Utilization of pyrolytic oil and hydrogen enriched syngas from single feedstock (delonix regia) through pyrolysis process and its influence on performance and emission characteristics in CI engine

The main objective of the present investigation is to conduct the performance, combustion and emission analysis of CI engine operated using hydrogen enriched syngas (pyrolytic gas) and biodiesel (pyrolytic oil) as dual fuel mode condition. Both the pyrolytic oil and syngas is obtained from single feedstock delonix regia fruit pod through pyrolysis process and then pyrolytic oil is converted into biodiesel through esterification. Initially biomass is subjected to thermal degradation at various pyrolysis temperature ranges like 350–600 °C. During the pyrolysis process syngas, pyrolytic oil and char are produced. The syngas is directly used in the CI engine and pyrolytic oil is converted into biodiesel and then used in the CI engine. The pyrolytic oil and syngas is subjected to FTIR and GC/TCD analysis respectively. The syngas analysis confirms the presence of various gases like H₂, CH₄, CO₂, CO and C₂H₄ in different proportions. The various proportions of the syngas is mainly depending upon the reactor temperature and moisture content in the biomass. The syngas composition varies with increase in the temperature and at 400 °C, higher amount of hydrogen is present and its composition are H₂ 28.2%, CO is 21.9%, CH₄ is 39.1% and other gases in smaller amounts. The biodiesel of B20 and syngas of 8lpm produced from the same feedstock are considered as test sample fuels in the CI engine under dual fuel mode operation to study the performance and emission characteristics. The study reveals that BTE has slight increase than diesel of 1.5% at maximum load. On the another hand emission like CO, HC and smoke are reduced by 15%,25% and 32% respectively at full load condition, whereas NO_x emission is increased at all loads in the range of 10–15%. Therefore B20+syngas of 8lpm can be used as an alternative fuel in CI engine without any modification and major products from pyrolysis process with waste biomass is fully used as fuel in the CI engine.     

A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.     

Optimal resilient power grid operation during the course of a progressing wildfire

We study a two-stage stochastic and nonlinear optimization model for operating a power grid exposed to a natural disaster. Although this approach can be generalized to any natural hazard of continuous (and not instantaneous) nature, our focus is on wildfires. We assume that an approaching wildfire impacts the power grid by reducing the transmission capacity of its overhead lines. At the time when proactive decisions have to be taken, the severity of the wildfire is not known. This introduces uncertainty. In this paper, we extend previous work by more realistically capturing this uncertainty and by strengthening the mathematical programming formulation through standard reformulation techniques. With these reformulation techniques, the resulting two-stage, convex mixed-integer quadratically constrained programming formulation can be efficiently solved using commercial quadratic programming solvers as demonstrated on a case study on a modified version of the IEEE 123-bus test system with 100 scenarios. We also quantify the uncertainties through a second case study using the following three standard metrics of two-stage stochastic optimization: the expected value of perfect information, the expected result of using the expected value solution and the value of the stochastic solution.     

基于二元水循环的水量-水质-水效联合调控模型开发与应用

为将我国最严格水资源管理制度的实践与二元水循环理论相结合，提高“三条红线”控制指标的科学性与合理性，本文以SWAT模型为基础，通过改进子流域划分方法、添加经济社会模块和人工用水模块，对其人工侧支循环模拟进行了系统的完善，开发了基于SWAT的水量-水质-水效联合调控模型SWAT_WAQER。以广西南流江流域为例，从国民经济用水量、河道径流与水质等方面对模型进行校验，并在此基础上划分了2030年“三条红线”控制指标。结果表明：该模型性能良好，能够用于不同节水情景下的国民经济用水量、污染物排放量、水功能区水质达标结果分析，可以作为科学制定“三条红线”控制指标的有力支撑工具。     

Data sharing mechanism of various mineral resources based on blockchain

Basins with various mineral resources coexisting and enriching often occupy an important strategic position. The exploration of various mineral resources is repetitive at present due to unshared data and imperfect management mechanism. This situation greatly increases the cost of energy exploitation in the country. Traditional data-sharing mode has several disadvantages, such as high cost, difficulty in confirming the right of data, and lack of incentive mechanism, which make achieving real data sharing difficult. In this paper, we propose a data-sharing mechanism based on blockchain and provide implementation suggestions and technical key points. Compared with traditional data-sharing methods, the proposed data-sharing mechanism can realize data sharing, ensure data quality, and protect intellectual property. Moreover, key points in the construction are stated in the case study section to verify the feasibility of the data-sharing system based on blockchain proposed in this paper.     

