WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

高熵形状记忆合金的研究进展

高熵形状记忆合金是在等原子比NiTi合金的基础上,结合高熵合金的概念,逐渐发展起来的一种新型高温形状记忆合金。近年来,已开发出了综合性能优异的(TiZrHf)50(NiCoCu)50系和(TiZrHf)50(NiCuPd)50系高熵形状记忆合金,引起了广泛的关注和研究兴趣。本文从物相组成、微观组织、马氏体相变行为、形状记忆效应和超弹性等角度出发,综述了高熵形状记忆合金的研究进展,并对高熵形状记忆合金未来的研究重点进行了展望。     

Phase and microstructure evolution of Sc2O3–CeO2 –ZrO2ceramics in Na2SO4 + V2O5 molten salts

In this study, the destabilization resistance of Sc₂O₃ and CeO₂ co-stabilized ZrO₂ (SCZ) ceramics was tested in Na₂SO₄ + V₂O₅ molten salts at 750°C–1100 °C. The phase structure and microstructure evolution of the samples during the hot corrosion testing were analyzed with X-ray diffraction (XRD), Raman spectra, scanning electron microscopy (SEM), energy dispersive X-ray spectrum (EDS), and X-ray photoelectron spectroscopy (XPS). Results showed that the destabilization of SCZ ceramics at 750 °C was the result of the chemical reaction with V₂O₅ to produce m-ZrO₂ and CeVO₄, and little ScVO₄ was detected in the Sc₂O₃-rich SCZ ceramics. The primary corrosion products at 900 °C and 1100 °C were CeO₂ and m-ZrO₂ due to the mineralization effect. The Sc₂O₃-rich SCZ ceramics exhibited excellent degradation resistance and phase stability owing to the enhanced bond strength and the decreased size misfit between Zr⁴⁺ and Sc³⁺. The destabilization mechanism of SCZ ceramic under hot corrosion was also discussed.     

Characterization of the structure and properties of processed alumina-graphene and alumina-zirconia composites

The onset of hybrid alumina-based composites, which combines two or more nano-particles within the alumina matrix has already shown promising improvements in the matrix material. However, variations in mechanical properties including the optimum compositions that give improved properties faced with the development of alumina-based composites require further studies to understand the underlying mechanisms and synergistic effects of the nano-particle additions on the alumina matrix. In the current study, the structure and properties of Al?O?-graphene (0.5 wt%) and Al?O?–ZrO? (4 wt% and 10 wt%) composites fabricated via hot-pressing was studied as a baseline for multiple combinations. Even though the addition of 10 wt%ZrO? resulted in a 23% reduction in the grain size of the alumina matrix, the 4 wt%ZrO? addition resulted in a 14% increase in grain size as compared to the parent alumina matrix. X-ray diffraction analysis revealed that there was approximately 85% monoclinic (m-ZrO₂) vs. 15% tetragonal (t-ZrO₂) crystal structures in the A4ZrO? sample whilst the A₁₀ZrO? had approximately 93% m-ZrO₂ vs. 7% t-ZrO₂. The high-volume fraction of the monoclinic crystal structures in the A₁₀ZrO? accounts for the induced microcracks in the sample since the transition from the ductile-tetragonal to brittle-monoclinic is associated with the exertion of compressive stresses on the alumina matrix by the associated elastic volume expansion of m-ZrO₂. Also, the addition of 0.5 wt%graphene resulted in about 37% reduction in the grain size of the alumina matrix, and approximately 10% increase in hardness as a result of the distribution of graphene along the grain boundaries of the parent alumina matrix, which restricts grain coalescence and growth during processing. Furthermore, an increase up to 115% and 164% were observed in the fracture toughness (K_IC) with the inclusion of 0.5 wt%graphene and 10 wt%ZrO? respectively, which was primarily ascribed to the fine-grained microstructures and toughening mechanisms of the intergranular graphene and ZrO? particles.     

煤炭资源型城市转型模式研究：以徐州贾汪区为例

煤炭资源型城市为我国经济发展提供了重要的资源和能源支持,研究资源型城市转型的经验模式对调整区域经济结构、确保社会稳定和改善生态环境具有重要的实践意义。本文采用文献综述法和实证分析法,研究我国东部煤炭资源枯竭型城市转型所面临的共性难题,并以徐州贾汪区转型探索经历为例,总结城市转型的"徐州贾汪区模式",主要包括放大正向外部效应、长期坚持矿地融合、大力建设矿区社会生态系统恢复力三条路径。研究结果表明,煤炭城市转型发展的共性问题相互联系、相互影响,是一个系统性难题,必须引入系统性思维。我国东部矿区普遍人口密集,农业发达、沉陷积水是最主要的共性特征,煤炭开采产生的社会问题、经济问题、生态问题、环境问题基本相同,转型发展模式值得互鉴。     

Sub-band coding of hexagonal images

According to the circle-packing theorem, the packing efficiency of a hexagonal lattice is higher than an equivalent square tessellation. Consequently, in several contexts, hexagonally sampled images compared to their Cartesian counterparts are better at preserving information content. In this paper, novel mapping techniques alongside the wavelet compression scheme are presented for hexagonal images. Specifically, we introduce two tree-based coding schemes, referred to as SBHex (spirally-mapped branch-coding for hexagonal images) and BBHex (breadth-first block-coding for hexagonal images). Both of these coding schemes respect the geometry of the hexagonal lattice and yield better compression results. Our empirical results show that the proposed algorithms for hexagonal images produce better reconstruction quality at low bits per pixel representations compared to the tree-based coding counterparts for the Cartesian grid.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Polishing of zirconia ceramics by chemically-induced micro-nano bubbles

This study introduces micro-nano bubbles (MNBs) in the process of polishing zirconia ceramics through sodium borohydride hydrolysis to assist in polishing yttria-stabilized zirconia (YSZ). Compared with conventional silica sol, the material removal rate using this MNB-assisted technology is increased by 261.4%, and a lower surface roughness of 1.28 nm can be obtained. Raman, X-ray diffraction, and X-ray photoelectron spectroscopy are used to study the structural changes and phase stability of the YSZ during different polishing periods. The results show that MNBs are the key factor promoting the transformation from the tetragonal phase to the monoclinic phase on the surface of the YSZ during polishing. The H₂O molecules (or OH^? ions) on the surface of the YSZ are driven by the thermal kinetic energy of the micro-jets formed by the collapse of micro-bubbles, and they permeate to occupy more oxygen vacancies in the crystal lattice. Atomic force microscopy and nano-indentation tests show that the micro-protrusions on the surface of the YSZ preferentially undergo phase transformation, and their hardness decreases. This promotes abrasives to preferentially remove rough spots on the surface and achieve more efficient polishing. We believe this work adds valuable insights regarding low-temperature degradation and ultra-precise machining of YSZ ceramic materials.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.