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This study examines interaction patterns in a series of game activities for learning social skills by autistic youth in a 3D game‐based collaborative virtual learning environment (CVLE). Researchers studying collaborative learning have indicated the importance of social interactions and social presence. However, few studies have examined the relationship of avatar social interactions with embodied social presence in a 3D game‐based CVLE. Specifically, we examined avatar‐mediated verbal and nonverbal interactions by autistic youth in iSocial, a game‐based 3D CVLE for developing social competencies. How are avatar‐mediated verbal and nonverbal social interactions related to the extent of embodied social presence? Building on prior studies on embodied social presence (ESP) theory and the verbal and nonverbal social interaction framework, this paper aims to explore the link between the combination of verbal (appropriate and inappropriate) and nonverbal (avatar proximity, orientation, joint attention and gesture) interaction patterns and experienced ESP level. We report on the results of 3 cohorts of a total of 11 youth aged from 11 to 14 who were diagnosed with Autism Spectrum Disorder learning in 13 game activities in iSocial. The video data of the participants’ screen recordings were analyzed and coded based on the ESP theory and verbal and nonverbal social interaction framework. Through cluster analysis, the results identify distinct patterns of verbal and nonverbal interaction that are associated with different levels of embodied social presence. The findings of this study (1) shed light on the link between social interactions and embodied social presence and (2) provide a deeper understanding of how the unique spatial and visual characteristics of 3D CVLE and the design of game activities in 3D CVLE may transform collaborative learning, especially for autistic youth. [ABSTRACT FROM AUTHOR]

This study extended previous work investigating two-step liquefaction by supercritical ethanol of rice straw under CO2 atmosphere at temperatures of 270–345 °C. Subcritical CO2–subcritical ethanol (SubCO2–SubEtOH) pretreatment decreased the content of lignin in the rice stalk from 22.94 to 21.43 wt%. The results showed that although oxygen-transfer reaction, transesterification, carbonylation, and other reactions may occur with the supercritical CO2–supercritical ethanol (ScCO2–ScEtOH) liquefaction reactions, transesterification was the main reaction. The “de-oxygen-transfer” reaction mainly comprised de-oxygenation and decarboxylation. For temperatures exceeding 320 °C, the bio-oil yield decreased because the effects of esters decreased. The residence time affected the H/C and O/C ratios to a minor extent. It was shown that the nucleophilic and hydrolytic functions of ethanol might be strengthened, generating higher amounts of ester, phenolic, acidic, and hydrocarbon derivatives in the bio-oil fraction.

Discussion forums are increasingly central to massive open online courses (MOOCs), and it is vital for learners to participate in associated forum activities. Active forum participation positively ...

The purpose of this study is to design a structural model explaining how elementary students use digital textbooks on mobile devices. This study extends the technology acceptance model framework, with self-efficacy, learning motivation, learning strategies, and parent education level as external variables. Results show that perceived usefulness was a significant mediating factor for students’ actual usage of digital textbook on mobile devices. Self-efficacy and learning strategies influence self-reported actual usage through perceived usefulness and perceived ease of use. In addition, parent education level has a significant influence on students’ self-efficacy and especially learning motivation. These findings have broadened research on technology acceptance with emphasis on a more learning-centered framework that focuses on the learners’ characteristics and their unique contexts when using digital textbooks via mobile devices.

Massive open online courses (MOOCs) show great potential to transform traditional education through the Internet. However, the high attrition rates in MOOCs have often been cited as a scale-efficacy tradeoff. Traditional educational approaches are usually unable to identify such large-scale number of at-risk students in danger of dropping out in time to support effective intervention design. While building dropout prediction models using learning analytics are promising in informing intervention design for these at-risk students, results of the current prediction model construction methods do not enable personalized intervention for these students. In this study, we take an initial step to optimize the dropout prediction model performance toward intervention personalization for at-risk students in MOOCs. Specifically, based on a temporal prediction mechanism, this study proposes to use the deep learning algorithm to construct the dropout prediction model and further produce the predicted individual student dropout probability. By taking advantage of the power of deep learning, this approach not only constructs more accurate dropout prediction models compared with baseline algorithms but also comes up with an approach to personalize and prioritize intervention for at-risk students in MOOCs through using individual drop out probabilities. The findings from this study and implications are then discussed.

The growing global trade disputes have raised concerns about the supply security of key minerals needed for strategic emerging industries. As one of the key minerals for many economically powerful countries, the international trade of graphite is exposed to high supply risks. Each country should not only pay attention to the paths through which trade risks propagate but also increasingly focus on how resource redistribution between countries can reduce the losses due to supply risks. Therefore, based on the construction of global graphite trade network and the principle of maximum entropy, this paper constructs a graphite trade redistribution model. Taking the trade relationship with larger export share and typical trading countries (China, the largest exporter, and Germany, a major intermediary country) as examples and from the global perspective, the resource redistribution among graphite-trading countries under different supply risk scenarios is simulated to analyze the changes in trade relations among countries. The results provide an important reference for national resource recovery after a graphite supply risk and a new way of thinking for those who study international trade.

In this study, a three-year sampling campaign was conducted at a roadside air pollution monitoring station in Kanazawa, Japan. A total of 7 water-soluble inorganic ions (WSIIs) in ambient particulate matter (PM2.5) was determined via ion chromatography. After the implementation of a new vehicle emission regulation enacted in 2016 in Japan, the annual average concentration of the total WSIIs decreased, from 5.32 ± 3.27 μg/m3 in 2017 to 3.70 ± 2.43 μg/m3 in 2018. This decrease is mainly attributed to the reduction in the three major species of sulfate (SO42−), ammonium (NH4+), and nitrate (NO3−). The reduction in NO3− with decreasing nitrogen oxide (NOx) emphasizes the role of the new regulation. The reduction in NOx might also indirectly lead to a decrease in SO42− or directly lead to a decrease in NH4+. Through a comparison to other WSIIs emission sources, a similar composition was found to that of other traffic-related WSIIs, but the considered WSIIs are clearly different from those emitted by coal and biomass combustion sources. Via further comparison of the distribution of the [NO3−]/[SO42−] ratio values from different sources, we observed that the ratio values are close to those of WSIIs emitted by coal combustion sources, which indicates that this ratio might not be a suitable indicator for the identification of the contribution of mobile and stationary sources in Japanese cities. Overall, this study affirms the effectiveness of the new regulation in terms of WSIIs emission reduction and provides basic WSIIs data pertaining to the roadside environment in Kanazawa for the first time.

