Unraveling specific role of carbon matrix over Pd/quasi-Ce-MOF facilitating toluene enhanced degradation

Metal organic frameworks (MOFs) derivatives represented by quasi-MOFs have excellent physical and chemical properties and can be applied for the catalytic combustion of volatile organic compounds (VOCs). In this work, Pd/quasi-Ce-BTC synthesized by simple one-step N₂ pyrolysis was applied to the oxidation of toluene, showing excellent toluene catalytic activity (T₉₀ = 175 °C, 30000 mL/(g·h)). Microscopic analyses indicate the formation and interaction of a carbon matrix composite quasi-MOF structure interface. The results show that the amorphous carbon matrix formed during the partial pyrolysis of Ce-BTC significantly improves the adsorption and activation capacity of toluene in the reaction, and constructs a reductive system to maintain high concentrations of Ce³⁺ and Pd⁰, which can facilitate the activation and utilization of oxygen in reaction. Quasi in-situ XPS proves that carbon matrix is indirectly involved in the activation and storage of oxygen, and Pd⁰ is the crucial active site for the activation of oxygen. Stability and water resistance tests display good stability of Pd/quasi-Ce-BTC. This work provides a potential method for designing quasi-MOF catalysts towards VOCs effective abatement.     

Neural Emotion Detection via Personal Attributes

There has been a recent line of work to automatically detect the emotions of posts in social media. In literature, studies treat posts independently and detect their emotions separately. Different from previous studies, we explore the dependence among relevant posts via authors' backgrounds, since the authors with similar backgrounds, e.g., "gender", "location", tend to express similar emotions. However, personal attributes are not easy to obtain in most social media websites. Accordingly, we propose two approaches to determine personal attributes and capture personal attributes between different posts for emotion detection: the Joint Model with Personal Attention Mechanism (JPA) model is used to detect emotion and personal attributes jointly, and capture the attributes-aware words to connect similar people; the Neural Personal Discrimination (NPD) model is employed to determine the personal attributes from posts and connect the relevant posts with similar attributes for emotion detection. Experimental results show the usefulness of personal attributes in emotion detection, and the effectiveness of the proposed JPA and NPD approaches in capturing personal attributes over the state-of-the-art statistic and neural models.     

Formation of single-crystalline BaTiO3 nanorods from glycolate by tuning the supersaturation conditions

We have studied peculiarities in the formation of single-crystalline barium titanate (BaTiO₃) nanorods from a glycolate-mediated complex via a single-step hydrothermal process under different supersaturation (S_R) conditions. X-ray diffraction (XRD) showed the formation of pure BaTiO₃ with an S_R of above 19. The tetragonality for the BaTiO₃ (c/a) reached 1.013 at S_R = 19–29 and dropped to 1.010 for S_R = 39. According to the transmission electron microscopy (TEM) and XRD analyses, the rod-shaped particles exhibited single crystallinity and crystal growth along the [001] plane. With scanning electron microscopy (SEM), the morphological evolution from a plate-shaped intermediate precursor (S_R = 6–9) to a rod-shaped product with an aspect ratio of 6–9 (S_R = 19–29), and to non-polar material with an irregular structure (S_R = 39), was observed. The negative slope, linear dependence of the particles’ width and length on the supersaturation level in the range S_R = 19–39 was established for the first time. The replacement of the prevailing crystallization mechanism from in-situ topotactic transformation into dissolution-precipitation above S_R = 19 was observed. It was shown that with a simple regulation of the S_R, the structural and morphological characteristics of the obtained BaTiO₃ nanoparticle can be effectively tuned.     

谷氨酰胺代谢在原发性肝癌发生发展及治疗中的研究进展

肝癌是我国高发并且危害性极大的恶性肿瘤，其具有高死亡率并起病隐匿等特点。目前，肝癌治疗主要是以靶向药物，手术和放化疗为主，容易出现复发率高、耐药性强等现象。本文以谷氨酰胺代谢为切入点，对目前研究较多的肝癌相关的谷氨酰胺代谢酶及相关基因分别予以综述，以期为肝癌的发病机制及药物治疗提供开放性新思路。     

Hydraulic reactivity and cement formation of baghdadite

In this study, the hydraulic reactivity and cement formation of baghdadite (Ca₃ZrSi₂O₉) was investigated. The material was synthesized by sintering a mixture of CaCO₃, SiO₂, and ZrO₂ and then mechanically activated using a planetary mill. This leads to a decrease in particle and crystallite size and a partial amorphization of baghdadite as shown by X-ray powder diffraction (XRD) and laser diffraction measurements. Baghdadite cements were formed by the addition of water at a powder to liquid ratio of 2.0 g/ml. Maximum compressive strengths were found to be ~2 MPa after 3-day setting for a 24-h ground material. Inductively coupled plasma mass spectrometry (ICP-MS) measurements showed an incongruent dissolution profile of set cements with a preferred dissolution of calcium and only marginal release of zirconium ions. Cement formation occurs under alkaline conditions, whereas the unground raw powder leads to a pH of 11.9 during setting, while prolonged grinding increased pH values to approximately 12.3.     

