Impact of online public opinion regarding the Japanese nuclear wastewater incident on stock market based on the SOR model

The exposure of the Japanese nuclear wastewater incident has shaped online public opinion and has also caused a certain impact on stocks in aquaculture and feed industries. In order to explore the impact of network public opinion caused by public emergencies on relevant stocks, this paper uses the stimulus organism response(SOR) model to construct a framework model of the impact path of network public opinion on the financial stock market, and it uses emotional analysis, LDA and grounded theory methods to conduct empirical analysis. The study draws a new conclusion about the impact of online public opinion on the performance of relevant stocks in the context of the nuclear waste water incident in Japan. The positive change of media sentiment will lead to the decline of stock returns and the increase of volatility. The positive change of public sentiment will lead to the decline of stock returns in the current period and the increase of stock returns in the lag period. At the same time, we have proved that media attention, public opinion theme and prospect theory value have certain influences on stock performance in the context of the Japanese nuclear wastewater incident. The conclusion shows that after the public emergency, the government and investors need to pay attention to the changes of network public opinion caused by the event, so as to avoid the possible stock market risks

Analyzing the Relationship between Consumer Satisfaction and Fresh E-Commerce Logistics Service Using Text Mining Techniques

The rapid development of the Internet and the transformation of consumption patterns have prompted consumers to purchase fresh products online. For fresh e-commerce enterprises, logistics is an important aspect of customer satisfaction. Therefore, this study focused on online review information and used a convolutional neural network text mining model for its analysis. Logistics service elements concerned with customer satisfaction are convenience, communication, integrity, responsiveness, and reliability. Thereafter, comment information was converted to digital information using sentiment analysis. Finally, a correlation analysis was carried out to compare the significance of various influencing factors. The results confirm that convenience, communication, reliability, and responsiveness had a significant impact on customer satisfaction, whereas integrity had none. Fresh e-commerce logistic services need to improve for the development of the companies

Three-Dimensional Numerical Method for Simulating Large-Scale Free Water Surface by Massive Parallel Computing on a GPU

Water wave dynamics and its engineering application have always been a key issue in the field of hydraulics, and effective and efficient numerical methods need to be proposed to perform three-dimensional (3-D) simulation of large-scale water fluctuation in engineering practice. A single-phase free-surface lattice Boltzmann method (SPFS-LB method) is coupled with a large-eddy simulation approach for simulating large-scale free water surface flows, and the simulation is accelerated on a GPU (graphic processing unit). The coupling model is used to simulate the evolution process of dam-break wave after complete and partial dam-break. The formation mechanism of horizontal and vertical vortices in water after partial dam-break and the advance and evolution process of dam-break flow on non-contour riverbed are analyzed. The method has been verified to be reasonable and can obtain a more accurate time curve of water level fluctuation. Applying this method to practical arch dams, discharge coefficients consistent with empirical formulas can be obtained by comparison and analysis, and the surface flow phenomena (such as tongue diffusion, surface fragmentation, and surface fusion) can be well simulated by this method. In addition, based on the key technology of parallel computing on a GPU, the implementation of the SPFS-LB model on a GPU unit achieves tens of millions of lattice updates per second, which is over fifty times higher than that on a single CPU chip. It is proved that the proposed method for large-scale water fluctuations can be used to study practical engineering problems. The mathematical model method realizes the efficient and accurate simulation of practical physical problems

The macrophage-associated prognostic gene ANXA5 promotes immunotherapy resistance in gastric cancer through angiogenesis

Abstract Gastric cancer (GC) remains a predominant form of malignant tumor globally, necessitating innovative non-surgical therapeutic approaches. This investigation aimed to delineate the expression landscape of macrophage-associated genes in GC and to evaluate their prognostic significance and influence on immunotherapeutic responsiveness. Utilizing the CellMarker2.0 database, we identified 69 immune cell markers with prognostic relevance in GC, including 12 macrophage-specific genes. A Weighted Gene Co-Expression Network Analysis (WGCNA) isolated 3,181 genes correlated with these macrophage markers. The Cancer Genome Atlas (TCGA-STAD) dataset was employed as the training set, while data from the GSE62254 served as the validation cohort. 13 genes were shortlisted through LASSO-Cox regression to formulate a prognostic model. Multivariable Cox regression substantiated that the calculated risk score serves as an imperative independent predictor of overall survival (OS). Distinct macrophage infiltration profiles, pathway associations, treatment susceptibilities, and drug sensitivities were observed between high- and low-risk groups. The preliminary validation of ANXA5 in predicting the survival rates of GC patients at 1 year, 3 years, and 5 years, as well as its expression levels were higher and role in promoting tumor angiogenesis in GC through immunohistochemistry and angiogenesis experiments. In summary, macrophage-related genes were potentially a novel crosstalk mechanism between macrophages and endothelial cells in the tumor microenvironment, and the interplay between inflammation and angiogenesis might have also offered new therapeutic targets, providing a new avenue for personalized treatment interventions

Multi-Transcriptomic Analysis Reveals the Heterogeneity and Tumor-Promoting Role of SPP1/CD44-Mediated Intratumoral Crosstalk in Gastric Cancer

GC is a fatal disease with high heterogeneity and invasiveness. Recently, SPP1 has been reported to be involved in the tumor progression of multiple human cancers; however, the role of SPP1 in GC heterogeneity and whether it is associated with the invasiveness and mortality of GC remain unclear. Here, we combined multiple RNA sequencing approaches to evaluate the impact of SPP1 on GC. Through bulk RNA sequencing (bulk RNA-seq) and immunohistochemistry (IHC), we found that SPP1 was highly expressed in GC, and high levels of SPP1 were associated with macrophage infiltration, an advanced tumor stage, and higher mortality for advanced GC patients. Furthermore, through simultaneous single-cell and spatial analysis, we demonstrated that SPP1+ macrophages are tumor-specific macrophages unique to cancer and enriched in the deep layer of GC tissue. Cell—cell communication analysis revealed that SPP1/CD44 interactions between SPP1+ macrophages and their localized tumor epithelial cells could activate downstream target genes in epithelial cells to promote dynamic changes in intratumor heterogeneity. Moreover, these activated genes were found to be closely associated with poor clinical GC outcomes and with cancer-related pathways that promote GC progression, as shown by survival analysis and enrichment analysis, respectively. Collectively, our study reveals that tumor-specific SPP1+ macrophages drive the architecture of intratumor heterogeneity to evolve with tumor progression and that SPP1 may serve as a prognostic marker for advanced GC patients, as well as a potential therapeutic target for GC

Graphene-Based Sandwich Structures for Frequency Selectable Electromagnetic Shielding

Due to substantial development of electronics and telecommunication techniques, materials with electromagnetic interference (EMI) shielding performance are significant in alleviating the interference impacts induced from a remarkable variety of devices. In the work, we propose novel sandwich structures for manipulating the EM wave transport, which holds unique EMI shielding features of frequency selectivity. By employing electrical and magnetic loss spacers, the resultant sandwich structures are endowed with tunable EMI shielding performance, showing substantial improvements in overall shielding effectiveness along with pronounced shielding peak shift. The mechanisms suggest that the multiple interfaces, electromagnetic loss media, and changes of representative EM wavelength could be critical roles in tailoring the EMI shielding performance. The results provide a versatile strategy that could be extended in other frequency ranges and various types of sandwich structures, promising great opportunities for designing and fabricating advanced electromagnetic attenuation materials and devices