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Wheat scab can reduce wheat yield and quality. Currently, unmanned aerial vehicles (UAVs) are widely used for monitoring field crops. However, UAV is constrained by limited computational resources on-board the platforms. In addition, compared to ground images, UAV images have complex backgrounds and smaller targets. Given the aforementioned challenges, this paper proposes a lightweight wheat scab detection network based on UAV. In addition, overlapping cropping and image contrast enhancement methods are designed to preprocess UAV remote-sensing images. Additionally, this work constructed a lightweight wheat scab detection network called LWSDNet using mixed deep convolution (MixConv) to monitor wheat scab in field environments. MixConv can significantly reduce the parameters of the LWSDNet network through depthwise convolution and pointwise convolution, and different sizes of kernels can extract rich scab features. In order to enable LWSDNet to extract more scab features, a scab feature enhancement module, which utilizes spatial attention and dilated convolution, is designed to improve the ability of the network to extract scab features. The MixConv adaptive feature fusion module is designed to accurately detect lesions of different sizes, fully utilizing the semantic and detailed information in the network to enable more accurate detection by LWSDNet. During the training process, a knowledge distillation strategy that integrates scab features and responses is employed to further improve the average precision of LWSDNet detection. Experimental results demonstrate that the average precision of LWSDNet in detecting wheat scab is 79.8%, which is higher than common object detection models and lightweight object detection models. The parameters of LWSDNet are only 3.2 million (M), generally lower than existing lightweight object detection networks. [ABSTRACT FROM AUTHOR]

This review explores additive manufacturing (AM) for refractory tungsten (W) and its alloys, highlighting the primary challenges and determining factors in the AM of pure W, W alloys and composites. The challenges mainly arise from W's high melting point, low laser absorptivity, high thermal conductivity, high melt viscosity, high oxygen affinity, high ductile-to-brittle transition temperature, and inherent embrittlement, which lead to defects and anomalies in AM-produced parts. This review focuses on both processes and alloying strategies to address the issues related to densification, micro-cracking, and the resultant properties in W-based components. Cracking in additively manufactured W remains a persistent issue due to thermal stress, embrittlement, and oxide formation. Powder characteristics, process parameters, and thermal management strategies are crucial for W densification. Throughout the review, existing knowledge and insights are organized into comprehensive tables, serving as valuable resources for researchers delving deeper into this topic. Future research in W-AM should focus on understanding the interaction between AM process parameters and microstructural and material design. Advances in atomic-level understanding, thermodynamic modeling, and data analytics have the potential to significantly enhance the precision, sustainability, and applicability of W-AM. [ABSTRACT FROM AUTHOR]

At present, footprint image retrieval based on deep learning mainly focuses on complete footprint, but many of the footprints obtained in the field of public safety and criminal investigation are incomplete forms, Therefore, the feature analysis of incomplete footprint has important practical significance. Based on multiple scale features fusion, we proposed a method to solve incomplete footprints retrieval. On the basis of extracting the global feature of footprint, this method simultaneously extracts multiple local features from different stages of the backbone network to supplement the footprint feature information. The multi-scale feature orthogonal fusion module is used to reduce redundant features, improve the expression ability of footprint features, and solve the problem of incomplete footprint retrieval to a certain extent. The experiment shows that our method has certain effectiveness in retrieving problems on incomplete footprint, with a Top 1 accuracy of 87.08%, expanding the scope of footprint research. [ABSTRACT FROM AUTHOR]

