Traditional analytical algorithm needs to combine the transmission functions of grating and lens to generate a computer generated hologram (CGH), so as to realize the distribution of three-dimensional (3D) multi-focal points in space, but the grating phase will inevitably produce high-order diffraction focus, resulting in energy loss, and the traditional analytic algorithm is more suitable for generating array multi-focal distribution with equal spacing. To solve this problem, this paper simplifies the traditional analytical algorithm, and proposes a method that only uses multi-lens phase and random phase superposition to generate the CGH required by the target light location, by changing the focal length of the lens phase, the multi-focus distribution along the z-axial direction of multiple independent focal planes is realized. Then the phase of these different focal planes is superimposed, and a 0~2π random phase modulation is added, which can quickly generate 3D multi-focus distribution with controllable number and position. The simulation results show that the energy uniformity of focal spot on each focal plane is between 89.45% and 98.08%. The experimental results show that the energy uniformity of focal spots on each focal plane is between 88.40% and 96.13%, which is consistent with the simulation results. Compared with traditional analytical algorithm, the proposed method is more universal for multi-focus distribution in 3D space without special requirements of array distribution with equal spacing, and has potential application value in laser processing, holographic optical tweezers, optical communication and other fields.
Since December 2019, COVID-19 has become a public health emergency of international concern, from local area to the current worldwide pandemic. Since March this year, the epidemic in Chinese cities has been effectively controlled, and the number of newly confirmed local cases in many places has reached zero growth. However, it is worth noting that some Chinese cities represented by Beijing have undergone secondary local transmission of COVID-19. According to epidemiological and laboratory studies, meteorological factors are key factors affecting the spread of infectious diseases such as coronavirus and influenza, but the impact of meteorological factors on the spread of COVID-19 virus remains controversial. This study explored the correlation between daily meteorological data in Beijing and the increase in the number of COVID-19 cases, and compared three Chinese cities with similar conditions (Jilin, Dalian and Urumqi) to explore the role of meteorological factors in the spread of COVID-19 virus. Szpilman and Kendall correlation coefficients were used to study the correlation between COVID-19 and meteorological factors. The results showed that in the first round of COVID-19 transmission, meteorological factors were significantly correlated with the development of COVID-19 (p<0.01): temperature and wind speed were positively correlated with the increase in the number of cases, while air pressure and relative humidity were negatively correlated. In the second round of epidemic spread, the impact of meteorological factors was not significant. This study is of great significance for enhancing the understanding of the current situation of COVID-19 transmission and developing relevant prevention and control measures to prevent a second outbreak of COVID-19.
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