Universiti Malaysia Perlis

The aim of this study is to study the influence of different solvents on the structure and electrical properties of graphene oxide. GO was obtained from graphite flakes by using modified hummers method in which different from conventional hummer's method. In this method, the experiment was synthesized without sodium nitrate (NaNO3) and ice bath, but carried out at room temperature. Prepared GO powders were then dissolved into different solvents, namely acetone and ethanol. Then spin-coated onto silicon wafer and IDE to produce acetone-GO (A-GO) and ethanol-GO (E-GO). SEM result shows that several square micron GO were obtained. In addition, due to the large agglomerates and contact between the flakes in E-GO sample, current-voltage pattern indicated the E-GO produced higher current flow than A-GO. Meanwhile, GO characterized using FTiR shows that both samples contain several functional groups such as hydroxyl, epoxy, carboxyl and carbonyl. Besides that, due to the lower diffraction peak of A-GO, XRD result shows the interlayer spacing of A-GO sample is slightly higher than E-GO sample.

In an effort to mitigate the outbreak of COVID-19, many countries have imposed drastic lockdown, movement control or shelter in place orders on their residents. The effectiveness of these mitigation measures is highly dependent on cooperation and compliance of all members of society. The knowledge, attitudes and practices people hold toward the disease play an integral role in determining a society's readiness to accept behavioural change measures from health authorities. The aim of this study was to determine the knowledge levels, attitudes and practices toward COVID-19 among the Malaysian public. A cross-sectional online survey of 4,850 Malaysian residents was conducted between 27th March and 3rd April 2020. The survey instrument consisted of demographic characteristics, 13 items on knowledge, 3 items on attitudes and 3 items on practices, modified from a previously published questionnaire on COVID-19. Descriptive statistics, chi-square tests, t-tests and one-way analysis of variance (ANOVA) were conducted. The overall correct rate of the knowledge questionnaire was 80.5%. Most participants held positive attitudes toward the successful control of COVID-19 (83.1%), the ability of Malaysia to conquer the disease (95.9%) and the way the Malaysian government was handling the crisis (89.9%). Most participants were also taking precautions such as avoiding crowds (83.4%) and practising proper hand hygiene (87.8%) in the week before the movement control order started. However, the wearing of face masks was less common (51.2%). This survey is among the first to assess knowledge, attitudes and practice in response to the COVID-19 pandemic in Malaysia. The results highlight the importance of consistent messaging from health authorities and the government as well as the need for tailored health education programs to improve levels of knowledge, attitudes and practices.

Foot plantar pressure is the pressure field that acts between the foot and the support surface during everyday locomotor activities. Information derived from such pressure measures is important in gait and posture research for diagnosing lower limb problems, footwear design, sport biomechanics, injury prevention and other applications. This paper reviews foot plantar sensors characteristics as reported in the literature in addition to foot plantar pressure measurement systems applied to a variety of research problems. Strengths and limitations of current systems are discussed and a wireless foot plantar pressure system is proposed suitable for measuring high pressure distributions under the foot with high accuracy and reliability. The novel system is based on highly linear pressure sensors with no hysteresis.

In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Researchers have attempted to determine driver drowsiness using the following measures: (1) vehicle-based measures; (2) behavioral measures and (3) physiological measures. A detailed review on these measures will provide insight on the present systems, issues associated with them and the enhancements that need to be done to make a robust system. In this paper, we review these three measures as to the sensors used and discuss the advantages and limitations of each. The various ways through which drowsiness has been experimentally manipulated is also discussed. We conclude that by designing a hybrid drowsiness detection system that combines non-intrusive physiological measures with other measures one would accurately determine the drowsiness level of a driver. A number of road accidents might then be avoided if an alert is sent to a driver that is deemed drowsy.

Microplastic pollution is becoming a major issue for human health due to the recent discovery of microplastics in most ecosystems. Here, we review the sources, formation, occurrence, toxicity and remediation methods of microplastics. We distinguish ocean-based and land-based sources of microplastics. Microplastics have been found in biological samples such as faeces, sputum, saliva, blood and placenta. Cancer, intestinal, pulmonary, cardiovascular, infectious and inflammatory diseases are induced or mediated by microplastics. Microplastic exposure during pregnancy and maternal period is also discussed. Remediation methods include coagulation, membrane bioreactors, sand filtration, adsorption, photocatalytic degradation, electrocoagulation and magnetic separation. Control strategies comprise reducing plastic usage, behavioural change, and using biodegradable plastics. Global plastic production has risen dramatically over the past 70 years to reach 359 million tonnes. China is the world's top producer, contributing 17.5% to global production, while Turkey generates the most plastic waste in the Mediterranean region, at 144 tonnes per day. Microplastics comprise 75% of marine waste, with land-based sources responsible for 80-90% of pollution, while ocean-based sources account for only 10-20%. Microplastics induce toxic effects on humans and animals, such as cytotoxicity, immune response, oxidative stress, barrier attributes, and genotoxicity, even at minimal dosages of 10 μg/mL. Ingestion of microplastics by marine animals results in alterations in gastrointestinal tract physiology, immune system depression, oxidative stress, cytotoxicity, differential gene expression, and growth inhibition. Furthermore, bioaccumulation of microplastics in the tissues of aquatic organisms can have adverse effects on the aquatic ecosystem, with potential transmission of microplastics to humans and birds. Changing individual behaviours and governmental actions, such as implementing bans, taxes, or pricing on plastic carrier bags, has significantly reduced plastic consumption to 8-85% in various countries worldwide. The microplastic minimisation approach follows an upside-down pyramid, starting with prevention, followed by reducing, reusing, recycling, recovering, and ending with disposal as the least preferable option.

