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Silicon is considered as one of the most promising anodes for Li-ion batteries (LIBs), but it is limited for commercial applications by the critical issue of large volume expansion during the lithiation. In this work, the structure of silicon/carbon (Si/C) particles on graphene sheets (Si/C–G) was obtained to solve the issue by using the void space of Si/C particles and graphene. Si/C–G material was from Si/PDA-GO that silicon particles was coated by polydopamine (PDA) and reacted with oxide graphene (GO). The Si/C–G material have good cycling performance as the stability of the structure during the lithiation/dislithiation. The Si/C–G anode materials exhibited high reversible capacity of 1910.5 mA h g−1 and 1196.1 mA h g−1 after 700 cycles at 357.9 mA g−1, and have good rate property of 507.2 mA h g−1 at high current density, showing significantly improved commercial viability of silicon electrodes in high-energy-density LIBs.

Nanostructured iron sulfides are regarded as a potential anode material for sodium-ion batteries in virtue of the rich natural abundance and remarkable theoretical capacity. However, poor rate performance and inferior cycling stability caused by sluggish kinetics and volume swelling represent two main obstacles at present. The previous research mainly focuses on nanostructure design and/or hybridizing with conductive materials. Further boosting the property by adjusting Fe/S atomic ratio in iron sulfides is rarely reported. In this work, Fe7S8 and FeS2 encapsulated in N-doped hollow carbon fibers (NHCFs/Fe7S8 and NHCFs/FeS2) are constructed by a combined chemical bath deposition and subsequent sulfidation treatment. The well-designed NHCFs/Fe7S8 electrode displays a remarkable capacity of 517 mAh g−1 at 2 A g−1 after 1000 cycles and a superb rate capability with a capability of 444 mAh g−1 even at 20 A g−1 in ether-based electrolyte. Additionally, the rate capability of NHCFs/Fe7S8 is superior to that of the contrast NHCFs/FeS2 electrode and also much better than the values of the most previously reported iron sulfide-based anodes. The in-depth mechanism explanation is explained by further experimental analysis and theoretical calculation, revealing Fe7S8 displays improved intrinsic electronic conductivity and faster Na+ diffusion coefficient as well as higher reaction reversibility.

In the era of big data, tremendous amounts of information and data have drastically changed human civilization. The rapid growth in the number of documents generated everyday means that a large amount of knowledge is proposed, improved, and used. For readers, especially newcomers to a given field, excavating suitable knowledge entities from massive documents is time-consuming and labor-consuming, negatively impacting research efficiency. The broad availability of information provides more opportunities for people, but a new challenge has risen as well; that is, how to extract and use knowledge from numerous information resources, especially how to conduct knowledge extraction and text mining (TM) from massive documents in special domains. A knowledge entity is a relatively independent and integral knowledge module in a special discipline or research domain (Chang & Zheng, 2007). In scientific documents, knowledge entities refer to the knowledge mentioned or cited by authors, such as algorithms, models, theories, datasets, and software (Wang & Zhang, 2018), and reflect various resources used by the authors in problem-solving (Zhang, Mayr, Lu, & Zhang, 2020; Hou, Jochim, Gleize, Bonin, & Ganguly, 2019; Brack, D'Souza, Hoppe, Auer, & Ewerth, 2020). Extracting knowledge entities from numerous information resources is useful for multiple downstream tasks in information extraction, TM, natural language processing (NLP), information retrieval, digital library research, and so on. Particularly, in the field of artificial intelligence (AI), information science, and some other related disciplines, discovering methods from a large scale of academic literature, and evaluating the performance and influence of such methods, have become increasingly necessary and meaningful (Hou et al., 2020). In 2019, the “Heart of Machine” launched the project “SOTA (state of the art) model”1 . Targeting more than 100 tasks in machine learning research, the project obtained models, open datasets, evaluation indicators, and results from academic literature through manual annotation and named entity recognition, and provided open retrieval services for users. Defense Advanced Research Projects Agency (DARPA) has recently launched the Automating Scientific Knowledge Extraction (ASKE) project2 to develop next-generation applications of artificial intelligence. In parallel, deep learning techniques introduce new progresses to NLP and TM. Many kinds of neural network models, e.g., convolutional neural network (CNN), recurrent neural network (RNN), graph neural networks (GNN), and attention mechanism, have been widely involved in these tasks (Qiu et. al, 2020), particularly, text classification (Zhang, Zhao, & LeCun, 2015; Lai, Xu, Liu, & Zhao, 2015; Yao, Mao, & Luo, 2019; Liu & Guo, 2019) and clustering (Xu et al., 2015; Xu et al., 2017). There are some conferences and workshops in line with this topic, such as the Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL) (Cabanac et al., 2016), the Workshop on Mining Scientific Publications (WOSP), the Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE) (Zhang et al., 2020), the Workshop on AI + Informetrics (AII) (Zhang, Zhang, Mayr, & Suominen, 2021), and the Workshop on Scholarly Document Processing (SDP) (Chandrasekaran et al., 2020). We are very grateful that three contributions were invited to the special issue of Data and Information Management (DIM). These three submissions were accepted after several rounds of peer-reviewing and revisions. The paper “Discovering Booming Bio-entities and Their Relationship with Funds” (Tan, Zhang, Yang, Wu, & Xu, 2021) tracked the overall trends and changes in biomedical topics from 1988 to 2017. It collected funding information in the PubMed database and the website of the United States National Institutes of Health (USNIH), and extracted funding-related entities and research hotspots in the corresponding fields. This study provides new insights for research funding allocation, and may support the science policy and strategic management of stakeholders. The paper “A Pattern and POS Auto-Learning Method for Terminology Extraction from Scientific Text” (Shao, Hua, & Song, 2021) proposed an unsupervised method based on sentence patterns and part of speech (POS) sequences extracted from scientific texts. The proposed method only requires a few initial learnable patterns to obtain initial terminological tokens and their POS sequences. Experiments on abstracts of articles in the Web of Science (WoS) database demonstrate its recognized performance. The paper “Automatic Subject Classification of Public Messages in E-government Affairs” (Pan & Chen, 2021) touched upon the task of automatic classification using bi-directional long short-term memory (Bi-LSTM) network model based on attention mechanism. This paper used the Bi-LSTM algorithm to strengthen the relevance of messages before and after the training process, and introduced semantic attention to highlight the weight of important text features.

