National University of Malaysia

This review explores the diverse applications of nitrogen‐doped carbon derived from Albizia procera, known as white siris. Native to the Indian subcontinent and tropical Asia, this species thrives in varied conditions, contributing to sustainable development. The nitrogen‐rich leaves of Albizia procera are an excellent source for synthesizing nitrogen‐doped carbon, which possesses remarkable properties for advanced technologies. This material demonstrates significant potential in energy conversion and storage systems, such as supercapacitors and batteries, due to its high surface area, electrical conductivity, and chemical stability. Nitrogen doping introduces active sites that enhance charge storage, making it ideal for renewable energy applications. Additionally, this material shows promise in environmental processes like water splitting and carbon dioxide capture, where its porous structure and chemical functionality enable efficient adsorption and remediation. The review discusses synthesis methodologies, including pyrolysis and activation, to optimize its properties for energy and environmental uses. Nitrogen‐doped carbon derived from Albizia procera may expand into catalytic applications, enhancing its role in sustainable technologies. This review underscores the importance of utilizing natural resources like Albizia procera to develop materials that drive both environmental sustainability and technological innovation.

Advancements in deep learning (DL) and machine learning (ML) in recent times have paved the way for transformative applications in healthcare, offering unprecedented opportunities for better healthcare for patients, diagnosis, and treatment. Among the array of methodologies emerging in this domain, bio-inspired algorithms have garnered significant attention for their potential to enhance ML and DL models. These algorithms, inspired by natural processes observed in biological systems, offer creative solutions to the intricate difficulties encountered in the medical field. This paper explores present research directions and challenges in leveraging bio-inspired algorithms for advancing ML and DL models in healthcare. We delve into the potential applications and limitations of these bio-inspired approaches, shedding light on their efficacy in optimizing model parameters, facilitating feature selection, and refining architecture design for healthcare-specific tasks. However, despite their promise, bio-inspired algorithms also confront various challenges like Scalability, interpretability, and robustness to noisy and heterogeneous healthcare data which remain primary concerns. Additionally, the ethical implications of utilizing these algorithms in sensitive healthcare contexts warrant careful consideration. By fostering interdisciplinary collaboration and advancing novel algorithmic approaches, we aim to get beyond these obstacles and unleash the complete potential of bio-inspired algorithms in healthcare. Ultimately, our goal is to harness the power of these algorithms to drastically transform healthcare delivery, improving patient outcomes, individualized treatment strategies, and more precise diagnosis.

This study assessed the spatial variations of water quality and trophic state of the ex-mining lakes converted into man-made wetlands in Paya Indah Wetlands, Selangor, Malaysia. The variations of the parameters were referred to the National Water Quality Standard (NWQS) to determine the water quality index (WQI) and Carlson's Trophic State Index (CTSI), guided by the National Lake Water Quality Standard (NLWQS) to assess the quality and trophic state of lake water. Water sampling was carried out at 13 stations within the Main Lake, Sendayan Lake and Teratai Lake through the DotS sampling method. The potential pollution sources affecting water quality were quantified using a statistical approach, including Pearson's correlation and principal component analysis/factor analysis (PCA/FA). The results show that the water quality parameters in some stations exceeded the NLWQS. Pearson analysis shows that nutrients flow with the organic and inorganic matter in the lake. Average WQI values ranged from 62 to 77, indicating slightly polluted to clean water quality in Paya Indah Wetlands. Two factors were found to account for over 82% of the total variation in the dataset when PCA was used to compare the compositional patterns among the samples that were analysed. This suggests that the point source (open areas for development) and non-point source (agriculture-oil palm estate) as well as the natural processes are the main causes of fluctuations in the concentration of the water components. Organic matter and nutrient regimes mainly affect water quality. Even though the lakes at the studied stations are currently hypertrophic, the overall water quality assessment categorises Paya Indah Wetlands as Class III. Hence, Paya Indah Wetlands has great potential to be an alternative water source supplying water to surrounding areas which require extensive water treatment.

