University of Malaysia, Perlis

The effect of small additions of niobium pentoxide (Nb2O5) from 0 to 0.7 wt% on the zirconia toughened alumina (ZTA) ceramics sintered at 1600 °C was studied. Based on the results, the small addition of Nb2O5 was discovered to be able to significantly influence on phase, microstructure, and mechanical properties of ZTA ceramics. The presence of the secondary phase of Nb2Zr6O17 as a square-shaped particle is confirmed by SEM and FESEM-EDX up to 0.5 weight percent (wt.%) of Nb2O5 additions. The addition of 0.3 wt.% resulted in the highest Vickers hardness value of 1500 Vickers hardness (HV). However, it was found that adding Nb2O5 more than 0.3 wt% causes ZTA's hardness and indentation fracture resistance (KIFR) values to decline from 1500 HV to 1438 HV and 4.88 MPa.√m to 4.18 MPa.√m, respectively. Additionally, it was found that when the amount of Nb2O5 added increased, the value for bulk density climbed while porosity reduced.

Most previously reported susceptors for microwave welding are in powder form. In this study, a thin-film susceptor was employed due to its uniform heating rate and ease of handling. Silicon carbide nanowhisker (SiCNW) were incorporated into a poly(methyl methacrylate) (PMMA) matrix to create a nanocomposite thin film, which served as the susceptor. The microwave welding process involved three straightforward steps: fabrication of the PMMA/SiCNW nanocomposite thin film, application of the nanocomposite film to the target area, and subsequent microwave heating. Upon cooling, a robust microwave-welded joint was formed. The mechanical properties and microstructure of the welded joints were characterized using single-lap shear tests, three-point bending tests, and scanning electron microscopy. Results demonstrated that the shear strength and elastic modulus of the welded joints were optimized with increased heating time and SiCNW filler loading. This optimization is attributed to the formation of a SiCNW-filled polypropylene (PP) nanocomposite layer of increasing thickness at the welded joint interface. However, the incorporation of SiCNW also constrained the mobility of the PP chains, reducing the joint’s flexibility. Furthermore, the welded joint formed with the PMMA/SiCNW nanocomposite thin-film susceptor exhibited an 18.82% improvement in shear strength compared to joints formed with a powdered SiCNW susceptor. This study not only demonstrates the potential of PMMA/SiCNW nanocomposite thin films as efficient susceptors for microwave welding but also paves the way for developing high-performance polymer-based composite joints with improved mechanical properties for applications in the automotive, aerospace, and construction industries.

The present study evaluates moisture induced damage potential using a sessile drop method and a pneumatic adhesion tensile testing instrument (PATTI). The bonding behavior of the aggregates (granite and limestone) and cup lump rubber modified asphalt binder (CMB) with wax-based surfactant (WS) was evaluated. The results revealed that the granite aggregate exhibited a higher work of adhesion compared to the limestone. In the dry condition, the addition of more than 0.15% WS to the CMB reduced the work of adhesion and the bonding strength. Using the sessile drop method, the moisture resistance of the limestone aggregate with the CMB and WS was enhanced, but the bonding strength was reduced. The incorporation of WS reduced the surface free energy (SFE) regardless of the aging conditions and made the aggregate surface more hydrophobic for the increased interfacial adhesion. Incorporating WS in the CMB improved the work of adhesion under the wet condition, thus indicating that WS is an effective anti-stripping agent. Considering its comprehensive properties in the CMB, the amount of WS should be limited to 0.15%.

Xylanase is one of the hydrolytic enzymes with a broad industrial application in several industries. Bioethanol can be synthesised from lignocellulosic biomass by using xylanase and other hydrolytic enzymes. A filamentous fungus, which is Aspergillus niger produces xylanase under submerged fermentation when oil palm empty fruit brunches were used as carbon sources. This study aimed to optimize the operating conditions (medium pH and incubation temperature) of xylanase production process using the OFAT analysis technique. From the data obtained, the highest xylanase production was 0.508 U/mL at pH 5.0 and 0.524 U/mL at an incubation temperature of 32°C, respectively. S. cerevisiae yeast was added into the fermentation supernatant for bioethanol fermentation. The concentration of bioethanol produced by xylanase enzyme from A. niger at optimum operating condition was 15.54±0.47 g/L. This study proved that A. niger is one of the filamentous fungi which show the potential of hydrolysing lignocellulosic material to carbon sources and subsequently to bioethanol production.

