The Role of Entrepreneurial Orientations in Talent Retention amongst Malaysian Engineers

Objective: This paper examines the linkage between entrepreneurial orientation (EO) and talent retention amongst Malaysian engineers from the perspective of entrepreneurial orientation theory. Methodology: A cross-sectional survey of 104 engineers from private organisations in Malaysia was conducted to test the hypothesised relationships between constructs. The population comprised graduate and professional engineers who were registered under the Board of Engineers Malaysia (BEM).The purposive sampling method was employed for data analysis purposes. Data was analysed using partial least squarestructural equation modelling technique. Results: The results of this study indicated a significant relationship between innovativeness, proactiveness, risk-taking, and competitive aggressiveness and the intention to stay (ITS). Autonomy was found not significant in predicting engineers’ ITS the same jobs. Engineers require EO to support their freedom of ideas and thoughts to exploit opportunities, produce creativity, and solve engineering task-related problems and uncertainty situations. Implication: EO dimensions can be used to predict engineers’ ITS current employments. This study provides crucial information for the organisations and policy makers to develop mechanisms and policies to enhance the engineers’ involvement of effective EO for increasing retention behaviours and career satisfaction. As the EO of engineers’ increase, the ITS will also increase

The Role of Entrepreneurial Orientations in Talent Retention Amongst Malaysian Engineers

This paper examines the linkage between entrepreneurial orientation (EO) and talent retention amongst Malaysian engineers from the perspective of entrepreneurial orientation theory.A cross-sectional survey of 104 engineers from private organisations in Malaysia was conducted to test the hypothesised relationships between constructs.The population comprised graduate and professional engineers who were registered under the Board of Engineers Malaysia (BEM).The purposive sampling method was employed for data analysis purposes.Data was analysed using partial least square-structural equation modelling technique.The results of this study indicated a significant relationship between innovativeness, proactiveness, risk-taking, and competitive aggressiveness and the intention to stay (ITS).Autonomy was found not significant in predicting engineers’ ITS the same jobs.Engineers require EO to support their freedom of ideas and thoughts to exploit opportunities, produce creativity, and solve engineering task-related problems and uncertainty situations.EO dimensions can be used to predict engineers’ ITS current employments.This study provides crucial information for the organisations and policy makers to develop mechanisms and policies to enhance the engineers’ involvement of effective EO for increasing retention

Development of comparative genomic hybridization(CGH) technique for the study of nasopharyngeal carcinoma(NPC)

NPC is a disease in which malignant cells are formed in the tissue of nasopharynx. It is a highly prevalent disease in Southern China and Southeast Asia including Malaysia. CGH is a molecular cytogenetic technique which is used to identify imbalanced genetic alterations in this malignancy. Twenty eight samples were obtained. Out of this; twelve tumors were extracted from twelve NPC biopsies while twelve references DNA was extracted from twelve normal controls peripheral blood. Tumor DNA and normal DNA was labeled by nick translation method with green and red fluorescent dyes. These were hybridized at metaphase chromosomes DNA and counterstained with DAPL Finally, the image was captured and analyzed. Chromosomal gains that were found in this study were 4q26, llql3-ql4, 9pl3, 8ql3-q22 and 10q22- q26 while chromosomal losses were found at region 20p12 and 13q21-q31. We believe this study has provided the platform for further investigations to locate possible tumorsuppressor genes and oncogenes in our NPC patients

Fluorescence microscopy on the biocompatibility of gentamicin-coated hydroxyapatite (HA) material on osteoblast

