Remanufacturing is a way for product recovery initiative and maintaining sufficient production flow to satisfy customer demand through circular economy. Recently, manufacturers have been progressively incorporating remanufacturing processes, making their supply chain vulnerable to disruptions. Among the disruptions that usually occur is the shortage in spare parts supply, which causes unexpected delay in production and possible loss of sales. In the face of potential disruption, it is essential for remanufacturing facilities to manage their supply chains in an optimum manner as to decrease the adverse impact of disruptions to their business. In this study, a two-stage production-inventory system is analysed by developing a cost-minimisation model focusing on the recovery schedule after a disruption occurrence in sourcing spare parts for a remanufacturer’s production cycle. The developed model was solved using the branch and bound algorithm. Through numerical experiments, the results indicate that the optimal recovery schedule and the number of recovery cycles are significantly dependant on disruption time, lost sales and backorder costs. Moreover, a sensitivity analysis shows that the lost sales option seems to be more effective than the backorder option in optimising the system’s overall cost. The proposed model could assist managers in deciding the optimal production strategy while providing interesting managerial insights into vital spare parts recovery issues when disruption strikes.

Mechanochemical production of copper (II) isonicotinate Metal-Organic Framework ([Cu (INA)2]-MOF) and its modified magnetic iron composite ([Cu (INA)2]-MOF@Fe3O4]) allowed for the adsorptive removal of Terbutaline from water. A variety of characterization techniques, including Fourier, transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and scanning electron microscopy (SEM), were used to elucidate the distinct chemical and morphological features of the two advanced materials. The optimal adsorption conditions were determined by investigating a wide range of adsorption-related variables, including contact time, initial Terbutaline concentration, adsorbent dosages pH, and temperature. The chemistry involved in the adsorption process between the adsorbents and the adsorbate molecules was evaluated using the best-fitting models, such as kinetics, isotherms, and thermodynamics, and the regeneration study was performed to evaluate the adsorbents' reusability. Incredibly maximum adsorption capacities (Qmax) of 1667 and 2500 mg L-1 were attained within 40 minutes under alkaline pH 11 by the [Cu (INA)2]-MOF and the [Cu (INA)2]-MOF@Fe3O4, respectively. The adsorbents have been proven to be good for the adsorption of Terbutaline as a priority pollutant in an aqueous solution, with pseudo-first order and Langmuir as the best-fitting models for the kinetic and isotherm models respectively.

Computer vision is a fast-expanding discipline focusing on analyzing, altering, and comprehending images at a high level. Its goal is to figure out what's going on in front of a camera and use that knowledge to manage a computer or robotic system or to show people new visuals that are more instructive or attractive than the original camera photos. Video surveillance, biometrics, automotive, photography, movie production, Web search, medicine, augmented reality gaming, new user interfaces, and many other applications are all possible with computer vision technologies. This paper aims to describe how computer vision will be used to play a winning game of blackjack.

Coating of suitable materials having thickness of few atoms to several microns on a substrate is of great interest to the scientific community. Hard coatings develop under the significant composition of suitable-natured atoms where their force-energy behaviors when in certain transition state favour binding. In the binding mechanism of suitable atoms, electron belonging to outer ring filled state of gas-atom undertakes another clamp of energy knot belonging to outer ring unfilled state of solid-atom. Set process conditions develop the binding of different-natured atoms when processing their suitable composition in a system. Atoms of different nature develop structure in the form of hard coating by locating their ground points between the original ones. Here, gas-natured atoms increase the potential energy under decreasing levitational force of electrons, whereas, solid-natured atoms decrease the potential energy under decreasing gravitational force of electrons. In TiN coating, Ti–Ti atoms bind under the difference of expansion of their lattices, called nets of energy knots, where one atom just lands on the already landed atom. An adhered N-atom to a Ti-atom forms its position among four Ti-atoms where N-atom occupies the interstitial site of Ti-atoms. Two oppositely working force-energy behavior atoms deposit in the form of coating at substrate surface as per set conditions of the process. The rate of ejecting (or dissociating) solid-natured atoms depend on the nature of their source (target), process parameters and processing technique. In random arc-based vapor deposition system, depositing differently natured atoms at substrate surface depends on the input power. In addition to intrinsic nature of atoms, different properties and characteristics of coatings emerge as per engaged forces under their involved energy. The present study sets new trends in the field of coatings involving the diversified class of materials and their counterparts.

Election Algorithm (EA) is a powerful metaheuristics model motivated by phenomena of the socio-political mechanism of the presidential election conducted in many countries. EA is selected as a topic of discussion due to its capability and robustness to carry out complex problems in the random-2SAT logic program. This paper utilizes a hybridized EA assimilated with the Hopfield neural network (HNN) in carrying out random logic program (HNN-R2SATEA). The efficiency of the proposed method was compared with the existing traditional exhaustive search (HNN-R2SATES) model and the recently introduced HNN-R2SATICA model. From the result obtained, clearly proven that based on our proposed hybrid model outperformed other existing model based on the Global Minima Ratio (ZM), Mean Absolute Error (MAE), Bayesian Information Criterion (BIC) and Execution Time (ET). The expected outcome portrays that the EA algorithm outperformed the other two algorithms in doing random-kSAT logic program. The results proved the robustness, effectiveness, and compatibility of the HNN-R2SATEA model.

Purpose: For businesses of all sizes, turnover is a significant issue that has a detrimental impact on organizational performance. This study investigates the variables influencing SME workers' intentions to leave their current employers. This study also examines the moderating effect of organizational commitment on the relationships between attitude, subjective norms, perceived behavioral control, and turnover intentions. Methodology: Six hypotheses were proposed regarding the connections between the initial TPB components and organizational commitment. Results: The PLS-SEM structural path analysis findings revealed that the three fundamental predictors of TPB significantly influence turnover intention, with perceived behavioral control most strongly influencing intention. Furthermore, the results revealed that organizational commitment moderated the relationship between TPB constructs and turnover intention. Practical Implications and Originality: This study used an extended TPB model to introduce fresh perspectives into the literature on SME workers' organizational commitment.

In its 8th Malaysia Plan (MP*), the Malaysian government has given nanotechnology development a high priority and has been made a Strategic Research (SR) programme. Consequently, an exhaustive and long-term approach is essential. Additionally, specific laws are required to provide an optimal health and safety environment for workers. Consequently, the current study intends to assist Malaysian policymakers in promoting improved safety, risk assessment, and management for nanotechnology workplaces, as well as drafting a comprehensive policy for the recently released DOSH guideline in 2018. Utilizing a unique methodology, this study evaluated the assessment and management of nanotechnology health and safety risks in Malaysia using the international risk governance council (IRGC) framework. In addition to document analysis, n = 20 semi-structured interviews were conducted with representatives of several nanotechnology platforms to collect data that was then analyzed thematically. The research evaluated current workplace safety regulations and laws. Consequently, we propose a future dynamic strategy for Malaysian nanotechnology with more favourable upgrades supported by increased concentrations in the following areas: I policy creation, ii) comprehensive management system, iii) knowledge transfer, and iv) infrastructure management. In addition, the findings highlight the need of cross-sectional communication in bridging existing gaps. This study laid the groundwork for a more systematic and comprehensive health and safety strategy.

With global climate change and resource constraints looming large, sustainable design has become a focus of attention for all industries. The purpose of this study was to investigate the attitudes and behavioural intentions of undergraduate fashion design students towards sustainable fashion practices. Undergraduate fashion design students (n = 441) from three universities in Guangdong Province, China, participated in this survey. By constructing different scales of environmental knowledge, attitude towards sustainable fashion practice and behavioural intention towards sustainable fashion practice, and by using structural equation modelling to analyse the relationship between environmental knowledge and sustainable fashion practice, the following conclusions were drawn: (1) environmental knowledge has a positive effect on attitude towards sustainable fashion practice (p＜0.05); (2) environmental knowledge has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05); (3) Subjective norms has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05). (4) Attitudes towards sustainable fashion practice play a mediating role in the relationship between environmental knowledge and intentions towards sustainable fashion practice behaviour (p＜0.05). The findings of this study have implications for environmental education for undergraduate fashion design students and for sustainable production in companies.

