Cognition, Application and Discussion on Shaped Charge Hydraulic Smooth Blasting Technology

In the past, the main method of tunnel excavation in China was drilling and blasting, but the biggest shortcoming of the traditional drilling and blasting method is that it is easy to cause serious overexcavation and underexcavation. At the same time, the operation cycle time of this method is long, which leads to a serious waste of resources. Not only that, a large number of toxic gases and dust produced after blasting also do harm to the health of construction workers. So this is an urgent need for a new construction technology to solve this worldwide problem. In this situation, the leading experts in the field of tunnel, "The survey and design master of China" Shi Yuxin, Liu Pei, and well known expert in explosion field, yan-sheng ding, professor Chen Chengguang and Gu Yicheng, the experts group, cooperate with The Fifth Branch of China Railway 18th Bureau in northwest project management department, developed a new technology. This technology has passed the appraisal of scientific and technological achievements organized by Tianjin Science and Technology Commission, which is shaped hydraulic smooth blasting technology. The comprehensive evaluation of the technology is "international leading" level.This paper is mainly aimed at the drawbacks of drilling and blasting construction,combined with the author's cognition and discussion on the introduction of the new technology of cumulative hydraulic blasting and the practical application effect in the tunnel excavation process of the fourth company of China Railway 14th Bureau Group in the second division of the 9th bid section of Zhangjihuai Railway in Huainan Province

Supply of Online Environmental Information to Unknown Demand : The Importance of Interpretation and Liability Related to a National Network of River Level Data

The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1. It has been ethically considered within the University of Aberdeen's Framework for Research Ethics and Governance.Peer reviewedPublisher PD

MicroRNA-30b is a multifunctional regulator of aortic valve interstitial cells

ObjectiveCalcific aortic valve disease is an active process involving a wide range of pathologic changes. Valve interstitial cells are the most prevalent cells in the heart valve and maintain normal valve structure and function. MicroRNAs (miRNAs) are essential posttranscriptional modulators of gene expression, and miRNA-30b is a known repressor of bone morphogenetic protein 2–mediated osteogenesis. We hypothesized that miRNA-30b is a multifunctional regulator of aortic valve interstitial cells during calcification.MethodsTo determine the role of miRNA-30b in calcific aortic valve disease, we evaluated miRNA expression in human calcific aortic valve leaflets obtained intraoperatively. Furthermore, human valve interstitial cells were evaluated with regard to miRNA-30b expression and osteogenesis by quantitative real-time polymerase chain reaction, Western blotting, flow cytometry, and alkaline phosphatase assays.ResultsIn this study, we demonstrated that miRNA-30b attenuates bone morphogenetic protein 2–induced osteoblast differentiation by targeting Runx2, Smad1, and caspase-3. Transfection of a mimic of miRNA-30b led to decreases in alkaline phosphatase activity and expressions of Runx2, Smad1, and caspase-3. Furthermore, dual luciferase reporter assays confirmed that Runx2, Smad1, and caspase-3 are direct targets of miRNA-30b.ConclusionsWe demonstrated a remarkable role of miRNA-30b in calcific aortic valve disease as a regulator of human aortic valvular calcification and apoptosis through direct targeting of Runx2, Smad1, and caspase-3. Targeting of miRNA-30b could serve as a novel therapeutic strategy to limit progressive calcification in aortic stenosis

Split Over-Training For Unsupervised Purchase Intention Identification

Recognizing user-expressed intentions in social media can be useful for many applications such as business intelligence, as intentions are intimately linked to potential actions or behaviors. This paper focuses on a binary classification problem: whether a text expresses purchase intention (PI) or not (non-PI). In contrast to existing research, which relies on labeled intention corpus or linguistic knowledge, we proposed an unsupervised method called split over-training for the PI identification task. Experiments on PI identification from tweets showed that our approach was effective and promising. The best classifying accuracy of 84.6% and PI F-measure of 70.4% was achieved, which are only 7.7% and 4.9% respectively lower than fully supervised models. This means our unsupervised method may provide reasonable preprocessing for intention corpus labeling or intention knowledge acquisition

Environmental communication in the Information Age : Institutional barriers and opportunities in the provision of river data to the general public

Acknowledgements The authors thank SEPA, as well as all interviewees for their time, effort and openness. We are also grateful to two reviewers for their constructive comments. The research described here was supported by an award (EP/G066051/1) made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub at the University of Aberdeen. We also thank the ‘Science without Borders Programme’ funded by CNPq, Brazil (314033/2014-9).Peer reviewedPublisher PD