This study investigates the mechanical properties of single-span steel-concrete double-sided composite beam, and describes the first practical application of this beam type in building structure. Four steel-concrete composite beams were tested with different parameters that govern the thickness and material strength of the bottom concrete slab . As a control, one ordinary composite beam without a bottom concrete slab was also tested for comparison. The failure mode, load carrying capacity, stiffness, interfacial slippage, internal force of the bottom concrete slab and cross sectional strain distribution are analyzed for all specimens. The results show that most of the damage occurred in the front section of the bottom concrete slab. The bearing capacity and stiffness of the double-sided composite beam are greatly improved compared to the ordinary composite beam. The stability of the lower steel beam flange in the negative moment region is also higher in the composite beams. Theoretical models of the bearing capacity for the various loading stages agree well with test results. The tests also show that interfacial slippage can be effectively mitigated through a full shear connection design. Additionally, to better improve the mechanical performance of the composite beams, the bottom concrete slab should be made with high strength materials or possess a large thickness. Finally, the first-ever practical application of the double-sided composite beam in a building structure is described in this paper.

It is difficult for China to use its domestic uranium resources to meet its demand, so its external dependency will remain at a high level, which is not conducive to the sustainable development of the nuclear power industry in China. This paper analyzes the supply and demand pattern of uranium resources in the world, and forecasts the demand for uranium resources in China to 2030. According to our empirical model, together with China’s nuclear power development plan, demand will reach 20113 tU by 2030 (in the medium scenario). In addition, we discuss four problems associated with China’s uranium resources: (1) domestic uranium production is increasing slowly, so the country’s external dependency is rising; (2) there are potential supply risks because the source of imports is concentrated; (3) global uranium resources tend to be controlled by a monopoly, so there is the possibility of manipulating the market; and (4) with the development of a nuclear power industry in developing countries, uranium prices will rise significantly. Finally, we offer relevant countermeasures and suggestions.

To definitively diagnose active pulmonary Tuberculosis (TB), Mycobacterium tuberculosis complex (MTBC) bacilli must be identified within clinical specimens from patients. In this study, we introduced a rapid and visual detection method of MTBC using recombinase polymerase amplification (RPA) combined with lateral flow (LF) strips. The LF-RPA assay, read results with naked eyes, could detect as few as 5 genome copies of M. tuberculosis H37Rv (ATCC 27294) per reaction and had no cross-reactions with other control bacteria even using excessive amount of template DNA. The system could work well at a broad range of temperature 25–45 °C and reach detectable level even within 5 min. When testing a total of 137 clinical specimens, the sensitivity and specificity of the LF-RPA assay were 100% (95% CI: 95.94%–100%) and 97.92% (95% CI: 88.93%–99.95%), respectively, compared to culture identification method. Therefore, the LF-RPA system we have demonstrated is a rapid, simple, robust method for MTBC detection which, subject to the availability of a suitable sample extraction method, has the potentiality to diagnose TB at the point-of-care testing.

MicroRNAs (miRNAs) are endogenous molecules with regulatory functions. The purification and enrichment of miRNA are essential for its precise and sensitive detection. miRNA isolated using commercial kits contains abundant interfering RNAs, and the concentration of miRNA may not be adequate for detection. Herein, we prepared a reduced graphene oxide (rGO)-based magnetic solid-phase extraction material for the enrichment and ultrasensitive detection of miRNA from intricate nucleic acid solutions. In situ reverse transcription (RT) was developed as the most efficient approach to desorb miRNA from rGO among the methods that are compatible for the subsequent amplification reported thus far. Additionally, rolling circle amplification and qPCR were used to detect let-7a with a decrease of the limit of detection by 24.7- and 31.3-fold, respectively. This material was also successfully used to extract and detect miRNA from total RNA isolated from human plasma. Our results show that the material prepared in this study has the potential for cancer biopsy in clinics and the discovery of new miRNAs in scientific research.

The adsorption/desorption of CH4/CO2/N2 mixture was investigated at 294 K, 311 K, 333 K, and 353 K with a wide pressure range (0∼70 Bar) on anthracite from China using a High Pressure Volumetric Analyzer (HPVAII-200). When the temperature is relatively low (293 K and 311 K), as the pressure rises, the excess adsorbed amount increases and peaks before experiencing a decrease. However, when the temperature is relatively high (353 K), the excess adsorbed amount increases and plateaus among the entire pressure range in this study. The pressure corresponding to the maximum adsorbed amount is lower in the process of desorption compared with adsorption, because there exists a hysteresis between adsorption and desorption. With the increasing temperature, the excess adsorbed amount is on the decline, which is the same as pure gas. While the pressure corresponding to the maximum adsorbed amount ascends as the temperature rises, even beyond the pressure range in this study. Moreover, the excess adsorbed amount have a good linear relationship with the temperature. Furthermore, the CO2 shows the best adsorption capacity and the adsorption capacity of CH4 is greater slightly than N2. In addition, with the increasing temperature, the competitive adsorption among CO2, CH4 and N2 is weaker.

This paper’s purpose is to predict China’s uranium resources demand from 2016 to 2030 based on experimental modeling. In addition, we discuss the future supply structure of China’s uranium resources by analyzing the domestic and foreign supply capacity of China’s uranium resources. According the forecast results, Chinese uranium resource demand will reach 21385 tU in 2030 under a medium scenario. Due to the poor endowment of uranium resources, China’s domestic uranium production will increase slowly. It can be calculated that the total demand of uranium resources in China during 2016–2030 will be 216581 tU, the cumulative production of domestic production will be 37900 tU, the overseas production will be 41950 tU, and the international market purchases will be 130574 tU. Hence, the cumulative degree of dependence on foreign resources is approximately 80%. China’s foreign dependence on uranium will be greater than for oil, and the situation will become extremely serious. Therefore, we put forward s...

This case study describes the verbal and nonverbal social interaction of 11 youth with Autism Spectrum Disorders in a 3D Collaborative Virtual Learning Environment—iSocial. The youth were developing social competence through participation in a social competence intervention curriculum implemented online so as to provide access to high quality instruction for youth in small and rural communities. The data show the ability and variability of verbal and nonverbal reciprocal social interactions while online. In addition, the results of this case study revealed associations between pedagogical design features of the iSocial 3D CVLE, such as, goal-oriented, narrative embedded, game/role play enriched and peer-supported 3D CVLE activity design and higher frequencies and better quality of reciprocal social interaction. Therefore, these findings have potential to inform future design of 3D social learning spaces.

