10 research outputs found

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Soybean Futures Price Prediction Model Based on EEMD-NAGU

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    The soybean futures market in China occupies an important position in the agricultural product futures market. The research on the fluctuation of soybean futures price and the prediction of the future price trend has always been the focus of extensive attention in the field of agricultural economics. This paper proposes an EEMD-NAGU hybrid prediction model for soybean futures price based on Ensemble Empirical Mode Decomposition (EEMD) and New Attention Gate Unit (NAGU). The model first uses EEMD to process soybean futures price data into multiple Intrinsic Mode Functions (IMFs) and residual sequence. Then calculates the sample entropy of each IMF and reconstructed the IMF into three components of low-frequency, medium-frequency, and high-frequency, according to the size of the sample entropy. NAGU is formed by embedding the Attention mechanism (Attention) into the Gate Recurrent Unit (GRU) structure, further improving the learning capability of the model. NAGU splits the original reset gate and update gate, sets up two-stage respectively, and uses different activation functions to capture the information in historical data better. Soybean futures price data is complex nonlinearities and contain more noise. In this model, EEMD plays denoises the time series data and fixes the model input. NAGU can perform differential learning on data and finally produce prediction results. EEMD-NAGU is compared with thirteen other prediction models (Support Vector Regression (SVR), LSTM, GRU, NAGU, EEMD-LSTM, EEMD-GRU, EEMD-NGU, Attention-LSTM, Attention-GRU, Attention-NGU, EEMD-Attention-LSTM, EEMD-Attention-GRU, and EEMD-Attention-NGU). The evaluation indexes of the experiment are Mean Absolute Error (MAE), Mean Square Error (MSE), and R Squared ( R2R^{2} ). The experimental results show that the EEMD-NAGU model outperforms other models with better prediction performance. The model can be widely used to predict the price of wheat, corn, gold, oil, and other time series data

    Internet Use and Better-Informed Divorce in China

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    China has witnessed a rapid expansion in Internet penetration in recent years, with profound impacts on people’s family life and marital relationships. This paper aims to examine the causal effects and functionary of information access through Internet on marital stability. This paper identifies a robust association between Internet use and increasing divorce rates in China by using nationally representative, individual-level survey data and province-level aggregate data. Various regression techniques and specifications demonstrated the statistical and economic significance of the association. Given the ever-expanding role of the Internet and the serious consequences of divorce on families and society, it is imperative that we study the underlying mechanisms as the first step toward socially responsible policymaking. Our analysis revealed a significant mediating effect of the self-reported importance of Internet information acquisition, the frequency of chatting with online friends, the frequency of meeting with online friends, and the intensity of Internet use. These findings are consistent with the theory that the increase in divorce decisions is due to better information access and is, therefore, rational and that policies such as a mandatory cooling-off period for divorce may lower societal welfare. We also conducted a series of heterogeneity analyses that showed, among other findings, that the Internet effect is stronger for women

    Passionfruit Genomic Database (PGD): a comprehensive resource for passionfruit genomics

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    Abstract Passionfruit (Passiflora edulis) is a significant fruit crop in the commercial sector, owing to its high nutritional and medicinal value. The advent of high-throughput genomics sequencing technology has led to the publication of a vast amount of passionfruit omics data, encompassing complete genome sequences and transcriptome data under diverse stress conditions. To facilitate the efficient integration, storage, and analysis of these large-scale datasets, and to enable researchers to effectively utilize these omics data, we developed the first passionfruit genome database (PGD). The PGD platform comprises a diverse range of functional modules, including a genome browser, search function, heatmap, gene expression patterns, various tools, sequence alignment, and batch download, thereby providing a user-friendly interface. Additionally, supplementary practical tools have been developed for the PGD, such as gene family analysis tools, gene ontology (GO) terms, a pathway enrichment analysis, and other data analysis and mining tools, which enhance the data’s utilization value. By leveraging the database’s robust scalability, the intention is to continue to collect and integrate passionfruit omics data in the PGD, providing comprehensive and in-depth support for passionfruit research. The PGD is freely accessible via http://passionfruit.com.cn

    Improving the Forming Quality of Laser Dynamic Flexible Micropunching by Laser Pre-Shocking

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    Laser pre-shocking (LPS) was introduced into the laser dynamic flexible micropunching process to refine the grain size of a workpiece to improve the forming quality of punched parts. T2 copper foils with five different grain sizes and seven different laser power densities with and without LPS were used for the experiment. The results showed that the grains are refined and the average surface roughness Ra decreases after LPS. For copper foils annealed at 650 °C, the value of Ra decreases from 0.430 to 0.363 µm. The increase in laser energy density and grain size leads to the deterioration of the fracture surface. LPS can improve the quality of the fracture surface. Compared with punched holes without LPS, the dimensional accuracy and shape accuracy of punched holes can be improved by LPS. When grain size is close to the thickness of the copper foil, the forming quality of the punched parts becomes uncertain, owing to the difference in the orientation of the initial grains. The instability of laser dynamic flexible micropunching can be reduced by LPS. Especially, the improvement of forming quality of the punched part brought by LPS is significant for the copper foils with coarse grains

    Highly Efficient and Stable Strain-Release Radioiodination for Thiol Chemoselective Bioconjugation

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    We report a novel thiol selective radioiodination method based on strain-release reaction. A new heterobifunctional radioiodination agent which has very good thiol selectivity and excellent stability with high radiolabeling yield was synthesized, characterized, and applied successfully for thiol-contained peptide labeling
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