Risk factors of warehouse receipt pledge : a research based on risk assessments for Chinese logistics enterprises

This dissertation is concerned with risk analysis of Warehouse Receipt Pledge (WRP) business based on the application of risk theory as well as principle component analysis methodology. It is aimed at helping logistics providers engaged in WRP take appropriate measures to manage risks effectively during business process. Simultaneously, it explicitly clarifies the risks regarding the business flow of WRP and how it becomes bridge to integrate conventional logistics business with finance business. In order to enable logistics providers to adopt right ways to address identified categories of risk, it combines China Shipping Line (CSL) as a research case with risk theory and PCA methodology. Risks are examined through business disputes. There were 17 disputes taken place at CSL in recent years. Expert Evaluation Method is applied in the assessment of risk factors related to each dispute. Analysis using SPSS 18 is conducted so as to find out weight of influence caused by each risk factor. As a result, the aggregated loss of each risk delegated as consequence is acquired. Meanwhile, likelihood of each risk is calculated by the number of occurrence of each risk. Therefore, the value of each risk is achieved in term of R = P×C (Risk = Probability x Consequence) and the aggregated value for each category of risk is fulfilled accordingly. As per the numeric size of each category of risk, it summarized that the higher the R, the riskier. CSL should determine to take either preventive or precautious step towards different risks in order to mitigate them. In the final part of the dissertation, conclusions are drawn with regard to the contribution and deficiency and to the analysis of the risk of WRP from the standpoint of logistics providers rather than commercial banks. It is hoped that it will be helpful for logistics providers to control the fundamental risks regarding WRP within limited resources. It also points out that Cost Benefit Analysis should be carried out as future study on WRP

A simplified climate change model and extreme weather model based on a machine learning method

The emergence of climate change (CC) is affecting and changing the development of the natural environment, biological species, and human society. In order to better understand the influence of climate change and provide convincing evidence, the need to quantify the impact of climate change is urgent. In this paper, a climate change model is constructed by using a radial basis function (RBF) neural network. To verify the relevance between climate change and extreme weather (EW), the EW model was built using a support vector machine. In the case study of Canada, its level of climate change was calculated as being 0.2241 ("normal"), and it was found that the factors of CO2 emission, average temperature, and sea surface temperature are significant to Canada's climate change. In 2025, the climate level of Canada will become "a little bad" based on the prediction results. Then, the Pearson correlation value is calculated as being 0.571, which confirmed the moderate positive correlation between climate change and extreme weather. This paper provides a strong reference for comprehensively understanding the influences brought about by climate change

Three-Leaf Dart-Shaped Single-Crystal BN Formation Promoted by Surface Oxygen

Two-dimensional hexagonal boron nitride (h-BN) single crystals with various shapes have been synthesized by chemical vapor deposition over the past several years. Here we report the formation of three-leaf dart (3LD)-shaped single crystals of h-BN on Cu foil by atmospheric-pressure chemical vapor deposition. The leaves of the 3LD-shaped h-BN are as long as 18 {\mu}m and their edges are smooth armchair on one side and stepped armchair on the other. Careful analysis revealed that surface oxygen plays an important role in the formation of the 3LD shape. Oxygen suppressed h-BN nucleation by passivating Cu surface active sites and lowered the edge attachment energy, which caused the growth kinetics to change to a diffusion-controlled mode.Comment: 7 pages,6 figure

The mechanisms and diagnostic potential of lncRNAs, miRNAs, and their related signaling pathways in cervical cancer

Cervical cancer (CC), the fourth most prevalent type of cancer among women worldwide, is associated with high rates of morbidity and mortality. Due to the long period of latency in CC, most patients are already in the middle to late stages when initially diagnosed, which greatly reduces the clinical cure rate and quality of survival, thus resulting in poor outcomes. In recent years, with continuous exploration in the fields of bioinformatics and molecules, it has been found that ncRNAs, including miRNAs and lncRNAs, without the ability to translate proteins are capable of activating or inhibiting certain signaling pathways by targeting and modulating the level of expression of proteins involved in these signaling pathways. ncRNAs play important roles in assisting with diagnosis, drug administration, and prediction of prognosis during CC progression. As an entry point, the mechanisms of interaction between miRNAs, lncRNAs, and signaling pathways have long been a focus in basic research relating to CC, and numerous experimental studies have confirmed the close relationship of miRNAs, lncRNAs, and signaling pathways with CC development. Against this background, we summarize the latest advances in the involvement of lncRNA- and miRNA-related signaling pathways in the development of CC to provide guidance for CC treatment

