This paper presents the development of a system which supports teacher to manage his/her students' studying information including records of attendance for every student and their examination results. For teacher, in order to grasp every student's studying situation, calling the roll is an old but important means to help achieve the purpose. In our system teacher's activity of calling the roll is strongly supported by adding some multimedia data such as student's face photo to be shown in the process of calling the roll. The system manages attendance data up to now and shows statistics compiled from the data to teacher's window when a new calling the roll is under execution. The digitized records of student's attendance can be easily and rapidly shared with the college administration office and related teachers and then timely measures can be taken to deal with the student's studying troubles.
Abstract Exploration of efficient and stable photocatalysts to mimic natural leaves for the conversion of atmospheric CO 2 into hydrocarbons utilizing solar light is very important but remains a major challenge. Herein, we report the design of four novel metal–salen‐incorporated conjugated microporous polymers as robust artificial leaves for photoreduction of atmospheric CO 2 with gaseous water. Owing to the rich nitrogen and oxygen moieties in the polymeric frameworks, they show a maximum CO 2 adsorption capacity of 46.1 cm 3 g −1 and adsorption selectivity for CO 2 /N 2 of up to 82 at 273 K. Under air atmosphere and simulated solar light (100 mW cm −2 ), TEPT‐Zn shows an excellent CO yield of 304.96 μmol h −1 g −1 with a selectivity of approximately 100%, which represents one of the best results in terms of organic photocatalysts for gas‐phase CO 2 photoreduction so far. Furthermore, only small degradation in the CO yield is observed even after 120‐h continuous illumination. More importantly, a good CO yield of 152.52 μmol g −1 was achieved by directly exposing the photocatalytic reaction of TEPT‐Zn in an outdoor environment for 3 h (25–28°C, 52.3 ± 7.9 mW cm −2 ). This work provides an avenue for the continued development of advanced polymers toward gas‐phase photoconversion of CO 2 from air.
With increasing attention to urban temperature and outdoor thermal comfort, monitoring urban microenvironments at a lower cost is an effective method to supplement the spatiotemporal deficiencies of traditional monitoring networks. But widespread use of low-cost sensors has been hampered by uncertainty about their data quality. The calibration of low-cost sensors is key to promoting their large-scale application and increasing people's confidence in related research. The purpose of this study is to calibrate low-cost integrated environmental sensors and effectively improve their hourly data quality based on an IoT case study in Wuhan, China. Based on the standards of 24 traditional weather stations in different locations of the meteorological regulatory authorities, this study applied a total of eight machine learning (ML) algorithms to calibrate low-cost sensors and compared their performance. The eight ML algorithms are: (a) Multiple Linear Regression (MLR); (b) Random Forest (RF); (c) K-Nearest Neighbors (KNN); (d) Gradient Boosting Regression Tree (GBRT); (e) Decision Tree (DT); (f) AdaBoost; (g) Bagging; (h) Extremely randomized Trees (Extra-Trees). Hourly raw data collected by 34 low-cost sensors deployed near traditional weather stations were calibrated, and the model was tested using ten-fold cross-validation. The two farthest locations are 121km apart in a straight line, and the maximum data collected from a single sensor is 12,406 hours. In addition, the model migration effects in different field scenarios were also considered, including six typical land surface types, namely built area, scrub, water, artificial surfaces, woodland, and cultivated land. The results show that the random forest model shows better performance than other models on multiple low-cost sensors at different locations. By applying our method, it shows an average improvement with its R-squared value from 0.682 to 0.980, Root Mean Square Error (RMSE) from 5.989 to 1.355, and Mean Absolute Error (MAE) from 4.250 to 0.932. The random forest model has a better migration effect in similar scenarios. Using a model with a surface type that is more similar to the sensor to be calibrated, the average R-squared obtained by calibrating 34 sensors is 0.946, and the average MAE is 1.584. At the same time, the distance between the sensor to be calibrated and the best-performing migration model was also considered, with the farthest straight-line distance being 94km and the nearest being 7km. This study introduces a calibration method for low-cost meteorological integrated sensors for long-term complex field environment monitoring. Moreover, we compared the migration effect of the random forest model in different typical scenes in the field. Similar surface types are more beneficial to model migration. Even in locations far apart, our model still has stable performance. The results show that this method can significantly improve data quality and increase user confidence in low-cost environmental sensor applications.
