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Fulltext An oil fraction neural sensor developed using electrical capacitance tomography sensor data

Zainal-Mokhtar K, Mohamad-Saleh J

Sensors (Basel), 2013;13(9):11385-406.
PMID: 24064598 DOI: 10.3390/s130911385

This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes.
Fulltext New enhanced artificial bee colony (JA-ABC5) algorithm with application for reactive power optimization

Sulaiman N, Mohamad-Saleh J, Abro AG

ScientificWorldJournal, 2015;2015:396189.
PMID: 25879054 DOI: 10.1155/2015/396189

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement.
Dorsal Hand Vein Image Enhancement Using Fusion of CLAHE and Fuzzy Adaptive Gamma

Yakno M, Mohamad-Saleh J, Ibrahim MZ

Sensors (Basel), 2021 Sep 27;21(19).
PMID: 34640769 DOI: 10.3390/s21196445

Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership planes and modified with FAG operator for the same purposes. Finally, the resultant images from CLAHE and FAG are fused using improved weighted averaging methods for clearer vein patterns. Then, matched filter with first-order derivative Gaussian (MF-FODG) is employed to segment vein patterns. The proposed technique was tested on self-acquired dorsal hand vein images as well as images from the SUAS databases. The performance of the proposed technique is compared with various other image enhancement techniques based on mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM). The proposed enhancement technique's impact on the segmentation process has also been evaluated using sensitivity, accuracy, and dice coefficient. The experimental results show that the proposed enhancement technique can significantly enhance the hand vein patterns and improve the detection of dorsal hand veins.
Fulltext A hybrid sensing approach for pure and adulterated honey classification

Subari N, Mohamad Saleh J, Md Shakaff AY, Zakaria A

Sensors (Basel), 2012;12(10):14022-40.
PMID: 23202033 DOI: 10.3390/s121014022

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.
Fulltext Correction to: Initiating or Switching to Insulin Degludec/Insulin Aspart in Adults with Type 2 Diabetes: A Real-World, Prospective, Non-interventional Study Across Six Countries

Fulcher GR, Akhtar S, Al-Jaser SJ, Medina J, Mohamed M, Nicodemus NA, et al.

Adv Ther, 2023 Jan;40(1):389-390.
PMID: 36315342 DOI: 10.1007/s12325-022-02349-1
Fulltext Intelligent color vision system for ripeness classification of oil palm fresh fruit bunch

Fadilah N, Mohamad-Saleh J, Abdul Halim Z, Ibrahim H, Syed Ali SS

Sensors (Basel), 2012;12(10):14179-95.
PMID: 23202043 DOI: 10.3390/s121014179

Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested during optimum stage for maximum oil production. This paper presents the application of color vision for automated ripeness classification of oil palm FFB. Images of oil palm FFBs of type DxP Yangambi were collected and analyzed using digital image processing techniques. Then the color features were extracted from those images and used as the inputs for Artificial Neural Network (ANN) learning. The performance of the ANN for ripeness classification of oil palm FFB was investigated using two methods: training ANN with full features and training ANN with reduced features based on the Principal Component Analysis (PCA) data reduction technique. Results showed that compared with using full features in ANN, using the ANN trained with reduced features can improve the classification accuracy by 1.66% and is more effective in developing an automated ripeness classifier for oil palm FFB. The developed ripeness classifier can act as a sensor in determining the correct oil palm FFB ripeness category.
Evaluation of biodegradability, toxicity and ecotoxicity of organic acid-based deep eutectic solvents

Hayyan A, Zainal-Abidin MH, Putra SSS, Alanazi YM, Saleh J, Nor MRM, et al.

Sci Total Environ, 2024 Jul 25;948:174758.
PMID: 39025152 DOI: 10.1016/j.scitotenv.2024.174758

Over the past decade, deep eutectic systems (DES) have become popular, yet their potential toxicity to living organisms is not well understood. This study fills this gap by examining the toxicity, antibacterial activity and biodegradability of p-toluenesulfonic acid monohydrate (PTSA)-based DESs prepared from ammonium or phosphonium salts. Brine shrimp assays revealed varying toxicity levels of PTSA and salts. Allyltriphenylphosphonium bromide showing the longest survival time among all tested salts while PTSA exhibited a significantly longer duration of cell survival compared to other hydrogen bond donors. PTSA and ammonium salts (N,N-diethylethanolammonium chloride and choline chloride) as individual components showed non-toxic behavior for Gram-negative and Gram-positive bacteria while different PTSA-based DESs showed significant inhibition zones. Fish acute ecotoxicity tests indicated moderately toxicity for individual components and DESs, though higher concentrations increased fish mortality, highlighting the need for careful handling and disposal of PTSA-based DESs to the environment. Biodegradability analyses found all tested DESs to be readily biodegradable and it was reported that, DES 3 prepapred form PTSA and choline chloride has the highest biodegradability level. Notably, all tested DESs showed over 60 % biodegradability after 28 days. This groundbreaking study explores PTSA-based DESs, highlighting their biodegradability and potential use as antibacterial agents. Results revealed that PTSA as individual component is much better from toxicity point of view in comparison with PTSA-based DESs for any further industrial applications.
Fulltext Palm Raceme as a Promising Biomass Precursor for Activated Carbon to Promote Lipase Activity with the Aid of Eutectic Solvents

Abed KM, Hayyan A, Elgharbawy AAM, Hizaddin HF, Hashim MA, Hasan HA, et al.

