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Fast and accurate counting of wheat ears in field conditions is a key element for determining wheat yield. To obtain the number of wheat ears in a field, we propose a new counting algorithm based on computer vision. This algorithm counts wheat ears in remote images through semantic segmentation regression network (SSRNet). SSRNet is a multistage convolutional neural network that we propose to achieve counting problems through regression. In SSRNet, first, the original image is cropped to increase the amount of data. This method effectively solves the small sample dataset. Next, based on the cropping results, we build a fully convolutional neural network (FCNN) to segment wheat ears in field conditions. FCNN increases the accuracy of wheat ears counting by accurately segmenting wheat ears in a complex background. Then, we build a regression convolutional neural network (RCNN) to count wheat ears based on the segmentation results of FCNN. In RCNN, we propose a new activation function positive rectification linear unit (PrLU) to process the last layer of the fully connected layer, so that RCNN can effectively count the number of wheat ears in the image. Finally, a counting strategy is proposed to count the number of wheat ears in the original image. To verify the counting performance of SSRNet, we compare the counting result of SSRNet with the real value of manual statistics. The results show that the average accuracy (Acc), R², and root mean squared error (RMSE) of the SSRNet count results on the test set in this article are 0.980, 0.996, and 9.437, respectively. It can be seen from the results that our proposed method can accurately count wheat ears in field conditions. At the same time, the counting time (0.11 s) shows that SSRNet can quickly estimate the number of wheat ears in field conditions. We concluded that this study can provide important technical support for the high-throughput field wheat ears counting task in large-scale phenotyping work.

Background Fine-scale genetic structure of ethnolinguistically diverse Chinese populations can fill the gap in the missing diversity and evolutionary landscape of East Asians, especially anthropologically informed Chinese minorities. Hmong-Mien (HM) people were one of the most important indigenous populations from South China and Southeast Asia, which were suggested to be the descendants of the Yangtze rice farmers based on linguistic and archeological evidence. Guizhou Miao, possessing a specific genetic structure, harbored a close genetic relationship with geographically close Guizhou populations and Guangxi historical people. We genotyped genome-wide SNP data in Guizhou HM-speaking populations and merged it with modern and ancient reference populations to explore the evolutionary and adaptive characteristics of Miao people via a comprehensive population genetic analysis. Results The overall genetic admixture landscape of Guizhou Miao showed genetic differentiation between them and other linguistically diverse Guizhou populations. Admixture models further confirmed that Miao people derived their primary ancestry from geographically close Guangxi Gaohuahua people. The estimated identity by descent (IBD) and effective population size further confirmed a plausible population bottleneck, contributing to their unique genetic diversity and structure pattern. We finally identified several natural selection candidate genes associated with several biological pathways. Conclusions We found Guizhou Miao with a specific genetic structure harbored a close genetic relationship with geographically close Guizhou populations and Guangxi historic people. Miao people derived their major ancestry from geographically close Guangxi Gaohuahua people and a plausible population bottleneck which contributed to the unique pattern of their genetic diversity and structure. Future ancient DNA from Shijiahe and Qujialing would further promote new insights into the origin of the Miao people.

ABIN-1, also called TNIP1, is an ubiquitin-binding protein that serves an important role in suppressing RIPK1-independent apoptosis, necroptosis, and NF-κB activation. However, the involvement of ABIN-1 in the regulation of RIPK1-dependent apoptosis (RDA) is unknown. In this study, we found that poly(I:C) + TAK1 inhibitor 5Z-7-oxozeaenol (P5) concurrently induces RDA and necroptosis in Abin-1−/−, but not in Abin-1+/+ mouse embryonic fibroblasts (MEFs). Upon P5 stimulation, cells initially die by necroptosis and subsequently by RDA. Furthermore, we explored the therapeutic effect of ABIN-1 deficiency in necroptosis-based cancer therapy in colorectal cancer (CRC). We found that poly(I:C) + 5Z-7-oxozeaenol + IDN-6556 (P5I) yields a robust pro-necroptosis response, and ABIN-1 deficiency additionally enhances this P5I-induced necroptosis. Moreover, phase I/II cIAP inhibitor birinapant with clinical caspase inhibitor IDN-6556 (BI) alone and 5-fluorouracil with IDN-6556 (FI) alone are sufficient to induce necroptotic cell death in CRC cells by promoting auto-secretion of tumor necrosis factor (TNF); ABIN-1 deficiency amplifies the BI- or FI-induced necroptosis. Two independent xenograft experiments using HT-29 or COLO205 cells show that both BI and P5I remarkably inhibit tumor growth via necroptosis activation. For poly(I:C)-induced cell death, the sensitizing effect of ABIN-1 deficiency on cell death may be attributed to increased expression of TLR3. In TNF-induced necroptosis, ABIN-1 deficiency increases TNF-induced RIPK1 polyubiquitination by reducing the recruitment of ubiquitin-editing enzyme A20 to the TNFR1 signaling complex and induces more TNF secretion in CRC cells upon pro-necroptosis stimulation. With this combined data, ABIN-1 deficiency promotes greater sensitization of CRC cells to necroptosis.

