Population is one of the core elements of sustainable development. Quantifying the estimation accuracy of population spatial distribution has been recognized as a critical and challenging task. This study aims to evaluate the data accuracy of four population datasets in China, including three global gridded population datasets, the Gridded Population of the World (GPW), Global Rural and Urban Mapping Project (GRUMP), and WorldPop project (WorldPop), and a Chinese regional gridded population dataset, the China 1 km Gridded Population (CnPop) dataset. These datasets are assessed using a specific method based on a GIS-linked 2000 census dataset at the township level in China. The results indicate that WorldPop had the highest estimation accuracy, estimating about 60% of the total population. CnPop accurately estimated about half of the total population, showing a good mapping performance. The GPW had an acceptable estimation accuracy in a few plain and basin areas, accounting for about 30% of the total population. Compared to the GPW, GRUMP accurately estimated about 40% of the total population. The relative estimation error analysis discovered the disadvantages of the generation strategies of these datasets. The conclusions are expected to serve as a quality reference for potential dataset users and producers, and promote accuracy assessment for population datasets in other regions and globally.

Metasurfaces emerge as a promising photonic platform for biosensing because they offer strong optical confinement and tunable optical resonances. Here, we show that metasurface-based biosensors consisting of gold nanoantenna arrays loaded with graphene and working in the midinfrared (mid-IR) spectral range can achieve simultaneous high-sensitivity and high-specificity detection of biomolecules. Strong light−molecule interactions in deeply subwavelength optical spots created by the biosensors allow us to determine the concentration of protein molecules via spectral shifts of the metasurface resonance. A combination of passive and active tuning of the metasurface sensors allows us to spectrally overlap the metasurface resonance and the protein vibrational modes, so that protein molecules can be identified via their characteristic mid-IR "fingerprints". The high sensitivity and specificity of the metasurface sensors enable us to determine the secondary structure of protein immunoglobulin (IgG) molecules 4 orders of magnitude more sensitive than attenuated total reflection Fourier transform infrared spectroscopy.

A logistic model was employed to correlate the outbreak of highly pathogenic avian influenza (HPAI) with related environmental factors and the migration of birds. Based on MODIS data of the normalized difference vegetation index, environmental factors were considered in generating a probability map with the aid of logistic regression. A Bayesian maximum entropy model was employed to explore the spatial and temporal correlations of HPAI incidence. The results show that proximity to water bodies and national highways was statistically relevant to the occurrence of HPAI. Migratory birds, mainly waterfowl, were important infection sources in HPAI transmission. In addition, the HPAI outbreaks had high spatiotemporal autocorrelation. This epidemic spatial range fluctuated 45 km owing to different distribution patterns of cities and water bodies. Furthermore, two outbreaks were likely to occur with a period of 22 d. The potential risk of occurrence of HPAI in Mainland China for the period from January 23 to February 17, 2004 was simulated based on these findings, providing a useful meta-model framework for the application of environmental factors in the prediction of HPAI risk.highly pathogenic avian influenza, meta-modeling, remote sensing, geographical information system, Bayesian maximum entropy, logistic regression, spatiotemporal autocorrelation Citation:Cao C X, Xu M, Chang C Y, et al. Risk analysis for the highly pathogenic avian influenza in Mainland China using meta-modeling.

Due to the rapid melting and solidification mechanisms involved in selective laser melting (SLM), CoCrMo alloys fabricated by SLM differ from the cast form of the same alloy. In this study, the relationship between process parameters and the morphology and macromechanical properties of cobalt-chromium alloy micro-melting pools is discussed. By measuring the width and depth of the molten pool, a theoretical model of the molten pool is established, and the relationship between the laser power, the scanning speed, the scanning line spacing, and the morphology of the molten pool is determined. At the same time, this study discusses the relationship between laser energy and molding rate. Based on the above research, the optimal process for the laser melting of cobalt-chromium alloy in the selected area is obtained. These results will contribute to the development of biomedical CoCr alloys manufactured by SLM.

The generation of high-density plasmas on the surface of porous catalysts is very important for plasma catalysis, as it determines the active surface of the catalyst that is available for the reaction. In this work, we investigate the mechanism of surface and volume plasma streamer formation and propagation near micro-sized pores in dielectric barrier discharges operating in air at atmospheric pressure. A two-dimensional particle-in-cell/Monte Carlo collision model is used to model the individual kinetic behavior of plasma species. Our calculations indicate that the surface discharge is enhanced on the surface of the catalyst pores compared with the microdischarge inside the catalyst pores. The reason is that the surface ionization wave induces surface charging along the catalyst pore sidewalls, leading to a strong electric field along the pore sidewalls, which in turn further enhances the surface discharge. Therefore, highly concentrated reactive species occur on the surfaces of the catalyst pores, indicating high-density plasmas on the surface of porous catalysts. Indeed, the maximum electron impact excitation and ionization rates occur on the pore surface, indicating the more pronounced production of excited state and electron-ion pairs on the pore surface than inside the pore, which may profoundly affect the plasma catalytic process.

Abstract:We investigated the mode transition from volume to surface discharge in a packed bed dielectric barrier discharge reactor by a two-dimensional particle-in-cell/Monte Carlo collision method. The calculations are performed at atmospheric pressure for various driving voltages and for gas mixtures with different N 2 and O 2 compositions. Our results reveal that both a change of the driving voltage and gas mixture can induce mode transition. Upon increasing voltage, a mode transition from hybrid (volume+surface) discharge to pure surface discharge occurs, because the charged species can escape much more easily to the beads and charge the bead surface due to the strong electric field at high driving voltage. This significant surface charging will further enhance the tangential component of the electric field along the dielectric bead surface, yielding surface ionization waves (SIWs). The SIWs will give rise to a high concentration of reactive species on the surface, and thus possibly enhance the surface activity of the beads, which might be of interest for plasma catalysis. Indeed, electron impact excitation and ionization mainly take place near the bead surface. In addition, the propagation speed of SIWs becomes faster with increasing N 2 content in the gas mixture, and slower with increasing O 2 content, due to the loss of electrons by attachment to O 2 molecules. Indeed, the negative O − 2 ion density produced by electron impact attachment is much higher than the electron and positive O + 2 ion density. The different ionization rates between N 2 and O 2 gases will create different amounts of electrons and ions on the dielectric bead surface, which might also have effects in plasma catalysis.

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A novel influenza A (H1N1) has been spreading worldwide. Early studies implied that international air travels might be key cause of a severe potential pandemic without appropriate containments. In this study, early outbreaks in Mexico and some cities of United States were used to estimate the preliminary epidemic parameters by applying adjusted SEIR epidemiological model, indicating transmissibility infectivity of the virus. According to the findings, a new spatial allocation model totally based on the real-time airline data was established to assess the potential spreading of H1N1 from Mexico to the world. Our estimates find the basic reproductive number R0 of H1N1 is around 3.4, and the effective reproductive number fall sharply by effective containment strategies. The finding also implies Spain, Canada, France, Panama, Peru are the most possible country to be involved in severe endemic H1N1 spreading. H1N1 influenza A, airline transmission, early warning, basic reproductive number, containment strategiesCitation:Chang C Y, Cao C X, Wang Q, et al. The novel H1N1 Influenza A global airline transmission and early warning without travel containments.