight the importance of monitoring mycotoxins in livestock feed and implementing feed management and bioremediation strategies to reduce mycotoxin exposure.

A triaxial creep model for deep coal considering temperature effect based on fractional derivative is proposed for the condition of triaxial stress state. In order to study the temperature effect on creep deformation of deep coal, the thermal damage variable is established based on the Weibull distribution and continuum damage mechanics theory. The thermal damage variable is assigned to the Hooke body and Abel dashpot in order to characterize the effect of temperature on elastic modulus and viscosity coefficient. The temperature-dependent mechanical elements are connected to the creep model, and a three-dimensional creep constitutive equation based on fractional derivative is established. A creep experimental study for deep coal under the constant axial pressure and unloading confining pressure at different temperatures is carried out to characterize the creep deformation of deep coal during mining. The experimental results show that the coal sample with higher temperature has greater axial deformation, but the radial deformation does not change monotonically with the change of temperature. Moreover, the proposed triaxial creep model is validated by experimental data and the nonlinear least square method is used to determine the model parameters. It is indicated that the triaxial creep model can better describe the time-dependent deformation under the effect of temperature, especially the accelerated creep stage of creep. In addition, the sensitivity analysis of key parameters of the proposed model, especially axial stress level and creep temperature, is carried out to further verify the accuracy of the triaxial creep model.

Designing optimal material flow into a semiconductor inter-bay handling’s layout boosts production efficiency, increases yield and throughput, and cuts work-in-process (WIP) as well as cycle time. Intelligent layout of production plants is vital for modern manufacturing, and particularly so for 450-mm wafer-size semiconductor plants. In light of the particular bay nature of a semiconductor plant’s inter-bay, its shortcut design that results on more efficient flow movement become challenging differed from those of a manufacturing system. Additionally, a semiconductor bay’s shortcut layout considerations must address not just how to group stockers, but also how to determine the type of shortcut points and sequence of shortcut locations. Prior to mass production, the assessment expressed by designers’ artificial language, linguistic variable, for the shortcut design phase remains ambiguous and subjective. The need for efficient ways to take designers’ linguistic variables into account in the layout decision increases. The present study suggests a method based on fuzzy set theory to design the shortcut location for a semiconductor inter-bay equipped with a multiple-zone overhead shuttle (OHS) handling system. Unlike traditional layout approaches which can only handle quantitative data with Boolean logic problems, fuzzy-set-based methods offer a way to incorporate the attitude of designers using linguistic variables to represent a problem in decision making when designing semiconductor bay’s shortcut layout. The paper also develops an intelligent hybrid heuristic algorithm incorporating with the goal of maximizing in-sequence movements and minimizing total flow distance to search a better shortcut layout design. An illustrative example from a wafer foundry company is used to demonstrate that the fuzzy-set-based layout design found by the proposed layout method outperforms by other approaches in the OHS travel time, throughput, and flow time performance. The method suggested here can assist semiconductor facility designers in qualitatively and quantitatively improving the material flow and increasing production efficiency by solving their semiconductor bay’s shortcut layout problems.

Bacterial bloodstream infection is responsible for the majority of cases of sepsis and septic shock. Early recognition of the causative pathogen is pivotal for administration of adequate empiric antibiotic therapy and for the survival of the patients. In this study, we developed a feasible machine learning (ML) model to predict gram-positive and gram-negative bacteremia based on routine laboratory parameters. Data for 2118 patients with bacteremia were obtained from the Medical Information Mart for Intensive Care dataset. Patients were randomly split into the training set and test set by stratified sampling, and 374 routine laboratory blood test variables were retrieved. Variables with missing values in more than 40% of the patients were excluded. Pearson correlation test was employed to eliminate redundant features. Five ML algorithms were used to build the model based on the selected features. Additionally, 132 patients with bacteremia who were treated at Qilu Hospital of Shandong University were included in an independent test cohort to evaluate the model. After feature selection, 32 variables remained. All the five ML algorithms performed well in terms of discriminating between gram-positive and gram-negative bacteremia, but the performance of convolutional neural network (CNN) and random forest (RF) were better than other three algorithms. Consider of the interpretability of models, RF was chosen for further test (ROC-AUC = 0.768; 95%CI = 0.715-0.798, with a sensitivity of 75.20% and a specificity of 63.79%). To expand the application of the model, a decision tree (DT) was built utilizing the major variables, and it achieved an AUC of 0.679 (95%CI = 0.632-0.723), a sensitivity of 66%, and a specificity of 67.82% in the test cohort. When tested in the Qilu Hospital cohort, the ROC-AUC of the RF and DT models were 0.666 (95%CI = 0.579-0.746) and 0.615 (95%CI = 0.526-0.698), respectively. Finally, a software was developed to make the RF- and DT-based prediction models easily accessible. The present ML-based models could effectively discriminate between gram-positive and gram-negative bacteremia based on routine laboratory blood test results. This simple model would be beneficial in terms of guiding timely antibiotic selection and administration in critically ill patients with bacteremia before their pathogen test results are available.

In 2020, coronavirus disease (COVID-19) left around 81% of the global workforce, nearly 2.7 billion workers, affected. Employment in China was the first to be hit by COVID-19. The Regional Comprehensive Economic Partnership (RCEP) is expected to bring dynamism to China's employment market in an era of long COVID-19. This study aims to examine the number of sectoral jobs that the RCEP will create in China, with the number of skilled or unskilled labour employed in each sector. The exogenous shocks to the RCEP can be reflected in the number of jobs created through multipliers based on a social accounting matrix compiled from China's input-output tables in 2017, combined with the employment satellite accounts compiled. The results show that the RCEP is expected to create over 17 million potential jobs in China, with unskilled labour accounting for 10.44 million and skilled labour for 6.77 million. It is even expected that there will be job losses in the metalworking machinery sector. The contribution of this paper can serve as a reference for policies to protect vulnerable sectors, further open up trade markets and strengthen cooperation among RCEP members as important measures to address the employment impact of long COVID-19.

Drug-eluting stents implanted after ischaemic injury reduce the proliferation of endothelial cells and vascular smooth muscle cells and thus neointimal hyperplasia. However, the eluted drug also slows down the re-endothelialization process, delays arterial healing and can increase the risk of late restenosis. Here we show that stents releasing exosomes derived from mesenchymal stem cells in the presence of reactive oxygen species enhance vascular healing in rats with renal ischaemia-reperfusion injury, promoting endothelial cell tube formation and proliferation, and impairing the migration of smooth muscle cells. Compared with drug-eluting stents and bare-metal stents, the exosome-coated stents accelerated re-endothelialization and decreased in-stent restenosis 28 days after implantation. We also show that exosome-eluting stents implanted in the abdominal aorta of rats with unilateral hindlimb ischaemia regulated macrophage polarization, reduced local vascular and systemic inflammation, and promoted muscle tissue repair.