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Rational hospital human resource allocation planning is important to improve the efficiency of China’s health human resource allocation and reduce the losses caused by staff waste and shortage. In this paper, we take the medical and nursing configuration of a general tertiary hospital in X city as a guiding framework and use inductive and deductive methods to summarize the factors affecting medical and nursing staffing and the experience of management in the previous period. By proposing an adaptive algorithm based on learning rate for improving BP neural network with differentiated learning rate, the dynamic adjustment of weights between different nodes is achieved. Finally, through database design and module design, two functional modules of human resource management and human resource prediction are constructed. The results of the case validation show that the HR demand forecasting model has the best prediction effect for health technicians, and the relative errors are all less than 5%, with an average relative error of 1.23% and a minimum value of only 0.25%. The relative error between the predicted and actual values of the ARIMA (2, 2, 2) dataset for practicing (assistant) physicians is less than 0.005. It shows that the HR model constructed in this paper has a certain quantitative guidance value for the rational planning of human resource allocation for hospital positions.

The continual transmission of epidemics makes health workers aware of the importance of airborne transmission in special cases. The well-known equation Wells-Riley highlights the importance of ventilation to dilution of infectious aerosol as well. And the airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been confirmed. The main problem of the coronavirus disease 2019 (COVID-19) epidemic of three families in a restaurant in Guangzhou lies in unreasonable ventilation. An air-conditioning system of Ceiling radiant cooling plate (CRCP) combined with a dedicated outdoor air system (DOAS) has been proposed in this paper. The simulation of the diffusion of tiny exhaled droplets is carried out through SF6 tracer gas. A numerical simulation of the original indoor air distribution of the restaurant and that of the new air-conditioning system has been conducted. Pollutant concentrations of different indoor locations and exposure indexes under four working conditions of ventilation rates 3, 6, 9, and 12 ACH are calculated. The results suggest that the air supply mode of air conditioners put forward in this paper can decrease the risk of indoor infection to a large extent. When the ventilation rate is 1L/s, the probability of infection is very high. With the increase in ventilation times, the risk of infection gradually decreases. Offering suitable ventilation in crowded spaces can greatly prevent and control the air transmission of coronavirus.

Abstract Background The chemokine receptors CXCR4 and CCR7 play an important role in cancer invasion and metastasis. This study investigated the expression of CXCR4, CCR7, CXCL12, CCL21, and EGFR to illustrate the role of these biomarkers in breast cancer metastasis and prognosis. Methods The CXCR4, CCR7, CXCL12, CCL21, and EGFR biomarkers were analyzed along with ER, PR, and HER-2/neu in breast cancer tissue microarray (TMA) specimens, including 200 primary breast cancer specimens by immunohistochemistry. Corresponding lymph nodes from the same patients were also examined using the same method. Results Together with their CXCL12 and CCL21 ligands, CXCR4 and CCR7 were significantly highly expressed in tumor cells with lymph node (LN) metastasis. Similarly, EGFR was expressed highly in tumors with LN metastasis. The ligands were especially expressed in metastatic tumors than in primary tumors from the same patients. Moreover, the expression of both CXCR4 accompanied by CCR7 and CXCL12 accompanied by CCL21 were up-regulated. Kaplan-Meier survival analysis revealed that patients exhibiting high CXCR4, CCR7, and EGFR expression experienced a shorter survival period compared with those with low expression. Conclusions The expression of CXCR4, CCR7, and EGFR may be associated with LN metastasis. Moreover, the expression of these receptors can serve as an indicator of undesirable prognosis in patients with breast cancer.

By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time–domain Gaussian fitting method is proposed in this paper. The concept of a time–domain Gaussian curve is firstly put forward, and the procedure of determining projector coordinates with a time–domain Gaussian curve is illustrated in detail. The neural network technique is applied to rapidly compute peak positions of time-domain Gaussian curves. Relying on the computing power of the neural network, the proposed method can reduce the computing time greatly. The binary defocusing technique can be combined with the neural network, and fast 3D profilometry with a large depth of field is achieved. Moreover, because the time–domain Gaussian curve is extracted from individual image pixel, it will not deform according to a complex surface, so the proposed method is also suitable for measuring a complex surface. It is demonstrated by the experiment results that our proposed method can extends the system DoF by five times, and both the data acquisition time and computing time can be reduced to less than 35 ms. [ABSTRACT FROM AUTHOR]