Enhancing performance of low-temperature processed CsPbI2Br all-inorganic perovskite solar cells using polyethylene oxide-modified TiO_(2)

CsPbX_(3)-based(X=I,Br,Cl)inorganic perovskite solar cells(PSCs)prepared by low-temperature process have attracted much attention because of their low cost and excellent thermal stability.However,the high trap state density and serious charge recombination between low-temperature processed TiO_(2)film and inorganic perovskite layer interface seriously restrict the performance of all-inorganic PSCs.Here a thin polyethylene oxide(PEO)layer is employed to modify TiO_(2)film to passivate traps and promote carrier collection.The impacts of PEO layer on microstructure and photoelectric characteristics of TiO_(2)film and related devices are systematically studied.Characterization results suggest that PEO modification can reduce the surface roughness of TiO_(2)film,decrease its average surface potential,and passivate trap states.At optimal conditions,the champion efficiency of CsPbI_(2)Br PSCs with PEO-modified TiO_(2)(PEO-PSCs)has been improved to 11.24%from 9.03%of reference PSCs.Moreover,the hysteresis behavior and charge recombination have been suppressed in PEO-PSCs.

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

A Two-step Design Method for Shaft Work Targeting on Low-temperature Process

In low-temperature processes, there are interactions between heat exchanger network(HEN) and refrigeration system. The modification on HEN of the chilling train for increasing energy recovery does not always coordinate with the minimum shaft work consumption of the corresponding refrigeration system. In this paper, a systematic approach for optimizing low-temperature system is presented through mathematical method and exergy analysis. The possibility of "pockets", which appears as right nose section in the grand composite curve(EGCC) of the process, is first optimized. The EGCC with the pockets cutting down is designed as a separate part. A case study is used to illustrate the application of the approach for a HEN of a chilling train with propylene and ethylene refrigerant system in an ethylene production process.

A Joint Entity Relation Extraction Model Based on Relation Semantic Template Automatically Constructed

The joint entity relation extraction model which integrates the semantic information of relation is favored by relevant researchers because of its effectiveness in solving the overlapping of entities,and the method of defining the semantic template of relation manually is particularly prominent in the extraction effect because it can obtain the deep semantic information of relation.However,this method has some problems,such as relying on expert experience and poor portability.Inspired by the rule-based entity relation extraction method,this paper proposes a joint entity relation extraction model based on a relation semantic template automatically constructed,which is abbreviated as RSTAC.This model refines the extraction rules of relation semantic templates from relation corpus through dependency parsing and realizes the automatic construction of relation semantic templates.Based on the relation semantic template,the process of relation classification and triplet extraction is constrained,and finally,the entity relation triplet is obtained.The experimental results on the three major Chinese datasets of DuIE,SanWen,and FinRE showthat the RSTAC model successfully obtains rich deep semantics of relation,improves the extraction effect of entity relation triples,and the F1 scores are increased by an average of 0.96% compared with classical joint extraction models such as CasRel,TPLinker,and RFBFN.

New Process of Low-temperature Fixed-bed Fisher-Tropsch Reaction Using JL-GX Catalyst

On April 17, 2017 the new process of low-temperature fixed-bed Fisher-Tropsch reaction using the JL-GX catalyst developed independently by the Beijing Jingli Clean Energy Technology Company, Ltd., has been realized through the commissioning of the commercial demonstration unit at the Xingtai Rising Sun Chemical Company. In comparison with the conventional Fisher-Tropsch process, this novel Fisher-Tropsch process can be adapted to a variety of feed gases, which besides natural gas can also use the industrial offgases (including the coke oven gas, the coal seam gas, the oilfield associated gas, and the marsh gas) to manufacture synthetic chemicals through Fisher-Tropsch process.

Semantic-based query processing for relational data integration

To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.

The Analysis of Chapter One of Pride and Prejudice——Via Material Processes and Relational Processes

This paper, based on the material processes and relational processes, aims to analysis the deep meaning of chapter one of Pride and Prejudice. The relevant theories will come first in this paper. I will then analyze this extract from three aspects: the analysis of the objective plane of narration, the analysis of Mrs. Bennet' s discourse and the analysis of Mr. Bennet' s discourse.

Role of Microphysical Parameterizations with Droplet Relative Dispersion in IAP AGCM 4.1

Previous studies have shown that accurate descriptions of the cloud droplet effective radius （Re） and the autoconversion process of cloud droplets to raindrops （At） can effectively improve simulated clouds and surface precipitation, and reduce the uncertainty of aerosol indirect effects in GCMs. In this paper, we implement cloud microphysical schemes including two-moment Ar and Re considering relative dispersion of the cloud droplet size distribution into version 4.1 of the Institute of Atmospheric Physics＇s atmospheric GCM （IAP AGCM 4.1）, which is the atmospheric component of the Chinese Academy of Sciences＇ Earth System Model. Analysis of the effects of different schemes shows that the newly implemented schemes can improve both the simulated shortwave and longwave cloud radiative forcings, as compared to the standard scheme, in lAP AGCM 4.1. The new schemes also effectively enhance the large-scale precipitation, especially over low latitudes, although the influences of total precipitation are insignificant for different schemes. Further studies show that similar results can be found with the Community Atmosphere Model, version 5.1.

