Showing papers by "National University of Malaysia published in 2018"

A review of ZnO nanoparticles as solar photocatalysts: Synthesis, mechanisms and applications

Abstract: Persistent organic pollutants (POPs) are carbon-based chemical substances that are resistant to environmental degradation and may not be completely removed through treatment processes. Their persistence can contribute to adverse health impacts on wild-life and human beings. Thus, the solar photocatalysis process has received increasing attention due to its great potential as a green and eco-friendly process for the elimination of POPs to increase the security of clean water. In this context, ZnO nanostructures have been shown to be prominent photocatalyst candidates to be used in photodegradation owing to the facts that they are low-cost, non-toxic and more efficient in the absorption across a large fraction of the solar spectrum compared to TiO 2 . There are several aspects, however, need to be taken into consideration for further development. The purpose of this paper is to review the photo-degradation mechanisms of POPs and the recent progress in ZnO nanostructured fabrication methods including doping, heterojunction and modification techniques as well as improvements of ZnO as a photocatalyst. The second objective of this review is to evaluate the immobilization of photocatalyst and suspension systems while looking into their future challenges and prospects.

Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Abstract: Summary Background Neurological disorders are now the leading source of disability globally, and ageing is increasing the burden of neurodegenerative disorders, including Parkinson's disease. We aimed to determine the global burden of Parkinson's disease between 1990 and 2016 to identify trends and to enable appropriate public health, medical, and scientific responses. Methods Through a systematic analysis of epidemiological studies, we estimated global, regional, and country-specific prevalence and years of life lived with disability for Parkinson's disease from 1990 to 2016. We estimated the proportion of mild, moderate, and severe Parkinson's disease on the basis of studies that used the Hoehn and Yahr scale and assigned disability weights to each level. We jointly modelled prevalence and excess mortality risk in a natural history model to derive estimates of deaths due to Parkinson's disease. Death counts were multiplied by values from the Global Burden of Disease study's standard life expectancy to compute years of life lost. Disability-adjusted life-years (DALYs) were computed as the sum of years lived with disability and years of life lost. We also analysed results based on the Socio-demographic Index, a compound measure of income per capita, education, and fertility. Findings In 2016, 6·1 million (95% uncertainty interval [UI] 5·0–7·3) individuals had Parkinson's disease globally, compared with 2·5 million (2·0–3·0) in 1990. This increase was not solely due to increasing numbers of older people, because age-standardised prevalence rates increased by 21·7% (95% UI 18·1–25·3) over the same period (compared with an increase of 74·3%, 95% UI 69·2–79·6, for crude prevalence rates). Parkinson's disease caused 3·2 million (95% UI 2·6–4·0) DALYs and 211 296 deaths (95% UI 167 771–265 160) in 2016. The male-to-female ratios of age-standardised prevalence rates were similar in 2016 (1·40, 95% UI 1·36–1·43) and 1990 (1·37, 1·34–1·40). From 1990 to 2016, age-standardised prevalence, DALY rates, and death rates increased for all global burden of disease regions except for southern Latin America, eastern Europe, and Oceania. In addition, age-standardised DALY rates generally increased across the Socio-demographic Index. Interpretation Over the past generation, the global burden of Parkinson's disease has more than doubled as a result of increasing numbers of older people, with potential contributions from longer disease duration and environmental factors. Demographic and potentially other factors are poised to increase the future burden of Parkinson's disease substantially. Funding Bill & Melinda Gates Foundation.

Environmental triggers in IBD: a review of progress and evidence.

Abstract: A number of environmental factors have been associated with the development of IBD. Alteration of the gut microbiota, or dysbiosis, is closely linked to initiation or progression of IBD, but whether dysbiosis is a primary or secondary event is unclear. Nevertheless, early-life events such as birth, breastfeeding and exposure to antibiotics, as well as later childhood events, are considered potential risk factors for IBD. Air pollution, a consequence of the progressive contamination of the environment by countless compounds, is another factor associated with IBD, as particulate matter or other components can alter the host's mucosal defences and trigger immune responses. Hypoxia associated with high altitude is also a factor under investigation as a potential new trigger of IBD flares. A key issue is how to translate environmental factors into mechanisms of IBD, and systems biology is increasingly recognized as a strategic tool to unravel the molecular alterations leading to IBD. Environmental factors add a substantial level of complexity to the understanding of IBD pathogenesis but also promote the fundamental notion that complex diseases such as IBD require complex therapies that go well beyond the current single-agent treatment approach. This Review describes the current conceptualization, evidence, progress and direction surrounding the association of environmental factors with IBD.

