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Biodiesel can be produced from vegetable oils, animal fats, frying oils, and from microorganism-synthesized oils. These sources render biodiesel an easily biodegradable fuel. The aim of this work was to perform an advanced bibliometric analysis of primary studies relating to biodiesel production worldwide by identifying the key countries and regions that have shown a strong engagement in this area, and by understanding the dynamics of their collaboration and research outputs. Additionally, an assessment of the main primary feedstocks employed in this research was carried out, along with an analysis of the current and future trends that are expected to define new paths and methodologies to be used in the manufacture of biodegradable and renewable fuels. A total of 4586 academic outputs were selected, including peer-reviewed research articles, conference papers, and literature reviews related to biodiesel production, in the time period spanning from 2010 to 2021. Articles that focused on feedstocks for the production of biodiesel were also included, with a search that returned 330 papers. Lastly, 60 articles relating to biodiesel production via sewage were specifically included to allow for an analysis of this source as a promising feedstock in the future of the biofuel market. Via the geocoding and the document analyses performed, we concluded that China, Malaysia, and India are the largest writers of articles in this area, revealing a great interest in biofuels in Asia. Additionally, it was noted that environmental concerns have caused authors to conduct research on feedstocks that can address the sustainability challenges in the production of biodiesel. [ABSTRACT FROM AUTHOR]

With the rapid growth in urban construction in Malaysia, road breakage has challenged traditional manual inspection methods. In order to quickly and accurately detect the extent of road breakage, it is crucial to apply automated road crack detection techniques. Researchers have long studied image-based road crack detection techniques, especially the deep learning methods that have emerged in recent years, leading to breakthrough developments in the field. However, many issues remain in road crack detection methods using deep learning techniques. The field lacks state-of-the-art systematic reviews that can scientifically and effectively analyze existing works, document research trends, summarize outstanding research results, and identify remaining shortcomings. To conduct a systematic review of the relevant literature, a bibliometric analysis and a critical analysis of the papers published in the field were performed. VOSviewer and CiteSpace text mining tools were used to analyze and visualize the bibliometric analysis of some parameters derived from the articles. The history and current status of research in the field by authors from all over the world are elucidated and future trends are analyzed. [ABSTRACT FROM AUTHOR]

Plastics are used for various applications, including in the food and beverage industry, for the manufacturing of plastic utensils and straws. The higher utilization of plastic straws has indirectly resulted in the significant disposal of plastic waste, which has become a serious environmental issue. Alternatively, bio-plastic and paper straws have been introduced to reduce plastic waste. However, limited studies are available on the environmental assessment of drinking straws. Life cycle assessment (LCA) studies for bio-plastic and paper straws have not been comprehensively performed previously. Therefore, the impact of both bio-plastic and paper straws on the environment are quantified and compared in this study. Parameters, such as the global warming potential (GWP), acidification potential (AP) and eutrophication potential (EP), were evaluated. The input–output data of the bio-plastic and paper straws processes from a gate-to-grave analysis were obtained from the literature and generated using the SuperPro Designer V9 process simulator. The results show that bio-plastic straws, which are also known as polylactic acid (PLA) straws, had reduced environmental impacts compared to paper straws. The outcomes of this work provide an insight into the application of bio-plastic and paper straws in effectively reducing the impact on the environment and in promoting sustainability, especially from the perspective of Malaysia. [ABSTRACT FROM AUTHOR]

Many shocks, including COVID-19, wars, inflation, contractionary U.S. monetary policy, and oil price hikes, have recently buffeted the world economy. The literature has reported mixed results concerning how these shocks impact Malaysian stock returns. Some studies found that U.S. monetary policy mattered for Malaysia, while others reported that it did not. This paper, employing two U.S. monetary policy measures over the 2001–2019 period, finds that U.S. policy matters little for Malaysian equities. Some studies found that oil price hikes increased Malaysian stock returns while others reported that they did not. This paper, employing updated data, reports that oil price increases, driven by both world demand shocks and oil supply shocks, raise Malaysian stock returns. The paper also compares the performance of Malaysian equities since the pandemic began, with returns forecasted based on macroeconomic variables. The period since the pandemic started has been labeled the megacrisis era. Interconnected crises, including the pandemic, wars, rising commodity prices, and climate events, all overlapped. The results indicate that industrial metals and banks have performed well since the pandemic began. Food producers, healthcare providers, medical equipment suppliers, tourist-related companies, and semiconductor firms have suffered. This paper considers several steps that could help these sectors to recover. [ABSTRACT FROM AUTHOR]

The government has set an ambitious target of renewable energy development in Malaysia. As a promising renewable energy source, wind energy plays an important role in the Malaysia renewable energy roadmap. Compared to onshore wind energy, offshore wind resources with better quality can be provided in the areas away from the coast, which has greater potential to contribute to electricity generation. Wind and bathymetry conditions are two important factors that determine the feasibility and economics of offshore wind turbines. In this paper, an investigation is conducted on wind and bathymetry conditions around Malaysia. The data source mainly originates from the Global Wind Atlas. The conditions of the coastal areas in different states and federal territories of both Peninsular Malaysia and East Malaysia are analysed, with a specific focus on wind speed, wind energy density, and bathymetry conditions in high-wind-speed regions. The data and survey are verified and compared with the past published literature. This paper aims to investigate the wind and bathymetry conditions around Malaysia, assess the potential of offshore wind energy, discuss the feasibility of offshore wind turbines, and provide references for offshore wind development in Malaysia. [ABSTRACT FROM AUTHOR]

Significant water loss caused by pipeline leaks emphasizes the importance of effective pipeline leak detection and localization techniques to minimize water wastage. All of the state-of-the-art approaches use deep learning (DL) for leak detection and cross-correlation for leak localization. The existing methods' complexity is very high, as they detect and localize the leak using two different architectures. This paper aims to present an independent architecture with a single sensor for detecting and localizing leaks with enhanced performance. The proposed approach combines a novel EMD with an optimal mode selector, an MFCC, and a two-dimensional convolutional neural network (2DCNN). The suggested technique uses acousto-optic sensor data from a real-time water pipeline setup in UTAR, Malaysia. The collected data are noisy, redundant, and a one-dimensional time series. So, the data must be denoised and prepared before being fed to the 2DCNN for detection and localization. The proposed novel EMD with an optimal mode selector denoises the one-dimensional time series data and identifies the desired IMF. The desired IMF is passed to the MFCC and then to 2DCNN to detect and localize the leak. The assessment criteria employed in this study are prediction accuracy, precision, recall, F-score, and R-squared. The existing MFCC helps validate the proposed method's leak detection-only credibility. This paper also implements EMD variants to show the novel EMD's importance with the optimal mode selector algorithm. The reliability of the proposed novel EMD with an optimal mode selector, an MFCC, and a 2DCNN is cross-verified with cross-correlation. The findings demonstrate that the novel EMD with an optimal mode selector, an MFCC, and a 2DCNN surpasses the alternative leak detection-only methods and leak detection and localization methods. The proposed leak detection method gives 99.99% accuracy across all the metrics. The proposed leak detection and localization method's prediction accuracy is 99.54%, precision is 98.92%, recall is 98.86%, F-score is 98.89%, and R-square is 99.09%. [ABSTRACT FROM AUTHOR]

