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1.
Thin Solid Films ; 774, 2023.
Article in English | Web of Science | ID: covidwho-20236292

ABSTRACT

Herein, refined LaxCa0.89-xSr0.11MnO3 (LCSMO, x = 0.65, 0.68, 0.71 and 0.74) films were prepared through the sol-gel spin-coating. The influence of La3+ content on the structural properties of LCSMO films was investigated by X-ray diffraction and Atomic force microscope, demonstrating that LCSMO films can grow well on SrTiO3 (00l) substrate. Besides, X-ray photoemission spectroscopy verified the double exchange (DE) effect was weakened with La3+ dopant. The La3+ doping and interconnected grains boundaries (GBs) led to the weakening DE effect and GBs scattering, respectively. Due to superior GBs connectivity, the resistivity of LCSMO films was less than 7.1 x 10(-4) Omega.cm at low temperature of 100 K. Importantly, it is an effective control method to keep the temperature (T-k) corresponding to temperature coefficient of resistivity (TCR) at room temperature with Sr2+ content as constant in LCSMO films. At x = 0.71, the peak TCR value was found to be 8.84%/K and corresponding T-k was 283.15 K. These results are beneficial for advanced application of uncooling infrared bolometer.

2.
PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY (IOTBDS) ; : 103-111, 2021.
Article in English | Web of Science | ID: covidwho-1939303

ABSTRACT

The COVID-19 pandemic is highly infectious and has caused many deaths. The COVID-19 infection diagnosis based on blood test is facing the problems of long waiting time for results and shortage of medical staff. Although several machine learning methods have been proposed to address this issue, the research of COVID-19 prediction based on deep learning is still in its preliminary stage. In this paper, we propose four hybrid deep learning models, namely CNN+GRU, CNN+Bi-RNN, CNN+Bi-LSTM and CNN+Bi-GRU, and apply them to the blood test data from Israelta Albert Einstein Hospital. We implement the four proposed models as well as other existing models CNN, CNN+LSTM, and compare them in terms of accuracy, precision, recall, F1-score and AUC. The experiment results show that CNN+Bi-GRU achieves the best performance in terms of all the five metrics (accuracy of 0.9415, F1-score of 0.9417, precision of 0.9417, recall of 0.9417, and AUC of 0.91).

3.
Journal of Building Engineering ; 45:11, 2022.
Article in English | Web of Science | ID: covidwho-1517355

ABSTRACT

According to the discussion of the design method and operational effect for Wuhan Huoshenshan Hospital, this paper summarized the design control points of indoor and outdoor environment of COVID-19 emergency hospital. Based on the design of Wuhan Huoshenshan Hospital, this paper analyzed and discussed the site design, building layout, three-zones and two-passages, the design scheme of the ventilation and air conditioning system for negative pressure ward and negative pressure isolation ward, air distribution, as well as some other key designs for COVID-19 emergency hospital. The design points were summarized and refined. The design methods and technology requirements of the COVID-19 emergency hospital were provided in this study, such as ventilation and air conditioning system setting, ventilation quantity of wards, pressure gradient control measures among different areas, upper and lower air distribution, filter setting mode and distance of air inlet and outlet, which could benefit to provide references for the design of similar projects in the future.

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