Outsourcing CO2 within China

Recent studies have shown that the high standard of living enjoyed by people in the richest countries often comes at the expense of CO2 emissions produced with technologies of low efficiency in less affluent, developing countries. Less apparent is that this relationship between developed and developing can exist within a single country’s borders, with rich regions consuming and exporting high-value goods and services that depend upon production of low-cost and emission-intensive goods and services from poorer regions in the same country. As the world’s largest emitter of CO2, China is a prominent and important example, struggling to balance rapid economic growth and environmental sustainability across provinces that are in very different stages of development. In this study, we track CO2 emissions embodied in products traded among Chinese provinces and internationally. We find that 57% of China’s emissions are related to goods that are consumed outside of the province where they are produced. For instance, up to 80% of the emissions related to goods consumed in the highly developed coastal provinces are imported from less developed provinces in central and western China where many low–value-added but high–carbon-intensive goods are produced. Without policy attention to this sort of interprovincial carbon leakage, the less developed provinces will struggle to meet their emissions intensity targets, whereas the more developed provinces might achieve their own targets by further outsourcing. Consumption-based accounting of emissions can thus inform effective and equitable climate policy within China

Impact resistance of Nomex honeycomb sandwich structures with thin fibre reinforced polymer facesheets

In order to investigate the impact resistance of the Nomex honeycomb sandwich structures skinned with thin fibre reinforced woven fabric composites, both drop-weight experimental work and meso-mechanical finite element modelling were conducted and the corresponding output was compared. Drop-weight impact tests with different impact parameters, including impact energy, impactor mass and facesheets, were carried out on Nomex honeycomb-cored sandwich structures. It was found that the impact resistance and the penetration depth of the Nomex honeycomb sandwich structures were significantly influenced by the impact energy. However, for impact energies that cause full perforation, the impact resistance is characterized with almost the same initial stiffness and peak force. The impactor mass has little influence on the impact response and the perforation force is primarily dependent on the thickness of the facesheet, which generally varies linearly with it. In the numerical simulation, a comprehensive finite element model was developed which considers all the constituent materials of the Nomex honeycomb, i.e. aramid paper, phenolic resin, and the micro-structure of the honeycomb wall. The model was validated against the corresponding experimental results and then further applied to study the effects of various impact angles on the response of the honeycomb. It was found that both the impact resistance and the perforation depth are significantly influenced by the impact angle. The former increases with the obliquity, while the latter decreases with it. The orientation of the Nomex core has little effect on the impact response, while the angle between the impact direction and the fibre direction of the facesheets has a great influence on the impact response. </jats:p

BioNMT: A Biomedical Neural Machine Translation System

To solve the problem of translation of professional vocabulary in the biomedical field and help biological researchers to translate and understand foreign language documents, we proposed a semantic disambiguation model and external dictionaries to build a novel translation model for biomedical texts based on the transformer model. The proposed biomedical neural machine translation system (BioNMT) adopts the sequence-to-sequence translation framework, which is based on deep neural networks. To construct the specialized vocabulary of biology and medicine, a hybrid corpus was obtained using a crawler system extracting from universal corpus and biomedical corpus. The experimental results showed that BioNMT which composed by professional biological dictionary and Transformer model increased the bilingual evaluation understudy (BLEU) value by 14.14%, and the perplexity was reduced by 40%. And compared with Google Translation System and Baidu Translation System, BioNMT achieved better translations about paragraphs and resolve the ambiguity of biomedical name entities to greatly improved

A prospective study on the association between spinal anesthesia and obesity

Purpose: To compare the outcomes of spinal anesthesia in obese and non-obese patients.Methods: In this study, 199 patients who underwent total knee replacement arthroplasty (TKRA) were categorized into obesity group (n = 61) and non-obesity group (n = 138). Anesthesia was considered successful if a bilateral T12 sensory blockage occurred within the first 15 min of injection of intrathecal drug. Parameters that influence spinal anesthesia were analyzed using logistic regression by means of multiple variables that independently influence the outcome of spinal anesthesia.Results: It was observed that the independent predictors for successful anesthesia in the patients were dose of bupivacaine (odds ratio at 95 % confidence interval = 2.08; range: 1.61 - 2.67) and obesity status (odds ratio at 95 % confidence interval = 2.83; range: 1.21 - 6.49). The outcome of the multivariate analysis also indicated that the dose of bupivacaine, body mass index (BMI) and obesity were predictors of spinal anesthesia. It was also found that the period of the sensory blockage due to bupivacaine was longer in the obesity group than in the non-obesity group.Conclusion: Sensory blockage in bupivacaine anesthesia during TKRA is influenced by dose of bupivacaine, obesity and BMI.Keywords: Spinal anesthesia, Total knee replacement arthroplasty, Bupivacaine, Obesity, Body mass index, Logistic regressio

Research on the impact mechanism of scientific and technological innovation on the high-quality development of the marine economy

Promoting the high-quality development of the marine economy is an inevitable choice for building a maritime power, and technological innovation can provide strong impetus for the high-quality development of the marine economy. Therefore, it is urgent to clarify the impact mechanism of technological innovation on the high-quality development of the marine economy, and promote the high-quality development of the marine economy. This study employs panel data from 11 coastal provinces and municipalities (autonomous regions) in China, spanning the years 2006 to 2020. The objective is to empirically evaluate the mechanism through which scientific and technical innovation impacts the high-quality development of the marine economy. This is achieved by utilizing the PVAR model and the mediation effect model. The research findings indicate that there is a noteworthy impact of enhancing scientific and technological innovation on the marine economy of China. Moreover, there exists a significant reciprocal relationship between scientific and technological innovation and the pursuit of high-quality development in the marine economy. It is observed that scientific and technological innovation not only has a positive influence on the high-quality development of the marine economy by enhancing green total factor productivity and optimizing the industrial structure, but it also facilitates the advancement of the marine economy through the chain mediation path of “improving green total factor productivity and optimizing industrial structure”