This study was carried out to observe the biocompatibility of gentamicin-coated hydroxyapatite (HA) on osteoblast using fluorescence microscopy. The specific objective was to observe the viability of the osteoblast on the gentamicin-coated hydroxyapatite (HA) and to determine the effect of the biomaterial coated with gentamicin on the osteoblast. Osteoblast cell lines were cultured and maintained in complete medium, 1:1 HAM's F12 Medium Dulbecco's modified Eagle's medium without phenol red (DMEM) and incubated at 37°C in a 5% CO 2. The cell lines were treated with different concentration of gentamicin-coated hydroxyapatite and the interactions of the antibiotic beads against osteoblast were tested using the 3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. The MTT assay results indicated that varying concentrations of gentamicin coated HA from 0.1 mg/ml to 10 mg/ml did not significantly affect viability of osteoblast. By employing fluorescence microscopy, the morphology of osteoblast observed appeared red in color which indicated that the osteoblast was viable on biomaterial. The pore size of hydroxyapatite is between 150 to 350 nm. This preliminary result suggested that the gentamicin-coated HA had a good biocompatibility towards osteoblast

Cytotoxic effect of gentamycin-coated hydroxyapatite on Staphylococcus aureus biofilm.

A biofilm is a multilayered complex microorganism, which attached on a surface and resistant to antibiotics. In this study, we examined the cytotoxicity of the HA biomaterial coated with gentamycin on S. aureus biofilm. The microtiter plate biofilm assay and catheter-associated biofilm had been described in this study. The surface morphology of S. aureus biofilm was examined under scanning electron microscope (SEM). The IC50 of gentamycincoated HA treated on S. aureus biofilm was 0.1mg/ml (100μg/ml)

Role of Entrepreneurial Orientation in Talent Retention among Malaysian Engineers

Purpose: This paper examines the linkage between entrepreneurial orientation (EO) and talent retention amongst Malaysian engineers from the perspective of entrepreneurial orientation theory. Design/Methodology/Approach: A cross-sectional survey of 104 engineers from private organisations in Malaysia was conducted to test the hypothesised relationships between constructs. The population comprised graduate and professional engineers who were registered under the Board of Engineers Malaysia (BEM). The purposive sampling method was employed for data analysis purposes. Data was analysed using partial least square-structural equation modelling technique. Findings: The results of this study indicated a significant relationship between innovativeness, proactiveness, risk-taking, and competitive aggressiveness and the intention to stay (ITS). Autonomy was found not significant in predicting engineers’ ITS the same jobs. Engineers require EO to support their freedom of ideas and thoughts to exploit opportunities, produce creativity, and solve engineering task-related problems and uncertainty situations. Implications/Originality/Value: EO dimensions can be used to predict engineers’ ITS current employments. This study provides crucial information for the organisations and policy makers to develop mechanisms and policies to enhance the engineers’ involvement of effective EO for increasing retention behaviours and career satisfaction. As the EO of engineers’ increase, the ITS will also increase

An automated approach for fibroblast cell confluency characterisation and sample handling using AIoT for bio-research and bio-manufacturing

AbstractCurrent methods used in cell culture monitoring, characterisation and handling are manual, time consuming and highly dependent on subjective observations made by human operators, resulting in inconsistent outcomes. This project focuses on developing an automated system for cell growth analysis, utilising Artificial Intelligence of Things (AIoT) for use in bio-manufacturing and bio-research. The proposed AIoT system applies a U-Net convolutional neural network (CNN) model for fibroblast cell segmentation to monitor confluency and incorporates a mechanical robotic arm for automated sample handling. Intel Movidius Neural Compute Stick 2 (NCS2) and OpenVINO Toolkit were used to allow for standalone deployment on an UP2 Squared and a Raspberry Pi board that is integrated with a digital microscope system. The robotic arm was programmed to pick, place and sort the cell samples within the working environment. The results obtained from the CNN model development achieved an accuracy of 95% and an intersection over Union (IoU) of 66%. The OpenVINO Toolkit successfully optimised power-consumption and accelerated the segmentation on a 2K image to be completed in less than 13 seconds. The AIoT cell detection and characterisation system is able to automatically analyse the cell culture while reducing manual sample handling by laboratory personnel. Eventually, it is hoped that this AIoT automated cell detection and characterisation system will have a positive impact and contribute towards the implementation of the Industrial Revolution IR4.0 in bio-based research and industries