The development of intelligent transport systems, mobile cellular networks, microwave links, and vehicle communications has accelerated with the use of wireless connections as a communication channel in 5G wireless technology. Weather, including rain, fog, snow, sand, and dust, impacts wireless communication channels in various ways. These effects are more pronounced at the high frequencies of millimeter-wave bands. Recently, the 5G network has made it possible to support a variety of applications with fast speeds and high-quality content. To facilitate the use of high-millimeter-wave frequencies, a recent study investigated how sand and dust affect the 5G communication channel. In this paper, we consider the impact of frequent and heavy rainfall on millimeter-wave propagation and cross-polarization of the wave at various points along the propagation path caused by rainfall in urban and highway scenarios in Malaysia. We estimate rainfall attenuation, path loss, and link margin at various millimeter-wave frequencies. From our simulation results, it is evident that rainfall attenuation, path loss, and link margin depend on the operating frequency, path difference, and rainfall rate. In this paper, we estimate and compare the optimal path difference values under urban and highway scenarios both with and without rainfall attenuation. [ABSTRACT FROM AUTHOR]

Malaysia's energy intensity (GWh/GDP) shows an increasing trend since the 1990s, leading to the government's efforts to promote energy efficiency via policies such as the National Energy Efficiency Action Plan (NEEAP), which includes the Energy Performance Contracting (EPC) initiative. This paper reviews recent publications in industrial Combined Heat and Power (CHP) with a focus on international case studies relevant to Malaysian industries that use industrial steam and highlights trends within the research area. It also provides the basis for more case studies to be performed in the Malaysian industry to improve energy efficiency while also supporting further academic research in the area. Additionally, the paper documents the importance of data collection and analysis as well as demand forecasting, not only for a better understanding of industrial energy systems but also to increase profitability since system loads may vary throughout a typical year. A multi-criteria and comprehensive approach is recommended in future case studies to ensure energy efficiency, economic returns and environmental impact are considered to ensure long-term sustainability. A summary of barriers to CHP implementation in the industry is also included to provide a broad understanding of industrial CHP. [ABSTRACT FROM AUTHOR]

Palm oil is a very important commodity which will be required well into the future. However, the consequences of growing oil palm (OP) are often detrimental to the environment and contribute to climate change. On the other hand, climate change stress will decrease the production of palm oil by causing mortality and ill health of OP, as well as reducing yields. Genetically modified OP (mOP) may be produced in the future to resist climate change stress, although it will take a long time to develop and introduce, if they are successfully produced at all. It is crucial to understand the benefits mOP may bring for resisting climate change and increasing the sustainability of the palm oil industry. This paper employs modeling of suitable climate for OP using the CLIMEX program in (a) Indonesia and Malaysia, which are the first and second largest growers of OP respectively, and (b) Thailand and Papua New Guinea, which are much smaller growers. It is useful to compare these countries in terms of future palm oil production and what benefits planting mOP may bring. Uniquely, narrative models are used in the current paper to determine how climate change will affect yields of conventional OP and mOP. The effect of climate change on the mortality of mOP is also determined for the first time. The gains from using mOP were moderate, but substantial, if compared to the current production of other continents or countries. This was especially the case for Indonesia and Malaysia. The development of mOP requires a realistic appreciation of what benefits may accrue. [ABSTRACT FROM AUTHOR]

This paper presents a thorough review and analysis of solar photovoltaic (PV) home systems in Malaysia, offering a comprehensive exploration of their implementation, challenges, benefits, and future potential. As a nation striving to embrace sustainable and renewable energy solutions, Malaysia's adoption of solar PV systems at the residential level is of paramount importance. The study delves into the current state of solar PV deployment, government initiatives, and policy frameworks that influence adoption trends. It examines the economic, environmental, and societal advantages of solar PV home systems, outlining their contribution to reducing electricity costs, carbon emissions, and energy dependence. Addressing barriers to wider acceptance, the paper scrutinizes challenges encompassing cost, awareness, intermittency, and regulatory constraints. Furthermore, the study evaluates the socio-economic implications of solar PV home systems, including potential job creation and energy independence. Technological advancements, such as enhanced efficiency and smart grid integration, are also explored for their role in surmounting obstacles. Drawing insights from practical case studies, the paper underscores successful installations and the lessons they offer. In examining policy and regulatory frameworks, it analyzes existing incentives while suggesting improvements to accelerate adoption. Finally, the paper offers a visionary perspective on the future trajectory of solar PV home systems in Malaysia, envisioning increased affordability, advanced energy storage solutions, and seamless integration with emerging technologies. This holistic analysis contributes valuable insights to propel Malaysia's sustainable energy transition and inform strategic decision making for stakeholders across sectors. [ABSTRACT FROM AUTHOR]

The purpose of this concept paper is to suggest a theoretical framework for understanding the post-privatisation performance of statutory bodies, subject to government shareholding. We identify a suitable model, from the analytical economics literature. We argue that this model is a manifestation of agency theory. Our proposed framework for using this theory is replete with examples from Malaysia. We conclude that in Malaysia, the principal determinant of whether government subsidisation enhances or erodes shareholder wealth is the level of government shareholding. We also predict that in Malaysia, the relation between shareholder wealth and government shareholding follows an "inverted U" shape. However, the turning is likely to vary, cross-sectionally and temporally. We believe that the framework presented within this paper can be used to understand empirical results reported by other Malaysian studies into the shareholder wealth effects arising from economic policies featuring close co-operation between the public and private sectors. [ABSTRACT FROM AUTHOR]

Steel slag is one of the most common waste products from the steelmaking industry. Conventional methods of slag disposal can cause negative impacts on humans and the environment. In this paper, the process of steel and steel slag production, physical and chemical properties, and potential options of slag recycling were reviewed. Since steel is mainly produced through an electric arc furnace (EAF) in Malaysia, most of the recycling options reviewed in this paper focused on EAF slag and the strengths and weaknesses of each recycle option were outlined. Based on the reports from previous studies, it was found that only a portion of EAF slag is recycled into more straightforward, but lower added value applications such as aggregates for the construction industry and filter/absorber for wastewater treatments. On the other hand, higher added value recycling options for EAF slag that are more complicated such as incorporated as raw material for Portland cement and ceramic building materials remain at the laboratory testing stage. The main hurdle preventing EAF slag from being incorporated as a raw material for higher added value industrial applications is its inconsistent chemical composition. The chemical composition of EAF slag can vary based on the scrap metal used for steel production. For this, mineral separation techniques can be introduced to classify the EAF slag base on its physical and chemical compositions. We concluded that future research on recycling EAF slag should focus on separation techniques that diversify the recycling options for EAF slag, thereby increasing the waste product's recycling rate. [ABSTRACT FROM AUTHOR]