State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations

Abstract: A variety of rechargeable batteries are now available in world markets for powering electric vehicles (EVs). The lithium-ion (Li-ion) battery is considered the best among all battery types and cells because of its superior characteristics and performance. The positive environmental impacts and recycling potential of lithium batteries have influenced the development of new research for improving Li-ion battery technologies. However, the cost reduction, safe operation, and mitigation of negative ecological impacts are now a common concern for advancement. This paper provides a comprehensive study on the state of the art of Li-ion batteries including the fundamentals, structures, and overall performance evaluations of different types of lithium batteries. A study on a battery management system for Li-ion battery storage in EV applications is demonstrated, which includes a cell condition monitoring, charge, and discharge control, states estimation, protection and equalization, temperature control and heat management, battery fault diagnosis, and assessment aimed at enhancing the overall performance of the system. It is observed that the Li-ion batteries are becoming very popular in vehicle applications due to price reductions and lightweight with high power density. However, the management of the charging and discharging processes, CO2 and greenhouse gases emissions, health effects, and recycling and refurbishing processes have still not been resolved satisfactorily. Consequently, this review focuses on the many factors, challenges, and problems and provides recommendations for sustainable battery manufacturing for future EVs. This review will hopefully lead to increasing efforts toward the development of an advanced Li-ion battery in terms of economics, longevity, specific power, energy density, safety, and performance in vehicle applications.

Review of Energy Storage System Technologies in Microgrid Applications: Issues and Challenges

Abstract: A microgrid (MG) is a local entity that consists of distributed energy resources (DERs) to achieve local power reliability and sustainable energy utilization. The MG concept or renewable energy technologies integrated with energy storage systems (ESS) have gained increasing interest and popularity because it can store energy at off-peak hours and supply energy at peak hours. However, existing ESS technology faces challenges in storing energy due to various issues, such as charging/discharging, safety, reliability, size, cost, life cycle, and overall management. Thus, an advanced ESS is required with regard to capacity, protection, control interface, energy management, and characteristics to enhance the performance of ESS in MG applications. This paper comprehensively reviews the types of ESS technologies, ESS structures along with their configurations, classifications, features, energy conversion, and evaluation process. Moreover, details on the advantages and disadvantages of ESS in MG applications have been analyzed based on the process of energy formations, material selection, power transfer mechanism, capacity, efficiency, and cycle period. Existing reviews critically demonstrate the current technologies for ESS in MG applications. However, the optimum management of ESSs for efficient MG operation remains a challenge in modern power system networks. This review also highlights the key factors, issues, and challenges with possible recommendations for the further development of ESS in future MG applications. All the highlighted insights of this review significantly contribute to the increasing effort toward the development of a cost-effective and efficient ESS model with a prolonged life cycle for sustainable MG implementation.

Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge gaps

Abstract: Partial least squares-discriminant analysis (PLS-DA) is a versatile algorithm that can be used for predictive and descriptive modelling as well as for discriminative variable selection. However, versatility is both a blessing and a curse and the user needs to optimize a wealth of parameters before reaching reliable and valid outcomes. Over the past two decades, PLS-DA has demonstrated great success in modelling high-dimensional datasets for diverse purposes, e.g. product authentication in food analysis, diseases classification in medical diagnosis, and evidence analysis in forensic science. Despite that, in practice, many users have yet to grasp the essence of constructing a valid and reliable PLS-DA model. As the technology progresses, across every discipline, datasets are evolving into a more complex form, i.e. multi-class, imbalanced and colossal. Indeed, the community is welcoming a new era called big data. In this context, the aim of the article is two-fold: (a) to review, outline and describe the contemporary PLS-DA modelling practice strategies, and (b) to critically discuss the respective knowledge gaps that have emerged in response to the present big data era. This work could complement other available reviews or tutorials on PLS-DA, to provide a timely and user-friendly guide to researchers, especially those working in applied research.

Advances in cellulose nanomaterials

Abstract: Research on nanocellulose has significantly increased over the past few decades, owing to the various attractive characteristics of this material, such as renewability, widespread availability, low density, excellent mechanical properties, economic value, biocompatibility, and biodegradability. Nanocellulose categorized into two main types, namely cellulose nanofibrils (CNFs) and cellulose nanocrystals (CNCs). In this review, we present the recent advances made in the production of CNFs and CNCs. In addition to the conventional mechanical and chemical treatments used to prepare CNFs and CNCs, respectively, other promising techniques as well as pretreatment processes have been also proposed in recent times, in an effort to design an economically efficient and eco-friendly production route for nanocellulose. Further, while the hydrophilic nature of nanocellulose limits its use in polymeric matrices and in some industrial applications, the large number of hydroxyl groups on the surface of nanocellulose provides a suitable platform for various kinds of modification treatments. The various chemical and physical surface treatment procedures reported for nanocellulose have been reviewed in this paper. Finally, in this review, we summarize the life cycle assessment studies conducted so far on nanocellulose, which quantify the environmental impact of nanocellulose products. The current paper is a comprehensive review of the recent literature on nanostructured cellulose.

