The Washback Effect of Reformed CET 6 Listening Comprehension Test

In China, the English Test Band 6 (CET6) is a national test that is used to assess the English proficiency of test-takers by the state with unified questions, unified fees, and unified organization of tests. It is held twice a year. This test has had a great impact on college students and college teachers. It was introduced in 1978. In 2016, the Ministry of Education reformed CET-6, especially in listening tests. The reformed listening test not only brings scenes and dialogues closer to daily life but also emphasizes the examination of students' comprehensive English listening and speaking ability. From the perspective of learners, this paper draws on the theoretical models and empirical results of washback at home and abroad and studies the backwash of the reformed English CET-6 listening to learners' listening learning through a questionnaire. To do the survey, the paper was surveyed by quantitative research methods with 60 samples in several public universities. After the collection and analysis of data, the authors have affirmed and determined this test has a significant washback effect on student learning

Genetic Variation and Geographical Differentiation of \u3cem\u3eElymus nutans\u3c/em\u3e (Poaceae: Triticeae) from West China

Elymus nutans Griseb. is not only an important alpine forage grass, but also as a crucial gene pool for improving cereal crops. Understanding and maintaining the genetic diversity of the species are essential for both conservation strategy and breeding programs. However, little is known about its genetic and geographical differentiation patterns. E. nutans is a perennial, caespitose and allohexaploid (2n=6x=42) species that contains the St, H and Y genomes. It is native to temperate and tropical Asia, ranging from western and central Asia in the west to China and Mongolia in the east, from Russia in the north to India and the Himalayas areas in the south (Clayton et al. 2006). It is distributed in the north, northwest and southwest China, particularly in the Qinghai-Tibet Plateau. E. nutans is a valuable forage grass in the alpine regions that is resistant to cold, drought and pests, which can be used to improve cereal crops. In addition, it can play an important role in the restoration of disturbed grasslands and the establishment of artificial grasslands, especially at altitudes from 3,000 to 4,500 m (Chen and Jia 2000). During recent decades, its distribution has contracted because of over-exploitation, habitat destruction and fragmentation. Therefore, it is urgent to understand and monitor the genetic and geographical differentiation of wild germplams of E. nutans

Effect of YKL-40 RNA Interference on VEGF Gene Polymorphism Expression in Atherosclerotic Mice

Aims: To investigate the effect of YKL-40 RNA interference on VEGF gene polymorphism expression in atherosclerotic mice. Methods: After the atherosclerosis models in mice were built, the mice were divided into three groups including control group, negative control group and observation group, which were separately given to normal saline, negative virus (5 × 107 TU) and YKL-40 RNA interference lentivirus. Then the whole blood DNA was extracted and genotyped in each group of mice and the expression of VEGF in each group of mice was detected by PCR, while the expression level of inflammatory factors in each group of mice was detected by ELISA. Meanwhile, the aortas of mice in each group were pathologically analyzed and the atherosclerosis of mice was detected. Results: Compared with the control group, the VEGF content in both the virus negative control group and the observation group was significantly increased（P<0.05）. The detection rates of CC genotype and C allele at rs699947 of VEGF gene in the observation group were significantly higher than those in the control group and the virus negative control group, and the difference was statistically significant. There were no significant changes for the expression of HDL-C, LDL-C, TC and TG in mice of each group（P>0.05）. Moreover, the levels of Lp-PLA2 and MCP-1 in the negative control group were significantly increased (P < 0.05), while those in the observation group were significantly decreased (P < 0.05) compared to that in control group. What’s more, the histomorphology of the observation group was significantly different from that of the control group and the virus negative control group. The thickness of the fibrous cap of the as plaque was significantly higher than that of the control group and the virus negative control group, but the plaque area and fat content were significantly lower than that of the control group and the virus negative control group and the NC group. Besides, there was no significant difference in lipid content, fiber cap thickness and plaque area between the control group and the virus negative control group. Conclusion: YKL-40 RNAi could improve the VEGF polymorphism, reduce the expression of LPâƒPLA2 and MCPâƒ1, and significantly inhibit the occurrence and development of atherosclerosis, which was expected to provide a new target for the prevention and treatment of atherosclerosis

Identification of microRNA precursors based on random forest with network-level representation method of stem-loop structure

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play a key role in regulating various biological processes such as participating in the post-transcriptional pathway and affecting the stability and/or the translation of mRNA. Current methods have extracted feature information at different levels, among which the characteristic stem-loop structure makes the greatest contribution to the prediction of putative miRNA precursor (pre-miRNA). We find that none of these features alone is capable of identifying new pre-miRNA accurately.</p> <p>Results</p> <p>In the present work, a pre-miRNA stem-loop secondary structure is translated to a network, which provides a novel perspective for its structural analysis. Network parameters are used to construct prediction model, achieving an area under the receiver operating curves (AUC) value of 0.956. Moreover, by repeating the same method on two independent datasets, accuracies of 0.976 and 0.913 are achieved, respectively.</p> <p>Conclusions</p> <p>Network parameters effectively characterize pre-miRNA secondary structure, which improves our prediction model in both prediction ability and computation efficiency. Additionally, as a complement to feature extraction methods in previous studies, these multifaceted features can reflect natural properties of miRNAs and be used for comprehensive and systematic analysis on miRNA.</p

Experimental investigation into coal wettability changes caused by reactions with scCO2-H2O