Dolomite is a raw carbonate mineral rich in contents with calcium, magnesium and oxide compounds also including other minor impurities from other compounds. It could be easily found in sedimentary rock which is most likely known as dolostone associated with limestone and chalk carbonates. This mineral has been used in a variety of industries including agricultural, metallurgy, constructions, biomass and others. Currently, there are abundant sources of local dolomite minerals but have very limited applications when compared to other types of carbonate minerals. This was contributed by the lack of basic technical information on dolomite properties and no extensive research has been done to evaluate the new potential of this mineral. Therefore, this paper made a brief review on the important characteristics, properties and thermal behavior of dolomite and based on these findings discussed the dolomite's suitability and potential to be used as bioceramics and in biomedical applications.

The antibiotic pollutant treatment in wastewater using conventional method remains a challenge. One of the most fluoroquinolone antibiotics family used by human and animal cure is ciprofloxacin (CIP). CIP has exhibited as a recalcitrant compound in nature with concentration from ng to mg. To overcome this issue, recent technologies have applied such as photocatalysis technology for water decontamination. Furthermore, photocatalyst materials that used in this research were zinc ferrite and graphitic carbon nitride. A simple hydrothermal-coprecipitation method has succeed to synthesis zinc ferrite. While, unexfoliated graphitic carbon nitride (ZFO@ue-CN) was synthesized by calcination at 550 °C for 4 h under air condition. A heterostructure approach combining zinc ferrite and unexfoliated graphitic carbon nitride (ZFO@ue-CN) has been investigated as a potential solution. In this study, a ZFO@ue-CN was constructed by calcination method under atmosphere condition at 400 °C for 2 h. The ZFO@ue-CN has been characterized involving structural, morphological, and optical. Furthermore, ZFO@ue-CN exhibited excellent degradation performance with over 88% removal of ciprofloxacin. The heterojunction formation of ZFO@ue-CN nanocomposite provide more efficient electron transfer compared to single material. Combination between metal oxide@ue-CN can open up the new platform for simple material preparation, nevertheless it can keep the photodegradation performance. This result also emphasizes that the ZFO@ue-CN nanocomposites has prominent application for wastewater treatment.

This study aims to assess the performance of an Additive Manufacturing (AM) machine, specifically a Selective Laser Sintering (SLS) machine, through the design and evaluation of a benchmarking artifact. Drawing from insights gained in previous research, the artifact is meticulously crafted with two distinct materials to explore potential variations in geometric accuracy. The artifact comprises two types: one featuring straight geometries and another incorporating curved elements. The research methodology involves printing both artifact types at default machine settings, followed by precise measurements using a 3D scanner. The inclusion of straight and curved features facilitates a comprehensive examination of the machine’s ability to reproduce diverse geometries. The amalgamation of these features into a combined artifact provides a holistic assessment of the machine’s overall performance. To validate the benchmarking artifact, the final design is reproduced, and its output is compared not only with the original design but also with real-life parts. The results show that flexible polymers offer higher accuracy but lower resolution, while rigid polymers provide better resolution but with a greater number of defects. This comparative analysis serves to highlight the accuracy and reliability of the benchmarking artifact in reflecting the machine’s performance in practical scenarios. In conclusion, this study endeavours to advance the understanding of an SLS machine’s capabilities by leveraging a carefully designed benchmarking artifact.

