NTM-Based Skill-Aware Knowledge Tracing for Conjunctive Skills.

Knowledge tracing (KT) is the task of modelling students' knowledge state based on their historical interactions on intelligent tutoring systems. Existing KT models ignore the relevance among the multiple knowledge concepts of a question and characteristics of online tutoring systems. This paper proposes a neural Turing machine-based skill-aware knowledge tracing (NSKT) for conjunctive skills, which can capture the relevance among the knowledge concepts of a question to model students' knowledge state more accurately and to discover more latent relevance among knowledge concepts effectively. We analyze the characteristics of the three real-world KT datasets in depth. Experiments on real-world datasets show that NSKT outperforms the state-of-the-art deep KT models on the AUC of prediction. This paper explores details of the prediction process of NSKT in modelling students' knowledge state, as well as the relevance of knowledge concepts and conditional influences between exercises.

Effects of Nanoplastics on the Dinoflagellate Amphidinium carterae Hulburt from the Perspectives of Algal Growth, Oxidative Stress and Hemolysin Production.

Recently, the effects of nanoplastics (NPs) on aquatic organisms have attracted much attention; however, research on the toxicity of NPs to microalgae has been insufficient. In the present study, the effects of polystyrene nanoplastics (nano-PS, 50 nm) on growth inhibition, chlorophyll content, oxidative stress, and algal toxin production of the marine toxigenic dinoflagellate Amphidinium carterae Hulburt were investigated. Chlorophyll synthesis was promoted by nano-PS on day 2 but was inhibited on day 4; high concentrations of nano-PS (≥50 mg/L) significantly inhibited the growth of A. carterae. Moreover, despite the combined effect of superoxide dismutase (SOD) and glutathione (GSH), high reactive oxygen species (ROS) level and malondialdehyde (MDA) content were still induced by nano-PS (≥50 mg/L), indicating severe lipid peroxidation. In addition, the contents of extracellular and intracellular hemolytic toxins in nano-PS groups were significantly higher than those in control groups on days 2 and 8, except that those of extracellular hemolytic toxins in the 100 mg/L nano-PS group decreased on day 8 because of severe adsorption of hemolytic toxins to the nano-PS. Hence, the effects of nano-PS on A. carterae are closely linked to nano-PS concentration and surface properties and exposure time. These findings provide a deep understanding of the complex effects of NPs on toxigenic microalgae and present valuable data for assessing their environmental risks.

Phototransformation of zinc oxide nanoparticles and coexisting pollutant: Role of reactive oxygen species.

In this study, the photochemistry of ZnO NPs and their effect on phototransformation of coexisting pollutants (sulfamethazine, SMZ) were systematically investigated under UV illumination. SMZ (40 µM) degradation was accelerated by ZnO NPs, as the observed reaction rate constant (kobs) increased from 0.0809 h-1 to 0.7982 h-1 at the concentration of 5-50 mg/L ZnO NPs. Free radical quenching and quantification experiments indicated the reactive oxygen species, especially the hydroxyl radicals (OH) and singlet oxygen (1O2), made great contributions to SMZ degradation. Moreover, SMZ was prone to be degraded at high pH with kobs reaching upto 0.5734 h-1 at pH 12.0. The presence of Cl- (1000 mM) reduced the SMZ decomposition greatly by 2.4-fold while the effects of SO42- (30 mM) were very limited. Natural organic matter including humic acid and tannic acid both inhibited the degradation of SMZ with kobs decreasing by 35.4-fold and 132-fold, respectively. During the photoreaction process, ZnO NPs fragmented into relative small size pieces obviously along with the release of Zn2+. Finally, the possible cotransformation pathways of ZnO NPs and SMZ were proposed based on SMZ degradation intermediates and the above results. These findings of the present study suggested that the photoreactions of ZnO NPs greatly influenced the transformation of contaminants and ZnO NPs themselves in aquatic environment, which may have significant implications for the fate assessment of NPs and environmental pollutants.

Sorption of fluoroquinolones to nanoplastics as affected by surface functionalization and solution chemistry.

Microplastics have attracted much attention in recent years as they can interact with pollutants in water environment. However, nanoplastics (NPs) with or without the surface functionalization modification have not been thoroughly explored. Here, the sorption behaviors of two fluoroquinolones (FQs), including norfloxacin (NOR) and levofloxacin (LEV) on polystyrene NPs (nano-PS) and carboxyl-functionalized polystyrene NPs (nano-PS-COOH) were investigated. The results showed that sorption isotherms were nonlinear and well fitted by Langmuir model. The sorption capacities of NOR and LEV on nano-PS-COOH were higher than those on nano-PS, and their physical interactions, including polar interaction, electrostatic interaction and hydrogen bonding may be the dominant mechanisms. Moreover, the increase of pH firstly increased the sorption of two FQs on NPs and then decreased because NOR and LEV had a reverse charge at different pH values. Salinity and dissolved organic matter both inhibited the sorption process. These findings show that NPs with or without the surface functionalization modification have different sorption behaviors for environmental pollutants, which deserve our further concern.

Measuring popularity of ecological topics in a temporal dynamical knowledge network.

As interdisciplinary branches of ecology are developing rapidly in the 21st century, contents of ecological researches have become more abundant than ever before. Along with the exponential growth of number of published literatures, it is more and more difficult for ecologists to get a clear picture of their discipline. Nevertheless, the era of big data has brought us massive information of well documented historical literature and various techniques of data processing, which greatly facilitates the implementation of bibliometric analysis on ecology. Frequency has long been used as the primary metric in keyword analysis to detect ecological hotspots, however, this method could be somewhat biased. In our study, we have suggested a method called PAFit to measure keyword popularity, which considered ecology-related topics in a large temporal dynamical knowledge network, and found out the popularity of ecological topics follows the "rich get richer" and "fit get richer" mechanism. Feasibility of network analysis and its superiority over simply using frequency had been explored and justified, and PAFit was testified by its outstanding performance of prediction on the growth of frequency and degree. In addition, our research also encourages ecologists to consider their domain knowledge in a large dynamical network, and be ready to participate in interdisciplinary collaborations when necessary.