Adaptive Prompt Learning with Distilled Connective Knowledge for Implicit Discourse Relation Recognition

Implicit discourse relation recognition (IDRR) aims at recognizing the discourse relation between two text segments without an explicit connective. Recently, the prompt learning has just been applied to the IDRR task with great performance improvements over various neural network-based approaches. However, the discrete nature of the state-art-of-art prompting approach requires manual design of templates and answers, a big hurdle for its practical applications. In this paper, we propose a continuous version of prompt learning together with connective knowledge distillation, called AdaptPrompt, to reduce manual design efforts via continuous prompting while further improving performance via knowledge transfer. In particular, we design and train a few virtual tokens to form continuous templates and automatically select the most suitable one by gradient search in the embedding space. We also design an answer-relation mapping rule to generate a few virtual answers as the answer space. Furthermore, we notice the importance of annotated connectives in the training dataset and design a teacher-student architecture for knowledge transfer. Experiments on the up-to-date PDTB Corpus V3.0 validate our design objectives in terms of the better relation recognition performance over the state-of-the-art competitors

Integrated analysis of single-cell and Bulk RNA sequencing reveals a malignancy-related signature in lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD), the most common histotype of lung cancer, may have variable prognosis due to molecular variations. The research strived to establish a prognostic model based on malignancy-related risk score (MRRS) in LUAD.MethodsWe applied the single-cell RNA sequencing (scRNA-seq) data from Tumor Immune Single Cell Hub database to recognize malignancy-related geneset. Meanwhile, we extracted RNA-seq data from The Cancer Genome Atlas database. The GSE68465 and GSE72094 datasets from the Gene Expression Omnibus database were downloaded to validate the prognostic signature. Random survival forest analysis screened MRRS with prognostic significance. Multivariate Cox analysis was leveraged to establish the MRRS. Furthermore, the biological functions, gene mutations, and immune landscape were investigated to uncover the underlying mechanisms of the malignancy-related signature. In addition, we used qRT-PCR to explore the expression profile of MRRS-constructed genes in LUAD cells.ResultsThe scRNA-seq analysis revealed the markers genes of malignant celltype. The MRRS composed of 7 malignancy-related genes was constructed for each patient, which was shown to be an independent prognostic factor. The results of the GSE68465 and GSE72094 datasets validated MRRS’s prognostic value. Further analysis demonstrated that MRRS was involved in oncogenic pathways, genetic mutations, and immune functions. Moreover, the results of qRT-PCR were consistent with bioinformatics analysis.ConclusionOur research recognized a novel malignancy-related signature for predicting the prognosis of LUAD patients and highlighted a promising prognostic and treatment marker for LUAD patients

Interannual to Interdecadal Variability of the Southern Yellow Sea Cold Water Mass and Establishment of “Forcing Mechanism Bridge”

The Yellow Sea cold water mass (YSCWM) occupies a wide region below the Yellow Sea (YS) thermocline in summer which is the most conservative water and may contain clearer climate signals than any other water masses in the YS. This study investigated the low-frequency variability of the southern YSCWM (SYSCWM) and established the “forcing mechanism bridge” using correlation analysis and singular value decomposition. On the interannual timescale, the southern oscillation can affect the SYSCWM through both the local winter monsoon (WM) and the sea surface net heat flux. On the decadal timescale, the Pacific decadal oscillation (PDO) can affect the SYSCWM via two “bridges”. First, the PDO affects the SYSCWM intensity by Aleutian low (AL), WM, and surface air temperature (SAT). Second, the PDO affects the SYSCWM by AL, WM, Kuroshio heat transport, and Yellow Sea warm current. The Arctic oscillation (AO) affects the SYSCWM by the Mongolian high, WM, and SAT. Before and after the 1980s, the consistent phase change of the PDO and the AO contributed to the significant decadal variability of the SYSCWM. Finally, one simple formula for predicting the decadal variability of SYSCWM intensity was established using key influencing factors

Interannual to Interdecadal Variability of the Southern Yellow Sea Cold Water Mass and Establishment of “Forcing Mechanism Bridge”

