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Accurate and high-throughput maize plant phenotyping is vital for crop breeding and cultivation research. Tassel-related phenotypic parameters are important agronomic traits. However, fully automatic and fine tassel organ segmentation of maize shoots from three-dimensional (3D) point clouds is still challenging. To address this issue, a tassel point cloud segmentation method based on point cloud super voxels clustering and local geometric features was proposed in this study. Firstly, the undirected graph of the maize plant point cloud was established, the edge weights were calculated by using the difference of normal vectors, and the spectral clustering method was used to cluster the point cloud to form multiple super voxel sub-regions. Then, the principal component analysis method was used to find the two end regions of the plant and based on the observation of the straight direction of the bottom stem regions, the top and bottom regions were distinguished by the point cloud linear features. Finally, the tassel points were identified based on the plane local features of the point cloud. The sub-regions of the top region of the plant were classified into leaf regions, tassel regions, and mixed regions by plane local features of the point cloud, the tassel points in the tassel sub-region, and the mixed region were the finally segmented tassel point clouds. In this study, 15 mature maize plants with 3 point cloud densities were tested. Compared with the ground truth segmented manually, the average F1 scores of the tassel segmentation were 0.763, 0.875 and 0.889 when the point cloud density was 0.8/cm, 1.3/cm, and 1.9/cm, respectively. The segmentation accuracy of this method increased with the increase of plant point cloud density. The increase of point cloud density and the number of point clouds mainly affected the calculation results of point cloud plane features in tassel segmentation. When the number of point clouds was small, the top leaf point cloud was relatively sparse. Therefore, the difference between the plane feature of the leaf point and the plane feature of the tassel point was not obvious, which led to the increase of the misclassification of the point cloud. However, the time complexity of the algorithm was O(n3), so the increase in the density and number of point clouds would lead to a significant increase in the running time. Considering the segmentation accuracy and running time, the research obtained the best effect on the mature maize plants with a point cloud density of 1.3/cm and an average number of 15,000. The segmentation F1 score reached 0.875 and the running time was 6.85 s. The results showed that this method could extract tassels from maize plant point cloud, and provided technical support for the research and application of high-throughput phenotyping and three-dimensional reconstruction of maize.

Super thermal insulation aerogel materials featuring nano-sized cavities, abundant heterogeneous interfaces, and low dielectric properties offer a promising avenue for the development of materials that excel in both passive cooling and high-frequency terahertz (THz) communication efficiency. In this work, a pre-polymerized vinyl trimethoxy silane (PVTMS) molecule with high cross-linking density was fabricated via radical polymerization, and then polyhedral oligomeric silsesquioxane (POSS) was used for tailoring the cross-linking density and polar functional group ratio of the PVTMS nano-aerogel system, simultaneously. The fabricated aerogels possessed a nanoscale bimodal structure including small (∼30 nm) and large (∼200 nm) pores, where the small pores lead to the nanoscale Knudsen effect and ultra-low thermal conductivity (lower than air), while the large pores induce the Mie scattering effect and enhance solar reflectance for radiation blocking. Thanks to the tailored nanostructure design, the POSS@PVTMS aerogel possessed a high specific surface area (728 m2 g−1), ultra-low thermal conductivity (25.5 mW m−1 K−1), hydrophobic properties (137° water contact angle), high infrared emissivity (averaging ∼99%), and ultra-low dielectric properties (average Dk = 1.13). Hence, the aerogel exhibited an enhanced passive cooling capability (ΔT reached 3.7 °C) along with an impressive THz transmission rate (average 88.7%). [ABSTRACT FROM AUTHOR]

This study aims to improve the mechanical properties of post-consumer recycled (PCR) plastic composed primarily of polypropylene (PP) and polyethylene (PE), which generally exhibit poor miscibility, by applying coupling agents and graphene. Here, we compare a commercially available coupling agent with a directly synthesized maleic anhydride (MA) coupling agent. When applied to a 5:5 blend of recycled PP and PE, an optimum tensile strength was achieved at a 3 wt% coupling agent concentration, with the MA coupling agent outperforming the commercial one. Characterization through Fourier transform infrared spectroscopy (FT-IR) and thermogravimetry analysis (TGA) revealed a PP:PE ratio of approximately 3:7 in the PCR plastics, with 4.86% heterogeneous materials present. Applying 3 wt% of the commercial and MA coupling agents to the PCR plastics resulted in a significant 53.9% increase in the tensile strength, reaching 11.25 MPa, and a remarkable 421.54% increase in the melt flow index (MFI), reaching 25.66 g/10 min. Furthermore, incorporating 5 wt% graphene led to a notable 64.84% increase in the tensile strength. In addition, the application of MA coupling agents and graphene improved the thermal stability of the PCR plastics. These findings show significant promise for addressing environmental concerns associated with plastic waste by facilitating the recycling of PCR plastics into new products. The utilization of coupling agents and graphene offers a viable approach to enhance the mechanical properties of PCR plastics, paving the way for sustainable and environmentally friendly solutions. [ABSTRACT FROM AUTHOR]