Face Restoration via Plug-and-Play 3D Facial Priors

State-of-the-art face restoration methods employ deep convolutional neural networks (CNNs) to learn a mapping between degraded and sharp facial patterns by exploring local appearance knowledge. However, most of these methods do not well exploit facial structures and identity information, and only deal with task-specific face restoration (e.g.,face super-resolution or deblurring). In this paper, we propose cross-tasks and cross-models plug-and-play 3D facial priors to explicitly embed the network with the sharp facial structures for general face restoration tasks. Our 3D priors are the first to explore 3D morphable knowledge based on the fusion of parametric descriptions of face attributes (e.g., identity, facial expression, texture, illumination, and face pose). Furthermore, the priors can easily be incorporated into any network and are very efficient in improving the performance and accelerating the convergence speed. Firstly, a 3D face rendering branch is set up to obtain 3D priors of salient facial structures and identity knowledge. Secondly, for better exploiting this hierarchical information (i.e., intensity similarity, 3D facial structure, and identity content), a spatial attention module is designed for image restoration problems. Extensive face restoration experiments including face super-resolution and deblurring demonstrate that the proposed 3D priors achieve superior face restoration results over the state-of-the-art algorithm

The Inhibitory Effect of Regulatory T Cells on the Intimal Hyperplasia of Tissue-Engineered Blood Vessels in Diabetic Pigs

Severe inflammatory response and functional impairment of endothelial progenitor cells (EPCs) often lead to the implantation failure of EPC-captured tissue-engineered blood vessels (TEBVs) in diabetes. Regulatory T cells (Treg cells) are the most important inhibitory immune cells, but their effects in angiogenesis remain undefined, and the differences in the microenvironment may be an important reason. Here, we constructed a TEBV coated with an anti-CD34 antibody-functionalized heparin-collagen multilayer (anti-CD34 antibody-modified TEBV) using layer-by-layer self-assembly. Then, TEBVs were implanted into diabetic pigs. All TEBVs remained unobstructed 60 days after implantation, although varying degrees of intimal hyperplasia were detectable. Severe intimal hyperplasia was observed in the control group and peripheral injection of Treg cells group. Intravenous injection of Treg cells significantly inhibited intimal hyperplasia, inflammation, and cell apoptosis. Moreover, intravenous injection increased the proportion of circulating EPCs, while peripheral injection did not have these effects and reduced microvessel density around the TEBV. Interestingly, many Nestin+ cells could be detected in TEBVs, most of which were fusiform, showing the characteristics of smooth-muscle cells. Treg cell intravenous transplantation markedly reduced the number of Nestin+ cells in the TEBV. In conclusion, Treg cells inhibited the intimal hyperplasia of TEBVs in diabetic pigs by promoting EPC mobilization, anti-inflammatory action, and cellular protection

Identification of hub genes significantly linked to tuberous sclerosis related-epilepsy and lipid metabolism via bioinformatics analysis

BackgroundTuberous sclerosis complex (TSC) is one of the most common genetic causes of epilepsy. Identifying differentially expressed lipid metabolism related genes (DELMRGs) is crucial for guiding treatment decisions.MethodsWe acquired tuberous sclerosis related epilepsy (TSE) datasets, GSE16969 and GSE62019. Differential expression analysis identified 1,421 differentially expressed genes (DEGs). Intersecting these with lipid metabolism related genes (LMRGs) yielded 103 DELMRGs. DELMRGs underwent enrichment analyses, biomarker selection, disease classification modeling, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and AUCell analysis.ResultsIn TSE datasets, 103 DELMRGs were identified. Four diagnostic biomarkers (ALOX12B, CBS, CPT1C, and DAGLB) showed high accuracy for epilepsy diagnosis, with an AUC value of 0.9592. Significant differences (p < 0.05) in Plasma cells, T cells regulatory (Tregs), and Macrophages M2 were observed between diagnostic groups. Microglia cells were highly correlated with lipid metabolism functions.ConclusionsOur research unveiled potential DELMRGs (ALOX12B, CBS, CPT1C and DAGLB) in TSE, which may provide new ideas for studying the psathogenesis of epilepsy