Molybdenum disulfides (MoS2) are presently attracting immense research interest as high gravimetric capacity anode materials in next-generation electrochemical batteries. However, achieving outstanding rate capability with high volumetric capacity in a single electrode remains highly challenging. Here, MoS2-based heterostructure materials including a conductive Fe9S10 core and carbon coating (Fe9S10@MoS2@C) are developed with a dense spatial geometry architecture and demonstrated as an advanced anode for simultaneously achieving high volumetric capacity and enhanced the reaction kinetics in both sodium-ion batteries (SIBs) and potassium-ion batteries (PIBs). The introduced Fe9S10 core plays crucial roles in significantly improving the electronic conductivity, facilitating the densifying of MoS2 particles, and constructing abundant heterogeneous interfaces with a strong electric field. Experimental studies and density functional theory calculation reveal that the formed heterointerfaces help to improve fast charging capability and cycle stability by decreasing the ion diffusion energy barrier and reinforcing geometry architecture. As a result, the Fe9S10@MoS2@C anode delivers a high volumetric capacity of 662 mAh cm−3, stable cycling performance (a capacity retention of 93.4% for 1000 cycles) and outstanding rate capability (high gravimetric capacities of 197 and 132 mA h g−1 at a large current densities of 30 and 50 A g−1, respectively) for SIBs, meanwhile, a high volumetric capacity of 408 mAh cm−3 with 95.4% capacity retention is achieved after 50 cycles for PIBs. The present work could guide the future designing protocol of heterostructure architectures by integrating suitable components for potential applications as high-performance alkali ion batteries electrode.

Excessive fluoride exposure can induce neuron apoptosis that is associated with neurodegenerative changes, but the mechanisms remain elusive. It has been suggested that chronic fluoride-induced microglia activation contributes to neuronal damage by producing pro-inflammatory cytokines. IL-1β, a pro-inflammatory cytokine released by activated microglia, is capable of inducing JNK phosphorylation and is associated with neurodegenerative diseases. In the current study, in vivo results demonstrate that excessive NaF impaired spatial learning and memory ability, microglia activation, and up-regulation of IL-1β in rats. Moreover, NaF exposure induced JNK pathway activation and associated apoptosis. These results were validated in vitro: NaF could induce BV-2 microglia cell activation and increase the concentration of IL-1β in the culture medium. When PC-12 cells were cultured with BV-2 CM or IL-1β for 24 h, the viability of PC-12 cells decreased, with enhanced apoptosis. In addition, IL-1 receptor antagonist (IL-1Ra) or SP600125 (JNK pathway inhibitor) diminished the IL-1β-induced activation of JNK pathway-mediated neuron apoptosis. Therefore, our study demonstrates that the IL-1β/JNK signaling pathway is involved in NaF-induced apoptosis of hippocampal neurons and cognitive dysfunction.