In vitro pollen germination is considered the most efficient method to assess pollen viability. The pollen germination frequency and pollen tube length, which are key indicators of pollen viability, should be accurately measured during in vitro culture. In this study, a Mask R-CNN model trained using microscopic images of tree peony (Paeonia suffruticosa) pollen has been proposed to rapidly detect the pollen germination rate and pollen tube length. To reduce the workload during image acquisition, images of synthesized crossed pollen tubes were added to the training dataset, significantly improving the model accuracy in recognizing crossed pollen tubes. At an Intersection over Union threshold of 50%, a mean average precision of 0.949 was achieved. The performance of the model was verified using 120 testing images. The R 2 value of the linear regression model using detected pollen germination frequency against the ground truth was 0.909 and that using average pollen tube length was 0.958. Further, the model was successfully applied to two other plant species, indicating a good generalizability and potential to be applied widely. [ABSTRACT FROM AUTHOR]

In this study, we aimed to provide an accurate method for the detection of oil and moisture content in soybeans. Introducing two-dimensional low-field nuclear magnetic resonance (LF-2D-NMR) qualitatively solved the problem of overlapping component signals that one-dimensional (1D) LF-NMR techniques cannot distinguish in soybean detection research. Soxhlet extraction, oven drying, LF-NMR spectrum, and LF-NMR oil and moisture content software were used to detect soybean oil and moisture content. The comparison showed that the LF-NMR oil and moisture content software was faster and more accurate than the other methods. The specific identification of the oil and moisture signals of soybean seeds using longitudinal relaxation time (T1) and transverse relaxation time (T2) successfully solved the problems of less mobile water, overlapping free water, and oil signals. Therefore, LF-2D-NMR can complement conventional LF-NMR assays, and this study provides a new method for the analysis and detection of moisture and oil in soybeans. [ABSTRACT FROM AUTHOR]

Traditional machine learning sequence models, such as RNN and LSTM, can solve sequential data problems with the use of internal memory states. However, the neuron units and weights are shared at each time step to reduce computational costs, limiting their ability to learn time-varying relationships between model inputs and outputs. In this context, this paper proposes two methods to characterize the dynamic relationships in real-world sequential data, namely, the internal time-varying sequence model (ITV model) and the external time-varying sequence model (ETV model). Our methods were designed with an automated basis expansion module to adapt internal or external parameters at each time step without requiring high computational complexity. Extensive experiments performed on synthetic and real-world data demonstrated superior prediction and classification results to conventional sequence models. Our proposed ETV model is particularly effective at handling long sequence data. [ABSTRACT FROM AUTHOR]

Microcapillary films (MCFs) are microextrusion‐processed plastic films containing an array of parallel microcapillaries, and have been widely utilized as microfluidic platforms. However, the nonuniform size distribution within a single MCF strip limits the application of MCFs in monodisperse droplet generation. In this paper, the mechanisms that lead to uneven microcapillary dimensions in conventional MCFs whose gas pressures in all channels are the same is first clarified. The effect of gas pressure in a single channel on the microcapillary dimensions in the film is then studied. Finally, the size uniformity of the microcapillaries is improved by separate gas injection in different channels, providing new possibilities for the generation of highly monodisperse microdroplets. [ABSTRACT FROM AUTHOR]

Flexible polymeric microtubes with rectangular‐lumen are useful in chemical and bioengineering. However, improving the aspect ratio of the rectangular lumen is still a tough task. In this study, numerical simulations are carried out to study the influences of the processing parameters and the design of the extrusion die on the aspect ratio of the rectangular microchannels. Increasing the length of the inner die and reducing its width are critical to improving the aspect ratio of channels. The pressure difference is also important for controlling the sizes and shapes of channels. A linear mathematical relationship is built between the aspect ratio of channels and processing parameters and the sizes of the die. According to the simulating results, the geometry of the inner die is optimized and manufactured experimentally. The flexible rectangular microtubes are produced with well‐controlled channel sizes. The highest aspect ratio of the channel we achieve is 87. [ABSTRACT FROM AUTHOR]

Rectangular microchannels are useful in biological and chemical research. However, high-efficient method for producing rectangular microchannels has not been established. Here, flexible rectangular microtubes are produced via a micro-extrusion method. The size of the rectangular channels is controlled by drawing speed, flow rates of the polymer melt and air. A theoretical model is built to predict the size of the channels. To show the capability of the products, they are used as disposable micro-emulsifiers and used for protecting and observing volatile samples. More applications are to be developed for the novel tool which will facilitate research in many fields. [ABSTRACT FROM AUTHOR]

A dual‐pore network is favored in applications such as tissue engineering scaffolds. In this paper, foamed microcapillary films (FMCFs) are prepared based on a poly(lactic acid)/poly(butylene succinate) blend using melt extrusion and batch foaming with supercritical carbon dioxide. Such films are characterized by multiple hollow microcapillaries (diameter of 100–360 µm) connected with cells (size of 3–194 µm, open‐cell content of over 80%) within the scaffold. By plugging the ends of the MCF before foaming, the formation of a solid skin layer is successfully avoided. Furthermore, the diameter of the microcapillaries of an FMCF can be adjusted using the designed foaming strategy. The effects of the foaming condition on the FMCF foaming behavior are also investigated. When other conditions are fixed, the foaming behavior changes dramatically when the foaming temperature changes within the range of 120–123 °C. [ABSTRACT FROM AUTHOR]

