Showing papers by "National University of Malaysia published in 2023"

Solid waste management in emerging economies: opportunities and challenges for reuse and recycling

Abstract: The increasing generation of solid waste, varying waste compositions, and inefficient waste recovery processes have limited the performance of traditional approaches. It is urgent to collect a virtual special issue (VSI) that consolidates research on efficient models and better treatment technologies to break up the current system limitations. Recently, Solid Waste Management (SWM) strategies that focus on reuse and recycling have revealed their current limitations or challenges. An awareness of the progress in addressing these limitations through the advancement in available technologies and the development of new systematic approaches for SWM are of increasing importance not just for advanced but more for emerging economies. Herein, this VSI aims to provide a review and collect important studies for SWM on reuse and recycling. The challenges and future opportunities in the application of SWM have been discussed to highlight the potential development in this VSI.

Necking mechanism under various sintering process parameters – A review

Abstract: The process of sintering involves applying pressure and heat to the materials without melting them in order to fuse the particles together into a solid mass. The fusion between the particle are also known as interparticles necking which plays an important role in producing high-density products. Increasing in necking size between particles will allow the formation of smaller pore sizes which help to produce stronger and higher hardness materials. The necking also plays an essential role in producing high porosity products that are commonly used for medical applications which still required high tensile value and hardness. For this, proper process parameters were required to produce larger necking growth. To get a better understanding of this matter, the effect of powder and processing parameters will be reviewed in this article. The parameters for different processes such as conventional sintering, microwave sintering, selective laser melting, and others will be discussed in this paper as well.

A Survey on Resource Management for 6G Heterogeneous Networks: Current Research, Future Trends, and Challenges

Abstract: The sixth generation (6G) mobile communication system is expected to meet the different service needs of modern communication scenarios. Heterogeneous networks (HetNets) have received a lot of attention in recent years due to their potential as a novel structure for evolutionary networks. When compared to homogeneous networks, HetNets provide more potential for spatial spectrum reuse and higher quality of service (QoS). However, effective resource management (RM) solutions are essential to prevent interference and accomplish spectrum sharing due to mutual interference. This paper presents a comprehensive review of resource management in 6G HetNets. The study aims to give crucial background on HetNets to aid in the creation of more effective methods in this field of study. First, a detailed examination of recent work is presented in resource management aspects such as power allocation, user association, mode selection, and spectrum allocation. Second, we identify the most severe challenges associated with the current resource management methods and propose suitable solutions. Finally, several open issues and emerging areas of research are highlighted.

Biosensor Development

Abstract: Research and development of biosensors has become the focus of many research disciplines due to the COVID-19 pandemic. The existence of biosensors has had a huge positive impact towards users due to their simple, rapid, cost effective, highly selective, and sensitive nature. The technology advancement has contributed to the improvement of healthcare systems and medicine. This chapter overviews the evolution of biosensors from the beginning until now. Three generations of biosensors with their commercialized products are highlighted. Besides that, a list of advance biomaterials which are bioresorbable and flexible are itemized. Then, the standard protocol of bio-sensing is emphasized.

Uncertainty Quantification and Sensitivity Analysis for Digital Twin Enabling Technology: Application for BISON Fuel Performance Code

Abstract: As US Nuclear Regulatory Committee (NRC) recently announced machine learning (ML) and artificial intelligence (AI) will be the main research topics in the nuclear industry. One of the applications is the development of new nuclear fuels using digital twin technology, in which machine learning-based data analysis methods will significantly contribute to accelerate developments. This chapter introduces the ML-based uncertainty quantification and sensitivity analysis methods and shows its actual application to nuclear fuel development codes: a finite element-based nuclear fuel performance code BISON.

Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification

Abstract: Robust optimization is a method for optimization under uncertainties in engineering systems and designs for applications ranging from aeronautics to nuclear. In a robust design process, parameter variability (or uncertainty) is incorporated into the engineering systems’ optimization process to assure the systems’ quality and reliability. This chapter focuses on a robust optimization approach for developing robust and reliable advanced systems and explains the framework for using uncertainty quantification and optimization techniques. For the uncertainty analysis, a polynomial chaos-based approach is combined with the optimization algorithms MOSA (Multi-Objective Simulated Annealing), and the process is discussed with a simplified test function. For the optimization process, gradient-free genetic algorithms are considered as the optimizer scans the whole design space, and the optimal values are not always dependent on the initial values.