Accurate counting of wheat ears in field conditions is vital to predict yield and for crop breeding. To quickly and accurately obtain the number of wheat ears in a field, we propose herein a method to count wheat ears based on fully convolutional network (FCN) and Harris corner detection. The technical procedure consists essentially of 1) constructing a dataset of wheat-ear images from acquired red-green-blue (RGB) images; 2) training a FCN as the wheat-ear segmentation model by using the constructed image dataset; 3) preparing testing images and inputting them into the segmentation model to get the initial segmentation results; 4) binarizing the initial segmentation by using the Otsu algorithm (to facilitate subsequent processing); and 5) applying Harris corner detection after extracting the wheat-ear skeleton to obtain the number of wheat ears in the images. The segmentation results show that the proposed FCN-based segmentation model segments wheat ears with an average accuracy of 0.984 and at low computational cost. An average of only 0.033 s is required to segment a 256× 256 -pixel wheat-ear image. Moreover, the segmentation result is improved by nearly 10% compared with the previous segmentation methods under conditions of wheat-ear occlusion, leaf occlusion, uneven illumination, and soil disturbance. Subsequently, the proposed counting method achieves good results, with an average accuracy of 0.974, a coefficient of determination (R2) of 0.983, and a root mean square error (RMSE) of 14.043. These metrics are all improved by 10% compared with the previous methods. These results show that the proposed method accurately counts wheat ears even under conditions of wheat-ear adhesion. Furthermore, the results provide an important technique for studying wheat phenotyping.

The in vivo function of p38 mitogen-activated protein kinase (MAPK) signaling in regulating the response to simulated microgravity is still largely unclear. Using Caenorhabditis elegans as an assay system, we investigated the in vivo function of p38 MAPK signaling in regulating the response of animals to simulated microgravity and the underlying molecular mechanism. Simulated microgravity treatment significantly increased the transcriptional expressions of genes (pmk-1, sek-1, and nsy-1) encoding core p38 MAPK signaling pathway and the expression of phosphorylated PMK-1/p38 MAPK. The pmk-1, sek-1, or nsy-1 mutant was susceptible to adverse effects of simulated microgravity. The intestine-specific activity of PMK-1 was required for its function in regulating the response to simulated microgravity, and the entire p38 MAPK signaling pathway could act in the intestine to regulate the response to simulated microgravity. In the intestine, SKN-1 and ATF-7, two transcriptional factors, were identified as downstream targets for PMK-1 in regulating the response to simulated microgravity. Therefore, the activation of p38 MAPK signaling may mediate a protection mechanism for nematodes against the adverse effects of simulated microgravity. Additionally, our results highlight the potential crucial role of intestinal cells in response to simulated microgravity in nematodes.

In the assessment of breathing cracks, it is assumed that both sides of the crack will contact each other along with the vibration, causing the blades to exhibit nonlinear behaviors. Therefore, nonlinear approaches are much more sensitive to the cracks and are also capable of detecting their location and size. Recently, a nonlinearity measure-based damage location method was proposed for the distributed vibration responses of beam-like structures. However, its procedures require collecting the trajectories of the non-destructive status of structures, which introduce substantial difficulties to engineering applications. In this paper, a bicoherence-based nonlinearity measurement method is proposed for identifying the location of breathing cracks in blades. It can evaluate the extent of nonlinearity in the responses of blades under random excitations and avoids using the non-destructive status of structures. The additional nonlinearity in a blade with a breathing crack, based on distributed parameter modeling, is discussed, while the distributed responses on characteristic point were collected to estimate the degree of nonlinearity. A Total Nonlinearity Index (TNLI) was used to establish the damage indicator of the blade, and the crack was identified by finding the maximum components. Validation experiments were conducted to verify the effectiveness of the proposed method, in which a vision measurement system was employed to obtain the distributed vibration responses.

