Natural Occurrence of cowpea mild mottle virus infecting sesame (Sesamum indicum L.) in Anhui Province, China.

Sesame (Sesamum indicum L.) is one of the primary oilseed crops in China, and often intercropped with shorter crops like peanuts and soybeans. Cowpea mild mottle virus (CpMMV), a member of the Betaflexiviridae family, has been reported in numerous countries worldwide and can infect natural hosts including cowpeas, soybeans, common beans, peanuts, and tomatoes, causing symptoms such as leaf mottling, mosaic patterns, or spotted patterns on the infected leaves. CpMMV is transmitted by whiteflies in nature and by mechanical inoculation in laboratory settings (Iwaki et al., 1982). In September 2023, while surveying soybean virus diseases in Huang-Huai-Hai region of China, we observed sesame plants near a soybean field (longitude 115.76°E, latitude 32.89°N) showing stunted growth, leaf mottling, and mosaic patterns. These symptoms affected approximately one-third of the sesame plants in a 0.1-hectare field. To identify the virus associated with symptomatic leaves, two sesame samples were collected for small RNA deep sequencing. Total RNA was extracted using TRIZOL and sent to BGI for library construction and sequencing with the BGISEQ-500 sequencer. De novo assembly of sRNA reads was performed using Velvet software (version 1.2.10) as described (Su et al., 2016), followed by BLASTn and BLASTx searches against the nonredundant nucleotide and protein databases. CpMMV was identified from sesame plants, with twenty-three contigs ranging from 51 to 368 nucleotides showing similarity to CpMMV, covering 33.7% of the total CpMMV genome. The largest CpMMV contig, spanning 368 nucleotides (nt), exhibited 97% identity to CpMMV isolate Anhui_SZ_DN1383 (Genbank Accession No. MN908944.1) from soybean (Wei et al., 2020). To validate the presence of CpMMV in sesame, RNA from each sample was individually extracted, and CpMMV was detected by reverse-transcription polymerase chain reaction (RT-PCR) according to the manufacturer's instructions (Vazyme, Nanjing, China). Primers were designed based on two small RNA-assembled contigs spanning the CpMMV triple gene block protein 1 (TGBp1) and TGBp2 ORF (Forward: 5´-GGTACCAAAAGATAAGCTTGTTATCTTG-3´; Reverse: 5´-TTAGTACCGTCTCTGTAACAGCCA-3´). Both sesame samples tested RT-PCR positive for CpMMV. The PCR amplicon (597 nt) of these two sesame samples were purified and sequenced. Sequences shared 100% nucleotide identity between them. Nucleotide sequence comparisons confirmed the virus as CpMMV (Accession No. PP767740), exhibiting >99% identity to CpMMV isolate HN_SQ (MW354940.1). Phylogenetic analysis of the 597 nt amplicon, using MEGA7 with eighteen other CpMMV isolates, revealed that the CpMMV isolate from sesame was most closely related to soybean isolates HN_SQ (MW354940.1) and Anhui_SZ_DN1383 (MN908944.1). To fulfill Koch's postulates, healthy sesame leaves were rub-inoculated with crude extracts from CpMMV-infected field samples. RT-PCR confirmed systemic infection at 4 weeks post-inoculation, with symptoms of stunted height, leaf mottle, and mosaic mirroring those observed in the field. Previously, CpMMV has been experimentally documented to infect sesame (Thouvenel et al., 1982), but to our best knowledge, this is the first report of CpMMV infecting sesame under natural conditions. With widespread whiteflies in the Huang-Huai-Hai region of China, CpMMV poses a significant risk to sesame production and may serve as a reservoir, threatening nearby crops such as soybeans.

A Lightweight and High-Precision Passion Fruit YOLO Detection Model for Deployment in Embedded Devices.