Hydrodeoxygenation (HDO) of lignin-derived bio-oil offers a promising route for the production of advanced biofuels. However, the conventional HDO of lignin-derived bio-oil faces serious problems, such as low hydrocarbon yield and easy deactivation of catalysts. Herein, a novel reaction system consisting of a highly stable bifunctional catalyst (i.e., Ni−WOx/NiAl2O4) and a dodecane solvent was developed for the HDO of lignin-derived phenolics. The Ni0 species, derived from NiWO4 precursors on the NiAl2O4, were of small crystallite size and high dispersion, together with the strong oxophilicity of W, thereby exhibiting high activity. The use of a highly stable NiAl2O4 spinel support and the replacement of common solid acid with more stable WOx for the cleavage of C O bond accounted for excellent stability. The optimized 10Ni−15WOx/NiAl2O4 exhibited a high guaiacol conversion of 97.8% with a high cycloalkane yield of 83.8% under the optimum conditions (250 °C, 5 MPa H2, and 4 h). Cycloalkanes with a high yield over 90% were also obtained by the HDO of other complex lignin-derived compounds. More importantly, the catalyst always retained its initial activity for the HDO of guaiacol in five runs, with negligible coke formation. Subsequently, the HDO behavior of the bio-oil obtained from walnut shell pyrolysis was also studied. The relative content of cycloalkanes in the products reached 44.3% after the reaction. This study highlights the prospect of a highly stable catalyst consisting of hydrogenation metal and oxophilic promoter, and dodecane solvent to enable efficient production of cycloalkanes from the HDO of lignin-derived phenolics.

Tin disulfide (SnS2), one transition metal dichalcogenide (TMD) is a cost-effective and promising electrocatalyst for hydrogen evolution reactions (HER) in the alkaline electrolytes. Its electrocatalytic HER performance is unfortunately limited, originating from its un-conspicuous inherent catalytic activities and non-favorable adsorption sites for hydrogen. Herein, a tin disulfide/stannic oxide (SnS2/SnO2) heterostructure is designed and grown on the nickel foam (denoted as SnS2/SnO2-NF). The SnS2/SnO2 heterostructure introduces more active (100) facets or a high density of active sites, accelerates the diffusion kinetic of electrons and ions, lowers the water dissociation energies, and optimizes adsorption energies of hydrogen atoms. On this catalyst, superior HER performance is realized in an alkaline medium. An overpotential of 108 mV at a current density of −10 mA cm–2 with a Tafel slope of 50.1 mV dec–1 and long-term durability are achieved for HER in 1 M KOH. This work paves a new way to design high-performance HER electrocatalyst through facet engineering of the designed heterostructures.

A type of sandwich-type and mesoporous CoS-based coaxial nanocables with conductive CNT backbone core, well-confined CoS nanoparticle interlayer and conformal carbon coating shell (denoted as CNT@CoS@C) are developed through a bottom-up method and investigated as potential anode materials for sodium/lithium ion storage. The rationally constructed architecture successively achieves the integration of one-dimensional conducting networks, ultrafine active nanoparticles, well-developed mesoporosity and sophisticated surface modification via a layer-by-layer assembly strategy, thus upholding good structural/interfacial robustness and enhanced charge-transfer reaction kinetics. As a result, the CNT@CoS@C coaxial nanocables exhibit a high reversible capacity of 494 mAh g −1 , stable cycling with more than 318 mAh g −1 at 500 mA g −1 over 500 cycles (corresponding to 74% capacity retention with 0.05% decay rate per cycle) and impressive rate capability (278 mAh g −1 at 5000 mA g −1 ) for sodium ion batteries (SIBs) and excellent electrochemical performance for lithium ion batteries (LIBs) (1010 mAh g −1 during 200 cycles with no capacity loss and 467 mAh g −1 at 5000 mA g −1 ). In addition, the electrochemical experimental results and simulated calculations suggest that the CoS-based active species possesses better electrochemical properties in term of reaction reversibility and structural stability than its Co 3 O 4 -based counterpart with similar morphological features.

