E-Commerce Catalogue Application For EON (Edaran Otomobil Nasional)

The purpose of this project is to develop a prototype e-commerce catalogue application for EON (Edaran Otomobil Nasional). The EON web page provides online customization and ordering of cars services to customers. The cars available are Proton Waja, Proton Perdana V6, Proton Wira Sedan and Proton Iswara. Other services include on-line booking of time to service cars, information about the cars such as prices, model specifications, pictures of cars etc, links to other homepages such as financial institution, insurance companies and second hand Proton cars dealers. There is also information about the EON sales branches and EON services centers throughout Malaysia. The business module of EON web page consiss of four main funtional modules. They are the view information module, online customization and ordering module, on-line booking module and advertisement module. This project uses the Web Page Development Methodology (WPD) as the development methodology. Finally, this project discusses some flaws, constraints and recommendations for future development

Digital or Diligent? Web 2.0's challenge to formal schooling

This paper explores the tensions that arise for young people as both 'digital kids' and 'diligent students'. It does so by drawing on a study conducted in an elite private school, where the tensions between 'going digital' and 'being diligent' are exacerbated by the high value the school places on academic achievement, and on learning through digital innovation. At the school under study, high levels of intellectual and technological resourcing bring with them an equally high level of expectation to excel in traditional academic tasks and high-stakes assessment. The students, under constant pressure to perform well in standardised tests, need to make decisions about the extent to which they take up school-sanctioned digitally enhanced learning opportunities that do not explicitly address academic performance. The paper examines this conundrum by investigating student preparedness to engage with a new learning innovation – a student-led media centre – in the context of the traditional pedagogical culture that is relatively untouched by such digital innovation. The paper presents an analysis of findings from a survey of 481 students in the school. The survey results were subjected to quantitative regression tree modelling to flesh out how different student learning dispositions, social and technological factors influence the extent to which students engage with a specific digital learning opportunity in the form of the Web 2.0 Student Media Centre (SMC) designed to engage the senior school community in flexible digital-networked learning. What emerges from the study is that peer support, perceived ease of use and usefulness, learning goals and cognitive playfulness are significant predictors of the choices that students make to negotiate the fundamental tensions of being digital and/or diligent. In scrutinising the tensions around a digital or a diligent student identity in this way, the paper contributes new empirical evidence to understanding the problematic relationship between student-led learning using new digital media tools and formal schooling

Teaching smarter: how mining ICT data can inform and improve learning and teaching practice

The trend to greater adoption of online learning in higher education institutions means an increased opportunity for instructors and administrators to monitor student activity and interaction with the course content and peers. This paper demonstrates how the analysis of data captured from various IT systems could be used to inform decision making process for university management and administration. It does so by providing details of a large research project designed to identify the range of applications for LMS derived data for informing strategic decision makers and teaching staff. The visualisation of online student engagement/effort is shown to afford instructors with early opportunities for providing additional student learning assistance and intervention – when and where it is required. The capacity to establish early indicators of ‘at-risk’ students provides timely opportunities for instructors to re-direct or add resources to facilitate progression towards optimal patterns of learning behaviour. The project findings provide new insights into student learning that complement the existing array of evaluative methodologies, including formal evaluations of teaching. Thus the project provides a platform for further investigation into new suites of diagnostic tools that can, in turn, provide new opportunities to inform continuous, sustained improvement of pedagogical practice

Development of titanium dioxide nanoparticles/nanosolution for photocatalytic activity

Biological and chemical contaminants by man-made activities have been serious global issue. Exposure of these contaminants beyond the limits may result in serious environmental and health problem. Therefore, it is important to develop an effective solution that can be easily utilized by mankind. One of the effective ways to overcome this problem is by using titanium dioxide (TiO2). TiO2 is a well-known photocatalyst that widely used for environmental clean-up due to its ability to decompose organic pollutant and kill bacteria. Although it is proven TiO2 has an advantage to solve this concern, its usefulness unfortunately is limited only under UV light irradiation. Therefore, the aim of this work was to investigate the potential of TiO2 that can be activated under visible light by the incorporation of metal ions (Fe, Ag, Zr and Ag-Zr). In this study, sol-gel method was employed for the synthesis of metal ions incorporated TiO2. XRD analysis revealed that all samples content biphasic anatase-brookite TiO2 of size 3 nm to 5 nm. It was found that the incorporation of these metal ions did not change the morphology of TiO2 but the crystallinity and optical properties were affected. The crystallinity of anatase in the biphasic TiO2 was found to be decreased and favored brookite formation. PL analysis showed metal ions incorporation suppressed the recombination of electron-hole pairs while the band gap energy of TiO2 (3.2 eV) was decreased by the incorporation of Fe (2.46 eV) and Ag (2.86 eV). Among this incorporation, Ag-Zr incorporated TiO2 showed highest performance for methyl orange degradation (93%) under fluorescent xxv light irradiation for 10 h. This follows by Zr-TiO2 (82%), Fe-TiO2 (75%) and Ag�TiO2 (43%). Meanwhile, the highest antibacterial performance was exhibited by Ag�TiO2. TEM images showed that E.coli bacterium was killed within 12 h after treated with Ag-TiO2. The results obtained from the fieldwork study established that Ag-Zr incorporation have excellent performances for VOC removal and antibacterial test. The VOC content after treated with Ag-Zr-TiO2 fulfilled the Industry Code of Practice on Indoor Air Quality 2010 which is lower than 3 ppm. In addition, the percentage of microbes also found to be decrease around 45 % within 5 days of monitoring