Innate immunity, the first line of host defense against viral infections, recognizes viral components through different pattern-recognition receptors. Nucleic acids derived from viruses are mainly recognized by Toll-like receptors, nucleotide-binding domain leucine-rich repeat-containing receptors, absent in melanoma 2-like receptors, and cytosolic DNA sensors (e.g., Z-DNA-binding protein 1 and cyclic GMP-AMP synthase). Different types of nucleic acid sensors can recognize specific viruses due to their unique structures. PANoptosis is a unique form of inflammatory cell death pathway that is triggered by innate immune sensors and driven by caspases and receptor-interacting serine/threonine kinases through PANoptosome complexes. Nucleic acid sensors (e.g., Z-DNA-binding protein 1 and absent in melanoma 2) not only detect viruses, but also mediate PANoptosis through providing scaffold for the assembly of PANoptosomes. This review summarizes the structures of different nucleic acid sensors, discusses their roles in viral infections by driving PANoptosis, and highlights the crosstalk between different nucleic acid sensors. It also underscores the promising prospect of manipulating nucleic acid sensors as a therapeutic approach for viral infections. [ABSTRACT FROM AUTHOR]

Peptidoglycan hydrolases are enzymes responsible for breaking the peptidoglycan present in the bacterial cell wall, facilitating cell growth, cell division and peptidoglycan turnover. Xanthomonas citri subsp. citri (X. citri), the causal agent of citrus canker, encodes an Escherichia coli M23 peptidase EnvC homolog. EnvC is a LytM factor essential for cleaving the septal peptidoglycan, thereby facilitating the separation of daughter cells. In this study, the investigation focused on EnvC contribution to the virulence and cell separation of X. citri. It was observed that disruption of the X. citri envC gene (ΔenvC) led to a reduction in virulence. Upon inoculation into leaves of Rangpur lime (Citrus limonia Osbeck), the X. citri ΔenvC exhibited a delayed onset of citrus canker symptoms compared with the wild-type X. citri. Mutant complementation restored the wild-type phenotype. Sub-cellular localization confirmed that X. citri EnvC is a periplasmic protein. Moreover, the X. citri ΔenvC mutant exhibited elongated cells, indicating a defect in cell division. These findings support the role of EnvC in the regulation of cell wall organization, cell division, and they clarify the role of this peptidase in X. citri virulence. [ABSTRACT FROM AUTHOR]

Diffusion‐weighted imaging (DWI) is an established MRI technique that can investigate tissue microstructure at the scale of a few micrometers. Musculoskeletal tissues typically have a highly ordered structure to fulfill their functions and therefore represent an optimal application of DWI. Even more since disruption of tissue organization affects its biomechanical properties and may indicate irreversible damage. The application of DWI to the musculoskeletal system faces application‐specific challenges on data acquisition including susceptibility effects, the low T2 relaxation time of most musculoskeletal tissues (2–70 msec) and the need for sub‐millimetric resolution. Thus, musculoskeletal applications have been an area of development of new DWI methods. In this review, we provide an overview of the technical aspects of DWI acquisition including diffusion‐weighting, MRI pulse sequences and different diffusion regimes to study tissue microstructure. For each tissue type (growth plate, articular cartilage, muscle, bone marrow, intervertebral discs, ligaments, tendons, menisci, and synovium), the rationale for the use of DWI and clinical studies in support of its use as a biomarker are presented. The review describes studies showing that DTI of the growth plate has predictive value for child growth and that DTI of articular cartilage has potential to predict the radiographic progression of joint damage in early stages of osteoarthritis. DTI has been used extensively in skeletal muscle where it has shown potential to detect microstructural and functional changes in a wide range of muscle pathologies. DWI of bone marrow showed to be a valuable tool for the diagnosis of benign and malignant acute vertebral fractures and bone metastases. DTI and diffusion kurtosis have been investigated as markers of early intervertebral disc degeneration and lower back pain. Finally, promising new applications of DTI to anterior cruciate ligament grafts and synovium are presented. The review ends with an overview of the use of DWI in clinical routine. Evidence Level: 5 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Summary: Callus formation is important for numerous biological processes in plants. Previously, we revealed that the PdeWRKY75–PdeRBOHB module positively regulates hydrogen peroxide (H2O2) accumulation, thereby affecting callus formation in poplar.In this study, we identified and confirmed a transcription factor, PdeERF114, that interacts with PdeWRKY75 both in vitro and in vivo. Gene expression analysis identified both PdeRBOHB and PdeEXPB2 as downstream genes of PdeERF114 and PdeWRKY75. Overexpression (OE) and reduced‐expression (RE) transgenic poplar lines for these four genes were generated, and the observation of callus formation was also performed in all plant materials.We demonstrated that PdeERF114 and PdeWRKY75 formed a protein complex and that this complex could bind W‐Box motifs in the promoters of PdeRBOHB and PdeEXPB2, thereby positively regulating the expression of PdeRBOHB and PdeEXPB2. The OE/RE transgenic lines for these four genes also showed enhanced/reduced callus formation.Overall, we revealed a novel gene regulatory network for the regulation of callus formation in plants that involves four genes and regulates callus formation through two pathways: the accumulation of H2O2 in explants and the relaxation of cell walls. In the future, the four genes could be used to enhance transformation effectiveness in genetic engineering. [ABSTRACT FROM AUTHOR]