Geological CO2 sequestration (GCS) can help mitigate global warming and enhance methane recovery from coal beds. However, few studies have linked the effects of CO2 to surface chemistry changes controlling wetting behavior in deep coal beds. Contact angles (CAs) of CO2/N2-high volatile bituminous coal-water systems were measured under different temperatures and pressures. The surface chemistry and physical structure of coals were characterized to investigate changes in physicochemical properties and their relations with wettability after reactions. For N2 treatment, the time-dependence of static and dynamic CAs were insignificant, ranging within 4°. For gaseous CO2 treatment, the static CAs and the average advancing angles increased slightly. With supercritical (sc) CO2, both the static and dynamic CAs increased significantly, and θ adv changed to intermediate-wet (92°). Reactions with minerals exposed to scCO2 resulted in greater surface roughness and heterogeneity, greater contact angle hysteresis and more surface sites occupied by scCO2 rather than H2O. Increases in hydrophobic functional groups and decreases in hydrophilicity were shown by FTIR spectra, reflecting the shedding of polar oxygen-containing functional groups, reduction of hydrogen bonds, and increasing percentage of hydrocarbons. XRD patterns obtained following scCO2-treatment showed that crystallite growth and molecular polymerization were higher toward graphite-like. The calculated structural parameters of functional groups and crystallites both showed elevated coal rank. Changes in crystallite structure, notably higher carbon content and decreased negative surface charge, are unfavorable for water-wetting. This study contributes to understanding surface chemistry changes responsible for decreased wettability during CO2-enhanced coal bed methane recovery and GCS in coal reservoirs

Differential and Prognostic Significance of HOXB7 in Gliomas

Diffuse glioma is the most common primary tumor of the central nervous system. The prognosis of the individual tumor is heavily dependent on its grade and subtype. Homeobox B7 (HOXB7), a member of the homeobox family, is abnormally overexpressed in a variety of tumors. However, its function in glioma is unclear. In this study, HOXB7 mRNA and protein expression levels were analyzed in 401 gliomas from the CGGA RNA-seq database (325 cases) and our hospital (76 cases). HOXB7 expression, at both mRNA and protein levels, were upregulated in glioblastoma (GBM) and isocitrate dehydrogenase 1 (IDH1) wild-type glioma tissues. Kaplan–Meier with log-rank test showed that patients with high HOXB7 expression had a poor prognosis (p < 0.0001). Moreover, HOXB7 protein was deleted in 90.9% (20/22) of oligodendrogliomas and 13.0% (3/23) of astrocytomas. The sensitivity and specificity of HOXB7 protein deletion in oligodendroglioma were 90.9% (20/22) and 87.0% (20/23), respectively. To verify the reliability of using HOXB7 in differentiating oligodendroglioma, we used 1p/19q fluorescence in situ hybridization (FISH) testing as a positive control. The Cohen’s kappa coefficient of HOXB7 immunohistochemistry staining and 1p/19q FISH testing was 0.778 (95% CI: 0.594–0.962, p < 0.001). In conclusion, HOXB7 is an independent predictor of poor prognosis in all grade gliomas. Additionally, HOXB7 is also a highly sensitive and specific indicator to differentiate oligodendroglioma from astrocytoma

Lightweight tomato ripeness detection algorithm based on the improved RT-DETR

Tomatoes, widely cherished for their high nutritional value, necessitate precise ripeness identification and selective harvesting of mature fruits to significantly enhance the efficiency and economic benefits of tomato harvesting management. Previous studies on intelligent harvesting often focused solely on identifying tomatoes as the target, lacking fine-grained detection of tomato ripeness. This deficiency leads to the inadvertent harvesting of immature and rotten fruits, resulting in economic losses. Moreover, in natural settings, uneven illumination, occlusion by leaves, and fruit overlap hinder the precise assessment of tomato ripeness by robotic systems. Simultaneously, the demand for high accuracy and rapid response in tomato ripeness detection is compounded by the need for making the model lightweight to mitigate hardware costs. This study proposes a lightweight model named PDSI-RTDETR to address these challenges. Initially, the PConv_Block module, integrating partial convolution with residual blocks, replaces the Basic_Block structure in the legacy backbone to alleviate computing load and enhance feature extraction efficiency. Subsequently, a deformable attention module is amalgamated with intra-scale feature interaction structure, bolstering the capability to extract detailed features for fine-grained classification. Additionally, the proposed slimneck-SSFF feature fusion structure, merging the Scale Sequence Feature Fusion framework with a slim-neck design utilizing GSConv and VoVGSCSP modules, aims to reduce volume of computation and inference latency. Lastly, by amalgamating Inner-IoU with EIoU to formulate Inner-EIoU, replacing the original GIoU to expedite convergence while utilizing auxiliary frames enhances small object detection capabilities. Comprehensive assessments validate that the PDSI-RTDETR model achieves an average precision mAP50 of 86.8%, marking a 3.9% enhancement over the original RT-DETR model, and a 38.7% increase in FPS. Furthermore, the GFLOPs of PDSI-RTDETR have been diminished by 17.6%. Surpassing the baseline RT-DETR and other prevalent methods regarding precision and speed, it unveils its considerable potential for detecting tomato ripeness. When applied to intelligent harvesting robots in the future, this approach can improve the quality of tomato harvesting by reducing the collection of immature and spoiled fruits

RealDex: Towards Human-like Grasping for Robotic Dexterous Hand

In this paper, we introduce RealDex, a pioneering dataset capturing authentic dexterous hand grasping motions infused with human behavioral patterns, enriched by multi-view and multimodal visual data. Utilizing a teleoperation system, we seamlessly synchronize human-robot hand poses in real time. This collection of human-like motions is crucial for training dexterous hands to mimic human movements more naturally and precisely. RealDex holds immense promise in advancing humanoid robot for automated perception, cognition, and manipulation in real-world scenarios. Moreover, we introduce a cutting-edge dexterous grasping motion generation framework, which aligns with human experience and enhances real-world applicability through effectively utilizing Multimodal Large Language Models. Extensive experiments have demonstrated the superior performance of our method on RealDex and other open datasets. The complete dataset and code will be made available upon the publication of this work