In order to shorten detection times and improve average precision in embedded devices, a lightweight and high-accuracy model is proposed to detect passion fruit in complex environments (e.g., with backlighting, occlusion, overlap, sun, cloud, or rain). First, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computational complexity while improving the detection speed. Second, a new feature branch is added to the backbone network and the feature fusion layer in the neck network is reconstructed to effectively combine the lower- and higher-level features, which improves the accuracy of the model while maintaining its lightweight nature. Finally, a knowledge distillation method is used to transfer knowledge from the more capable teacher model to the less capable student model, significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than that of the original YOLOv5s model. Furthermore, the model size is 7.14 MB, half that of the original model, and its real-time detection frame rate is 11.25 FPS when implemented on the Jetson Nano. The proposed model is found to outperform state-of-the-art models in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruit in complex orchard scenes, offering valuable technical support for the development of orchard picking robots and greatly improving the intelligence level of orchards.

Off-Axis Integral Cavity Carbon Dioxide Gas Sensor Based on Machine-Learning-Based Optimization.

Accurately detecting atmospheric carbon dioxide is a vital part of responding to the global greenhouse effect. Conventional off-axis integral cavity detection systems are computationally intensive and susceptible to environmental factors. This study deploys an Extreme Learning Machine model incorporating a cascaded integrator comb (CIC) filter into the off-axis integrating cavity. It is shown that appropriate parameters can effectively improve the performance of the instrument in terms of lower detection limit, accuracy, and root mean square deviation. The proposed method is incorporated successfully into a monitoring station situated near an industrial area for detecting atmospheric carbon dioxide (CO2) concentration daily.

Research on Internal Damage Identification of Wire Rope Based on Improved VGG Network.

In order to solve the problem of great difficulty in detecting the internal damage of wire rope, this paper proposes a method to improve the VGG model to identify the internal damage of wire rope. The short-time Fourier transform method is used to transform the wire rope damage signal into a time-frequency spectrogram as the model input, and then the traditional VGG model is improved from three aspects: firstly, the attention mechanism module is introduced to increase the effective feature weights, which effectively improves the recognition accuracy; and then, the batch normalization layer is added to carry out a uniform normalization of the data, so as to make the model easier to converge. At the same time, the pooling layer and the fully connected layer are improved to solve the redundancy problem of the traditional VGG network model, which makes the model structure more lightweight, greatly saves the computational cost, shortens the training time, and finally adopts the joint-sample uniformly distributed cross-entropy as the loss function to solve the overfitting problem and further improve the recognition rate. The experimental results show that the improved VGG model has an identification accuracy of up to 98.84% for the internal damage spectrogram of the wire rope, which shows a good identification ability. Not only that, but the model is also superior, with less time-consuming training and stronger generalization ability.

Magnon-Skyrmion Hybrid Quantum Systems: Tailoring Interactions via Magnons.

Coherent and dissipative interactions between different quantum systems are essential for the construction of hybrid quantum systems and the investigation of novel quantum phenomena. Here, we propose and analyze a magnon-skyrmion hybrid quantum system, consisting of a micromagnet and nearby magnetic skyrmions. We predict a strong-coupling mechanism between the magnonic mode of the micromagnet and the quantized helicity degree of freedom of the skyrmion. We show that with this hybrid setup it is possible to induce magnon-mediated nonreciprocal interactions and responses between distant skyrmion qubits or between skyrmion qubits and other quantum systems like superconducting qubits. This work provides a quantum platform for the investigation of diverse quantum effects and quantum information processing with magnetic microstructures.

GhHDZ76, a cotton HD-Zip transcription factor, involved in regulating the initiation and early elongation of cotton fiber development in G. hirsutum.