Review on Home Energy Management System Considering Demand Responses, Smart Technologies, and Intelligent Controllers

Abstract: The increasing demand for electricity and the emergence of smart grids have presented new opportunities for a home energy management system (HEMS) that can reduce energy usage. The HEMS incorporates a demand response (DR) tool that shifts and curtails demand to improve home energy consumption. This system commonly creates optimal consumption schedules by considering several factors, such as energy costs, environmental concerns, load profiles, and consumer comfort. With the deployment of smart meters, performing load control using the HEMS with DR-enabled appliances has become possible. This paper provides a comprehensive review on previous and current research related to the HEMS by considering various DR programs, smart technologies, and load scheduling controllers. The application of artificial intelligence for load scheduling controllers, such as artificial neural network, fuzzy logic, and adaptive neural fuzzy inference system, is also reviewed. Heuristic optimization techniques, which are widely used for optimal scheduling of various electrical devices in a smart home, are also discussed.

Enhanced photoelectrochemical performance of Z-scheme g-C3N4/BiVO4 photocatalyst

Abstract: BiVO4 is a considerably promising semiconductor for photoelectrochemical water splitting due to its stability, low cost and moderate band gap. In this research, g-C3N4 was proposed in Z-scheme configuration which boosted the performance of BiVO4 up to four times. The experimental observations were counterchecked with Density Functional Theory (DFT) simulations. A TiO2/BiVO4 heterojunction was developed and its performance was compared with that of g-C3N4/BiVO4. The photocurrent for g-C3N4/BiVO4 was 0.42 mAcm−2 at 1.23 V vs. RHE which was the highest among g-C3N4 based Z-scheme heterojunction devices. Lower charge transfer resistance, higher light absorption and more oxygen vacancy sites were observed for the g-C3N4 based heterojunction. The simulated results attested that g-C3N4 and BiVO4 formed a van der Waals type heterojunction, where an internal electric field facilitated the separation of electron/hole pair at g-C3N4/BiVO4 interface which further restrained the carrier recombination. Both the valence and conduction band edge positions of g-C3N4 and BiVO4 changed with the Fermi energy level. The resulted heterojunction had small effective masses of electrons (0.01 me) and holes (0.10 me) with ideal band edge positions where both CBM and VBM were well above and below the redox potential of water.

A marine heatwave drives massive losses from the world’s largest seagrass carbon stocks

Abstract: Seagrass ecosystems contain globally significant organic carbon (C) stocks. However, climate change and increasing frequency of extreme events threaten their preservation. Shark Bay, Western Australia, has the largest C stock reported for a seagrass ecosystem, containing up to 1.3% of the total C stored within the top metre of seagrass sediments worldwide. On the basis of field studies and satellite imagery, we estimate that 36% of Shark Bay’s seagrass meadows were damaged following a marine heatwave in 2010/2011. Assuming that 10 to 50% of the seagrass sediment C stock was exposed to oxic conditions after disturbance, between 2 and 9 Tg CO2 could have been released to the atmosphere during the following three years, increasing emissions from land-use change in Australia by 4–21% per annum. With heatwaves predicted to increase with further climate warming, conservation of seagrass ecosystems is essential to avoid adverse feedbacks on the climate system. Marine ecosystems and their stored carbon are threatened by warming and marine heatwaves. During a 2010–2011 heatwave, around a third of a Western Australian seagrass ecosystem suffered damage, potentially releasing 2–9 Tg CO2 in the following years.

Geometric and design parameters of fins employed for enhancing thermal energy storage systems: a review

Abstract: The continuous increase in the level of green-house gas emissions and the depletion of fossil ‎fuels are identified, as the major driving forces behind efforts to effectively utilize different sources of renewable energy. Solar energy ‎considered one of the most prospective sources of this energy. This review paper mainly focuses on the majority of heat-transfer enhancement techniques between the phase-change material (PCM) and the heat-transfer fluid (HTF) based on the application of fins embedded in the PCM. This study ‎also investigated the geometrical dimensions, dimensionless numbers, and fin location through numerical ‎and experimental works conducted to assess the influences of these parameters on the thermal performance of PCM-latent heat thermal energy storage (LHTES) containers. The best enhancement is ‎achieved using the longitudinal finned configurations because of its easy design and fabrication, especially along circumference of the cylindrical PCM containers. The circular-finned tube was also more effective than the pinned-tube for different shell and tube. PCMs based on heat sinks with internal pin fins were widely used for the thermal ‎management of various pieces of electronic products. The heat enhancement factor was effectively dependent on increasing the numbers and dimensions ‎of these fins. Further researches still require to explore the ‎possible geometrical designs of fins and their key findings, which have more effect on the thermal performance of the ‎finned-LHTES system.