Visible-light-driven photocatalytic hydrogen production on defective, sulfur self-doped g-C3N4 nanofiber fabricate via electrospinning method

Abstract: This study scrutinized the impact of the sulfur (<1.0 wt. %), calcination temperature (550–650 ºC), and structure (bulk, nanofiber) on the texture-photoelectronic characters, crystallinity, and performance of the fabricated g-C3N4 over H2 evolution rate (HER). Sulfur self-doped g-C3N4 nanofiber with porous structure and carbon vacancies (labeled as SCNF) was fabricated via an electrospinning process followed by suitable thermal treatment. The formation mechanism was proposed. Compared to S-doped g-C3N4 bulk, the S-doped g-C3N4 nanofiber showed a 2.84 folds improvement in HER (ca. 632 μmol/h.g) under identical testing conditions. The enhancement for the photocatalytic activity of SCNF samples related to the photoelectronic-texture feature, which enhanced the charge separation efficiency, suppressed the recombination rate, and improved the Vis-light harnessing capability. Interestingly, the modified g-C3N4 showed the ability to interact with long wavelengths up to 710 nm. As the synthesis method for SCNF with high performance is simple, the SCNF can be envisioned as applicable in solar energy conversion and environmental remediation, which is beneficial to the environment and human development.

One-pot gamma radiolysis synthesis of a graphene oxide-supported cobalt oxyhydroxide electrocatalyst for oxygen reduction reaction

Abstract: In this work, high-performance non-platinum group metal (non-PGM) electrocatalysts for oxygen reduction reaction (ORR) are synthesized from graphene oxide-supported cobalt oxyhydroxide nanoparticles via a one-pot gamma radiolysis method. Investigations are conducted into how cobalt precursor concentration and the amount of gamma radiation affect the electrocatalysts' ability to perform oxygen reduction reactions as well as their physicochemical characteristics. Results show that the electrocatalyst prepared with the 0.1 M cobalt precursor and gamma radiation dose of 25 kGy has an advantage over the other samples in displaying good oxygen reduction activity. The characterization results of the synthesized electrocatalyst obtained through field-emission scanning electron microscopy–energy dispersive spectroscopy and X-ray diffraction combined with Rietveld refinement confirm the presence of nanosized cobalt oxyhydroxide particles that are evenly distributed on the surface of graphene oxide. ORR results show that the electrocatalyst has an onset potential of 0.90 V (vs. the reversible hydrogen electrode or RHE), a half-wave potential of 0.75 V (vs. RHE), a low peroxide yield of 7.08%, and an electron transfer number of 3.86, indicating a four-electron transfer path-way in the ORR process. This work provides an alternative facile means to mass-produce competitive non-PGM ORR electrocatalysts for fuel cell applications.

Multi-method evaluation of a 2-(1,3,4-thiadiazole-2-yl)pyrrolidine corrosion inhibitor for mild steel in HCl: combining gravimetric, electrochemical, and DFT approaches

Abstract: The corrosion inhibition properties of 2-(1,3,4-thiadiazole-2-yl)pyrrolidine (2-TP) on mild steel in a 1 M HCl solution were investigated using weight loss, potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and open circuit potential (OCP) measurements. In addition, DFT calculations were performed on 2-TP. The polarization curves revealed that 2-TP is a mixed-type inhibitor. The results indicate that 2-TP is an effective inhibitor for mild steel corrosion in a 1.0 M HCl solution, with an inhibition efficiency of 94.6% at 0.5 mM 2-TP. The study also examined the impact of temperature, revealing that the inhibition efficiency increases with an increasing concentration of 2-TP and decreases with a rise in temperature. The adsorption of the inhibitor on the mild steel surface followed the Langmuir adsorption isotherm, and the free energy value indicated that the adsorption of 2-TP is a spontaneous process that involves both physical and chemical adsorption mechanisms. The DFT calculations showed that the adsorption of 2-TP on the mild steel surface is mainly through the interaction of the lone pair of electrons on the nitrogen atom of the thiadiazole ring with the metal surface. The results obtained from the weight loss, potentiodynamic polarization, EIS and OCP measurements were in good agreement with each other and confirmed the effectiveness of 2-TP as a corrosion inhibitor for mild steel in 1.0 M HCl solution. Overall, the study demonstrates the potential use of 2-TP as a corrosion inhibitor in acid environments.

Resistance Spot Welding and Laser Welding Effect on Nickel Tab for Electric Vehicle Battery Development

Abstract: In this study, the joint ability of two different joining techniques, namely resistance spot welding and laser welding of nickel weld interfaces and joint microstructure were addressed. Similar materials of nickel joint were used to investigate the parallel connection of tab cells for electric vehicle (EV) battery development. It was found that using the parameters discussed, the joining of two similar nickel was successfully achieved via these welding methods. The results show that the material joints fabricated using laser welding had the highest average stress value of 155.86 MPa, whereas the average for nickel joints of resistance spot welding was 122.25 MPa. In addition, the results of FESEM analysis on the cross-section of the weld material also found that the length of the surface for the material being connected and affects the stress value. For resistance spot welding process, 0.09 s of welding time promoted the formation of sound weld beads with better control of penetration depth and excellent joint interface. Compared to the resistance spot welding process, laser welding produced a better weld interface, which contributes to a higher strength value.

