Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Reliability analysis for mine blast performance based on delay type and firing time

Mining blasts may be defined as the use of explosive charges in a controlled manner by following a tightly controlled timing sequence according to an assigned firing order. Changes of timing between charges may result in an altered firing order and failure of the blasting sequence, which can cause high vibration levels, poor fragmentation, and/or an undesirable rock mass movement direction. Despite the importance of timing in determining mine blast results, there exists a lack of methodologies or tools with which to assess performance of a complete blast based on delay type and timing sequence. This document applies reliability engineering principles to evaluate the performance of a mine blast. The analyses are based on test results of the accuracy and precision of electronic and pyrotechnic detonators for typical firing times used in a surface coal mine, but may be applied to a variety of mines and timing scenarios.     

Exploring behavioural patterns during complex problem-solving

In this explorative study, we investigate how sequences of behaviour are related to success or failure in complex problem-solving (CPS). To this end, we analysed log data from two different tasks of the problem-solving assessment of the Programme for International Student Assessment 2012 study (n = 30,098 students). We first coded every interaction of students as (initial or repeated) exploration, (initial or repeated) goal-directed behaviour, or resetting the task. We then split the data according to task successes and failures. We used full-path sequence analysis to identify groups of students with similar behavioural patterns in the respective tasks. Double-checking and minimalistic behaviour was associated with success in CPS, while guessing and exploring task-irrelevant content was associated with failure. Our findings held for both tasks investigated, from two different CPS measurement frameworks. We thus gained detailed insight into the behavioural processes that are related to success and failure in CPS.     

Targeted editing of intronic-splicing silencer enhancement of SMN2 Exon 7 inclusion by CRISPR/Case 9

Spinal muscular atrophy (SMA) is an autosomal recessive hereditary neuromuscular disease. Exon 7 and 8 of survival of motor neuron 1 (SMN1) gene or only exon 7 homology deletion leads to the failure to produce a full-length SMN gene. The copy number of SMN2 gene with high homology of SMN1 affects the degree of disease and was the target gene for targeting therapy, in which splicing silencer in intron 7 was the key to suppress the inclusion of exon 7. In this study, we projected to use CRISPR/Case 9 for the targeted editing of intronic-splicing silencer (ISS) sequence to promote the inclusion of SMN2 exon 7 and increase the production of SMN2 full-length (FL) gene expression. It happens that there was a protospacer adjacent motif (PAM) at one end of the ISS sequence according to the design of sgRNA. The recombinant vector of sgRNA HSMN2 CRISPR/Case 9 was constructed and transfected into HEK293 cells. Sequencing results showed that the ISS sequence could be edited accurately and targeting in the predicted direction, in which deleting small fragments, inserting small amounts and mutation. Quantitative analysis of RT-PCR products by restriction enzyme of DdeI digestion showed that the FL of SMN2 increased by 8% (P < 0.05). In the primary cultured chondrocytes of SMA mice, in which sgRNA HSMN2 CRISPR/Case9 recombinant vector transfection could increase the SMN2 FL gene by 23% (P < 0.05) and significantly improve SMN protein levels (P < 0.05). CRISPR/Case 9 is an effective tool for gene editing and therapy of hereditary diseases, but it is rarely reported in the treatment of SMA diseases. This study shows that CRISPR/Case 9 was first used for the precision target of ISS sequence editing, which can effectively promote the production of SMN2 FL gene expressions, in which there was an important clinical reference value.     

A novel long short-term memory networks-based data-driven prognostic strategy for proton exchange membrane fuel cells

Proton exchange membrane fuel cell (PEMFC) long-term prognostic facilitates reducing the time/cost of the durability tests and is a critical starting point for control/maintenance suggestions. Long short-term memory (LSTM) recurrent neural networks have excellent time series processing capabilities and are proved to be useful for the short-term prognostic of PEMFC. However, LSTM prognostic models usually suffer from accumulated errors and model recognition uncertainties, which make it difficult to break the historical degradation data limitations, resulting in unsatisfactory long-term prediction performance. To tackle the problem, this paper proposes a novel model named navigation sequence driven LSTM (NSD-LSTM) for long-term prognostic. In the strategy, a navigation sequence is firstly generated by using an autoregressive integrated moving average model with exogenous variables. The sequence is then fed iteratively into LSTM in the implementation stage to achieve long-term perdition. The proposed strategy is evaluated using the aging experimental data of two types of PEMFC under different operating conditions. The long-term prognostic performance of the proposed model and other two state-of-the-art prognostic models, namely, nonlinear autoregressive exogenous and echo state network, are evaluated through comparison experiments. The simulation and experimental results show that the proposed prognostic strategy has better long-term degradation trend prediction consistency and remaining useful life estimation robustness.     

奇周期最佳几乎二进序列偶理论研究

提出了一种新的具有良好奇周期相关特性的最佳离散信号——奇周期最佳几乎二进序列偶。奇周期最佳几乎二进序列偶中2个序列中均有一个元素为 “0”元素,其他元素取值均为“＋1”或“－1”,并且其奇周期自相关函数为单值脉冲函数。同时研究了奇周期最佳几乎二进序列偶的变换性质和频谱特性,给出了一些组合允许条件。研究结果表明,奇周期最佳几乎二进序列偶扩大了奇周期最佳几乎二进序列的存在空间,且为奇周期最佳几乎二进序列偶中2个序列相同时的特殊情况。     

从《赞美》一诗看穆旦对自由诗学的实验

穆旦提出自由诗"新的抒情"的诗学主张,在他的早期代表诗歌<赞美>中有充分的体现.通过分析<赞美>诗的节奏韵律特色,从声与意相结合的诗学标准,总结穆旦所提出的"洪大节奏"创作原则,归纳出穆旦诗歌节奏的两个原则:循序渐进原则与对等原则.对穆旦<赞美>的分析,再一次地让人体味到诗人是以自己的方式写自由诗,用自己的"身体"和"头脑"来为自由诗正名.穆旦的诗歌"主要意义在于它的坚韧探索本身与探索所包含的深刻启迪性".     

潜江凹陷潜江组盐湖地层演化与层序发育特征

结合盐湖层序地层分析，在系统测试了潜江凹陷潜江组碳、氧同位素后，对其演化规律与层序地层的关系进行了探讨，研究结果表明：潜江组内δ^13C和δ^18O值的变化范围分别是-7.37‰～2.35‰。和-6.42‰～0．23‰(PDB)。在低位体系域的初期和高位体系战的末期，由于湖水范围较小，这对如果降雨量小于蒸发量就会有盐岩的沉积，所以其碳、氧同位素的值偏大；而在水进体系战时期，由于湖平面上升，湖水的注入量大于蒸发量，所以这一对期没有盐岩的沉积，碳、氧同位素的值也偏低。然而在对潜江组的潜四段进行研究时，却发现碳、氧同位素的分布不具上述规律。在潜四段盐岩不仅分布于低位体系战的初期和高位体系战的末期，而且在水进体系域中也可见盐岩。作者认为潜江凹陷潜江组可能存在另一种成盐模式一深水事件性成盐。     

基于混沌时间序列的神经网络对瓦斯涌出量预测

瓦斯灾害是煤矿中最严重的灾害之一,瓦斯治理是我国煤矿安全的主攻方向。瓦斯涌出量的预测对遏制矿山瓦斯灾害、保证矿山安全和矿山技术经济指标都有重要意义。传统的方法预测精度不高,而神经网络在构建网络模型时具有一定的主观性。将混沌时间序列理论引入瓦斯预测中,为构建神经网络模型提供理论依据。通过实例证明在实际应用中是可行的。