Rising solid waste production has caused high levels of environmental pollution. Population growth, economic patterns, and lifestyle patterns are major factors that have led to the alarming rate of solid waste production. Generally, solid wastes such as paper, wood, and plastic are disposed into landfills due to its low operation and maintenance costs. However, leachate discharged from landfills could be a problem in surfaces and groundwater if not adequately treated. This study investigated the patterns of the water quality index (WQI) and polycyclic aromatic hydrocarbons (PAH) along Johan River in Perak, Malaysia, which received treated leachate from a nearby landfill. An artificial neural network (ANN) was also applied to predict WQI and PAH concentration of the river. Seven sampling stations were chosen along the river. The stations represented the upstream of leachate discharge, point of leachate discharge, and five locations downstream of the landfill. Sampling was conducted for one year starting July 2018. Physicochemical parameters, namely pH, biological oxygen demand, chemical oxygen demand, ammoniacal nitrogen, total suspended solids, and dissolved oxygen, were used to compute the water quality index (WQI). PAH concentrations were determined by liquid–liquid extraction of water samples followed by an analysis using gas chromatography. Results showed that WQI of Johan River was under Class III where intensive treatment was required to make it suitable for drinking purposes. The highest recorded PAH concentrations were fluoranthene (333.4 ppb) in the dry season and benzo(a) pyrene (93.5 ppb) in the wet season. A correlation coefficient (Rp) for a model prediction based on WQI-ANN and TEC-ANN (toxicity equivalent concentration) in the wet and dry seasons was 0.9915, 0.9431, 0.9999, and 0.9999, respectively. ANN results showed good model performance with Rp ≈ 0.9. This study suggested that ANN is a useful tool for water quality studies. [ABSTRACT FROM AUTHOR]

This paper attempts to ascertain the thermal and acoustic impacts of introducing a vegetative roof layer on insulated and uninsulated metal roofs for tropical climates, through field measurements in Skudai, Johor, Malaysia, that were conducted for both dry and wet days. Four small-scale roof modules were tested, namely an uninsulated metal roof (uiMDR), an insulated metal roof (iMDR), and two identical corresponding modules with an additional vegetative component (uiGR and iGR, respectively). Outdoor ambient temperature (Tamb) was the most influential correlated variable affecting the roof outer surface temperature (RTOS) in 50% of the assessed scenarios. On the selected dry day, the inter-quartile ranges (IQR) of iGR, iMDR, uiGR, and uiMDR were 6.21 °C, 8.32 °C, 6.69 °C, and 1.66 °C, respectively; the IQRs were 1.6 °C, 4.11 °C, 2.59 °C, and 1.78 °C, respectively, on the selected wet day. Based on design U-value calculations, iGR was better than iMDR and uiMDR for both dry and wet days. The U-value of uiGR was also better than iMDR under dry-day conditions. The Wilcoxon signed-rank test also indicated a statistically significant difference in the roof inner surface temperature (RTIS) measurements (p-value = 0.00) during Malaysian daylight hours, between 8.00 a.m. and 6.00 p.m., regardless of the weather. In terms of sound level reduction under dry-day conditions, the Kruskal–Wallis and Wilcoxon signed-rank tests showed statistically significant differences in sound level reductions, with iGR and uiGR performing better than iMDR and uiMDR (p-values = 0.00). The sound level reductions for iGR, iMDR, and uiGR were 51%, 32%, and 31%, respectively, while uiMDR experienced sound level amplifications by 6%, possibly due to the acoustic resonance effect. This proof of concept may encourage a broader application of extensive GRs in Malaysia using metal roofs, beyond the conventional RC base construction method. [ABSTRACT FROM AUTHOR]

Pipe jacking is a trenchless technology used to install buried pipelines, such as sewer lines in wastewater management systems. Existing mechanistic approaches based on geomaterial strength parameters (i.e., friction angle and apparent cohesion) can provide an estimation of the potential jacking forces during construction. However, extracting intact rock cores for strength characterisation is challenging when dealing with highly weathered 'soft rocks' which exhibit RQD values of zero. Such was the case for a pipe jacking drive traversing the highly weathered lithology underlying Kuching City, Malaysia. Furthermore, mechanistic approaches face limitations during construction when jacking forces are dependent on operation parameters, such as jacking speed and lubrication. To address these knowledge gaps, the primary objectives of this study are the development of rock strength parameters based on in situ pressuremeter testing for the purpose of estimating jacking forces. Furthermore, this study investigates the influence of various pipe jacking operation parameters, with a particular focus on their impact on jacking forces in weathered 'soft rocks'. To achieve this, a novel deep learning model with an attention mechanism is introduced. The proposed methods of rock strength parameters derived from pressuremeter testing and the utilisation of deep learning will help to provide insights into the key factors affecting the development of jacking forces. This paper successfully shows the use of in situ pressuremeter testing in developing Mohr–Coulomb (MC) parameters directly from the site. In addition, the developed deep learning model with an attention mechanism successfully highlights the significance of pipe jacking operation parameters with an accuracy of 88% in predicting the jacking forces. [ABSTRACT FROM AUTHOR]

This paper presents a detailed study of the energy savings that can be achieved through residential appliances by implementing conservation voltage reduction (CVR). The computed energy savings are derived from the ZIP coefficients of a load model (static) under varying voltage conditions that represent the power consumed by each appliance tested. Multiple studies have shown energy savings at the substation level but not at the level of a specific residence and appliance; hence, the latter is the focus of this analysis. The appliances are determined based on the type of heating and cooling loads, and the daily duration of use for each appliance, which contributes to the total monthly consumption that is billed for a household are included in this study. Energy savings in Malaysia has been a focus of many current studies, and this study is the first attempt to achieve energy savings through the implementation of CVR. No published work has compared individual appliances that truly benefits from CVR, and this is addressed in this study. The main contribution of this study is that it provides very detailed and measured data that are used to analyze and generate energy savings for very specific residential appliances intended to meet every 1% voltage drop. The load model is developed for the common household appliances in Malaysia, and then a voltage reduction study is applied to the appliances as well as the Malaysian distribution networks. Here, we also provide insight for performing voltage reduction at an electric vehicle (EV) charging station in Malaysia. The results of this study should serve as a foundation for all practicing utilities engineers to address the issue of CVR in Malaysia. The CVR factors for residential, commercial, and industrial networks in Malaysia are also published in this paper. [ABSTRACT FROM AUTHOR]

The occurrence of fires in tropical peatlands poses significant threats to their ecosystems. An Internet of Things (IoT) system was developed to measure and collect fire risk factors in the Raja Musa Forest Reserve (RMFR) in Selangor, Malaysia, to address this issue. In this paper, neural networks with different layers were employed to predict peatland forests' Fire Weather Index (FWI). The neural network models used two sets of input parameters, consisting of four and nine fire factors. The predicted FWI values were compared with actual values obtained from the Malaysian meteorological department. The findings revealed that the five-layer neural network outperformed others in both the four-input and nine-input models. Specifically, the nine-input neural network achieved a mean square error (MSE) of 1.116 and a correlation of 0.890, surpassing the performance of the four-input neural network with the MSE of 1.537 and the correlation of 0.852. These results hold significant research and practical implications for precise peatland fire prevention, control, and the formulation of preventive measures. [ABSTRACT FROM AUTHOR]

