Characterization of the Semi-Permeable Layer in Seed of \u3cem\u3eElymus nutans\u3c/em\u3e

A semi-permeable layer of the seed coat exists in many species which allows controlled water uptake and gas ex-change, while preventing solute transport (Beresniewicz et al. 1995). This layer could act as a barrier to apoplastic permeability and radicle emergence (Salanenka et al. 2009). It could also restrict the tetrazolium viability test and the electrical conductivity vigour test applied to evaluate seed quality (Yan and Wang 2008; Zhou and Wang 2012). An earlier study reported that semi-permeable layers exist in grass species, but recently research has shown that the layer was not found in seeds of oat (He 2011) or tall fescue (Yan 2008). This paper reports the location and chemical composition of a semi-permeable layer and its relationship to the electrical conductivity vigour tests in seeds of Elymus nutans, an important forage grass species widely distributed in Northwestern alpine grasslands China

On Cultivating Senior Middle School Students’ Cross-Cultural Awareness in English Classes

Language is not only an important means for people to communicate, but also an important carrier of cultural heritage. But at the present stage of high school English teaching in China, teachers merely put the emphasis on the basic knowledge of English, such as the vocabulary, grammar and so on, while ignoring cultivating cross-cultural awareness. By empirical methods and the analysis of the survey results, the present study analyzes the reasons and points out some ways to cope with the problem

A Floral Diet Increases the Longevity of the Coccinellid Adalia bipunctata but Does Not Allow Molting or Reproduction

Adalia bipunctata L. (Coleoptera: Coccinellidae) is a generalist aphidophagous coccinellid and an important natural enemy in many agroecosystems including orchards. Coccinellid species have been observed to consume non-prey food like nectar and pollen, but the value of these foods for A. bipunctata is poorly known. The objective of this study was to determine the effect of different prey and non-prey diets on A. bipunctata larval development and adult longevity and fecundity. Larval development was studied on three prey diets: The aphids Dysaphis plantaginea and Myzus persicae and Lepidopteran eggs of Ephestia kuehniella; five flower diets: Matricaria chamomilla, Daucus carota, Fagopyrum esculentum, Anethum graveolens, and Sinapis alba; four pollen diets from three plant species: Typha angustifolia, Malus pumila (two varieties) and A. graveolens; and 1 M solutions of three sugars: glucose, fructose, and sucrose. Adult longevity and fecundity were tested on one prey diet (E. kuhniella eggs), three flower diets (F. esculentum, A. graveolens, and S. alba); the same four pollen diets and three sugar diets with larvae; and finally a mixed diet of sucrose and A. graveolens pollen. A water-only (starvation) control was used for both larval development and adult longevity and fecundity. Adult lipid content was assessed as a measure of how non-prey food affects the ladybeetles' nutritional status. Larvae did not develop beyond the first instar on any of the non-prey diets, but they lived more than twice as long as on F. esculentum and sugar diets than on water. Sugar and flower diets improved A. bipunctata adult longevity (71–92 days and 10–66 days, respectively) over a pure pollen diet (6–7 days). Fecundity was nil on all non-prey diets, and within a normal range on E. kuhniella eggs. The results suggest that pure floral diets do not support A. bipunctata molting or reproduction, but flowering plants can prolong A. bipunctata larval survival and adults longevity considerably when prey are absent. Adults on sugar diets had high lipid content, indicating that sugar feeding can improve overwintering survival. The findings could be used in agroecosystem design, such as the composition of flower strips for optimal functional diversity

Plane grid structure damage location identification by model curvature

AbstractThe mode curvature is good identification effect for one-dimensional beam damage location. The whole plane grid structure modal shape similar to 2D bending plate, also similar to beam in each dimension, therefore, the beam damage location identification by curvature mode method can be improved for plane grid structure. The damage location identification method is established by computation and integration the two directions of the damaged structure modal curvature changes. Through the simulation examples proved the feasibility of this method