The development of pharmaceutical formulations typically adopts a lengthy and costly trial-and-error approach, often yielding inaccurate predictions of effectiveness and safety of drug-delivery systems, including hydrogels for antibiotics. Accordingly, machine learning (ML) has emerged as a useful method for predictions based on experimental data. ML can predict a numerical value through numerous supervised models, which are trained and assessed to determine the optimal option. Upon attaining the desired accuracy, the selected model can be applied for prospective predictions and interpreted to extract useful insights. The aim of our study was to apply a hybrid ML approach to predict the release profiles of an antibiotic (silver sulfadiazine) from temperature-responsive hydrogels based on in vitro data. The study explored hydrogel formulations of varying PF-127 and cellulose percentages, temperatures, and drug concentrations. Under this hybrid approach, ML models were investigated alongside different kinetics and mechanisms models. Six ML models—random forest, Gaussian regressor, linear regression, MLP regressor, support vector machine, and kernel ridge—were adopted to predict experimental drug-release data. Model performances were evaluated through the correlation coefficient (R²) and mean absolute percentage error (MAPE). We found that the random forest model exhibited a superior performance, achieving an R² of 0.99 and MAPE 0.002, indicating a robust fit to the data. The release half-life (t50%) increased as temperature rose from 18 to 32 °C, then decreased at 40 °C, while increasing the drug percentage and polymer concentration prolonged t50%. Zero-order and Higuchi kinetic models best fit the data, with non-Fickian diffusion and Super Case II mechanisms dominating. These findings demonstrate the potential of ML to streamline pharmaceutical development, reducing the need for extensive laboratory trials.

The novel coronavirus that caused the epidemic and pandemic resulting in the acute respiratory illness known as coronavirus disease 2019 (COVID-19) has plagued the world. This is unlike other coronavirus outbreaks that have occurred in the past, such as Middle East respiratory syndrome (MERS) or severe acute respiratory syndrome (SARS). COVID-19 has spread more quickly and posed special challenges due to the lack of appropriate treatments and vaccines. Real-time polymerase chain reaction (RTPCR) and rapid antibody tests (surveillance tests) are the two most used tests (confirmation tests). However, the latter takes hours to complete, and the former may produce false positives. Scientists have invested significant effort to create a COVID-19 diagnostic system that is both highly sensitive and reasonably priced. Early detection of COVID-19 is a major area of focus for sensing devices based on nanomaterials. This overview enhanced insights into potential coronavirus biomarkers and, compared to earlier studies, introduced new avenues. Further, it covers the development of COVID-19 diagnostic systems from an analytical point of view, including clinical markers and their subsequent applications with biosensors.

The maximum power delivered by a photovoltaic system is greatly influenced by atmospheric conditions such as irradiation and temperature and by surrounding objects like trees, raindrops, tall buildings, animal droppings, and clouds. The partial shading caused by these surrounding objects and the rapidly changing atmospheric parameters make maximum power point tracking (MPPT) challenging. This paper proposes a hybrid MPPT algorithm that combines the benefits of the salp swarm algorithm (SSA) and hill climbing (HC) techniques. As long as the rate of change of irradiance does not exceed a specific limit, the HC mode is applied to track the global maximum power point (GMPP). Once a high rate of change in irradiation is detected, the SSA mode is activated. Moreover, the proposed algorithm employs the concept of boundary conditions to handle fast and slow fluctuating irradiance patterns. A comprehensive comparative evaluation of the proposed hybrid SSA-HC with state-of-the-art MPPT algorithms has been undertaken. Four distinct cases have been examined, including irradiance conditions with varying rates of change and partial shading conditions. The proposed hybrid SSA-HC algorithm has been validated and tested using a developed hardware setup, simulated in MATLAB for solar photovoltaic (PV) systems, and compared with standard SSA and HC. The performance of the tracking capability of this proposed hybrid technique at both steady-state and dynamic conditions under rapid and gradual irradiance changes demonstrates its superiority over recent state-of-the-art algorithms.

Power Quality Analyzers (PQA) play an important role in monitoring and controlling health of the electrical systems. They can report the fluctuations in the field measurements with different power quality issues as well as due to load variations. Internet of Things (IoT) is a potential technology to design Smart PQAs for remote monitoring and easy integration of the field information on the cloud platform using gateway units. This paper focuses on the development of a Smart PQA system using low-cost IoT hardware and software design solutions. The hardware development is completed using Arduino Mega 2560 microcontroller in combination with ESP32 Wroom Wi-Fi gateway and SIM900A GSM gateway. The real-time field data is gathered at the ThingSpeak platform for future analysis, while GSM-based design ensures timely alerts to the end users for any major fluctuation in the power supply. The performance of the proposed low-cost system has been compared with the readings obtained from FPGA-based conventional PQA and standard Fluke Meter when connected to different loads. The proposed system output values are tabulated and compared using graphs. The proposed system is expected to be useful for the critical assessment, monitoring, and control of power quality parameters in various commercial and residential premises.

