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The labor-efficient automation of grafting has been recognized as a key factor in the wider adoption of grafting. In growing cucurbits, the root pruned one-cotyledon grafting method is the most commonly used method with grafting machines. The cutting angle, which affects the matching of the rootstock and scion, is key to the survival of the graft seedling. In the production of cucurbit graft seedlings, the cutting parameters are established based on experience, leading to low grafting success. To determine accurate cutting parameters, the watermelon cv. 'Zaojia84-24′ was used as the scion and the pumpkin cv. 'Zhenzhuang' was used as rootstock, and two one-way experiments investigating the cutting angle of the watermelon scion and the rootstock as factors were conducted. The cutting angle of the rootstock and scion had no significant effect on the xylem reconnection rate or the grafting survival rate. A larger cutting angle for the rootstock and scion led to a delay in the reconnection of the phloem. Different cutting angles for the scion significantly affected the growth of the scion after grafting. Compared with a scion graft cutting angle of 10° (SL), graft cutting angles of 14° (SM) and 20° (SS) led to significantly greater scion dry weights, with increases of 16.00% and 18.61%, respectively. Different cutting angles of the rootstock significantly affected the growth of roots after grafting. Compared with a rootstock graft cutting angle of 10° (RL), graft cutting angles of 17° (RM) and 27° (RS) led to significantly greater root dry weights, with increases of 29.33% and 22.54%, respectively. The results of this study can provide a reference for the design of cutting mechanisms for cucurbit grafting robots, improving the cutting precision of grafting robots. [ABSTRACT FROM AUTHOR]

Diopside, an important component of the crustal and upper mantle, plays an important role in the formation of nephrite. Polysynthetic twinning in natural diopside, especially from skarns, has rarely been systematically researched. Here, the polysynthetic twinning of natural diopside was investigated in two skarn-type nephrite deposits (Niewang and Tatliksu) in Qiemo, Xinjiang, China. Petrographic observations revealed periodic alternations of dark–light lamellae under cross-polarized light and parallel striations under plane-polarized light, whereas backscattered electron images indicated high homogeneity, which suggested a type of mechanical polysynthetic twinning. According to the optical indicatrix, twins were predominantly oriented as a (100)[100] system. Raman spectra and chemical data show that pyroxenes in nephrite are close to the Di end-member with 0.90–1.04 a.p.f.u. Mg and 0.98–1.05 a.p.f.u. Ca. Both diopside and tremolite from Tatliksu contain slightly higher Fe than those from Niewang. Given the seismic origin of mechanical clinopyroxenes twins, twins of studied diopsides are likely to be attributed to Paleozoic-Mesozoic paleoearthquakes in the Altyn Mountain. A shear stress ≥ 140 MPa and a differential stress greater than 280 MPa are suggested as conditions linked to generation of the twinning of diopsides in the nephrite deposits. The replacement of diopside by tremolite along its twin planes highlights the potential gemological implications, as such replacement by tremolite probably facilitated the formation of dense, fine fibre textures in the nephrites. [ABSTRACT FROM AUTHOR]

Convolutional Neural Networks (CNN) have led to promising performance in super-resolution (SR). Most SR methods are trained and evaluated on predefined blur kernel datasets (e.g., bicubic). However, the blur kernel of real-world LR image is much more complex. Therefore, the SR model trained on simulated data becomes less effective when applied to real scenarios. In this paper, we propose a novel super resolution framework based on blur kernel estimation and dual attention mechanism. Our network learns the internal relations from the input image itself, thus the network can quickly adapt to any input image. We add the blur kernel estimation structure into the network, correcting the inaccurate blur kernel to generate high quality images. Meanwhile, we propose a dual attention mechanism to restore the texture details of the image, adaptively adjusting the features of the image by considering the interdependencies both in channel and spatial. The combination of blur kernel estimation and attention mechanism makes our network perform well for complex blur images in practice. Extensive experiments show that our method (KASR) achieves promising accuracy and visual improvements against most existing methods. [ABSTRACT FROM AUTHOR]

The Activator Protein-1 (AP-1) transcription factor (TF) family, composed of a variety of members including c-JUN, c-FOS and ATF, is involved in mediating many biological processes such as proliferation, differentiation and cell death. Since their discovery, the role of AP-1 TFs in cancer development has been extensively analysed. Multiple in vitro and in vivo studies have highlighted the complexity of these TFs, mainly due to their cell-type specific homo- or hetero-dimerization resulting in diverse transcriptional response profiles. However, as a result of the increasing knowledge of the role of AP-1 TFs in disease, these TFs are being recognized as promising therapeutic targets for various malignancies. In this review, we focus on the impact of deregulated expression of AP-1 TFs in CD30-positive lymphomas including Classical Hodgkin Lymphoma and Anaplastic Large Cell Lymphoma. [ABSTRACT FROM AUTHOR]

