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Big data in education promotes access to the analysis of learning behavior, yielding many valuable analysis results. However, with obscure and insufficient guidelines commonly followed when applying the analysis results, it is difficult to translate information knowledge into actionable strategies for educational practices. This study aimed to solve this problem by utilizing the learning analytics (LA) framework. We proposed a learning analytics framework based on human-centered Artificial Intelligence (AI) and emphasized its analysis result application step, highlighting the function of this step to transform the analysis results into the most suitable application strategy. To this end, we first integrated evidence-driven education for precise AI analytics and application, which is one of the core ideas of human-centered AI (HAI), into the framework design for its analysis result application step. In addition, a cognitive load test was included in the design. Second, to verify the effectiveness of the proposed framework and application strategy, two independent experiments were carried out, while machine learning and statistical data analysis tools were used to analyze the emerging data. Finally, the results of the first experiment revealed a learning strategy that best matched the analysis results through the application step in the framework. Further, we conclude that students who applied the learning strategy achieved better learning results in the second experiment. Specifically, the second experimental results also show that there was no burden on cognitive load for the students who applied the learning strategy, in comparison with those who did not.

Educational data mining and learning analytics have become a very important topic in the field of education technology. Many frameworks have been proposed for learning analytics which make it possible to identify learning behavior patterns or strategies. However, it is difficult to understand the reason why behavior patterns occur and why certain strategies are used. In other words, all of the existing frameworks lack an important step, that is, result confirmation. In this paper, we propose a Result Confirmation-based Learning Behavior Analysis (ReCoLBA) framework, which adds a result confirmation step for exploring the hidden reasons underlying the learning patterns and strategies. Using this ReCoLBA framework, a case study was conducted which analyzed e-book reading data. In the case study, we found that the students had a tendency to delete markers after adding them. Through an investigation, we found that the students did this because they could not grasp the learning emphasis. To apply this finding, we proposed a learning strategy whereby the teacher highlights the learning emphasis before students read the learning materials. An experiment was conducted to examine the effectiveness of this strategy, and we found that it could indeed help students achieve better results, reduce repetitive behaviors and save time. The framework was therefore shown to be effective.

Online learning has become a part of daily life. However, it has fostered a tendency to shallow reading. Notably, little attention has been paid to precisely identifying shallow reading behaviors using quantified education big data in favor of methods such as conceptual descriptions, opinions, and questionnaires, resulting in an imprecise analysis of its impact on learning and a lack of strategies to mitigate its causative factors. This study addresses the issue by introducing a behavior-identifying model grounded in measurable data to precisely identify shallow reading behaviors. Initially, three key dimensions of shallow reading behaviors were proposed, along with corresponding mathematical indicators. Subsequently, the k-means algorithm and Pearson correlation coefficient were employed to evaluate the relationship between shallow reading and learning performance, underscoring its significance. The analysis showed that shallow reading behaviors are highly associated with poor learning performance, thus hindering critical reading. These findings further validate the predominant influence of reading speed on learning performance. Consequently, a strategy was developed to intentionally decrease reading speed. Following that, an experiment was conducted to assess the effectiveness of this strategy in mitigating shallow reading. The results revealed improved learning performance and a significant reduction in shallow reading behaviors without increasing cognitive load. [ABSTRACT FROM AUTHOR]

Antibiotic resistance is one of the biggest challenges to public health and ecological safety in the 21st century. Urban wastewater treatment plants (UWTPs), as reservoirs of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB), simultaneously contain a wide variety of chemical pollutants. The review introduces the actual concentration levels and the mechanisms of antibiotic resistance drivers (ARDs) in UWTPs, including antibiotics, heavy metals, disinfectants, cosmetics and personal care products, non-antibiotic drugs, and microplastics. Moreover, this review emphasizes the importance of approaching the actual activated sludge environment in future research and proposes future directions. [ABSTRACT FROM AUTHOR]

