China\u27s Soft Power in the Arab World through Higher Educational Exchange

As the world marveled at China’s rapid growth of economic and military power in the past few decades, China\u27s soft power expansion has received relatively little attention. My research looks at Chinese university programs that have attracted an increasing number of Arab students in recent years, which coincides with China\u27s larger scheme of soft power projection in the MENA region. Through quantitative analysis of an original survey and interviews with Arab students in China, I attempt to examine whether Chinese university programs can effectively enhance China\u27s soft power in the Arab World. My research finds that studying in China can lead to more favorable feelings toward China among Arab students as a result of increased familiarity and understanding of Chinese language, culture, society, and people. However, this positive change of impression has little to do with the length of time students spend studying in China. Their academic experience in Chinese universities does not seem to contribute significantly to this change either

Understanding the Mobile Gaming Context and Player Behaviour: A Review and a Research Agenda

The technological developments in mobile network and mobile computing underpin the dominance of mobile games in the global games market. Extant literature has enriched our understanding on the antecedents of playing mobile games, yet we still lack a comprehensive portrait of this unique gaming context that is distinguished from the context of traditional computer or console gaming. In response, we conduct a literature review to review research gaps on extant mobile gaming literature. Through a review of 181 works, we propose a framework based on the environmental psychology theory to guide future research to investigate the mobile gaming context. Drawing on this framework, we elaborate a research agenda that proposes potential research questions for future research to study the impacts of 1) mobile game design features and mobile application usability, 2) the use context more broadly, and 3) subjective individual differences, on mobile game player’s gaming experience, continued playing intention and in-game purchasing

Analysis of factors influencing spatiotemporal differentiation of the NDVI in the upper and middle reaches of the Yellow River from 2000 to 2020

Surface vegetation represents a link between the atmosphere, water, and human society. The quality of the ecological environment in the upper and middle reaches of the Yellow River (UMRYR) has a direct impact on the downstream basin. However, only few studies have investigated vegetation changes in the UMRYR. Therefore, we used the coefficient of variation and linear regression analyses to investigate spatiotemporal variations in the normalized difference vegetation index (NDVI). Further, we used the geographical detector model (GDM) to determine the spatial heterogeneity of the NDVI and its driving factors and then investigated the factors driving the spatial distribution of the NDVI in different climatic zones and vegetation types. The results showed that the NDVI in the UMRYR was high during the study period. The NDVI was distributed in a spatially heterogeneous manner, and it decreased from the southeast to the northwest. We observed severe degradation in the southeast, mild degradation in the northwest and the Yellow River source region, and substantial vegetation recovery in the central basin. Precipitation and vegetation type drove the spatial distribution of the NDVI. Natural factors had higher influence than that of anthropogenic factors, but the interactions between the natural and anthropogenic factors exhibited non-linear and bivariate enhancements. Inter-annual variations in precipitation were the main natural factor influencing inter-annual NDVI variations, while precipitation and anthropogenic ecological restoration projects jointly drove NDVI changes in the UMRYR. This study provides a better understanding of the current status of the NDVI and mechanisms driving vegetation restoration in the UMRYR

Novel Nonphosphorylated Peptides with Conserved Sequences Selectively Bind to Grb7 SH2 Domain with Affinity Comparable to Its Phosphorylated Ligand

The Grb7 (growth factor receptor-bound 7) protein, a member of the Grb7 protein family, is found to be highly expressed in such metastatic tumors as breast cancer, esophageal cancer, liver cancer, etc. The src-homology 2 (SH2) domain in the C-terminus is reported to be mainly involved in Grb7 signaling pathways. Using the random peptide library, we identified a series of Grb7 SH2 domain-binding nonphosphorylated peptides in the yeast two-hybrid system. These peptides have a conserved GIPT/K/N sequence at the N-terminus and G/WD/IP at the C-terminus, and the region between the N-and C-terminus contains fifteen amino acids enriched with serines, threonines and prolines. The association between the nonphosphorylated peptides and the Grb7 SH2 domain occurred in vitro and ex vivo. When competing for binding to the Grb7 SH2 domain in a complex, one synthesized nonphosphorylated ligand, containing the twenty-two amino acid-motif sequence, showed at least comparable affinity to the phosphorylated ligand of ErbB3 in vitro, and its overexpression inhibited the proliferation of SK-BR-3 cells. Such nonphosphorylated peptides may be useful for rational design of drugs targeted against cancers that express high levels of Grb7 protein