A sustainable, scalable source of energy‐dense chemical fuel is urgently needed to ensure the security of our energy supply for future generations. Solar energy is the only renewable energy source of sufficient scale to replace fossil fuels and meet rising environmental demand. Hydrogen is expected to play a key role as an energy carrier in future energy systems of the world. As fossil fuel supplies become scarcer and environmental concerns increase, hydrogen is likely to become an increasingly important chemical energy carrier and eventually may become the principal chemical energy carrier. When most of the world’s energy sources become non-fossil based, hydrogen and electricity are expected to be the two dominant energy carriers for the provision of end-use services. Photocatalytic hydrogen evolution from water by solar energy over semiconductors offers a promising way for clean and renewable production of hydrogen. The TiO2-based materials have received considerable attention in recent years due to their extensive application in photocatalysis for hydrogen evolution. Though TiO2 is the most widely investigated photocatalyst for hydrogen evolution, it still provides low photocatalytic activity due to the wide bandgap that results in photocatalytic activity only under ultraviolet (UV) irradiation. Modification of TiO2 photocatalysts with several transition metals has been extensively studied to extend the absorbance capacity of TiO2 into the visible range. The effect of different photocatalytic deposition and reaction parameters also play major roles in enhancing the photostability of photoanode and increasing the hydrogen gas output, respectively.

Bioconvective flows have attracted attention in recent years due to actual and potential applications. In this paper, we consider a steady and laminar convective MHD flow of a nanofluid with heat, mass and microorganism transfer with a heat source/sink present. In addition, we assume there exists a first order chemical reaction. The governing partial differential equations (PDEs) are reduced to ordinary differential equations (ODEs) using the scaling group transformation and the associated boundary value problem is then solved. The influences of selected governing parameters on the dimensionless velocity, temperature, nanoparticle concentration, density of motile microorganisms, skin friction, heat transfer, mass transfer, and motile microorganism density rates are computed and discussed

Joining of aluminium alloys to steels has been extensively studied, especially in the automotive sector. However, aluminium alloys are known to be difficult to join with steels when methods involving fusion welding are used because of hot cracking problem. Hence, a high strength joint between these dissimilar metals would be of benefit especially in reducing the weight of products. In this work the torch brazing method was applied to join AR500 steel with AA7075 aluminium alloy using Al-Si-Zn base filler metal at various flame times. The effect of the brazing work on the intermetallic phase formation and the mechanical strength of the joints were investigated. In this work, the maximum shear load obtained was 6460 N and the presence of the intermetallic phases had reduced the shear strength of the brazed joints. However, the torch brazing process using Al-Si-Zn filler metal had successfully facilitated the joining of these dissimilar metals.

A biofilm is any syntrophic consortium of microorganisms in which cells adhere to one another and, in some cases, to a surface. These adherent cells become encased in a slimy extracellular matrix made up of extracellular polymeric substances (EPSs). Until now, the use of commercial disinfectants remains the main strategy to control biofilm-mediated problems. This mini review summarizes common antibiofilm mode of actions taken by disinfectants and how water channels in microbial biofilms contribute to disinfectant resistance.

The development of quantum computers seeks software developers' attention regarding security in the era of Information Technology, software security is the primary goal for our quantitative assessment of software security in the development cycle of software. Security assessment of software is identifying the key security factors of the software. A security elective provides ex-tensive strategies and calculations to ensure product safety. The security assessment is the key factor in surveying, administering, and controlling security to further enhance the nature of safety. It should be acknowledged that assessing security early on in the development process is beneficial in identifying worms, hazards, flaws, and threats. The definition and portrayal of Quantum Computing (QC) in software security will be discussed in this study. Researchers use cryptography calculations to secure our financial institutions, medical devices, military weaponry, planes, ships, vehicles, and pilots. Here authors of this study use the Fuzzy Technique for Order Preference by Similarity to Ideal Situation (FTOPSIS) to quantitatively assess the weight/rank of the quantum enable security alternatives like (Diffie-Hellman key-exchange algorithm, Quantum key distribution algorithm, Deutsch-Jozsa Algorithm, Special Deutsch-Jozsa Algorithm, Grover’s Algorithm and Quantum key distribution algorithm in GHZ state) with security factors like (Confidentiality, Integrity, Authenti-cation, Privacy, Reliability, Maintainability, Authorization, Integrity, Possessions, and Availability). Additionally, they critically analyze and select the six alternatives of quantum-based security algorithms. The nature of safety infers the ability to execute a thing on time in this exploration study, specifically 'software security'.

The Ranau Earthquake that struck on 5, June 2015 and follow by February 2018 and April 2021, were a new disaster in Sabah and caused many Sabahan to panic. The unpredicted disaster also caused a serious impact on all aspects of life in Sabah. The earthquake has caused severe damage to eight primary schools in the vicinity of the epicenter; although no casualties were reported. However, the disaster has passing deep psychological effects among students. In this study, we examine how the primary school teachers enabled the student to be resilient during and after the disaster. Based on the interviews of 16 primary school students it was revealed that most of the teachers used WhatsApp to support resilience during and after the earthquake. Interviews with 16 primary school teachers revealed there were two main reasons for them to communicate with students namely, delivering emotional aid and monitoring their stress. Based on student interviews, five content categories of emotional support were identified: caring, reassuring, emotion sharing, belonging, and distracting. The main contribution of this study is social media can be used as a spontaneously and proactive tool to support student's resilience during and after the earthquake trauma.

Nanofibres have gained increasing attention due to their advantages of having a high porous structure, narrow pore size and distribution, and a high specific surface area. One of the most efficient techniques for producing nanofibres is via electrospinning. Nanofibres are currently being used in various fields, including water filtration. Although nanofibres possess the ability to filter various components, the fibres generally have a low mechanical strength that can mitigate the performance over time. Therefore, in overcoming this issue, several studies have focused on improving the strength of the nanofibre membranes for a water filtration application. This review discusses the advantages and challenges of nanofibres for water filtration membranes and summarises the methods to increase the strength of the membranes, including solvent vapour, thermal treatment, and chemical crosslinking.

Electrification coverage in Sarawak is the lowest at 78.74%, compared to Peninsular Malaysia at 99.62% and Sabah at 82.51%. Kapit, Sarawak with its 88.4% populations located in rural areas and mostly situated along the main riverbanks has great potential to generate electrical energy by hydrokinetic system. Yearly water velocity data is the most significant parameter to perform hydrokinetic analysis study. Nevertheless, the data retrieved from local river databases are inadequate for river energy analysis, thus hindering its progression. Instead, flow rates and rainfall data had been utilised to estimate the water velocity data. This signifies no estimation of water velocity in an unregulated river by using water level data had been made. Therefore, a novel technique of estimating the daily average water velocity data in unregulated rivers is proposed. The modelling of regression equation for water velocity estimation was performed and two regression model equations were generated to estimate both water level and water velocity on-site and proven to be valid as the coefficient of determination values had been R² = 87.4% and R²=87.9%, respectively. The combination of both regression model equations can be used to estimate long-term time series water velocity data for type-C unregulated river in remote areas.