Peatland refers to the peat soil and wetland biological environment growing on the surface. However, unexpected fires in peatlands frequently have brought severe greenhouse gas emissions and transboundary haze to Southeast Asia. To alleviate this issue, this paper first establishes an Internet of Things (IoT) system for peatland monitoring and management in the Raja Musa Forest Reserve (RMFR) in Selangor, Malaysia, and proposes a more efficient and low-complexity model for calculating the Duff Moisture Code (DMC) in peatland forests using groundwater level (GWL) and relative humidity. The feasibility of the IoT system is verified by comparing its data with those published by Malaysian Meteorological Department (METMalaysia). The proposed Linear_DMC Model and Linear_Mixed_DMC Model are compared with the Canadian Fire Weather Index (FWI) model, and their performance is evaluated using IoT measurement data and actual values published by METMalaysia. The results show that the correlation between the measured data of the IoT system and the data from METMalaysia within the same duration is larger than 0.84, with a mean square error (MSE) of 2.56, and a correlation of 0.91 can be achieved between calculated DMC using the proposed model and actual values. This finding is of great significance for predicting peatland forest fires in the field and providing the basis for fire prevention and decision making to improve disaster prevention and reduction. [ABSTRACT FROM AUTHOR]

Social media has evolved into a platform for the dissemination of information, including fake news. There is a lot of false information about the current situation of the Coronavirus Disease 2019 (COVID-19) pandemic, such as false information regarding vaccination. In this paper, we focus on sentiment analysis for Malaysian COVID-19-related news on social media such as Twitter. Tweets in Malaysia are often a combination of Malay, English, and Chinese with plenty of short forms, symbols, emojis, and emoticons within the maximum length of a tweet. The contributions of this paper are twofold. Firstly, we built a multilingual COVID-19 Twitter dataset, comprising tweets written from 1 September 2021 to 12 December 2021. In particular, we collected 108,246 tweets, with over  67 %  in Malay language,  27 %  in English,  2 %  in Chinese, and  4 %  in other languages. We then manually annotated and assigned the sentiment of 11,568 tweets into three-class sentiments (positive, negative, and neutral) to develop a Malay-language sentiment analysis tool. For this purpose, we applied a data compression method using Byte-Pair Encoding (BPE) on the texts and used two deep learning approaches, i.e., the Multilingual Bidirectional Encoder Representation for Transformer (M-BERT) and convolutional neural network (CNN). BPE tokenization is used to encode rare and unknown words into smaller meaningful subwords. With the CNN, we converted the labeled tweets into image files. Our experiments explored different BPE vocabulary sizes with our BPE-Text-to-Image-CNN and BPE-M-BERT models. The results show that the optimal vocabulary size for BPE is 12,000; any values beyond that would not contribute much to the F1-score. Overall, our results show that BPE-M-BERT slightly outperforms the CNN model, thereby showing that the pre-trained M-BERT network has the advantage for our multilingual dataset. [ABSTRACT FROM AUTHOR]

BIM (Building Information Modelling) is used to create and manage data during design, construction, and operation. It helps to effectively manage resources and optimize processes in the construction industry. Geotechnical engineering is one of the complex disciplines that may require BIM integration. Various data types must be provided in a timely manner and require real-time feedback, fast processing, and construction guidance. The first problem presented in the paper is the use of the traditional 2D-based method used by engineers for a particular task. It seems to be impractical when some adjustments are included. Another issue is the lack of communication between the workers. It poses the problem of information exchange and misunderstanding during the interpretation of technical data. This paper aims to find different integration techniques and steps for integrating geotechnical data into the BIM process. Methods used to examine the topic are qualitative research, literature review, and case studies. These methods were useful for studying the problems and introducing the soil information into the BIM application. Firstly, a case study with I-BIM was considered, and the BIM–FEM–BIM interaction was applied to introduce geotechnical information with Plaxis 3D. The results have shown that further development of BIM in infrastructure is needed. Another case study explored the present state of the geotechnical design in BIM and potential solutions. The new frameworks were recreated: many boreholes were imported to the BIM, and a 3D geometric model of the entire hill was created for the hill fortification structure with soil clogging. The last two studies in Malaysia modeled a 3D subsurface and used two geotechnical formats, AGS and CVS. The first includes more information than the second; however, the second can be used for a more generalized model. Overall, BIM–FEM interaction can be used as a geometric model for data transfer. However, the open data format of the Industry Foundation Class (IFC) or geotechnical data format of the AGS and CVS were suggested to be used for greater flexibility. It was also found that excessive information makes the model loaded and complex. Therefore, it was recommended that big data be summarized properly with minimal loss of necessary data. Further research is needed to understand data transmission schemes of geotechnical information better. Moreover, it is recommended to put all the strategies directly into practice to create a geotechnical design. [ABSTRACT FROM AUTHOR]

Conventional bitumen pavement is no longer suitable for handling increasing loads and weather variations, which cause road deterioration, Thus, the modification of bitumen has been suggested to counter this issue. This study provides a detailed assessment of various additives for modifying natural rubber-modified bitumen used in road construction. This work will focus on the use of additives with cup lump natural rubber (CLNR), which has recently started to gain attention among researchers, especially in rubber-producing countries such as Malaysia, Thailand and Indonesia. Furthermore, this paper aims to briefly review how the addition of additives or modifiers helps elevate the performance of bitumen by highlighting the significant properties of modified bitumen after the addition of modifiers. Moreover, the amount and method of application of each additive are discussed further to obtain the optimum value for future implementation. On the basis of past studies, this paper will review the utilisation of several types of additives, including polyphosphoric acid, Evotherm, mangosteen powder, trimethyl-quinoline and sulphur, and the application of xylene and toluene to ensure the homogeneity of the rubberised bitumen. Numerous studies were conducted to verify the performance of various types and compositions of additives, particularly in terms of physical and rheological properties. In general, additives enhance the properties of conventional bitumen. Future research should investigate CLNR because studies on its utilisation are limited. [ABSTRACT FROM AUTHOR]

This paper studies the history of the Singapore Girls' Buddhist Institute, the first and only modern Buddhist education institution for women in Singapore and Malaysia. This paper aims to explore a dynamic transregional Buddhist network constructed by nuns, vegetarian nuns, and laywomen, with a particular emphasis on the prominent female figures and religious women communities involved. Through an analysis of the movements and religious practices of the Buddhist women community, the author demonstrates the contributions of Buddhist women to the transmission of religious knowledge and modern experiences. It is this paper's intention that the micro-history of the case could contribute to restaging the women-centered Buddhist community in the narrative of "South China Sea Buddhism". [ABSTRACT FROM AUTHOR]

Malaysia has great geo-economic advantages, especially in becoming a major logistics and investment hub. However, as operational risk events create uncertainties, logistics companies suffer from supply and demand issues which affect their bottom lines, customer satisfaction and reputations. This is a pioneer paper to propose the optimization of the efficiency of listed logistics companies in Malaysia with operational risk factor using a data envelopment analysis (DEA) model. The basic indicator approach (BIA) is used as an output indicator for the operational risk capital requirement factor in the proposed model. This paper has practical and managerial implications with the identification of potential improvements for the inefficient listed logistics companies based on the optimal solution of the DEA model. This proposed model can be applied in emerging fields such as finance and project-based construction companies, where operational risk is a high concern. [ABSTRACT FROM AUTHOR]