Rainfall-induced landslides are a frequent geohazard for tropical regions with prevalent residual soils and year-round rainy seasons. The water infiltration into unsaturated soil can be analyzed using the soil-water characteristic curve (SWCC) and permeability function which can be used to monitor and predict incoming landslides, showing the necessity of selecting the appropriate model parameter while fitting the SWCC model. This paper presents a set of data from six different sections of the studied slope at varying depths that are used to test the performance of three SWCC models, the van Genuchten-Mualem (vG-M), Fredlund-Xing (F-X) and Gardner (G). The dataset is obtained from field monitoring of the studied slope, over a duration of 6 months. The study discovered that the van Genuchten-Mualem model provided the best estimation based on RMSE and evaluation metric, R2 followed by Fredlund and Xing, and Gardner, however, the difference between them is minor. The R2 obtained varies as the value at the crest with 1.0 m depth has a mean of 0.44, the lowest among the overall data fitted but it also has the best RMSE value with a mean of 0.00473. Whereas the location mid-section at a depth of 1.0 m has the highest R2 with a mean of 0.97, and an average value of RMSE of 0.0145 which is the middle of the group that was fitted. This indicates that R2 measurement for model performance relies highly on the dispersion of the variables collected. The dispersion of the data set is mainly due to the sensors’ inability to detect effectively at exceedingly high matric suction and zero matric suction. The investment in improving the equipment’s precision will boost reliability and reduce the number of assumptions as the data is collected from the site rather than laboratory testing.

Gender equality and women’s empowerment have been increasingly emphasised in food production systems, including fisheries and aquaculture. Accurate assessment and understanding of the state, progress and changes in women’s empowerment in the sub-sectors is required. We applied the project level Women’s Empowerment in Fisheries and Aquaculture Index (pro-WEFI), which is based on the project-level women’s empowerment in agriculture index (pro-WEAI) to standardize the measurement of women’s agency and empowerment in fisheries and aquaculture. Drawing on a survey conducted in north-western Bangladesh, we examined quantitative pro-WEFI data collected from 217 households engaged in aquaculture. Only 33% of the women and 48% of the men in the sample achieved empowerment in aquaculture, attaining scores of 0.75 and above. The mean disempowerment score (1-3DE) revealed that both women and men failed to achieve adequacy on average in nearly 28% of the indicators. Nearly 40% of the dual adult households did not attain gender parity with women achieving lower adequacy scores than men from the same household. Women’s disempowerment was primarily driven by lack of autonomy in their use of income (18.5%), inability to visit important locations (17.4%), and inadequate access to and decision making on financial services (13.4%). Our findings emphasize the significance of conducting comprehensive assessments of women’s empowerment in aquaculture initiatives and its various domains and indicators inform the development of targeted and effective interventions. By identifying domains where gender inequality is most pronounced, projects can better design interventions to create targeted impacts in critical areas.

Climate change is expected to result in intensifying extreme weather that would increase the risks of climate hazards; leading to natural hazards triggering technological disasters (Natech) events. This paper highlights a simple method using easily available information to identify potential sites for Natech associated with climate change based on a case study of the Selangor River Basin in Malaysia. The approach draws heavily on susceptibility modelling, in combination with screening processes to delineate exposed potential point sources, followed by field inspection to validate the information. Findings reveal that with the onset of climate change, over 55% of the manufacturing industries in the Selangor River Basin are exposed to the risk of Natech due to floods and coastal inundation. The approach can be applied to river basins where industrial activities are prevalent and local information on future climate conditions is limited. It is useful for raising awareness, providing early warning of emerging hazards in worst-case scenarios, and prioritizing climate actions on Natech risk due to climate change.