Fusarium head blight (FHB), one of the most important diseases of wheat, mainly occurs in the ear. Given that the severity of the disease cannot be accurately identified, the cost of pesticide application increases every year, and the agricultural ecological environment is also polluted. In this study, a neural network (NN) method was proposed based on the red-green-blue (RGB) image to segment wheat ear and disease spot in the field environment, and then to determine the disease grade. Firstly, a segmentation dataset of single wheat ear was constructed to provide a benchmark for the segmentation of the wheat ear. Secondly, a segmentation model of single wheat ear based on the fully convolutional network (FCN) was established to effectively realize the segmentation of the wheat ear in the field environment. An FHB segmentation algorithm was proposed based on a pulse-coupled neural network (PCNN) with K-means clustering of the improved artificial bee colony (IABC) to segment the diseased spot of wheat ear by automatic optimization of PCNN parameters. Finally, the disease grade was calculated using the ratio of the disease spot to the whole wheat ear. The experimental results show that: (1) the accuracy of the segmentation model for single wheat ear constructed in this study is 0.981. The segmentation time is less than 1 s, indicating that the model can quickly and accurately segment wheat ear in the field environment; (2) the segmentation method of the disease spot performed under each evaluation indicator is improved compared with the traditional segmentation methods, and the accuracy is 0.925 in the disease severity identification. These research results can provide important reference value for grading wheat FHB in the field environment, which also can be beneficial for real-time monitoring of other crops’ diseases under near-Earth remote sensing.

In order to obtain a lightweight Honda energy-saving race car body, the carbon fiber materials and monocoque technology were introduced into the design of the car body. Firstly, a lightweight structural monocoque body geometric model was constructed. Then the design geometric model was subjected to static strength, and the performance simulation analysis of the front collision condition and the rollover condition showed that the designed monocoque body can meet the requirements. Finally, the monocoque body model was processed and manufactured, which was assembled and integrated on the car for physics. The experiment results showed that the designed lightweight body meet the requirements of work performance.

This report details the first organocatalytic method for nitrenoid transfer and its application to intermolecular, site-selective C(sp3)–H amination., This report details the first organocatalytic method for nitrenoid transfer and its application to intermolecular, site-selective C(sp3)–H amination. The method utilizes a trifluoromethyl iminium salt as the catalyst, iminoiodinanes as the nitrogen source, and substrate as the limiting reagent. Activated, benzylic, and aliphatic substrates can all be selectively functionalized in yields up to 87%. A mechanistic proposal for the observed reactivity supported by experimental evidence invokes the intermediacy of a diaziridinium salt or related organic nitrenoid, species that have not been previously explored for the purpose of C–H amination. Finally, examples of late-stage functionalization of complex molecules highlight the selectivity and potential utility of this catalytic method in synthesis.

Preference choice on food is an important response strategy for animals living in the environment. Using assay system of preference choice on bacterial foods, OP50 and PA14, we identified the involvement of ADL sensory neurons in the control of preference choice in Caenorhabditis elegans. Both genetically silencing and ChR2-mediated activation of ADL sensory neurons significantly affected preference choice. ADL regulated preference choice by inhibiting function of G protein-coupled receptor (GPCR)/SRH-220. ADL sensory neurons might regulate preference choice through peptidergic signals of FLP-4 and NLP-10 and function of FLP-4 or NLP-10 in regulating preference choice was regulated by SRH-220. FLP-4 released from ADL sensory neurons further regulated preference choice through its receptor of NPR-4 in AIB interneurons. In AIB interneurons, NPR-4 was involved in the control of preference choice by activating the functions of ASH-2 trithorax complex consisting of SET-2, ASH-2 and WDR-5, implying the crucial role of molecular machinery of trimethylation of histone H3K4 in the preference choice control. The identified novel neuronal circuit and the underlying molecular mechanisms will strengthen our understanding neuronal basis of preference choice in animals.

