Input Enhancement on Foreign Language Vocabulary Acquisition: Current Status and Future Prospect

This study reviewed the empirical research on the role of input enhancement on foreign language vocabulary acquisition published in core journals from 2009 to 2023, from which the current status and future trends of the studies were analyzed. The results manifested that (1) the number of input enhancement research demonstrated a trend of a spiral upward development; (2) the studies used different types of input enhancement as independent variable to explore their effects on the acquisition of target vocabulary; (3) the research materials applied in input enhancement were mostly in the reading mode, while lacked investigation in the listening mode. Therefore, future research could further examine the interactive and comparative effects of input enhancement on vocabulary acquisition as well as enhancing vocabulary in the materials with a variety of modes

Mining the Impact of Investor Sentiment on Stock Market from WeChat

In this study, the CSI 300 Index in China mainland and original articles from authoritative stock WeChat public accounts are investigated regarding their relations. First, a sentence-level sentiment classification approach for analyzing investor sentiment polarities in text corpus is proposed by expanding synonyms. Then, the Granger causality test is utilized to examine the impact of sentiment index on the stock price and volume-values. It shows that the influence of overall investor sentiment on volume-values is more rapid than that on stock price and the impact of positive sentiment is found to be more lasting than the negative in both stock price and volume-values. Furthermore, it is worth noting that there is a dual-stage phenomenon in the impact of positive sentiment on volume-values, which indicates that some investors react to positive information immediately while others may choose to wait and follow the trend

Small interfering RNA targeting CDC25B inhibits liver tumor growth in vitro and in vivo

<p>Abstract</p> <p>Background</p> <p>Using gene expression profiling, we previously identified CDC25B to be significantly highly expressed in hepatocellular carcinoma (HCC) compared to non-tumor liver. CDC25B is a cell cycle-activating phosphatase that positively regulates the activity of cyclin-dependent kinases, and is over-expressed in a variety of human malignancies. In this study, we validated the over-expression of CDC25B in HCC, and further investigated its potential as a therapeutic target for the management of HCC.</p> <p>Results</p> <p>Quantitative real-time polymerase chain reaction and immunohistochemical staining of patient samples confirmed the significant over-expression of CDC25B in HCC compared to non-tumor liver samples (<it>P </it>< 0.001). Thus, intefering with the expression and activity of CDC25B may be a potential way to intervene with HCC progression. We used RNA interference to study the biological effects of silencing CDC25B expression in HCC cell lines (Hep3B and Hep40), in order to validate its potential as a therapeutic target. Using small oligo siRNAs targeting the coding region of CDC25B, we effectively suppressed CDC25B expression by up to 90%. This was associatetd with significant reductions in cell growth rate, cell migration and invasion through the matrigel membrane, and caused significant cell cycle delay at the G2 phase. Finally, suppression of CDC25B significantly slowed the growth of Hep40 xenografts in nude mice.</p> <p>Conclusion</p> <p>Our data provide evidence that the inhibition of CDC25B expression and activity lead to suppression of tumor cell growth and motility, and may therefore be a feasible approach in the clinical management of HCC.</p

Short-term PV power prediction based on the 24 traditional Chinese solar terms and adaboost-GA-BP model

High-precision, short-term power forecasting for photovoltaic systems not only reduces unnecessary energy consumption but also provides power grid security. To this end, in this paper we propose a photovoltaic short-term power forecasting model based on the division of data of the 24 traditional Chinese solar terms and the Adaboost-GA-BP model. The 24 solar terms were condensed from the laws of meteorology, phenology, and seasonal changes to adapt to agricultural times in ancient China and have become intangible cultural heritage. This article first analyzes the numerical characteristics of meteorological factors and demonstrates their close correlation with the turning points of the 24 solar terms. Second, using Standardized Euclidean Distance and Spearman’s Correlation Coefficients to analyze data similarity between the Gregorian half-months and the 24 solar terms divisions for comparative analysis purposes, it is shown that the intragroup data under the division of the 24 solar terms have a higher similarity, leading to an average decrease of 15.68%, 40.57%, 14.68%, and 14.64% in the MAE, MSE, RMSE, and WMAPE of the predicted results, respectively. Finally, based on the data derived from the 24 solar terms, the combined algorithm was compared with the Adaboost-GA-BP model and then was verified. The genetic algorithm and Adaboost were used to optimize the BP neural network algorithm in initial value assignment and neural network structure, resulting in a 23.42%, 18.12%, and 22.28% reduction in the mean values of the MAE, RMSE, and WMAPE of the predicted results, respectively. Analysis of the results show that using the Adaboost-GA-BP model based on the 24 solar terms for short-term photovoltaic power forecasting can improve the accuracy of photovoltaic power forecasting and significantly improve the predictive performance of the model