Background High‐income countries (HICs) are over‐represented in current global dementia incidence rates, skewing estimates. Variance in diagnostic methods between HICs and low‐ and middle‐income countries (LMICs) is speculated to contribute to the regional differences in rates. Cohort Studies of Memory in an International Consortium (COSMIC) offers a unique opportunity to address these research inequalities by harmonising data from international studies, including representation from LMICs. This study aimed to identify dementia incidence rates by age and sex in various regions worldwide, where data for dementia diagnosis were available. Method Data were obtained from 36 members of COSMIC, representing 28 countries across 6 continents (HICs: Australia, Canada, Faroe Islands, France, Germany, Greece, Italy, Japan, Netherlands, South Korea, Spain, Sweden, & USA; LMICs: Brazil, China, Cuba, Dominican Republic, Ecuador, Indonesia, Malaysia, Mexico, Nigeria, Peru, Philippines, Republic of Congo, & Tanzania). For each member study, we calculated incidence rates for all‐cause dementia. Findings from 14 studies, with a consensus diagnosis are presented in the results. Using an Item Response Theory approach, we are currently calculating a comparable incidence rate for those studies without a consensus diagnosis. Result Consistent with previous trends, incidence rates (per 100 person‐years) increased with age, from 65‐70 years‐old to 85‐90 years‐old, for both males (i.e., Republic of Congo, 4.41 to 19.57; France, 0.46 to 3.89; USA, 0.17 to 3.22; Spain, 0.31 to 4.22; 65‐70 & 85‐90 cohorts respectively) and females (i.e., Republic of Congo, 3.57 to 15.31; France, 0.45 to 3.72; USA, 0.22 to 4.25; Spain, 0.36 to 4.96; 65‐70 & 85‐90 cohorts respectively). There were no sex differences in incidence rates in younger age groups (60‐65). Among older age groups, however, women tended to have higher incidence rates than men, in some countries (Faroe Islands, Germany, Sweden, and USA). Conclusion Geographical differences in dementia incidence rates likely represent inherent variation among countries, beyond methodological considerations. We are working to expand the range of studies and regions for which we calculate dementia incidence rates. This involves the development of approaches to classify and harmonise incident dementia in studies lacking consensus diagnoses. Doing so will bolster LMIC representation.

Ecological discourse analysis (EDA) has sparked growing attention in ecolinguistics. To reveal the status and trend of EDA (2014–2023), this research conducts a systematic literature review (SLR) on this topic, employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement as the established standard. After analysis, the SLR revealed that the number of EDA increased significantly between 2014 and 2023. Notably, Chinese scholars demonstrated the greatest focus on this topic. While EDA was widespread across various countries, international collaboration still needs to be enhanced. Meanwhile, some scholars tended to conduct EDA by adopting multiple research approaches. This SLR also unveiled the latest focuses on EDA, such as the language and its relationship with ecosophy, the ecological influence of discourses, the noteworthy topics of climate change and children’s literature, and the gap of the study on video discourse. This enables the employment of multimodal discourse research and interdisciplinary approaches for EDA to be the future trend. Since this SLR gives a comprehensive description of the trajectory of EDA, it can offer a meaningful reference for the studies relating to EDA in the linguistics domain.

The global incidence of mosquito-borne diseases has markedly increased in recent years. The control of mosquito vector is crucial in order to prevent epidemics across many countries. Nanoemulsions have been regarded as good carriers for delivering essential oil with the intervention of biopolymers to increase their efficacy. Therefore, the present study aimed to assess the effectiveness of three types of nanoemulsion formulations which consist of betel and clove essential oils encapsulated with cationic guar gum as fabric finishes. The nanoemulsion formulations were characterised using dynamic light scattering (DLS) and high-resolution transmission electron microscopy (HR-TEM), while field emission scanning electron microscopy (FESEM) was used to characterise treated fabrics. All nanoemulsion formulations exhibit up to more than 50% of encapsulation efficiency and are able to control the release of essential oils from their colloidal systems up to 150 h. Nanoemulsion formulations recorded -16.8 to -25.2 mV of zeta potential with 0.25 to 0.49 polydispersity index values. Based on the Excito chamber study, after a single washing and heating cycle, the effectiveness of repellency against Aedes aegypti applied to cotton and polyester fabrics was in the range of 98 to 100%. Following 5 washing and heating cycles, the nanoemulsion formulations were able to retain 30 to 50% of essential oil on cotton and polyester fabrics and repel 36 to 40% of mosquitoes. Overall, results from this study are significant to research and development particularly innovation of anti-mosquito fabric finishes.

