ObjectiveTo determine the prevalence of avian influenza viruses in the external environment of poultry in Anqing City， Anhui Province， and provide scientific evidence for prevention and control of animal-derived influenza in humans. MethodsA total of 28 farmers’ markets/farms in 10 counties （cities， districts） of Anqing City， Anhui Province， were selected as surveillance sites by simple random sampling strategy. Poultry faeces and other related samples were collected for 6 consecutive weeks. Real-time fluorescence quantitative PCR was used to examine the nucleic acids of influenza A virus. Subtypes H5， H7， and H9 of avian influenza virus were further tested in the positive samples. ResultsA total of 426 specimens were collected， among which 113 tested positive with a positive rate of 26.53%. Among the positive specimens， 104 were determined to be subtype H9， accounting for 92.04%. It did not significantly differ in the positive rate between the main and non-main urban areas （χ²<0.01， P>0.05） or among the specimens collected in different weeks （χ²=7.57， P>0.05）. However， it significantly differed in the positive rate among the specimens collected in the third week and other weeks （χ²=6.89， P<0.05）. Furthermore， among the different sampling sites， farms had the highest positive rate of 46.67%. Among the specimens from different sources， the surface-coated specimens from poultry cages had the highest positive rate of 34.78%. ConclusionAvian influenza viruses are prevalent in the external environment of poultry in Anqing City. It warrants strengthening the surveillance and risk assessment to reduce the virus transmission in the external environment and risk of human infection with animal-derived influenza.

Acute respiratory distress syndrome (ARDS) is a serious threat to human life and health disease, with acute onset and high mortality. The current diagnosis of the disease depends on blood gas analysis results, while calculating the oxygenation index. However, blood gas analysis is an invasive operation, and can't continuously monitor the development of the disease. In response to the above problems, in this study, we proposed a new algorithm for identifying the severity of ARDS disease. Based on a variety of non-invasive physiological parameters of patients, combined with feature selection techniques, this paper sorts the importance of various physiological parameters. The cross-validation technique was used to evaluate the identification performance. The classification results of four supervised learning algorithms using neural network, logistic regression, AdaBoost and Bagging were compared under different feature subsets. The optimal feature subset and classification algorithm are comprehensively selected by the sensitivity, specificity, accuracy and area under curve (AUC) of different algorithms under different feature subsets. We use four supervised learning algorithms to distinguish the severity of ARDS (P/F ≤ 300). The performance of the algorithm is evaluated according to AUC. When AdaBoost uses 20 features, AUC = 0.832 1, the accuracy is 74.82%, and the optimal AUC is obtained. The performance of the algorithm is evaluated according to the number of features. When using 2 features, Bagging has AUC = 0.819 4 and the accuracy is 73.01%. Compared with traditional methods, this method has the advantage of continuously monitoring the development of patients with ARDS and providing medical staff with auxiliary diagnosis suggestions.
Algorithms ; Area Under Curve ; Blood Gas Analysis ; Humans ; Machine Learning ; Monitoring, Physiologic ; methods ; ROC Curve ; Respiratory Distress Syndrome, Adult ; diagnosis ; Sensitivity and Specificity

Objective To design a temperature control strategy for riptide bioreactor to eliminate integral saturation by conventional proportion integration differentiation (PID) control.Methods According to the requirement of the riptide bioreactor for the temperature control,the temperature control system model determined by experiment was got,then the effectiveness of the integral limiter PID control method was verified,and finally the integral limiter PID control method wasimproved further using the integral separation combined with the actual experimental results and its effectiveness was tested.Results The simulation results showed that the control effects of the integral limiter PID was good.However,the actual tests proved that there was still deficiencies in large overshoot and long stable time,and good experimental results were obtainedafter improving the integral limiter PID by the integral separation method.Conclusion The improved integral limiter PID control method effectively avoids the overshoot of the system caused by the integral saturation,achieves high control precision,has a very good control performance for the temperature control of riptide bioreactor,and well meets the requirements of mammalian cell culture.

Objective To design a temperature control strategy for wave bioreactors.Methods According to the requirements of temperature control precision and response speed of wave bioreactors,the traditional PID control method was combined with fuzzy control method which was used to adjust the parameters of the PID control in real time online in order to strengthen the ability of the temperature control strategy to regulate temperature.Results A fuzzy PID controller was completed and simulation results were compared with the traditional PID controller.Conclusion The fuzzy PID control method has a smaller overshoot and shorter stability than the traditional one, so it has a higher temperature control performance.