Assessment of phytochemical content, polyphenolic composition, antioxidant and antibacterial activities of Leguminosae medicinal plants in Peninsular Malaysia

Background: Many medicinal plants from Leguminosae family can be found easily in Malaysia. These plants have been used as traditional medicines by local ethnic groups, where they are prepared as decoction, pastes for wound infections, and some have been eaten as salad. This paper focused on the assessment of antioxidant potential, antibacterial activity and classes of phytochemicals of nine plants from the Leguminosae family. Methods: Acacia auriculiformis, Bauhinia kockiana, Bauhinia purpurea, Caesalpinia pulcherrima, Calliandra tergemina, Cassia surattensis, Leucaena leucocephala, Peltophorum pterocarpum, and Samanea saman were extracted with aqueous methanol and dichloromethane:methanol mixture to test for antioxidant and antibacterial activities. The Folin-Ciocalteu assay was conducted to quantify the total phenolic content and 2, 2-diphenyl-1-picrylhydrazyl (DPPH) assay was used to determine the free radical quenching capacity. Antibacterial activity was assessed using disc diffusion (Kirby-Bauer) assay. Screening for major classes of phytochemical was done using standard chemical tests. Results: B. kockiana flowers and C. pulcherrima leaves contained high total phenolic content (TPC) and strong DPPH radical scavenging ability with TPC of 8280 ± 498 mg GAE/100 g, IC50 of 27.0 ± 5.0 μg/mL and TPC of 5030 ± 602 mg GAE/100 g, IC50 of 50.0 ± 5.0 μg/mL respectively. Positive correlation was observed between TPC and free radical scavenging ability. Most extracts showed antibacterial activity against Gram positive bacteria at 1 mg, while none showed activity against Gram negative bacteria at the same dose. All extracts (except Samanea saman flower) showed antibacterial activity against two strains of methicillin resistant Staphylococcus aureus (MRSA) with MID values ranging between 100 μg/disc and 500 μg/disc. Conclusion: The potential source of antioxidant and antibacterial agents, especially for MRSA infection treatments were found in B. kockiana, C. pulcherrima, C. tergemina and P. pterocarpum. These preliminary results would be a guide in the selection of potential candidates for further pharmacological study and in search of new drug candidate in treating MRSA infections

Proteomics Analysis of the Expression of Neurogranin in Murine Neuroblastoma (Neuro-2a) Cells Reveals Its Involvement for Cell Differentiation

Neurogranin (Ng) is a neural-specific, calmodulin (CaM)-binding protein that is phosphorylated by protein kinase C (PKC). Although its biochemical property has been well characterized, the physiological function of Ng needs to be elucidated. In the present study, we performed proteomics analysis of the induced compositional changes due to the expression of Ng in murine neuroblastoma (Neuro-2a) cells using isotope coded affinity tags (ICAT) combined with 2-dimensional liquid chromatography/tandem mass spectrometry (2D-LC/MS/MS). We found that 40% of identified proteins were down-regulated and most of these proteins are microtubule components and associated proteins that mediated neurite outgrowth. Western blot experiments confirmed the expression of α-tubulin and microtubule- associated protein 1B (MAP 1B) was dramatically reduced in Neuro-2a-Ng cells compared to control. Cell morphology of Neuro-2a-Ng showed far less neurites than the control. Serum deprivation induced the extension of only one or two long neurites per cell in Neuro-2a-Ng, contrasting to the extension of multiple neurites per control cell. Ng may be linked to neurite formation by affecting expression of several microtubule related proteins. Furthermore, the PKC activator (PMA) induced an enhanced ERK1/2 activity in the cells that expressed Ng. The mutation of Ng at S36A caused sustained increase of ERK1/2 activity, whereas the ERK1/2 activity in mutation at I33Q showed no difference compared to wild type Ng, suggesting the phosphorylation of Ng but not the CaM /Ng interaction plays an important role in ERK activation. Ng may be involved in neuronal growth and differentiation via PKC and ERK1/2 signaling pathways

