Use data mining to improve student retention in HE - a case study

Data mining combines machine learning, statistics and visualization techniques to discover and extract knowledge. One of the biggest challenges that higher education faces is to improve student retention (National Audition Office, 2007). Student retention has become an indication of academic performance and enrolment management. Our project uses data mining and natural language processing technologies to monitor student, analyze student academic behaviour and provide a basis for efficient intervention strategies. Our aim is to identify potential problems as early as possible and to follow up with intervention options to enhance student retention. In this paper we discuss how data mining can help spot students ‘at risk’, evaluate the course or module suitability, and tailor the interventions to increase student retention

Automatic generation of data merging program codes

Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and their merging types in conceptual level. Our formalized transformation described using ATL (ATLAS Transformation Language) enables automatic generation of PL/SQL packages to execute data merging in commercial ETL tools. With this approach data warehouse engineers can be relieved from the burden of repetitive complex script coding and the pain of maintaining consistency of design and implementation

Isolation and Purification of a Novel Deca-Antifungal Peptide from Potato (Solanum tuberosum L. cv. Jopung) Against Candida albicans

In a previous study, an antifungal protein, AFP-J, was purified from tubers of the potato (Solanum tuberosum cv. L Jopung) and by gel filtration and HPLC. In this study, the functional peptide was characterized by partial acid digestion using HCl and HPLC. We obtained three peaks from the AFP-J, the first and third peaks were not active in the tested fungal strain. However, the second peak, which was named Potide-J, was active (MIC; 6.25 μg/mL) against Candida albicans. The amino acid sequences were analyzed by automated Edman degradation, and the amino acid sequence of Potide-J was determined to be Ala-Val-Cys-Glu-Asn-Asp-Leu-Asn-Cys-Cys. Mass spectrometry showed that its molecular mass was 1083.1 Da. Finally, we confirmed that a disulfide bond was present between Cys3 and Cys9 or Cys10. Using this structure, Potide-J was synthesized via solid-phase methods. In these experiments, only the linear sequence was shown to display strong activity against Candida albicans. These results suggest that Potide-J may be an excellent candidate compound for the development of commercially applicable antibiotic agents

Over-expression of the IGI1 leading to altered shoot-branching development related to MAX pathway in Arabidopsis

Shoot branching and growth are controlled by phytohormones such as auxin and other components in Arabidopsis. We identified a mutant (igi1) showing decreased height and bunchy branching patterns. The phenotypes reverted to the wild type in response to RNA interference with the IGI1 gene. Histochemical analysis by GUS assay revealed tissue-specific gene expression in the anther and showed that the expression levels of the IGI1 gene in apical parts, including flowers, were higher than in other parts of the plants. The auxin biosynthesis component gene, CYP79B2, was up-regulated in igi1 mutants and the IGI1 gene was down-regulated by IAA treatment. These results indicated that there is an interplay regulation between IGI1 and phytohormone auxin. Moreover, the expression of the auxin-related shoot branching regulation genes, MAX3 and MAX4, was down-regulated in igi1 mutants. Taken together, these results indicate that the overexpression of the IGI1 influenced MAX pathway in the shoot branching regulation

A case study on modelling of complex event processing in enterprise architecture

Over the decades, Enterprise Architecture (EA) has been researched to supply all the necessary components for enterprise system modelling including taxonomies, meta-models, architecture development methods, and modelling tools. The main benefits of EA are the knowledge infrastructure for analysis and reporting by all stakeholders and the possibility of designing new conditions in an organized manner. However, EA now faces a big challenge with the growing dynamic of market demands and the rapid changes in business environments, which requires agile system response and self-evolutionary behaviour to support quick decision-making. In technology side, there are already matured, promising paradigm to tackle this challenges, which is Complex Event Processing, however it has not been fully dealt with EA. No standardized method for applying event driven approach in business and IT systems modelling has been developed yet. The paper investigates a possibility of integration of EDA by adding ev ent process layer between business operating and business process layers in the EA stack. Complex event patterns are identified and an event meta-model extending ArchiMate is also proposed to integrate complex event modelling to the business modelling. Using a case study, we modeled a business scenario with event driven approach