On-line commerce through Internet is gaining attention from students today. The aim of this research is to studythe factors influencing student’s buying intention through internet shopping in an institution of higher learning inMalaysia. Several factors such as usefulness, ease of use, compatibility, privacy, security, normative-beliefs andattitude that influence student’s buying intention were analyzed. Respondents who were selected are studying ina public institution of higher learning in Penang, Malaysia. Based on theory of reasoned action (TRA), thetechnology acceptance model (TAM) concluded that there are two salient beliefs which are ease of use andusefulness. This theory has been applied on the study to adopt technology user different and has been emerged asa model in investigation to increase predictive power. Such theory was used in this study to explain students’buying intention on-line. Besides the ease of use and usefulness, others factors such as: compatibility, privacy,security, normative beliefs and self-efficacy are utilized at this TAM. The results support seven hypotheses fromnine. Compatibility, usefulness, ease of use and security has been found to be important predictors towardattitude in on-line shopping.

This study looks at the correlation of the English learning which is by using weblog and the adaptation for international students at Universiti Malaysia Perlis. The study was conducted on the first batch of International students. There were 37 students from three countries with the majority from China followed by Indonesia and Sudan. The students were in the Intensive English Course for nine months which was a pre-requisite before entering into the first year of Bachelor Degree program. The adaptation level is determined using the Sociocultural Adaptation Scale (SCAS) by Searle and Ward (1990). The English proficiency level is determined by using DYNED software. This courseware is designed to help learners acquire the target language in a natural but accelerated mode of learning. The result of the study shows that the students have improved their language competencies after attending the course. Although the language improvements differ individually based on their postings in the blog most of the students show better flow of writing and seemed to be at ease as compared to earlier stages of the course.

This study attempted to identify factors that are affecting business success of small and medium enterprises (SMEs) in Thailand. The intention of this study is to provide the understanding on how people should start their business by looking at all the factors affecting business success hence help to reduce the risk of failure and increase chances of success. The study examined eight factors that influence the SMEs business success. These factors are: SMEs characteristic, management and know-how, products and services, Customer and Market, the way of doing business and cooperation, resources and finance, Strategy, and external environment. The theoretical framework has been drawn out and questionnaire was designed based on the factors chosen. Eight hypotheses were developed to find out factors that are affecting Business Success of SMEs in Thailand. The entire hypotheses were successfully tested with SPSS and five hypotheses were accepted. The regression analysis result shown that the most significant factors affecting business success of SMEs in Thailand were SMEs characteristics, customer and market, the way of doing business, resources and finance, and external environment.

One of Malaysia’s national energy policy’s objectives is to promote efficient utilization of energy and the elimination of wasteful and non-productive patterns of energy consumption. The government wishes to intensify energy efficiency (EE) initiatives in a broad range of areas, including in government buildings. University Malaysia Perlis (UniMAP), a Malaysian public institution of higher learning, has been chosen for an action research in the implementation of an energy efficiency program, in line with the government’s aspiration. This highly populated organization was an ideal selection for an energy consumption and silent waste research. Research objective was to identify areas of possible energy waste within the Campus. To achieve the objective, 2 projects were selected: one was to reduce energy use of chillers and the other was to find if there is any wastage with wrong setting of luminous flux in specific areas. For the first project, the staging method was adopted, where chillers will be loaded with 15 minutes intervals and for the second, luminous flux was set according to government body’s requirement to attain energy saving as initial stage findings showed that luminous flux setting was more than what is required. The results from just these 2 projects demonstrated, that UniMAP was able to save approximately 53,000 kWh of electricity within the research duration. From the preliminary results, it is apparent that more energy wastage analysis within the campus should be carried out in order to maximize potential savings that can be achieved in the future.