In this study, the whole HD-Zip family members of G. hirsutum were identified, and GhHDZ76 was classified into the HD-Zip IV subgroup. GhHDZ76 was predominantly expressed in the 0-5 DPA of fiber development stage and localized in the nucleus. Overexpression of GhHDZ76 significantly increased the length and density of trichomes in Arabidopsis thaliana. The fiber length of GhHDZ76 knockout lines by CRISPR/Cas9 was significantly shorter than WT at the early elongation and mature stage, indicating that GhHDZ76 positively regulate the fiber elongation. Scanning electron microscopy showed that the number of ovule surface protrusion of 0 DPA of GhHDZ76 knockout lines was significantly lower than WT, suggesting that GhHDZ76 can also promote the initiation of fiber development. The transcript level of GhWRKY16, GhRDL1, GhEXPA1 and GhMYB25 genes related to fiber initiation and elongation in GhHDZ76 knockout lines were significantly decreased. Yeast two-hybrid and Luciferase complementation imaging (LCI) assays showed that GhHDZ76 can interact with GhWRKY16 directly. As a transcription factor, GhHDZ76 has transcriptional activation activity, which could bind to L1-box elements of the promoters of GhRDL1 and GhEXPA1. Double luciferase reporter assay showed that the GhWRKY16 could enhance the transcriptional activity of GhHDZ76 to pGhRDL1, but it did not promote the transcriptional activity of GhHDZ76 to pGhEXPA1. GhHDZ76 protein may also promote the transcriptional activity of GhWRKY16 to the downstream target gene GhMYB25. Our results provided a new gene resource for fiber development and a theoretical basis for the genetic improvement of cotton fiber quality.

Cortical lipid metabolic pathway alteration of early Alzheimer's disease and candidate drugs screen.

BACKGROUND: Lipid metabolism changes occur in early Alzheimer's disease (AD) patients. Yet little is known about metabolic gene changes in early AD cortex. METHODS: The lipid metabolic genes selected from two datasets (GSE39420 and GSE118553) were analyzed with enrichment analysis. Protein-protein interaction network construction and correlation analyses were used to screen core genes. Literature analysis and molecular docking were applied to explore potential therapeutic drugs. RESULTS: 60 lipid metabolic genes differentially expressed in early AD patients' cortex were screened. Bioinformatics analyses revealed that up-regulated genes were mainly focused on mitochondrial fatty acid oxidation and mediating the activation of long-chain fatty acids, phosphoproteins, and cholesterol metabolism. Down-regulated genes were mainly focused on lipid transport, carboxylic acid metabolic process, and neuron apoptotic process. Literature reviews and molecular docking results indicated that ACSL1, ACSBG2, ACAA2, FABP3, ALDH5A1, and FFAR4 were core targets for lipid metabolism disorder and had a high binding affinity with compounds including adenosine phosphate, oxidized Photinus luciferin, BMS-488043, and candidate therapeutic drugs especially bisphenol A, benzo(a)pyrene, ethinyl estradiol. CONCLUSIONS: AD cortical lipid metabolism disorder was associated with the dysregulation of the PPAR signaling pathway, glycerophospholipid metabolism, adipocytokine signaling pathway, fatty acid biosynthesis, fatty acid degradation, ferroptosis, biosynthesis of unsaturated fatty acids, and fatty acid elongation. Candidate drugs including bisphenol A, benzo(a)pyrene, ethinyl estradiol, and active compounds including adenosine phosphate, oxidized Photinus luciferin, and BMS-488043 have potential therapeutic effects on cortical lipid metabolism disorder of early AD.

COL8A1 Regulates Esophageal Squamous Carcinoma Proliferation and Invasion Through PI3K/AKT Pathway.

PURPOSE: Esophageal squamous carcinoma (ESCC) is a gastrointestinal malignancy with a high mortality, but the tumorigenesis is still unclear, restricting the target therapy development of ESCC. We explored the role of COL8A1 in ESCC development. METHODS: Tissue microarrays were used to investigate the expression level of COL8A1 in ESCC tissues. The association between COL8A1 and the overall survival of ESCC patients was assessed. The effect of differential COL8A1 expression on tumor growth was investigated by the xenograft model. The regulation of COL8A1 on tumor growth, migration, and invasion was studied by using ESCC cell lines. The signal transduction pathways involved in COL8A1 were bioinformatically profiled and validated. RESULTS: The COL8A1 was significantly expressed in cancerous tissues and was associated with poor prognosis in patients with ESCC. In vivo, the tumor growth obviously declined after inhibition of the COL8A1 expression. The abilities of cell proliferation and invasion were both decreased when the expression of COL8A1 was knockdown in ESCC cell line. Furthermore, we found the inactivation of the PI3K/AKT pathway that was mediated by knockdown of COL8A1 in ESCC cells, which was reversed with COL8A1 overexpression, whereas the cell proliferation and invasion ability were restored. CONCLUSIONS: This is the first report that COL8A1 promote ESCC progression, which hopefully will provide a theoretical basis for clinical targeting of ESCC.

