E-learning Evolution: From M-learning to Educational Semantic Web and beyond

Abstract: An e-learning model with ICT technology (ELM) is proposed in this paper. With this model, some education technologies and e-learning evolution are interpreted, such as network education, mobile education, ubiquitous education, educational semantic web, and etc. In the meantime, the way of how to combine new ICT technologies into education is also demonstrated. After discussing the convenience and challenge of various education technologies, a new model called intelligent education is introduced and some recent research results are presented. At last, the author looks ahead the future of information technology and human related disciplines and their effects on education

Improving text classification using local latent semantic indexing

Latent Semantic Indexing (LSI) has been shown to be extremely useful in information retrieval, but it is not an optimal representation for text classification. It always drops the text classification performance when being applied to the whole training set (global LSI) because this completely unsupervised method ignores class discrimination while only concentrating on representation. Some local LSI methods have been proposed to improve the classification by utilizing class discrimination information. However, their performance improvements over original term vectors are still very limited. In this paper, we propose a new local LSI method called “Local Relevancy Weighted LSI ” to improve text classification by performing a separate Single Value Decomposition (SVD) on the transformed local region of each class. Experimental results show that our method is much better than global LSI and traditional local LSI methods on classification within a much smaller LSI dimension. 1

The Novel Protease Activities of JMJD5–JMJD6–JMJD7 and Arginine Methylation Activities of Arginine Methyltransferases Are Likely Coupled

The surreptitious discoveries of the protease activities on arginine-methylated targets of a subfamily of Jumonji domain-containing family including JMJD5, JMJD6, and JMJD7 pose several questions regarding their authenticity, function, purpose, and relations with others. At the same time, despite several decades of efforts and massive accumulating data regarding the roles of the arginine methyltransferase family (PRMTs), the exact function of this protein family still remains a mystery, though it seems to play critical roles in transcription regulation, including activation and inactivation of a large group of genes, as well as other biological activities. In this review, we aim to elucidate that the function of JMJD5/6/7 and PRMTs are likely coupled. Besides roles in the regulation of the biogenesis of membrane-less organelles in cells, they are major players in regulating stimulating transcription factors to control the activities of RNA Polymerase II in higher eukaryotes, especially in the animal kingdom. Furthermore, we propose that arginine methylation by PRMTs could be a ubiquitous action marked for destruction after missions by a subfamily of the Jumonji protein family

A combined priority scheduling method for distributed machine learning

Abstract Algorithms and frameworks for distributed machine learning have been widely used in numerous artificial intelligence engineering applications. A cloud platform provides a large number of resources at a lower cost and is a more convenient method for such applications. With the rapid development of containerization, native cloud combinations based on Docker and Kubernetes have provided effective resource support for distributed machine learning. However, native Kubernetes does not provide efficient priority or fair resource scheduling strategies for distributed machine learning in computationally intensive and time-consuming jobs, which easily leads to resource deadlock, resource waste, and low job execution efficiency. Therefore, to utilize the execution order between multiple jobs in distributed machine learning as well as the dependencies between multiple tasks for the same job, considering intra- and inter-group scheduling priorities, a combined priority scheduling method is proposed for distributed machine learning based on Kubernetes and Volcano. Considering the user priority, task priority, longest wait time, task parallelism, and affinity and non-affinity between the parameter server and worker nodes, a combined priority scheduling model of inter- and intra-job priority is proposed, which is mapped into a scheduling strategy of inter- and intra-group priorities of pods, enabling the efficient scheduling and training of distributed machine learning. The experiment results show that the proposed method achieves preferential resource allocation for urgent, high parallelism, and high-priority jobs with high-priority users and improves the job execution efficiency. The affinity and anti-affinity settings among pods reduce the time of information interaction between the parameter server and worker nodes to a certain extent, thereby improving the job completion efficiency. This group scheduling strategy alleviates the problems of resource deadlock and waste caused by insufficient resources in cloud computing

Helicase of Type 2 Porcine Reproductive and Respiratory Syndrome Virus Strain HV Reveals a Unique Structure

Porcine reproductive and respiratory syndrome virus (PRRSV) is prevalent throughout the world and has caused great economic losses to the swine industry. Nonstructural protein 10 (nsp10) is a superfamily 1 helicase participating in multiple processes of virus replication and one of the three most conserved proteins in nidoviruses. Here we report three high resolution crystal structures of highly pathogenic PRRSV nsp10. PRRSV nsp10 has multiple domains, including an N-terminal zinc-binding domain (ZBD), a β-barrel domain, a helicase core with two RecA-like domains, and a C-terminal domain (CTD). The CTD adopts a novel fold and is required for the overall structure and enzymatic activities. Although each domain except the CTD aligns well with its homologs, PRRSV nsp10 adopts an unexpected extended overall structure in crystals and solution. Moreover, structural and functional analyses of PRRSV nsp10 versus its closest homolog, equine arteritis virus nsp10, suggest that DNA binding might induce a profound conformational change of PRRSV nsp10 to exert functions, thus shedding light on the mechanisms of activity regulation of this helicase

Is it possible for knowledge-based planning to improve intensity modulated radiation therapy plan quality for planners with different planning experiences in left-sided breast cancer patients?