Multidisciplinary cooperation is now common in research since social issues inevitably involve multiple disciplines. In research articles, reference information, especially citation content, is an important representation of communication among different disciplines. Analyzing the distribution characteristics of references from different disciplines in research articles is basic to detecting the sources of referred information and identifying contributions of different disciplines. This work takes articles in PLoS as the data and characterizes the references from different disciplines based on Citation Content Analysis (CCA). First, we download 210,334 full-text articles from PLoS and collect the information of the in-text citations. Then, we identify the discipline of each reference in these academic articles. To characterize the distribution of these references, we analyze three characteristics, namely, the number of citations, the average cited intensity and the average citation length. Finally, we conclude that the distributions of references from different disciplines are significantly different. Although most references come from Natural Science, Humanities and Social Sciences play important roles in the Introduction and Background sections of the articles. Basic disciplines, such as Mathematics, mainly provide research methods in the articles in PLoS. Citations mentioned in the Results and Discussion sections of articles are mainly in-discipline citations, such as citations from Nursing and Medicine in PLoS.

Alkali metal anodes are promising anodes for constructing novel battery systems with high energy density. Nevertheless, limited nucleation sites and nonuniform local electric field caused dendrites growth and unlimited volume expansion hindered their practical implementation during electrochemical plating/stripping. Herein, a 3D N-doped carbon nanofiber skeleton wrapped with Ni nanoparticles encapsulated carbon nanotubes (CNTs-Ni@NCFs) is prepared by hydrothermal process and followed catalytic reaction under ethanol atmosphere to construct a superior Li/Na-philic host with stable chemical properties. The 3D NCF networks serve as a primary framework, providing sufficient voids for alkali metal deposition and rapid electron and ion transport. The Li/Na-philic Ni nanoparticles and catalyzed CNTs on CFs provide evenly distributed nucleation sites and uniform local electric field, leading to dendrite-free Li deposition, which is confirmed by theoretical calculations. Because of the guided deposition behavior and bare volume change, the CNTs-Ni@NCFs anode delivers an extremely low nucleation overpotential in the initial deposition and a superior plating/stripping voltage hysteresis under a high current density of 30 mA cm−2 for 300 cycles. The CNTs-Ni@NCFs-Li full cell with LiFePO4 cathodes demonstrates 94.2% capacity retention after 200 cycles under 2 C. When coupled with Na3V2(PO4)3 cathode, the CNTs-Ni@NCFs-Na cell shows a good suitability in full cell. This work shed new light on fabricating novel stable alkali metal anodes, which may also pave the way toward to other practical applications with high energy densities, such as in Li-air and Li-S batteries, etc.

Fluoride has been considered as a risk factor of cardiovascular disease due to its endothelial toxicology. However, the mechanism underlying the endothelial toxicity of fluoride has not been clearly illustrated. MiR-200c-3p was strongly linked with endothelial function and its level is increased in serum of fluorosis patients, but it is unclear the role of miR-200c-3p in the fluoride induced endothelial dysfunction. In this study, we confirmed that fluoride exposure induced the apoptosis of endothelial cells both in established rats model and cultured human umbilical vein endothelial cells (HUVECs). And miR-200c-3p was found to be upregulated in NaF treated HUVECs. Fluoride stimulation increased caspase-dependent apoptosis through miR-200c-3p upregulation, with repressing expression of its target gene Fas-associated phosphatase 1 (Fap-1), which functioned as Fas inhibitor. This resulted in activation of Fas-associated extrinsic apoptosis via interaction with increased Fas, Fadd, Cleaved Caspase-8 and Cleaved Caspase-3. The activation of Fas-associated extrinsic apoptosis was abrogated by miR-200c-3p inhibitor. Furthermore, the antiapoptotic effect of downregulated miR-200c-3p was restored by Fap-1 siRNA. These results suggested a determinant role of the miR-200c-3p/Fap-1 axis in fluoride induced endothelial apoptosis.

Compared with journal articles, books can provide broader, deeper and more comprehensive information, and often have higher expertise and academic depth. However, most researches on book assessment focus on measuring academic value of books (e.g. citations analysis) or identifying attitudes of readers (e.g. book review mining), depth and breadth reflected by book contents is neglected. Therefore, in this paper, we measure books’ depth and breadth by mining books’ tables of contents, so as to enrich resources and methods for book assessment research, help users understand book contents quickly and improve efficiency of book selection. Specifically, we measured books’ depth and breadth based on books’ tables of contents via two levels: topic level and feature level. Firstly, we obtained topic-level metrics by identifying topics expressed in tables of contents and calculating topic distributions. Then, we got feature-level results via feature extraction and feature distribution calculation. Finally, we compared depth and breadth metrics and other book assessment metrics. Experimental results reveal that, books’ depth and breadth at two levels are different, and substantial differences between disciplines and book types are obvious. In addition, books’ depth and breadth can provide alternative and supplementary information for assessing multi-dimensional values of books.