Abstract Due to complexity and variety of pharmaceutical wastewater composition, little is known as for functionally important microflora of pharmaceutical wastewater treatment plants (pWWTPs). We compared bacterial composition and diversity of pWWTPs (27 sludge samples collected from 12 full-scale pWWTPs) with those of other industrial (iWWTPs) (27 samples) and municipal wastewater treatment plants (mWWTPs) (27 samples) through meta-analysis based on 16S rRNA gene amplicon sequencing, and identified putatively important organisms and their ecological correlations. Non-metric multidimensional scaling indicated that the pWWTPs, iWWTPs and mWWTPs showed distinctive differences in bacterial community composition (P < 1e−04), and the pWWTPs had significantly lower bacterial diversity than the mWWTPs (P < 1e−06). Thermotogae and Synergistetes phyla only strictly dominated in the pWWTPs, and 26, 30 and 6 specific genera were identified in the pWWTPs, mWWTPs and iWWTPs, respectively. Totally, 15 and 1300 OTUs were identified as core and occasional groups, representing 23.2% and 66.2% of the total read abundance of the pWWTPs, respectively. Permutational multivariate analysis of variance revealed that the bacterial components were clearly clustered corresponding to the types of pharmaceutical wastewater, and a total of 129 local specific OTUs were identified in the pWWTPs, among which anticancer antibiotics pWWTPs had the highest number of specific OTUs (40 ones). Co-occurrence network revealed that the species dominating in the same type of pWWTPs tended to co-occur much more frequently than theoretical random expectation. The results may extend our knowledge regarding the ecological status and correlation of the key microflora in pWWTPs. Graphical abstract Unlabelled Image Highlights • Meta-analysis was conducted to explore key components of bacterial assemblages in pWWTPs. • pWWTPs showed relatively lower bacterial diversity and unique community composition. • Type of wastewater mainly drove the divergence of bacterial community in pWWTPs. • pWWTPs contain core and specific species as key components of bacterial community. • Bacterial assemblages within specific community tend to co-occur in pWWTPs. [ABSTRACT FROM AUTHOR]

Information is currently limited regarding the distribution of antibiotic resistance genes (ARGs) in smog and their correlations with airborne bacteria. This study characterized the diversity and abundance of ARGs in the particulate matters (PMs) of severe smog based on publicly available metagenomic data, and revealed the occurrence of 205 airborne ARG subtypes, including 31 dominant ones encoding resistance to 11 antibiotic types. Among the detectable ARGs, tetracycline, β-lactam and aminoglycoside resistance genes had the highest abundance, and smog and soil had similar composition characteristics of ARGs. During the smog event, the total abundance of airborne ARGs ranged from 4.90 to 38.07 ppm in PM 2.5 samples, and from 7.61 to 38.49 ppm in PM 10 samples, which were 1.6–7.7 times and 2.1–5.1 times of those in the non-smog day, respectively. The airborne ARGs showed complicated co-occurrence patterns, which were heavily influenced by the interaction of bacterial community, and physicochemical and meteorological factors. Lactobacillus and sulfonamide resistance gene sul 1 were determined as keystones in the co-occurrence network of microbial taxa and airborne ARGs. The results may help to understand the distribution patterns of ARGs in smog for the potential health risk evaluation. [ABSTRACT FROM AUTHOR]

To understand the diversity and abundance of antibiotic resistance genes (ARGs) in pharmaceutical wastewater treatment bioreactors, the ARGs in sludge from two full-scale pharmaceutical wastewater treatment plants (PWWTPs) were investigated and compared with sludge samples from three sewage treatment plants (STPs) using metagenomic approach. The results showed that the ARG abundances in PWWTP sludge ranged from 54.7 to 585.0 ppm, which were higher than those in STP sludge (27.2 to 86.4 ppm). Moreover, the diversity of ARGs in PWWTP aerobic sludge (153 subtypes) was higher than that in STP aerobic sludge (118 subtypes). In addition, it was found that the profiles of ARGs in PWWTP aerobic sludge were similar to those in STP aerobic sludge but different from those in PWWTP anaerobic sludge, suggesting that dissolve oxygen (DO) could be one of the important factors affecting the profiles of ARGs. In PWWTP aerobic sludge, aminoglycoside, sulfonamide and multidrug resistance genes were frequently detected. While, tetracycline, macrolide-lincosamide-streptogramin and polypeptide resistance genes were abundantly present in PWWTP anaerobic sludge. Furthermore, we investigated the microbial community and the correlation between microbial community and ARGs in PWWTP sludge. And, significant correlations between ARG types and seven bacterial genera were found. In addition, the mobile genetic elements (MGEs) were also examined and correlations between the ARGs and MGEs in PWWTP sludge were observed. Collectively, our results suggested that the microbial community and MGEs, which could be affected by DO, might be the main factors shaping the profiles of ARGs in PWWTP sludge. [ABSTRACT FROM AUTHOR]

