SNR-based adaptive acquisition method for fast Fourier ptychographic microscopy

Fourier ptychographic microscopy (FPM) is a computational imaging technique with both high resolution and large field-of-view. However, the effective numerical aperture (NA) achievable with a typical LED panel is ambiguous and usually relies on the repeated tests of different illumination NAs. The imaging quality of each raw image usually depends on the visual assessments, which is subjective and inaccurate especially for those dark field images. Moreover, the acquisition process is really time-consuming.In this paper, we propose a SNR-based adaptive acquisition method for quantitative evaluation and adaptive collection of each raw image according to the signal-to-noise ration (SNR) value, to improve the FPM's acquisition efficiency and automatically obtain the maximum achievable NA, reducing the time of collection, storage and subsequent calculation. The widely used EPRY-FPM algorithm is applied without adding any algorithm complexity and computational burden. The performance has been demonstrated in both USAF targets and biological samples with different imaging sensors respectively, which have either Poisson or Gaussian noises model. Further combined with the sparse LEDs strategy, the number of collection images can be shorten to around 25 frames while the former needs 361 images, the reduction ratio can reach over 90%. This method will make FPM more practical and automatic, and can also be used in different configurations of FPM.Comment: 11 pages, 6 figure

The Sihailongwan Maar Lake, northeastern China as a candidate Global Boundary Stratotype Section and Point for the Anthropocene Series

Sihailongwan Maar Lake, located in Northeast China, is a candidate Global boundary Stratotype Section and Point (GSSP) for demarcation of the Anthropocene. The lake’s varved sediments are formed by alternating allogenic atmospheric inputs and authigenic lake processes and store a record of environmental and human impacts at a continental-global scale. Varve counting and radiometric dating provided a precise annual-resolution sediment chronology for the site. Time series records of radioactive (239,240Pu, 129I and soot 14C), chemical (spheroidal carbonaceous particles, polycyclic aromatic hydrocarbons, soot, heavy metals, δ13C, etc), physical (magnetic susceptibility and grayscale) and biological (environmental DNA) indicators all show rapid changes in the mid-20th century, coincident with clear lithological changes of the sediments. Statistical analyses of these proxies show a tipping point in 1954 CE. 239,240Pu activities follow a typical unimodal globally-distributed profile, and are proposed as the primary marker for the Anthropocene. A rapid increase in 239,240Pu activities at 88 mm depth in core SHLW21-Fr-13 (1953 CE) is synchronous with rapid changes of other anthropogenic proxies and the Great Acceleration, marking the onset of the Anthropocene. The results indicate that Sihailongwan Maar Lake is an ideal site for the Anthropocene GSSP

Transgene Expression Is Associated with Copy Number and Cytomegalovirus Promoter Methylation in Transgenic Pigs

Transgenic animals have been used for years to study gene function, produce important proteins, and generate models for the study of human diseases. However, inheritance and expression instability of the transgene in transgenic animals is a major limitation. Copy number and promoter methylation are known to regulate gene expression, but no report has systematically examined their effect on transgene expression. In the study, we generated two transgenic pigs by somatic cell nuclear transfer (SCNT) that express green fluorescent protein (GFP) driven by cytomegalovirus (CMV). Absolute quantitative real-time PCR and bisulfite sequencing were performed to determine transgene copy number and promoter methylation level. The correlation of transgene expression with copy number and promoter methylation was analyzed in individual development, fibroblast cells, various tissues, and offspring of the transgenic pigs. Our results demonstrate that transgene expression is associated with copy number and CMV promoter methylation in transgenic pigs

Temporal Asynchrony of Trophic Status Between Mainstream and Tributary Bay Within a Giant Dendritic Reservoir: The Role of Local-Scale Regulators