Correlation between birefringence and absorption mapping in large-size Sapphire substrates for gravitational-wave interferometry.

In high-sensitive laser interferometers, such as the gravitational-wave detector KAGRA, ultra-high-quality mirrors are essential. In the case of KAGRA, where cavity mirrors are cooled down to 20 K, large-size Sapphire crystals are used as the substrate for the main mirrors to achieve both a good optical quality (i.e., low absorption and uniform refractive index) and optimized thermal behavior under cryogenic temperatures. To implement the very tight optical specifications required by this demanding application, it is mandatory to test the optical homogeneity of different substrates. In order to characterize refractive-index inhomogeneities of large-size uniaxial samples such as the KAGRA Sapphire test masses, we developed a dedicated setup, allowing to resolve birefringence changes with a sensitivity in the order of [Formula: see text] and a spatial resolution of [Formula: see text]. Moreover, the same setup allows us to simultaneously record residual absorption maps, thus allowing for a comparison between birefringence and absorption features. In this paper, we will present for the first time measurements on a KAGRA-sized Sapphire substrate which has been characterized in terms of absorption already in an earlier work. Both birefringence inhomogeneities and absorption distributions will be compared and correlations discussed.

Model-based reinforcement learning with non-Gaussian environment dynamics and its application to portfolio optimization.

The rapid development of quantitative portfolio optimization in financial engineering has produced promising results in AI-based algorithmic trading strategies. However, the complexity of financial markets poses challenges for comprehensive simulation due to various factors, such as abrupt transitions, unpredictable hidden causal factors, and heavy tail properties. This paper aims to address these challenges by employing heavy-tailed preserving normalizing flows to simulate the high-dimensional joint probability of the complex trading environment under a model-based reinforcement learning framework. Through experiments with various stocks from three financial markets (Dow, NASDAQ, and S&P), we demonstrate that Dow outperforms the other two based on multiple evaluation metrics in our testing system. Notably, our proposed method mitigates the impact of unpredictable financial market crises during the COVID-19 pandemic, resulting in a lower maximum drawdown. Additionally, we explore the explanation of our reinforcement learning algorithm, employing the pattern causality method to study interactive relationships among stocks, analyzing dynamics of training for loss functions to ensure convergence, visualizing high-dimensional state transition data with t-SNE to uncover effective patterns for portfolio optimization, and utilizing eigenvalue analysis to study convergence properties of the environment's model.

Few-photon isolation in a one-dimensional waveguide using chiral quantum coupling.

We investigated the transmission of single and two photons in a one-dimensional waveguide that is coupled with a Kerr micro-ring resonator and a polarized quantum emitter. In both cases, a phase shift occurs, and the non-reciprocal behavior of the system is attributed to the unbalanced coupling between the quantum emitter and the resonator. Our analytical solutions and numerical simulations demonstrate that the nonlinear resonator scattering causes the energy redistribution of the two photons through the bound state. When the system is in the two-photon resonance state, the polarization of the correlated two photons is locked to their propagation direction, leading to non-reciprocity. As a result, our configuration can act as an optical diode.

Reconstruction of heavy metal(loid) pollution history based on dendrochemistry in Jiuzhaigou World Natural Heritage site, southwestern China.

