Effects of Autonomous Learning Software on Chinese Learners’ English Performance and Course Assessment

Based on the construction of an autonomous learning platform for college English learners, a one-year teaching reform experiment has been carried out and 204 subjects were involved. Data collection was conducted mainly through questionnaires and the subjects’ autonomous learning achievements, regular grades, final exam performance, and English listening achievements. The software SPSS17.0 was applied to analyze those data. The results reveal that the experimental class’ achievements on the self-learning platform are positively correlated with their achievements in the final examination. In addition, the correlation between the experimental class’ regular grades and final exam performance is more statistically significant than the control class; moreover, the experimental class performed significantly better than the control class in the English listening test. The vast majority of the students in the experimental class hold positive attitudes towards the software; however, there is still some room to improve it

The Effects of Cooperative Teaching Reform on Chinese English Learners’ Linguistic Abilities and Non-linguistic Abilities

This paper studies the different effects of co-teaching and traditional teaching on students’ English linguistic abilities and non-linguistic abilities in Chinese context. Ninety-one non-English majors in a college in south-eastern China were involved in this experiment. The results of one-way ANOVA showed that the effects of Chinese-foreign teachers’ cooperative teaching on participants’ linguistic abilities were significantly better than the traditional Chinese teachers’ teaching. The results of questionnaires revealed that co-teaching made a greater contribution to students’ non-linguistic abilities than the traditional way did. In addition, students held more positive attitudes to co-teaching than the traditional teaching. Finally, reasons that may lead to the results have been discussed

End-to-End Learning for Simultaneously Generating Decision Map and Multi-Focus Image Fusion Result

The general aim of multi-focus image fusion is to gather focused regions of different images to generate a unique all-in-focus fused image. Deep learning based methods become the mainstream of image fusion by virtue of its powerful feature representation ability. However, most of the existing deep learning structures failed to balance fusion quality and end-to-end implementation convenience. End-to-end decoder design often leads to unrealistic result because of its non-linear mapping mechanism. On the other hand, generating an intermediate decision map achieves better quality for the fused image, but relies on the rectification with empirical post-processing parameter choices. In this work, to handle the requirements of both output image quality and comprehensive simplicity of structure implementation, we propose a cascade network to simultaneously generate decision map and fused result with an end-to-end training procedure. It avoids the dependence on empirical post-processing methods in the inference stage. To improve the fusion quality, we introduce a gradient aware loss function to preserve gradient information in output fused image. In addition, we design a decision calibration strategy to decrease the time consumption in the application of multiple images fusion. Extensive experiments are conducted to compare with 19 different state-of-the-art multi-focus image fusion structures with 6 assessment metrics. The results prove that our designed structure can generally ameliorate the output fused image quality, while implementation efficiency increases over 30\% for multiple images fusion.Comment: repor

Izraženost surfaktantnog proteina B u bronhoalveolarnom ispirku terminske novorođenčadi sa sindromom respiracijskog distresa

The aim was to investigate the surfactant protein B (SP-B) expression in the bronchoalveolar lavage fluid (BALF ) of full-term neonates with respiratory distress syndrome (RD S). The enzyme-linked immunosorbent assay was performed to assess SP-B expression in BALF of 60 full-term neonates with RD S and 23 healthy neonates and correlation of SP-B level with RD S classification according to chest x-ray findings and PaO2/FiO2 before mechanical ventilation in neonates with RD S. The SP-B level was significantly lower in the RD S group (17.63±6.80 ng/mL) than in healthy neonates (103.95±6.38 ng/mL) (P<0.001). The SP-B level correlated positively with PaO2/ FiO2 before mechanical ventilation (r=0.838, P<0.001). Moreover, the lower the SP-B level, the more severe was the RD S as determined by chest x-ray (P<0.001). In conclusion, full-term neonates with RD S had reduced SP-B in BALF , which was related to the severity of RD S, suggesting that SP-B supplement may be an effective strategy in the treatment of RD S in full-term neonates.Cilj studije bio je ispitati izraženost surfaktantnog proteina B (SP-B) u bronhoalveolarnom ispirku (BALF ) terminske novorođenčadi sa sindromom respiracijskog distresa (SRD ). Izraženost SP-B određena je testom ELI SA u BALF 60 terminske novorođenčadi sa SRD i 23 zdrave novorođenčadi. Utvrđena je korelacija razine SP-B s klasifikacijom SRD prema rendgenskoj snimci prsišta i vrijednosti PaO2/FiO2 prije mehaničke ventilacije u novorođenčadi sa SRD . U skupini novorođenčadi sa SRD razina SP-B bila je značajno niža (17,63±6,80 ng/mL) od one u zdrave novorođenčadi (103,95±6,38 ng/ mL) (P<0,001). Utvrđena je pozitivna korelacija razine SP-B i PaO2/FiO2 prije mehaničke ventilacije (r=0,838, P<0,001). Štoviše, što je bila niža razina SP-B, to je teži bio SRD procijenjen prema rendgenskoj snimci prsišta (P<0,001). Zaključuje se da terminska novorođenčad sa SRD ima sniženu razinu SP-B u BALF i to je povezano s težinom SRD . Ovi nalazi ukazuju na to da bi dodatak SP-B mogla biti učinkovita strategija u liječenju SRD kod terminske novorođenčadi

