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In this study, a capillary microfluidic device was constructed, and sodium alginate solution and a pH-sensitive hydrophobic polymer (p(BMA-co-DAMA-co-MMA)) solution were introduced into the device for the preparation of hydrogel fibers loaded with polymer microspheres. The structure of the microsphere fiber, including the size and spacing of the microspheres, could be controlled by flow rate, and the microspheres were able to degrade and release cargo responding to acidic pH conditions. By modification with carboxymethylcellulose (CMC), alginate hydrogel exhibited enhanced pH sensitivity (shrunk in acidic while swollen in basic condition). This led to an impact on the diffusion rate of the molecules released from the inner microspheres. The microsphere fiber showed dramatic and negligible degradation and drug release in tumor cell (i.e., A431 and A549 cells) and normal cell environments, respectively. These results indicated that the microsphere fiber prepared in this study showed selective drug release in acidic environments, such as tumor and inflammation sites, which could be applied as a smart surgical dressing with normal tissue protective properties. [ABSTRACT FROM AUTHOR]

A fast evacuation from buildings to emergency shelters is necessary and important after the occurrence of a disaster. We investigated the variations in physical behaviors and cognition processes while finding emergency shelter. The on-site emergency-shelter-finding experiments were conducted in Beijing, China. Participants performed the task by using a wearable eye-tracking device. We aimed to assess three eye metrics: fixation counts, mean fixation duration, and visual attention index, to perform cognitive searching analysis for the environmental elements. The results showed that most people spend more fixation time on digital maps (297.77 ± 195.90 ms) and road conditions (239.43 ± 114.91 ms) than signs (150.90 ± 81.70 ms), buildings (153.44 ± 41.15 ms), and plants (170.11 ± 47.60 ms). Furthermore, most participants exhibit hesitation and retracing behaviors throughout the wayfinding process. The participants with relatively rich disaster experience and a proactive personality exhibit better performance in the shelter-finding task, such as a shorter retracing distance (p = 0.007) and nearer destination (p = 0.037). Eye metrics, together with the questionnaire, can mirror the complexity and heterogeneity of evacuation behavior during emergency shelter-finding. In addition, this also provides insights for the optimization of guidance sign systems and improvements in emergency management. [ABSTRACT FROM AUTHOR]

The number of building occupants is an important indicator for predicting building energy consumption and developing control strategies for building automation. However, most occupancy estimation models were developed depending on the training steps where the true number of occupants is necessary. In order to calculate the occupant number independently, the newly-developed parameter estimation models were proposed, which are based on Maximum Likelihood (ML) approach and Bayesian analysis. A combination of multiple common measurements is used, including real-time CO2 concentration, energy consumption of facilities and make-up air system. The model starts by smoothing the raw CO2 concentration data using moving average, two-hour median as well as globally smooth. Then, ML and Bayesian analysis are used to establish the occupancy estimation models. The proposed models are evaluated in a commercial office which contains 36 occupants for validation. We find that the calculation errors could be reduced by using moving averaged data and globally smoothed data. The superiority of the parameter estimation models can be identified based on its lower calculation error and higher calculation accuracy compared to the previous established models. Practical Application: Occupancy estimation models developed in this study are able to calculate occupant numbers independently and accurately in a non-intrusive way based on the indoor carbon dioxide concentration. This can provide input to a predictive building controller based on the application of occupancy estimation models. This could be applied to buildings across a district, informing demand-side management systems by employing occupancy behaviour and energy characteristics of individual buildings. This could allow both utility companies and building operators to simultaneously optimise their performance and benefit from this dedicated control strategy. [ABSTRACT FROM AUTHOR]

Converting CO2 into valuable solar fuels through photocatalysis has been considered a green and sustainable technology that is promising for alleviating global warming and providing energy in an environmentally friendly manner. However, traditional photocatalysts generally suffer from low surface-reactive reaction sites, inefficient light harvesting and rapid recombination of electron–hole pairs. Lead halide perovskite materials have been considered ideal semiconductor photocatalysts for photocatalytic CO2 reduction due to their tunable band gaps, strong light absorption, and low cost. Herein, a series of L2Csn−1PbnX3n+1 (L = ba, ha, oa; X = Cl, Br, I; n = 1, 2) 2D layered perovskites were synthesized by a facile solvothermal method. The effects of alkyl amine chain length, halogen atoms and inorganic layer number on their properties were studied. More importantly, these 2D materials were used as photocatalysts for CO2 reduction without any sacrificial agents. These 2D perovskites exhibited markedly increased performance in comparison with 3D bulk materials, benefitting from the larger surface-area-to-volume ratio and faster and more efficient exciton dissociation, which achieved the highest CO yield of 158.69 μmol g−1 h−1 and CH4 yield of 6.9 μmol g−1 h−1 through the design of the photocatalytic system. In addition, the influence of light source conditions on photocatalysis was studied systematically, including light source intensity and wavelength. The experimental results indicated that an appropriate solvent, high light intensity and monochromatic light source matching the wavelength of exciton absorption can effectively improve the photocatalytic efficiency. [ABSTRACT FROM AUTHOR]

In building performance simulation, occupant behavior contributes to large uncertainties, which often lead to considerable discrepancies between actual energy consumption and simulation results. This paper aims to extract occupant-behavior related electricity load patterns using classical K-means clustering approach at the initial investigation stage. Smart-metering data from a case study in Shanghai, China, was used for the load pattern analysis. The electricity load patterns of occupants were examined on a daily/weekly/seasonal basis. According to their load patterns, occupants were categorized as (a) white-collar workers, (b) poor or older families and (c) rich or young families. The daily patterns indicated that electricity use was much more random and fluctuated over a wide range. Most households of the monitored communities consumed relatively-low electricity; the characteristic double peak with higher level of consumption in the morning and evening were only apparent in a relatively small subset of residents (mostly white-collar workers). The weekly analysis found that significant load shifting towards weekend days occurred in the poor or old family group. The electricity saving potential was greatest in the white-collar workers and the rich or young family groups. This study concludes with recommendations to stakeholders utilizing our load profiling results. The research provides a rare insight into the electricity-use-related occupant behaviors of Shanghai residents through the case study of two communities. The findings of the study are also presented in a meaningful way so that they can directly aid the decision-making of governments and other stakeholders interested in energy efficiency. The research results are also relevant to the building energy simulation community as they are derived from observations, and thus can have the potential to improve the efficiency and accuracy of numerical simulation results. [ABSTRACT FROM AUTHOR]