Compositional and thermal characteristics of palm olein-based diacylglycerol in blends with palm super olein

Palm olein-based diacylglycerol (POL-DAG) was blended with palm super olein (POoo) in various concentrations (10–90%), with increments of 10% (wt/wt) POL-DAG. The physical and chemical characteristics, i.e., iodine value, acylglycerol content, fatty acid composition, melting and crystallization profiles and solid fat content, for POL-DAG, POoo and their binary blends were evaluated. The mid-infrared FTIR was used to determine the absorption bands of the different concentrations of the oil blends. Only slight differences of FAC and IV were observed. POL-DAG:POoo blends showed significant changes (p < 0.05) in DAG content and decreases in TAG content with increasing POL-DAG content. The DSC thermograms showed that the addition of different concentrations of POL-DAG changed the melting and crystallization behavior of the oil blends (POL-DAG:POoo). The crystallization onset point increased (p < 0.05) with an increasing POL-DAG concentration (10–90%). POL-DAG has the same absorption bands as POoo, with the exception of several minor peaks that appeared at (I) 2954 cm− 1, (II) 1267 cm− 1, (III) 1199 cm− 1, (IV) 1222 cm− 1 and (V) 966 cm− 1. This study will provide essential information for the palm oil industry to identify the most suitable POL-DAG blends with desirable physicochemical properties for food application purposes

Prediction models for chronic postsurgical pain in patients with breast cancer based on machine learning approaches

PurposeThis study aimed to develop prediction models for chronic postsurgical pain (CPSP) after breast cancer surgery using machine learning approaches and evaluate their performance.MethodsThe study was a secondary analysis based on a high-quality dataset from a randomized controlled trial (NCT00418457), including patients with primary breast cancer undergoing mastectomy. The primary outcome was CPSP at 12 months after surgery, defined as modified Brief Pain Inventory &gt; 0. The dataset was randomly split into a training dataset (90%) and a testing dataset (10%). Variables were selected using recursive feature elimination combined with clinical experience, and potential predictors were then incorporated into three machine learning models, including random forest, gradient boosting decision tree and extreme gradient boosting models for outcome prediction, as well as logistic regression. The performances of these four models were tested and compared.Results1152 patients were finally included, of which 22.1% developed CPSP at 12 months after breast cancer surgery. The 6 leading predictors were higher numerical rating scale within 2 days after surgery, post-menopausal status, urban medical insurance, history of at least one operation, under fentanyl with sevoflurane general anesthesia, and received axillary lymph node dissection. Compared with the multivariable logistic regression model, machine learning models showed better specificity, positive likelihood ratio and positive predictive value, helping to identify high-risk patients more accurately and create opportunities for early clinical intervention.ConclusionsOur study developed prediction models for CPSP after breast cancer surgery based on machine learning approaches, which may help to identify high-risk patients and improve patients’ management after breast cancer

The relationship between career development practices and high performance talent in private organizations in Malaysia

The purpose of this study is to examine the relationship between career development practices and high performance talent. Particularly, the objectives of this study were (1) to identify the career development practice in selected service organization; (2) to examine the talent’s perception in regards to career development practice in the organization; (3) to identify the talent’s perception in regards to their current performance; (4) to study the relationship between succession planning, job rotation, pipeline system, mentoring program, educational and tuition reimbursement practices toward developing high performance talent; (5) to determine the relationship between overall career development practices and high performance talent. This study utilized theory developed by Gutteridge (1993), Holstein (2005) and Super (1954). Data were collected by both qualitative and quantitative methods. Focus group discussion with 15 selected Human Resource Manager was initially conducted to help the researchers to develop the survey questionnaire. A number 233 respondents from three selected organizations namely aviation, postal service and manufacturing involved in the survey. Qualitative data were analyzed using thematic analysis. Both descriptive and inferential statistics namely frequency, mean, and Pearson correlation were used to analyze the quantitative data. Results of focus group discussion found that among the career development practices that were practiced in their organizations are job rotation, mentoring, pipeline system, succession planning and education tuition fees reimbursement. Results of that correlation analysis showed a significant relationship between educational and tuition reimbursement, job rotation, mentoring program, pipeline system, succession planning and high performance talent ranges from moderate to strong relationship.The results also showed that overall career development practices was significantly correlated with high performance talent. Lastly, recommendations for practices and future studies were also discusses