Cold atmospheric plasma (CAP) is a group of various chemical active species, such as ozone and nitric oxide, generated by working gas. CAP was demonstrated to have an effect on tissue regeneration and wound healing. We conducted this study to evaluate the efficacy and safety of CAP as a novel therapy for diabetic wounds in vitro and in vivo. The plasma consists of ionised helium gas that is produced by a high-voltage and high-frequency power supply. Eight-week-old male db/db mice and C57BL mice were treated with helium gas (control group), 90s' CAP (low-dose group), and 180s' CAP (high-dose group). Mice were treated and observed for 2 weeks. Skin samples from around the wound and blood samples were collected. Our in vitro analysis included scratch wound-healing assays by using human HaCaT immortalised human epidermal cells. After 14 days of treatment, CAP could obviously promote diabetic wound healing. Wound closure rates were significantly higher in the low-dose group and high-dose groups compared with the control group. Meanwhile, compared with the control group, the protein expression of IL-6, tumour necrosis factor-α, inducible nitric oxide synthase, and superoxide dismutase in two CAP groups significantly decreased, while the protein expression of vascular endothelial growth factor and transforming growth factor-β in two CAP groups significantly increased (all P < .05); these data show good agreement with the change in mRNA level (all P < .05). In vitro, scratch wound-healing assays showed that plasma treatment could effectively ensure healing within 3 minutes of exposure (all P < .05). In addition, no difference was found in histological observations of normal skin and the level of serum alanine transaminase, aspartate aminotransferase, blood urea nitrogen, creatinine, and white blood cells among the CAP groups and control group. CAP treatment for 3 minutes every day improves wound healing in diabetic mice by suppressing inflammation, reducing oxidative stress, and enhancing angiogenesis, involving several proteins signalling, and it is safe for the liver and kidney.

PM

Particulate matter (PM) was collected in three different areas, SY-1, SY-2, and SY-3, in Shenyang, China, during the warm and cold seasons from 2012 to 2014. SY-1 was located beside a thermal power plant, far from the central area. SY-2 was near a coal heating boiler on the main road, close to the central area. SY-3 was on the main road, without fixed emission sources. Nine PM-bound polycyclic aromatic hydrocarbons (PAHs) were analyzed. The results showed that the mean concentration of total PAHs was higher in the cold season (92.6&ndash, 316 ng m&minus, 3) than in the warm season (18.4&ndash, 32.2 ng m&minus, 3). Five- and six-ring PAHs occupied a large percentage at all sites in the warm season, and four-ring PAHs were the dominant components in the cold season. Several diagnostic PAH ratios indicated that the main sources of PAHs in Shenyang in the warm and cold seasons were not only coal burning but also vehicle emission. In this study, we suggest that a benzo[a]pyrene/benzo[ghi]perylene ratio ([BaP]/[BgPe]) of 0.6 was a useful indicator to speculate the relative significance of coal burning and vehicle exhaust. Although the Shenyang government has undertaken actions to address air pollution, the PM and PAH concentrations did not decrease significantly compared to those in our previous studies. The cancer risk calculated from the BaP equivalent total concentration at all three sites in the warm and cold seasons exceeded the acceptable limit established by the US EPA.

During disasters, discover people's concerns dynamically is crucial to disaster rescue and relief. In this paper, we propose a social media based framework to analyze people's concerns, to access the importance and to track the dynamic changes of these concerns. To better understand people's concerns across platforms and to monitor the dynamics, we make comparisons between Tweets and news on the mentioned aspects and disclosed some interesting findings. Specifically, we take 2018 Camp Fire, the most destructive wildfire on record in history of California as a case study. We find that despite their keen attentions towards the disaster, social media and news media focus on different aspects of the disaster, so are the contents and dynamic changes of their concerns.

Aims: Cold atmospheric plasma (CAP) interacted with tissue and had potential effects on wound healing and tissue regeneration. The aim of this study is to investigate the efficacy and safety of CAP as a novel therapy for diabetic wounds in vitro and in vivo. Methods: The plasma consists of ionized helium gas that is produced by a high-voltage (8.5kV) and high-frequency (17kHz) power supply. Eight-week-old male db/db mice were treated with conventional wound dressing only (control group), additional 90’s CAP (low-dose group) or 180’s CAP (high-dose group) for 2 weeks, respectively. Skin samples around wound in 3, 7, 14 days and blood samples were collected and analyzed in three groups. We carried out in vitro analysis included scratch wound healing assays in immortalized human epidermal HaCaT cells. Results: After 14 days of treatment, CAP could obviously promote diabetic wound healing because of inflammation inhibition and angiogenesis increase. Wound- closure rates of two CAP groups were significantly faster than that of control group. The protein expression of IL-6, TNF-α, iNOS and SOD significantly decreased while the protein level of VEGF, TGF-β in two CAP groups significantly increased compared to those in control group (all p < 0.05). And such changes showed a good consistency with the change in mRNA level (all p < 0.05). In vitro, scratch wound healing assays showed that plasma treatment could effectively accelerate the wound healing within 3 minutes exposure (all p < 0.05). Additionally, there were no significant differences in histological observation and the level of serum ALT, AST, BUN, CREA and WBC among the three groups. Conclusions: CAP treatment for 3 min daily improves diabetic wound healing by inhibiting inflammation, reducing oxidative stress and enhancing angiogenesis without toxicity to liver and kidney. Disclosure R. He: None. Q. Li: None. M. Yu: None. T. Wang: None. H. Lu: None. J. Lu: None. W. Zhu: None. M. Luo: None. J. Zhang: None. H. Gao: None. W. Xing: None. D. Wang: None. F. Liu: None. Funding National Natural Science Fund of China; Shanghai Science & Technology; Shanghai Municipal Education Commission

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the atmosphere and they mostly stem from the imperfect combustion of fossil fuels and biofuels. PAHs are inherently associated with homogenous fine particles or distributed to different-sized particles during the aging of air masses. PAHs carried by fine particles undergo a long-range transport to remote areas while those adsorbed on coarse particles have a shorter lifetime in ambient air. More importantly, PAHs with higher molecular weights tend to be bound with finer particles and can deeply enter the lungs, posing severe health risks to humans. Thus, the environmental fate and health effects of particulate PAHs are strongly size-dependent. This review summarizes the size distributions of particulate PAHs freshly emitted from combustion sources as well as the distribution patterns of PAHs in ambient particles. It was found that PAHs from stationary sources are primarily bound to fine particles, which are slightly larger than particles to which PAHs from mobile sources are bound. In ambient air, particulate PAHs are distributed in larger size modes than those in the combustion fume, and the particle size decreases with PAH molecular weight increasing. The relevant mechanisms and influencing factors of particle size distribution changes are illustrated in this article, which are essentially attributed to combustion and ambient temperature as well as the physical and chemical properties of PAHs. Overall, the study on the particle size distribution of PAHs will contribute for a full understanding of the origin, atmospheric behaviors and health effects of particulate PAHs.