Differentiated instruction has been implemented in classrooms where students who come from various backgrounds require appropriate lessons that are tailored to their varied learning preferences. As the spread of coronavirus 19 (Covid-19) is becoming more rampant, online learning has been lifted up as the main platform of teaching and learning, forcing the need to shift from the conventional face-to-face classroom to online, or virtual, mode of knowledge transfer. Having such global phenomenon affecting education, how does it affect the implementation of differentiated instruction that has been practised regularly by teachers before the wake of Covid-19? Previous studies have shown how it is done in the normal classroom setting, and that the practice of differentiated instruction contributes to students’ motivation as well as academic performance. However, there is a need to explore how do teachers go about with online differentiated instruction and how does it affect the students, since online learning poses various threads to both teachers and students; and thus, one might argue the effectiveness of not only the teaching approach but also the overall teaching and learning outcomes. Borg’s framework of teacher cognition, which has been extensively used in exploring how teachers teach, can be utilized to document the practice of online differentiated instruction. This study aimed to explore the practice of online differentiated instruction by teachers and examined its impact on students’ motivation and academic performance during the Covid-19 outbreak. The participants of this study consists of 247 gifted students from a public school in Malaysia. To meet these aims, this study employed a mixed method research design, utilizing the framework of teacher cognition to explore the teachers’ practice of online differentiated through interviews; and, utilizing a survey design using a questionnaire to determine the impact of online differentiated instruction towards students’ motivation and academic performance. The findings revealed that although online differentiated instruction is feasible, however, appropriate combination of differentiation constructs need to be applied in order to achieve higher motivation and better academic performance among the students.

Populaces are prominent indicators of livability in creating ‘street life’ for cities and public spaces. Evaluating people’s experiences is significant in creating a city liveliness and urban heritage trail. The exploration of design strategies that could allow them to integrated and connected with other spaces in the context of city and heritage as well as creating a social life among them. The measuring variables are people’s experience on the spaces; thus, create the pattern of behavior, which cause spaces liveliness, using Kuala Lumpur Heritage Trail as an example of pedestrian priority streets, city environment and heritage value. The aim of this research is to evaluate people’s experiences and analyze their behavior towards the urban street design within cities environment and Malaysia heritage values. The analyzed review comprising on the livability of the street in the context of interrelation between behavioral patter of people and the preferences of urban heritage. Hence, this paper will give an understanding of how people experiences the presence of urban streets and heritage values, thus, bringing liveliness to the streets.

Global waste generation keeps increasing over the year and requires innovative solutions to minimize their impacts on environmental quality and public health. Predicted 2.2 billion tonnes per year of global municipal waste generation in the year 2025 which 1.6 fold is higher than in 2012. Hence, a strategic plan must be ascertained to overcome the future challenges of MSW locally and globally. Universiti Putra Malaysia (UPM) coined an initiative to demonstrate a showcase pilot plant for green energy production from MSW. Therefore, the data was obtained from the survey and actual sampling within the UPM compound to estimate the MSW generated and it's potentially used for green energy production. It is estimated that 5.0 – 7.0 tonne per day of MSW generated which about 30 - 35% is an organic fraction. Upon separation, the organic fractions were digested into biogas through anaerobic. At the maximum conversion of organic fraction, about 775 kWh of electricity may able to generate from the waste. In this study, the complete biorefinery setup and utilize organic components from the MSW generated in UPM was proposed that the biogas subsequently will be used to produce green energy in the form of electricity or cooking fuel.

Assessment of the trends of land cover and vegetation dynamics (VD) using remote sensing (RS) and indicators such as anthropogenic activities and the socio-demographic information is essential in order to make proper planning for sustainable management. This paper attempts to evaluate land cover change (LCC) and VD in Kebbi State, Nigeria using historical Landsat data from 1986-2016 by means of remote sensing. The Driver-Pressure-State-Impact-Response (DPSIR) framework was later employed using both primary and secondary data for a better understanding of the drivers, the state of the environmental condition, the causes as well as the impact of the change. The images were classified into five thematic land cover classes as Dense Vegetation, shrubs/built area, farmland, bare/grassland and water body by means of Maximum likelihood supervised classification technique in accordance with Anderson classification scheme level 1, with acceptable accuracy. Pre-classification and post-classification change detection (CD) methodologies were executed using Normalized difference vegetation index (NDVI) and Image differencing respectively. The study illustrates a steady decline in dense vegetation and shrubs/build areas while farmland and bare/grassland increases, however, water bodies remain unchanged. The DPSIR pin-point that the major drivers of change in the study area have been the pressing need for farming land as the population grows and socioeconomic demands including fuelwood consumption and endemic poverty. Expansion of Farming land, fuelwood consumption and the need for construction materials are identified as the main key elements exerting pressure for the change. The state of the condition indicates a steady decline in dense vegetation and shrubs areas while farmland and bare/grassland are increasing significantly. The impacts include land degradation, the decline in the provision ecosystem goods and services, biodiversity loss through loss of habitats. The study, however, noted that many international and national policies in response to land degradation are channelled toward land restoration and remediating of the environment, through afforestation programs and improving the livelihood of the rural people through providing alternative income sources since they depend heavily on land for sustenance. However, the state governments, communities and individual commonly organized annual tree planting campaign with the main purpose of environmental protection.

The integration of artificial intelligence (AI) into academic settings in Sabah, Malaysia, is transforming education and research landscapes. While AI technologies promise to enhance teaching, learning, and scholarly activities, they also pose challenges such as ethical concerns and skill gaps among academic staff. This study addresses the multifaceted impacts of AI adoption on academicians in Sabah, focusing on two key research questions: the impact of AI-based intelligent tutoring systems on student engagement, learning outcomes, and educational equity, and the challenges and opportunities in building academicians' capacity to integrate AI technologies effectively. Through a multidisciplinary approach, incorporating insights from education, computer science, social sciences, and ethics, this research aims to evaluate the effectiveness of AI tools in educational settings and identify strategies for skill development and infrastructure support. The study recommends empirical assessments within Sabah's educational institutions, considering contextual factors and fostering collaborative partnerships with local communities. Professional development programs, collaboration with industry partners, and improved access to AI infrastructure are proposed strategies. Longitudinal studies and interdisciplinary research initiatives are suggested for future research, along with qualitative methods to capture diverse perspectives. Ultimately, by embracing a collaborative and multidisciplinary approach, Sabah's academic community can harness the transformative potential of AI to advance education, research, and scholarship while promoting ethical and inclusive practices.

Moringa oleifera is a miracle plant with many nutritional and medicinal properties. Chemopreventive value of the combined mixture of moringa leaves and seed residues (MOLSr) at different ratios (M1S9, M1S1 and M9S1) were investigated. MOLSr extracts were subjected to phytochemical screening, antioxidant assays, metabolite profiling and cytotoxic activity on various human cancer cell lines including primary mammary epithelial cells (PMEC). The MOLSr ratio with the most potent antiproliferative activities were used in xenograft mice injected with MDA-MB-231 cell lines for in vivo tumourigenicity study as well as protein and gene expression studies. M1S9, specifically comprised of saponin and amino acid, retained the lowest antioxidant activity and highest glucosinolates content as compared to other ratios. Cell viability decreased significantly in MCF-7 breast cancer cells and PMEC after treatment with M1S9. Solid tumour from MDA-MB-231 xenograft mice was inhibited up to 64.5% at third week after treatment with high-dose M1S9. High-dose M1S9 significantly decreased the expression of calcineurin (CaN) and vascular endothelial cell growth factor (VEGF) proteins as well as the secreted frizzled-related protein 1 (SFRP1) and solute carrier family 39 member 6 (SLC39A6) genes. This study provides new scientific evidence for the chemoprevention properties of MOLSr in breast cancer model.