Electrode for proton exchange membrane fuel cells: A review

Abstract: The electrode is the key component of the membrane electrode assembly (MEA) of proton exchange membrane fuel cells (PEMFCs). The electrochemical reaction of hydrogen (fuel) and oxygen that transform into water and electrical energy occurs at the catalyst site. Attempts to improve the performance and durability of electrodes have sought to overcome the challenges arising from utilizing PEMFCs as an efficient and competitive energy source. To accomplish this goal and to solve the problems related to using PEMFC electrodes, the structure and function of each component and the manufacturing method must be comprehensively understood, and the electrode performance and durability of the cell must be characterized. Therefore, in this paper, we discuss the components, preparation, functions and performance of the electrodes used in PEMFCs. This review aims to provide comprehensive information regarding PEMFC electrodes.

Moringa Genus: A Review of Phytochemistry and Pharmacology.

Abstract: Moringa is a genus of medicinal plants that has been used traditionally to cure wounds and various diseases such as colds and diabetes. In addition, the genus is also consumed as a source of nutrients and widely used for purifying water. The genus consists of 13 species that have been widely cultivated throughout Asia and Africa for their multiple uses. The purpose of this review is to provide updated and categorized information on the traditional uses, phytochemistry, biological activities, and toxicological research of Moringa species in order to explore their therapeutic potential and evaluate future research opportunities. The literature reviewed for this paper was obtained from PubMed, ScienceDirect, and Google Scholar journal papers published from 1983 to March 2017. Moringa species are well-known for their antioxidant, anti-inflammatory, anticancer, and antihyperglycemic activities. Most of their biological activity is caused by their high content of flavonoids, glucosides, and glucosinolates. By documenting the traditional uses and biological activities of Moringa species, we hope to support new research on these plants, especially on those species whose biological properties have not been studied to date.

Graphitic carbon nitride (g-C3N4) electrodes for energy conversion and storage: a review on photoelectrochemical water splitting, solar cells and supercapacitors

Abstract: Graphitic carbon nitride (g-C3N4) has emerged as one of the most promising photocatalysts due to its metal-free nature, abundance of raw material, and thermal physical–chemical stability. The breakthrough research studies in recent years have mostly been concentrated on the engineering of the intrinsic and morphological properties of g-C3N4-based photocatalysts in the framework of powder suspensions for artificial photosynthesis and environmental remediation. However, practical applications of g-C3N4-based electrodes and devices are still in the early stages of development due to challenging fabrication methods of g-C3N4 thin films. This review addresses the classification of diverse techniques to deposit g-C3N4-based thin films and explores a broad spectrum of applications pertinent to g-C3N4-based electrodes. Although this paper is principally focused on photoelectrochemical water splitting, other emerging applications of g-C3N4 in solar cells, electrocatalysts and supercapacitors are also reviewed. Lastly, further suggestions are posited for other potential applications, challenges and future orientations.

Prospects of life cycle assessment of renewable energy from solar photovoltaic technologies: A review

Abstract: Life cycle assessment (LCA) is a comprehensive method used to investigate the environmental impacts and energy use of a product throughout its entire life cycle. For solar photovoltaic (PV) technologies, LCA studies need to be conducted to address environmental and energy issues and foster the development of PV technologies in a sustainable manner. This paper reviews and analyzes LCA studies on solar PV technologies, such as silicon, thin film, dye-sensitized solar cell, perovskite solar cell, and quantum dot-sensitized solar cell. The PV life cycle assumes a cradle-to-grave mechanism, starting from the extraction of raw materials until the disposal or recycling of the solar PV. Three impact assessment methods in LCA were reviewed and summarized, namely, cumulative energy demand (CED), energy payback time (EPBT), and GHG emission rate, based on data and information published in the literature. LCA results show that mono-crystalline silicon PV technology has the highest energy consumption, longest EPBT, and highest greenhouse gas emissions rate compared with other solar PV technologies.

