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Marine Predator Algorithm and Related Variants: A Systematic Review
Get PDF—The Marine Predators Algorithm (MPA) is
classified under swarm intelligence methods based on its type of inspiration. It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the
biological relationship between prey and predators. The algorithm is easy to implement and robust in searching, yielding better solutions to many real-world problems. It is attracting huge and growing interest. This paper provides a systematic review of the research progress and applications of the MPA by analyzing more than 100 articles sourced from Scopus and Web of Science databases using the PRISMA approach. The study expounded the classical MPA’s workflow. It also unveiled a steady upward trend in the use of the algorithm. The research presented different improvements and variants of MPA including parameter-tuning, enhancement of the balance between exploration and exploitation, hybridization of MPA with other techniques to harness the strengths of each of the algorithms towards complementing thecweaknesses of the other, and more recently proposed advances. It further underscores the application of MPA in various areas such as Engineering, Computer Science, Mathematics, and Energy. Findings reveal several search strategies implemented to improve the algorithm’s performance. In conclusion, although MPA has been widely accepted, other areas remain yet to be applied, and some improvements are yet to be covered. These have been
presented as recommendations for future research direction
Stand Structure Characteristics of Fragmented and Primary Forests and Their Correlation to Carbon Stocks
Get PDFStand structure contributes to forest biodiversity and productivity. The disparity of stand structure between fragmented and primary forests and how they affect carbon storage are poorly understood. This study determined differences among some stand parameters in fragmented and primary forests and the correlation between forest stand structure and carbon stock. Twenty-five replicate quadrats were established in Bukit Durang and Division 5, representing the fragmented forests, and Lambir Hills National Park and Kubah National constitute the primary forests. All trees with diameter at breast height of 10 cm and above were measured, and the tree species were recorded. Aboveground biomass was calculated and converted to carbon stock. Statistical analyses showed that tree density is comparable among the forests. However, species abundance, species dominance, basal area aboveground biomass, and carbon stocks are different. Large-diameter trees significantly contribute to carbon storage. Principal component analyses revealed basal area, tree diameter and carbon stock were positively intercorrelated and associated. Species dominance and tree density are intercorrelated and strongly associated. Conversely, the number of species is negatively correlated to species dominance and tree density. This study showed the significance of tree diameter in impacting carbon stock
Synthesis of Willow Leaves and Apricot Leaves-based Carbon Quantum Dots Fluorescent Probes and their Applications in Biosensing
Get PDFMetal cations and biomolecules are essential for a wide range of physiological processes. The unique nanostructure of carbon quantum dots (CQDs) gives them excellent fluorescence properties and biocompatibility as fluorescent probes, which have great potential for applications in biosensing. However, current research on CQDs as fluorescent probes faces three major challenges: the use of unsafe and toxic chemical raw materials, low quantum yield, and low accuracy. A technique was devised to synthesize CQDs fluorescent probes from non-toxic willow leaves. An experiment was conducted for 12 h at a pH of 7.4 and a
temperature of 200°C. Based on the ability of Cu²⁺ ions to form a complex with CQDs and pyrophosphate (PPi), an "off-on-off" fluorescent probe was developed. This probe enables
the selective detection of pyrophosphatase (PPase) with a CQDs dosage of 50 µL, a PPi concentration of 5.0×10⁻⁴ mol/L, and a response time of 40 min. The results indicated that the linearity of PPase was satisfactory within the range of 0 to 0.8 U/mL, represented by the linear equation y=-656.83x+710.43, with a linear correlation coefficient of R2=0.9968. This method is expected to be applicable to the detection of human serum samples. The use of willow leaves gives the CQDs a quantum yield of 12.1% only. Therefore, a novel phosphorus-doped biomass CQDs (P-BCQDs) fluorescent probe was designed. The addition of sodium pyrophosphate gives the quantum yield as high as 25.4%. The P-BCQDs exhibit a response time of 2 minutes for the detection of Hg²⁺ at a pH of 7, with concentrations of Hg²⁺ ranging from 0 to 20 µmol/L. A linear relationship between the F0/F of the P-BCQDs and Hg2+ concentration was established, with a detection limit of 9 nmol/L. Notably, the fluorescence of the P-BCQDs-Hg²⁺ system gradually increased with the concentration of glutathione (GSH) ranging from 0 to 10 μmol/L. This method is expected to enable the