Medicinal plants show important therapeutic value in chronic disease treatment. However, due to their diverse ingredients and complex biological effects, the molecular mechanisms of medicinal plants are yet to be explored. By means of several high-throughput platforms, here we show hawk tea extract (HTE) inhibits Niemann–Pick C1-like 1 (NPC1L1)-mediated free cholesterol uptake, thereby inducing the transcription of low-density lipoprotein receptor (LDLR) downstream of the sterol response element binding protein 2 (SREBP2) pathway. Meanwhile, HTE suppresses hepatocyte nuclear factor 4α (HNF4α)-mediated transcription of microsomal triglyceride transfer protein (MTP) and apolipoprotein B (APOB), thereby decreasing the production of very-low-density lipoprotein. The catechin EGCG ((−)-epigallocatechin gallate) and the flavonoids kaempferol and quercetin are identified as the bioactive components responsible for the effects on the NPC1L1-SREBP2-LDLR axis and HNF4α-MTP/APOB axis, respectively. Overall, hawk tea works as a previously unrecognized cholesterol-lowering agent in a multi-target and multi-component manner., Juan Feng et al. show that hawk tea extract reduces cholesterol by suppressing Niemann-Pick C1 like 1-mediated free cholesterol uptake and decreasing the production of very low-density lipoprotein through hepatocyte nuclear factor 4 alpha. This study suggests a therapeutic potential of hawk tea extract for hypercholesterolemia.

Background Breast cancer is one of the most lethal cancers in women when it reaches the metastatic stage. The plant Carpesium cernuum has been used as an anti-inflammatory, analgesic, and detoxifying agent in Chinese folk medicine. However, the inhibitory activity and molecular mechanisms of Carpesium cernuum in breast cancer cells have not been investigated. Methods RNA sequencing experiments were performed to elucidate the cellular pathways affected by Carpesium cernuum extract (CCE). Cell viability and EdU incorporation assays were conducted to determine the effect of CCE on cell proliferation. The inhibitory effects of CCE on the expression levels of target genes were confirmed by qRT-PCR and Western blot. Cell migration and invasion were analysed with transwell chamber assays. Results Proliferation assays indicated that CCE inhibited cell proliferation in multiple cancer cell lines and the IC50 value of CCE was the smallest in MDA-MB-231 cells. Transcriptome analysis showed that CCE significantly affected the cell adhesion pathway. Further experiments revealed that CCE suppressed cell migration and invasion. The inhibitory effect on migration was likely mediated by targeting TIMP1, MMP9, CD44 and COL4A2. The main active components of CCE were isolated, and CCE-derived sesquiterpene lactone substances could reproduce the inhibitory effect of CCE on cell migration and invasion. Conclusions Overall, both molecular and phenotypic assays showed that CCE has potential in the treatment of breast cancer, especially for the treatment of breast cancer metastasis. CCE-derived sesquiterpene lactone substances are the foundation for the tumor inhibitory effect of CCE.

Scientific argumentation is an epistemic practice where scientific theories are proposed, refined, and refuted, and also a language-based practice where evidence is provided in support of claims. This chapter explores how techniques of computerized image processing can help researchers to identify relationships between features of images and the quality of written artifacts used in scientific argumentation. In this chapter, secondary school students worked in an interactive simulation model and made claims about whether rain water was trapped underground. Automated image processing was employed to precisely quantify several image features relevant to the students' claims. Chi-square tests and independent samples t-tests were used to determine the relationships between the extracted features and the argumentation. The results revealed that the presence of a line on a student's snapshot had a significant effect on that student's claim and explanation scores and the starting and endpoints of the students' lines significantly influenced their explanation scores, but not their claim scores.

Particulate matter (PM) is a major factor contributing to air quality deterioration that enters the atmosphere as a consequence of various natural and anthropogenic activities. In PM, polycyclic aromatic hydrocarbons (PAHs) represent a class of organic chemicals with at least two aromatic rings that are mainly directly emitted via the incomplete combustion of various organic materials. Numerous toxicological and epidemiological studies have proven adverse links between exposure to particulate matter-bound (PM-bound) PAHs and human health due to their carcinogenicity and mutagenicity. Among human exposure routes, inhalation is the main pathway regarding PM-bound PAHs in the atmosphere. Moreover, the concentrations of PM-bound PAHs differ among people, microenvironments and areas. Hence, understanding the behaviour of PM-bound PAHs in the atmosphere is crucial. However, because current techniques hardly monitor PAHs in real-time, timely feedback on PAHs including the characteristics of their concentration and composition, is not obtained via real-time analysis methods. Therefore, in this review, we summarize personal exposure, and indoor and outdoor PM-bound PAH concentrations for different participants, spaces, and cities worldwide in recent years. The main aims are to clarify the characteristics of PM-bound PAHs under different exposure conditions, in addition to the health effects and assessment methods of PAHs.

Eleven years (2005–2015) of data from long-term monitoring at a Japanese remote background site in Wajima, were analyzed to investigate temporal trends and sources. Water-soluble inorganic ions (WSIIs) were analyzed for aerosol chemical composition. The total WSIIs concentration was 7.93 ± 3.93 μg/m3, accounting for 42.3% of TSP mass, ranged from 11.4 to 93.9%. SO42− is the most abundant ion, contributing a total WSII mass from 18.0 to 79.8%, and non-sea-salt (nss-) SO42− contributed from 63.6% to 99.6% of total SO42−, which was related to human activities on the Asian continent and the effects of marine precursors in spring and summer, respectively. NO3− and NH4+ contribute 6.3 and 7.4% of the total WSIIs and were affected by long-range transport and local sources as well. The increasing trend of Na+ and Cl− indicates the increased influence of sea salt, which is caused by more frequent strong winds. K+ is mainly produced from biomass burning with a stable seasonal variation, Ca2+ as the characteristic ion of dust has the highest concentration in spring. Mg2+ comes from minerals and marine sources during spring and summer, respectively. This work describes in detail the annual change trend of the WSIIs of atmospheric particles in the Wajima area, seasonal characteristics, and source contributions, provide a comprehensive understanding of long-term variation in atmospheric particulate.

