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Ergonomic study for optimum printing workstation using factorial experiment and response surface methodology

Mohammad Iqbal, Hartomo Soewardi, Azmi Hassan, Che Hassan Che Haron

Journal of Occupational Safety and Health, 2004;1(2):42-48.
MyJurnal

This paper presents the use of factorial experiments and response surface methodology to determine the best workstation design configuration of an existing electronic industry. The aim is to find the value of physical dimensions that gives the best performance for the workstation. Four performance measures are selected; the cycle time, the metabolic energy expenditure, worker’s posture during the task and lifting limitations. The methodology used in this study consists of two parts. The first part is based on factorial experiments and handles discrete search over combinations of factor-levels for improving the initial solution. In the second part, the solution that was obtained earlier is further refined by changing the continuous factors by using response surface methodology. The result of this optimization study shows that the optimum value of physical dimensions gives a significant improvement for the performance measures of the workstation.
Fulltext High-frequency ultrasound imaging in wound assessment: current perspectives

Hamidreza Mohafez, Siti Anom Ahmad, Mohammad Hamiruce Marhaban, Maryam Hadizadeh, Mohammad Iqbal Saripan

Pertanika Journal of Science & Technology, 2017;25(4):1039-1050.
MyJurnal

Non-invasive imaging modalities for wound assessment have become increasingly popular over the past
two decades. The wounds can be developed superficially or from within deep tissues, depending on the
nature of the dominant risk factors. Developing a reproducible quantitative method to assess woundhealing
status has demonstrated to be a convoluted task. Advances in High-Frequency Ultrasound (HFU)
skin scanners have expanded their application as they are cost-effective and reproducible diagnostic tools
in dermatology, including for the measurement of skin thickness, the assessment of skin tumours, the
estimation of the volume of melanoma and non-melanoma skin cancers, the visualisation of skin structure
and the monitoring of the healing of acute and chronic wounds. Previous studies have revealed that HFU
images carry dominant parameters and depict the phenomena occurring within deep tissue layers during
the wound-healing process. However, the investigations have mostly focussed on the validation of HFU
images, and few studies have utilised HFU imaging in quantitative assessment of wound generation and
healing. This paper is an introductory review of the
important studies proposed by the researchers in
the context of wound assessment. The principles
of dermasonography are briefly explained,
followed by a review of the relevant literature that
investigated the wound-healing process and tissue
structures within the wound using HFU imaging.
Evaluation of bisindole as potent β-glucuronidase inhibitors: synthesis and in silico based studies

Khan KM, Rahim F, Wadood A, Taha M, Khan M, Naureen S, et al.

Bioorg Med Chem Lett, 2014 Apr 1;24(7):1825-9.
PMID: 24602903 DOI: 10.1016/j.bmcl.2014.02.015

Bisindole analogs 1-17 were synthesized and evaluated for their in vitro β-glucuronidase inhibitory potential. Out of seventeen compounds, the analog 1 (IC50=1.62±0.04 μM), 6 (IC50=1.86±0.05 μM), 10 (IC50=2.80±0.29 μM), 9 (IC50=3.10±0.28 μM), 14 (IC50=4.30±0.08 μM), 2 (IC50=18.40±0.09 μM), 19 (IC50=19.90±1.05 μM), 4 (IC50=20.90±0.62 μM), 7 (IC50=21.50±0.77 μM), and 3 (IC50=22.30±0.02 μM) showed superior β-glucuronidase inhibitory activity than the standard (d-saccharic acid 1,4-lactone, IC50=48.40±1.25 μM). In addition, molecular docking studies were performed to investigate the binding interactions of bisindole derivatives with the enzyme. This study has identified a new class of potent β-glucouronidase inhibitors.
Fulltext Strength and Acid Resistance of Ceramic-Based Self-Compacting Alkali-Activated Concrete: Optimizing and Predicting Assessment

Algaifi HA, Khan MI, Shahidan S, Fares G, Abbas YM, Huseien GF, et al.