Green Software Product: The Empirical Study on Social Factor and Measurements

Abstract: Today's digitised world is concerned with software products that highlight sustainability and green compliance with social requirements and expectations. Literature investigations reveal that many studies have focussed on green hardware. Nevertheless, little effort was proposed to ensure the greenness of software that complies with the specification. Green software products are essential because they may address issues related to sustainability and ensure that software can be used indefinitely. According to the current literature, investigations on the social sustainability of software products still have a deficit. The green elements are still needed for further investigation in the scope of green assessment of software products. This study aims to identify the principal factor and measurements of the social sustainability requirements of a green software product. The analysis of the factor and measurements shows strong relationships between them. The results are validated through the empirical study conducted with 102 respondents.

Local Community Involvement in Protecting Malaysia’s Historic Buildings: An Exploratory Study

Abstract: The local community contributes significantly to the preservation of historic structures. Through the participation of the local community, the preservation of historic structures will be enhanced. In addition to the benefits from a more efficient management perspective, the preservation of this heritage is also perceived to help the local population. Nevertheless, previous research indicates that aspects of heritage management and the involvement of the local community are still at a minimal level, with many previous studies focusing more on the uniqueness of heritage and conservation methods that link heritage subjects with culture and history than on strategic cooperation between stakeholders, particularly the local community. Consequently, the purpose of this study is to identify effective incentives that have been cultivated abroad that can serve as a model for ensuring the participation of local populations in the preservation of historic structures in Malaysia. To reach this objective, a qualitative method has been employed in this study. An examination of 150 prior studies at the local and international levels that focused on the participation of local communities in guaranteeing more effective preservation efforts for historic buildings. This study identified four sorts of incentives that can stimulate the involvement of the local community, thereby making heritage conservation efforts more effective: (i) communities that live near historic structures are more likely to be involved in conservation efforts; (ii) the community's sense of attachment and significant duty to preserve their heritage contained in a historic building; (iii) early introduction of children to the relevance of history; and (iv) implementation of economic activities as a container for the preservation of historic buildings. This study concludes that the local Malaysian population lacks the motivation to maintain historic structures. However, as evidenced by research conducted abroad, encouragement that has been successful in improving local community motivation to protect historic structures can be utilised as a model to inspire conservation within Malaysia's local community.

Effects of mobile apps intervention on medication adherence and type 2 diabetes mellitus control: A systematic review and meta-analysis

Abstract: The prevalence of non-adherence to antidiabetic treatment remains high despite various efforts. Thus, the positive effects of the antidiabetic treatment cannot be optimised and the disease progresses to complications. This present systematic review and meta-analysis aimed to evaluate the effects of mobile applications (apps) intervention on medication adherence and type 2 diabetes mellitus (T2DM) control.This research was conducted following the PRISMA guidelines. The databases that had been searched included Web of Science, PubMed, Scopus, Cochrane Library and Ovid from 2017 to 2022. Study characteristics were retrieved and study outcomes such as adherence status and diabetes control were extracted and quantitatively analysed through meta-analysis.Eight studies met the final inclusion criteria and were included in the analysis, contributing to a total of 884 subjects. The methodological quality of the included studies was variable. Three studies reported statistically significant improvement in medication adherence through mobile apps intervention. Additionally, the mobile apps intervention proved effective in reducing glycaemic outcomes. As compared to non-mobile apps users, glycated haemoglobin (HbA1c) significantly decreased by 0.36% (95% CI -0.47% to -0.25%), whereas fasting plasma glucose (FPG) significantly decreased by 16.75 mg/dL (95% CI -17.60 mg/dL to -15.80 mg/dL).Mobile apps intervention had beneficial impacts on medication adherence and glycaemic parameters. Future research should explore the best practical approach for real-world settings.