Massive open online courses (MOOCs) have recently taken center stage in discussions surrounding online education, both in terms of their potential as well as their high dropout rates. The high attrition rates associated with MOOCs have often been described in terms of a scale-efficacy tradeoff. Building from the large numbers associated with MOOCs and the ability to track individual student performance, this study takes an initial step towards a mechanism for the early and accurate identification of students at risk for dropping out. Focusing on struggling students who remain active in course discussion forums and who are already more likely to finish a course, we design a temporal modeling approach, one which prioritizes the at-risk students in order of their likelihood to drop out of a course. In identifying only a small subset of at-risk students, we seek to provide systematic insight for instructors so they may better provide targeted support for those students most in need of intervention. Moreover, we proffer appending historical features to the current week of features for model building and to introduce principle component analysis in order to identify the breakpoint for turning off the features of previous weeks. This appended modeling method is shown to outperform simpler temporal models which simply sum features. To deal with the kind of data variability presented by MOOCs, this study illustrates the effectiveness of an ensemble stacking generalization approach to build more robust and accurate prediction models than the direct application of base learners. Propose a temporal modeling approach for students' dropout behavior in MOOCs.Demonstrate the advantage of appended feature modeling space based on PCA over a summed features modeling space.Explore the power of the ensemble learning method (stacking generalization) in enhancing the prediction ability.

Previous studies have invested much effort in understanding how participation in asynchronous online discussion affects student learning, and what factors influence student participation behavior. Results of these studies have been inconclusive and these investigations are often conducted from isolated perspectives. Relying on social cognitive theory, this study proposes two dynamic student participation models in online dialogue and particularly highlights understudied factors - collective efficacy, social ability, reading behavior, the time dimension of participation - to examine the mediation and causal relationship among those factors and their influence on learning. The models are tested utilizing data collected from a large US university. Specifically, while the predictive constructs are operationalized through the survey instruments, the outcome measures are modeled using electronic trace data and actual evaluation information. Data is analyzed using the Partial Least Squares modeling method. Results demonstrate the intertwined relationship among constructs and a different influencing mechanism for each construct on participation behavior and learning. By comparing these two built models, the time dimension of participation is shown to be more influential in predicting student learning than posting and reading actions. The paper concludes with a discussion of the implications of this study. Shows two social cognitive theory informed online student participation models.Applies collective efficacy, social ability, and temporal dimensions to online learning.Computational model shows the relationship between participation behavior and learning.The time dimension of model predicts student learning.

This case study explores the experience of embodied social presence while learning social competence of 11 youth with Autism Spectrum Disorders (ASD). The learning takes place in a series of 13 Naturalistic Practice (NP) learning activities which are part of a 3D Collaborative Virtual Learning Environment (CVLE)-iSocial. iSocial is a translation of a face-to-face clinic based curriculum, Social Competence Intervention-Adolescents (SCI-A), into a 3D CVLE for delivery over the Internet,. This study developed a direct-observation instrument that built upon the Embodied Social Presence (ESP) theory framework to describe youth with ASDs' embodied presence, embodied copresence and embodied social presence. The findings show that youth with ASD achieved embodied presence and embodied copresence in almost all of the NP activities. However, they achieved embodied social presence in only a handful of NP activities. From comparisons between the learning activities that had high or low percentages of achieving ESP, the results indicate associations of design features (narratives, choosing roles, fantasy settings and ease of use of learning tools) with having a higher percentage of youth achieve embodied social presence. Furthermore, the work of this study provides a method for researchers interested in studying ESP and the results can inform future design decisions in the development 3D CVLE and the structure of learning activities within the 3D CVLE. The study explores 11 youth with Autism embodied social presence in 3D CVLE.Evidence-based observation method is developed based on ESP theory.Rich descriptions of levels of embodied presence, copresence, and social presence.Higher percentages of achieved ESP are associated with 3D CVLE Design features.

The adsorption/desorption of CO2/CH4 mixtures with three different volume fractions was investigated at 294 K, 311 K, 333 K, and 353 K with pressures of up to 70 bar on anthracite from China using a high-pressure volumetric analyzer (HPVA II-200). For the mixtures, the total excess adsorbed amount decreased as the temperature rose. In addition, it displayed an upward tendency with an increase in the CO2 fraction in the feed gas. The excess adsorbed amounts of the component gases were calculated on the basis of the composition of the gas phase measured by gas chromatography. For a mixture with a CO2 fraction of 50%, relatively good adsorptivity for CO2 was displayed at low pressures (

C25H24N3O3, monoclinic, P21/c (no. 14), a = 9.4549(11) Å, b = 10.7640(12) Å, c = 21.279(3) Å, β = 98.778(2)°, V = 2140.2(4) Å3, Z = 4, R gt(F) = 0.0498, wR ref(F 2) = 0.1408, T = 296(2) K.

From a network perspective, self-regulated learning (SRL) can be conceptualized as networks of mutually interacting self-regulatory learning behaviors. Nevertheless, the research on how SRL behaviors dynamically interact over time in a network architecture is still in its infancy, especially in the context of STEM (sciences, technology, engineering, and math) learning. In the present paper, we used a multilevel vector autoregression (VAR) model to examine the temporal dynamics of SRL behaviors as 101 students designed green buildings in Energy3D, a simulation-based computer-aided design (CAD) environment. We examined how different performance groups (i.e., unsuccessful, success-oriented, and mastery-oriented groups) differed in SRL competency, actual SRL behaviors, and SRL networks. We found that the three groups had no significant difference in their perceived SRL competency; however, they differed in SRL behaviors of evaluation. Both the mastery-oriented and success-oriented groups performed more evaluation behaviors than the unsuccessful group. Moreover, the mastery-oriented group showed stronger interaction between SRL behaviors than the success-oriented group and the unsuccessful group. The SRL networks of the three groups shared some similarities, but they were different from each other in general. This study has significant theoretical and methodological implications for the advancement of research in SRL dynamics.