Graphene oxide (GO) and reduced graphene oxide (RGO) are known to have superior properties for various applications. This work compares the properties of GO and RGO with graphite. GO was prepared by using Improved Hummer’s method whereas the produced GO was subjected to chemical reduction with the use of hydrazine hydrate. Graphite, GO and RGO had different morphologies, quality, functionalized groups, UV-Vis absorption peaks and crystallinity. With the removal of oxygen-containing functional group during reduction for RGO, the quality of samples was decreased due to higher intensity of D band than G band was seen in Raman results. In addition, platelet-like surface can be observed on the surface of graphite as compared to GO and RGO where wrinkled and layered flakes, and crumpled thin sheets were observed on GO and RGO surface respectively. Fourier Transform Infra-Red (FTIR) analysis showed the presence of abundant oxygen-containing functional groups in GO as compared to RGO and graphite. The characteristic peaks at 26.62°, 9.03° and 24.10° for graphite, GO and RGO, respectively, can be detected from X-Ray diffraction (XRD). Furthermore, the reduction also caused red shift at 279nm from 238nm, as obtained from ultraviolet visible (UV-Vis) analysis. The results proved that GO was successfully oxidized from graphite whereas RGO was effectively reduced from GO.

The ability to detect pathogenic and physiologically relevant molecules in the body with high sensitivity and specificity offers a powerful opportunity in the early diagnosis and treatment of diseases. Early detection and diagnosis can be used to greatly reduce the cost of patient care associated with the advanced stages of many diseases. However, despite their widespread clinical use, these techniques have a number of potential limitations. For example, a number of diagnostic devices have slow response times and are burdensome to patients. Furthermore, these assays are expensive and cost the health care industry billions of dollars every year. Therefore, there is a need to develop more efficient and reliable sensing and detection technologies. A biosensor is commonly defined as an analytical device that uses a biological recognition system to target molecules or macromolecules. Biosensors can be coupled to a physiochemical transducer that converts this recognition into a detectable output signal. Typically biosensors are comprised of three components: (1) the detector, which identifies the stimulus; (2) the transducer, which converts this stimulus to a useful output; and (3) the signal processing system, which involves amplification and display of the output in an appropriate format. The goal of this combination is to utilize the high sensitivity and selectivity of biological sensing for analytical purposes in various fields of research and technology. We review here some of the main advances in this field over the past few years, explore the application prospects, and discuss the issues, approaches, and challenges, with the aim of stimulating a broader interest in developing biosensors and improving their applications in medical diagnosis.

An enriched theoretical model of regulatory compliance is developed in this paper. The body of empirical evidence demonstrates that the pure deterrence model of regulatory compliance, which focuses primarily on the certainty and severity of sanctions as key determinants of compliance, provides only a partial explanation of compliance behavior. To offer a more complete explanation, the model developed herein integrates economic theory with theories from psychology and sociology to account for both tangible and intangible motivations influencing individuals’ decisions whether to comply with a given set of regulations. Specifically, the model accounts for moral obligation and social influence in addition to the conventional costs and revenues associated with illegal behavior. While cast in a natural resource management context, the theory developed here is applicable to a variety of institutional conditions. The resulting framework enables the design and implementation of more efficient compliance and regulatory programs than was heretofore possible.

Natural fiber such as bamboo fiber, oil palm empty fruit bunch (OPEFB) fiber, kenaf fiber, and sugar palm fiber-reinforced polymer composites are being increasingly developed for lightweight structures with high specific strength in the automotive, marine, aerospace, and construction industries with significant economic benefits, sustainability, and environmental benefits. The plant-based natural fibers are hydrophilic, which is incompatible with hydrophobic polymer matrices. This leads to a reduction of their interfacial bonding and to the poor thermal stability performance of the resulting fiber-reinforced polymer composite. Based on the literature, the effect of chemical treatment of natural fiber-reinforced polymer composites had significantly influenced the thermogravimetric analysis (TGA) together with the thermal stability performance of the composite structure. In this review, the effect of chemical treatments used on cellulose natural fiber-reinforced thermoplastic and thermosetting polymer composites has been reviewed. From the present review, the TGA data are useful as guidance in determining the purity and composition of the composites’ structures, drying, and the ignition temperatures of materials. Knowing the stability temperatures of compounds based on their weight, changes in the temperature dependence is another factor to consider regarding the effectiveness of chemical treatments for the purpose of synergizing the chemical bonding between the natural fiber with polymer matrix or with the synthetic fibers.