Molecules, 2022 Dec 09;27(24).
PMID: 36557866 DOI: 10.3390/molecules27248734

This study concerns the role of activated carbon (AC) from palm raceme as a support material for the enhancement of lipase-catalyzed reactions in an aqueous solution, with deep eutectic solvent (DES) as a co-solvent. The effects of carbonization temperature, impregnation ratio, and carbonization time on lipase activity were studied. The activities of Amano lipase from Burkholderia cepacia (AML) and lipase from the porcine pancreas (PPL) were used to investigate the optimum conditions for AC preparation. The results showed that AC has more interaction with PPL and effectively provides greater enzymatic activity compared with AML. The optimum treatment conditions of AC samples that yield the highest enzymatic activity were 0.5 (NaOH (g)/palm raceme (g)), 150 min, and a carbonization temperature of 400 °C. DES was prepared from alanine/sodium hydroxide and used with AC for the further enhancement of enzymatic activity. Kinetic studies demonstrated that the activity of PPL was enhanced with the immobilization of AC in a DES medium.
Nanodiamonds and natural deep eutectic solvents as potential carriers for lipase

Putra SSS, Chew CY, Hayyan A, Elgharbawy AAM, Taskin-Tok T, Hayyan M, et al.

Int J Biol Macromol, 2024 May 08.
PMID: 38729477 DOI: 10.1016/j.ijbiomac.2024.132245

This study investigates the use of nanodiamonds (ND) as a promising carrier for enzyme immobilization and compares the effectiveness of immobilized and native enzymes. Three different enzyme types were tested, of which Rhizopus niveus lipase (RNL) exhibited the highest relative activity, up to 350 %. Under optimized conditions (1 h, pH 7.0, 40 °C), the immobilized ND-RNL showed a maximum specific activity of 0.765 U mg-1, significantly higher than native RNL (0.505 U mg-1). This study highlights a notable enhancement in immobilized lipase; furthermore, the enzyme can be recycled in the presence of a natural deep eutectic solvent (NADES), retaining 76 % of its initial activity. This aids in preserving the native conformation of the protein throughout the reusability process. A test on brine shrimp revealed that even at low concentrations, ND-RNL had minimal toxicity, indicating its low cytotoxicity. The in silico molecular dynamics simulations performed in this study offer valuable insights into the mechanism of interactions between RNL and ND, demonstrating that RNL immobilization onto NDs enhances its efficiency and stability. All told, these findings highlight the immense potential of ND-immobilized RNL as an excellent candidate for biological applications and showcase the promise of further research in this field.
Development of the Asia Pacific Lupus Collaboration cohort

Kandane-Rathnayake R, Golder V, Louthrenoo W, Luo SF, Jan Wu YJ, Li Z, et al.

Int J Rheum Dis, 2019 Mar;22(3):425-433.
PMID: 30398013 DOI: 10.1111/1756-185X.13431

AIM: The aim of this manuscript is to describe the development of the Asia Pacific Lupus Collaboration (APLC) cohort.
METHOD: The APLC cohort is an ongoing, prospective longitudinal cohort. Adult patients who meet either the American College of Rheumatology (ACR) Modified Classification Criteria for systemic lupus erythematosus (SLE), or the Systemic Lupus International Collaborating Clinics (SLICC) Classification Criteria, and provide informed consent are recruited into the cohort. Patients are routinely followed up at 3- to 6-monthly intervals. Information on demographics, clinical manifestations, treatment, pathology results, outcomes, and patient-reported quality of life (Short-form 36 version 2) are collected using a standardized case report form. Each site is responsible for obtaining local ethics and governance approval, patient recruitment, data collection, and data transfer into a centralized APLC database.
RESULTS: The latest APLC cohort comprises 2160 patients with >12 000 visits from Australia, China, Hong Kong, Indonesia, Japan, Malaysia, Philippines, Singapore, Taiwan and Thailand. The APLC has proposed the Lupus Low Disease Activity State (LLDAS) as a treat-to-target (T2T) endpoint, and reported several retrospective and cross-sectional analyses consistent with the validity of LLDAS. Longitudinal validation of LLDAS as a T2T endpoint is currently underway.
CONCLUSION: The APLC cohort is one of the largest contemporary SLE patient cohorts in the world. It is the only cohort with substantial representation of Asian patients. This cohort represents a unique resource for future clinical research including evaluation of other endpoints and quality of care.