Supply chain management based on volatility clustering: The effect of CBDC volatility

A Central Bank Digital Currency (CBDC) launched by the Bank of England could enable businesses to directly make electronic payments. It can be argued that digital payment is helpful in supply chain management applications. However, the adoption of CBDC in the supply chain could bring new turbulence since the CBDC value may fluctuate. Therefore, this paper intends to optimize the production plan of manufacturing supply chain based on a volatility clustering model by reducing CBDC value uncertainty. We apply both GARCH model and machine learning model to depict the CBDC volatility clustering. Empirically, we employed Baltic Dry Index, Bitcoin and exchange rate as main variables with sample period from 2015 to 2021 to evaluate the performance of the two models. On this basis, we reveal that our machine learning model overwhelmingly outperforms the GARCH model. Consequently, our result implies that manufacturing companies’ performance can be strengthened through CBDC uncertainty reduction

Modification of m5C regulators in sarcoma can guide different immune infiltrations as well as immunotherapy

BackgroundRecent studies have found that 5-methylcytosine (m5C) modulators are associated with the prognosis and treatment of cancer. However, the relevance of m5C modulators in sarcoma prognosis and the tumour microenvironment is unclear.MethodsWe selected 15 m5C regulators and performed unsupervised clustering to identify m5C modification patterns and differentially expressed genes associated with the m5C phenotype in The Cancer Genome Atlas (TCGA) sarcomas. The extent of immune cell infiltration in different clustering groups was explored using single-sample gene set enrichment analysis and estimation algorithms. A principal component analysis algorithm-based m5C scoring protocol was performed to assess the m5C modification patterns of individual tumors.ResultsWe identified two distinct m5C modification patterns in the TCGA sarcoma cohort, which possess different clinical outcomes and biological processes. Tumour microenvironment analysis revealed two groups of immune infiltration patterns highly consistent with m5C modification patterns, classified as immune inflammatory and immune desert types. We constructed m5C scores and found that high m5C scores were closely associated with leiomyosarcoma and other subtypes, and were associated with poorer prognosis, lower PD-L1 expression, and poorer immunotherapy outcomes. The best application was validated against the m5C database.ConclusionWe constructed an m5C score for sarcoma based on the TCGA database and identified a poorer prognosis in the high m5c score group. The stability and good prognostic predictive power of the m5C score was verified by an external database. We found that sarcomas in the low m5C score group may have a better response to immunotherapy

Myocardin Marks the Earliest Cardiac Gene Expression and Plays an Important Role in Heart Development

Myocardin belongs to the SAP domain family of transcription factors and is expressed specifically in cardiac and smooth muscle during embryogenesis and in adulthood. Myocardin functions as a transcriptional coactivator of SRF and is sufficient and necessary for smooth muscle gene expression. However, the in vivo function of myocardin during cardiogenesis is not completely understood. Here we clone myocardin from chick embryonic hearts and show that myocardin protein sequences are highly conserved cross species. Detailed studies of chick myocardin expression reveal that myocardin is expressed in cardiac and smooth muscle lineage during early embryogenesis, similar to that found in mouse. Interestingly, the expression of myocardin in the heart was found enriched in the outflow tract and the sinoatrial segments shortly after the formation of linear heart tube. Such expression pattern is also maintained in later developing embryos, suggesting that myocardin may play a unique role in the formation of those cardiac modules. Similar to its mouse counterpart, chick myocardin is able to activate cardiac and smooth muscle promoter reporter genes and induce smooth muscle gene expression in nonmuscle cells. Ectopic overexpression of myocardin enlarged the embryonic chick heart. Conversely, repression of the endogenous chick myocardin using antisense oligonucleotides or a dominant negative mutant form of myocardin inhibited cardiogenesis. Together, our data place myocardin as one of the earliest cardiac marker genes for cardiogenesis and support the idea that myocardin plays an essential role in cardiac gene expression and cardiogenesis

Host Langerin (CD207) is a receptor for Yersinia pestis phagocytosis and promotes dissemination

Yersinia pestis is a Gram-negative bacterium that causes plague. After Y. pestis overcomes the skin barrier, it encounters antigen-presenting cells (APCs), such as Langerhans and dendritic cells. They transport the bacteria from the skin to the lymph nodes. However, the molecular mechanisms involved in bacterial transmission are unclear. Langerhans cells (LCs) express Langerin (CD207), a calcium-dependent (C-type) lectin. Furthermore, Y. pestis possesses exposed core oligosaccharides. In this study, we show that Y. pestis invades LCs and Langerin-expressing transfectants. However, when the bacterial core oligosaccharides are shielded or truncated, Y. pestis propensity to invade Langerhans and Langerin-expressing cells decreases. Moreover, the interaction of Y. pestis with Langerin-expressing transfectants is inhibited by purified Langerin, a DC-SIGN (DC-specific intercellular adhesion molecule 3 grabbing nonintegrin)-like molecule, an anti-CD207 antibody, purified core oligosaccharides and several oligosaccharides. Furthermore, covering core oligosaccharides reduces the mortality associated with murine infection by adversely affecting the transmission of Y. pestis to lymph nodes. These results demonstrate that direct interaction of core oligosaccharides with Langerin facilitates the invasion of LCs by Y. pestis. Therefore, Langerin-mediated binding of Y. pestis to APCs may promote its dissemination and infection.Peer reviewe

Qwen Technical Report

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans. In this work, we introduce Qwen, the first installment of our large language model series. Qwen is a comprehensive language model series that encompasses distinct models with varying parameter counts. It includes Qwen, the base pretrained language models, and Qwen-Chat, the chat models finetuned with human alignment techniques. The base language models consistently demonstrate superior performance across a multitude of downstream tasks, and the chat models, particularly those trained using Reinforcement Learning from Human Feedback (RLHF), are highly competitive. The chat models possess advanced tool-use and planning capabilities for creating agent applications, showcasing impressive performance even when compared to bigger models on complex tasks like utilizing a code interpreter. Furthermore, we have developed coding-specialized models, Code-Qwen and Code-Qwen-Chat, as well as mathematics-focused models, Math-Qwen-Chat, which are built upon base language models. These models demonstrate significantly improved performance in comparison with open-source models, and slightly fall behind the proprietary models.Comment: 59 pages, 5 figure

Nonlinear Effects of Governmental and Civil Environmental Regulation on Green Total Factor Productivity in China

This paper employs metafrontier Malmquist-Luenberger index to measure green total factor productivity and then builds panel model to investigate the nonlinear effects of both governmental and civil environmental regulation on green total factor productivity in 30 provinces of China in 2007–2016, where the threshold variables are environmental awareness and regulatory foundation. The results show that green total factor productivity takes the characteristic of cyclical fluctuation, and the magnitude and its growth rate in the eastern region are higher than those in the midwestern region. The degrees of the governmental and civil environmental regulation and green total factor productivity display single environmental awareness threshold and regulatory foundation threshold. It should be noted that the sign of governmental and civil environmental regulation on green total factor productivity will transform from negative to positive, if and only if threshold variables ascend and surpass the threshold value. Under the condition of metafrontier technology, governmental environmental awareness threshold value, based on the investigated corruption and malpractice cases by the procuratorates among every hundred thousand people, reaches 0.2158, and civil environmental awareness threshold value based on the per capita education level will attain 12.2330 years, and the corresponding regulatory foundation index threshold values are 0.0163 and 0.0154. These findings show clear policy implications: rather than continually promoting the level of governmental environmental regulation, civil performance, environmental awareness, and regulatory foundation should be considered