simultaneous detection of intracellular Hg2+ and GSH. Finally, to enhance the quantum yield and to address the issue of low detection accuracy associated with a single fluorescent probe, a novel ratiometric fluorescent probe was developed by incorporating gold nanoclusters (AuNCs). CQDs with a quantum yield of 27.6% were synthesized using non-toxic, chemically rich apricot leaves as raw materials. These CQDs were then combined with GSH-conjugated AuNCs, which were synthesized through the GSH reduction of chloroauric acid to, form an AuNCs/CQDs ratio fluorescent probe. The quantitative detection of Cu(II) was accomplished through visual analysis of colour change and the ratio of emission peak intensities. During the reaction, the probe changed colour from pink to purple to blue at varying concentrations of Cu(II). The linear range of the AuNCs/CQDs ratiometric fluorescent probe for Cu(II) was 0-120 µmol/L, and the limit of detection was 0.65 µmol/L. This method is intended for the visual detection of intracellular Cu(II)
Phytochemical analysis and antibacterial activity on methanolic extract of Boesenbergia stenophylla (Jerangau Merah) rhizome against waterborne bacteria
Get PDFBoesenbergia stenophylla, locally known as Jerangau Merah, is a native wild ginger in Borneo Highlands, Sarawak. It is commonly used by the local as a traditional medicine for various diseases. The purposes of the current study are to investigate the phytochemicals and evaluate the antibacterial activities of methanolic B. stenophylla rhizome extract against Bacillus sp., Staphylococcus sp., Citrobacter sp. and Enterobacter sp. The rhizomes of B. stenophylla were extracted with pure methanol using Soxhlet method at 64°C for 8 h. The antibacterial properties of methanol extract were assessed using disc-diffusion assay. Phytochemical assays analysis revealed the presence of alkaloids, terpenoids, steroids, saponins, flavonoids and phenols. The antibacterial activity revealed that the extract had high to moderate inhibition against the growth of Bacillus sp. and Staphylococcus sp. at 100 mg/mL, with inhibition zones of 16.3 mm and 11.3 mm, respectively. Thus, the methanolic extract from B. stenophylla has potential to act as antibacterial agent
Performance Analysis of NoC and WiNoC in Multicore System Architectures
Get PDFWireless network-on-chip has emerged as an innovative and effective solution to meet the growing demands for efficient data communication in multi-core processors. It offers an alternative approach to overcoming scalability challenges in communication systems. This study offers an in-depth performance assessment of network-on-chip and wireless network-on-chip multicore system architectures in the context of a 64-core and 256-core system. The analysis includes four synthetic traffic patterns—random, shuffle, butterfly, and transpose—giving a detailed overview of how each impacts system performance. Key metrics such as data transmission delay, network throughput efficiency, and energy consumption were thoroughly analyzed. To support our conclusions, simulations were conducted on 64-core and 256-core for NoC and WiNoC multicore system. The results highlight the effectiveness of the WiNoC multicore system design, demonstrating its advantage in network performance based on the simulations carried out with Noxim. WiNoC’s enhanced ability to handle higher traffic loads and achieve lower latency across all traffic profiles showcases its advantage over the traditional NoC setup
Antimicrobial resistance in Malaysia : a cross-sectional study analysing trends and economic impacts.
Get PDFObjective This national study assessed the economic
impact of treating patients with antimicrobial resistance
(AMR) pathogens within Malaysia’s Ministry of Health
(MoH) hospitals.
Design A cross- sectional study design and top- down
costing approach, analysing Malaysian diagnosis- related
group (DRG) data for AMR patients admitted to MoH
hospitals from 2017 to 2020.
Setting and participants A total of 1190 cases were
identified using International Statistical Classification of
Diseases-10 version 2010 codes for AMR pathogens.
Outcome measures The study aims to estimate direct
healthcare costs for treating AMR patients. Costs per
admission were calculated based on each patient’s length
of stay (LOS). A binary logistic regression model identified
cost determinants, with significant factors (p<0.05) further
analysed using a multivariate multiple logistic regression.
ORs with 95% CIs were determined, and treatment costs
were categorised as above or below the annual national
base rate.
Results Findings showed that costs are influenced by the
volume of cases identified through DRG codes and LOS,
which averaged between 21.7 and 36.4 days. Median
admission costs for AMR patients ranged from RM12
476.28 (IQR RM 15 655.93) to RM19 295.11 (IQR RM20
200.28). Both LOS and total costs increased annually, from
RM3 711 046.10 in 2017 to RM9 700 249.08 in 2019.
Patients over 56 years old and those with severity levels II
and III were more likely exceeding the national base rate.
