Carbonation Curing on Magnetically Separated Steel Slag for the Preparation of Artificial Reefs

Magnetic separation is an effective method to recover iron from steel slag. However, the ultra-fine tailings generated from steel slag become a new issue for utilization. The dry separation processes generates steel slag powder, which has hydration activity and can be used as cement filler. However, wet separation processes produce steel slag mud, which has lost its hydration activity and is no longer suitable to be used as a cement filler. This study investigates the potential of magnetically separated steel slag for carbonation curing and the potential use of the carbonated products as an artificial reef. Steel slag powder and steel slag mud were moulded, carbonation-cured and seawater-cured. Various testing methods were used to characterize the macro and micro properties of the materials. The results obtained show that carbonation and hydration collaborated during the carbonation curing process of steel slag powder, while only carbonation happened during the carbonation curing process of steel slag mud. The seawater-curing process of carbonated steel slag powder compact had three stages: C-S-H gel formation, C-S-H gel decomposition and equilibrium, which were in correspondence to the compressive strength of compact increasing, decreasing and unchanged. However, the seawater-curing process of carbonated steel slag mud compact suffered three stages: C-S-H gel decomposition, calcite transfer to vaterite and equilibrium, which made the compressive strength of compact decreased, increased and unchanged. Carbonated steel slags tailings after magnetic separation underwent their lowest compressive strength when seawater-cured for 7 days. The amount of CaO in the carbonation active minerals in the steel slag determined the carbonation consolidation ability of steel slag and durability of the carbonated steel slag compacts. This paper provides a reference for preparation of artificial reefs and marine coagulation materials by the carbonation curing of steel slag

Climate change increases carbon allocation to leaves in early leaf green-up

Global greening, characterized by an increase in leaf area index (LAI), implies an increase in foliar carbon (C). Whether this increase in foliar C under climate change is due to higher photosynthesis or to higher allocation of C to leaves remains unknown. Here, we explored the trends in foliar C accumulation and allocation during leaf green-up from 2000 to 2017 using satellite-derived LAI and solar-induced chlorophyll fluorescence (SIF) across the Northern Hemisphere. The accumulation of foliar C accelerated in the early green-up period due to both increased photosynthesis and higher foliar C allocation driven by climate change. In the late stage of green-up, however, we detected decreasing trends in foliar C accumulation and foliar C allocation. Such stage-dependent trends in the accumulation and allocation of foliar C are not represented in current terrestrial biosphere models. Our results highlight that a better representation of C allocation should be incorporated into models

The Multimodal Information based Speech Processing (MISP) 2022 Challenge: Audio-Visual Diarization and Recognition

The Multi-modal Information based Speech Processing (MISP) challenge aims to extend the application of signal processing technology in specific scenarios by promoting the research into wake-up words, speaker diarization, speech recognition, and other technologies. The MISP2022 challenge has two tracks: 1) audio-visual speaker diarization (AVSD), aiming to solve ``who spoken when'' using both audio and visual data; 2) a novel audio-visual diarization and recognition (AVDR) task that focuses on addressing ``who spoken what when'' with audio-visual speaker diarization results. Both tracks focus on the Chinese language, and use far-field audio and video in real home-tv scenarios: 2-6 people communicating each other with TV noise in the background. This paper introduces the dataset, track settings, and baselines of the MISP2022 challenge. Our analyses of experiments and examples indicate the good performance of AVDR baseline system, and the potential difficulties in this challenge due to, e.g., the far-field video quality, the presence of TV noise in the background, and the indistinguishable speakers.Comment: 5 pages, 4 figures, to be published in ICASSP202

The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region

Data and code availability The authors declare that the majority of the data supporting the findings of this study are available through the links given in the paper. The unpublished data are available from the corresponding author upon request. The new estimate of Tibetan soil carbon stock and R code are available in a persistent repository (https://figshare.com/s/4374f28d880f366eff6d). Acknowledgements This study was supported by the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA20050101), the National Natural Science Foundation of China (41871104), Key Research and Development Programs for Global Change and Adaptation (2017YFA0603604), International Partnership Program of the Chinese Academy of Sciences (131C11KYSB20160061) and the Thousand Youth Talents Plan project in China. Jinzhi Ding acknowledges the General (2017M620922) and the Special Grade (2018T110144) of the Financial Grant from the China Postdoctoral Science Foundation.Peer reviewedPublisher PD

Crystal structure of the ethyl 2,4-dihydroxy-6-methylbenzoate from Illicium difengpi K.I.B et K.I.M.