This work considered the natural convection in a 3D trapezoidal cavity filled with Al2O3-water nanofluid. The left and right vertical cavity walls were maintained at different hot and cold temperatures. We compared the results of the considered tests to those of pure water and evaluated the effect of the solid volume fraction at two different values. The examined range of Rayleigh number was 103 ≤ Ra ≤ 106. In three considered cases, the insertion of a cylindrical body into a cavity was also explored. The cylinder’s radius of the first case is 0.15 times the length of the cavity. The remaining situations were two vertically aligned cylinders, and their radius was 7.5% of the cavity side length. The findings indicate that a higher solid volume fraction improves the average $\text{Nu}$ , and this improvement increases with $\text{Ra}$. For the inner cylinder cases with double cylinders above single cylinders, the average $\text{Nu }$was increased. On the other hand, the cylinders’ misaligned location improves more than in any other case. Also, when the locations of the cylinders varied at the maximum horizontal or vertical velocities, it was determined that Ra had no influence.

To improve the scientific accuracy and precision of children’s physical fitness evaluations, this study proposes a model that combines self-organizing maps (SOM) neural networks with cluster analysis. Existing evaluation methods often rely on traditional, single statistical analyses, which struggle to handle the complexity of high-dimensional, nonlinear data, resulting in a lack of precision and personalization. This study uses the SOM neural network to reduce the dimensionality of high-dimensional health data. Moreover, it integrates cluster analysis to categorize and analyze key physical fitness attributes, such as strength, flexibility, and endurance. Experimental results show that the proposed optimized model outperforms comparison models such as T-distributed stochastic neighbor embedding, density peak clustering, and deep embedded clustering in terms of performance. The accuracy for the strength dimension reaches 0.934, the F1 score is 0.862, and the area under the curve of receiver operating characteristic is 0.944. The silhouette coefficients for cluster analysis in strength, flexibility, and endurance dimensions are 0.655, 0.559, and 0.601, respectively, demonstrating good intra-class and inter-class distances. The proposed model enhances the comprehensive analysis of children’s physical fitness and provides a scientific basis for personalized health interventions, making an important contribution to research in this field.

Osteoarthritis (OA) is a chronic degenerative joint disorder characterized by an imbalance in chondrocyte metabolism. Ferroptosis has been implicated in the pathogenesis of OA. The role of Sirt1, a deacetylase, in mediating deacetylation during ferroptosis in OA chondrocytes remains underexplored. This study aimed to elucidate the mechanisms by which Sirt1 influences chondrocyte ferroptosis in the development of OA. In vitro and in vivo models of OA were established using IL-1β-induced mouse chondrocytes and a destabilization of the medial meniscus (DMM) mouse model, respectively. Ferroptosis was evaluated through measurements of cell viability, lactate dehydrogenase (LDH) release, intracellular levels of Fe2+, glutathione (GSH), malondialdehyde (MDA), lipid reactive oxygen species (ROS), propidium iodide staining, and Western blot analysis. The underlying mechanisms were further investigated using quantitative real-time polymerase chain reaction, Western blotting, immunoprecipitation (IP), co-immunoprecipitation (Co-IP), and glutathione-S-transferase pulldown assays. In vivo validation was performed via Safranin O staining. IL-1β induced ferroptosis and increased histone acetylation, effects that were partially reversed by Sirt1 overexpression. Mechanistically, Sirt1 overexpression upregulated ferritin light polypeptide (Ftl) expression by deacetylating Ftl at the K181 residue. Ftl knockdown inhibited the ferroptosis-enhancing effect of Sirt1 overexpression in chondrocytes. In vivo studies showed that Sirt1 overexpression mitigated the progression of OA and reduced ferroptosis in the DMM-induced OA mouse model. Our findings confirm that Sirt1 overexpression promotes Ftl expression through deacetylation at the K181 site, thereby suppressing chondrocyte ferroptosis and attenuating the progression of OA. These results suggest a potential therapeutic target for OA treatment.

This article presents a polarization-insensitive, negative indexed inverted U-shaped flexible metamaterial absorber based on a microstructure resonator for multi-band energy harvester application. The vertical inverted U-shaped joint and central split ring resonator together create significant resonance covering three consecutive L-, S-, and C-band absorption peaks for four resonance frequencies: 1.975 GHz with 99.99% absorption, 2.85 GHz with 99.28% absorption, 5.265 GHz with 96.79% absorption, and 5.5 GHz with 89.12% absorption. The design has a rare double negative metamaterial feature at 5.265 GHz, while a balanced geometrical appearance that is polarization insensitive for θ and φ improved the structure’s durability and tunability. Finite computer simulation technology was used to simulate and examine the mechanisms involved in absorption at 1— 6 GHz. Based on Rogers RO4350 B and copper, the structural design showed excellent absorption for 15° and 30° bends and 2 × 4, 4 × 8 arrays with an efficiency of 96.38% at an incidence angle of 30° in transverse magnetic mode, a 3x 3 array was developed for energy harvesting. For energy harvesting applications using array structure, the efficiency parameter is unnoted in most of the reported articles. Moreover, the array demonstrated polarization insensitivity for both transverse electric and transverse magnetic modes at angles of 0°, 30°, and 60°. The proposed quad-band absorber shows significant potential for energy harvesting applications.