Photodegrading toxic organic pollutants in effluents over semiconductor photocatalysts is friendly and promising. The key is to develop a universally powerful and stable photocatalyst. In this work, highly efficient AgIO3@X heterojunction photocatalysts, composed of AgI and AgIO3 two phases, are fabricated via a facile in situ reduction method. AgIO3 is reduced and then AgI is generated on the surface of AgIO3, so the interfacial interaction between AgI and AgIO3 is very intimate. Introduction of AgI on the surface of AgIO3 extends the photoabsorption from an ultraviolet region to a visible region and also greatly improves charge transfer, giving rise to the remarkedly enhanced photocatalysis activity under visible-light excitation over AgIO3@X samples relative to the pristine AgIO3. The methyl orange (MO) photodegradation rate constant of the optimal AgIO3@20% photocatalyst reaches 0.175 min–1 under visible-light illumination (λ > 420 nm), about 86.5-fold enhanced compared with the pristine counterpart, outperforming most of previously reported state-of-the-art photocatalysts. Particularly, after 20 min of natural sunlight irradiation with a light intensity of 13.8 mW/cm2, the AgIO3@20% sample can rapidly decompose 81.1% of MO. The as-obtained composite photocatalysts also exhibit excellent photocatalytic activity against rhodamine B (RhB) and 2,4-dichlorophenol (2,4-DCP) under the illumination of visible light. The possible reaction pathways and the MO degradation mechanism have been systematically investigated and illustrated. The study paves a new way for designing and developing efficient visible-light-driven photocatalysts with an intimate interfacial interaction.
Abstract In this work, a simple but efficient strategy is proposed to boost the H 2 production activities of polyfluorene polyelectrolyte (PFN‐Br) through doping an anionic polyelectrolyte based on Förster resonance energy transfer strategy for the first time. In this artificial photosystem, cationic PFN‐Br is used as the energy donor and a 3,4‐dithia‐7 H ‐cyclopenta[ a ]pentalene‐based polyelectrolyte (PCP‐2F‐Li) is employed as the energy acceptor. The photoexcited fluorescence of PFN‐Br is completely quenched when the energy donor/acceptor ratio of [PFN‐Br]/[PCP‐2F‐Li] = 10:1. Moreover, the addition of a low concentration of PCP‐2F‐Li enables greater charge transport rate of polyelectrolyte blends than that of PFN‐Br. As a result, compared to single PFN‐Br (549 µmol h −1 g −1 ) and PCP‐2F‐Li (125 µmol h −1 g −1 ), the polyelectrolyte blends show a significantly higher H 2 evolution rate of 1346 µmol h −1 g −1 , which is mainly ascribed to the reduced energy loss through fluorescence and increased photoinduced charge transport during the photocatalytic process. This work highlights the rational construction of binary polymer blends as efficient method to increase photocatalytic activity of conjugated polyelectrolytes and this also provides a new opportunity for the design of multicomponent polyelectrolyte based photocatalysts.
Heterojunction fabrication and noble metal deposition serving as efficacious means for promoting photocatalytic activity attract huge interests. Here, a series of ternary Ag/AgBr/BiOIO3 composite photocatalysts that integrate the above two aspects are prepared by in situ crystallization of Ag/AgBr on BiOIO3. The photocatalytic performance is first investigated by degrading MO with visible light and UV light irradiation. The results indicate that Ag/AgBr/BiOIO3 composites present strengthened photocatalytic activity compared with BiOIO3 and Ag/AgBr under both light sources. Distinct activity enhancement levels corresponding to different mechanisms with UV and visible light illumination are uncovered, which are closely related to the applied light source. The universal catalytic activity of Ag/AgBr/BiOIO3 is surveyed by decomposition of diverse antibiotics and phenols, including tetracycline hydrochloride, chlortetracycline hydrochloride, bisphenol A, phenol, and 2,4-dichlorophenol which discloses that this ternary heterojunction photocatalyst demonstrates unselective catalytic activity with universality. Importantly, Ag/AgBr/BiOIO3 displays a strong mineralization ability, completely decomposing BPA into CO2 and H2O. This work affords a new reference for designing heterojunction photocatalyst with multiple advantageous effect and powerful capability for environmental purification.
Hydrogen represents an ideal fuel with environmental‐friendly properties and high energy density. It is attractive to directly produce clean hydrogen from inexhaustible solar energy and the most abundant seawater on the earth. Nevertheless, the search for highly efficient and stable photocatalysts remains a big challenge so far because of the dissolved salts in natural seawater, which may result in the decomposition of photocatalysts and undesirable side reactions. Herein, three polyfluorene‐based conjugated polyelectrolytes (CPEs) with different grafted groups in the polymer backbone for hydrogen production in natural seawater under solar light illumination are reported. The change in the grafted groups on the main chain of CPEs provides them very similar UV light absorption, but PFNH‐Br grafted with H group exhibits significantly improved charge transport and lower emission intensity compared with PFN‐Br (grafted with C 8 H 17 ) and PFPABr (grafted with CH 2 CH 2 N(CH 3 ) 3 Br). As a result, PFNH‐Br yield the highest hydrogen evolution rate (HER) of 1806 μmol h −1 g −1 without external cocatalysts under simulated solar light, while lower HERs of 356 and 225 μmol h −1 g −1 are found for PFN‐Br and PFPABr, respectively. This study shows that grafted group optimization is a powerful strategy to maximize the activity of polyfluorene‐based CPEs for direct photocatalytic seawater splitting.
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