Mainland Chinese Students in the U.K.: An Investigation Into the Cultural, Linguistic and Financial Barriers in Academic and Social Life

As the title suggests, this was an investigation into the cultural and linguistic barriers inhibiting students from mainland China in the U.K.. It was aimed to find out what problems existed, why they existed and how they affected the daily life of Chinese students. This research was based on certain assumptions. It was assumed that Chinese students in the U.K. would experience language difficulties as well as cultural conflicts. After a literature review on language and culture, and educational evaluation, and a pilot study in Glasgow, the main survey throughout the U.K. involved a representative sample of Chinese students studying in a cross- section of British universities. Findings were analysed by computer and under strict confidentiality, and enabled the researcher to build up a picture of the daily and academic life of Chinese students, interpreted by personal knowledge and experience

Substrate Temperature Effect on the Microstructure and Properties of (Si, Al)/a-C:H Films Prepared through Magnetron Sputtering Deposition

Hydrogenated amorphous carbon films codoped with Si and Al ((Si, Al)/a-C:H) were deposited through radio frequency (RF, 13.56 MHz) magnetron sputtering on Si (100) substrate at different temperatures. The composition and structure of the films were investigated by means of X-ray photoelectron spectroscopy (XPS), TEM, and Raman spectra, respectively. The substrate temperature effect on microstructure and mechanical and tribological properties of the films was studied. A structural transition of the films from nanoparticle containing to fullerene-like was observed. Correspondingly, the mechanical properties of the films also had obvious transition. The tribological results in ambient air showed that high substrate temperature (>573 K) was disadvantage of wear resistance of the films albeit in favor of formation of ordering carbon clusters. Particularly, the film deposited at temperature of 423 K had an ultralow friction coefficient of about 0.01 and high wear resistance

Cyclodepsipeptide Toxin Promotes the Degradation of Hsp90 Client Proteins through Chaperone-Mediated Autophagy

Promoting the degradation of Hsp90 client proteins by inhibiting Hsp90, an important protein chaperone, has been shown to be a promising new anticancer strategy. In this study, we show that an oxazoline analogue of apratoxin A (oz-apraA), a cyclodepsipeptide isolated from a marine cyanobacterium, promotes the degradation of Hsp90 clients through chaperone-mediated autophagy (CMA). We identify a KFERQ-like motif as a conserved pentapeptide sequence in the kinase domain of epidermal growth factor receptor (EGFR) necessary for recognition as a CMA substrate. Mutation of this motif prevents EGFR degradation by CMA and promotes the degradation of EGFR through the proteasomal pathway in oz-apraA–treated cells. Oz-apraA binds to Hsc70/Hsp70. We propose that apratoxin A inhibits Hsp90 function by stabilizing the interaction of Hsp90 client proteins with Hsc70/Hsp70 and thus prevents their interactions with Hsp90. Our study provides the first examples for the ability of CMA to mediate degradation of membrane receptors and cross talks of CMA and proteasomal degradation mechanisms

Dual adversarial models with cross-coordination consistency constraint for domain adaption in brain tumor segmentation

The brain tumor segmentation task with different domains remains a major challenge because tumors of different grades and severities may show different distributions, limiting the ability of a single segmentation model to label such tumors. Semi-supervised models (e.g., mean teacher) are strong unsupervised domain-adaptation learners. However, one of the main drawbacks of using a mean teacher is that given a large number of iterations, the teacher model weights converge to those of the student model, and any biased and unstable predictions are carried over to the student. In this article, we proposed a novel unsupervised domain-adaptation framework for the brain tumor segmentation task, which uses dual student and adversarial training techniques to effectively tackle domain shift with MR images. In this study, the adversarial strategy and consistency constraint for each student can align the feature representation on the source and target domains. Furthermore, we introduced the cross-coordination constraint for the target domain data to constrain the models to produce more confident predictions. We validated our framework on the cross-subtype and cross-modality tasks in brain tumor segmentation and achieved better performance than the current unsupervised domain-adaptation and semi-supervised frameworks

Evidence for Ag participating the electrochemical migration of 96.5Sn-3Ag-0.5Cu alloy

Ag participating the electrochemical migration (ECM) of Sn-Ag based alloys is still controversial. In this work,Ag+concentration in electrolyte layer and Ag distribution in dendrites formed during the ECM of 96.5Sn-3Ag-0.5Cu alloy were investigated using Inductively Coupled Plasma Source Mass Spectrometer and ScanningTransmission Electron Microscopy, respectively. Results show that Ag+can only be detected when Ag can re-lease from Ag3Sn during the anodic polarization of 96.5Sn-3Ag-0.5Cu alloy. Under such a condition, Ag couldalso be found in dendrites. Therefore, it can be concluded that Ag participates the ECM of 96.5Sn-3Ag-0.5Cualloy, but it is potential-dependent

Real-Time Segmentation Method of Lightweight Network For Finger Vein Using Embedded Terminal Technique