Acylated homoserine lactone (AHL)-mediated quorum sensing (QS) is ecologically important in multi-species systems in laboratory-scale studies; however, little is known about QS in the biofilm formation process in full-scale wastewater treatment plants, which is driven by multiple environmental variables. Here, a model integrated fixed-film-activated sludge system was employed in full-scale municipal wastewater treatment plant to investigate the AHL distribution during the biofilm development process in response to variable environmental factors. The whole biofilm development process can be divided into three phases: initial biofilm attachment process (week 1 to 3), biofilm development and mature phase (week 4 to 6), and biofilm detachment and reformation process (week 7 to 17). N-decanoyl-DL-homoserine lactone (C10-HSL) and N-dodecanoyl-DL-homoserine lactone (C12-HSL) presented high concentrations during the biofilm formation process, which was closely related with the biofilm initial attachment process. The AHL concentration in biofilms was higher than in activated sludge. During the initial attachment process, tryptophan and protein-like substances related to biological substance were strongly positively correlated with all detected AHL concentrations (p < 0.05). Three environmental variables (total nitrogen, pH, and Na+) were closely related to AHL distribution in municipal wastewater biofilms. High wastewater pH was found to contribute to a low AHL concentration. AHLs in the biofilm were significantly (p < 0.01) influenced by the concentration of Na+, and higher concentrations of Na+ (10.84–18.58 mg/L) in wastewater treatment plants potentially contribute to the biofilm formation processes. In addition, bacteria with nitrogen removal ability showed QS functionality. The results of this study indicate that AHL-based regulation of tryptophan and protein-like substances related to biological substance production was significantly influenced by the surrounding chemical environment, which has been underestimated in previous studies. AHL-mediated QS potentially suggests a novel solution for the advanced AHL-based regulation of the biofilm development processes. Unlabelled Image • A model IFAS was employed in full-scale wastewater treatment plants. • Biofilms presented higher AHLs release ability than activated sludge. • C10-HSL and C12-HSL were key AHLs during biofilm development process. • TN, pH, and Na+ were closely related to biofilm AHL distribution in WWTP. [ABSTRACT FROM AUTHOR]

Abstract Progestagens discharged from municipal wastewater treatment plants (WWTPs) have increasingly gained attention due to their potential risks to the aquatic organisms. However, limited information is available on the occurrence and removal of various progestagens in WWTPs in different cities of China. This work investigated the occurrence and removal of 11 progestagens in 21 WWTPs from 19 Chinese cities. Results showed that progestagens are widely distributed in the investigated WWTPs, with higher influent concentrations of total progestagens in northern WWTPs. The concentration of progestagens in WWTP influent were closely correlated with influent quality, service population and daily service volume of the WWTPs. Additionally, progesterone (PGT) and dydrogesterone (DDT) were two predominant progestagens in influent, effluent and excess sludge. Up to 5 of 11 progestagens showed high aqueous removal efficiencies (median removal efficiency >90%), whereas megestrol acetate (MTA), chlormadinone acetate (CMA), drospirenone (DSP) and levonorgestrel (LNG) had a removal efficiency of below 50%. Specially, the behaviors of progestagens along the anaerobic-anoxic-oxic of a WWTP were further explored and the aerobic tank is the main contributor to the removal of progestagens. Finally, in the effluent of these 21 WWTPs, daily mass loadings of the total progestagens ranged from 0.51 to 10.4 g d−1. Notably, LNG exhibited high potential risk to the fish base on risk quotient. Graphical abstract Unlabelled Image Highlights • Contamination profiles of 11 progestagens in 21 WWTPs investigated. • Progesterone and dydrogesterone are the predominant progestagens in China's WWTPs. • Higher influent concentrations of total progestagens in northern WWTPs. • Many of the progestagens were eliminated in the aerobic tank. • Levonorgestrel in the effluent exhibited high risk to the fish. [ABSTRACT FROM AUTHOR]