Energy is one of the essential inputs for modernization and social development. Energy demand is increasing, and the primary energy source is fossil fuels, which negatively impact the environment. Energy saving and renewables are the potential solutions which could minimize environmental impact. This paper investigates the energy-saving and solar photovoltaic energy potential of an educational institution, Politeknik Sultan Azlan Shah (PSAS), Malaysia. The feasibility analysis was conducted by assuming that PSAS joined the Net Energy Metering (NEM 3.0) program, where PSAS, as a NEM consumer, has a tripartite supply agreement with renewable energy (SARE) with a distribution licensee known as Tenaga National Berhad (TNB). This paper focuses on zero capital expenditure (CAPEX) saving through a 20-year contract. This paper proposes a rooftop solar photovoltaic diagram using a NEM meter installed in the ring distribution system at PSAS. The estimated savings to be obtained by PSAS in the 20 years that the contract is in force are calculated based on the assumption that the installed solar system has a capacity of 688 kW. The maximum value of power generated by the system for a year is 990,720 kWh. The feasibility analysis found that the cumulative net savings estimate for PSAS based on the overall calculation for 21 years of solar use is RM 3,534,250. Meanwhile, the cumulative assessment of carbon emission reduction obtained in the same period is 14,559,760 kg CO2 or 14,559.76 tons of CO2, which would save 363,994 mature trees from being cut down. [ABSTRACT FROM AUTHOR]

This paper discussed the prevailing issues currently faced by Islamic banks on the offering of Letter of Credit (LC), originally brought forward by the International Chamber of Commerce, using Shariah contracts and puts forth recommendations on practical solutions to solve the issues. The study adopted a qualitative method where the information on the issues of Islamic LCs was gathered throughout interviews with different bankers closely involved in LC issuance from 12 Islamic banks in Malaysia. The results indicate that there are three vital issues related to LCs offered by Islamic banks which lead to Shariah non-compliance issues. The issues revolve around the conversion of LC Wakalah (agency) to LC Murabahah (cost-plus), the existence of a sale contract between the customer and exporter and lastly the title of goods stated in the bill of lading. The findings recommend several solutions in relation to LCs within the underlying Shariah contracts to ensure that their operation complies with the Shariah requirements and Malaysian laws, standards and regulations. This paper highlights the issues of Islamic LC yet to be discussed thoroughly based on the views of a panel of experts and Islamic bankers. [ABSTRACT FROM AUTHOR]

The land surface of Malaysia mostly constitutes forest cover. For decades, forest fires have been one of the nation's most concerning environmental issues. With the advent of machine learning, many studies have been conducted to resolve forest fire issues. However, the findings and results have been very case-specific. Most experiments have focused on particular regions with independent methodology settings, which has hindered the ability of others to reproduce works. Another major challenge is lack of benchmark datasets in this domain, which has made benchmark comparisons almost impossible to conduct. To our best knowledge, no comprehensive review and analysis have been performed to streamline the research direction for forest fires in Malaysia. Hence, this paper was aimed to review all works aimed to combat forest fire issues in Malaysia from 1989 to 2021. With the proliferation of publicly accessible satellite data in recent years, a new direction of utilising big data platforms has been postulated. The merit of this approach is that the methodology and experiments can be reproduced. Thus, it is strongly believed that the findings and analysis shown in this paper will be useful as a baseline to propagate research in this domain. [ABSTRACT FROM AUTHOR]

This paper examines the phenomena of the local government's inadequate reaction to the national programme of geographical infrastructure for the effective sharing of spatial data in Malaysia. We investigate the determinants of sharing data for Malaysia's spatial data infrastructure (SDI) and aim to define the model for spatial data-sharing of Malaysia's local SDI. The main contribution of this paper is an explanation of the novel methodology to study factors that affect spatial data sharing including a new qualitative analysis method through an interview with people concerned in this field, including engineers, technicians and academics, which was undertaken in Kuala Lumpur, and a new methodology to identify the necessary approach that affects spatial data sharing. An interview and a questionnaire were used in this study as part of a sequential exploratory approach. Among land use, Plan Malaysia, and Telekom Malaysia Berhad TMOne, 15 participants were interviewed in-depth to obtain their responses, and 83 individuals took part in the survey questionnaires. Interview data were measured by content analysis, while questionnaire data were measured by partial least squares analysis. In the structural model analysis, Smart PLS was used to choose the fit items based on validity and reliability measurements. According to the hypothesis measurement, technology and organisation both significantly affect the practice of spatial data sharing, but human resources and spatial data do not significantly affect it. All R-Squared values represent a value above 56 per cent for the human resource aspect, technology aspect and spatial data aspect. However, the R-Square value for spatial data sharing is 47%. Spatial data and human resources have a less substantial impact on spatial data sharing; hence, this study proposes a national awareness programme and mentoring to improve local SDI support for spatial data sharing. [ABSTRACT FROM AUTHOR]

In recent years, kenaf has gained significant global attention as a more cost-effective, adaptable, and manageable alternative to other fibre crops. India and China, with nearly 70% of the global kenaf production, have emerged as the leading producers of kenaf plants. While kenaf was traditionally valued for its paper production, it has evolved into a multipurpose crop with diverse industrial applications over the past two decades. Conventional soil-based cultivation methods for kenaf require up to six months for plant maturity. However, in vitro propagation techniques offer a promising alternative that enables faster growth and reduced labour costs. In vitro propagation can be achieved using solid and liquid media, with limited research available on the pure liquid culture method for kenaf. This review aims to introduce and compare the production of kenaf using solid and liquid media, with a specific focus on the emerging country of Malaysia, which seeks to harness the potential of kenaf cultivation for the 15th Sustainable Development Goal, "life on land", and its contribution to the economy. [ABSTRACT FROM AUTHOR]

Malaysian healthcare institutions still use ineffective paper-based vaccination systems to manage childhood immunization schedules. This may lead to missed appointments, incomplete vaccinations, and outbreaks of preventable diseases among infants. To address this issue, a text messaging vaccination reminder and recall system named Virtual Health Connect (VHC) was studied. VHC simplifies and accelerates immunization administration for nurses, which may result in improving the completion and timeliness of immunizations among infants. Considering the limited research on the acceptance of these systems in the healthcare sector, we examined the factors influencing nurses' attitudes and intentions to use VHC using the extended technology acceptance model (TAM). The novelty of the conceptual model is the incorporation of new predictors of attitude, namely, perceived compatibility and perceived privacy and security issues. We conducted a survey among 121 nurses in Malaysian government hospitals and clinics to test the model. We analyzed the collected data using partial least squares structural equation modeling (PLS-SEM) to examine the significant factors influencing nurses' attitudes and intentions to use VHC. Moreover, we applied an artificial neural network (ANN) to determine the most significant factors of acceptance with higher accuracy. Therefore, we could offer more accurate insights to decision-makers in the healthcare sector for the advancement of health services. Our results highlighted that the compatibility of VHC with the current work setting of nurses developed their positive perspectives on the system. Moreover, the nurses felt optimistic about the system when they considered it useful and easy to use in the workplace. Finally, their attitude toward using VHC played a pivotal role in increasing their intention to use it. Based on the ANN models, we also found that perceived compatibility was the most significant factor influencing nurses' attitudes towards using VHC, followed by perceived ease of use and perceived usefulness. [ABSTRACT FROM AUTHOR]