Global, regional, and national burden of meningitis, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

Abstract: Summary Background Acute meningitis has a high case-fatality rate and survivors can have severe lifelong disability. We aimed to provide a comprehensive assessment of the levels and trends of global meningitis burden that could help to guide introduction, continuation, and ongoing development of vaccines and treatment programmes. Methods The Global Burden of Diseases, Injuries, and Risk Factors (GBD) 2016 study estimated meningitis burden due to one of four types of cause: pneumococcal, meningococcal, Haemophilus influenzae type b, and a residual category of other causes. Cause-specific mortality estimates were generated via cause of death ensemble modelling of vital registration and verbal autopsy data that were subject to standardised data processing algorithms. Deaths were multiplied by the GBD standard life expectancy at age of death to estimate years of life lost, the mortality component of disability-adjusted life-years (DALYs). A systematic analysis of relevant publications and hospital and claims data was used to estimate meningitis incidence via a Bayesian meta-regression tool. Meningitis deaths and cases were split between causes with meta-regressions of aetiological proportions of mortality and incidence, respectively. Probabilities of long-term impairment by cause of meningitis were applied to survivors and used to estimate years of life lived with disability (YLDs). We assessed the relationship between burden metrics and Socio-demographic Index (SDI), a composite measure of development based on fertility, income, and education. Findings Global meningitis deaths decreased by 21·0% from 1990 to 2016, from 403 012 (95% uncertainty interval [UI] 319 426–458 514) to 318 400 (265 218–408 705). Incident cases globally increased from 2·50 million (95% UI 2·19–2·91) in 1990 to 2·82 million (2·46–3·31) in 2016. Meningitis mortality and incidence were closely related to SDI. The highest mortality rates and incidence rates were found in the peri-Sahelian countries that comprise the African meningitis belt, with six of the ten countries with the largest number of cases and deaths being located within this region. Haemophilus influenzae type b was the most common cause of incident meningitis in 1990, at 780 070 cases (95% UI 613 585–978 219) globally, but decreased the most (–49·1%) to become the least common cause in 2016, with 397 297 cases (291 076–533 662). Meningococcus was the leading cause of meningitis mortality in 1990 (192 833 deaths [95% UI 153 358–221 503] globally), whereas other meningitis was the leading cause for both deaths (136 423 [112 682–178 022]) and incident cases (1·25 million [1·06–1·49]) in 2016. Pneumococcus caused the largest number of YLDs (634 458 [444 787–839 749]) in 2016, owing to its more severe long-term effects on survivors. Globally in 2016, 1·48 million (1·04—1·96) YLDs were due to meningitis compared with 21·87 million (18·20—28·28) DALYs, indicating that the contribution of mortality to meningitis burden is far greater than the contribution of disabling outcomes. Interpretation Meningitis burden remains high and progress lags substantially behind that of other vaccine-preventable diseases. Particular attention should be given to developing vaccines with broader coverage against the causes of meningitis, making these vaccines affordable in the most affected countries, improving vaccine uptake, improving access to low-cost diagnostics and therapeutics, and improving support for disabled survivors. Substantial uncertainty remains around pathogenic causes and risk factors for meningitis. Ongoing, active cause-specific surveillance of meningitis is crucial to continue and to improve monitoring of meningitis burdens and trends throughout the world. Funding Bill & Melinda Gates Foundation.

Neural Network Approach for Estimating State of Charge of Lithium-Ion Battery Using Backtracking Search Algorithm

Abstract: The state of charge (SOC) is a critical evaluation index of battery residual capacity. The significance of an accurate SOC estimation is great for a lithium-ion battery to ensure its safe operation and to prevent from over-charging or over-discharging. However, to estimate an accurate capacity of SOC of the lithium-ion battery has become a major concern for the electric vehicle (EV) industry. Therefore, numerous researches are being conducted to address the challenges and to enhance the battery performance. The main objective of this paper is to develop an accurate SOC estimation approach for a lithium-ion battery by improving back-propagation neural network (BPNN) capability using backtracking search algorithm (BSA). BSA optimization is utilized to improve the accuracy and robustness of BPNN model by finding the optimal value of hidden layer neurons and learning rate. In this paper, Dynamic Stress Test and Federal Urban Driving Schedule drive profiles are applied for testing the model at three different temperatures. The obtained results of the BPNN based BSA model are compared with the radial basis function neural network, generalized regression neural network and extreme learning machine model using statistical error values of root mean square error, mean absolute error, mean absolute percentage error, and SOC error to check and validate the model performance. The obtained results show that the BPNN based BSA model outperforms other neural network models in estimating SOC with high accuracy under different EV profiles and temperatures.