Internet shopping is a phenomena that is growing rapidly nowadays. A peep into the exponential growth of the main players in this industry indicates there is still a large reservoir of market potential for e-commerce. The conveniency of online shopping rendering it an emerging trend among consumers, especially the Gen Y. The prevalence of online shopping has raised the interest of the retailers to focus on this area. Therefore, this study was to determine the relationship between subjective norm, perceived usefulness and online shopping behavior while mediated by purchase intention. University students aged between 18 and 34 that currently pursuing their studies in University Malaysia Perlis were selected as the subject of analysis. 662 out of 800 sets of questionnaires distributed were valid for coding, analyzing and testing the hypothesis. Collected data were then analyzed using SPSS version 18.0 and AMOS version 16.0. Structural Equation Modeling to examine the model fits and hypothesis testing. The conclusion can be depicted that subjective norm and perceived usefulness significant positively influence online purchase intention but subjective norm insignificant influence shopping behavior in a negative way. It is interesting to note that perceived usefulness also insignificantly influence online shopping behavior. Finding also revealed that purchase intention significant positively influence online shopping behavior. For future research, sample from working adults and other variables that related to online shopping were to be included to minimise sampling bias.

In this paper, we summarize the human emotion recognition using different set of electroencephalogram (EEG) channels using discrete wavelet transform. An audio-visual induction based protocol has been designed with more dynamic emotional content for inducing discrete emotions (disgust, happy, surprise, fear and neutral). EEG signals are collected using 64 electrodes from 20 subjects and are placed over the entire scalp using International 10-10 system. The raw EEG signals are preprocessed using Surface Laplacian (SL) filtering method and decomposed into three different frequency bands (alpha, beta and gamma) using Discrete Wavelet Transform (DWT). We have used “db4” wavelet function for deriving a set of conventional and modified energy based features from the EEG signals for classifying emotions. Two simple pattern classification methods, K Nearest Neighbor (KNN) and Linear Discriminant Analysis (LDA) methods are used and their performances are compared for emotional states classification. The experimental results indicate that, one of the proposed features (ALREE) gives the maximum average classification rate of 83.26% using KNN and 75.21% using LDA compared to those of conventional features. Finally, we present the average classification rate and subsets of emotions classification rate of these two different classifiers for justifying the performance of our emotion recognition system.

The coronavirus disease 2019 is a new pandemic that spreads primarily through contact with an infected person when they cough or sneeze. The outbreak of COVID-19 is starting in China then spreading to worldwide that contributes to large number of deaths (40,598 deaths, 1 st April 2020). The COVID-19 is a disease causes respiratory illness with symptoms such as a cough, fever, and in more severe cases, difficulty breathing. To preventing spreading of this pandemic, many countries implementing lockdown procedure to stopping the chain of infection for this new disease. The government-ordered lockdowns have disrupted life for billions and in the same time creates economic collapse scenario. The country with the most COVID-19 infections reported a record surge in unemployment. Therefore, this research calculates the effect of COVID-19 to tourism industry for affected countries in the worldwide. This study evaluated the impact using supply and demand curve to detect the economic changes in tourism industry. The result shows COVID-19 CREATES panic among public that contributes to lower demand in tourism industry. This is one of effect because of disease spreading including lockdown approach that implemented in current situation. This scenario, contributes to lower demand price by customer. Therefore, according to market equilibrium of supply-demand theory, the price of tourism sector is keep decreasing parallel with decrement in demand. The finding of this study is very important to government in preventing and stopping decrement demand in tourism industry. The government need to introduce a mechanism that economy and in the same time developing anti-virus for COVIC-19. If the action of prevention is not mange properly, the tourism industry will face more decremental effects that creates economic collapse.

Natural fibres (NFRs) composite materials are acquiring popularity in the modern world due to their eco-friendliness and superior mechanical properties. Although it has been shown that determining this is a herculean endeavour in the literature, the water absorption (WA) qualities of the natural fibre (NFR) are crucial in the progressive degradation of the features of the resulting composites. This article seeks to report exhaustively on studies pertaining to the WA attributes of polymer composites reinforced with NFRs. This article provides an overview of NFR, its characterization, and the issues related to its addition to the matrix. The primary purpose of this research study is to investigate existing studies on the problems associated with the creation of cellulosic fibre hybrid composites, water absorption, and its impact on the tensile (TS), flexural (FS), and impact strength (IS) of NFR reinforced composites. We reviewed various surface treatments (ST) applied to NFR, including alkali treatment, silane treatment, acetylation, as well as recent advancements aimed at mitigating WA, enhancing hydrophobicity, and improving the interfacial bonding (IB) between NFR and the polymer matrix (PM). Additionally, we assessed the effectiveness of utilizing nanoparticles (NAPs) in specific ST of NFR to minimize water absorption.