Ribosylation Rapidly Induces α-Synuclein to Form Highly Cytotoxic Molten Globules of Advanced Glycation End Products

BACKGROUND: Alpha synuclein (alpha-Syn) is the main component of Lewy bodies which are associated with several neurodegenerative diseases such as Parkinson's disease. While the glycation with D-glucose that results in alpha-Syn misfold and aggregation has been studied, the effects of glycation with D-ribose on alpha-Syn have not been investigated. METHODOLOGY/PRINCIPAL FINDINGS: Here, we show that ribosylation induces alpha-Syn misfolding and generates advanced glycation end products (AGEs) which form protein molten globules with high cytotoxcity. Results from native- and SDS-PAGE showed that D-ribose reacted rapidly with alpha-Syn, leading to dimerization and polymerization. Trypsin digestion and sequencing analysis revealed that during ribosylation the lysinyl residues (K(58), K(60), K(80), K(96), K(97) and K(102)) in the C-terminal region reacted more quickly with D-ribose than those of the N-terminal region. Using Western blotting, AGEs resulting from the glycation of alpha-Syn were observed within 24 h in the presence of D-ribose, but were not observed in the presence of D-glucose. Changes in fluorescence at 410 nm demonstrated again that AGEs were formed during early ribosylation. Changes in the secondary structure of ribosylated alpha-Syn were not clearly detected by CD spectrometry in studies on protein conformation. However, intrinsic fluorescence at 310 nm decreased markedly in the presence of D-ribose. Observations with atomic force microscopy showed that the surface morphology of glycated alpha-Syn looked like globular aggregates. thioflavin T (ThT) fluorescence increased during alpha-Syn incubation regardless of ribosylation. As incubation time increased, ribosylation of alpha-Syn resulted in a blue-shift (approximately 100 nm) in the fluorescence of ANS. The light scattering intensity of ribosylated alpha-Syn was not markedly different from native alpha-Syn, suggesting that ribosylated alpha-Syn is present as molten protein globules. Ribosylated products had a high cytotoxicity to SH-SY5Y cells, leading to LDH release and increase in the levels of reactive oxygen species (ROS). CONCLUSIONS/SIGNIFICANCE: alpha-Syn is rapidly glycated in the presence of D-ribose generating molten globule-like aggregations which cause cell oxidative stress and result in high cytotoxicity

Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP

Open-vocabulary segmentation is a challenging task requiring segmenting and recognizing objects from an open set of categories. One way to address this challenge is to leverage multi-modal models, such as CLIP, to provide image and text features in a shared embedding space, which bridges the gap between closed-vocabulary and open-vocabulary recognition. Hence, existing methods often adopt a two-stage framework to tackle the problem, where the inputs first go through a mask generator and then through the CLIP model along with the predicted masks. This process involves extracting features from images multiple times, which can be ineffective and inefficient. By contrast, we propose to build everything into a single-stage framework using a shared Frozen Convolutional CLIP backbone, which not only significantly simplifies the current two-stage pipeline, but also remarkably yields a better accuracy-cost trade-off. The proposed FC-CLIP, benefits from the following observations: the frozen CLIP backbone maintains the ability of open-vocabulary classification and can also serve as a strong mask generator, and the convolutional CLIP generalizes well to a larger input resolution than the one used during contrastive image-text pretraining. When training on COCO panoptic data only and testing in a zero-shot manner, FC-CLIP achieve 26.8 PQ, 16.8 AP, and 34.1 mIoU on ADE20K, 18.2 PQ, 27.9 mIoU on Mapillary Vistas, 44.0 PQ, 26.8 AP, 56.2 mIoU on Cityscapes, outperforming the prior art by +4.2 PQ, +2.4 AP, +4.2 mIoU on ADE20K, +4.0 PQ on Mapillary Vistas and +20.1 PQ on Cityscapes, respectively. Additionally, the training and testing time of FC-CLIP is 7.5x and 6.6x significantly faster than the same prior art, while using 5.9x fewer parameters. FC-CLIP also sets a new state-of-the-art performance across various open-vocabulary semantic segmentation datasets. Code at https://github.com/bytedance/fc-clipComment: code and model available at https://github.com/bytedance/fc-cli