A comparative study of CuO/TiO_2-SnO_2,CuO/TiO_2 and CuO/SnO_2 catalysts for low-temperature CO oxidation

Nanometer SnO2 particles were synthesized by sol-gel dialytic processes and used as a support to prepare CuO supported catalysts via a deposition-precipitation method. The samples were characterized by means of TG-DTA, XRD, H2-TPR and XPS. The catalytic activity of the CuO/TiO2-SnO2 catalysts was markedly depended on the loading of CuO, and the optimum CuO loading was 8 wt.% （Tloo = 80 ℃）. The CuO/TiO2-SnO2 catalysts exhibited much higher catalytic activity than the CuO/TiO2 and CuO/SnO2 catalysts. H2-TPR result indicated that a large amount of CuO formed the active site for CO oxidation in 8 wt.% CuO/TiO2-SnO2 catalyst.

Batch process monitoring based on WGNPE–GSVDD related and independent variables

In many batch processes, there are related or independence relationships among process variables. The traditional monitoring method usually carries out a single statistical model according to the related or independent method, and in the feature extraction there is not fully taken into account the characterization of fault information, it will make the process monitoring ineffective, so a fault monitoring method based on WGNPE(weighted global neighborhood preserving embedding)–GSVDD(greedy support vector data description) related and independent variables is proposed. First, mutual information method is used to separate the related variables and independent variables. Secondly, WGNPE method is used to extract the local and global structures of the related variables in batch process and highlight the fault information, GSVDD method is used to extract the process information of the independent variables quickly and effectively. Finally, the statistical monitoring model is established to achieve process monitoring based on WGNPE and GSVDD. The effectiveness of the proposed method was verified by the penicillin fermentation process.

Construction of a macromolecular structural model of Chinese lignite and analysis of its low-temperature oxidation behavior

The aim of this paper is to analyze the change in the active structure of lignite during the process of lowtemperature oxidation by constructing a molecular structure model for lignite. Using quantum computation combined with experimental results of proximate analysis, ultimate analysis, Fourier transform infrared spectroscopy(FTIR) and X-ray photoelectron spectroscopy(XPS), a structural model for the large molecular structure was constructed. By analyzing the bond lengths in the model molecule, the evolution law for the active structure of lignite was predicted for the process of low-temperature oxidation. In low-temperature oxidation,alkanes and hydroxyls are the primary active structures observed in lignite, though ether may also react. These active functional groups react with oxygen to release heat, thereby speeding up the reaction between coal and oxygen. Finally, the content of various functional groups in the process of lignite low-temperature oxidation was analyzed by infrared analysis, and the accuracy of the model was verified.

A systematic approach for synthesizing a low-temperature distillation system

In this paper, by combining a stochastic optimization method with a refrigeration shaft work targeting method,an approach for the synthesis of a heat integrated complex distillation system in a low-temperature process is presented. The synthesis problem is formulated as a mixed-integer nonlinear programming(MINLP) problem,which is solved by simulated annealing algorithm under a random procedure to explore the optimal operating parameters and the distillation sequence structure. The shaft work targeting method is used to evaluate the minimum energy cost of the corresponding separation system during the optimization without any need for a detailed design for the heat exchanger network(HEN) and the refrigeration system(RS). The method presented in the paper can dramatically reduce the scale and complexity of the problem. A case study of ethylene cold-end separation is used to illustrate the application of the approach. Compared with the original industrial scheme, the result is encouraging.

A Discussion on the Relational Process of Business Negotiation

It is widely known that business negotiation is an indispensable part in international trade and probably the most common type of negotiation.Generally speaking,business negotiation is a process which business negotiators would make the interaction in order to get specific exchange goals.Because of the important role of business negotiations in business world,many Chinese researchers have engaged in study of business and achieved many useful findings.Although there are many researches in the field of business negotiation,focusing on the analysis of relational process of business negotiation is less,which is the main con cern of this thesis.The aim of this thesis is to find the language mechanism and characteristic of business negotiation.At the meantime,negotiators are more likely to attain the deep perception in choosing the better words and structure among the negotiation.

Analysis of sea level changes in the Caspian Sea related to Cosmo-geophysical processes based on satellite and terrestrial data

Analysis results of the average annual sea levels in the Caspian Sea obtained from ground and satellite observations, corresponding to solar activity characteristics, magnetic field data, and length of day are presented. Spectra of the indicated processes were investigated and their approximation models were also built. Previously assumed statistical relationships between space-geophysical processes and Caspian Sea level(CSL) changes were confirmed. A close connection was revealed between the low-frequency models of the solar and geomagnetic activity parameters and the CSL changes. Predictions extending into the next decades showed a high probability of an increase in the CSL and a decrease of the compared space-geophysical parameters.

