燕麦蒽酰胺生理功能研究进展

目的 探究尾静脉注射短链酰基辅酶A脱氢酶(SCAD)重组腺病毒能否改善自发性高血压大鼠(SHR)血管重构。方法 实验分为6组:Wistar+NS组、Wistar+GFP组、Wistar+Ad-SCAD组、SHR+NS组、SHR+GFP组和SHR+Ad-SCAD组。腺病毒包装的SCAD和GFP纯化后,以尾静脉方式注射给药8周。采用超声心动图检测大鼠心功能情况；采用无创血压仪检测大鼠的血压变化；主动脉HE染色、天狼星红染色、DHE染色、TUNEL染色、EVG染色,观察血管重构。采用实时荧光定量PCR检测相关基因mRNA表达变化、Western blot检测相关蛋白表达变化,观察游离脂肪酸、一氧化氮(NO)和ATP含量变化。结果 (1)尾静脉注射SCAD重组腺病毒,大鼠主动脉中SCAD蛋白出现过表达,mRNA水平增高,SCAD酶活性增加；(2)在病理状态下,增加主动脉中SCAD表达,可以降低血压,改善心功能,改善血管管腔大小,减少胶原沉积,减少血管活性氧(ROS)的生成和细胞凋亡；(3)在病理状态下,SCAD的表达增加可减少血清和主动脉中游离脂肪酸的含量,增加组织中的ATP水平,激活内皮型一氧化氮合酶(eNOS)磷酸化,增加主动脉NO的生成。结论 自发性高血压大鼠主动脉SCAD的表达增加能逆转高血压血管重构,可能与其减少血清中游离脂肪酸的含量、增加NO水平、减少活性氧生成、消除氧化应激有关。     

Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art,challenges and opportunities

Blockchain possesses the potential of transforming global supply chain management. Gartner predicts that blockchain could be able to track $2?T of goods and services in their movement across the globe by 2023, and blockchain will be a more than $3 trillion business by 2030. Nowadays, a growing number of blockchain initiatives are disrupting traditional business models in each sector. In this paper, we provide a timely and holistic overview of the state-of-the-art, challenges, gaps and opportunities in global supply chain and trade operations for both the private sector and governmental agencies, by synthesising a wide range of resources from business leaders, global international organisations, leading supply chain consulting firms, research articles, trade magazines and conferences. We then identify collaborative schema and future research directions for industry, government, and academia to jointly work together in ensuring that the full potential of blockchain is unleashed amidst the socioeconomic, geopolitical and technological disruptions that global supply chains and trade are facing.     

5G基站供配电勘察设计思路的调整分析

针对5G基站设备相对于以往2G/3G/4G设备的变化,面向一线勘察设计人员,阐述5G基站在供配电需求方面功耗增大、供电方式多样化、供配电改造工作量和难度加大等相应变化,归纳相应的勘察前期准备工作要点,分析在实际工作中可能面临的外市电引入改造、供电方式选择的多样性、新型锂电池应用等重点、难点,介绍理想的5G供配电模式及发展方向,最后提出5G基站供配电勘察设计工作思路调整的建议。     

Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor

A semiconductor distributor that plays a third-party role in the supply chain will buy diverse components from different suppliers, warehouse and resell them to a number of electronics manufacturers with vendor-managed inventories, while suffering both risks of oversupply and shortage due to demand uncertainty. However, demand fluctuation and supply chain complexity are increasing due to shortening product life cycle in the consumer electronics era and long lead time for capacity expansion for high-tech manufacturing. Focusing realistic needs of a leading distributor for semiconductor components and modules, this study aims to construct a UNISON framework based on deep reinforcement learning (RL) for dynamically selecting the optimal demand forecast model for each of the products with the corresponding demand patterns to empower smart production for Industry 3.5. Deep RL that integrates deep learning architecture and RL algorithm can learn successful policies from the dynamic and complex real world. The reward function mechanism of deep RL can reduce negative impact of demand uncertainty. An empirical study was conducted for validation showing practical viability of the proposed approach. Indeed, the developed solution has been in real settings.     

Dynamic Stabilization of DNA Assembly by Using Pyrrole-Imidazole Polyamide

We used N-methylpyrrole (Py)-N-methylimidazole-(Im) polyamide as an exogenous agent to modulate the formation of DNA assemblies at specific double-stranded sequences. The concept was demonstrated on the hybridization chain reaction that forms linear DNA. Through a series of melting curve analyses, we demonstrated that the binding of Py−Im polyamide positively influenced both the HCR initiation and elongation steps. In particular, Py−Im polyamide was found to drastically stabilize the DNA duplex such that its thermal stability approached that of an equivalent hairpin structure. Also, the polyamide served as an anchor between hairpin pairs in the HCR assembly, thus improving the originally weak interstrand stability. We hope that these proof-of-concept results can inspire future use of Py−Im polyamide as a molecular tool to modulate the formation of DNA assemblies.     

不同苯乙烯工艺技术经济分析及建议

通过对国内外苯乙烯市场供需趋势的梳理,针对4种苯乙烯主要生产工艺,重点从原料可获性、产品质量、能耗物耗以及成本竞争力等方面对不同工艺主要技术经济指标进行了对比分析,并提出了行业可持续发展的有关建议。     

亲子乐园空调送风方式的数值模拟研究

大型综合室内亲子乐园属于高大空间,设有游乐设施和游戏的特殊性使得对空间的舒适性要求一致,但是送风气流遇阻严重,室内存在较多气流死角,影响室内空气质量和儿童健康。因此其空调设计不仅需要考虑温度、风速的空间均匀度,还要考虑各点的空气龄和PMV-PPD指标。以天津某亲子乐园为研究对象,利用scSTREAM软件对适用于该房间的辐射供冷加新风、置换通风、混合通风三种空调方式的送风效果进行数值模拟分析,从流场的均匀性、人员的热舒适性等方面对模拟结果进行探讨,研究结果表明辐射供冷加新风方式的空间均匀性和PMV指标最佳,混合通风方式的空气龄最小。     

一种5 重real-time PCR筛查转基因水稻方法的建立

以转基因水稻中最常用的CaMV35S启动子、NOS终止子、Cry1Ab/Ac基因、HPT基因及SPS水稻内标基因为研究对象，利用5 种不同的荧光信号（FAM、HEX、Taxas Red、Cy5、Cy5.5）进行多重实时聚合酶链式反应（real-time polymerase chain reaction，real-time PCR）检测方法的研究。通过引物组合筛选、反应体系优化、特异性测试、灵敏度测试、适用性测试等一系列实验，建立了5 重real-time PCR方法，灵敏度可达0.032%。此方法具有灵敏度高、结果准确、通量大等优点，可实现水稻中转基因成分的快速、高效检测。