A Myxococcus xanthus gene, MXAN3487, was identified by transposon mutagenesis to be required for the expression of mcuABC, an operon coding for part of the chaperone–usher (CU) system in this bacterium. The MXAN3487 protein displays sequence and structural homology to adenosine 5′-phosphosulphate (APS) kinase family members and contains putative motifs for ATP and APS binding. Although the MXAN3487 locus is not linked to other sulphate assimilation genes, its protein product may have APS kinase activity in vivo and the importance of the ATP-binding site for activity was demonstrated. Expression of MXAN3487 was not affected by sulphate availability, suggesting that MXAN3487 may not function in a reductive sulphate assimilation pathway. Deletion of MXAN3487 significantly delayed fruiting body formation and the production of McuA, a spore coat protein secreted by the M. xanthus Mcu CU system. Based on these observations and data from our previous studies, we propose that MXAN3487 may phosphorylate molecules structurally related to APS, generating metabolites necessary for M. xanthus development, and that MXAN3487 exerts a positive effect on the mcuABC operon whose expression is morphogenesis dependent.

Caenorhabditis elegans is a useful model to study the neuronal or molecular basis for behavioral choice, a specific form of decision-making. Although it has been implied that both D1-like and D2-like dopamine receptors may contribute to the control of decision-making in mammals, the genetic interactions between D1-like and D2-like dopamine receptors in regulating decision-making are still largely unclear. In the present study, we investigated the molecular control of behavioral choice between conflicting alternatives (diacetyl and Cu2+) by D1-like and D2-like dopamine receptors and their possible genetic interactions with C. elegans as the assay system. In the behavioral choice assay system, mutation of dop-1 gene encoding D1-like dopamine receptor resulted in the enhanced tendency to cross the Cu2+ barrier compared with wild-type. In contrast, mutations of dop-2 or dop-3 gene encoding D2-like dopamine receptor caused the weak tendency to cross the Cu2+ barrier compared with wild-type. During the control of behavioral choice, DOP-3 antagonistically regulated the function of DOP-1. The behavioral choice phenotype of dop-2; dop-1dop-3 triple mutant further confirmed the possible antagonistic function of D2-like dopamine receptor on D1-like dopamine receptor in regulating behavioral choice. The genetic assays further demonstrate that DOP-3 might act through Gαo signaling pathway encoded by GOA-1 and EGL-10, and DOP-1 might act through Gαq signaling pathway encoded by EGL-30 and EAT-16 to regulate the behavioral choice. DOP-1 might function in cholinergic neurons to regulate the behavioral choice, whereas DOP-3 might function in GABAergic neurons, RIC, and SIA neurons to regulate the behavioral choice. In this study, we provide the genetic evidence to indicate the antagonistic relationship between D1-like dopamine receptor and D2-like dopamine receptor in regulating the decision-making of animals. Our data will be useful for understanding the complex functions of dopamine receptors in regulating decision-making in animals.

Caenorhabditis elegans is as an ideal model system for the study of mechanisms underlying learning and memory. In the present study, we employed C. elegans assay system of thermotaxis memory to investigate the possible role of serotonin neurotransmitter in memory control. Our data showed that both mutations of tph-1, bas-1, and cat-4 genes, required for serotonin synthesis, and mutations of mod-5 gene, encoding a serotonin reuptake transporter, resulted in deficits in thermotaxis memory behavior. Exogenous treatment with serotonin effectively recovered the deficits in thermotaxis memory of tph-1 and bas-1 mutants to the level of wild-type N2. Neuron-specific activity assay of TPH-1 suggests that serotonin might regulate the thermotaxis memory behavior by release from the ADF sensory neurons. Ablation of ADF sensory neurons by expressing a cell-death activator gene egl-1 decreased the thermotaxis memory, whereas activation of ADF neurons by expression of a constitutively active protein kinase C homologue (pkc-1(gf)) increased the thermotaxis memory and rescued the deficits in thermotaxis memory in tph-1 mutants. Moreover, serotonin released from the ADF sensory neurons might act through the G-protein-coupled serotonin receptors of SER-4 and SER-7 to regulate the thermotaxis memory behavior. Genetic analysis implies that serotonin might further target the insulin signaling pathway to regulate the thermotaxis memory behavior. Thus, our results suggest the possible crucial role of serotonin and ADF sensory neurons in thermotaxis memory control in C. elegans.