Virtual robot: Virtual becomes reality

One of the benefits that education reaps from Virtual Reality (VR) is the ability to visualize,simulate and interact with virtual objects.This ability allows the students to have the trial and error session before actually practicing it on real things.Here comes to the point where the idea of having virtual robot in assisting students learning emerged.Instead of studying the physical robot in class, students can study the virtual robot on computer at home prior to class or even in the class itself.Students can immerse themselves in this digitized world; experience the sense of moving and becoming part of the robot system.This paper presents the methodology for the whole-robot 3D graphics design, integration between the object modeling to VR and the construction of real-time behavior and interactivity modification to accommodate changes in the virtual environment

Preliminary results of electrical characterization of GO towards MCF7 and MCF10a at different concentrations

GO is the 2D carbon sheet with additional functional groups, is more stable in various solvents, easy to be produced and manipulated especially in biological system. At the moment, GO is only utilized as the drug delivery agent during treatment. In this study, the resistivity of GO towards breast cancer cell (MCF7) and normal breast cell (MCF10a) using interdigitated electrodes (IDE) were investigated. The interaction of different concentrations of GO as the sensing material on the tested cells which act as analyte can change electrical response. The tested cell were treated with six different concentrations of GO and was dropped to the IDE with different period of time in order to examine electrical behavior. For MCF10a, at high concentration the resistances of MCF10 remain in the same order of magnitude with increasing time of detection while for MCF7 at high concentration, the resistances were greatly influenced by the time of detection where the value significantly changed after 5 minutes and 10 minutes. The number of viable cell does not give effect to the resistance

Biosynthesized silver nanoparticles by aqueous stem extract of Entada spiralis and screening of their biomedicalactivity

Silver nanoparticles (Ag-NPs) have been established as antibacterial nanoparticles and have been innovatively developed to overcome the occurrence of antibiotic resistance in the environment. In this study, an environmentally friendly and easy method of the biosynthesis of Ag-NPs plants, mediated by aqueous extract stem extract of Entada spiralis (E. spiralis), was successfully developed. The E. spiralis/Ag-NPs samples were characterized using spectroscopy and the microscopic technique of UV-visible (UV-vis), X-ray Diffraction (XRD), Field Emission Transmission Electron Microscope (FETEM), zeta potential, and Fourier Transform Infrared (FTIR) analyses. Surface Plasmon Resonance (SPR) absorption at 400–450 nm in the UV-vis spectra established the formation of E. spiralis/Ag-NPs. The crystalline structure of E. spiralis/Ag-NPs was displayed in the XRD analysis. The small size, around 18.49 ± 4.23 nm, and spherical shape of Ag-NPs with good distribution was observed in the FETEM image. The best physicochemical parameters on Ag-NPs biosynthesis using E. spiralis extract occurred at a moderate temperature (~52.0°C), 0.100 M of silver nitrate, 2.50 g of E. spiralis dosage and 600 min of stirring reaction time. The antibacterial activity was tested against Staphylococcus aureus, Enterococcus faecalis, Escherichia coli, and Proteus vulgaris using an antibacterial disk diffusion assay. Based on the results, it is evident that E. spiralis/Ag-NPs are susceptible to all the bacteria and has promising potential to be applied in both the industry and medical fields

Case report: Unusual cause of difficulty in intubation and ventilation with asthmatic-like presentation of Endobronchial Tuberculosis

Endobronchial Tuberculosis is hazardous in causing circumferential narrowing of tracheobronchial tree despite the eradication of tubercle bacilli in the initial insult from Pulmonary Tuberculosis. They may present as treatment resistant bronchial asthma and pose challenge to airway management in the acute setting. We present a 25 year-old lady who was newly diagnosed bronchial asthma with a past history of Pulmonary Tuberculosis that had completed treatment. She presented with sudden onset of difficulty breathing associated with noisy breathing for 3 days and hoarseness of voice for 6 months. Due to resistant bronchospasm, attempts were made to secure the airway which led to unanticipated difficult intubation and ventilation. Subsequent investigations confirmed the diagnosis of Endobronchial Tuberculosis and patient was managed successfully with anti TB medication, corticosteroids and multiple sessions of tracheal dilatation for tracheal stenosis. This case highlights the unusual cause of difficulty in intubation and ventilation due to Endobronchial Tuberculosis, which required medical and surgical intervention to improve the condition

Electrical characterization of GO at different pH towards MCF7 and MCF10a: preliminary result