Conclusions These findings, explaining 9.3% of the
variance in the regression model, can inform policies to
reduce the economic burden of AMR and improve patient
outcomes, highlighting the need for a comprehensive
strategy to address this global health threat
Preserving and Exploring Transition of Indigenous Knowledge on Traditional Healing Ritual Among Melanau Community in Mukah Division of Sarawak
Get PDFTraditional healing rituals are a part of Indigenous Knowledge that has been utilized by indigenous communities as a healthcare system because it is significant and more profoundly established and complex than is generally perceived. In today’s modern world, Indigenous Knowledge is experiencing extinction due to the fact that it has been ignored and not documented. This research focused on preserving and exploring transition of Indigenous Knowledge on traditional healing rituals among the Melanau community in Mukah Division (Mukah, Dalat and Oya) of Sarawak. There are three main objectives of this research; (1) to identify the importance of preserving Indigenous Knowledge on traditional healing rituals; (2) to analyze the transition of Indigenous Knowledge on traditional healing ritual among the Melanau community and; (3) to examine the function of sago (balau) and the changes in its importance in Melanau community and traditional healing ritual. This qualitative research involved 20 informants who consisted of a Melanau traditional healer, a community leader, cultural related authorities and three groups from the Melanau community which are the elderly, adult, and youth group from Mukah Division. The informants were selected through a purposive sampling method and the data was collected through in-depth interviews. The findings of this study revealed that there was only one Melanau traditional healing ritual that is still practiced which is the dakan/bilum healing rituals and there are only two Melanau traditional healers available. This study also discovered that dance, museum, and oral narrations are some of the ways used to preserve this Indigenous Knowledge. Modern medicine, religious conversion and restrictions are the main factors that impacted the Melanau traditional healing rituals. This research also discovered that balau or sago is connected to the Melanau way of life because it is the main source of food, income, traditional healing rituals and many other usages. This research is significant because it
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contributed to the corpus of knowledge on preservation of the Indigenous Knowledge on Melanau traditional healing ritual among Melanau community. The policy implication is the need to establish protective, inclusive, and empowering frameworks that safeguard Indigenous Knowledge, promote cultural preservation, and integrate traditional wisdom into sustainable development and modern systems while respecting indigenous rights and self- determination. Governments, NGOs, and academic institutions must work collaboratively with indigenous communities to ensure IK remains vibrant and impactful for future generations
Kinetics modelling of green solvents delignified oil palm empty fruit bunch pyrolysis via thermogravimetric analysis
No full textThe urge to seek for green alternatives in replacement of conventional pretreatment methods has led to the disclosure of a new class of designer solvents termed Low-Transition-Temperature-Mixtures (LTTMs) as a prospective green pretreatment method. Correspondingly, a kinetic study on the pyrolysis process of sucrose-based LTTMs pretreated oil palm empty fruit bunch (EFB) was carried out by using thermogravimetric analysis (TGA) equipment at various heating rates of 10, 30, 50 and 70 ℃/min. The present research project focused on the thermal degradation and determination of kinetic parameters such as the activation energy and frequency factor by means of three model-free methods namely Kissinger model, Kissinger-Akahira-Sunose (KAS) model and Flynn-Wall-Ozawa (FWO) model. The results derived from TGA showed that three stages of thermal decomposition of oil palm EFB were identified such as dehydration, devolatilisation and degradation. In addition, the weight loss curves indicated that the pyrolysis of untreated and delignified EFB took place mainly in the range of 200 ℃ to 400 ℃. Moreover, the peaks of the differential thermogravimetry (DTG) curves which represent maximum degradation tended to shift slightly towards the right at higher temperature when the heating rates were being increased. The results showed that the values of kinetic parameters evaluated from model-free methods were compatible with each other whether it be untreated EFB or the delignified EFB. Furthermore, there was an increase in the activation energies after the process of pretreatment. Specifically, the activation energies increased from 129.40 kJ/mol to 188.83 kJ/mol for Kissinger model; 167.87 kJ/mol to 194.93 kJ/mol for KAS model; 167.22 kJ/mol to 190.09 kJ/mol for FWO model
Enhancing logistic regression model through AHP-initialized weight optimization using regularization and gradient descent adaptation: A comparative study
Get PDFThis study explores an approach to improving the performance of logistic regression model (LR) integrated with Analytic Hierarchy Process (AHP) for weight initialization model with regularization and adaptation of gradient descent (GD). Traditional LR model relies on random weight initialization leading to suboptimal performances. By employing AHP, a hybrid model that deployed priority vector as initial weights is obtained, reflecting the relative importance of input features. Previous works reported subpar performances of AHP-LR hybrid model due to the lack of optimizing for the initialized weights. In this study, the weights are proposed to be optimized with L1 and L2 regularization approach, penalizing deviations from the AHP-initialized weights through modified log-likelihood function with modified GD optimization. This comparative analysis involves four models: LR with L2 regularization, AHP weights as LR weights, and AHP-weights optimized with L1 and L2 regularization. A prediction experiment is conducted using synthetic dataset to assess the models' performance in terms of accuracy, recall, precision, F1-score, and ROC-AUC. The results indicate that optimizing weights with L1 or L2 regularization significantly enhances model performance, compared to direct application of AHP weights without optimization yields near-random guesses. Additionally, incorporating true expert-derived weights, evaluating their impact on model performance and experimenting with authentic dataset and different weight derivation methods would offer valuable insights