The Yellow Sea cold water mass (YSCWM) occupies a wide region below the Yellow Sea (YS) thermocline in summer which is the most conservative water and may contain clearer climate signals than any other water masses in the YS. This study investigated the low-frequency variability of the southern YSCWM (SYSCWM) and established the “forcing mechanism bridge” using correlation analysis and singular value decomposition. On the interannual timescale, the southern oscillation can affect the SYSCWM through both the local winter monsoon (WM) and the sea surface net heat flux. On the decadal timescale, the Pacific decadal oscillation (PDO) can affect the SYSCWM via two “bridges”. First, the PDO affects the SYSCWM intensity by Aleutian low (AL), WM, and surface air temperature (SAT). Second, the PDO affects the SYSCWM by AL, WM, Kuroshio heat transport, and Yellow Sea warm current. The Arctic oscillation (AO) affects the SYSCWM by the Mongolian high, WM, and SAT. Before and after the 1980s, the consistent phase change of the PDO and the AO contributed to the significant decadal variability of the SYSCWM. Finally, one simple formula for predicting the decadal variability of SYSCWM intensity was established using key influencing factors

The Interaction between Storm Surge and Concomitant Waves in Shandong Peninsula

Storm surge and concomitant waves induced by extreme weather systems can significantly modulate the marine dynamic environment. In this study, we used the Advanced Circulation-Simulating Waves Nearshore (ADCIRC-SWAN) coupled model to analyze spatiotemporal variation in dynamic processes during two types of weather systems, i.e., typhoons and extratropical storms, in the sea area near the Shandong Peninsula. The effects of waves on water level, water level change on wave height, and currents on wave height were investigated and quantified separately by performing sensitivity experiments. Our results showed that the interaction between water level change and waves occurred mainly in the nearshore zone. The wave-induced surge accounted for about 10–15% of the total storm surge. The water level change-induced significant wave height reached up to 0.9–1.3 m. Wave–current interaction occurred mainly in the offshore zone and was related to the relative angle between wave and current directions. The modulations of water level and wave height were strongly dependent on not only storm track and intensity but also topography and coastline shapes

SOAT1 enhances lung cancer invasion through stimulating AKT-mediated mitochondrial fragmentation

Sterol O-acyltransferase 1 (SOAT1) is a key enzyme in lipid metabolism, which mediates cholesterol esterification metabolism and is closely associated with many cancers. However, the role of SOAT1 in lung cancer invasion remains unclear. We found that SOAT1 expression was positively correlated with lung cancer invasion. Downregulation of SOAT1 inhibited invasion, mitochondrial fragmentation, AKT phosphorylation, and phospho-Drp (Ser616) in lung cancer cells and promoted intracellular free cholesterol accumulation. Mechanistically, AKT phosphorylation inhibitor MK-2206 alleviated both SOAT1 overexpression or high expression-induced mitochondrial fragmentation and lung cancer cell invasion. Furthermore, intracellular free cholesterol accumulation reduced AKT phosphorylation, SREBP1 mRNA expression, cell invasion, and mitochondrial fragmentation in lung cancer cells with high SOAT1 expression. In summary, our findings suggest that SOAT1 promotes lung cancer invasion activates the PI3K/AKT signaling pathway by downregulating intracellular free cholesterol levels, thereby affecting the regulation of mitochondrial fragmentation.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Influence of Tropical Cyclone Intensity and Size on Storm Surge in the Northern East China Sea

Typhoon storm surge research has always been very important and worthy of attention. Less is studied about the impact of tropical cyclone size (TC size) on storm surge, especially in semi-enclosed areas such as the northern East China Sea (NECS). Observational data for Typhoon Winnie (TY9711) and Typhoon Damrey (TY1210) from satellite and tide stations, as well as simulation results from a finite-volume coastal ocean model (FVCOM), were developed to study the effect of TC size on storm surge. Using the maximum wind speed (MXW) to represent the intensity of the tropical cyclone and seven-level wind circle range (R7) to represent the size of the tropical cyclone, an ideal simulation test was conducted. The results indicate that the highest storm surge occurs when the MXW is 40–45 m/s, that storm surge does not undergo significant change with the RWM except for the area near the center of typhoon and that the peak surge values are approximately a linear function of R7. Therefore, the TC size should be considered when estimating storm surge, particularly when predicting marine-economic effects and assessing the risk