Enhanced wide-activated residual network for efficient and accurate image deblocking

To save bandwidth and storage space as well as speed up data transmission, people usually perform lossy compression on images. Although the JPEG standard is a simple and effective compression method, it usually introduces various visually unpleasing artifacts, especially the notorious blocking artifacts. In recent years, deep convolutional neural networks (CNNs) have seen remarkable development in compression artifacts reduction. Despite the excellent performance, most deep CNNs suffer from heavy computation due to very deep and wide architectures. In this paper, we propose an enhanced wide-activated residual network (EWARN) for efficient and accurate image deblocking. Specifically, we propose an enhanced wide-activated residual block (EWARB) as basic construction module. Our EWARB gives rise to larger activation width, better use of interdependencies among channels, and more informative and discriminative non-linearity activation features without more parameters than residual block (RB) and wide-activated residual block (WARB). Furthermore, we introduce an overlapping patches extraction and combination (OPEC) strategy into our network in a full convolution way, leading to large receptive field, enforced compatibility among adjacent blocks, and efficient deblocking. Extensive experiments demonstrate that our EWARN outperforms several state-of-the-art methods quantitatively and qualitatively with relatively small model size and less running time, achieving a good trade-off between performance and complexity.     

Effect of crystal structures on nucleation mechanism in hydrothermal synthesis of MZrO3 (M=Ba,Sr, Ca)

Hydrothermal method is widely used in the synthesis of perovskite-type oxides, whereas few studies are reported for the nucleation mechanism, so that the relationship between the crystal structures and reactive activities of reactants and products is still unknown. Herein, the reaction processes are analyzed on the basis of XRD, SEM and Raman characterizations, and the nucleation mechanism is investigated for the hydrothermal synthesis of MZrO₃ (M = Ba, Sr, Ca). We propose that the negative charged cyclic tetramer complexes [Zr₄(OH)₈(OH)₁₆]^8- form in the hydrothermal reaction, which play major roles in the nucleation process. The tetramer complexes continually dehydrate and condensate to form substructural units composed of alkali-earth ions and 6-fold Zr tetramers; substructural units further dehydrate and distort to form perovskite structures. The reactive activation energy increases with the decreasing of M²⁺ (M = Ba, Sr, Ca) ionic radius because the incorporation of smaller A site ions in the perovskite structure is accompanied by greater rotation and distortion of the ZrO₆ octahedra, leading to the decrease of reactive activity accordingly. In a word, the proposed nucleation mechanism in this paper is of great significance for the study of perovskite.     

Role of Polyinosinic:Polycytidylic Acid-Induced Maternal Immune Activation and Subsequent Immune Challenge in the Behaviour and Microglial Cell Trajectory in Adult Offspring: A Study of the Neurodevelopmental Model of Schizophrenia

Multiple lines of evidence support the pathogenic role of maternal immune activation (MIA) in the occurrence of the schizophrenia-like disturbances in offspring. While in the brain the homeostatic role of neuron-microglia protein systems is well documented, the participation of the CX3CL1-CX3CR1 and CD200-CD200R dyads in the adverse impact of MIA often goes under-recognized. Therefore, in the present study, we examined the effect of MIA induced by polyinosinic:polycytidylic acid (Poly I:C) on the CX3CL1-CX3CR1 and CD200-CD200R axes, microglial trajectory (MhcII, Cd40, iNos, Il-1β, Tnf-α, Il-6, Arg1, Igf-1, Tgf-β and Il-4), and schizophrenia-like behaviour in adult male offspring of Sprague-Dawley rats. Additionally, according to the “two-hit” hypothesis of schizophrenia, we evaluated the influence of acute challenge with Poly I:C in adult prenatally MIA-exposed animals on the above parameters. In the present study, MIA evoked by Poly I:C injection in the late period of gestation led to the appearance of schizophrenia-like disturbances in adult offspring. Our results revealed the deficits manifested as a diminished number of aggressive interactions, presence of depressive-like episodes, and increase of exploratory activity, as well as a dichotomy in the sensorimotor gating in the prepulse inhibition (PPI) test expressed as two behavioural phenotypes (MIA_PPI-low and MIA_PPI-high). Furthermore, in the offspring rats subjected to a prenatal challenge (i.e., MIA) we noticed the lack of modulation of behavioural changes after the additional acute immune stimulus (Poly I:C) in adulthood. The important finding reported in this article is that MIA affects the expression and levels of the neuron-microglia proteins in the frontal cortex and hippocampus of adult offspring. We found that the changes in the CX3CL1-CX3CR1 axis could affect microglial trajectory, including decreased hippocampal mRNA level of MhcII and elevated cortical expression of Igf-1 in the MIA_PPI-high animals and/or could cause the up-regulation of an inflammatory response (Il-6, Tnf-α, iNos) after the “second hit” in both examined brain regions and, at least in part, might differentiate behavioural disturbances in adult offspring. Consequently, the future effort to identify the biological background of these interactions in the Poly I:C-induced MIA model in Sprague-Dawley rats is desirable to unequivocally clarify this issue.     

Sequential alignment attention model for scene text recognition

Scene text recognition has been a hot research topic in computer vision due to its various applications. The state-of-the-art solutions usually depend on the attention-based encoder-decoder framework that learns the mapping between input images and output sequences in a purely data-driven way. Unfortunately, there often exists severe misalignment between feature areas and text labels in real-world scenarios. To address this problem, this paper proposes a sequential alignment attention model to enhance the alignment between input images and output character sequences. In this model, an attention gated recurrent unit (AGRU) is first devised to distinguish the text and background regions, and further extract the localized features focusing on sequential text regions. Furthermore, CTC guided decoding strategy is integrated into the popular attention-based decoder, which not only helps to boost the convergence of the training but also enhances the well-aligned sequence recognition. Extensive experiments on various benchmarks, including the IIIT5k, SVT, and ICDAR datasets, show that our method substantially outperforms the state-of-the-art methods.