Role of trace elements (TEs) in long-term anaerobic digestion of food waste (FW) under fixed and stepwise increasing loads and under early and medium volatile fatty acid (VFA) inhibition was investigated. Digesters under high load suffered VFA inhibition. Mismatch between scarce TEs in FW and essential TEs for sustainable methanogenesis suppressed Methanosaeta causing blocked aceticlastic methanogenesis and shift to CO2 reduction pathway, as indicated by decreased Methanosaeta from above 70.0% to below 42.0% and enriched hydrogenotrophic methanogens (Methanospirillum, Methanoculleus, Methanobacterium) from below 15.0% to above 53.6%. Dual stresses of VFA inhibition and TEs deficiency resulted in recession of syntrophic Bacteria Syntrophomonadaceae. Conversely, digesters with TEs supplementation maintained high activity of Syntrophomonadaceae and ensured predominant aceticlastic methanogenesis and powerful methanogenic community functions. Early and medium VFA inhibition were reversed by TEs supplementation or coupling with pH adjustment by stimulating VFAs degradation via syntrophic metabolism and unclogging acetate conversion via aceticlastic methanogenesis.

Thin film photovoltaic technologies are playing an increasingly important role in the transition to a low carbon economy. Their extensive deployment will require large amounts of raw materials, especially those of companion metals. Concerns about whether the availability of materials will impede the development of low-carbon technologies have led to growing research in resource criticality. However, previous studies on criticality generally provide only static assessment models and pay little attention to the difference between base metals and companion metals. This article makes an attempt to dynamically evaluate the long-term criticalities of companion metals at a global level by combining the supply risk and impact of supply disruption. The results highlight germanium and indium as the elements with the highest criticality; tellurium and selenium exhibit a relatively moderate criticality while gallium and cadmium show very low criticality. The findings will offer proper guidance for stakeholders to address supply shortages in advance and encourage thin film technologies development. Priority measures for high criticality materials are discussed to alleviate the supply disruption potential, such as strategic stockpiling, implementing fixed-price contracts, increasing by-product recovery and secondary supply, material substitution and strengthening global mining.

It is vital to develop an understanding of students' self-regulatory processes in the domains of STEM (Science, Technology, Engineering, and Mathematics) for the quality delivery of STEM education. However, most studies have followed a variable-centered approach, leaving open the question of how specific SRL (Self-regulated Learning) behaviors group within individual learners. Furthermore, little is known about how students' SRL profiles unfold over time in STEM education, specifically in the context of engineering design. In this study, we examined the change of students’ SRL profiles over time as 108 middle school students designed green buildings in a simulation-based computer-aided design (CAD) environment. We identified three distinct SRL profiles using a longitudinal clustering approach: reflective-oriented, adaptive, and minimally self-regulated learners. In addition, we found that students with different profile memberships differed significantly in their design performance. Specifically, adaptive self-regulated learners outperformed minimally self-regulated learners on design completeness, whereas reflective-oriented self-regulated learners demonstrated higher design efficiency than minimally self-regulated learners. This study provides researchers with both theoretical and methodological insights concerning SRL dynamics. Findings from this research also inform practitioners about the design of adaptive interventions.

Natural aeolian dust (AD) particles are potential carriers of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere. The heterogeneous interaction between them may lead to worsened air quality and enhanced cytotoxicity and carcinogenicity of ambient particulates in downwind areas, and this topic requires in-depth exploration. In this study, AD samples were collected from four Asian dust sources, and their physical properties and compositions were determined, showing great regional differences. The physical and chemical interactions of different AD particles with naphthalene (Nap; model PAH) were observed in aqueous systems. The results showed that AD particles from the Loess Plateau had weak adsorption to Nap, which was fitted by the Langmuir isotherm. There was no obvious adsorption to Nap found for the other three AD samples. This difference seemed to depend mainly on the specific surface area and/or the total pore volume. In addition, the Nap in the aqueous solution did not undergo chemical reactions under dark conditions and longwave ultraviolet (UV) radiation but degraded under shortwave UV radiation, and 2-formylcinnamaldehyde and 1,4-naphthoquinone were the first-generated products. The degradation of Nap in the aqueous solution was probably initiated by photoionization, and the reaction rate constant (between 1.44 × 10−4 min−1 and 8.55 × 10−4 min−1) was much lower than that of Nap with hydroxyl radicals. Instead of inducing or promoting the chemical change in Nap, the AD particles slowed photodegradation due to the extinction of radiation. Therefore, it is inferred that natural AD particles have no substantial effect on the transportation and transformation of PAHs in the atmosphere.

Background Hypoxic ischemic encephalopathy (HIE) is brain injury caused by different reasons and the most common diagnosed is neonatal HIE. Most of the existing treatments have their own shortcomings or there are still some unexplained mechanisms in it. Topiramate (TPM) is a new drug for the treatment for seizures in neonates with HIE, but is currently used off-label. Our protocol aims to access the efficiency and safety of TPM for HIE. Methods and analysis Eight databases will be searched by 2 independent researchers for the article on the topic of using TPM as treatment for HIE, including PubMed, the Cochrane Central Register of Controlled Trials (Cochrane Library), Embase, and Web of Science, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), Wang Fang Database and Chinese Science and Technology Periodical database (VIP). The included papers are those published from the established date of the databases to 2019. The therapeutic effects based on the grade of neonatal behavioral neurological assessment will be regarded as the primary outcomes. RevMan V5.3 will be used to compute the data synthesis and carry out meta-analysis. The risk of bias will be appraised by the Cochrane risk of bias tool. Rare ratio for dichotomous outcomes and mean different for continuous data will be expressed with 95% confidence intervals (CI) for analysis. A random effects model or a fixed effects model will be employed, when heterogeneity is found or not. Subgroup analysis and sensitivity analysis will be applied if the heterogeneity is obvious. Results This study will provide the recent evidence of TPM for HIE from reducing seizure acticity. Conclusion The conclusion of this study will provide proof to evaluate if TPM is effective and safe in the treatment of HIE.PROSPERO registration number: PROSPERO CRD42018117981.