Abstract Background Knowledge-based planning (KBP) is a promising technique that can improve plan quality and increase planning efficiency. However, no attempts have been made to extend the domain of KBP for planners with different planning experiences so far. The purpose of this study was to quantify the potential gains for planners with different planning experiences after implementing KBP in intensity modulated radiation therapy (IMRT) plans for left-sided breast cancer patients. Methods The model libraries were populated with 80 expert clinical plans from treated patients who previously received left-sided breast-conserving surgery and IMRT with simultaneously integrated boost. The libraries were created on the RapidPlanTM. 6 planners with different planning experiences (2 beginner planners, 2 junior planners and 2 senior planners) generated manual and KBP optimized plans for additional 10 patients, similar to those included in the model libraries. The plan qualities were compared between manual and KBP plans. Results All plans were capable of achieving the prescription requirement. There were almost no statistically significant differences in terms of the planning target volume (PTV) coverage and dose conformality. It was demonstrated that the doses for most of organs-at-risk (OARs) were on average lower or equal in KBP plans compared to manual plans except for the senior planners, where the very small differences were not statistically significant. KBP data showed a systematic trend to have superior dose sparing at most parameters for the heart and ipsilateral lung. The observed decrease in the doses to these OARs could be achieved, particularly for the beginner and junior planners. Many differences were statistically significant. Conclusions It is feasible to generate acceptable IMRT plans after implementing KBP for left-sided breast cancer. KBP helps to effectively improve the quality of IMRT plans against the benchmark of manual plans for less experienced planners without any manual intervention. KBP showed promise for homogenizing the plan quality by transferring planning expertise from more experienced to less experienced planners

Cellular toxicity of silicon carbide nanomaterials as a function of morphology.

Silicon carbide has been shown to be biocompatible and is used as a coating material for implanted medical devices to prevent biofilms. Silicon carbide nanomaterials are also promising in cell tracking due to their stable and strong luminescence, but more comprehensive studies of this material on the nanoscale are needed. Here, we studied the toxicity of silicon carbide nanomaterials on human mesenchymal stem cells in terms of metabolism, viability, adhesion, proliferation, migration, oxidative stress, and differentiation ability. We compared two different shapes and found that silicon carbide nanowires are toxic to human mesenchymal stem cells but not to cancer cell lines at the concentration of 0.1 mg/mL. Control silicon carbide nanoparticles were biocompatible to human mesenchymal stem cells at 0.1 mg/mL. We studied the potential mechanistic effect of silicon carbide nanowires on human mesenchymal stem cells' phenotype, cytokine secretion, and gene expression. These findings suggest that the toxic effect of silicon carbide nanomaterials to human mesenchymal stem cells are dependent on morphology

Galectin-1 : a link between tumor hypoxia and tumor immune privilege

Purpose: To identify a 15-KDa novel hypoxia-induced secreted protein in head and neck squamous cell carcinomas (HNSCC) and to determine its role in malignant progression. Methods: We used surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and tandem MS to identify a novel hypoxia-induced secreted protein in FaDu cells. We used immunoblots, real-time polymerase chain reaction (PCR), and enzyme-linked immunoabsorbent assay to confirm the hypoxic induction of this secreted protein as galectin-1 in cell lines and xenografts. We stained tumor tissues from 101 HNSCC patients for galectin-1, CA IX (carbonic anhydrase IX, a hypoxia marker) and CDS (a T-cell marker). Expression of these markers was correlated to each other and to treatment outcomes. Results: SELDI-TOF studies yielded a hypoxia-induced peak at 15 kDa that proved to be galectin-1 by MS analysis. Immunoblots and PCR studies confirmed increased galectin-1 expression by hypoxia in several cancer cell lines. Plasma levels of galectin-1 were higher in tumor-bearing severe combined immunodeficiency (SCID) mice breathing 10% O 2 compared with mice breathing room air. In HNSCC patients, there was a significant correlation between galectin-1 and CA IX staining (P = .01) and a strong inverse correlation between galectin-1 and CDS staining (P = .01). Expression of galectin-1 and CDS were significant predictors for overall survival on multivariate analysis. Conclusion: Galectin-1 is a novel hypoxia-regulated protein and a prognostic marker in HNSCC. This study presents a new mechanism on how hypoxia can affect the malignant progression and therapeutic response of solid tumors by regulating the secretion of proteins that modulate immune privilege. © 2005 by American Society of Clinical Oncology

Hydrogen bonds are a primary driving force for de novo protein folding.

The protein-folding mechanism remains a major puzzle in life science. Purified soluble activation-induced cytidine deaminase (AID) is one of the most difficult proteins to obtain. Starting from inclusion bodies containing a C-terminally truncated version of AID (residues 1-153; AID153), an optimized in vitro folding procedure was derived to obtain large amounts of AID153, which led to crystals with good quality and to final structural determination. Interestingly, it was found that the final refolding yield of the protein is proline residue-dependent. The difference in the distribution of cis and trans configurations of proline residues in the protein after complete denaturation is a major determining factor of the final yield. A point mutation of one of four proline residues to an asparagine led to a near-doubling of the yield of refolded protein after complete denaturation. It was concluded that the driving force behind protein folding could not overcome the cis-to-trans proline isomerization, or vice versa, during the protein-folding process. Furthermore, it was found that successful refolding of proteins optimally occurs at high pH values, which may mimic protein folding in vivo. It was found that high pH values could induce the polarization of peptide bonds, which may trigger the formation of protein secondary structures through hydrogen bonds. It is proposed that a hydrophobic environment coupled with negative charges is essential for protein folding. Combined with our earlier discoveries on protein-unfolding mechanisms, it is proposed that hydrogen bonds are a primary driving force for de novo protein folding