In this study, the effects of music therapy on anxiety for patients undergoing regional anaesthesia in an operating room was succinctly investigated. This investigation was largely based on the adapted Hospital Anxiety and Depression Score (HADS) and Spielberger State-Trait Anxiety Inventory (STAI-S), of patients undergoing regional anaesthesia in an operating room. A randomized control trial was performed on 90 patients due for surgery. The selected patients for regional anaesthesia were allocated to either the music therapy group who listened to music using headphones for the entire surgery or the no-treatment control group. Based on the findings, it has been conclusively demonstrated that music can decrease the patient's anxiety level. According to the socio-demographic evaluation, elderly patients have the highest stress hormones levels when compared to young patients. Although elderly patients are more likely to choose religious songs to help them relax, cortisol analysis revealed an increase in cortisol levels among the elderly compared with younger patients. As a result, music is especially important to be delivered to elderly patients. Nonetheless, there is no restriction against administering music to elderly patients because evidence from the Hospital Anxiety and Depression Score (HADS) and State-Trait Anxiety Inventory (STAI-S) has shown that music helps to shift their attention away from pain and complications and makes them feel tranquil. Similarly, the HADS and modified Spielberger STAI (STAI-S) analyses demonstrate a substantial outcome for both groups, with respondents responding positively. The study found that listening to music during regional anaesthesia might help people feel less worried.

Abstract: The effect of some weather parameters (rainfall and temperature) on the production of oil palm in Peninsular Malaysia was investigated. Data were analysed using the Statistical Package for Social Sciences (SPSS 20.0 version), with descriptive statistics, time series analysis, and multiple linear regression (MLR) carried out. SPSS and Microsoft Excel 2010 were used to analyse the results. The MLR model determined the strength of the relationship between oil palm yield (dependent variable) and the changing variables of temperature and rainfall (independent variables). The regression output returned three components; regression coefficients, regression statistics and ANOVA. The findings of the study revealed medium to high rainfall variability at the rate of 0.0008. This implies that rainfall is increasing over time with variations in its amount and intensity. As rainfall increases oil palm FFB production is predicted to increase at a slow rate of 0.0009. The estimation of average annual temperature indicated an increase of 5.6℃ at the rate of 0.0357℃ per year with a temperature maximum of 32.01℃ and minimum of 25.45℃. The result also revealed an increase in oil palm yield at the rate of 0.2581 per year with a mean value of 176247.6. Overall, there is a significant difference in the impact of rainfall and temperature on oil palm yield. This signifies that rainfall has a significant impact on oil palm yield (FFB) compared to temperature.

Computer vision is a rapidly developing field that focuses on highly sophisticated picture analysis, manipulation, and comprehension. Its objective is to analyze what is happening in front of a camera and utilize that understanding to control a computer or robotic system or to present users with fresh visuals that are more enlightening or appealing than the original camera images. Computer vision technologies make it feasible for new user interfaces, augmented reality gaming, biometrics, automobile, photography, movie creation, Web search, and many more applications. This essay seeks to explain how computer vision can be utilized to play blackjack successfully.

The new emergence and re-emergence of arbovirus infections vectored by Aedes mosquitoes have been spread across Southeast Asia, Central Africa, United States, tropical Oceania and become a major of public health concerns. These arbovirus diseases found to have a similar vector, symptoms of the diseases and environments. The situation has become complicated without any specific vaccine or treatment for the diseases. As far as we concern, vector control is the best defense with many challenges, a scattered breeding site and biological behavioral sometimes, more difficult to control. Herein, we present a review of studies on current techniques proposed to combat arbovirus infections vectored by Aedes mosquitoes. A crucial gap in a vector control program is the inability to eliminate and destroy the cryptic breeding site by using conventional control methods. The idea and proper concept of using mosquitoes to bring insecticide to their oviposition site had been getting more interest in people to explore. Autodissemination is a self-delivery technique by manipulating the behavior of mosquitoes, carrying the insecticide and disseminate to cryptic breeding sites. This technique has shown a promising result in some countries and can be considered as additional tools in a vector control program

Extensive research has been conducted on printable antenna technologies, believed to be fast-growing due to their significant impact on wireless devices. It is necessary to study the progress of printable antenna technology as they are core devices for wireless technology today. This review work offers a comprehensive account of the previous and recent research achievements based on the principle of printable antenna, and parametric studies of several key design parameters, for future wireless network applications. The systems considered for evaluation include broadband techniques, large Bandwidth, high gain, dual/multi-band, or reconfigurable structure, low-profile, size-reduction, compact, linear, or circular polarization applications. It also highlights the fabrication procedures, and the numerous material characteristics affecting the antenna performance for various wireless applications with design considerations. Fully printed antennas on different substrates and conductive ink were investigated, including polyethylene terephthalate (PET), synthetic paper (Teslin), resin-coated photo paper, and Kapton polyimide substrates, among many others. The findings show that the fully inkjet-printed antenna made fabrication easy, improving the accuracy and conductivity of the printed patterns by concentrating on the inherently difficult problems and opportunities. Inkjet-printed antennas are believed to be the futuristic demand for sustainability and wireless solution in several ways.

Abstract: Heavy metals (HMs) contamination is one of the main among abiotic factors affecting crop productivity and also threatens human health via consuming metal contaminated crops as a food source. Over the past few years, HMs have drawn a lot of attention due to their increased use for commercial purposes and their harmful effects on plants and other life forms, thus threatening human survival. However, in recent years, several methods have been adopted to combat the harsh effects of HMs. After phytohormones, use of mineral nutrients such as selenium (Se) in the prevention of HM stress has been explored by the researchers more recently. Selenium is an important micronutrient widely known for its antioxidant properties in both plants and animals. Exogenous Se inhibits metal uptake and its translocation and also improves the antioxidant system, thus imparts resistance to HM toxicity in plants. Moreover, Se also regulates the production of various osmolytes in cells that helps in developing cell osmolarity. Selenium also induces the production of different types of secondary metabolites (SMs) that are also involved in plant's secondary defense mechanisms to different stresses. Uptake of mineral nutrients is a vital process for plant growth and development, which is also positively correlated with Se under metalloid toxicity. However, in order to understand the exact mechanism of Se in HM tolerance, different metabolic processes stimulated by Se and their pathways need to be explored. Hence, this review focuses on the role of Se on nutritional status, antioxidants metabolism, interaction with phytohormones and its role in the regulation of various genes involved in Se induced HM tolerance. Thus, this study will help researchers in the future for the improvement of HM tolerance via Se application in plants.

Heavy metals pollution in the Straits of Malacca warrants the development of rapid, simple and sensitive assays. Enzyme-based assays are excellent preliminary screening tool with near real-time potential. The heavy-metal assay based on the protease ficin was optimized for mercury detection using Response Surface Methodology. The inhibitive assay is based on ficin action on the substrate casein and residual casein is determined using the Coomassie dye-binding assay. Heavy metals strongly inhibit the hydrolysis. A Central Composite Design (CCD) was utilized to optimize detection. The results show a marked improvement for the concentration causing 50% inhibition (IC50) for mercury, silver and copper. Compared to One-factor-at-a-time (OFAT) optimization, RSM gave an improvement of IC50 from 0.060 (95% CI, 0.0300.080) to 0.017 (95% CI, 0.0160.019), from 0.098 (95% CI, 0.0770.127) to 0.028 (95% CI, 0.0220.037) and from 0.040 (95% CI, 0.035.045) to 0.023 (95% CI, 0.0200.027), for mercury, silver and copper, respectively. A near real-time monitoring of mercury concentration in the Straits of Malacca at one location in Port Klang was carried out over a 4-h interval for a total of 24 h and validated by instrumental analysis with the result revealing an absence of mercury pollution in the sampling site.