Optimized sample preparation for two-dimensional gel electrophoresis of soluble proteins from chicken bursa of Fabricius

<p>Abstract</p> <p>Background</p> <p>Two-dimensional gel electrophoresis (2-DE) is a powerful method to study protein expression and function in living organisms and diseases. This technique, however, has not been applied to avian bursa of Fabricius (BF), a central immune organ. Here, optimized 2-DE sample preparation methodologies were constructed for the chicken BF tissue. Using the optimized protocol, we performed further 2-DE analysis on a soluble protein extract from the BF of chickens infected with virulent avibirnavirus. To demonstrate the quality of the extracted proteins, several differentially expressed protein spots selected were cut from 2-DE gels and identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS).</p> <p>Results</p> <p>An extraction buffer containing 7 M urea, 2 M thiourea, 2% (w/v) 3-[(3-cholamidopropyl)-dimethylammonio]-1-propanesulfonate (CHAPS), 50 mM dithiothreitol (DTT), 0.2% Bio-Lyte 3/10, 1 mM phenylmethylsulfonyl fluoride (PMSF), 20 U/ml Deoxyribonuclease I (DNase I), and 0.25 mg/ml Ribonuclease A (RNase A), combined with sonication and vortex, yielded the best 2-DE data. Relative to non-frozen immobilized pH gradient (IPG) strips, frozen IPG strips did not result in significant changes in the 2-DE patterns after isoelectric focusing (IEF). When the optimized protocol was used to analyze the spleen and thymus, as well as avibirnavirus-infected bursa, high quality 2-DE protein expression profiles were obtained. 2-DE maps of BF of chickens infected with virulent avibirnavirus were visibly different and many differentially expressed proteins were found.</p> <p>Conclusion</p> <p>These results showed that method C, in concert extraction buffer IV, was the most favorable for preparing samples for IEF and subsequent protein separation and yielded the best quality 2-DE patterns. The optimized protocol is a useful sample preparation method for comparative proteomics analysis of chicken BF tissues.</p

Insulin Attenuates Beta-Amyloid-Associated Insulin/Akt/EAAT Signaling Perturbations in Human Astrocytes

The excitatory amino acid transporters 1 and 2 (EAAT1 and EAAT2), mostly located on astrocytes, are the main mediators for glutamate clearance in humans. Malfunctions of these transporters may lead to excessive glutamate accumulation and subsequent excitotoxicity to neurons, which has been implicated in many kinds of neurodegenerative disorders including Alzheimer’s disease (AD). Yet, the specific mechanism of the glutamate system dysregulation remains vague. To explore whether the insulin/protein kinase B (Akt)/EAAT signaling in human astrocytes could be disturbed by beta-amyloid protein (Aβ) and be protected by insulin, we incubated HA-1800 cells with varying concentrations of Aβ1–42 oligomers and insulin. Then the alterations of several key substrates in this signal transduction pathway were determined. Our results showed that expressions of insulin receptor, phospho-insulin receptor, phospho-protein kinase B, phospho-mammalian target of rapamycin, and EAAT1 and EAAT2 were decreased by the Aβ1–42 oligomers in a dose-dependent manner (p 0.05), and the mRNA levels of EAAT1 and EAAT2 were also unchanged (p > 0.05). Taken together, this study indicates that Aβ1–42 oligomers could cause disturbances in insulin/Akt/EAAT signaling in astrocytes, which might be responsible for AD onset and progression. Additionally, insulin can exert protective functions to the brain by modulating protein modifications or expressions

Exploring the potential common denominator pathogenesis of system lupus erythematosus with COVID-19 based on comprehensive bioinformatics analysis

ObjectiveEvidences show that there may be a link between SLE and COVID-19. The purpose of this study is to screen out the diagnostic biomarkers of systemic lupus erythematosus (SLE) with COVID-19 and explore the possible related mechanisms by the bioinformatics approach.MethodsSLE and COVID-19 datasets were extracted separately from the NCBI Gene Expression Omnibus (GEO) database. The limma package in R was used to obtain the differential genes (DEGs). The protein interaction network information (PPI) and core functional modules were constructed in the STRING database using Cytoscape software. The hub genes were identified by the Cytohubba plugin, and TF-gene together with TF-miRNA regulatory networks were constructed via utilizing the Networkanalyst platform. Subsequently, we generated subject operating characteristic curves (ROC) to verify the diagnostic capabilities of these hub genes to predict the risk of SLE with COVID-19 infection. Finally, a single-sample gene set enrichment (ssGSEA) algorithm was used to analyze immune cell infiltration.ResultsA total of 6 common hub genes (CDC6, PLCG1, KIF15, LCK, CDC25C, and RASGRP1) were identified with high diagnostic validity. These gene functional enrichments were mainly involved in cell cycle, and inflammation-related pathways. Compared to the healthy controls, abnormal infiltration of immune cells was found in SLE and COVID-19, and the proportion of immune cells linked to the 6 hub genes.ConclusionOur research logically identified 6 candidate hub genes that could predict SLE complicated with COVID-19. This work provides a foothold for further study of potential pathogenesis in SLE and COVID-19