Doubled haploid (DH) technology is an efficient strategy for producing completely homozygous lines for breeding programs. Mutations in the MATRILINEAL (MTL) phospholipase trigger intraspecific haploid induction in cereals. Although an in vivo haploid induction system based on OsMTL-edited plants has been established in rice (Oryza sativa), DH technology is still limited by other factors, such as haploid identification, which is one of the essential steps required for DH technology. In the study, we addressed this technical challenge by integrating specific molecular and phenotypic markers into rice haploid inducers. We first generated large fragment insertion or deletion mutations within the OsMTL gene and designed a pair of primers flanking the mutational sites to be used as the specific and universal molecular markers between wild-type and Osmtl plants. Next, we screened for hairy leaf as a single dominant trait and integrated it into specific molecular marker-based haploid inducers using the cross and self-cross method. When crossing cytoplasmic male sterile lines with these haploid inducers, we utilized the specific InDel marker and hairy leaf phenotypic marker to identify putative haploids (or double haploids). These putative haploids were further confirmed through ploidy and phenotypic analysis, demonstrating the high efficiency of haploid identification using these markers. The haploid induction rate (HIR) of the developed specific molecular and phenotypic marker-based haploid inducers ranged from 3.7% to 12.5%. We have achieved successful integration of distinct molecular and phenotypic markers into rice haploid inducers. Our advanced marker-based system has significantly enhanced the accuracy of haploid identification, thereby expediting the adoption of DH technology in rice breeding. [ABSTRACT FROM AUTHOR]

Water temperature affects the peak pressure damping of transient flows in viscoelastic pipes. Owing to the viscoelastic properties of pipes, the accuracy of peak pressure damping simulations hinges on both viscoelastic and frictional factors. In simulations, the influence of both factors on peak pressure damping at different water temperatures is unclear. In this study, the Kelvin–Voigt model with both a quasi-steady friction model and modified Brunone model was employed. Based on experimental data, the accuracy of simulated peak pressure damping was verified at four different water temperatures (13.8, 25, 31, and 38.5 °C). From the perspective of energy transfer and dissipation, the influence of viscoelastic and frictional factors on peak pressure damping were clarified, and the applicability of different friction models was determined based on the contributions of viscoelastic and frictional factors to peak pressure damping. The numerical results indicate that the viscoelastic properties of pipes have a greater impact on peak pressure damping than their frictional properties at 25, 31, and 38.5 °C. Higher temperatures result in a delay in the rate of work and a decrease in the frequency of work performed by viscoelastic pipes. Viscoelastic properties play a more important role than frictional ones in calculating peak pressure damping as the water temperature increases. In addition, the one-dimensional quasi-steady friction model can accurately simulate peak pressure damping within a specified water temperature range. [ABSTRACT FROM AUTHOR]

Phosphorite is a nonrenewable strategic resource, a convenient and rapid method of phosphorite grade identification and classification is important to improve phosphate utilization. In this study, Raman spectroscopy has been combined with principal component analysis and hierarchical clustering analysis (PCA-HCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) models for an investigation of different grade phosphorite samples. Both the PCA-HCA and OPLS-DA models showed that different grade phosphorite samples can be clearly distinguished by statistically analyzing the Raman spectra after smoothing, baseline correction, and first derivation. In addition, the S-line study on the OPLS-DA model clearly demonstrated that the symmetrical stretching vibrational mode of phosphate near 960 cm−1 had a much more significant contribution than other vibrational modes for the differentiation of different grade phosphorite samples. [ABSTRACT FROM AUTHOR]

We propose a novel end-to-end image colorization framework which integrates attention mechanism and a learnable adaptive normalization function. In contrast to previous colorization methods that directly generate the whole image, we believe that the color of the significant area determines the quality of the colorized image. The attention mechanism uses the attention map which is obtained by the auxiliary classifier to guide our framework to produce more subtle content and visually pleasing color in salient visual regions. Furthermore, we apply Adaptive Group Instance Normalization (AGIN) function to promote our framework to generate vivid colorized images flexibly, under the circumstance that we consider colorization as a particular style transfer task. Experiments show that our model is superior to previous the state-of-the-art models in coloring foreground objects. [ABSTRACT FROM AUTHOR]