Oxidized low-density lipoprotein (oxLDL) is a critical factor in endothelial dysfunction and serves as an important biomarker for oxidative stress. Recent research has focused on lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), a receptor for oxLDL that plays a significant role in atherosclerosis progression. Mutant LOX-1 may show changes in its binding affinity for oxLDL, potentially leading to variations in oxLDL uptake and foam cell formation. Our previous investigation into graphene-based nanomaterials and their interactions with atherosclerosis-related proteins, including LOX-1, provided important insights into their binding characteristics. In this study, we delve deeper into the binding dynamics between graphene-based nanomaterials and mutant LOX-1, aiming to clarify their implications for atherosclerotic development. Using molecular docking techniques with AutodockVina and active site predictions from P2Rank, we evaluated the binding affinities of graphene, graphene oxide (GO), and reduced graphene oxide (rGO) to mutant LOX-1. Notably, all docking scores were below -5 kcal/mol, indicating strong interactions with the receptor. To investigate the dynamics of these interactions further, we performed molecular dynamics (MD) simulations using the CHARMM force field. Our simulations revealed significant conformational changes within the first 100 ns, particularly in the mutant LOX-1 and GO complex, which suggested improved binding stability. These results enhance our understanding of how graphene-based nanomaterials interact with mutant forms of LOX-1, offering potential avenues for targeted therapies in atherosclerosis management related to LOX-1 dysregulation.

Over the years, hundreds of empirical studies have been carried out and theoretical literature written to enhance people’s knowledge towards initial public offering (IPO), IPO underpricing, IPO flipping, IPO short profit, IPO long run underperformances; yet it is arduous for people to clearly understand the various issues related to IPOs especially with different types of equities in different industries and in different markets. The degree of underpricing varies from one issue to another. The degree of underpricing in the Bangladesh capital market is rather high compared to that of other Asian and advanced stock markets. This study analyzes the levels of underpricing in IPOs and its determinants of the Chittagong Stock Exchange (CSE). Key trends in the levels of underpricing and overpricing are highlighted out on a year to year, and industry to industry basis. Out of the 117 companies that were listed in the years 1995 to 2005, 102 (87.18%) IPOs were found to be underpriced, 13 (11.11%) overpriced while only 2 were accurately priced. The overall level of overpricing was 15.37% with a standard deviation of 18.89. Regression Analysis shows that offer size, and size of the company is positively related to the degree of underpricing. The industry type and age of the firm are found to be negatively related to the degree of underpricing. However timing of offer was found to have no significant influence on the degree of underpricing of IPOs in the Chittagong Stock Exchange.

The aim of this study is to investigate the relationship electronic procurement (e-procurement) adoption behavior and the level of Government e-procurement adoption amongst Small Medium Enterprise (SME) in Malaysia. Data was collected through questionnaires that were distributed by mail and e-mail to 150 SME selected randomly in all SME in Malaysia in various industries which are listed in Small and Medium Industries Development Corporation Directory (SMIDEC) and registered with electronic government procurement. The data were analyzed using factor analysis, reliability analysis, independent-sample t-test, descriptive statistics, Pearson Correlation and multiple regressions. Regression results reveals that ‘power’, ‘trust’ and ‘value’ have a positive relationship with the level of e-procurement adoption amongst SME in Malaysia. All dimensions, namely; the power of supplier, power of procurement, trust on supplier, trust on information technology, value of implementation system efficiency and value of cost efficiency were also correlated with the level of e-procurement adoption amongst SME. Past studies on e-procurement are beset by problems of buyer-seller relationship perspective. In addition, these studies are skewed towards Government-SME relationship perspective which the Government possesses more power than SME and provide a better incentive to educate and influence SME to adopt e-procurement. In investigation the relationship between a model of e-procurement adoption behavior and the level of Government e-procurement adoption amongst SME in Malaysia, this study also tries to provides recommendation to Malaysian government for improving the level of e-procurement adoption amongst SME. Keyword(s): Government procurement, Communication technologies, electronic procurement and