Ag/TiO₂ thin films were prepared using the sol-gel spin coating method. The microstructural growth behaviors of the prepared Ag/TiO2 thin films were elucidated using real-time synchrotron radiation imaging, its structure determined using grazing incidence X-ray diffraction (GIXRD), its morphology imaged using the field emission scanning electron microscopy (FESEM), and its surface topography examined using the atomic force microscope (AFM) in contact mode. Cubical white spots were detected, identified as Ag, while the TiO₂ thin film resembles a porous ring-like structure with each ring coalescing and forming channels. Junction growth is directly proportional with time under continuous heating conditions (annealing), and its growth orientations and patterns were seemingly random.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women, characterized by fluid-filled sacs in the ovaries and various symptoms including high androgen levels, endometrial irregularities, and cysts. While the cause of PCOS is unknown, it has been linked to genetic, endocrine, and metabolic factors, and there are several treatment options, including lifestyle modifications, medications, and surgery. Natural products, such as medicinal plants and fruits, are being explored as potential treatments for PCOS due to their bioactive compounds with pharmacological effects related to antioxidant, antimicrobial, anticancer, and antidiabetic properties. Some of these compounds improve insulin sensitivity, reduce inflammation, and enhance glucose metabolism, which is beneficial for women with PCOS. This review examined the effects of natural products on PCOS, including their effects on ovarian histological changes, blood glucose, sex hormones, and lipid profile, based on animal and human studies. This study suggests that the use of natural products as complementary medicine can be a promising resource for the development of effective therapeutics for PCOS, but that further research is needed to fully understand their benefits

Exploring new approaches to innovating higher vocational education is a worldwide pursuit driven by the increasing demand for graduates equipped with competencies. This study investigated how Outcomes-Based Education (OBE) influences the attainment of graduate competence (AGC) in China’s higher vocational education, using the theory of Constructive Alignment (CA) as its foundation. The OBE framework incorporates intended learning outcomes (ILOs), project-based learning (PjBL), assessment strategies (ASs), and AGC. The study tested the model by assessing the impact of ILOs, PjBL, and ASs on AGC, respectively and sequentially. Surveys were administered to 320 CBEC learners in April 2024, resulting in 301 usable responses. Data were analyzed using structural equation modeling (SEM) with SPSS 23.0 and AMOS 24.0. Results indicated that PjBL and ASs were directly and positively related to graduate competency attainment, while ILOs were indirectly associated with graduate competence through the mediating roles of PjBL and ASs. The most substantial mediating effect between ILOs and graduate competence was ASs, followed by PjBL, and then, the chain mediating effect of PjBL and ASs. These findings enhance the theoretical understanding of OBE and provide detailed procedures for tracking and enhancing sustainability in higher vocational education. Beneficiaries include educators, policymakers, and accreditation bodies.

Crop digital twin is redefining traditional farming practices, offering unprecedented opportunities for real-time monitoring, predictive and simulation analysis, and optimization. This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and regression algorithms to create a digital twin for augmenting farmers the concentration and composition prediction-based crop nutrient recovery. This captures the holistic representation of crop characteristics, considering the intricate relationships between environmental factors, nutrient concentrations, and crop compositions. However, the complexity arising from diverse soil and environmental conditions makes nutrient content analysis expensive and time-consuming. This paper presents the result of a predictive digital twin case study that employs six regression algorithms namely Elastic Net, Polynomial, Stepwise, Ridge, Lasso, and Linear Regression to predict rice nutrient content efficiently, particularly considering the coexistence and composition of multiple nutrients. Our research findings highlight the superiority of the Polynomial Regression model in predicting nutrient content, with a specific focus on accurate nitrogen percentage prediction. This insight can be used for nutrient recovery intervention by knowing the precise amount of nutrient to be added into the crop medium. The adoption of the Polynomial Regression model offers a valuable tool for nutrient management practices in the crop digital twin, potentially resulting in higher-quality rice production and a reduced environmental impact. The proposed method can be replicable in other low-resourced crop digital twin system.

The rural road landscape is crucial in forming rural areas' landscape character (LC). As a platform for portraying the rural landscape, the rural roads demonstrate the area's unique natural and cultural characteristics to the visitors. However, with the continuous development of rural areas, the rural LC has been severely impacted, thus impacting visitors' visual experience. In order to preserve and protect the rural landscape, this study aims to assess the visual quality of rural road landscapes based on public preference and heatmap analysis. The results indicated that most of the participants had a higher level of preference for rural landscapes with open horizontal views represented by agricultural areas such as paddy fields. It was also found that different paddy field characters based on their planting stages can also positively affect the visual quality of rural road landscapes. The study also revealed that rural LCs with roadside settlements, commercial structures, mixed agricultural crops, and vegetation received low preference ratings. These characters negatively impact the visual quality of the rural road landscape. These findings provide significant insight for planners and decision-makers regarding protecting and preserving the essential rural road landscapes for the rural tourism experience.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

Microalgae are known as a rich source of bioactive compounds which exhibit different biological activities. Increased demand for sustainable biomass for production of important bioactive components with various potential especially therapeutic applications has resulted in noticeable interest in algae. Utilization of microalgae in multiple scopes has been growing in various industries ranging from harnessing renewable energy to exploitation of high-value products. The focuses of this review are on the isolation of bioactive compounds from microalgae regarding different metabolites which are currently used and new possible applications of the compounds in industries and future prospects. Moreover, this work discusses the advantage, potential new beneficial strains, applications, limitations, research gaps and future prospect of microalgae in industry.

Biofilm-associated proteins (BAPs) are important in the development and resilience of biofilms, which are intricate populations of microbes protected by extracellular matrix. All members of the BAP family are known to possess common characteristics such as high molecular weight and a signal sequence for extracellular secretion. It has been shown that BAPs are directly linked to the pathogenicity of many bacteria. This mini review highlights several potential strategies to target BAPs for drug development.

This chapter is written for the welfare of the society, questioning and enlightening the effects of the increment or decrement in the percentage of quality of air causing pollution due to the rise in the traffic post-lockdown due to COVID-19 in metro cities, specifically in Delhi. In this chapter, we address the question about people's preference in moving in the shared taxis to their workplaces or their reluctance and denial of the idea of moving in the shared vehicle because of the fear of getting infected. The sensitivity of the situation will compel the people to move in a single occupied vehicle (SOV). The rise in the number of vehicles on the roads will result in traffic jams and different kinds of pollution where people battling with the pandemic will inevitably get exposed to other health-related issues. We use a BPR (Bureau of Public Roads) model to combat this issue endangering the environment and public health. We exploit the BPR function to relate average travel time to the estimated number of commuters travelling by car. We collect mode share data from the NITI Ayog, the State Resource Centre and other authentic sources, which gives unique figures of the impact of shared mobility in India and how, in its absence, various sectors will get affected. Using the given data and the BPR, we evaluate increased vehicle volumes on the road if different portions of transit and carpool users switch to single-occupancy vehicles and its effect on multiple other factors. Based on the study of densely populated city, Delhi, we predict that cities with significant transit ridership are at risk for extreme traffic and pollution unless transit systems can resume safe with effective protocols.

This study aimed to characterize the antioxidant, mechanical and physical properties of chicken skin gelatin/CMC/Centella asiatica blended film. The influence of Centella asiatica at 0.3% and 0.7% on antioxidant activities; mechanical properties and physical properties of chicken skin gelatin/CMC/Centella asiatica film were investigated. Characterization of the blended films with 0.7% Centella asiatica extract shows higher antioxidant activities with a total phenolic content of 0.36 mg/g of GAE, DPPH of 89.26%, and reducing power of 0.80 nm compared to 0.3% Centella asiatica extract. The addition of 0.3% of Centella extract provide higher value in tensile strength (5.0 × 10⁻² MPa), elongation at break (281%), melting point (131.31 °C), transparency (0.86) but lower UV-light penetration. While the addition of 0.7% Centella extract contribute to higher value in WVP (1.13 × 10⁻⁴ g m⁻¹s⁻¹Pa⁻¹) and puncture test (0.06 N). There are no significant differences between functional groups obtained from this blended film as evaluated by FTIR analysis (p > 0.05). Furthermore, XRD analysis showed the addition of extract decrease the crystallinity of film. In conclusion, the incorporation of Centella asiatica extracts on film greatly increased antioxidant levels and improved some of the mechanical and physical properties of the film blends.