Graphene has emerged as the most popular topic in the active research field since graphene's discovery in 2004 by Andrei Geim and Kostya Novoselov.

This tutorial review considers defect chemistry of TiO2 and its solid solutions as well as defect-related properties associated with solar-to-chemical energy conversion, such as Fermi level, bandgap, charge transport and surface active sites. Defect disorder is discussed in terms of defect reactions and the related charge compensation. Defect equilibria are used in derivation of defect diagrams showing the effect of oxygen activity and temperature on the concentration of both ionic and electronic defects. These defect diagrams may be used for imposition of desired semiconducting properties that are needed to maximize the performance of TiO2-based photoelectrodes for the generation of solar hydrogen fuel using photo electrochemical cells (PECs) and photocatalysts for water purification. The performance of the TiO2-based semiconductors is considered in terms of the key performance-related properties (KPPs) that are defect related. It is shown that defect engineering may be applied for optimization of the KPPs in order to achieve optimum performance.

Recent research in the field of Human Computer Interaction aims at recognizing the user's emotional state in order to provide a smooth interface between humans and computers. This would make life easier and can be used in vast applications involving areas such as education, medicine etc. Human emotions can be recognized by several approaches such as gesture, facial images, physiological signals and neuro imaging methods. Most of the researchers have developed user dependent emotion recognition system and achieved maximum classification rate. Very few researchers have tried to develop a user independent system and obtained lower classification rate. Efficient emotion stimulus method, larger data samples and intelligent signal processing techniques are essential for improving the classification rate of the user independent system. In this paper, we present a review on emotion recognition using physiological signals. The various theories on emotion, emotion recognition methodology and the current advancements in emotion research are discussed in subsequent topics. This would provide an insight on the current state of research and its challenges on emotion recognition using physiological signals, so that research can be advanced to obtain better recognition.

ABSTRACT Nanocellulose has received increasing attention in science and industry in recent years as a nanoscale material for the reinforcement of polymer matrix composites due to its superior mechanical properties, renewability, and biodegradability. New nanocellulose sources, modifications, and treatments are under development to reduce the high energy required during production and to create a more suitable industrial‐scale production process. Thus, this paper reviews plant‐based nanocellulose composites and their properties, with a focus on their thermal‐related characteristics. The purpose of this review is to establish for readers the impact of the incorporation of nanocellulose on the thermal and dynamic mechanical properties of nanocellulose composites. Understanding of the thermal properties is important for researchers to assess the suitability of the nanocomposites for a variety of applications in response to new and evolving societal requirements. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137 , 48544.

Abstract Alginate hydrogel beads are widely used as an encapsulation medium for biomedical, bioprocessing, and pharmaceutical applications. The size and shape of the beads are often critically controlled since in many usages the beads are monodisperse in size and spherical in shape. Extrusion dripping is a well‐known method to produce alginate beads. Nevertheless, the production of beads of desired size and spherical shape is often achieved based on one's experience or trial and error. An overview is provided on alginate properties, formulation and preparation of alginate and gelling solutions, production conditions, and post‐production treatment that may influence the bead size and shape. Various methods of bead size and shape measurement are also discussed.

Mercury is a type of hazardous and toxic pollutant that can result in detrimental effects on the environment and human health. This review is aimed at discussing the state-of-the-art progress on the recent developments on the toxicity of mercury and its chemical compounds. More than 210 recent works of literature are covered in this review. It first delineates the types (covering elemental mercury, inorganic mercury compounds, organic mercury compounds), structures, and sources of mercury. It then discusses the pharmacokinetic profile of mercury, molecular mechanisms of mercury toxicity, and clinical manifestation of acute and chronic mercury toxicity to public health. It also elucidates the mercury toxicity to the environment and human health in detail, covering ecotoxicity, neurotoxicity diseases, neurological diseases, genotoxicity and gene regulation, immunogenicity, pregnancy and reproductive system damage, cancer promotion, cardiotoxicity, pulmonary diseases, and renal disease. In order to mitigate the adverse effects of mercury, strategies to overcome mercury toxicity are recommended. Finally, some future perspectives are provided in order to advance this field of research in the future.

Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to calculate the percentage of mistakes in the least square method resulted in a percentage of 9.77% and it was decided that the least square method be worked for time series and trend data.