Poly[octa­aquadi-μ-phosphato-trinickel(II)]. Corrigendum

Corrigendum to Acta Cryst. (2008), E64, m259

Knowledge-refined Denoising Network for Robust Recommendation

Knowledge graph (KG), which contains rich side information, becomes an essential part to boost the recommendation performance and improve its explainability. However, existing knowledge-aware recommendation methods directly perform information propagation on KG and user-item bipartite graph, ignoring the impacts of \textit{task-irrelevant knowledge propagation} and \textit{vulnerability to interaction noise}, which limits their performance. To solve these issues, we propose a robust knowledge-aware recommendation framework, called \textit{Knowledge-refined Denoising Network} (KRDN), to prune the task-irrelevant knowledge associations and noisy implicit feedback simultaneously. KRDN consists of an adaptive knowledge refining strategy and a contrastive denoising mechanism, which are able to automatically distill high-quality KG triplets for aggregation and prune noisy implicit feedback respectively. Besides, we also design the self-adapted loss function and the gradient estimator for model optimization. The experimental results on three benchmark datasets demonstrate the effectiveness and robustness of KRDN over the state-of-the-art knowledge-aware methods like KGIN, MCCLK, and KGCL, and also outperform robust recommendation models like SGL and SimGCL

Poly[octa­aquadi-μ-phosphato-trinickel(II)]

In the title compound, [Ni3(PO4)2(H2O)8]n, which was synthesized hydro­thermally, all the Ni atoms are located in slightly distorted octa­hedral coordination environments. Two phosphate groups and two Ni atoms share a centrosymmetric four-membered ring and an eight-membered ring such that the four-membered ring is inside the eight-membered ring. The eight-membered rings are connected with the other Ni atoms (lying on centres of symmetry) through phosphate anions, generating a one-dimensional chain structure. Adjacent chains are connected through hydrogen bonds, forming a three-dimensional network

Reversible resistance switching properties in Ti-doped polycrystalline Ta2O5 thin films

Unipolar reversible resistance switching effects were found in 5 at% Ti-doped polycrystalline Ta 2O 5 films with the device structure of Pt/Ti-Ta 2O 5/Pt. Results suggest that the recovery/rupture of the conductive filaments which are involved in the participation of oxygen vacancies and electrons leads to the resistance switching process. Tidoped Ta 2O 5 thin films possess higher resistance whether in low-resistance state or high-resistance state and higher resistance switching ratio than Ta 2O 5 thin films, where Ti addition plays an important role in the resistance switching process by suppressing the migration of oxygen vacancies via forming an electrically inactive Ti/O-vacancy complex. Excellent retention properties of the high and low resistances under constant stress of applied voltage were obtained

Unipolar resistance switching and abnormal reset behaviors in Pt/CuO/Pt and Cu/CuO/Pt structures

The effects of Pt and Cu top electrodes on resistance switching properties were investigated for CuO thin films with Pt/CuO/Pt and Cu/CuO/Pt sandwich structures. Typical unipolar resistance switching (URS) behaviors and two different kinds of resistance changes in the reset process were observed in both structures. When voltages were applied to the film, the low-resistance state (LRS) with relatively low resistance value (50 Ω), the resistance first decreased then increased to HRS, showing abnormal reset behavior. The former variation of LRS could be ascribed to the decrease in filament size induced by Joule heating, while the latter one could be ascribed to the growth of disconnected filaments induced by high electric fields. This study indicates that the switching modes and the abnormal reset behaviors in CuO thin films are not due to Pt and Cu top electrodes, but the intrinsic properties of CuO film

Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration

The sparsity of extrinsic rewards poses a serious challenge for reinforcement learning (RL). Currently, many efforts have been made on curiosity which can provide a representative intrinsic reward for effective exploration. However, the challenge is still far from being solved. In this paper, we present a novel curiosity for RL, named DyMeCu, which stands for Dynamic Memory-based Curiosity. Inspired by human curiosity and information theory, DyMeCu consists of a dynamic memory and dual online learners. The curiosity arouses if memorized information can not deal with the current state, and the information gap between dual learners can be formulated as the intrinsic reward for agents, and then such state information can be consolidated into the dynamic memory. Compared with previous curiosity methods, DyMeCu can better mimic human curiosity with dynamic memory, and the memory module can be dynamically grown based on a bootstrap paradigm with dual learners. On multiple benchmarks including DeepMind Control Suite and Atari Suite, large-scale empirical experiments are conducted and the results demonstrate that DyMeCu outperforms competitive curiosity-based methods with or without extrinsic rewards. We will release the code to enhance reproducibility

Realization of rectifying and resistive switching behaviors of TiO2 nanorod arrays for nonvolatile memory

Both the rectifying and resistive switching behaviors are reported in single-crystalline TiO2 nanorod arrays (NRAs). The transition from rectifying to bipolar resistive switching behavior can be controlled by a forming process. The surface of TiO2 nanorods and the Pt/TiO2 NRAs interface play crucial roles on resistive switching. In low resistance state, the dependence of resistance on cell area indicates that filaments form on each individual nanorod, which contributes to the narrow distribution of resistive switching parameters. These results suggest that single-crystalline TiO2 NRAs could be used as nanowire-based switch element and memory cell for next-generation nonvolatile memory

Application of remote sensing method in coal fire identification in Ningwu Coalfield

Coal fire cause serious influence on environment, economy and safety of surrounding area. It is of great significance to accurately identify the scope of coal fire caused by spontaneous combustion in coal field for monitoring and controlling coal fire. Relevant scholars identified the scope of coal fire by extracting surface thermal anomaly or surface deformation information respectively, but due to the single method and means, there are many factors causing the occurrence of coal fire, so the experimental results are not accurate enough. In order to improve the accuracy of coal fire identification, the coal fire identification method combining satellite thermal infrared technology and radar technology is applied to the fire area identification of Ningwu Coalfield in Shanxi Province through practical application research. Firstly, the ASTER–TES(Temperature-Emissivity Separation) algorithm is used to retrieve land surface Temperature from ASTER thermal infrared data at night. At the same time, surface subsidence information is inverted using The Sentinel-1 data of SBAS–InSAR(Small Baseline Subset InSAR) technology, and then the abnormal high temperature area and abnormal settlement area in the study area are extracted by threshold segmentation method, and then the range of suspected coal field fire area is obtained by fusion processing. Finally, the experimental results are compared and verified by the coal fire range determined by the field survey method of measuring radon. The results show that the accuracy of the proposed method is as high as 93.78%, which is 43.29% and 62.23% higher than that of the single temperature inversion method and the settlement anomaly method. However, some fire zones have not been identified, mainly because it is difficult to obtain the threshold of identifying fire zones using surface deformation. The results show that the cooperative identification method of thermal infrared technology and radar technology can effectively overcome the deficiency of single identification method, significantly improve the identification accuracy of coal fire range, and provide a powerful reference for accurately determining the control range of fire area. In order to obtain more comprehensive and accurate range of coal fire, it is necessary to study the characteristics of surface deformation detection method in the future