Biogenic emission can have significant impact on atmospheric chemistry. Isoprene (C5H8) is known as the most predominant volatile organic compound and its emission is highly dependent on temperature and light (solar radiation). This study aims to investigate future changes of isoprene emission under climate change scenario. The Southeast Asia (SEA) region is home to 15% of the world’s tropical forest, and the biogenic emission from this region can have significant effect on the global climate chemistry. Three climate change scenarios (RCP4.5, RCP6.0 and RCP8.5) were used to drive climate change simulation in 2013 (baseline), 2030 (near-future), 2050 (mid-century), 2070 (post-mid) and 2100 (end of century) using the Weather Research Forecasting (WRF v3.9.1) model. The Model Emission of Gases and Aerosol from Nature (MEGAN v2.1) was then used to simulate isoprene fluxes using climate output datasets from the WRF model. This study highlights that the projected mean surface temperature and PAR (photosynthetic active radiation) were higher in July than in January. Towards the end of the century, the overall surface temperature and PAR over the SEA region is expected to increase by 0.9℃ - 2.1℃, and 7.6 W m-2 – 12 W m-2 under all RCPs. The all-time high isoprene emitters are Borneo and Papua Island. Meanwhile, the projected increment of isoprene emission over this region is between 10 – 14%, 15-30% and 29 – 53% for RCP4.5, RCP6.0 and RCP8.5, respectively. Our result concludes that the total isoprene emission was higher during July, consistent with the high surface temperature and PAR. The results also agreed with the hypothesis of high isoprene emission over the region that has oil palm plantation. Thus, challenges in dealing with future emissions of isoprene in SEA are closely tied to future climate policies to limit the warming of the atmosphere over this region and the land-use conversion of palm oil plantations.

While there has been a tremendous decline in malaria disease burden in the remote parts of the Malaysia, little is known about malaria incidence in its urban localities. This study aimed to analyse trends of malaria cases in urban Kuala Lumpur, Malaysia. All suspected cases presented to a university hospital in Kuala Lumpur from January 2005 to December 2020 were examined by microscopy. Infection status was analysed using descriptive statistics and curve estimation analysis. Of 3105 blood films examined, 92 (3%) were microscopically confirmed malaria cases. Plasmodium vivax infections accounted for the majority (36.9%) of all malaria cases. Nearly half (47.8%) of cases were found among foreign cases (P<0.001). The majority of foreign cases were males (86.4%) and came from Southeast Asian countries (65.9%). Curve estimation analysis showed significant decreases of malaria cases due to P. vivax (R2 = 0.598; P<0.001) and Plasmodium falciparum (R2 = 0.0259, P = 0.029), but increase for Plasmodium knowlesi (R2 = 0.325, P = 0.021) during the 16 years. This study revealed that malaria incidence in urban Kuala Lumpur is low and has remained stable since 2005. However, P. knowlesi played a significant role in the increase of overall malaria in the area, highlighting the importance of continued vigilance and improved surveillance.

Gender recognition is trivial for physiotherapist, but it is considered a challenge for computers. The electromyography (EMG) and heart rate variability (HRV) were utilized in this work for gender recognition during the stepping exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC) function in a combinatorial fusion approach (CFA) was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB), decision tree (J48), k-nearest neighbor (KNN) and support vector machine (SMO). Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Nazarloo's work (90.34%) and other classifiers.

The most modern technique utilized to create intricate and complexly manufactured parts for a variety of applications is called additive manufacturing (AM). Fused deposition modeling (FDM) has received the greatest attention in the development and manufacturing sectors. The main objective of this study was to investigate how printing factors affected the mechanical characteristics of printed samples. Samples were produced using an FDM 3D printer in compliance with ASTM D638 using a variety of input settings, including orientation, layer thickness, speed, and infill pattern. On the printed samples, tensile tests and morphological analysis using a scanning electron microscope (SEM) were done. The findings of this study demonstrate that factors including layer thickness, printing speed, and orientation significantly affect the tensile strength of ABS printed samples. Discovering the process settings that could lead to superior mechanical and physical characteristics would undoubtedly assist designers and manufacturers worldwide as the FDM 3D printer becomes more and more crucial in manufacturing engineering parts.

The global spread of multidrug-resistant (MDR) microbial infections is currently one of the most severe risks to global public health, with 10 million fatalities expected by 2050 unless action is taken. Nanotechnology has revolutionized science and medicine. The reliance on nanotechnology is growing. Nanoparticles have distinct properties that improve biological, chemical, and physical properties studied for various uses. A significant area of attention in the synthesis of nanoscale modulators is the utilization of crude formulations, retro-synthesized, and pure chemicals, mainly from herbal sources, with fewer adverse effects. Green chemistry has devised a tangential technique for synthesizing metals and metal oxides to produce nanoparticles. Plant extracts (leaves, stems, and shoots) and microorganisms (bacteria, fungus, and yeast) are used as reducing intermediates to make nanoparticles. Studies in microbiology have shown that nanoparticles kill bacteria, fungi, viruses, and protozoa. These green nanoparticles contain antibacterial, antifungal, and anti-inflammatory effects. Most nanoparticles have high antibacterial properties, indicating they may be used to combat diseases and biological contaminants. These nanoparticles have antibacterial action against pathogenic microorganisms that cause serious illnesses, including multidrug-resistant pathogens. The current research will pave the way for future applications and improved methods for producing nanoparticles, paving the way for an innovative route in nano-life sciences with widespread recognition.

Regarding landscape preferences for highways, there is a dynamic interaction between users and the variety of natural and cultural landscape elements along the roadside, reflecting a balance between the highway and the natural environment. However, the rapid pace of urbanization has accelerated the development of highways, leading to the neglect or destruction of valuable landscapes. This highlights the need for visual preference assessments to protect aesthetic and environmental values. Currently, there is a lack of comprehensive criteria for assessing the visual preference of highway landscapes. Therefore, this study aims to review existing literature and establish complete assessment criteria. This study conducted a systematic literature review by searching for keywords in three databases: Web of Science, Scopus, and Google Scholar. The review included 22 papers published between 2013 and 2023 that met the criteria. An additional four relevant papers were included through a “snowballing” approach to supplement the research and results. The results of the study focused on the relationships between highway landscapes and users, user preferences, preference methods, and related variables. These inter-established relationships were used to complete an assessment framework, which establishes a basic reference standard for professionals.

Genetic disorders are preeminent determinants of infant mortality. The inherited pediatric-onset genetic disorders have consequential stress on child growth and development: several congenital, complex and rare disorders with indistinguishable clinical symptoms where diagnosis always remains a challenging task. Traditional diagnosis methods include biochemical tests followed by chromosomal microarray and sequencing of a single gene or panel of genes. These methods had several limitations, but with the advent of whole-exome sequencing (WES), genetic testing has become cost-effective and transformative. Exome sequencing has been known for its effectiveness, which appropriately elucidates and distinguishes the heterogeneous disorders to avoid misdiagnosis and decode the underlying genetic alterations. WES has led to discovering genes and genomic variants in a broad spectrum of diseases, including autism, epilepsy, congenital heart diseases, neurodevelopmental diseases, cancer, nephrotic disorders, neural tube defects and fetal structural anomalies. WES is significant in producing immense genomic biomarkers that can be made as appropriate pharmacogenomic targets for drug therapy. In this article, we analyze the recent exploration of WES technology to revolutionize not only the process of genetic variation and disease detection but also the convention of preventative and targeted drug discovery.