Limnologists have regarded temporal coherence (synchrony) as a powerful tool for identifying the relative importance of local-scale regulators and regional climatic drivers on lake ecosystems. Limnological studies on Asian reservoirs have emphasized that climate and hydrology under the influences of monsoon are dominant factors regulating seasonal patterns of lake trophic status; yet, little is known of synchrony or asynchrony of trophic status in the single reservoir ecosystem. Based on monthly monitoring data of chlorophyll a, transparency, nutrients, and nonvolatile suspended solids (NVSS) during 1-year period, the present study evaluated temporal coherence to test whether local-scale regulators disturb the seasonal dynamics of trophic state indices (TSI) in a giant dendritic reservoir, China (Three Gorges Reservoir, TGR). Reservoir-wide coherences for TSICHL, TSISD, and TSITP showed dramatic variations over spatial scale, indicating temporal asynchrony of trophic status. Following the concept of TSI differences, algal productivity in the mainstream of TGR and Xiangxi Bay except the upstream of the bay were always limited by nonalgal turbidity (TSICHL−TSISD <0) rather than nitrogen and phosphorus (TSICHL−TSITN <0 and TSICHL−TSITP <0). The coherence analysis for TSI differences showed that local processes of Xiangxi Bay were the main responsible for local asynchrony of nonalgal turbidity limitation levels. Regression analysis further proved that local temporal asynchrony for TSISD and nonalgal turbidity limitation levels were regulated by local dynamics of NVSS, rather than geographical distance. The implications of the present study are to emphasize that the results of trophic status obtained from a single environment (reservoir mainstream) cannot be extrapolated to other environments (tributary bay) in a way that would allow its use as a sentinel site

Cassava genome from a wild ancestor to cultivated varieties

Cassava is a major tropical food crop in the Euphorbiaceae family that has high carbohydrate production potential and adaptability to diverse environments. Here we present the draft genome sequences of a wild ancestor and a domesticated variety of cassava and comparative analyses with a partial inbred line. We identify 1,584 and 1,678 gene models specific to the wild and domesticated varieties, respectively, and discover high heterozygosity and millions of single-nucleotide variations. Our analyses reveal that genes involved in photosynthesis, starch accumulation and abiotic stresses have been positively selected, whereas those involved in cell wall biosynthesis and secondary metabolism, including cyanogenic glucoside formation, have been negatively selected in the cultivated varieties, reflecting the result of natural selection and domestication. Differences in microRNA genes and retrotransposon regulation could partly explain an increased carbon flux towards starch accumulation and reduced cyanogenic glucoside accumulation in domesticated cassava. These results may contribute to genetic improvement of cassava through better understanding of its biology

Classification Method of Teaching Resources Based on Improved KNN Algorithm

In order to effectively utilize the network teaching resources, a teaching resource classification method based on the improved KNN (K-Nearest Neighbor) algorithm was proposed. Taking the text class primary and secondary school teaching resources as the research object, combined with the domain characteristics, the KNN algorithm was improved. By measuring the sample space density, the text of the high-density area was found. Different clipping methods were proposed for both intra-class and inter-class regions. The problem of cropping in the space of multiple class boundaries was considered. Results showed that the method ensured uniform distribution of samples and reduced the time of classification. Therefore, under the Weka platform, the improved KNN algorithm is effective

Classification Method of Teaching Resources Based on Improved KNN Algorithm

In order to effectively utilize the network teaching resources, a teaching resource classification method based on the improved KNN (K-Nearest Neighbor) algorithm was proposed. Taking the text class primary and secondary school teaching resources as the research object, combined with the domain characteristics, the KNN algorithm was improved. By measuring the sample space density, the text of the high-density area was found. Different clipping methods were proposed for both intra-class and inter-class regions. The problem of cropping in the space of multiple class boundaries was considered. Results showed that the method ensured uniform distribution of samples and reduced the time of classification. Therefore, under the Weka platform, the improved KNN algorithm is effective

Daily Spatial Distribution of Apparent Temperature Comfort Zone in China Based on Heat Index

Apparent temperature (AT) is used to evaluate human comfort and is of great importance for studies on the effects of environmental factors on human health. This study used the daytime heat index (HI) calculated by national surface meteorological stations in China as the AT dependent variable, with August 2020 employed as an example. The daytime fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5) data and multi-source data extracted from the stations were used as the independent variables. Due to the presence of multicollinearity among the independent variables, we implemented a multiple stepwise regression model and developed a daily near-surface 1 km HI estimation model. The correlation analysis using the model showed that the coefficient of determination (R2) was 0.89; the mean absolute error (MAE) was 1.49 °C, and the root mean square error (RMSE) was 2.08 °C. We also used 10-fold cross-validation to calculate the error between the parameter and predicted values. The R2 of the model was 0.96; the MAE was 1.80 °C, and the RMSE was 2.40 °C. In this month, the mean daily daytime HI was 20.51 °C. According to the Universal Thermal Climate Index (UTCI), the areas with more than 20 days of heat stress for one month were largely distributed in the desert areas of northwest China and the coastal areas in southeast China, accounting for 29.98% of the total land area of China. This study improves the spatial resolution and accuracy of HI prediction, thus providing a scientific reference for studying residential environments and the urban heat island effect