基于数据质量评价的目标估计

针对目标估计过程需要大量人工参与、自动化程度低的问题，提出了基于数据质量评价的目标估计方法。利用目标数据质量评价方法，对不同传感器得到的目标数据质量进行科学、有效的测度和评价，并根据质量得分动态调整各数据源在目标估计过程中所占的权重，从而减少人工干预，提高目标估计效能。仿真试验结果证明了该方法的有效性。     

Ni2P(O)–Fe2P(O)/CeOx as high effective bifunctional catalyst for overall water splitting

The development of cost-effective bifunctional catalysts with excellent performance and good stability is of great significance for overall water splitting. In this work, NiFe layered double hydroxides (LDHs) nanosheets are prepared on nickel foam by hydrothermal method, and then Ni₂P(O)–Fe₂P(O)/CeO_x nanosheets are in situ synthesized by electrodeposition and phosphating on NiFe LDHs. The obtained self-supporting Ni₂P(O)–Fe₂P(O)/CeO_x exhibit excellent catalytic performances in alkaline solution due to more active sites and fast electron transport. When the current density is 10 mA cm^?2, the overpotential of hydrogen evolution reaction and oxygen evolution reaction are 75 mV and 268 mV, respectively. In addition, driven by two Ni₂P(O)–Fe₂P(O)/CeO_x electrodes, the alkaline battery can reach 1.45 V at 10 mA cm^?2.     

Electronic regulation and core-shell hybrids engineering of palm-leaf-like NiFe/Co(PO3)2 bifunctional electrocatalyst for efficient overall water splitting

Constructing efficient and stable bifunctional electrocatalysts for overall water splitting remains a challenge because of the sluggish reaction kinetics. Herein, the core-shell hybrids composed of Co(PO₃)₂ nanorod core and NiFe alloy shell in situ grown on nickel foam (NiFe/Co(PO₃)₂@NF) are synthesized. Owing to the hierarchical palm-leaf-like structures and strong adhesion between NiFe alloys, Co(PO₃)₂ and substrates, the catalyst provides a large surface area and rapid charge transfer, which facilitates active sites exposure and conductivity enhancement. The interfacial effect in the NiFe/Co(PO₃)₂ core-shell structure modulates the electronic structure of the active sites around the boundary, thereby boosting the intrinsic activity. Benefiting from the stable structure, the durability of the catalyst is not impaired by the inevitable surface reconfiguration. The NiFe/Co(PO₃)₂@NF electrode presents a low cell voltage of 1.63 V to achieve 10 mA cm^?2 and manifests durability for up to 36 h at different current densities.     

离子型稀土矿山淋洗及尾水富集试验研究

对浸矿后离子型稀土原地浸矿场采用清水进行淋洗，在184天的清水淋洗过程中，尾水氨氮值从最开始的507mg/L，降低至140mg/L，淋洗尾水pH4.52~3.10。淋洗尾水采用两级反渗透膜分离，既回收有价资源稀土，又能使出水氨氮达标。结果表明，产水氨氮浓度稳定低于15mg/L，对稀土的截留率高于98.25%，浓水中稀土离子平均浓度313.4mg/L，可进一步回收稀土资源。     

Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

减水剂类型对赤泥—矿渣基地聚物注浆材料性能的影响及机理研究

针对赤泥等固体废弃物对环境危害性大且利用率低等问题,以碱激发赤泥-矿渣基地聚物注浆材料为 研究对象,研究了不同掺量的聚羧酸(PA)减水剂、醛酮缩合物(AKC)减水剂和萘系(N)减水剂对材料凝结时间、流动 性及强度等的影响,并通过 XRD、傅里叶红外光谱及 SEM 等设备对减水剂的作用机理进行研究。 结果表明:减水剂增 强了材料的流动性但降低了材料的剪切应力;N 和 PA 减水剂能缩短材料的凝结时间,但 AKC 减水剂会延长材料的凝 结时间;N 和 AKC 减水剂能提高材料的强度,但 PA 减水剂会降低材料的强度;N 减水剂对材料的综合性能提升效果 更加明显,其最优掺量为 0. 7%;减水剂对赤泥-矿渣基地聚物性能提升的作用机理主要是促进地聚合物凝胶的形成。 研究成果为拓展赤泥在工程上的使用途径和效率提供了理论指导。     