Navel orange cv. Gannanzao is a variant of the navel orange cv. Newhall (Citrus sinensis Osbeck cv. Newhall) that exhibits an earlier maturation, making it commercially valuable. However, the mechanisms underlying its early maturation remain obscure. To address this question, we conducted genome sequencing and de novo assembly of navel orange cv. Gannanzao. The assembled genome sequence is 334.57 Mb in length with a GC content of 31.48%. It comprises 318 contigs (N50 = 3.23 Mb) and 187 scaffolds (N50 = 31.86 Mb). The Benchmarking Universal Single-Copy Orthologs test demonstrates 94.6% completeness. The annotation revealed 23,037 gene models, 164.95 Mb of repetitive sequences, and 2,554 noncoding RNAs. A comparative analysis identified 323 fruit ripening–related genes in navel orange cv. Gannanzao genome, while navel orange cv. Newhall genome contained 345 such genes. These genes were organized into 320 orthologous gene families, with 30.3% of them exhibiting differences in gene copy numbers between the 2 genomes. Additionally, we identified 15 fruit ripening–related genes that have undergone adaptive evolution, suggesting their potential role in advancing fruit maturation in navel orange cv. Gannanzao. Whole-genome sequencing and annotation of navel orange cv. Gannanzao provides a valuable resource to unravel the early maturation mechanism of citrus and enriches the genomic resources for citrus research. [ABSTRACT FROM AUTHOR]

Selective oxidizing agent carbonate radical (CO 3 •- ) is an important secondary radical in radical-based advanced oxidation technology for wastewater treatment. However, the role of CO 3 •- in removing ionizable organic micropollutants (OMs) under environmentally relevant conditions remains unclear. Herein we investigated CO 3 •- effect on degradation kinetics of fluoxetine in UV/peroxymonosulfate (PMS) system based on a built radical model considering CO 3 •- reactivity differences with its different dissociation forms. Results revealed that the model, which incorporated CO 3 •- selective reactivity (with determined second-order rate constants, k src,CO3·- , of 7.33 ×10 6 and 2.56 ×10 8 M -1 s -1 for cationic and neutral fluoxetine, respectively) provided significantly more accurate predictions of fluoxetine degradation rates (k). A good linear correlation was observed between k src,CO3·- from experiments and literatures for 24 ionizable OMs and their molecular orbital energy gaps and oxidation potentials, suggesting the possible electron transfer reaction mechanism. Cl - slightly reduced the degradation rates of fluoxetine owing to rapid transformation of Cl • with HCO 3 - into CO 3 •- , which partially compensated for the quenching effects of Cl - on HO • and SO 4 •- . Dissolved organic matter significantly quenched reactive radicals. The constructed kinetic model successfully predicted fluoxetine degradation rates in real waters, with CO 3 •- being the dominant contributor (∼90 %) to this degradation process., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)