Semi-Supervised Model for Aspect Sentiment Detection

Abstract: Advancements in text representation have produced many deep language models (LMs), such as Word2Vec and recurrent-based LMs. However, there are scarce works that focus on detecting implicit sentiments with a small amount of labelled data because there are many different review areas. Deep learning techniques are suitable to automate the representation learning process. Hence, we proposed a semi-supervised aspect-based sentiment analysis (ABSA) model for online review to predict explicit and implicit sentiment in three domains (laptop, restaurant, and hotel). The datasets of this study, S1 and S2, were obtained from a standard SemEval online competition and Amazon review datasets. The proposed models outperform the previous baseline models regarding the F1-score of aspect category detection and accuracy of sentiment detection. This study finds more relevant aspects and accurate sentiment for ABSA by developing more stable and robust models. The accuracy of sentiment detection is 84.87% in the restaurant domain on the first dataset. For the second dataset, the proposed method achieved 84.43% in the laptop domain, 85.21% in the restaurant domain, and 85.57% in the hotel domain. The novelty is the proposed new semi-supervised model for aspect sentiment detection with embedded aspect inspired by the encoder–decoder architecture in the neural machine translation (NMT) model.

A novel technique on flexibility and adjustability of generalized fractional Bézier surface patch

Abstract: <abstract><p>Designing complex surfaces is one of the major problems in industries such as the automotive, shipbuilding and aerospace industries. To solve this problem, continuity conditions between surfaces are applied to construct the complex surfaces. The geometric and parametric continuities are the two metrics that usually have been used in connecting surfaces. However, the conventional geometric and parametric continuities have significant limitations. The existing continuity conditions only allow the two surfaces to be joined at the end of the boundary point. Therefore, if the designers want to connect at any arbitrary line of the first surface, the designers must use the subdivision method to splice the surfaces. Nevertheless, this method is tedious and involves a high computational cost, especially when dealing with a higher degree order of surfaces. Thus, this paper presents fractional continuity of degree two (or $ F^2 $) for generalized fractional Bézier surfaces. The fractional parameter embedded in the generalized fractional Bézier basis functions will solve the mentioned limitation by introducing fractional continuity. The generalized fractional Bézier surface also has excellent shape parameters that can alter the shape of the surface without changing the control points. Thus, the shape parameters enable the control of the shape flexibility of the surfaces, while fractional parameters enable the control of the adjustability of the surfaces' size. The $ F^2 $ continuity for generalized fractional Bézier surfaces can become an easier and faster alternative to the subdivision method. Therefore, the fractional continuity for generalized fractional Bézier surfaces will be a good tool to generate complex surfaces due to its flexibility and adjustability of shape and fractional parameters.</p></abstract>

Elucidating the dynamic remodelling of Escherichia Coli interactome in different growth conditions using multiplex co-fractionation MS (mCF-MS)

Abstract: Most proteins function by forming complexes within a dynamic interconnected network that underlies various biological mechanisms. To systematically investigate such interactomes, high-throughput techniques including CF-MS have been developed to capture, identify, and quantify protein-protein interactions (PPIs) in large-scale. Compared to other techniques, CF-MS allows the global identification and quantification of native protein complexes in one setting, without genetic manipulation and overexpression. Furthermore, quantitative CF-MS can potentially elucidate the distribution of a protein in multiple co-elution features, informing the stoichiometries and dynamics of a target protein complex. In this issue, Youssef et al. (Proteomics 2023, XX, XXXX-XXXX) combined multiplex CF-MS and an in-house algorithm to study the dynamics of the PPI network for Escherichia coli grown under ten different conditions. While the results demonstrated that while most proteins remained stable, the authors were able to detect disrupted interactions that were growth condition-specific. Further bioinformatics analyses also revealed biophysical properties and structural patterns that govern such a response.

A study to examine the ageing behaviour of cold plasma-treated agricultural seeds

Abstract: Cold plasma (low pressure) technology has been effectively used to boost the germination and growth of various crops in recent decades. The durability of these plasma-treated seeds is essential because of the need to store and distribute the seeds at different locations. However, these ageing effects are often not ascertained and reported because germination and related tests are carried out within a short time after the plasma-treatment. This research aims to fill that knowledge gap by subjecting three different types of seeds (and precursors): Bambara groundnuts (water), chilli (oxygen), and papaya (oxygen) to cold plasma-treatment. Common mechanisms found for these diverse seed types and treatment conditions were the physical and chemical changes induced by the physical etching and the cold plasma on the seeds and subsequent oxidation, which promoted germination and growth. The high glass transition temperature of the lignin-cellulose prevented any physical restructuring of the surfaces while maintaining the chemical changes to continue to promote the seeds germination and growth. These changes were monitored over 60 days of ageing using water contact angle (WCA), water uptake, electrical conductivity, field emission scanning electron microscopy (FE-SEM) and X-ray photoelectron spectroscopy (XPS). The vacuum effect was also investigated to separate its effect from cold plasma (low pressure). This finding offers a framework for determining how long agricultural seeds that have received plasma treatment can be used. Additionally, there is a need to transfer this research from the lab to the field. Once the impact of plasma treatment on seeds has been estimated, it will be simple to do so.