Lightweight, self-supporting, and flexible carbon nanofiber membranes are desirable electrode candidates for flexible supercapacitors. At present, inadequate electrical contact between adjacent nanofibers, poor wettability with electrolyte, and limited specific surface area are still challenges for further improving the capacitive property. In this work, a novel porous N-doped carbon nanofiber network membrane in which continuous ZIF-8-derived carbon layers “welding” adjacent carbon nanofibers is synthesized through bifunctional ZnO nanoparticles contained in the nanofibers. Here, ZnO nanoparticles not only serve as the pore-forming agent to create multiscale pores, but also provide zinc sources for in-situ growth of ZIF-8 nanoparticle layer. Because of highly interconnected networks, special spider-web-like surface nanostructure, and hierarchical pores, the as-prepared carbon membrane reveals superior electrical conductivity, high specific surface area and excellent wettability. An excellent rate performance with 75.5% capacitance retention even with 70-times current density increase and extraordinary cycling stability (98.8% capacitance retention after 100,000 cycles at 10 A g−1) could be found, when the optimized hierarchically porous N-doped welded carbon network membrane is used as the electrode. The quantitatively electrochemical kinetic analysis of the electrode indicates that fast double layer capacitive behavior is dominant at high current densities. Meanwhile, the flexible quasi-solid-state devices display excellent electrochemical stability in severely bending states.

A series of oxazole-substituted indanylacetic acids were prepared which show a spectrum of activity as ligands for PPAR nuclear receptor subtypes.

In this paper, the microaggregate effect of fly ash is studied systematically by micromechanics, the hypothesis of center particle and pore size distribution. It is pointed out that the microaggregate effect is an important effect of fly ash. It is strengthened with the increase of content of fly ash, but weakened with age. At early age, fly ash cannot fine the pore structure. At late age, fly ash may fine the pore structure. However, in general, the fining role is only a relative fining role.

The morphological effect is an important part of fly ash effects. The paper analyzes emphatically this effect and points out that it is composed of the filling role, surface role and lubricating role. For different fly ash, these roles are different. They must be considered synthetically when the morphological effect is analyzed. Analyzing result shows that the filling role is relative to the particle size, the surface role is relative to the specific surface area and the water affinity and the lubricating role is relative to the shape of particle. The morphological effect of fly ash is the synthetical embodiment of these roles.

In the paper, the influence of the particle size distribution in binary system on the packing density and the rate of hydration is analysed. On the basis of the analysis, the relationship between the porosity and the particle size distribution is calculated and discussed. The result indicates that: (1) The influence of the particle size distribution on the porosity is dependent on both the packing density and the rate of hydration. When the depth of hydration is less, the packing density is the main factor, thus the wide distribution can obtain the low porosity; when the depth of hydration is greater, the influence of both must be considered comprehensively. There is the best distribution, and the best value of d 1 d 2 is about 0.3 for binary system. (2) The relative ratio between two components depends mainly on the packing density. The mixture ratio when the porosity is the lowest equals to one when the packing density is the highest.

Lewis acids or ultrasound catalyze the condensation of imines with Wang resin bound H-phosphonates to give high yields of the corresponding α-amino phosphonates or phosphonic acids.

The filling role of pozzolanic material was analyzed in the paper. The influence of pozzolanic material on fluidity and strength of cement was also investigated. The fine pozzolanic material can increase the packing density and the amount of the water in surface layer and decrease the amount of filling water. Superplasticizer can reduce the amount of the water in surface layer. The compound fine pozzolanic material and superplasticizer can reduce water demand and increase strength.

The first example of a four component condensation of arylglyoxals, 1° amines, carboxylic acids and isocyanides on Wang resin is described. These products can be cyclized in the presence of NH4OAcAcOH to yield tetrasubstituted imidazoles.

The question whether a four or a five atom non phosphorus based internucleoside link leads to stronger binding of the resulting chimeric oligonucleotides to complementary sequences has been examined by comparing melting temperatures of relevant duplexes.

Solution-phase combinatorial chemistry was applied to the optimization and development of clinical candidate OC144-093 (22), a novel and nontoxic modulator of P-glycoprotein mediated multidrug resistance.

The stereochemical and regiochemical outcome of reactions of PhMe2SiLi/CuCN mixtures with vinyl epoxides depends on the PhMe2SiLi/CuCn ratio.