BackgroundDengue is a serious vector-borne disease, and incidence rates have significantly increased during the past few years, particularly in 2014 in Guangzhou. The current situation is more complicated, due to various factors such as climate warming, urbanization, population increase, and human mobility. The purpose of this study is to detect dengue transmission patterns and identify the disease dispersion dynamics in Guangzhou, China.MethodologyWe conducted surveys in 12 districts of Guangzhou, and collected daily data of Breteau index (BI) and reported cases between September and November 2014 from the public health authority reports. Based on the available data and the Ross-Macdonald theory, we propose a dengue transmission model that systematically integrates entomologic, demographic, and environmental information. In this model, we use (1) BI data and geographic variables to evaluate the spatial heterogeneities of Aedes mosquitoes, (2) a radiation model to simulate the daily mobility of humans, and (3) a Markov chain Monte Carlo (MCMC) method to estimate the model parameters.Results/ConclusionsBy implementing our proposed model, we can (1) estimate the incidence rates of dengue, and trace the infection time and locations, (2) assess risk factors and evaluate the infection threat in a city, and (3) evaluate the primary diffusion process in different districts. From the results, we can see that dengue infections exhibited a spatial and temporal variation during 2014 in Guangzhou. We find that urbanization, vector activities, and human behavior play significant roles in shaping the dengue outbreak and the patterns of its spread. This study offers useful information on dengue dynamics, which can help policy makers improve control and prevention measures.

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Integrated microwave photonics (MWP) is a fast growing area where high frequency microwave signals are processed in the optical domain, merging key advantages of both microwave photonics and photonic integrated circuits (PICs) technologies including low-loss, reconfigurability, advanced functionality, enhanced stability, and reduced footprint. Plenty of functionalities have been demonstrated in integrated MWP, especially based on spectral shaping technique, where the phase and amplitude of the optical spectrum is precisely tailored by PICs. However, on-chip linearization is lagging behind and has not been investigated deeply. It is crucial and urgent to study on-chip linearization methods, which will lead to advanced integrated MWP systems with large spurious-free dynamic range (SFDR). In this paper, we present two novel techniques for on-chip linearization of microwave photonic links. The first technique is based on line-by-line complex spectral shaping using a series of ring resonators. The second technique relies on spatial separation to achieve parallel spectral shaping in two complementary spatial channels. Both methods are demonstrated in low-loss programmable silicon nitride circuits that can already host a number of advanced functionalities. Our results point to the great potential of integrating advanced functionalities and linearization in the same integrated platform.

BackgroundGeographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China.MethodsA space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences.ResultsSince there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences.ConclusionsAlthough this study focuses mainly on the transmission of P. vivax, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.

In X‐ray imaging, anti‐scatter grids are used to reduce scatter radiation reaching image receptors, hence improving image quality. Optimization of grid performance is essential for improving image diagnostic quality and minimizing radiation doses to patients. This work investigated the performance of a series of grid designs modeled from the design of typically focused grid with grid ratio 8:1 (r8) and strip height 1.7 mm (h1.7) for high‐energy radiographic applications. Monte Carlo simulation was used to evaluate designs (r8h1.7) which had the strip thickness changed from 6 to 150 μm in 2 μm increments and the interspace distance fixed at 214 μm. The transmissions of radiation in grid materials were modeled by using a regression with radial‐basis‐function‐networks (RBFNS). KSNR was then determined from RBFNS models of radiation transmissions. The optimal strip‐thickness was obtained at the maximum signal‐to‐noise ratio (SNR) improvement factor (KSNR). For high‐energy applications at 100 peak‐kilo‐voltage (kVp) and 30 cm PMMA thickness, the optimal lead‐strip‐thickness was found approximately 74 μm resulting in a strip‐frequency approximately 35 per cm (N35). Using the optimal thickness for imaging condition at 100 kVp and 30 cm thickness, the KSNR would increase by approximately 5.3%. This work showed the existence of optimal strip‐thickness for a series of grids with a given grid‐ratio, strip‐height, strip‐, and interspace materials. The findings are useful and provide guidance to improve grid designs for better performance that will essentially lead to better image quality and better radiation protection for patients.

An on-chip linearization method for phase modulated microwave photonic link based on integrated ring resonators is proposed. By properly tailoring the phase and amplitude of optical carrier band and second-order sidebands, the third-order intermodulation distortion (IMD3) components can be suppressed. Theoretical analysis are taken and a proof-of-concept experiment is carried out. Experimental results demonstrate that IMD3 is suppressed by 21.7 dB. When the noise of the link is properly optimized, an SFDR of 112.7 dB·Hz2/3 can be achieved. This opens the possibility of integrating linearization into a functional photonic integrated circuit.

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Microwave photonics has adopted a number of important concepts and technologies over the recent pasts, including photonic integration, versatile programmability, and techniques for enhancing key radio frequency performance metrics such as the noise figure and the dynamic range. However, to date, these aspects have not been achieved simultaneously in a single circuit. Here, we report a multi-functional photonic integrated circuit that enables programmable filtering functions with record-high performance. We demonstrate reconfigurable filter functions with record-low noise figure and a RF notch filter with ultra-high dynamic range. We achieve this unique feature using versatile complex spectrum tailoring enabled by an all integrated modulation transformer and a double injection ring resonator as a multi-function optical filtering component. Our work breaks the conventional and fragmented approach of integration, functionality and performance that currently prevents the adoption of integrated MWP systems in real applications.