Sulfur-doped TiO2 anchored on a large-area carbon sheet as a high-performance anode for sodium-ion battery

Well-tailored sulfur-doped anatase titanium dioxide nanoparticles anchored on a large-area carbon sheet are designed, where the in situ sulfur-doped titanium dioxide directly comes from titanium oxysulfate and the large-area carbon sheet is derived from glucose. When applied as an anode material for sodium-ion batteries, it exhibits an excellent electrochemical performance including a high capacity [256.4 mA h g–1 at 2 C (1 C = 335 mA h g–1) after 500 cycles] and a remarkable rate of cycling stability (100.5 mA h g–1 at 30 C after 500 cycles). These outstanding sodium storage behaviors are ascribed to the nanosized particles (about 8–12 nm), good electronic conductivity promoted by the incorporation of carbon sheet and sulfur, as well as the unique chemical bond based on the electrostatic interaction

Unveiling the immune symphony: decoding colorectal cancer metastasis through immune interactions

Colorectal cancer (CRC), known for its high metastatic potential, remains a leading cause of cancer-related death. This review emphasizes the critical role of immune responses in CRC metastasis, focusing on the interaction between immune cells and tumor microenvironment. We explore how immune cells, through cytokines, chemokines, and growth factors, contribute to the CRC metastasis cascade, underlining the tumor microenvironment’s role in shaping immune responses. The review addresses CRC’s immune evasion tactics, especially the upregulation of checkpoint inhibitors like PD-1 and CTLA-4, highlighting their potential as therapeutic targets. We also examine advanced immunotherapies, including checkpoint inhibitors and immune cell transplantation, to modify immune responses and enhance treatment outcomes in CRC metastasis. Overall, our analysis offers insights into the interplay between immune molecules and the tumor environment, crucial for developing new treatments to control CRC metastasis and improve patient prognosis, with a specific focus on overcoming immune evasion, a key aspect of this special issue

Experimental study on shear mechanical properties and damage evolution ofartificial structural plane under constant normal stiffness

To study the influence of asperity angle and normal stiffness on the shear mechanical properties of the structural plane, a direct shear test of the artificial structural plane with constant normal stiffness (CNS) was carried out using the self-developed coal rock shear seepage coupling test system. The results show that the shear stress presents a periodic oscillation attenuation trend when the asperity angles are 15° and 30°. At the end of shearing, the reduction in peak shear stress with the increase of normal stiffness is 1.78, 1.42, 1.36 and 1.27 MPa, respectively, which is gradually decreasing. While the asperity angle is 45°, the shear stress gradually tends to residual strength after reaching the peak shear stress, and there is a one-to-one correspondence between normal displacement evolution and shear stress. With the increase of the asperity angles, the shear stiffness increases gradually. With the increase of normal stiffness, the peak shear stress of structural planes with 15° and 45° asperity angles increases linearly, and when the asperity angle is 30°, it presents the characteristic of piecewise function, but the peak shear dilatancy angle gradually decreases. The failure mode of the structural plane is obtained by analyzing the mass loss before and after shearing, the proportion of debris particle size, and the evolution of three-dimensional morphology parameters. When the fluctuation angles are 15° and 45°, the failure modes are relatively single, namely wear failure and tooth cutting failure. When the fluctuation angle is 30°, the failure mode has a strong and complex dependence on the experimental conditions, mainly including tooth tip shear failure and full tooth cutting failure. By combining the three-dimensional spatial point cloud data of the structural plane with the normal displacement values at the corresponding shear displacement, a simulated cloud map of the structural plane gap width at a specific shear displacement is obtained, which analyzes the dynamic evolution process of the structural plane during the shear process and obtains its failure mechanism