Crop diseases result in significant losses and affect farmers’ livelihoods, making it crucial for the agricultural sector to remain resilient against the onset and spread of these diseases. Recent studies have emphasized building this resilience through the engineering of plant microbiomes. This chapter explores the role of plant-microbe interactions in shaping microbiome communities and examines how root exudates influence the recruitment and suppression of microorganisms in the soil. Microbe-microbe interactions also plays a crucial role in regulating the growth and decline of specific microbial populations within the soil environment. Importantly, the chapter discusses how engineering the soil microbiome can enhance disease suppression and minimize disease occurrence and transmission.

Numerous studies have investigated polymeric composites fabricated using fused deposition modelling. However, the mechanical performance of these composites, which is influenced by various factors, including materials and printing parameters, remains unknown. Further understanding these factors helps improve the accuracy of mechanical performance predictions. Therefore, this study fabricates in-house polyamide reinforced with carbon fibre at a composition of 20 wt.% and controls its printing parameters, including layer height and printing orientations. Results indicated that controlling the orientation at a 0° angle are the most crucial factor compared to layer height, which leads to a maximum flexural strength of ∼21 MPa due to improvements in load-bearing capacity and adhesion bonding between the fibre and matrix.

Aluminium nitride (AIN) is a promising thin film electrical insulation material layer in electronic devices. The magnetron sputtering method is usually employed to sputter-deposit AlN thin film on silicon (Si) substrate using a pure aluminium (Al) metallic target in a low base pressure vacuum condition. In many cases, the thin film deposition of high quality AlN crystals requires the application of heat and bias to the substrate, highly pure nitrogen reactant gas, argon sputtering gas and Al target, low sputtering pressure, high sputtering power, post-deposition AlN annealing, ultra-low base pressure of the sputtering chamber and a distinctive crystal orientation of the nucleation layer or substrate underneath. In our work, the utilisation of AlN ceramic target instead of pure Al metallic target has allegedly facilitated the growth of AlN crystals without the need to conform to these requirements. Non-amorphous AlN〈100〉 and AlN〈002〉 thin film crystals have been successfully sputtered from AlN ceramic target on Si〈100〉 substrate in a relatively high sputtering chamberbase pressure and at a moderate 200 W - 250 W of sputtering power. Additionally, 250 W of sputtering power has been observed to assist in the growth of AlN〈002〉 crystals. The presence of AlN〈002〉 may have reduced the leakage/tunnel current density in AlN thin film layer to 46.33 pA cm⁻² and modified the small-scale surface height characteristics. A high degree of AlN〈002〉 crystallisation may suggest good electrical insulating properties in AlN thin film layer, which can be applied in electronic devices that critically require a low leakage current specification.

This paper investigates the use of tantalum aluminum carbide ( ${\rm Ta}_2{\rm AlC}$ ) as a passive pulse modulator for generating ultrafast mode-locked pulses in an erbium-doped fiber (EDF) laser cavity. The ${{\rm Ta}_2}{\rm AlC}$ modulator was prepared via an embedding method using polyvinyl alcohol as the host matrix, exhibiting a saturable absorption of 6.9% with a saturable intensity of ${100}\;{{\rm MW/cm}^2}$ . When integrated into a long EDF laser cavity, the modulator enabled the generation of a picosecond soliton pulse train. Operating within a pump range of 95.2 to 210.62 mW, the self-starting mode-locked EDF laser achieved a central wavelength of 1561.7 nm, a repetition rate of 1.866 MHz, and a pulse width of 3.80 ps. These findings demonstrate that ${{\rm Ta}_2}{\rm AlC}$ is an effective passive modulator for ultrafast laser generation through mode locking.