To improve the performance of the construction industry, innovative methods were introduced to make them better. Industrialised building systems (IBS) and prefabrication construction are the popular methods used and studied. However, these methods are still unable to meet the demands of the stakeholders. Design for manufacturing and assembly (DfMA) is a design principle that is seen as capable of improving the situation. The uptake of DfMA in the construction industry needs to be analysed to obtain a better picture of the existing condition of the method and its manner of implementation it going forward, but there are still too few studies performed on this topic. This paper gathers relevant articles from the previous studies on DfMA. With the available data, the main benefits, hindrance factors, and enabling factors for DfMA uptake in the construction industry were identified in this study. The authors also identified the research trend among the research themes and the benefits of building information modelling (BIM) integration with DfMA. By synthesising the information from previous studies, a conceptual framework was developed. Knowledge gaps and future potential research topics are also discussed in this paper, forming a simple research framework for future effort guidance. With a suitable strategy and guidelines, the application of DfMA could improve the performance of the construction industry in Malaysia and other places with similar construction environments and approaches. [ABSTRACT FROM AUTHOR]

Fifth-generation (5G) networks have been deployed alongside fourth-generation networks in high-traffic areas. The most recent 5G mobile communication access technology includes mmWave and sub-6 GHz C-bands. However, 5G signals possibly interfere with existing radio systems because they are using adjacent and co-channel frequencies. Therefore, the minimisation of the interference of 5G with other signals already deployed for other services, such as fixed-satellite service Earth stations (FSS-Ess), is urgently needed. The novelty of this paper is that it addresses issues using measurements from 5G base stations (5G-BS) and FSS-ES, simulation analysis, and prediction modelling based on artificial neural network learning models (ANN-LMs). The ANN-LMs models are used to classify interference events into two classes, namely, adjacent and co-channel interference. In particular, ANN-LMs incorporating the radial basis function neural network (RBFNN) and general regression neural network (GRNN) are implemented. Numerical results considering real measurements carried out in Malaysia show that RBFNN evidences better accuracy with respect to its GRNN counterpart. The outcomes of this work can be exploited in the future as a baseline for coexistence and/or mitigation techniques. [ABSTRACT FROM AUTHOR]

Sulfur hexafluoride (SF6) gas is one of the high global warming potential (GWP) gases regulated under the Kyoto Protocol. In Malaysia's Biennial Update Report 3, the Revised 1996 Intergovernmental Panel on Climate Change Guidelines were followed to estimate the SF6 emissions in the country, including the time series from 1990 to 2016. The majority of SF6 emissions originate from the use of this gas in electrical equipment, where it is predominantly used in transmission switch gears, which have increased rapidly because of increasing electricity demand. SF6 gas plays a significant role in greenhouse gas emissions in Malaysia because this gas has a higher GWP than carbon dioxide. Hence, this SF6 gas needs to be estimated using newer guidelines such as the 2006 IPCC Guidelines. Detailed activity data in the new methodology require stakeholders' engagement with utility providers and government agencies. This paper describes the GHG inventory improvement plan, focusing on SF6 emissions for Industrial Processes and Product Use for Malaysia through this transition of methodology. [ABSTRACT FROM AUTHOR]

Home education is a phenomenon that has been increasing globally over the past decade, particularly for families of children with special educational needs or disabilities. The impact of the COVID-19 pandemic has exacerbated this phenomenon with many families continuing to home educate even after their children can officially return to school. This paper reports on a small-scale design-based research project that explored the needs of families who are home educating children with autistic spectrum disorder (ASD). Working in partnership with educational settings, practitioners, and families during the second year of the pandemic, academic researchers in Malaysia and England designed, implemented and evaluated a home learning pack for children with ASD aged 6–12 years old. The findings emphasised the role of economic, social and cultural capital for the families involved and how this impacted their ability to work and educate their children successfully. This raises crucial questions in relation to the place of home education within the wider international inclusive education debate and matters of social equality whilst also highlighting key questions for future research in this field on how policy and provision might develop to meet a growing diversity of need. [ABSTRACT FROM AUTHOR]

This paper discusses the outcomes of an initiative to empower young people as active researchers. It highlights participants' understandings of their role as researchers in terms of the meaning of research, the research processes, and the participants' competences, knowledge, and skills. It describes a process that a group of 15 child councillors aged between 15 and 17 years went through that was aimed at equipping them with the knowledge and skills to conduct their research. Based on the data presented, it was clear that from the participants' point of view, the research process was challenging and time-consuming since it entailed several steps that needed to be carried out with careful attention to detail. Despite this, the participants were confident in their ability to undertake independent research, albeit with guidance from adults. Their research abilities and knowledge of child rights improved because of their having conducted research. The participants also noted that their learning was more meaningful when they were engaged in the subject topic, supporting the notion that learning by doing is vital. Due to its emphasis on acquiring children's meaningful participation and illustrating the complex reality of being a part of research, this study has made important contributions to the small body of literature on child participation in Malaysia. [ABSTRACT FROM AUTHOR]

Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controlling the traffic flow and facilitate road users, particularly in densely populated urban cities. Since road capacity in urban cities changes throughout the day, an optimal traffic light signal duration might be different. Hence, in this paper, the effect of vehicle composition and traffic light phases on traffic flow during peak and off-peak hours in Georgetown, Penang, one of the highly populated cities in Malaysia, is investigated. Through Agent-Based Modelling (ABM), this complex system is simulated by integrating the driver's behaviour into the model using the GIS and Agent-Based Modelling Architecture (GAMA) simulation platform. The result of predicted traffic flow varies significantly depending on the vehicle composition while the duration of the traffic signal timing has little impact on traffic flow during peak hours. However, during off-peak hour, it is suggested that 20 s duration of green light provides the highest flow compared to 30 s and 40 s duration of green light. This concludes that the planning for traffic light phasing should consider multiple factors since the vehicle composition and traffic light timing for an effective traffic flow varies according to the volume of road users. [ABSTRACT FROM AUTHOR]

Takaful operators are part of the Islamic financial institutions that are expected to achieve the commercial and social objectives by their stakeholders particularly the takaful participants (policyholders). First, this study aims to postulate a new framework to measure cost effectiveness by including the social and economic benefits of drone-assisted technology in the context of maq¯as. id Shariah. Second, the study intends to investigate how the takaful industry can benefit from the drone-assisted technology, particularly in terms of cost reduction. This paper presents an early finding that forms part of a bigger research project which is focusing on the use of drone for disaster victim identification (DVI). This study employs thematic analysis of qualitative research method by engaging key informants who are Shariah expert, drone practitioner and accounting expert. In the context of emerging economies like Malaysia, the adoption of drone is sporadic when some industries such as military and agriculture are quite experienced with it; but for the takaful sector is almost none. This study provides preliminary findings that suggests there is potential of cost effectiveness for drone usage from the perspectives of SCBA in the maq¯as. id Shariah framework. The main contributions from this paper are: (1) the new SCBA framework derived from the maq¯as. id Shariah perspective and, (2) the application of this framework in examining the cost effectiveness on the use of drones by the takaful operators especially during disaster. [ABSTRACT FROM AUTHOR]

