PREVALENCE OF AVIAN CHLAMYDOPHILA PSITTACI IN CHINA

Abstract Examinations were carried out in 46 intensive farms in northern China to investigate avian Chlamydophila psittaci. Five hundred and twenty-five avian sera were selected for examining antibodies to C. psittaci by ELISA. One hundred and fifty-five clinical samples from throat swabs and oviduct tissues were tested for the presence of chlamydial antigen using IDEIA TM PCE chlamydia dual amplification immunoassay, and 60 samples were tested by ompA gene-based PCR. C. psittaci antibodies were detected in 387 (77.8%) out of 525 serum samples, with seroprevalences ranging from 50% to 100%. Among the tested samples, 98/150 (65.3%) in broilers, 173/210 (82.3%) in ducks, and 116/165 (70.3%) in laying hens were detected to be positive, respectively. Using PCE-ELISA test kits, in 91 out of 155 clinical samples the presence of antigen was confirmed, while 64 samples were negative. Forty-three PCR's were tested as positive out of 60 samples, while 17 samples were confirmed to be negative. Both higher positive antibodies and the presence of antigens were found in avian flocks associated with typical clinical signs suggestive of chlamydiosis. This study showed a severe prevalence of C. psittaci among different species of domestic birds in China

Rational design of high-performance continuous-flow microreactors based on gold nanoclusters and graphene for catalysis

In this work, we rationally designed a high-performance microreactor system for continuous-flow catalysis. The membrane consists of ultrasmall gold nanoclusters (AuNCs) and two-dimensional graphene. The Au cores of the NCs act as catalysts, while their ligands have two functions: (1) protecting the Au cores to avoid agglomeration and (2) providing a well-defined surfactant assembly to disperse graphene in aqueous solution. Hydrogenation of 4-nitrophenol (4-NP) was employed as model reaction to evaluate catalytic activity. The catalytic membrane microreactor demonstrated excellent catalytic activity and stability, where complete 4-NP conversion was readily achieved via a single pass through the membrane. This desirable performance was maintained over 12 h of continuous operation, although a certain amount of organic buildup on the membrane was observed. The catalytic membrane microreactor outperforms conventional batch reactors due to its improved mass transport. 4-NP-spiked real water samples were also completely converted. This study provides new insights for the rational design of membrane reactors for industrial applications

Correlating Chemical Reaction and Mass Transport in Hydrogen-based Direct Reduction of Iron Oxide

Steelmaking contributes 8% to the total CO2 emissions globally, primarily due to coal-based iron ore reduction. Clean hydrogen-based ironmaking has variable performance because the dominant gas-solid reduction mechanism is set by the defects and pores inside the mm-nm sized oxide particles that change significantly as the reaction progresses. While these governing dynamics are essential to establish continuous flow of iron and its ores through reactors, the direct link between agglomeration and chemistry is still contested due to missing measurements. In this work, we directly measure the connection between chemistry and agglomeration in the smallest iron oxides relevant to magnetite ores. Using synthesized spherical 10-nm magnetite particles reacting in H2, we resolve the formation and consumption of w\"ustite (FeO) - the step most commonly attributed to agglomeration. Using X-ray scattering and microscopy, we resolve crystallographic anisotropy in the rate of the initial reaction, which becomes isotropic as the material sinters. Complementing with imaging, we demonstrate how the particles self-assemble, subsequently react and sinter into ~100x oblong grains. Our insights into how morphologically uniform iron oxide particles react and agglomerate H2 reduction enable future size-dependent models to effectively describe the multiscale iron ore reduction

Performance Evaluation of Personalized Ventilation - Personalized Exhaust (PV-PE) System in Air-conditioned Healthcare Settings

Ph.DDOCTOR OF PHILOSOPH

Urban Heat Island and Mitigation Technologies in Asian and Australian Cities—Impact and Mitigation

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Importance of community containment measures in combating the COVID-19 epidemic: From the perspective of urban planning

To contain the outbreak of COVID-19 in Wuhan, unprecedented interventions, including city lockdown and community closure, have been implemented. However, most of the current studies focused on evaluation of the city lockdown, but paid limited attention to the impacts of the community containment measures within the city. This research addressed this important issue from the perspective of urban planning, based on the epidemic and remote sensing data of 194 communities of Wuhan. We found that the number of confirmed cases of communities is highly related to urban planning factors, e.g. area percentage of buildings and density of neighboring markets. These factors are relevant to the residents’ activity patterns, which therefore impact the mode of virus transmission. Our research confirmed the effectiveness of the community-oriented control strategies, provided a valuable reference for other cities that are suffering from the epidemic, and exhibited new thoughts into future urban planning

Model Development and Comparison for the Evaluation of the Energy Performance of Three Tertiary Institutional Buildings in Singapore

AbstractThis study presents an investigation and discussion on the energy performance of three tertiary institutional buildings in Singapore. Building information, energy consumption data of the air-conditioning system, and energy consumption data of the plug loads were collected separately. MATLAB identification models are developed to simulate the real daily energy consumption data:. Three functions are introduced to represent the function of daily occupancy, function of additional occupancy due to visitors and the function of outdoor air temperature. The results show that the predicted value follows the trend of real energy consumption value very well and can predict the daily variations. The newly developed methodology is able to simulate the daily variations of energy consumption. R2 of 0.54, 0.66 and 0.63 can be achieved for the three buildings respectivel

Forecasting Energy Consumption of Institutional Buildings in Singapore

This study presents building energy forecasting methodology for cooling load for three institutional buildings. These buildings belong to a university campus in Singapore. The daily energy consumption for cooling load is obtained for a period of two years and the daily variation is analysed. The energy consumption is initially divided into five classes and the class numbers are used as inputs to develop a forecasting model. The model is developed using two machine learning tools. The tools used are Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Interface System (ANFIS). The division of data for training and testing the model is nearly 60% and 40% respectively. The results show that both ANN and ANFIS forecast the cooling load energy consumption of the three buildings with good accuracy. The correlation coefficient between measured and predicted consumption for training data are well above 0.98. The same is well above 0.96 for testing data. It is noted that such a methodology can be positively extended to other institutional buildings in the campus. (C) The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of ISHVAC-COBEE 201