Interactions of Li2O volatilized from ternary lithium-ion battery cathode materials with mullite saggar materials during calcination

In recent years, the rapid development of Li(Ni_xCo_yMn_1-x-y)O₂ (LNCM) materials for application in ternary lithium-ion batteries has led to an increased demand for refractory kiln saggars in industries. However, saggars used for firing ternary Li-ion battery cathode materials are often subjected to severe corrosion and spalling. To investigate the damage mechanism of the saggar materials, non-contact corrosion experiments were designed to study the effects of the precursor additions, calcination temperature, and number of calcinations during the interaction between mullite saggar and LNCM materials. The phase composition and microstructure of the mullite saggar specimens before and after corrosion were characterized using X-ray diffraction and scanning electron microscopy, respectively, to obtain a comprehensive understanding of the causes of the deterioration of mullite saggar materials during corrosion.     

Influence of metal-support interactions on reaction pathways over Ni/CeZrOx–Al2O3 catalysts for ethanol steam reforming

This work investigates selective Ni locations over Ni/CeZrO_x–Al₂O₃ catalysts at different Ni loading contents and their influences on reaction pathways in ethanol steam reforming (ESR). Depending on the Ni loading contents, the added Ni selectively interacts with CeZrO_x–Al₂O₃, resulting in the stepwise locations of Ni over CeZrO_x–Al₂O₃. This behavior induces a remarkable difference in hydrogen production and coke formation in ESR. The selective interaction between Ni and CeZrO_x for 10-wt.% Ni generates more oxygen vacancies in the CeZrO_x lattice. The Ni sites near the oxygen vacancies enhance reforming via steam activation, resulting in the highest hydrogen production rate of 1863.0 μmol/g_cat·min. In contrast, for 15 and 20-wt.% Ni, excessive Ni is additionally deposited on Al₂O₃ after the saturation of Ni–CeZrO_x interactions. These Ni sites on Al₂O₃ accelerate coking from the ethylene produced on the acidic sites, resulting in a high coke amount of 19.1 mg_c/g_cat·h (20Ni/CZ-Al).     

基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。     

4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

Preparation of high-activity coal char-based catalysts from high metals containing coal gangue and lignite for catalytic decomposition of biomass tar

The potential of using high metals containing coal gangue and lignite to prepare high-activity coal char-based catalysts is investigated for effective biomass tar decomposition. Loose structure and rough surface are formed for these char-based catalysts with heterogeneous distribution of a large number of inorganic particles. In the biomass tar decomposition, the performance of the coal char-based catalysts is significantly influenced by the content of the metals in the raw materials and coal gangue char (GC) with the ash content as high as 50.80% exhibits the highest activity in this work. A high biomass tar conversion efficiency of 93.5% is achieved at 800 °C along with a significant increase in the fuel gas product. During the five-time consecutive tests, the catalytic performance of GC increases a little at the second or third times reuse and remains relatively stable, showing the remarkable stability of the catalyst in biomass tar decomposition applications.     

The Function of Sialidase Revealed by Sialidase Activity Imaging Probe

Sialidase cleaves sialic acid residues from glycans such as glycoproteins and glycolipids. In the brain, desorption of the sialic acid by sialidase is essential for synaptic plasticity, learning and memory and synaptic transmission. BTP3-Neu5Ac has been developed for sensitive imaging of sialidase enzyme activity in mammalian tissues. Sialidase activity in the rat hippocampus detected with BTP3-Neu5Ac increases rapidly by neuronal depolarization. It is presumed that an increased sialidase activity in conjunction with neural excitation is involved in the formation of the neural circuit for memory. Since sialidase inhibits the exocytosis of the excitatory neurotransmitter glutamate, the increased sialidase activity by neural excitation might play a role in the negative feedback mechanism against the glutamate release. Mammalian tissues other than the brain have also been stained with BTP3-Neu5Ac. On the basis of information on the sialidase activity imaging in the pancreas, it was found that sialidase inhibitor can be used as an anti-diabetic drug that can avoid hypoglycemia, a serious side effect of insulin secretagogues. In this review, we discuss the role of sialidase in the brain as well as in the pancreas and skin, as revealed by using a sialidase activity imaging probe. We also present the detection of influenza virus with BTP3-Neu5Ac and modification of BTP3-Neu5Ac.     

Microstructure and mechanical properties of α/β-Si3N4 composite ceramics with novel ternary additives prepared via spark plasma sintering

In this study, α/β-Si₃N₄ composite ceramics with high hardness and toughness were fabricated by adopting two different novel ternary additives, ZrN–AlN–Al₂O₃/Y₂O₃, and spark plasma sintering at 1550 °C under 40 MPa. The phase composition, microstructure, grain distribution, crack propagation process and mechanical properties of sintered bulk were investigated. Results demonstrated that the sintered α/β-Si₃N₄ composite ceramics with ZrN–AlN–Al₂O₃ contained the most α phase, which resulted in a maximum Vickers hardness of 18.41 ± 0.31 GPa. In the α/β-Si₃N₄ composite ceramics with ZrN–AlN–Y₂O₃ additives, Zr₃AlN MAX-phase and ZrO phase were found and their formation mechanisms were explained. The fracture appearance presented coarser elongated β-Si₃N₄ grains and denser microstructure when 20 wt% TiC particles were mixed into Si₃N₄ matrix, meanwhile, exhibited maximum mean grain diameter of 0.98 ± 0.24 μm. As a result, the compact α/β-Si₃N₄ composite ceramics containing ZrN–AlN–Y₂O₃ additives and TiC particles displayed the optimal bending strength and fracture toughness of 822.63 ± 28.75 MPa and 8.53 ± 0.21 MPa?m^1/2, respectively. Moreover, the synergistic toughening of rod-like β-Si₃N₄ grains and TiC reinforced particles revealed the beneficial effect on the enhanced fracture toughness of Si₃N₄ ceramic matrix.     

Phase composition,microstructure, and properties of Al4O4C–(Al2OC)1-x(AlN)x –Zr2Al3C4–Al2O3 refractories prepared at high temperatures in nitrogen

The novel Al₄O₄C–(Al₂OC)_1-x(AlN)_x–Zr₂Al₃C₄–Al₂O₃ refractories with ultra-low carbon content have been successfully prepared by constructing the core-shell structure of aluminum at 1300–1700°C in nitrogen. The phase composition, microstructure, and properties of the novel refractories are deeply investigated. The cracking temperature on the core-shell structure of aluminum is further explored and the reaction mechanism of Zr₂Al₃C₄ has also added explanation. The results show that the novel refractories have excellent physical properties and cannot be corroded by molten iron. There exist two different Al₂OC solid solutions in the novel refractories, Al₂OC-rich (Al₂OC)_1-x(AlN)_x and AlN-rich (Al₂OC)_1-x(AlN)_x. The temperatures affect their relative content. When temperatures are less than 1600°C, the relative content of Al₂OC-rich (Al₂OC)_1-x(AlN)_x is more than that of AlN-rich (Al₂OC)_1-x(AlN)_x. When temperatures are above 1700°C, the relative content of AlN-rich (Al₂OC)_1-x(AlN)_x is more than that of Al₂OC-rich (Al₂OC)_1-x(AlN)_x. The core-shell structure of aluminum fully ruptures at about 1200°C. Zr₂Al₃C₄ begins to form at about 1000°C and generates in large at 1200°C.