基于Python的油田生产资料预处理软件设计与应用

油田内部生产资料类型包括钻井、录井、测井、试油等多种类型。针对资料整理过程中存在的问题如:从原始资料库中下载的资料格式多样;不同石油软件所需加载的数据格式不同;已有资料预处理软件功能均较单一等,从编程语言优选、软件兼容性、软件功能集成化三个方面出发,选取Python语言进行软件设计,利用Python扩展性强的特点,设计出红番茄资料预处理软件,并在新疆油田进行试点,生产资料整理时间缩短至原耗时间的约33%。Python语言在油田生产中的应用可为具有相同问题的其他油田提供参考。     

Optimizing PSMA Radioligand Therapy for Patients with Metastatic Castration-Resistant Prostate Cancer. A Systematic Review and Meta-Analysis

The aim of the review was to evaluate patient and treatment characteristics for patients with metastatic castration-resistant prostate cancer (mCRPC) treated with PSMA radioligand therapy (PRLT) associated with above-average outcome. The systematic review and meta-analysis followed recommendations by the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA). We searched for publications in PubMed, Embase, and ClinicalTrials.gov up to 31 September 2020. Thirty-six publications and four duplicates reported 2346 patients. Nearly two-thirds of the patients had bone metastases. Median overall survival (OS) was 16 months. Asymptomatic patients and patients with only lymph node metastases lived longer than symptomatic patients and patients with more extensive metastases. Patients treated with an intensified schedule of ¹⁷⁷Lu PRLT lived longer than those treated with a conventional schedule. Half of the patients obtained a PSA decline ≥ 50% and these patients lived longer than those with less PSA decline. Approximately 10% of the patients developed hematologic toxicity with anemia grade 3 as the most severe adverse effect. Characteristics for patients, cancer, restaging, and PRLT predict above average overall survival following treatment with PRLT.     

基于语言模型的预训练技术研究综述

预训练技术当前在自然语言处理领域占有举足轻重的位置。尤其近两年提出的ELMo、GTP、BERT、XLNet、T5、GTP-3等预训练模型的成功,进一步将预训练技术推向了研究高潮。该文从语言模型、特征抽取器、上下文表征、词表征四个方面对现存的主要预训练技术进行了分析和分类,并分析了当前自然语言处理中的预训练技术面临的主要问题和发展趋势。     

Ni2V2O7 dandelion microsphere for a high-performance electrocatalyst in water splitting

Water splitting is an effective way to produce hydrogen to solve the energy crisis problem, and inorganic metal compounds are widely used in electrocatalysis field due to efficient hydrogen evolution reaction (HER). Herein, we synthesize Ni₂V₂O₇ dandelion microsphere from nickel nitrate and vanadium pentoxide by “one-step hydrothermal” way, which exhibits large specific surface area of 102.74 m² g⁻¹. The as-prepared Ni₂V₂O₇ microsphere shows good electrocatalysis performances including OER overpotential of 358 mV and good stability, as well as HER overpotential of 195 mV. Furthermore, the Ni₂V₂O₇ microsphere electrode is assembled to Ni₂V₂O₇ microsphere//Ni₂V₂O₇ microsphere system, showing the water splitting voltage of 1.50 V at 10 mA cm⁻² by two-electrode method, which is much lower than those of commercial RuO₂//Pt/C system and most of spinel oxides electrocatalysts. Our work opens up a new and facile avenue for fabricating inorganic microsphere electrocatalyst in hydrogen production field.     

Specific Oxygenated Groups Enriched Graphene Quantum Dots as Highly Efficient Enzyme Mimics

Significant progress is achieved for the utilization of graphene quantum dots as enzyme mimics in various biomedical fields recently. Although promising, the biocatalytic performance is far from satisfactory. Here, the rational design and synthesis of specific oxygenated groups enriched graphene quantum dots (o‐GQDs) via a facile oxidation reflux route is reported. These well‐prepared o‐GQDs with uniform size exhibit an ultrahigh peroxidase‐like activity in a wide range of pH values, and their superior performance is verified by using glucose detection as a typical model. Compared with classical nanozymes, these o‐GQDs show multiple times higher enzymatic activity. It is believed that the super facile synthesis strategy can greatly facilitate the practical use of o‐GQDs as enzyme mimics in the future.     

跨领域文本情感分类研究进展

作为社会媒体文本情感分析的重要研究课题之一，跨领域文本情感分类旨在利用源领域资源或模型迁移地服务于目标领域的文本情感分类任务，其可以有效缓解目标领域中带标签数据不足问题.本文从三个角度对跨领域文本情感分类方法行了归纳总结：（1）按照目标领域中是否有带标签数据，可分为直推式和归纳式情感迁移方法；（2）按照不同情感适应性策略，可分为实例迁移方法、特征迁移方法、模型迁移方法、基于词典的方法、联合情感主题方法以及图模型方法等；（3）按照可用源领域个数，可分为单源和多源跨领域文本情感分类方法.此外，论文还介绍了深度迁移学习方法及其在跨领域文本情感分类的最新应用成果.最后，论文围绕跨领域文本情感分类面临的关键技术问题，对可能的突破方向进行了展望.     

酶解-挤出复合工艺对高直链淀粉材料制备和性质的影响

以高直链淀粉为原料制备的淀粉基材料力学性质优良。但其熔融流变性差,挤出加工能耗高。本论文采用酶解-挤出复合工艺,考察了耐高温α淀粉酶对挤出环境的耐受性,以及酶加入量、挤出时间等参数对材料制备和性质的影响。结果表明,耐高温α淀粉酶在密炼机的挤出环境中依然有酶活力,能够促进淀粉颗粒的结构相变,从而降低单位机械能耗,缩短加工时间。具体而言,在0.25%的酶加入量下(淀粉干基重量),G50淀粉挤出加工的单位能耗下降了21%。但酶解也会造成分子链的降解,削弱材料性质。与空白材料相比,经酶解-挤出工艺的淀粉基材料,其拉伸强度降低了33%,断裂伸长率减少了83%。另一方面,耐高温α淀粉酶对G80淀粉挤出加工的影响不显著。上述结果表明,可以利用酶解-挤出复合工艺降低生产能耗,缩短加工时间,且酶解会提高淀粉的活性位点和反应效率,有利于淀粉的反应挤出。     

Augmented reality in language learning: A state-of-the-art review of 2014–2019

This systematic review study synthesizes research findings pertaining to the use of augmented reality (AR) in language learning. Published research from 2014 to 2019 has been explored and specific inclusion and exclusion criteria have been applied resulting in 54 relevant publications. Our findings determined: (a) devices and software employed for mastering AR; languages and contexts in which AR had been applied; theoretical perspectives adopted for guiding the use of AR; the number of participants in AR activities and benefits from using AR as an educational tool in the language classroom; (b) alignment of the affordances of Augmented Reality with the KSAVE (Knowledge, Skills, Attitudes, Values, Ethics) 21st-century skills framework; (c) future directions in AR research and practice. The main findings from this review demonstrate the popularity of mobile-based AR for supporting vocabulary (23.9%), reading (12.7%), speaking (9.9%) writing (8.5%) or generic language skills (9.9%). Our findings also uncovered areas that merit future attention in the application of AR in language learning – for instance learning theories were not often considered in the implementation of AR. The study concludes with suggestions for future research especially in the areas of instructional design and user experience.