Because the existing finger vein segmentation networks are too large and not suitable for implementation in mobile terminals, the reduction of the parameters of the lightweight network leads to the reduction of the segmentation index, and the long-running time of deep network on hardware platforms; this paper proposes a lightweight real-time segmentation method for finger veins based on embedded terminal technique. In the preprocessing stage of the algorithm, the data is greatly expanded by randomly selecting the center to obtain sub-blocks on each image of the training set. The network first uses deep separable convolution to greatly reduce the U-Net parameters of a basic network and introduces an attention module to reorder the features to improve network performance, followed by a preliminary lightweight network Dinty-NetV1. Second, the Ghost module is added to the deep separable convolution, and the feature map of the network part is obtained through a cheap operation so that the network is further compressed to obtain Dinty-NetV2. After adding channel shuffle, all the characteristic channels are evenly shuffled and reorganized to obtain Dinty-NetV3. Finally, a study of the filter norm yields the distribution characteristics of the finger vein picture features. By using the geometric median pruning method, the network models for each stage of the algorithm proposed in this paper achieved better segmentation performance and shorter split time after pruning. The overall Dinty-NetV3 model size is only less than 9% of the U-Net and Mult-Adds is less than 2% of the U-Net with the same structure. After testing on two-finger vein datasets SDU-FV and MMCUBV-6000, we confirm that the performance of Dinty-NetV3 surpasses all previously proposed classic compression model algorithms and it is not inferior to more complex and huge networks such as U-Net, DU-Net, and R2U-Net. The proposed algorithm has advantages in terms of time needed to train the network, and we verify its universality using NVIDIA's full range of embedded terminals

Aqueous extract of Amydrium sinense (Engl.) H. Li alleviates hepatic fibrosis by suppressing hepatic stellate cell activation through inhibiting Stat3 signaling

Background: The present study aimed to investigate the protective effect of the water extract of Amydrium sinense (Engl.) H. Li (ASWE) against hepatic fibrosis (HF) and clarify the underlying mechanism.Methods: The chemical components of ASWE were analysed by a Q-Orbitrap high-resolution mass spectrometer. In our study, an in vivo hepatic fibrosis mouse model was established via an intraperitoneal injection of olive oil containing 20% CCl4. In vitro experiments were conducted using a hepatic stellate cell line (HSC-T6) and RAW 264.7 cell line. A CCK-8 assay was performed to assess the cell viability of HSC-T6 and RAW264.7 cells treated with ASWE. Immunofluorescence staining was used to examine the intracellular localization of signal transducer and activator of transcription 3 (Stat3). Stat3 was overexpressed to analyse the role of Stat3 in the effect of ASWE on HF.Results: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that candidate targets of ASWE, associated with protective effects against hepatic fibrosis, were related to inflammation response. ASWE ameliorated CCl4-induced liver pathological damage and reduced the liver index and alanine transaminase (ALT) and aspartate transaminase (AST) levels. ASWE also decreased the serum levels of collagen Ⅰ (Col Ⅰ) and hydroxyproline (Hyp) in CCl4-treated mice. In addition, the expression of fibrosis markers, including α-SMA protein and Acta2, Col1a1, and Col3a1 mRNA, was downregulated by ASWE treatment in vivo. The expression of these fibrosis markers was also decreased by treatment with ASWE in HSC-T6 cells. Moreover, ASWE decreased the expression of inflammatory markers, including the Tnf-α, Il6 and Il1β, in RAW264.7 cells. ASWE decreased the phosphorylation of Stat3 and total Stat3 expression and reduced the mRNA expression of the Stat3 gene in vivo and in vitro. ASWE also inhibited the nuclear shuttling of Stat3. Overexpression of Stat3 weakened the therapeutic effect of ASWE and accelerated the progression of HF.Conclusion: The results show that ASWE protects against CCl4-induced liver injury by suppressing fibrosis, inflammation, HSC activation and the Stat3 signaling pathway, which might lead to a new approach for preventing HF

Longitudinal Gut Bacterial Colonization and Its Influencing Factors of Low Birth Weight Infants During the First 3 Months of Life

Establishment of low birth weight (LBW) infant gut microbiota may have lifelong implications for the health of individuals. However, no longitudinal cohort studies have been conducted to characterize the gut microbial profiles of LBW infants and their influencing factors. Our objective was to understand how the gut bacterial community structure of LBW and normal birth weight (NBW) infants varies across the first 3 months of life and assess the influencing factors. In this observational cohort study, gut bacterial composition was identified with sequencing of the 16S rRNA gene in fecal samples of 69 LBW infants and 65 NBW controls at 0 day, 3 days, 2 weeks, 6 weeks, and 3 months (defined as stages 1–5) after birth. Alpha-diversity of both groups displayed a decreasing trend followed by slight variations. There were significant differences on the Shannon index of the two groups at stages 1 to 3 (P = 0.041, P = 0.032, and P = 0.014, respectively). The microbiota community structure of LBW infants were significantly different from NBW infants throughout the 3 months (all P < 0.05) but not at stage 2 (P = 0.054). There was a significant increase in abundance in Firmicutes while a decrease in Proteobacteria, and at genus level the abundance of Enterococcus, Klebsiella, and Streptococcus increased while it decreased for Haemophilus in LBW group. Birth weight was the main factor explaining the observed variation at all stages, except at stage 2. Delivery mode (4.78%) and antibiotic usage (3.50%) contributed to explain the observed variation at stage 3, and pregestational BMI (4.61%) partially explained the observed variation at stage 4. In conclusion, gut microbial communities differed in NBW and LBW infants from birth to 3 months of life, and were affected by birth weight, delivery mode, antibiotic treatment, and pregestational BMI