Heavy metal(loid)s are widely regarded as important environmental pollutants and have attracted extensive attention. In addition to such areas with frequent human activities as cities and industrial areas, the heavy metal(loid) pollution in remote areas lacking long-term monitoring data also deserves attention. In this study, Chinese pine (Pinus tabuliformis) in Jiuzhaigou World Natural Heritage was sampled to analyze concentration of Pb, Zn, Cu, As, Cd, Co, Cr, and Ni and to reconstruct pollution history. Source analysis and evaluation of the potential ecological risk of heavy metal(loid)s were also performed. Results showed that Jiuzhaigou has been polluted by heavy metal(loid)s at a relatively high level and concentrations were the highest at the location with intensive human activities (Nuorilang). Tree growth was inhibited by increased heavy metal(loid) concentration and this situation was more pronounced at high concentrations. The increased heavy metal(loid) concentrations were attributed to human activities such as forest logging, infrastructure construction, and tourism development. Heavy metal(loid) pollution reached a very high level of ecological harm at Nuorilang and a high level of ecological harm in Shuzheng and Heye villages. Overall, even at low concentrations, we demonstrated that Chinese pine can be used not only as a bioindicator for heavy metal(loid) pollution but also to infer pollution history over a relative long-term period and to enhance our understanding of the biogeochemical cycle of heavy metal(loid)s in forest ecosystems.

Hybrid Ligand Polymerization for Weakly Confined Lead Halide Perovskite Quantum Dots.

Rational ligand passivation is essential to achieve a higher performance of weakly confined lead halide perovskite quantum dots (PQDs) via a mechanism of surface chemistry and/or microstrain. In situ passivation with 3-mercaptopropyltrimethoxysilane (MPTMS) produces CsPbBr3 PQDs with an enhanced photoluminescence quantum yield (PLQY, ΦPL) of up to 99%; meanwhile, charge transport of the PQD film can be enhanced by one order of magnitude. Herein, we examine the effect of the molecular structure of MPTMS as the ligand exchange agent in comparison to octanethiol. Both thiol ligands promote crystal growth of PQDs, inhibit nonradiative recombination, and cause blue-shifted PL, while the silane moiety of MPTMS manipulates surface chemistry and outperforms owing to its unique cross-linking chemistry characterized by FTIR vibrations at 908 and 1641 cm-1. Emergence of the diagnostic vibrations is ascribed to hybrid ligand polymerization arising from the silyl tail group that confers the advantages of narrower size dispersion, lower shell thickness, more static surface binding, and higher moisture resistance. In contrast, the superior electrical property of the thiol-passivated PQDs is mostly determined by the covalent S-Pb bonding on the interface.

Enhanced Tripartite Interactions in Spin-Magnon-Mechanical Hybrid Systems.

Coherent tripartite interactions among degrees of freedom of completely different nature are instrumental for quantum information and simulation technologies, but they are generally difficult to realize and remain largely unexplored. Here, we predict a tripartite coupling mechanism in a hybrid setup comprising a single nitrogen-vacancy (NV) center and a micromagnet. We propose to realize direct and strong tripartite interactions among single NV spins, magnons, and phonons via modulating the relative motion between the NV center and the micromagnet. Specifically, by introducing a parametric drive (two-phonon drive) to modulate the mechanical motion (such as the center-of-mass motion of a NV spin in diamond trapped in an electrical trap or a levitated micromagnet in a magnetic trap), we can obtain a tunable and strong spin-magnon-phonon coupling at the single quantum level, with up to 2 orders of magnitude enhancement for the tripartite coupling strength. This enables, for example, tripartite entanglement among solid-state spins, magnons, and mechanical motions in quantum spin-magnonics-mechanics with realistic experimental parameters. This protocol can be readily implemented with the well-developed techniques in ion traps or magnetic traps and could pave the way for general applications in quantum simulations and information processing based on directly and strongly coupled tripartite systems.

Declining tree growth rates despite increasing water-use efficiency under elevated CO2 reveals a possible global overestimation of CO2 fertilization effect.