Objective To explore the relationship between the spot size and the result of ploidy analysis in the detection technology based on single-particles, and to fix the scope of spot thickness on the basis of the experimental result.Methods The influence of spot thickness on voltage signals produced by single cells was analyzed.The parameters of the beam shap system in the incident field were designed and optimized on ZEMAX.Finally, according to the cells′diameter, the target size of spots was set.A set of spots of different thickness and of Gaussian distribution obtained from the optical experimental platform was used to conduct ploidy detection experiments.Results Target spots were both obtained from ZEMAX simulation and the optical platform.When the spot thickness was larger than both monocytes and coenocytes, the mean fluorescence intensity ratio was 2.03,which met the demand of the index.Conclusion When the height of the pulse is used to represent the fluorescence density, the relative size of spots and cells will affect the result of ploidy detection.Only when spot thickness is larger than cells is the ploidy ratio accurate.

Objective To design and develop an air purification system for intensive care ambulances,which can effectively purify the air in the compartment and sterilize the microbes in the air.Methods By integrating titanium dioxide photocatalysts with air filtration materials,an air purification system was designed that was capable of effective sterilization of microbes in the air via photocatalytic oxidation and decomposition,and of effective filtration of particles in the air through HEPA filters.The protection effect was evaluated by air filtration and sterilization tests in accordance with the related national standards.Results The air cleanliness could reach the 100 000 level with bacteria counts no more than 1 CFU per pan for 15 minutes in the ambulance compartment when the air purification system worked normally,which could meet the demands of environmental hygienic standards for intensive care units.Conclusion The air purification system can effectively purify and sterilize the air in the compartment of an intensive care ambulance.The effects of air purification meet the requirements of related hygienic standards,which can satisfy the demands of treatment and intensive care for the victims in the ambulance.

Objective To design a real-time oxygen generation and supply device for ambulances and to carry out finite element simulated analysis and performance evaluation .Methods Based on the working principles of pressure swing adsorption (PSA) and oxygen pneumatic compression technology ,the structural components and technological processes of an oxygen generation and compression unit as well as an oxygen filling and supply unit were built .The integrated structure of the device was designed by Solidworks .The static structure of the oxygen generation and compression unit was analyzed by ANSYS.Modal analysis of the circuit board was also conducted .The performance of the prototype was evaluated .Results Wtih a stable structure and reliable circuitry , the device could produce and fill oxygen automatically at the flow of 5.0 L/min, concentration of 94.0%, and pressure of 13.0 MPa.Conclusion This device can produce , fill and supply oxygen automatically,and the goal of design is achieved .

Objective To develop a BP neural network to differentiate between ventricular fibrillation( VF) and non-VF rhythms.Methods Eighteen metrics were extracted from the ECG signals.Each of these metrics respectively characterized each aspect of the signals, such as morphology, gaussianity, spectra, variability, and complexity.These metrics were regarded as the input vector of the BP neural network.After training, a classifier used for VF and non-VF rhythm classification was obtained.Results and Conclusion The constructed BP neural network was tested with the databases of VFDB and CUDB, and the accuracy was 98.61%and 95.37%, respectively.

Objective To study and design a fluid resuscitation control system which is suitable for the treatment of hemorrhagic shock in the battlefield and prehospital settings. Methods The physiological parameters of the wounded were set as the system input and fuzzy control technology was used to identify the hemorrhagic shock (HS) severity and made a decision. At last, fluid resuscitation was finished with the use of the efficient blood transfusion and infusion pump. Results High-speed resuscitation could be carried out when the wounded was in severe condition, while low-speed resuscitation could be conducted when the wound was in mild condition. Conclusions Compared with the traditional resuscitation method, the designed fluid resuscitation control system can improve the efficiency of fluid resuscitation and the treatment success rate.

Objective To develop an intelligent system which is able to offer an optimized emergency treatment recommendation for fast triage automatically.Methods An algorithm and intelligent platform for grading injury were developed based on physiological signal collecting technology, intelligent grading algorithm and integration technology.A comparison between this system and traditional methods was made.Results This intelligent system was able to increase accuracy by 21%and took only 48%of the time taken by traditional methods.There was significant difference between the two groups(P=0.038<0.05).Conclusion The accuracy of the triage is improved by this intelligent system that is less time-consuming.With this device, the injury statement can be identified quickly and the targeted medical treatment can be performed accurately.The efficiency of emergency treatment in case of disaster will thus be dramatically increased.