Mechanisms underlying syntactic and semantic processing of Chinese simple sentences Evidence from event-related brain potentials

This study sought to test the processing of three types of sentences in Chinese, as correct sentences, semantic violation sentences, and sentences containing semantic and syntactic violations, based on the following sentence pattern： ＂subject （noun） ＋ yi/gang/zheng ＋ predicate （verb）＂. Event-related potentials on the scalp were recorded using 32-channel electroencephalography. Compared with correct sentences, target words elicited an early left anterior negativity （N400） and a later positivity （P600） over frontal, central and temporal sites in sentences involving semantic violations. In addition, when sentences contained both semantic and syntactic violations, the target words elicited a greater N400 and P600 distributed in posterior brain areas. These results indicate that Chinese sentence comprehension involves covert grammar processes.

百年中国现代化进程的历史反思与时代性超越——兼论“三农”问题的历史累积与乡村振兴的实现

以洋务运动为始,中国走上以工业化为主导的现代化道路。但是,中国传统文明与西方式现代化取向之间形成历史“悖论”,这种悖论关系更突出体现在城乡背离化发展态势上。如何走出具有中国特色的现代化道路,并从根本上摆脱这一困境,一直是中国共产党的历史使命之一。在总结和汲取近代以来中国现代化发展经验和教训的基础上,中国共产党领导人民成功走出中国式现代化道路。中国共产党通过乡村振兴战略的全面实施,从根本上突破近代以来百余年的“三农”困境,从而解决了中国现代化发展中的“悖论”问题。

婴幼儿头皮医用粘胶相关性皮肤损伤防护方案的构建与应用

目的降低视频脑电图监测婴幼儿头皮医用粘胶相关性皮肤损伤。方法采用历史对照设计,将2018年1月至2019年12月入住癫痫监测单元行头皮视频脑电图监测的患儿856例纳入对照组,实施常规皮肤护理;将2021年1月至2022年12月入住癫痫监测单元行头皮视频脑电图监测的患儿851例纳入观察组,构建和实施医用粘胶相关性皮肤损伤防护方案。比较两组头皮医用粘胶相关性皮肤损伤发生率。结果观察组头皮医用粘胶相关性皮肤损伤发生率显著低于对照组(P<0.05)。结论婴幼儿头皮医用粘胶相关性皮肤损伤防护方案的应用,可有效降低婴幼儿头皮医用粘胶相关性皮肤损伤发生率。

基于自适应损失函数的句子级远程监督关系抽取

远程监督关系抽取是一种关系抽取方法,现有方法主要采用多实例学习,在具有相同实体对的样例包上进行关系抽取。但是,包级方法只能缓解却并不能完全解决错误标签问题。基于此,文中首先分析了干净数据和噪声数据的分布,提出了一种新的自适应损失函数;在此基础上,提出了一种基于自适应损失函数的句子级远程监督关系抽取方法。在公开数据集NYT-10以及基于TACRED的合成数据集上的实验结果表明:文中提出的方法优于对比文献中的方法,能够更有效地区分错误标签噪声样例和干净样例,提高了句子级远程监督关系抽取的准确率。

海南省波浪能开发智能化适宜性分析模型研究

针对目前波浪能开发适宜性分析方法存在的问题及工作量大、成本高的特点,基于地理信息系统(Geographic information system, GIS)、改进的多准则决策方法(Multi-criteria decision making, MCDM)和人工神经网络(Artificial neural network, ANN)提出海南省波浪能开发智能化适宜性分析模型。对于该模型:首先,使用模糊层次分析(Fuzzy analytic hierarchy process, FAHP)法计算评价指标权重,降低专家主观偏差,更好地描述信息的不确定性;其次,提出灰色关联分析-折衷优化(Grey relation analysis-vlse kriterijumska optimizacijaⅠkompromisno resenje, GRA-VIKOR)法计算开发适宜性指数,解决评价过程中部分信息丢失、评价结果不准确的问题;最后依托反向传播(Back propagation, BP)神经网络进行模型训练并进行验证,实现海南省波浪能开发适宜性分析的智能化,不仅提高工作效率,而且降低计算成本。通过模型得到海南省波浪能可开发区域和开发适宜性等级,为海南省波浪能选址决策奠定基础,同时可填补海南省波浪能开发适宜性分析在智能化领域的空白。

基于信噪比和灰色关联分析的电火花喷爆加工工艺参数优化

随着SiCp/Al复合材料应用领域日益广泛,对其加工效率和表面质量提出了更高的要求。针对上述问题,设计L 25(56)的正交试验,使用一种新型高效的电火花加工方式——电火花喷爆加工,对20%的SiCp/Al复合材料进行工艺试验。主要优化指标为材料蚀除率(MRR)、电极损耗率(TWR)和表面粗糙度(Ra),工艺参数为高压波电流、高压波电压、低压波电流、低压波电压、脉宽和相位差。根据正交试验结果,采用信噪比分析法,研究得到各工艺参数对不同优化指标的影响以及单目标最优加工参数组合。基于灰色关联度分析法,以层次分析法确定各优化指标权重,分析得到综合考虑3个优化指标的多目标最优加工参数组合,并进行试验验证。结果表明,多目标优化的最优工艺参数组合为高压波电流6 A、高压波电压120 V、低压波电流2 A、低压波电压100 V、脉宽10μs、相位差50%,使用该加工参数组合进行加工可以有效地提高加工效率、改善表面质量。