A review of open-source image analysis tools for mammalian cell culture: algorithms, features and implementations

Cell culture is undeniably important for multiple scientific applications, including pharmaceuticals, transplants, and cosmetics. However, cell culture involves multiple manual steps, such as regularly analyzing cell images for their health and morphology. Computer scientists have developed algorithms to automate cell imaging analysis, but they are not widely adopted by biologists, especially those lacking an interactive platform. To address the issue, we compile and review existing open-source cell image processing tools that provide interactive interfaces for management and prediction tasks. We highlight the prediction tools that can detect, segment, and track different mammalian cell morphologies across various image modalities and present a comparison of algorithms and unique features of these tools, whether they work locally or in the cloud. This would guide non-experts to determine which is best suited for their purposes and, developers to acknowledge what is worth further expansion. In addition, we provide a general discussion on potential implementations of the tools for a more extensive scope, which guides the reader to not restrict them to prediction tasks only. Finally, we conclude the article by stating new considerations for the development of interactive cell imaging tools and suggesting new directions for future research

Deploying Patch-Based Segmentation Pipeline for Fibroblast Cell Images at Varying Magnifications

Cell culture monitoring necessitates thorough attention for the continuous characterization of cultivated cells. Machine learning has recently emerged to engage in a process, such as a microscopy segmentation task; however, the trained data may not be comprehensive for other datasets. Most algorithms do not encompass a wide range of data attributes and require distinct system workflows. Thus, the main objective of the research is to propose a segmentation pipeline specifically for fibroblast cell images on phase contrast microscopy at different magnifications and to achieve reliable predictions during deployment. The research employs patch-based segmentation for predictions, with U-Net as the baseline architecture. The proposed segmentation pipeline demonstrated significant performance for the UNet-based network, achieving an IoU score above 0.7 for multiple magnifications, and provided predictions for cell confluency value with less than 3% error. The study also found that the proposed model could segment the fibroblast cells in under 10 seconds with the help of OpenVINO and Intel Compute Stick 2 on Raspberry Pi, with its optimal precision limited to approximately 80% cell confluency which is sufficient for real-world deployment as the cell culture is typically ready for passaging at the threshold

Urban and long-range driving cycle for electric vehicle: a review

Electric vehicles (EV) according to the definition given by German government and the National Development Plan of Electric Mobility (NEP) consist of all road vehicles that are supplied by an electric motor and particularly get their energy from the power grid which can be recharged externally. There are three types of EV included which are the Range Extended Electric Vehicles (REEV), Plug-in Hybrid Electric Vehicles (PHEV), and the purely electric vehicles (EV). The performance of EV such as the energy and power consumption, and emission can be determined by the means of drive cycles just like for the conventional vehicles. In this paper, the methodology for the development of drive cycles is explained in detail. There are hundreds or even thousands of drive cycles developed all over the world either legislative or non-legislative. We will also be discussing about some of the prominent driving cycles used by international organizations such as the Environmental Protection Agency (EPA) and California Air Research Board (CARB). A total of 15 drive cycles will be covered in this paper covering the rural, urban, and highway areas. The drive cycles are INRETS drive cycle, Indian drive cycle, Manhattan drive cycle, Urban Dynamometer Driving Schedule (UDDS), Representative Non-LA4 (REP05) drive cycle, Highway Fuel Economy Test (HWFET) drive cycle, US06 drive cycle, SC03 drive cycle, BUSTRE drive cycle, ARB02 drive cycle, CLEVELAND drive cycle, Japanese 10-15 mode drive cycle, ECE drive cycle, EUDC, and New European Drive Cycle (NEDC). Heavy duty electric vehicles such as buses are also considered in this paper. For instance, the Manhattan drive cycle is included to represent the driving pattern of buses