The intracellular pH of cancerous cell is commonly acidic while the intracellular pH of normal cell is neutral. The objective of this study is to study the electrical characterization in terms of resistance between the pH of sensing material with the intracellular pH of the cells. Three different pH of Graphene Oxide (GO) were used as a solvent to analyze their interaction towards breast cancer cells (MCF7) and breast normal cells (MCF10a). GO which produced by Hummer's method was used due to their solubility and biocompatibility characteristics which easily diffuse through the cell. In this experiment, the characteristics of GO were analyzed and confirmed by using Atomic Force Microscopy (AFM) and Fourier Transform Infrared spectroscopy (FTIR). In order to measure the resistance of MCF7 and MCF10a cells after treated with GO for 24 hours, gold electrodes with 10 μ-gaps of interdigitated electrodes (IDEs) were used. The results were obtained for three periods of time which were immediate, 5 minutes and 10 minutes after the treated cells being exposed at room temperature. The results show that the resistance of MCF10a cells increased after treated with higher pH of GO which is pH 7 and the resistances of the MCF7 cells decreased as the pH of GO increased to pH 7. Finally, the viable cells were calculated by using haemocytometer in order to prove that the increased of the resistances were due to the increased number of viable cells

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

An efficient method to improve the clustering performance using hybrid robust principal component analysis-spectral biclustering in rainfall patterns identification

In this study, hybrid RPCA-spectral biclustering model is proposed in identifying the Peninsular Malaysia rainfall pattern. This model is a combination between Robust Principal Component Analysis (RPCA) and biclustering in order to overcome the skewness problem that existed in the Peninsular Malaysia rainfall data. The ability of Robust PCA is more resilient to outlier given that it assesses every observation and downweights the ones which deviate from the data center compared to classical PCA. Meanwhile, two way-clustering able to simultaneously cluster along two variables and exhibit a high correlation compared to one-way cluster analysis. The experimental results showed that the best cumulative percentage of variation in between 65%-70% for both Robust and classical PCA. Meanwhile, the number of clusters has improved from six disjointed cluster in Robust PCA-kMeans to eight disjointed cluster for the proposed model. Further analysis shows that the proposed model has smaller variation with the values of 0.0034 compared to 0.030 in Robust PCA-kMeans model. Evident from this analysis, it is proven that the proposed RPCA-spectral biclustering model is predominantly acclimatized to the identifying rainfall patterns in Peninsular Malaysia due to the small variation of the clustering result

An effective visualization and comparison of online terrain draped with multi-sensor satellite images

The objective of this paper is to discuss the effectiveness of visualizing online 3D terrain draped with different satellite imageries. The topographic data of the study area were obtained from the contour maps of Universiti Putra Malaysia, Selangor, Malaysia. The high resolution satellite imageries used in this project involving QUICKBIRD (0.6 m resolution), IKONOS (1 m resolution), and SPOT5 (5 m resolution). R2V software was used for editing the contour data, whereas Arc GIS was used for overlaying the imageries over the 3D terrain data. Then the data were exported into Virtual Reality Markup Language to compare the effectiveness of different satellite imageries based on the data file size, imageries size, number of images tile, loading time during office hours (from 8 a.m. to 5 p.m.) and out of office hours (after 5 p.m.), frame rate per second, and visualization quality. The results revealed that IKONOS satellite imageries are better for an effective online 3D terrain visualization utilizing GIS data even though it has lower resolution compared to QUICKBIRD

Rapid detection of pork in food products by electronic nose for halal authentication

In this study, electronic nose (zNoseTM) was introduced as a new potential real time and fast technique to analyze the aroma of raw meat and processed meat for halal authentication. The zNoseTM was successfully tested for its ability to provide individual fingerprints of the aroma of pork and different types of sausages (beef sausage, chicken sausage and pork sausage). This is achieved using a visual odor pattern called VaporPrintTM, derived from the frequency of the surface acoustic wave (SAW) detector. Principal component analysis (PCA) was used to structure the data matrix. The different meat samples were separated along the first PC. The first PC described 94% of the total variance and showed four well defined groups: chicken sausage, pork sausage, beef sausage and pork. This percentage seemed sufficient to define a good model, especially for qualitative purpose. The high negative score of pork was determined by the highest amount of C8, C13 and C16 among all samples

Classification of Lubricant Oil Adulteration Level using Case-Based Reasoning

The main purpose of this paper is to classify lubricant oil odor-profile using Case-based Reasoning classifier. Electronic nose was used for the purpose of taking data readings for each lubricant oil smell sample. The data that have been collected will be normalized so that the data can be evaluated in a smaller scale to establish an odor-profile for each sample. Then the odor-profiles were classified using Case-based Reasoning (CBR) classifier. The classification performance resulting 100% successfully correct classification