Diagnostic value of shear wave elastography combined with super microvascular imaging for BI-RADS 3-5 nodules

BackgroundTo investigate the diagnostic value of shear wave elastography (SWE) and super microvascular imaging (SMI) integrated with the traditional ultrasound breast imaging reporting and data system (BI-RADS) classification in differentiating between benign and malignant breast nodules.MethodsFor analysis, 88 patients with 110 breast nodules assessed as BI-RADS 3-5 by conventional ultrasound were selected. SWE and SMI evaluations were conducted separately, and all nodules were verified as benign or malignant ones by pathology. Receiver operating characteristic (ROC) curves were plotted after obtaining quantitative parameters of different shear waves of nodules, including maximum (Emax), mean (Emean), minimum (Emin) Young’s modulus, modulus standard deviation (SD), and modulus ratio (Eratio). The best cut-off value, specificity, sensitivity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) for diagnosing malignant nodules employing Emax were obtained, and the diagnostic value of combining Emax and BI-RADS classification was compared. SMI graded nodule based on the Alder blood flow grading standard, whereas the BI-RADS classification was based on microvascular morphology. We assessed the diagnostic value of SMI for breast nodules and investigated the diagnostic efficacy of SWE combined with SMI in differentiating benign and malignant breast nodules with BI-RADS classification 3–5.ResultsThe adjusted the BI-RADS classification using SMI and SWE technologies promoted the sensitivity, specificity, and accuracy of discriminating benign and malignant breast nodules (P < 0.05). The combination of traditional ultrasound BI-RADS classification with SWE and SMI technologies offered high sensitivity, specificity, accuracy, PPV, and NPV for identifying benign and malignant breast lesions. Moreover, combining SWE and SMI technologies with the adjusted BI-RADS classificationhad the best diagnostic efficacy for distinguishing benign and malignant breast nodules with BI-RADS 3–5.ConclusionThe combination of SWE and SMI with the adjusted BI-RADS classification is a promising diagnostic method for differentiating benign and malignant breast nodules

MaXTron: Mask Transformer with Trajectory Attention for Video Panoptic Segmentation

Video panoptic segmentation requires consistently segmenting (for both `thing' and `stuff' classes) and tracking objects in a video over time. In this work, we present MaXTron, a general framework that exploits Mask XFormer with Trajectory Attention to tackle the task. MaXTron enriches an off-the-shelf mask transformer by leveraging trajectory attention. The deployed mask transformer takes as input a short clip consisting of only a few frames and predicts the clip-level segmentation. To enhance the temporal consistency, MaXTron employs within-clip and cross-clip tracking modules, efficiently utilizing trajectory attention. Originally designed for video classification, trajectory attention learns to model the temporal correspondences between neighboring frames and aggregates information along the estimated motion paths. However, it is nontrivial to directly extend trajectory attention to the per-pixel dense prediction tasks due to its quadratic dependency on input size. To alleviate the issue, we propose to adapt the trajectory attention for both the dense pixel features and object queries, aiming to improve the short-term and long-term tracking results, respectively. Particularly, in our within-clip tracking module, we propose axial-trajectory attention that effectively computes the trajectory attention for tracking dense pixels sequentially along the height- and width-axes. The axial decomposition significantly reduces the computational complexity for dense pixel features. In our cross-clip tracking module, since the object queries in mask transformer are learned to encode the object information, we are able to capture the long-term temporal connections by applying trajectory attention to object queries, which learns to track each object across different clips. Without bells and whistles, MaXTron demonstrates state-of-the-art performances on video segmentation benchmarks.Comment: Code at https://github.com/TACJu/MaXTro