Attention-based Multi-modal Fusion Network for Semantic Scene Completion

This paper presents an end-to-end 3D convolutional network named attention-based multi-modal fusion network (AMFNet) for the semantic scene completion (SSC) task of inferring the occupancy and semantic labels of a volumetric 3D scene from single-view RGB-D images. Compared with previous methods which use only the semantic features extracted from RGB-D images, the proposed AMFNet learns to perform effective 3D scene completion and semantic segmentation simultaneously via leveraging the experience of inferring 2D semantic segmentation from RGB-D images as well as the reliable depth cues in spatial dimension. It is achieved by employing a multi-modal fusion architecture boosted from 2D semantic segmentation and a 3D semantic completion network empowered by residual attention blocks. We validate our method on both the synthetic SUNCG-RGBD dataset and the real NYUv2 dataset and the results show that our method respectively achieves the gains of 2.5% and 2.6% on the synthetic SUNCG-RGBD dataset and the real NYUv2 dataset against the state-of-the-art method.Comment: Accepted by AAAI 202

Intermittent Prediction Method Based On Marcov Method And Grey Prediction Method

This paper concentrates on the intermittent demand for electric power supply and studies the method of demand prediction. This chapter first divides the demand for electric power supply into two statistical sequences: (1) sequence of demand occurrence, among which “1”stands for the occurrence of demand,“0”means that the demand fails to occur; (2) sequence of demand quantity. Next the author predicts the moment of time and the number of times n that demand occurs within a specific time interval in the future based on 0-1 sequence using Markov arrival process (MAP). Then the paper forecasts the demand quantity in subsequent n intervals using Grey prediction model GM (1, 1) based on the sequence of demand quantity. Finally, the author places the demand quantity in the n intervals in order at the moments where demand occurs to get the predicted result of demand for electric material with intermittent demand. According to instance analysis, the integrated approach mentioned in this paper surpasses existing methods in providing accurate prediction on data of product with intermittent demand

Cell-specific and athero-protective roles for RIPK3 in a murine model of atherosclerosis

Receptor-interacting protein kinase 3 (RIPK3) was recently implicated in promoting atherosclerosis progression through a proposed role in macrophage necroptosis. However, RIPK3 has been connected to numerous other cellular pathways, which raises questions about its actual role in atherosclerosis. Furthermore, RIPK3 is expressed in a multitude of cell types, suggesting that it may be physiologically relevant to more than just macrophages in atherosclerosis. In this study

RetGen: A Joint framework for Retrieval and Grounded Text Generation Modeling

Recent advances in large-scale pre-training such as GPT-3 allow seemingly high quality text to be generated from a given prompt. However, such generation systems often suffer from problems of hallucinated facts, and are not inherently designed to incorporate useful external information. Grounded generation models appear to offer remedies, but their training typically relies on rarely-available parallel data where information-relevant documents are provided for context. We propose a framework that alleviates this data constraint by jointly training a grounded generator and document retriever on the language model signal. The model learns to reward retrieval of the documents with the highest utility in generation, and attentively combines them using a Mixture-of-Experts (MoE) ensemble to generate follow-on text. We demonstrate that both generator and retriever can take advantage of this joint training and work synergistically to produce more informative and relevant text in both prose and dialogue generation.Comment: accepted by AAAI-22, camera ready versio

Sulphur isotopes toward Sagittarius B2 extended envelope in the Galactic Center

The isotopic ratios are good tools for probing the stellar nucleosynthesis and chemical evolution. We performed high-sensitivity mapping observations of the J=7-6 rotational transitions of OCS, OC34S, O13CS, and OC33S toward the Galactic Center giant molecular cloud, Sagittarius B2 (Sgr B2) with IRAM 30m telescope. Positions with optically thin and uncontaminated lines are chosen to determine the sulfur isotope ratios. A 32S/34S ratio of 17.1\pm0.9 was derived with OCS and OC34S lines, while 34S/33S ratio of 6.8\pm1.9 was derived directly from integrated intensity ratio of OC34S and OC33S. With independent and accurate measurements of 32S/34S ratio, our results confirm the termination of the decreasing trend of 32S/34S ratios toward the Galactic Center, suggesting a drop in the production of massive stars at the Galactic centre.Comment: 20 pages, 7 figures, accepted by PAS