Critical thinking and clinical decision-making are two essential components of nursing services. The practice of nursing requires both components at every level of nurses' daily tasks. This paper describes the protocol for an ongoing project, which aims to examine the prevalence of critical thinking and clinical decision-making among registered nurses and determine the factors that influence the skills at individual and group levels using a multilevel modeling approach. Survey data will be collected from approximately nine states, with nine general hospitals, nine district hospitals, one private hospital, and one educational hospital in Malaysia included. We aim to recruit 800 registered nurses working shifts in hospital settings. We will use questionnaires to measure the perceived nurses' knowledge, critical thinking skills, and clinical decision-making skills. The study will have three levels as the nurses are nested within the unit and further nested within the hospitals. This study will give an insight into the nursing profession today where critical thinking and clinical decision-making skills can play a significant role in patient safety and the quality of care in nursing practice. [ABSTRACT FROM AUTHOR]

In recent decades, significant changes have occurred in the consumer lifestyle and energy consumption structure. In order to foster a more holistic understanding of how residential consumers use energy in their everyday life and how it affects energy efficiency, individual data about energy-related behaviour in six primary areas, namely, housing, mobility, diet, consumption, leisure activities, and information, were studied. Specifically, the objective of this study is to investigate energy efficiency behaviour based on residential consumers' lifestyles. An exploratory pilot study with a total of 50 respondents was carried out in month of July. Data were collected from residential consumers from six states in Peninsular Malaysia and were analysed using the Partial Least Square Structural Equation Modelling approach. The result showed that consumption, housing, and information are the dominant direct contributors to energy efficiency. By understanding these lifestyles, researchers and policymakers can better understand consumer energy consumption behaviour and design targeted interventions to encourage energy efficiency and conservation. The paper highlights the need for further research on consumer lifestyles and their contribution to energy efficiency. It also provides findings from this study that was used to refine the research tools for future research. [ABSTRACT FROM AUTHOR]

Predicting reservoir water levels helps manage droughts and floods. Predicting reservoir water level is complex because it depends on factors such as climate parameters and human intervention. Therefore, predicting water level needs robust models. Our study introduces a new model for predicting reservoir water levels. An extreme learning machine, the multi-kernel least square support vector machine model (MKLSSVM), is developed to predict the water level of a reservoir in Malaysia. The study also introduces a novel optimization algorithm for selecting inputs. While the LSSVM model may not capture nonlinear components of the time series data, the extreme learning machine (ELM) model—MKLSSVM model can capture nonlinear and linear components of the time series data. A coati optimization algorithm is introduced to select input scenarios. The MKLSSVM model takes advantage of multiple kernel functions. The extreme learning machine model—multi-kernel least square support vector machine model also takes the benefit of both the ELM model and MKLSSVM model models to predict water levels. This paper's novelty includes introducing a new method for selecting inputs and developing a new model for predicting water levels. For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. The testing means absolute of the same models was 0.710, 0.742, 0.832, 0.871, 0.912, and 0.919, respectively. The Nash–Sutcliff efficiency (NSE) testing of the same models was 0.97, 0.94, 0.90, 0.87, 0.83, and 0.18, respectively. The ELM-MKLSSVM model is a robust tool for predicting reservoir water levels. [ABSTRACT FROM AUTHOR]

The aim of this paper is to examine the characteristics and conduct of boards in non-financial Malaysian firms, with a particular emphasis on the companies' financial leverage, using panel data spanning from 2012 to 2018. Overall, the study reveals that the relationship between board attributes and a firm's financial leverage is significant, but mixed. Notably, we find that extremely small or large boards are ineffective in maintaining the optimal financial leverage level that benefits all stakeholders. Our study concludes that board independence is negatively correlated with financial leverage, whereas the tenure of board members is negatively associated with financial leverage. Additionally, board diversity exhibits a statistically significant and positive correlation with financial leverage. Currently, the Malaysian corporate governance code advocates announcing regulations to regulate corporate structures. [ABSTRACT FROM AUTHOR]

Blockchain technology is being looked at to solve numerous real-world problems that demand transparency by meeting sustainable goals. Do we ponder whether this technology is a boon or a bane for the environment? This paper analyses blockchain's dominant consensus method, Proof-of-Work (PoW), which consumes more energy than Malaysia and Sweden and further deteriorates the environment through carbon emissions. This study is the first systematic evaluation of PoW consensus-based blockchain applications' environmental consequences. We found 11 significant Theories, 6 Contexts, and 26 Methodologies (TCM) in 60 reviewed articles. We propose an Antecedents, Drivers, and Outcomes (ADO) model, which depicts that marginal profits drive high energy consumption and carbon emissions, with non-renewable energy proportionally responsible for carbon emissions. The article distinctively uses an integrated TCM-ADO framework for literature synthesis and the PESTLE framework for reporting future research areas. This is the first study to use the following four frameworks: PRISMA; TCM; ADO; and PESTLE for systematic literature review. Profit is identified as one of the most significant drivers of energy consumption and further carbon emissions. The article proposes 65 future research areas and makes theoretical contributions to the literature that may interest academicians, practitioners, and social stakeholders. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to investigate the impact of allocating shares to the indigenous (Bumiputera) investors on the oversubscription ratio of IPO. This factor is unique to Malaysian IPOs and would enable us to reflect the signaling theory. Data on 348 IPO firms listed on Bursa Malaysia over a span of 17 years from 2002 to 2018 were examined using a cross-sectional regression analysis. The findings demonstrated no significant impact arising from the fractions of shares allocated to Bumiputera investors on the oversubscription ratios, except that the revised guidelines on the Bumiputera equity requirement had a significant negative influence on oversubscription. Further tests showed that the influence of such share allocation on oversubscription was moderated by firm size, which was proxied by market capitalization. The findings lend support to the signaling theory, indicating that the demand for IPOs will be slightly higher for larger firms listed in bigger markets. [ABSTRACT FROM AUTHOR]

By using the Delphi technique and a case study on Malaysia's nanotechnology research and Information and Communication Technology (ICT) industries, this paper aims to determine the development and convergence of nanotechnology and ICT innovation systems from the perspective of science-industry relations. A total of 25 experts have provided their opinions and consensus on the present stage and possible future scenarios of nanotech-ICT development from four dimensions: technology landscape, economic viability, governance, and social acceptance. Results from two survey rounds indicate that the Malaysian ICT innovation system is presently economically viable and easily accepted by the market. The best-case scenario can be achieved with the help of nanotechnology. This would also require the implementation of policies and regulations from government. Although industrial and social adoption and the acceptance of nanotechnology are already strong, government is responsible for creating various programs to ensure greater awareness and development of knowledge. [ABSTRACT FROM AUTHOR]

Diabetes mellitus is a global pandemic, especially in Southeast Asia. Diabetic foot infection (DFI) is a common complication of this condition and causes significant morbidity and mortality in those affected. There is a lack of locally published data on the types of microorganisms and empirical antibiotics being prescribed. This paper highlights the importance of local microorganism culture and antibiotic prescription trends among diabetic foot patients in a tertiary care hospital in central Malaysia. This is a retrospective, cross-sectional study of data taken from January 2010 to December 2019 among 434 patients admitted with diabetic foot infections (DFIs) using the Wagner classification. Patients between the ages of 58 and 68 years old had the highest rate of infection. Pseudomonas Aeruginosa, Proteus spp., and Proteus mirabilis appeared to be the most isolated Gram-negative microorganisms, and Staphylococcus aureus, Streptococcus agalactiae, and MRSA appeared to be the most common Gram-positive microorganisms. The most common empirical antibiotics prescribed were ampicillin/sulbactam, followed by ciprofloxacin and ceftazidime, and the most common therapeutic antibiotics prescribed were ampicillin/sulbactam, ciprofloxacin, and cefuroxime. This study could be immensely pertinent in facilitating future empirical therapy guidelines for treating diabetic foot infections. [ABSTRACT FROM AUTHOR]