The oxidation ditch (OD) is one of the most widely used processes for treating municipal wastewater. However, the microbial communities in the OD systems have not been well characterized, and little information about the shift of bacterial community during the startup process of the OD systems is available. In this study, we investigated the bacterial community changes during the startup period (over 100 days) of a full-scale OD. The results showed that the bacterial community dramatically changed during the startup period. Similar to the activated sludge samples in other studies, Proteobacteria (accounting for 26.3%-48.4%) was the most dominant bacterial phylum in the OD system, but its relative abundance declined nearly 40% during the startup process. It was also found that Planctomycetes proliferated greatly (from 4.79% to 13.5%) and finally replaced Bacteroidetes as the second abundant phylum in the OD system. Specifically, some bacteria affiliated with genus Flavobacterium exhibited remarkable decreasing trends, whereas bacterial species belonging to the OD1 candidate division and Saprospiraceae family were found to increase during the startup process. Despite of the bacterial community shift, the organic matter, nitrogen, and phosphorus in the effluent were always in low concentrations, suggesting the functional redundancy of the bacterial community. Moreover, by comparing with the bacterial community in other municipal wastewater treatment bioreactors, some potentially novel bacterial species were found to be present in the OD system. Collectively, this study improved our understandings of the bacterial community structure and microbial ecology during the startup of a full-scale wastewater treatment bioreactor.

Goldfish (Carassius auratus) were exposed to 0-100 μg/L pentachlorophenol (PCP) for 28 days to investigate the correlations of fish gut microbial community shift with the induced toxicological effects. PCP exposure caused accumulation of PCP in the fish intestinal tract in a time- and dose-dependent manner, while hepatic PCP reached the maximal level after a 21 day exposure. Under the relatively higher PCP stress, the fish body weight and liver weight were reduced and hepatic CAT and SOD activities were inhibited, demonstrating negative correlations with the PCP levels in liver and gut content (R < -0.5 and P < 0.05 each). Pyrosequencing of the 16S rRNA gene indicated that PCP exposure increased the abundance of Bacteroidetes in the fish gut. Within the Bacteroidetes phylum, the Bacteroides genus had the highest abundance, which was significantly correlated with PCP exposure dosage and duration (R > 0.5 and P < 0.05 each). Bioinformatic analysis revealed that Bacteroides showed quantitatively negative correlations with Chryseobacterium, Microbacterium, Arthrobacter, and Legionella in the fish gut, and the Bacteroidetes abundance, Bacteroides abundance, and Firmicutes/Bacteroidetes ratio played crucial roles in the reduction of body weight and liver weight under PCP stress. The results may extend our knowledge regarding the roles of gut microbiota in ecotoxicology.

Disinfection byproducts (DBPs) in drinking water have been linked to various diseases, including colon, colorectal, rectal, and bladder cancer. Trichloroacetamide (TCAcAm) is an emerging nitrogenous DBP, and our previous study found that TCAcAm could induce some changes associated with host-gut microbiota co-metabolism. In this study, we used an integrated approach combining metagenomics, based on high-throughput sequencing, and metabolomics, based on nuclear magnetic resonance (NMR), to evaluate the toxic effects of TCAcAm exposure on the gut microbiome and urine metabolome. High-throughput sequencing revealed that the gut microbiome's composition and function were significantly altered after TCAcAm exposure for 90 days in Mus musculus mice. In addition, metabolomic analysis showed that a number of gut microbiota-related metabolites were dramatically perturbed in the urine of the mice. These results may provide novel insight into evaluating the health risk of environmental pollutants as well as revealing the potential mechanism of TCAcAm's toxic effects.

This study investigated the occurrence and abundance of class 1 integrons and related antibiotic resistance genes (ARGs) in a sewage treatment plant (STP) of China. Totally, 189 bacterial strains were isolated from influent, activated sludge and effluent, and 40 isolates contained the integons with a complete structure. The intl1-carrying isolates were found to harbor two types of gene cassettes: dfr17-aadA5 and aadA2, conferring resistances to trimethoprim and streptomycin, which were further confirmed by antimicrobial susceptibility analysis. Many other gene cassettes were carried on integron, including qnrVC1, catB-8-blaoxa-10-aadA1-aac(6'), aadB-aacA29b, aadA2, aac(6')-1b, aadA6 and aadA12, which were detected using DNA cloning. Quantitative real time PCR showed that over 99% of the integrons was eliminated in activated sludge process, but average copy number of integrons in given bacterial cells was increased by 56% in treated sewage. Besides integrons, other mobile gene elements (MGEs) were present in the STP with high abundance. MGEs and the associated ARGs may be wide-spread in STPs, which constitute a potential hot spot for selection of antibiotic resistant bacteria and horizontal transfer of ARGs.