Learning keyword phrases from query logs of USPTO patent examiners for automatic query scope limitation in patent searching

Professional search in patent repositories poses several unique challenges. One key requirement is to search the entire affected space of concepts, following well-defined procedures to ensure traceability of results obtained. Several techniques have been introduced to enhance query generation, preferably via automated query term expansion, to improve retrieval effectiveness. Currently, these approaches are mostly limited to computing additional query terms from patent documents based on statistical measures. For conceptual search to solve the limitation of traditional keyword search standard dictionaries are used to provide synonyms and keyword phrases for query refinement. Studies show that these are insufficient in such highly specialized domains. In this paper, we present an approach to extract keyword phrases from query logs created during the validation procedure of the patent applications. This creates valuable domain-specific lexical databases for several specific patent classes that can be used to both expand as well as limit the scope of a patent search. This provides a more powerful means to guide a professional searcher through the search process. We evaluate the lexical databases based on real query sessions of patent examiners.     

招远市金矿资源开发利用调查评价研究

为深入贯彻生态文明思想，促进矿产资源全面节约和高效利用，对招远市展开了金矿矿产资源开发利用水平调查评价，对2018年度数据进行整理和实地核查后，进行了单个矿山评价和多矿山评价，包括矿种评价、地区评价、行业评价。招远市16个矿山实际数据和基准值指标对比显示，单个矿山评价和多矿山评价的达标率均为100%。在此基础上，分析了金矿矿产资源资源开发利用水平调查评价的意义和存在问题。     

Malic acid production from renewables: a review

Malic acid derived from fossil resources is currently applied in the food and beverage industries with a medium global production capacity. However, in the transition from a fossil-based to a bio-based economy, biotechnologically produced l -malic acid may become an important platform chemical with many new applications, especially in the field of biopolymers. In this review, currently used petrochemical production routes to dl -malic acid are outlined and insights into possible bio-based alternatives for microbial l -malic acid production are provided. Besides ecological reasons, the possibility to produce enantiopure l -malic acid by microbial fermentation is the biggest advantage over chemical synthesis. State-of-the-art and open challenges concerning production host engineering, substrate choice and downstream processing are addressed. With regard to production hosts, a literature overview is given covering the leading natural production strains of Aspergillus, Ustilago and Aureobasidium, as well as Escherichia coli as the most important engineered recombinant host. The utilization of renewable substrates as an alternative to glucose is emphasized in particular as a key aspect for a competitive bio-based production. Out of the alternative substrates discussed in this review, the industrial side-streams crude glycerol and molasses seem to be most promising for large-scale l -malic acid production. © 2019 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

流域泥沙灾害与泥沙资源性的研究

泥沙灾害与泥沙资源性是流域泥沙的重要属性,二者在一定条件下可以相互转化。本文论述了泥沙淤积、泥沙冲刷、岸滩崩塌、山地崩塌与泥石流、粗沙淤积的土地沙化等泥沙灾害,指出泥沙灾害具有时空分布的不均匀性、渐变性或突发性、群发性、转化性及危害严重性等;流域泥沙资源化的主要途径包括填海造陆及造地、引洪淤灌、堤防淤临淤背、建筑材料、湿地形成(河流、湖泊与河口海岸)等,指出流域泥沙资源化及其优化配置既要解决思想观念、基本理论、目标效益等方面的问题,还要考虑与水资源联合配置问题。