Phage, which is often used therapeutically, has begun to receive interest as an alternative to antibiotic growth promoters (AGPs) to enhance chicken growth. Another option that has been extensively studied as a growth promoter in chicken is probiotics. However, there are no studies using phages and probiotics as prospective feed additives for broiler chickens. Therefore, this study demonstrated the effects of phage cocktail, probiotics and their combinations on growth performance and gut microbiota of broiler chickens. A total of 288 one-day-old male Cobb 500 broilers were randomly allotted to 1 of 6 treatments in a completely randomised design. The treatments were: (i) C (basal diet (BD) only), (ii) 1ɸ (BD + 0.1% phage cocktail), (iii) 2ɸ (BD + 0.2% phage cocktail), (iv) P (BD + 0.1% probiotic), (v) 1ɸP (BD + 0.1% phage cocktail + 0.1% probiotic), (vi) 2ɸP (BD + 0.2% phage cocktail + 0.1% probiotic). The 1ɸP treatment had significantly (P < 0.05) better BW (35 d), BWG (22 – 35 d, 1 – 35d), and FCR (1-21 d. 22-35 d, 1-35 d) compared to C. Unique gut microbiota diversity was also found between the ɸP (1ɸP and 2ɸP) and non-ɸP groups (C, 1ɸ, 2ɸ and P) in ilea, particularly in the 35 d chickens. Microorganisms associated with short-chain fatty acid (SCFA) producers were significantly (P <0.05) present in the ɸP group than in the non- ɸP group. The carbohydrate and amino acid metabolism predicted genes were significantly upregulated in ɸP groups compared to non- ɸP groups. These genes were involved in the digestion and absorption of nutrients as well as the production of energy. Our findings showed that 1ɸP treatment could be a potential alternative to AGPs for poultry where growth performance was enhanced, and gut microbiota was positively modulated.

A Zn(II) perchlorate complex has been prepared and characterized by single X-ray crystallography, nuclear magnetic resonance spectroscopy, thermogravimetric analysis, infrared spectroscopy, elemental analysis, and UV-vis spectroscopy. The complex crystallizes in the monoclinic space group P21/c (Z = 4) with a pentacoordinated zinc center. Interestingly, the Zn complex was found be to a potential fluorophore that could sense acetone and other ketones with high selectivity and sensitivity.

A study on the selection of hyperelastic constitutive model for polymeric materials is performed using a hybrid experimental-computational approach. Bis-GMA polymer is used as a case study of hyperelastic material to describe the polymer characteristics by determining its Poisson’s ratio and its valid range of the hyperelastic stress-strain curves. These two parameters are then used to determine the hyperelastic constitutive model by using the hybrid approach. Several uniaxial compression tests along with their finite element simulations are implemented in a systematic way, to identify the polymer behavior under the compressive loading conditions. Nano-indentation experiments are conducted to verify the hyperelastic behavior of the polymer. The experimental and computational evidences confirm that the Poisson’s ratio of Bis-GMA is 0.40 and the appropriate hyperelastic constitutive model for this polymer is of a second order polynomial. It is shown that, the results can be used to determine the true stress-strain curve of hyperelastic materials.

Assessment of stigma among cancer patients is of utmost importance as stigma may lead to various psychological sequelae and lower quality of life. This study aimed to translate the English version of the Shame and Stigma Scale (SSS) into Malay and validate the Malay version of the SSS (SSS-M) among cancer patients in Malaysia. Initially, concurrent translation and back translation of the SSS-M was performed, and face and content validity were assessed. Then, the SSS-M was administered to a total of 234 patients of mixed types of cancer to assess its reliability (internal consistency and test-retest reliability), construct validity (convergent and discriminant validity), exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The SSS-M total score registered good internal consistency (Cronbach’s α of 0.886) and test-retest reliability (intraclass correlation coefficient of 0.846, p < 0.001). EFA and CFA confirmed that the SSS-M consisted of 20 items in 5 domains. Its convergent and discriminant validity were achieved. Hence, the SSS-M demonstrated good psychometric properties and is available for use to assess stigma among cancer patients in Malaysia.

Real-time data processing and decision-making are increasingly crucial in various applications, driven by the continuous influx of data streams. Event-driven AI workflows within serverless computing environments offer a promising approach to handle these real-time demands efficiently. This paper presents a framework for simulating and analyzing the performance characteristics of such workflows. Our proposed approach utilizes simulated data with varying event rates and durations to investigate the impact on key performance metrics like latency, throughput, and resource utilization. This enables a comprehensive evaluation of the inherent trade-offs within event-driven AI systems. The key findings reveal a trade-off between latency and throughput. As the event rate increases, average processing latency generally increases while average throughput increases. Resource utilization remains relatively stable across different event rates in the simulated scenarios (e.g., 75.55\% at 2 events/second, 74.51\% at 10 events/second). This framework provides a valuable tool for understanding the performance characteristics of event-driven AI workflows and optimizing resource allocation strategies.

The effect of SARS-CoV-2 pandemic has been subsided significantly following the rapid development of vaccine. However, patients with cancer and immunosuppressed state, who are more prone to mortality and morbidity due to this infection, were excluded from majority of the vaccine trials. Moreover, suggested dose modification for cancer and immunosuppressed patients are often not followed because of lack of awareness or unavailability of vaccination schedule. This review will try to bridge this knowledge gap by summarizing the current suggestions of dose modification of COVID-19 vaccine for patients with cancer and immunosuppression.

Arabic was the language of philosophy, logic, Islamic sciences and rhetorical linguistic sciences. It was used in the writing of all sciences generally and became the language of world culture. Although the other languages of the Islamic world had a little share, but all peoples of Islamic countries; Arabs and non-Arabs, Muslims and non-Muslims attributed to that movement appreciated. Hence, Arab sciences flourished in their bright ages. Arabic language was a cultural container of the ancient Greek and Latin intellectual heritage. As the ancient Greek and Latin sciences and literatures were translated into Arabic in the bright ages of Islam. Arab language was a strong bond for them, as a common human heritage for the centuries to save it from being lost, as Muslims used it to develop their sciences and arts, as Muslims in the East used the Western sciences and literatures in the modern age, because they are not Eastern or Western, but the common efforts of all humanity. Arabic language opened for the dictionaries ​​and other tongues of cross-fertilization, civil friction and simulation. Arabic had become the language of sciences: mathematics, astronomy, engineering, logic, philosophy, mysticism, agriculture, industry and economics by the continuous efforts of scientists in their scientific research, invention, experimentation, knowledge collection and classification in various fields, where orientalists recognized the Arab leadership. That scientific and literary civilization moved to Europe through Italy, Andalusia, Crusades and the Ottoman Caliphate. Europeans learned Arabic language, literature and sciences in the centers of Toledo, Fez and cities of Maghreb.

This qualitative study aims at identifying the essence of personal experiences of accounting partners in Saudi Arabia. For this phenomenology approach employs to understand the lived experience of accounting partners and how would such experience affect their career. It mainly aims to explore the different experiences of fifteen (15) Saudi partners working in various accounting companies in Saudi Arabia. The interviews conducted to explore the most important challenges and difficulties for accountants to become a partner, and the most important job skills that the partners must have. This study found that there is urgent need for a number of things, including the required number of years of experience to become a partner, and to make sure that the partners are having the right education and professionally qualified. In addition, other different skills that the partner must have include responsible leadership, professional communication, good marketing skills and excellent command of English. Moreover, this research is vital for the concerned parties to identify the current challenges in the accounting profession in Kingdom of Saudi Arabia.

