NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval

Pseudo-relevance feedback (PRF) is commonly used to boost the performance of traditional information retrieval (IR) models by using top-ranked documents to identify and weight new query terms, thereby reducing the effect of query-document vocabulary mismatches. While neural retrieval models have recently demonstrated strong results for ad-hoc retrieval, combining them with PRF is not straightforward due to incompatibilities between existing PRF approaches and neural architectures. To bridge this gap, we propose an end-to-end neural PRF framework that can be used with existing neural IR models by embedding different neural models as building blocks. Extensive experiments on two standard test collections confirm the effectiveness of the proposed NPRF framework in improving the performance of two state-of-the-art neural IR models.Comment: Full paper in EMNLP 201

The application of improved signal summing method into the spacecraft force limited vibration test

This paper provides an improved signal summing method for the spacecraft force limited vibration test system with eight force transducers. The key point for this method is to change the combination way of the signals coming out of the eight force transducers while the formulas inside the signal conditioning amplifier have been used skillfully. This method had been successfully adopted in the spacecraft force limited vibration test and the accuracy requirements of key force and moment signals have been met. And this method has been proved to be a very powerful tool for providing the critical force and moment data used to determine the force limited profile during the spacecraft dynamic test

Arsenic and Cadmium Accumulation in Soil as Affected by Continuous Organic Fertilizer Application: Implications for Clean Production

As and Cd in soil can be assimilated and accumulated by vegetables and can be subsequently ingested by humans. Contradictory effects of organic fertilizer application on As and Cd accumulation in soil have been reported in previous studies. An eight-year greenhouse study was conducted on a sandy loam soil in Beijing, China to investigate the effects of organic fertilizer application rate on soil properties, and As and Cd accumulation in soil. The contamination risk of pak choi grown after eight years’ application of organic fertilizer was also evaluated. Soil organic carbon increased 3.0–3.8 times with low, medium and high rates of fertilizer application in 2018 compared to the initial soil. Organic fertilizer application significantly increased soil nutrients and microbial biomass while it mildly affected soil pH. The bioavailability of As/Cd has decreased after eight years’ application of organic fertilizer. Pak choi crop harvested from all three treatments in 2018 did not pose a threat to human health, even for life-time consumption. Soil total As content significantly decreased with organic fertilizer application, mainly due to the lower As content in the applied fertilizer than that in soil. Continuous application of clean organic fertilizer can be adopted to reduce the contamination risk of highly contaminated soil in the soil–plant system

Multi-Objective Optimization for Reservoir Operation Considering Water Diversion and Power Generation Objectives

Due to the uneven distribution of water resources in time and space, the problem of water shortage has become increasingly serious in some areas. To optimize use of water resources, it is urgent to establish multi-objective models and apply effective optimization algorithms to guide reservoir management. This study proposed a model of multi-objective optimization for reservoir operation (MORO) with the objectives of maximizing water diversion and power generation. The multi-objective evolutionary algorithm based on decomposition with adaptive weight vector adjustment (MOEA/D-AWA) was applied to solve the MORO problem. In addition, the performance of the MOEA/D-AWA was compared with two other algorithms based on the hyper-volume index. Huangjinxia reservoir, which is located in Shaanxi, China, was selected as the case study. The results show that: (1) the proposed model is effective and reasonable in theory; (2) the optimization results obtained by MOEA/D-AWA demonstrate this algorithm can be applied to the MORO problem, providing a set of evenly distributed non-dominated solutions; and (3) water diversion and power generation are indeed contradictory objectives. The MORO strategy can be used to efficiently utilize water resources, improve the comprehensive benefits of reservoirs, and provide decision support for actual reservoir operation