机器翻译译文质量估计综述

机器翻译译文质量估计(Quality Estimation,QE)是指在不需要人工参考译文的条件下,估计机器翻译系统产生的译文的质量,对机器翻译研究和应用具有很重要的价值。机器翻译译文质量估计经过最近几年的发展,取得了丰富的研究成果。该文首先介绍了机器翻译译文质量估计的背景与意义;然后详细介绍了句子级QE、单词级QE、文档级QE的具体任务目标、评价指标等内容,进一步概括了QE方法发展的三个阶段: 基于特征工程和机器学习的QE方法阶段,基于深度学习的QE方法阶段,融入预训练模型的QE方法阶段,并介绍了每一阶段中的代表性研究工作;最后分析了目前的研究现状及不足,并对未来QE方法的研究及发展方向进行了展望。     

A blockchain-based audit approach for encrypted data in federated learning

The development of data-driven artificial intelligence technology has given birth to a variety of big data applications. Data has become an essential factor to improve these applications. Federated learning, a privacy-preserving machine learning method, is proposed to leverage data from different data owners. It is typically used in conjunction with cryptographic methods, in which data owners train the global model by sharing encrypted model updates. However, data encryption makes it difficult to identify the quality of these model updates. Malicious data owners may launch attacks such as data poisoning and free-riding. To defend against such attacks, it is necessary to find an approach to audit encrypted model updates. In this paper, we propose a blockchain-based audit approach for encrypted gradients. It uses a behavior chain to record the encrypted gradients from data owners, and an audit chain to evaluate the gradients’ quality. Specifically, we propose a privacy-preserving homomorphic noise mechanism in which the noise of each gradient sums to zero after aggregation, ensuring the availability of aggregated gradient. In addition, we design a joint audit algorithm that can locate malicious data owners without decrypting individual gradients. Through security analysis and experimental evaluation, we demonstrate that our approach can defend against malicious gradient attacks in federated learning.     

非常规气藏储层改造体积评价方法研究

为精确描述非常规气藏压裂后的复杂流动特征及定量评价储层改造体积（SRV），利用自主研发的缝网重构算法“破裂树生长法”建立压后缝网模型，并以此为基础提出了使用拟稳态流动时特定的压力等值线来确定SRV范围的定量评价方法，最后以长宁201井区为例进行了矿场实例分析。该方法根据微地震监测点的位置，重构出微裂缝网的连通关系。在复杂微裂缝网的基础上建立离散裂缝地质模型并进行生产数值模拟，根据数值模拟结果的压力分布精确划定SRV的范围。利用该方法计算出长宁201井区的SRV体积为0.052 1 km3，以该缝网模型的数值模拟产量预测结果符合实际生产规律，方法实用性较好。     

Predictive environmental hydrogen embrittlement on fracture toughness of commercial ferritic steels with hydrogen-modified fracture strain model

In this work, a practical numerical model with few parameters was proposed for the prediction of environmental hydrogen embrittlement. The proposed method adopts hydrogen enhanced plasticity-based mechanism in a fracture strain model to describe hydrogen embrittlement. Fracture toughness degradation of three commercial steels SA372J70, AISI4130 and X80 in high pressure hydrogen environment were investigated. Firstly, governing equations for hydrogen distribution and material damage evolution was established. Hydrogen enhanced localized flow softening effect was coupled within fracture strain dependency on stress triaxiality. Then, the numerical implementation and identification process of model parameters was described. Model parameters of the investigated steels were determined based on experiment results from literatures. Finally, with the calibrated model, fracture toughness reduction of the steels was predicted in a wide range of hydrogen pressure. The prediction results were compared with experimental results. Reasonable accuracy was reached. The proposed method is an attempt to reach balance between physical accurate prediction and engineering practicality. It is promising to provide a simplified numerical tool for the design and fit for service evaluation of hydrogen storage vessels.