拜耳法赤泥的处理和利用

解决了与赤泥有关的环境相容性问题。拜耳法赤泥与适量的石灰混合，经石灰消化、水热处理、煅烧处理和碱液溶出，可从赤泥回收７０％以上的Ａｌ２Ｏ３和９０％以上的Ｎａ２Ｏ，并使不溶残渣中Ｎａ２Ｏ含量降到１％以下。分离的铝酸钠溶液被送往拜耳法溶出料浆稀释过程，分离的残渣被进一步在７５０～９５０℃煅烧，制得活性βＣ２Ｓ为主的胶凝材料，可用作水泥的活性混合成分     

不同植被重建模式下赣北红壤侵蚀坡地土壤养分效应

为了探讨植被重建模式与土壤养分的关系,合理改良与利用红壤侵蚀坡地,本文分析了草本、果树、果树+草、果树+草+农作物和果树+农作物等不同植被重建模式对土壤养分的影响,并运用灰色关联分析方法对不同恢复模式的土壤养分效应进行综合评价。研究结果表明:不同植被重建模式土壤养分效应差异显著,以果树+横坡套种农作物改善土壤养分效应最好,然后依次是果树+草本模式(全区覆盖优于带状覆盖)、果+草+农作物模式、果树+纵坡套种农作物,草本、果树模式改善土壤养分效应最差。赣北侵蚀坡地植被恢复,可以优先考虑恢复果树+横坡套种农作物模式和果树+草本模式。     

引洮7~#隧洞含水疏松砂岩地层冻结法施工数值模拟

为探究含水疏松砂岩地层引水隧洞冻结施工中冻土帷幕的形成过程及力学特性,对引水隧洞的冻结施工及开挖过程进行三维数值模拟。研究了冻土帷幕的温度场、应力及位移的分布,计算出冻土帷幕完全形成所需的时间及其压、拉、剪应力极值并确定极值发生的位置。结合现场监测数据,分析了冻结过程中冻土的温度变化规律及冻土帷幕的形成机理,最后提出了相应的措施及建议。     

抓住机遇迎接挑战 为保护美丽长江再谱新篇

当前长江流域水资源保护面临难得的机遇,如何推进长江水生态文明建设,打造水清地绿天蓝的生态廊道是长江水资源保护工作的重大课题。通过对长江水资源保护问题的梳理,规划了今后一段时期的总体构想,从规划体系、水功能区监管、水生态保护、应急管理和监测监控等5个方面探讨了下一步的工作重点;提出了长江干流、主要支流、三峡、丹江口和长江口以及重点湖泊的保护措施;通过健全法规体系、创新管理机制、强化能力建设等,以逐步提升长江水资源保护能力、健全长江水资源保护管理体系,为保护美丽长江再谱新篇。     

四川盆地含膏盐红层特征及坝基工程地质问题(Ⅱ)

本文探讨了四川盆地含膏盐红层类岩溶作用引起的坝基工程地质问题,首先是地下水化学成分的改变及其对水工结构混凝土的腐蚀作用及坝基渗漏问题,然后确定了表征类岩溶作用强度的类岩溶强度因子(k).最后,通过类岩溶岩体Vp与主要岩体工程力学指标,诸如:允许承载力fak、抗剪(断)摩擦系数f(f')、变形模量(E0)的回归关系,探讨了类岩溶作用对坝基岩体弱化的作用.     

掏挖基础在强风化砂岩地基中的应用探讨

文章对强风化砂岩抗剪强度指标进行了分析和探讨,提出了用岩体结构面抗剪强度指标折减来获得强风化砂岩的内摩擦角和粘聚力的方法,并结合掏挖基础应用条件,通过计算掏挖基础在强风化砂岩地基应用时扩底成型稳定性,得出在强风化泥质粉砂岩和粉砂岩地区掏挖基础在施工过程中能够掏挖成型并大量应用的结论.     

革命旧址与周边景观的保护研究——对枣园环境文化景观的探讨与设计实践分析

强调"红色文化"的主体属性以及研究和探讨在景观设计中综合运用方法。"红色文化"的基本属性本身附着于"传统文化"的历史长河中,二者是相形不悖的统一综合体,是现今革命旧址文物保护单位重视的多层面要素问题之一。     

用化学计量学方法评定贮存血液细胞品质因素

用自动血液分析仪测定贮存全血的10个化验参数测定,按照主成分分析方法量化处理、计算化验数据,在主成分分析基础上,提出"细胞品质因素"作为综合评定指标的概念.用坐标平面图对贮存全血质量作出准确量化评定.结果说明"细胞品质因素"能较理想的评价贮存血液的质量,表明化学计量学方法在医学化验数据中可发现更多、更有价值的化学规律和生物信息.     

Promote Intratumoral Drug Release and Penetration to Counteract Docetaxel-Induced Metastasis by Photosensitizer-Modified Red Blood Cell Membrane-Coated Nanoparticle

The red blood cell membrane (RBCm) provides tight protection, lowers the immunogenicity, and prolongs the circulation time of drugs in vivo when acting as the coating of drug delivery systems. However, the cellular uptake and release of drugs are hindered by RBCm. Docetaxel (DTX) is the first-line medicine for treating triple-negative breast cancer (TNBC), but it induces tumor metastasis. To solve these dilemmas, in this study, the photosensitizer 1,1-dioctadecyl-3,3,3,3-tetramethylindotricarbocyanine iodide (DiR)-modified RBCm (DM) is prepared, which is coated onto a hybrid micelle consisting of the prodrugs of DTX and the anti-metastasis agent calcitriol (CTL), obtaining a nanoparticle, named HDC-DM. In a 4T1 tumor-bearing mouse model, after injecting HDC-DM, the intratumoral DTX and CTL concentrations are increased by 1.7 and 2.5 times compared with the free drug groups. After irradiating tumors with near-infrared laser, DiR elicits the photothermal effect, triggering the rupture of RBCm and drug release, promoting drug penetration in tumors, and inducing immunogenic cell death. The tumor growth inhibition rate is 77%, and the formation of lung metastases is reduced by 82%, with good biocompatibility. It is suggested that the combination of phototherapy, chemotherapy, and anti-metastatic therapy using HDC-DM is expected to be a powerful strategy for treating TNBC.     

Intelligent Machine Learning with Metaheuristics Based Sentiment Analysis and Classification

Sentiment Analysis (SA) is one of the subfields in Natural Language Processing (NLP) which focuses on identification and extraction of opinions that exist in the text provided across reviews, social media, blogs, news, and so on. SA has the ability to handle the drastically-increasing unstructured text by transforming them into structured data with the help of NLP and open source tools. The current research work designs a novel Modified Red Deer Algorithm (MRDA) Extreme Learning Machine Sparse Autoencoder (ELMSAE) model for SA and classification. The proposed MRDA-ELMSAE technique initially performs preprocessing to transform the data into a compatible format. Moreover, TF-IDF vectorizer is employed in the extraction of features while ELMSAE model is applied in the classification of sentiments. Furthermore, optimal parameter tuning is done for ELMSAE model using MRDA technique. A wide range of simulation analyses was carried out and results from comparative analysis establish the enhanced efficiency of MRDA-ELMSAE technique against other recent techniques.