Though rising atmospheric CO2 concentrations (Ca) harm the environment and society, they may also raise photosynthetic rates and enhance intrinsic water-use efficiency (iWUE). Numerous short-term studies have investigated tree growth under elevated CO2 (eCO2) conditions, but no long-duration study has investigated eCO2 impacts on tree growth and iWUE under natural conditions. Utilizing a new dendrochronological experimental design in a heavily-touristed nature preserve in Southwest China (Jiuzhaigou National Nature Reserve), we compared tree growth (e.g., basal area increment) and iWUE in two biophysically and environmentally similar valleys with contrasting anthropogenic activities. Trees in the control valley with ambient CO2 benefited from increasing Ca, possibly due to the CO2 fertilization effect and optimal environmental conditions. However, trees in the treatment valley with intensive tourism experienced comparatively higher localized eCO2 and growth rate declines. While iWUE increased (1959-2017) in the control (25.3%) and treatment sites (47.8%), declining tree growth rates in the treatment site was likely because comparatively extreme CO2 exposure levels encouraged stomatal closures. As the first long-term study investigating eCO2 impacts on tree growth and iWUE under natural conditions, we demonstrate that increased forest iWUE is unlikely to overcome negative drought stress and rising temperature impacts. Thus, forest potential for mitigating eCO2 and global climate change is likely overestimated, particularly under dry temperate conditions.

Identification of genetic loci for flag-leaf-related traits in wheat (Triticum aestivum L.) and their effects on grain yield.

Flag-leaf-related traits including length (FLL), width (FLW), area (FLA), thickness (FLT), and volume (FLV) of flag leaves are the most important determinants of plant architecture and yield in wheat. Understanding the genetic basis of these traits could accelerate the breeding of high yield wheat varieties. In this study, we constructed a doubled haploid (DH) population and analyzed flag-leaf-related traits in five experimental locations/years using the wheat 90K single-nucleotide polymorphism array. It's worth noting that a novel method was used to measure FLT and FLV easily. Leaf thickness at two-thirds of the leaf length from tip to collar represented the average leaf thickness as measured with freehand sections and was used to calculate the leaf volume. In addition, flag-leaf-related traits showed positive correlations with yield related traits under two different water regimes. A total of 79 quantitative trait loci (QTL) controlling the five traits were detected among all chromosomes except 4D and 5A, explaining 3.09-14.52% of the phenotypic variation. Among them, 15 stable QTL were identified in more than three environments, including two major QTL for FLT, six for FLW, three for FLA, two for FLT and two for FLV. DH lines with positive alleles at both QTL regions had an average FLL (9.90%), FLW (32.87%), FLT (6.62%), FLA (18.47%), and FLV (20.87%) greater than lines with contrasting alleles. QFLT-2B, QFLV-2A, and QFLV-7D were co-located with yield-related traits. The 15 QTL were validated by tightly linked kompetitive allele specific PCR (KASP) markers in a recombinant inbred line (RIL) population derived from a different cross. QFLL-4A, QFLW-4B, QFLA-5D.1, QFLA-7A, QFLA-7D.1, QFLT-2B, QFLT-6A, QFLV-2A, and QFLV-7D are likely novel loci. These results provide a better understanding of the genetic basis underlying flag-leaf-related traits. Also, target regions for fine mapping and marker-assisted selection were identified and these will be valuable for breeding high yielding bread wheat.

[Advances of CRISPR/Cas9 activation system].

Gene editing technology has been a hotspot in the field of biotechnology. CRISPR/Cas systems are efficient gene editing tools because of its specificity, simplicity and flexibility, these features enabled the rapid application of CRISPR/Cas systems in a variety of organisms. Moreover, the combination of transcriptional activator with dead Cas protein can achieve specific regulation of gene expression at the transcription level, which has made important contributions to the development of biotechnology in medical and agriculture. Overexpression of foreign genes is a common method to verify gene function and regulation. However, due to the limitation of vector capacity, it is difficult to achieve overexpression of multiple genes. CRISPR/Cas9 activation system can regulate the expression of multiple genes under the guidance of different guide RNAs to verify gene functions at the regulatory level. This review summarizes the composition of the CRISPR/Cas9 activation system and different activation strategies, and summarizes solutions for excessive activation. It may facilitate the application of CRISPR/Cas9 activation system in genetic improvement of cotton and herbicide resistance research.