The Sāgaramatiparipṛcchā, "Questions of the Oceanic Intelligence," is the fifth chapter of the Mahāsaṃnipāta, "Great Collection," and is a canonical work belonging to the tradition of Mahāyāna sūtra literature. This sūtra is highly valued in the long history of Mahāyāna Buddhism for its thematic and metaphorical richness, as it personifies the ocean (Skt. sāgara) to represent core aspects of the Mahāyāna doctrinal system. This paper presents two small Sanskrit fragments of the Sāgaramatiparipṛcchā recently identified in the Schøyen Collection, with transliteration and annotated translation. In order to provide a fuller picture of the textual history of the Sāgaramatiparipṛcchā, a quotation from the text on votive tablets from Kedah, Malaysia, is also discussed. These materials are employed as a case study within the context of tangible and intangible heritage. On the basis of the UNESCO declaration of 2003, it is argued that these two kinds of heritage are intrinsically interlinked, and that the categories and their pertaining definitions can be broadened so as to be relevant to more traditions and their heritage. [ABSTRACT FROM AUTHOR]

Mobile health (mHealth) apps are designed to support health behavior outcomes and improve well-being. The existing body of literature confirms mHealth's overall efficacy in promoting physical activity; however, more research on its utility in sustaining user engagement is needed. Understanding the determinants of an individual's willingness to continue using mHealth is vital to improving the intervention's success. This study developed a unified model and survey instrument adapted from extant literature while introducing new constructs to predict the sustained use of gamified mHealth. A pilot study was conducted to validate the survey instrument using 48 gamified fitness app users in Malaysia. The survey instrument was tested following rigorous guidelines for quantitative research in the information system context. According to the findings, the reliabilities of most measurement items met the criterion, and those items were retained. Overall, this paper contributes by integrating social comparison theory and the self-determination theory for sustaining user engagement with gamified mHealth through an extrinsic and intrinsic motivation perspective. [ABSTRACT FROM AUTHOR]

In this paper, the optimal design of a hybrid energy system (HES), consisting of photovoltaic technology integrated with fuel cells (HPV/FC) and relying on hydrogen storage, is performed to meet the annual demand of a residential complex to find the minimum total net present cost (TNPC), while observing the reliability constraint as the energy-not-supplied probability (ENSP) and considering real meteorological data of the Kuala Lumpur city in Malaysia. The decision variables include the size of system components, which are optimally determined by an improved artificial ecosystem-based optimization algorithm (IAEO). The conventional AEO is improved using the dynamic lens-imaging learning strategy (DLILS) to prevent premature convergence. The results demonstrated that the decrease (increase) of the reliability constraint leads to an increase (decrease) in the TNPC, as well as the cost of electricity (COE). For a maximum reliability constraint of 5%, the results show that the TNPC and COE obtained USD 2.247 million and USD 0.4046 million, respectively. The superior performance of the IAEO has been confirmed with the AEO, particle swarm optimization (PSO), and manta ray foraging optimization (MRFO), with the lowest TNPC and higher reliability. In addition, the effectiveness of the hydrogen tank efficiency and load changes is confirmed in the hybrid system design. [ABSTRACT FROM AUTHOR]

Rivers are a source of life. However, these past years, the sustainability of rivers around the world has been threatened by urbanization, industrialization, and rapid development. These activities put pressure on waterway systems and rivers, leading to the emergence of riverine litter. The lack of understanding of the migration of litter in rivers can affect the decision-making efficiency of policymakers when it comes to riverine litter management. Therefore, the primary objective of this study is to evaluate the travel time for different densities of Floatable Litter (FL) in rivers influenced by river flow velocity. The density of the selected FL was manually determined by assessing litter characteristics of mass, volume, and size. The Sg. Berkelah river in Pahang, Malaysia was used as the simulation medium for the sampling of FL travel time utilizing the extrapolation of the Time of Travel (ToT) approach. The ToT technique utilizes a 30 m distance. The sampling was done under three different river flow velocity conditions. In this study, a correlation analysis between these two variables was carried out and evaluated. The results revealed that magazine papers possess the fastest FL travel time, with T = 43.93 s when v = 0.230 m/s, while cloth possesses the slowest FL travel time, with T = 204.90 s when v = 0.167 m/s. The travel time of FL is not influenced by low-class density, p < 1000 kg/m3, but by other factors that have a stronger influence on the travel time of horizontally migrated litter. This study provides a basic understanding and overview of FL migrating characteristics in rivers for further reference by local authorities for litter monitoring and also future riverine litter studies. [ABSTRACT FROM AUTHOR]

Leachate generation is among the main challenging issues that landfill operators must handle. Leachate is created when decomposed materials and rainwater pass through the waste. Leachate carries many harmful pollutants, with high concentrations of BOD, COD, colour, heavy metals, ammoniacal nitrogen (NH3-N), and other organic and inorganic pollutants. Among them, COD, colour, and NH3-N are difficult to be completely eliminated, especially with a single treatment. They should be handled by appropriate treatment facilities before being safely released into the environment. Leachate remediation varies based on its properties, the costs of operation and capital expenditures, as well as the rules and regulations. Up until now, much scientific and engineering attention was given to the development of comprehensive solutions to leachate-related issues. The solutions normally demand a multi-stage treatment, commonly in the form of biological, chemical, and physical sequences. This review paper discussed the use of contemporary techniques to remediate landfill leachate with an emphasis on concentrated COD, colour, and NH3-N levels with low biodegradability that is normally present in old landfill or dumping grounds in developing countries. A semi-aerobic type of landfill design was also discussed, as this concept is potentially sustainable compared to others. Some of the challenges and future prospects were also recommended, especially for the case of Malaysia. This may represent landfills or dumpsites in other developing countries with the same characteristics. [ABSTRACT FROM AUTHOR]

Water shortage has been an issue for urbanized areas. For the Penang state in Malaysia, it is forecast that there will be a significant increase in water demand in the future. Penang authorities in Malaysia are trying to find an alternative water source to overcome the problem, with one of the options being the Perai River catchment. However, the river water quality was found to be polluted and not suitable to be used for water extraction for domestic consumption. This paper aims to study the pollution level variation due to changes in rainfall during the year in the Perai River Basin, and estimate the TMDL of the river in a particular case for BOD, COD, and NH3N parameters. A water quality model was developed for the Perai River, Jarak River and Kulim River using InfoWorks ICM. The year 2016 was selected as a model event due to data availability. BOD, COD and NH3N concentrations were used for TMDL calculation, and the load duration curve approach was used to estimate TMDL. The tidal effect at the downstream of the Perai River was found to impact the data analysis in the river stretch. It was found that pollutant load exceedance was the highest during the rainy season and the problematic pollutant was NH3N. Thus, local authorities need to focus on tidal and seasonal change factors when developing action plans to manage water quality issues in this basin. [ABSTRACT FROM AUTHOR]