Gene set analysis is commonly used in functional enrichment and molecular pathway analyses. Most of the present methods are based on the competitive testing methods which assume each gene is independent of the others. However, the false discovery rates of competitive methods are amplified when they are applied to datasets with high inter-gene correlations. The self-contained testing methods could solve this problem, but there are other restrictions on data characteristics. Therefore, a statistically rigorous testing method applicable to different datasets with various complex characteristics is needed to obtain unbiased and comparable results. We propose a self-contained and competitive incorporated analysis (SCIA) to alleviate the bias caused by the limited application scope of existing gene set analysis methods. This is accomplished through a novel permutation strategy using a priori biological networks to selectively permute gene labels with different probabilities. In simulation studies, SCIA was compared with four representative analysis methods (GSEA, CAMERA, ROAST, and NES), and produced the best performance in both false discovery rate and sensitivity under most conditions with different parameter settings. Further, the KEGG pathway analysis on two real datasets of lung cancer showed that the results found by SCIA in both of the two datasets are much more than that of GSEA and most of them could be supported by literature. Overall, SCIA promisingly offers researchers more reliable and comparable results with different datasets. [ABSTRACT FROM AUTHOR]

Abstract: The hydrogen abstraction and displacement process of OH radicals with CHF2CF2OCH3 (R1) and CH2FCF2OCH3 (R2) are studied theoretically. Moreover, the secondary reactions of their products (CHF2CF2OCH2, CF2CF2OCH3, CH2FCF2OCH2, and CHFCF2OCH3) with OH radical are also carried out. Electronic structures of all stationary points are calculated at the BMK/6-311+G(d,p) level. And the single point energy calculation is performed using BMC-CCSD method to refine the reaction enthalpy and barrier height for each reaction channel. The correlation between the barrier height and the corresponding bond dissociation energy is studied. Using the canonical variational transition-state theory (CVT) including the small-curvature tunneling (SCT) correction, the rate constants for CHF2CF2OCH3/CH2FCF2OCH3 +OH reactions are calculated within 200–2000K. The total rate constants calculated from the sum of the individual rate constants taking into account the Boltzmann distribution of each conformer. A good agreement is obtained between theoretical and experimental rate constants. Finally, the theoretical rate constants are fitted to four-parameter expression to assist further experimental study. [Copyright &y& Elsevier]

Dual-level direct dynamics method is used to study the kinetic properties of the hydrogen abstraction reactions of CH3CHBr + HBr → CH3CH2Br + Br (R1) and CH3CBr2 + HBr → CH3CHBr2 + Br (R2). Optimized geometries and frequencies of all the stationary points and extra points along the minimum-energy path are obtained at the MPW1K/6-311+G(d,p), MPW1K/ma-TZVP, and BMK/6-311+G(d,p) levels. Two complexes with energies less than that of the reactants are located in the entrance of each reaction at the MPW1K/6-311+G(d,p) and MPW1K/ma-TZVP levels, respectively. The energy profiles are further refined with the interpolated single-point energies method at the G2M(RCC5)//MPW1K/6-311+G(d,p) level of theory. By the improved canonical variational transition-state theory with the small-curvature tunneling correction (SCT), the rate constants are evaluated over a wide temperature range of 200-2000 K. Our calculations have shown that the radical reactivity decreases from CH3CHBr to CH3CBr2. Finally, the total rate constants are fitted by two modified Arrhenius expression. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Highlights: [•] Ground-state geometric structures of all species are optimized at M06 level of theory. [•] The optical properties of all species are calculated by means of TD-M06 method. [•] Detailed analysis for electronic transitions is performed to elucidate the UV spectra. [Copyright &y& Elsevier]

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive human malignancies. The metabolomic approaches are developed to discover the novel biomarkers of PDAC. Methods: 550 preoperative, postoperative PDAC and normal controls (NCs) serums were employed to characterize metabolic alterations in training and validation sets by LC-MS. Results: The results of PLS-DA analysis indicated that three groups could be distinguished clearly and the post-PDAC group is adjacent to a normal group as compared with pre-PDAC group. Further results showed that histidinyl-lysine significantly increased whereas docosahexaenoic acid and LysoPC (14:0) decreased in pre-PDAC patients as compared with NCs. And these three markers had a significant tendency to recover after tumor resection. The validation set results revealed that for CA19-9 negative patients, 92.3% (12/13) of them can be screened using these three metabolites. The combination of these markers could significantly improve the diagnostic performance for PDAC, with higher sensitivity (0.93), specificity (0.92) and AUC (0.97). Moreover, network and pathways analyses explored the latent relationship among differential metabolites. The glycerolipid metabolism and primary bile acid synthesis showed variation in network and pathway analysis. Conclusions: These three markers combined with CA199 displayed high sensitivity and specificity for detecting PDAC patients from NCs. The results indicated that these three metabolites could be regarded as potential biomarkers to distinguish PDAC from NCs., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)