Materials (Basel), 2021 Oct 19;14(20).
PMID: 34683800 DOI: 10.3390/ma14206208

The development of self-compacting alkali-activated concrete (SCAAC) has become a hot topic in the scientific community; however, most of the existing literature focuses on the utilization of fly ash (FA), ground blast furnace slag (GBFS), silica fume (SF), and rice husk ash (RHA) as the binder. In this study, both the experimental and theoretical assessments using response surface methodology (RSM) were taken into account to optimize and predict the optimal content of ceramic waste powder (CWP) in GBFS-based self-compacting alkali-activated concrete, thus promoting the utilization of ceramic waste in construction engineering. Based on the suggested design array from the RSM model, experimental tests were first carried out to determine the optimum CWP content to achieve reasonable compressive, tensile, and flexural strengths in the SCAAC when exposed to ambient conditions, as well as to minimize its strength loss, weight loss, and UPVL upon exposure to acid attack. Based on the results, the optimum content of CWP that satisfied both the strength and durability aspects was 31%. In particular, a reasonable reduction in the compressive strength of 16% was recorded compared to that of the control specimen (without ceramic). Meanwhile, the compressive strength loss of SCAAC when exposed to acid attack minimized to 59.17%, which was lower than that of the control specimen (74.2%). Furthermore, the developed RSM models were found to be reliable and accurate, with minimum errors (RMSE < 1.337). In addition, a strong correlation (R > 0.99, R2 < 0.99, adj. R2 < 0.98) was observed between the predicted and actual data. Moreover, the significance of the models was also proven via ANOVA, in which p-values of less than 0.001 and high F-values were recorded for all equations.
Fulltext In-vitro diagnosis of single and poly microbial species targeted for diabetic foot infection using e-nose technology

Yusuf N, Zakaria A, Omar MI, Shakaff AY, Masnan MJ, Kamarudin LM, et al.

BMC Bioinformatics, 2015;16:158.
PMID: 25971258 DOI: 10.1186/s12859-015-0601-5

Effective management of patients with diabetic foot infection is a crucial concern. A delay in prescribing appropriate antimicrobial agent can lead to amputation or life threatening complications. Thus, this electronic nose (e-nose) technique will provide a diagnostic tool that will allow for rapid and accurate identification of a pathogen.
Fulltext An Emotion Assessment of Stroke Patients by Using Bispectrum Features of EEG Signals

Yean CW, Wan Ahmad WK, Mustafa WA, Murugappan M, Rajamanickam Y, Adom AH, et al.

Brain Sci, 2020 Sep 25;10(10).
PMID: 32992930 DOI: 10.3390/brainsci10100672

Emotion assessment in stroke patients gives meaningful information to physiotherapists to identify the appropriate method for treatment. This study was aimed to classify the emotions of stroke patients by applying bispectrum features in electroencephalogram (EEG) signals. EEG signals from three groups of subjects, namely stroke patients with left brain damage (LBD), right brain damage (RBD), and normal control (NC), were analyzed for six different emotional states. The estimated bispectrum mapped in the contour plots show the different appearance of nonlinearity in the EEG signals for different emotional states. Bispectrum features were extracted from the alpha (8-13) Hz, beta (13-30) Hz and gamma (30-49) Hz bands, respectively. The k-nearest neighbor (KNN) and probabilistic neural network (PNN) classifiers were used to classify the six emotions in LBD, RBD and NC. The bispectrum features showed statistical significance for all three groups. The beta frequency band was the best performing EEG frequency-sub band for emotion classification. The combination of alpha to gamma bands provides the highest classification accuracy in both KNN and PNN classifiers. Sadness emotion records the highest classification, which was 65.37% in LBD, 71.48% in RBD and 75.56% in NC groups.
Fulltext A study on volatile organic compounds emitted by in-vitro lung cancer cultured cells using gas sensor array and SPME-GCMS

Thriumani R, Zakaria A, Hashim YZH, Jeffree AI, Helmy KM, Kamarudin LM, et al.

BMC Cancer, 2018 04 02;18(1):362.
PMID: 29609557 DOI: 10.1186/s12885-018-4235-7

BACKGROUND: Volatile organic compounds (VOCs) emitted from exhaled breath from human bodies have been proven to be a useful source of information for early lung cancer diagnosis. To date, there are still arguable information on the production and origin of significant VOCs of cancer cells. Thus, this study aims to conduct in-vitro experiments involving related cell lines to verify the capability of VOCs in providing information of the cells.
METHOD: The performances of e-nose technology with different statistical methods to determine the best classifier were conducted and discussed. The gas sensor study has been complemented using solid phase micro-extraction-gas chromatography mass spectrometry. For this purpose, the lung cancer cells (A549 and Calu-3) and control cell lines, breast cancer cell (MCF7) and non-cancerous lung cell (WI38VA13) were cultured in growth medium.
RESULTS: This study successfully provided a list of possible volatile organic compounds that can be specific biomarkers for lung cancer, even at the 24th hour of cell growth. Also, the Linear Discriminant Analysis-based One versus All-Support Vector Machine classifier, is able to produce high performance in distinguishing lung cancer from breast cancer cells and normal lung cells.
CONCLUSION: The findings in this work conclude that the specific VOC released from the cancer cells can act as the odour signature and potentially to be used as non-invasive screening of lung cancer using gas array sensor devices.