Quantitative Identification of Internal and External Wire Rope Damage Based on VMD-AWT Noise Reduction and PSO-SVM.

As a common load-bearing component, mining wire rope produces different types of damage during a long period of operation, especially in the case of damage inside the wire rope, which cannot be identified by the naked eye, and it is difficult to accurately detect such damage using the present technology. In this study we designed a non-destructive testing device based on leakage magnetism, which can effectively detect the internal defects of wire rope damage, and carried out simulation analysis to lay a theoretical foundation for the subsequent experiments. To address the noise reduction problem in the design process, a variational mode decomposition-adaptive wavelet thresholding noise reduction method is proposed, which can improve the signal-to-noise ratio and also calculate the wavelet energy entropy in the reconstructed signal to construct multi-dimensional feature vectors. For the quantitative identification of system damage, a particle swarm optimization-support vector machine algorithm is proposed. Moreover, based on the signal following the noise reduction step, seven different feature vectors, namely, the waveform area, peak value, peak-valley value, wavelet energy entropy classification, and identification of internal and external damage defects, have been determined. The results show that the device can be used to effectively identify internal damage defects. In addition, the comparative analysis showed that the algorithm can reduce the system noise and effectively identify internal and external damage defects with a certain superiority.

Enhancing Wire-Rope Damage Signals Based on a Radial Magnetic Concentrator Bridge Circuit.

Hall-effect sensors are used for the non-destructive testing of wire ropes owing to their low power consumption and high operation frequency. The high-speed operation of wire ropes causes vibration inclination at different frequencies, which makes it difficult to detect the ropes. Considering that the radial signal in the magnetic flux leakage (MFL) detection method can respond to damages to the maximum extent possible, this study proposes a radial magnetic concentrator suitable for the non-destructive testing of wire ropes based on theoretical analysis and transient magnetic field simulations. The concentrator improves the radial magnetic circuit, polymerizes the leakage of the magnetic field in the detection device, and the leakage of the magnetic field of the defect converges at the sensor position of the circumferential array to improve the signal-to-noise ratio of the Hall-effect sensor. In addition, the MFL field is homogenized through the structure of the magnetic concentrator when the wire rope is tilted, which weakens the influence of the vibration tilt of the wire rope on the test results. Finally, the experiments show that the amplitude of the wire-rope damage signal is effectively improved by using the proposed radial magnetic concentration technology, hence being convenient for defect analyses.

Comprehensive identification and expression analysis of CRY gene family in Gossypium.

BACKGROUND: The cryptochromes (CRY) are specific blue light receptors of plants and animals, which play crucial roles in physiological processes of plant growth, development, and stress tolerance. RESULTS: In the present work, a systematic analysis of the CRY gene family was performed on twelve cotton species, resulting in 18, 17, 17, 17, and 17 CRYs identified in five alloteraploid cottons (Gossypium hirsutum, G. barbadense, G. tomentosum, G. mustelinum and G. darwinii), respectively, and five to nine CRY genes in the seven diploid species. Phylogenetic analysis of protein-coding sequences revealed that CRY genes from cottons and Arabidopsis thaliana could be classified into seven clades. Synteny analysis suggested that the homoeolog of G. hirsutum Gh_A02G0384 has undergone an evolutionary loss event in the other four allotetraploid cotton species. Cis-element analysis predicated the possible functions of CRY genes in G. hirsutum. RNA-seq data revealed that Gh_D09G2225, Gh_A09G2012 and Gh_A11G1040 had high expressions in fiber cells of different developmental states. In addition, the expression levels of one (Gh_A03G0120), 15 and nine GhCRY genes were down-regulated following the PEG, NaCl and high-temperature treatments, respectively. For the low-temperature treatment, five GhCRY genes were induced, and five were repressed. These results indicated that most GhCRY genes negatively regulate the abiotic stress treatments. CONCLUSION: We report the structures, domains, divergence, synteny, and cis-elements analyses systematically of G. hirsutum CRY genes. Possible biological functions of GhCRY genes in differential tissues as well as in response to abiotic stress during the cotton plant life cycle were predicted.