The title compound, C10H12O4, was isolated from Illicium difengpi K.I.B et K.I.M. An intramolecular O—H...O hydrogen bond stabilizes the molecular conformation. In the crystal, the compound forms offset slanted stacks of alternating inversion-related molecules along the a axis direction. Intermolecular O—H...O hydrogen bonds link the molecules into double strands parallel to the [101] direction

How Teacher Social-Emotional Competence Affects Job Burnout: The Chain Mediation Role of Teacher-Student Relationship and Well-Being

Teacher social-emotional competence plays a crucial role in teacher professional development as it is associated with effective stress alleviation at work. However, how and under what conditions teacher social-emotional competence contributes to job burnout is a black box. This study aimed to explored the impact of teacher social-emotional competence on job burnout, focusing on the chain mediation effects of teacher-student relationships and teacher well-being. For this undertaking, stratified random sampling was used and the questionnaire was filled out by 990 teachers in 14 primary schools in Beijing. We analyzed these data using structural equation modeling (SEM). The findings suggested that the teacher social-emotional competence and job burnout were negatively correlated, verifying that teacher social-emotional competence can influence job burnout through the separate and chain mediation effects of teacher-student relationship and teacher well-being. In addition, the separate mediation role of the teacher-student relationship had the most significant effect of all mediation paths. To alleviate teacher job burnout and promote the sustainability of teachers’ professional development, we suggested that emphasizing the development of teacher social-emotional competence and the sustained enhancement of teacher well-being, as well as focusing on improving teacher-student relationship

How Teacher Social-Emotional Competence Affects Job Burnout: The Chain Mediation Role of Teacher-Student Relationship and Well-Being

Teacher social-emotional competence plays a crucial role in teacher professional development as it is associated with effective stress alleviation at work. However, how and under what conditions teacher social-emotional competence contributes to job burnout is a black box. This study aimed to explored the impact of teacher social-emotional competence on job burnout, focusing on the chain mediation effects of teacher-student relationships and teacher well-being. For this undertaking, stratified random sampling was used and the questionnaire was filled out by 990 teachers in 14 primary schools in Beijing. We analyzed these data using structural equation modeling (SEM). The findings suggested that the teacher social-emotional competence and job burnout were negatively correlated, verifying that teacher social-emotional competence can influence job burnout through the separate and chain mediation effects of teacher-student relationship and teacher well-being. In addition, the separate mediation role of the teacher-student relationship had the most significant effect of all mediation paths. To alleviate teacher job burnout and promote the sustainability of teachers’ professional development, we suggested that emphasizing the development of teacher social-emotional competence and the sustained enhancement of teacher well-being, as well as focusing on improving teacher-student relationship

Hydrodynamics of gas phase under typical industrial gassing rates in a gas-liquid stirred tank using intrusive image-based method

The intrusive image-based method is used to probe local gas hydrodynamics, bubble size (BSD) and holdup distributions (BHD) in a gas-liquid stirred tank reactor (STR). A distinctive scheme combining automatic and manual processes is implemented to identify the object bubbles in the images. This method shows more accurate for judging the flow regime in gas-liquid STRs. Because of high intensity turbulence therein, the instantaneous local gas-liquid flow may present several very different patterns though the time-averaged bulk flow is homogeneous. More small bubbles are detected because of high resolution of the instrument, and consequently d(32) obtained is smaller than those by other methods. The BSD and BHD at moderate gassing rates are reported and found closer to the physical reality. The measurements are of significance to understanding the fluid mechanics and provide benchmark data for the validation of the mathematical models in the gas-liquid STRs operating at industrial conditions. (C) 2020 Elsevier Ltd. All rights reserved

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

Detecting the moisture content of grain accurately and rapidly has important significance for harvesting, transport, storage, processing, and precision agriculture. There are some problems with the slow detection speeds, unstable detection, and low detection accuracy of moisture contents in corn harvesters. In that case, an online moisture detection device was designed, which is based on double capacitors. A new method of capacitance complementation and integration was proposed to eliminate the limitation of single data. The device is composed of a sampling mechanism and a double-capacitor sensor consisting of a flatbed capacitor and a cylindrical capacitor. The optimum structure size of the capacitor plates was determined by simulation optimization. In addition to this, the detection system with software and hardware was developed to estimate the moisture content. Indoor dynamic measurement tests were carried out to analyze the influence of temperature and porosity. Based on the influencing factors and capacitance, a model was established to estimate the moisture content. Finally, the support vector machine (SVM) regressions between the capacitance and moisture content were built up so that the R2 values were more than 0.91. In the stability test, the standard deviation of the stability test was 1.09%, and the maximum relative error of the measurement accuracy test was 1.22%. In the dynamic verification test, the maximum error of the measurement was 4.62%, less than 5%. It provides a measurement method for the accurate, rapid, and stable detection of the moisture content of corn and other grains