Background: Background sites are mainly affected by long-range-transported air pollutants, resulting in potential adverse effects on local atmospheric environments. A 4&ndash, 5 year observational study was conducted to illustrate the air pollution profile at the Kanazawa University Wajima air monitoring station (KUWAMS), an ideal remote background site in Japan. Methods: Nine polycyclic aromatic hydrocarbons (PAHs) in the particulate phase and various air pollutants were continuously monitored for 4&ndash, 5 years. Diagnostic ratios of PAHs and back-trajectory analysis were applied to trace the possible sources of the air pollutants collected at the sampling site. Results: The atmospheric concentration of PAHs in the atmosphere at the site decreased from 2014 to 2019, benefit from the predominant air pollution control policy in China and Japan. Common air pollutants including sulfur dioxide (SO2), nitrogen oxides (NOx), ozone, methane (CH4), and non-methane hydrocarbon (NMHC) were detected in low concentrations from 2016 to 2019, while ozone (O3) and particulate matter (PM2.5, PM with a diameter less than 2.5 &mu, m) were present in high levels that exceeded the Japanese standards. Most air pollutants peaked in spring and showed evident diurnal variations in spring and summer. Conclusions: This is the first study to clarify the atmospheric behaviors of multiple air pollutants at a background site in Japan. Significant external air pollutant impact and unneglectable air pollution were demonstrated at KUWAMS, indicating the importance of studying atmospheric pollution at remote sites.

PM2.5 samples were collected inside and outside a primary school classroom in Beijing in 2015 and analysed for 11 polycyclic aromatic hydrocarbons (PAHs) and 10 nitro-PAHs (NPAHs). In the sampling period in the heating season (namely, the heating period), the median concentrations of indoor and outdoor PAHs were 223 ng/m3 and 264 ng/m3, respectively, and those of indoor and outdoor NPAHs were 3.61 ng/m3 and 5.12 ng/m3, respectively. The concentrations of PAHs and NPAHs were consistently higher in the heating period than those (indoor PAHs: 8.75 ng/m3, outdoor PAHs: 8.95 ng/m3, indoor NPAHs: 0.25 ng/m3, outdoor NPAHs: 0.40 ng/m3) in the sampling period in the non-heating season (namely, the non-heating period). In both periods, total PAHs and total NPAHs in indoor PM2.5, as well as most individual PAHs and NPAHs, were positively correlated with the outdoor PAH and NPAH concentrations (p

Background: Insomnia is a prevalent and bothersome disorder of sleep initiation and maintenance. Although efficacious treatments for insomnia have been available for decades, they all have their own limitations. Guizhi Gancao Longgu Muli Decoction (GGLMD), a popular complementary and alternative therapy, has been widely applied to treat insomnia in some Asian countries for centuries. Yet no systematic reviews have comprehensively assessed the efficacy and safety of GGLMD as a treatment for insomnia. Methods: A comprehensive search up to November, 2019 will be conducted in the following electronic databases: the Cochrane Library, Embase, PubMed, Web of Science, the Chinese National Knowledge Infrastructure (CNKI), the Chinese Biomedical Literature Database (CBM), the Chinese Scientific Journal Database (VIP), and the Wanfang Database. The primary outcomes will be sleep quality including Pittsburgh Sleep Quality Index (PSQI) and polysomnography (PSG). Stata 15 will be used for data analysis as well. Results: This study will provide the current evidence of insomnia treated with GGLMD from the several points including PSQI and PSG. Conclusion: The consequence of this summary will furnish proof to evaluate if GGLMD is effective in the treatment of insomnia. Ethics and dissemination: Without personal information involved, ethical approval and informed consent form is no need. The review will be submitted to a peer-reviewed journal prospectively to spread our findings. PROSPERO registration number: PROSPERO CRD42018118336.

Engineering design is a complex process which requires science, technology, engineering, and mathematic (STEM) knowledge. Students' self-regulation plays a critical role in interdisciplinary tasks. However, there is limited research investigating whether and how self-regulation leads to different learning outcomes among students in engineering design. This study analyzes the engineering design behaviors of 108 ninth-grade U.S. students using principal component analysis and cluster analysis. It classifies the students into four distinct types: competent, cognitive-oriented, reflective-oriented, and minimally self-regulated learners. Competent self-regulated learners perceived themselves as the most self-regulated learners and had the greatest learning gains, although they did not perform best in the task. Cognitive-oriented self-regulated learners perceived themselves as the least self-regulated learners although they were the second best in both the performance of the task and learning gains. In contrast, reflective learners had the best performance in the task. Minimally self-regulated learners did not perform well in the task and had the lowest learning gains. The results revealed that the competent self-regulated learners had an appropriate assessment of themselves to obtain knowledge, cognitive-oriented self-regulated learners underestimated themselves, reflective learners focused on the results of the task, and minimally self-regulated learners overestimated themselves and exerted the least effort. The results also offer new insights into STEM education and self-regulated learning with emerging learning analytics.

In this work, the effects of different torrefaction temperatures and durations on the physicochemical properties of rice straw (RS), and the emission characteristic of PM10 (particulate matter with aerodynamic diameters of ≤10 µm) during torrefied RS combustion, were investigated. Results indicate that the release of Cl and K, and decomposition of the organic matrix demonstrated a promoting effect during torrefaction. However, the removal of Cl and K did not reduce the emission of PM1. The emission concentration of PM1 and PM1–10 generated from torrefied RS was enhanced, and the yields of PM1–10 was much higher than those of PM1. The concentrations of K and Cl in PM1–10 increased with torrefaction temperature, combined with the microstructure, indicating that the torrefaction pretreatment promoted the heterogeneous condensation of KCl vapour to form PM1–10.

This study investigated mechanism of process imbalance of long-term anaerobic digestion (AD) of food waste (FW) and role of trace elements (TEs) in maintaining process stability. AD of FW was strongly inhibited by volatile fatty acids (VFA, mainly propionate). The deficiency of essential TEs in FW was the fundamental reason. TEs contents in digester gradually decreased with regular substrate feeding and digestate discharge, which greatly limited growth and metabolism of hydrogenotrophic methanogens and Methanosarcina. Finally, Methanosaeta replaced Methanosarcina and became dominant methanogen and hydrogenotrophic methanogens almost disappeared accompanied by declining methanogenic community diversity, which greatly suppressed ecological functions of methanogens and led to propionate inhibition. TEs supplementation eliminated all factors causing process imbalance and significantly enhanced process stability by maintaining strong ecological functions of methanogens via stimulating dominant growth of Methanosarcina (relative abundance between 67.2% and 87.5%), sustaining stable relative abundances of hydrogenotrophic methanogens (about 10%) and enhancing methanogenic community diversity.