Complex event as an core aspect of enterprise architecture EDEMF: Event Driven Enterprise Modelling Framework

For the last decade, Complex Event Processing (CEP) has been emerged as a powerful instrument supporting a more agile and intelligent enterprise. Although several studies have attempted to extend current business modelling standards with elements of complex event modelling they have not fully integrated into Enterprise Architecture (EA). EA provides holistic approach of enterprise business and IT system modelling. In our view CEP is not just an element associated with a business process, but at the centre of business analysis and design. This paper proposes an EA modelling framework that takes CEP as a core aspect of modelling. The framework supports CEP based business architecture within different levels of abstraction: contextual, conceptual/logical, and physical. Meta-models in three hierarchies and model mapping between the meta-models have been developed and demonstrated on a linked data platform in a case study. The case study used the framework as a tool of analysis and modell ing, aiming to integrate scattered information as event data by specifying a complex event layer on top of legacy systems. The designed models were then transformed into executable program codes using the model transformation, for example, RDF script from information model; SPARQL query from complex event model

Coordinated recruitment of conserved defense-signaling pathways in PVYO-Infected Nicotiana benthamiana

Potato virus Y (PVY) is an aphid-transmitted potyvirus that affects economically important solanaceous species. In this study, the phenomena and mechanisms following infection with PVY were investigated in tobacco (Nicotiana benthamiana). In tobacco plants, infection with a mild strain of PVY (PVYO) induced stunted growth in the first two leaves at the shoot apex starting 7 days post-infection (dpi), and mosaic symptoms began to appear on newly developing young leaves at 14 dpi. Using enzyme-linked immunosorbent assay and ultrastructure analysis, we confirmed that viral particles accumulated only in the upper developing leaves of infected plants. We analyzed reactive oxygen species (ROS) generation in leaves from the bottom to the top of the plants to investigate whether delayed symptom development in leaves was associated with a defense response to the virus. In addition, the ultrastructural analysis confirmed the increase of ATG4 and ATG8, which are autophagy markers by endoplasmic reticulum (ER) stress, and the expression of genes involved in viral RNA suppression. Overall, our results suggested that viral RNA silencing and induced autophagy may play a role in the inhibition of viral symptom development in host plants in response to PVYO infection

Malonic Acid Isolated from Pinus densiflora Inhibits UVB-Induced Oxidative Stress and Inflammation in HaCaT Keratinocytes

Skin aging is caused by exposure to various external factors. Ultraviolet B (UVB) irradiation induces oxidative stress, photoaging, and inflammation in skin cells. Pinus densiflora Sieb. et Zucc. (red pine) has various antimicrobial and antioxidant activities. However, the anti-inflammatory effects of red pine on skin have rarely been reported. The protective effects of malonic acid (MA) isolated from Pinus densiflora were investigated against UVB-induced damage in an immortalized human keratinocyte cell line (HaCaT). MA increased levels of the antioxidant enzymes superoxide dismutase 1 (SOD-1) and heme oxygenase 1 (HO-1) via activation of nuclear factor-erythroid 2-related factor-2 (Nrf2), resulting in a reduction in UVB-induced reactive oxygen species (ROS) levels. Additionally, the inhibition of ROS increased HaCaT cell survival rate. Thus, MA downregulated the expression of ROS-induced nuclear factor-κB, as well as inflammation-related cytokines (interleukin-6, cyclooxygenase-2, and tumor necrosis factor-α). Furthermore, MA significantly suppressed the mitogen-activated protein kinase/activator protein 1 signaling pathway and reduced the expression of matrix metalloproteinases (MMPs; MMP-1, MMP-3, and MMP-9). In contrast, MA treatment increased the expression of collagen synthesis regulatory genes (COL1A1 and COL3A1) via regulation of Smad2/3 signal induction through transforming growth factor-β. In conclusion, MA protected against UVB-induced photoaging via suppression of skin inflammation and induction of collagen biosynthesis