Bacterial infections may cause severe diseases such as tuberculosis, sepsis, nephritis and cystitis. The rapid and sensitive detection of bacteria is a prerequisite for the treatment of these diseases. The current gold standard for bacterial identification is bacteriological culture. However, culture-based identification takes 3-7 days, which is time-consuming and laborious. In this study, bacteria in urine samples were enriched using a portable filter-based pipette. Then, a centrifugal chip was constructed to detect multiple pathogenic bacteria from urine samples by integrating the DNA extraction, multiplex recombinase polymerase amplification (RPA) and fluorescent detection together. This eliminated the time-consuming cultivation step, and thus accelerated the diagnosis of the urinary tract infections (UTIs). The five major pathogenic bacteria in UTIs were detected in this study, which are Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa, Staphylococcus aureus and Salmonella typhimurium. Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa and Staphylococcus aureus were successfully detected with limits of detection of 100 CFU mL-1 from urine samples within 40 min. Salmonella typhimurium was successfully detected with a limit of detection of 1000 CFU mL-1 from urine samples. The chip-based bacteria detection proposed in this study is a promising tool for sensitive, accurate, and multiplex identification of bacteria in clinical urine samples of UTIs and bacteriuria.

In this paper, considering the complexity of AGV working environment, the image filtering, segmentation and graph morphology processing are carried out for the high noise of AGV working environment. To solve the problem of uneven light in the process of AGV travel, a dynamic threshold transfer and segmentation method is proposed, which greatly improves the accuracy and efficiency of the segmentation. At the same time, after extracting the morphological gradient of the marking line, the whole inspection method of image acquisition and the label processing of the boundary are established, and a one-sided fast center line searching algorithm is proposed. Compared with the traditional algorithm, the computation cost is reduced by more than 50%.

A laboratory investigation was performed to describe the detailed CO 2 –CH 4 displacement and dispersion in enhanced gas recovery. A series of experiments were conducted in a vertical sandpack sample of glass beads at a core pressure in the range of 4–14 MPa at temperature of 29–60 °C with a CO 2 injection flow rate of 0.2–0.5 ml/min. The displacement process was scanned with a resolution of approximately 34.2 μm by an X-ray CT scanner in this study. The porosity distribution of the sandpack sample was obtained along the core based on the CT image. Simultaneously, the existence of the mixing zone was proven, and no interface appeared in the process of CO 2 –CH 4 displacement. Furthermore, the dispersion coefficients were obtained by analysing the produced gas. The experimental results revealed that the dispersion coefficient increased with temperature exponentially in our experimental ranges, which can be interpreted by molecular kinetic theory. The dispersion coefficient becomes much larger as the pressure becomes closer to the critical pressure at 40 °C, which is probably enhanced by the fluctuation phenomenon, as the CO 2 density sharply changes with the pressure around the critical point. In addition, the dispersion coefficient increases with the flow rate. The heterogeneity of sandpack sample packed with BZ2 glass beads leads to a larger dispersion coefficient, whereas the growth trend in other samples is not obvious. Ultimately, the dispersivity of the BZ04 glass beads sandpack sample is estimated at 0.002–0.0055 m based on the dispersion coefficient data.

Background Exposure to aminoglycoside antibiotics can induce ototoxicity in genetically susceptible individuals carrying certain mitochondrial DNA (mtDNA) mutations (C1494T and A1555G), resulting in hearing loss. So, a rapid diagnostic approach is needed to accurately identify subjects carrying such gene mutations. Methods In the present study, we describe a rapid and reliable four-color, real-time quantitative polymerase chain reaction (qPCR) assay for simultaneously detecting two mtDNA 12S rRNA gene variants, A1555G and C1494T, which are prevalent in the Han Chinese population. This multiplex assay incorporates three allele-specific TaqMan probes labeled with different fluorophores in a single reaction, providing high genotyping accuracy for clinical blood samples. Results Tests with C1494T, A1555G and wild-type DNA exhibited high sensitivity, specificity, reproducibility and accuracy of discriminating mutations from wild-type. Conclusions This study shows that this simple and inexpensive method can be used for routine molecular diagnostics and potentially for large-scale genetic screening.

A theory-based method for a computational student performance prediction.A Genetic Programming model for grade prediction is described and tested.Model evaluation suggests high success rates for predicting student grades. Building a student performance prediction model that is both practical and understandable for users is a challenging task fraught with confounding factors to collect and measure. Most current prediction models are difficult for teachers to interpret. This poses significant problems for model use (e.g. personalizing education and intervention) as well as model evaluation. In this paper, we synthesize learning analytics approaches, educational data mining (EDM) and HCI theory to explore the development of more usable prediction models and prediction model representations using data from a collaborative geometry problem solving environment: Virtual Math Teams with Geogebra (VMTwG). First, based on theory proposed by Hrastinski (2009) establishing online learning as online participation, we operationalized activity theory to holistically quantify students' participation in the CSCL (Computer-supported Collaborative Learning) course. As a result, 6 variables, Subject, Rules, Tools, Division of Labor, Community, and Object, are constructed. This analysis of variables prior to the application of a model distinguishes our approach from prior approaches (feature selection, Ad-hoc guesswork etc.). The approach described diminishes data dimensionality and systematically contextualizes data in a semantic background. Secondly, an advanced modeling technique, Genetic Programming (GP), underlies the developed prediction model. We demonstrate how connecting the structure of VMTwG trace data to a theoretical framework and processing that data using the GP algorithmic approach outperforms traditional models in prediction rate and interpretability. Theoretical and practical implications are then discussed.

It is important to quantitatively understand the methane adsorption and transport mechanism in coal for an evaluation of the reserves and for its production forecast. In this work, a block coal sample was chosen to perform the CH4 adsorption experiments using the gravimetric method at temperatures of 293.60 K, 311.26 K, 332.98 K and 352.55 K and pressures up to 19 MPa. The excess adsorption capacity of CH4 in dry block anthracite increased, followed by a sequence decrease with the increasing pressure. High temperature restrained the growth of the excess adsorption due to that the adsorption is an intrinsically physical and exothermic process. The excess adsorption peak decreased slowly with the increase of temperature and intersected at a pressure of more than 18 MPa; meanwhile, the pressure at the excess adsorption peak increased. The existing correlations were examined in terms of density rather than pressure. The DR+k correlation, with an average relative deviation of ±0.51%, fitted our data better than the others, with an average relative deviation of up to 2.29%. The transportation characteristics of CH4 adsorption was also investigated in this study, including the adsorption rate and diffusion in block coal. The kinetic data could be described by a modified unipore model. The adsorption rates were found to exhibit dependence on pressure and temperature at low pressures, while the calculated diffusivities exhibited little temperature dependence. In addition, the kinetic characteristics were compared between CH4 and CO2 adsorption on the block coal. The excess adsorption ratios of CO2 to CH4 obtained from the DR+k model decreased with the increasing pressure.