The recent happenings in the world such as flood and wild forest fire were as a result of climate effect as being envisaged by scientists. It is urgent now to adopt a source of energy that will eliminate this effect on our universe. Solar energy is the major energy means that is abundant which could be utilized. In this review, the prospects of solar energy exploration were studied in Nigeria which include assessments, economic viability and hybrid systems. Findings show higher potential in the North as compared to the Southern region. Additionally, potential of offshore solar energy system was simulated by considering 2002, 2003 and 2004 data sets from Era5-land base. Their monthly mean, seasonal changes and annual mean value were estimated. The algebraic annual solar radiance for 2002, 2003 and 2004 were 34,914.732 kWh/m2, 33,898.316 kWh/m2 and 34,338.324 kWh/m2. Suggestions were made due to the present status of solar energy utilization that will enhance its maximum usage and development. One of these is the establishment of a functioning financial scheme and the database for all renewable energy systems. When all these are put in place, the energy supply will increase, climate effect will be reduced, and the economy will be boosted.

Customer satisfaction is the process of reaching a customer's expectations to generate delightful experiences with a product or a brand. Delight involves delivering an unforgettable experience to users by focusing on their requirements, desires, and interests. Delighting Customers is crucial for organizations’ economic growth worldwide, especially in the airline industry. This study aims to determine if safety measures, ticketing policies, and the cost of air travel impact among the airline passengers’ satisfaction post-COVID-19 in Malaysia. A research framework is designed to present an in-depth understanding of the mentioned variables. In this study, a comprehensive survey using online questionnaire was used and 388 valid responses were obtained from airline passengers in Malaysia. Data were analyzed by employing data reduction technique and multivariate data analysis. The results revealed that safety appears to be the most essential aspect of airline customer satisfaction among Malaysians, while cost is perceived as a significant factor. Moreover, as the cost of living rose because of the pandemic, many of the income earners in the lower category are less inclined to take vacations. In a nutshell, the study recommends that airlines implement a conscious practice that contributes to the happiness of passengers, which in turn increases profitability and ensures sustainable growth of the airlines.

Increase demand for palm oil production has indirectly increased waste and pollution. Empty fruit bunch (EFB), which is the major solid waste from this industry, has the potential to be further treated into valuable product. In this study, cellulose will be extracted from EFB through alkali treatment and acid hydrolysis treatment with a different approach and further modified via acetylation and silylation technique. The modified samples are to be utilized to reduce pollution due to palm oil mill effluent (POME) and carbon dioxide (CO2) emission from the industry. The characterization of the extracted and modified cellulose was carried out using attenuated total reflectance-Fourier transform infrared (ATR-FTIR), thermogravimetric analysis (TGA) and scanning electron microscope (SEM). ATR-FTIR analysis revealed that the cellulose was successfully extracted from raw EFB and the cellulose-acetyl, nanocrystalline cellulose (NCC) and cellulose-2 has been successfully modified from the cellulose. TGA analysis shows that both modified cellulose have higher thermal stability compared to raw EFB and extracted cellulose. SEM morphology of the modified cellulose shows a higher surface area due to the wrinkled formation while the wax layer and cuticle pore has been diminished clearly. The modified sample gave a significant performance where cellulose-acetyl absorbed 98.5% of oil compared to unmodified cellulose-1 sample that only absorbed 5% of oil from POME. NCC-AEAPDMS adsorbed physically and chemically 3.5 cm3/g CO2 gas compared to NCC sample, which undergoes only physical adsorption with maximum capacity up to 2.4 cm3/g. Thus, modification can enhanced the performance of cellulose for industrial applications.

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densi- ties and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on dierent set of true values. Some real data sets were employed to show the usefulness and exibility of the model which serves as generalization to many sub-models in the elds of engineering, medical, survival and reliability analysis.

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densities and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on different set of true values. Some real data sets were employed to show the usefulness and flexibility of the model which serves as generalization to many sub-models in the field of engineering, medical, survival and reliability analysis.

This paper aims to provide an evaluation of how Value Added Tax (VAT) policy alterations influence market liquidity, trading volume, and stock performance. To fill the existing literature gap on the direct effect of (VAT) adjustments on stock market dynamic, particulate within the banking industry. The study employs an event study methodology to analyse the immediate and medium-term effects on bank stocks listed in markets subject to a (VAT) adjustments. The core of the study analysis is anchored around two pivotal events, the initial application of (VAT) on 1st January 2018, and the subsequent (VAT) increase to 15% on 1st July 2020 using MATLAB R2022b. The study analysis encompasses the period immediately before and after the introduction and subsequent increase (VAT) in kingdom Saudi Ariba (KSA) employing an eleven sample comprises the (KSA) largest banks with a ±7 days window period from the event. The analysis revels that the imposition of 5% (VAT) lead a substation downturn in trading volume and stock returns of 9.5%, and 39.5%, subsequently. While when the (VAT) was increased by 15% the market exhibited a mixed but ultimately positive response of 3.3% trading volumes increases and 128.7% average stock return recovery.

Corporate identity has played a vital role in the Halal industry to create a strong foundation for its reputation in the long run. This paper used two modeling analyses for two different data. The first analysis aims to predict the relationship between Corporate Identity Management between Internal Brand and Employee Brand Support (consequence) mediated by CIM using partial-least squares-structural equation modeling (PLS-SEM). A total of 206 employees from Malaysia’s Halal food SMEs took part in the survey. The second analysis to identify topic proportions patterns using the topic modeling approach on Halal brand identity Machine learning approach of knowledge mining was applied for this analysis. Metadata of 1,091 articles were mined from the Scopus database on Halal studies across all social sciences fields. The result revealed that there was a partial relationship between Internal Brand (antecedent) and Employee Brand Support (consequence) mediated by CIM. This finding was supported by the identified topic proportions patterns from the topic modeling approach that pointed out a weak topic proportion on the Halal brand identity discussion globally, interestingly the result also found that the Halal brand identity discussion involving the Halal food industry is almost non-existed in Malaysia’s Halal food SMEs. The contributions of this paper were apparent in three major areas which are methodology, theoretical and future suggestions. The utilization of two different model analyses was able to confirm the consistency of the major findings with the literature review which opens up more possibilities for future researchers.

Virtual Histology- Intravascular Ultrasound (VH-IVUS) image is an available method for visualizing plaque component to detect thin cap fibroatheroma. Nevertheless, this imaging modality has considerable limitations to extract the plaque component features and identifying the TCFA plaque. The aim of this paper is to improve the identification of TCFA using fusion of IVUS and VH-IVUS images. In order to generate the automatic technique for reducing the human interaction, a new method namely Active Contour based Plaque Border Detection (ACPB) is proposed. In order to perform the pixel wise classification, hybrid of K-means algorithm with Particle Swarm Optimization and Plaque based Minimum Euclidean Distance (KMPSO-PMED) method is presented to classify the plaque region as well. Moreover, to obtain more significant information of imaging modalities, fusion of two different images consisting of VH-IVUS and IVUS is performed. Therefore, geometric features are extracted from the plaque region and combine with IVUS features. Furthermore, different group of plaque features are divided by means of the histopathological studies. SVM classifiers is applied to detect the TCFA and non-TCFA plaques. The proposed method is applied on 566 in-vivo IVUS and their matching VH-IVUS images obtained from 9 patients. The best result of SVM illustrates the accuracy rates of 99.41% for classification of TCFA plaque. The results prove that the highest accuracy is achieved by integrated features of IVUS and VH-IVUS images.

Taking care of stroke survivors can be taxing, however, it was understudied in Malaysia. This study aims to describe the burden of informal stroke caregivers within three months after hospital discharge. A longitudinal study design was conducted. Acute stroke survivors and their informal caregivers were recruited prior to hospital discharge, and the caregivers were interviewed by phone. Self-reported caregiver burdens were measured with Zarit Caregiver Burden Interview – Malay version (MZBI) and Caregiver Assessment of Function and Upset – Malay version (Malay-CAFU). The MZBI and Malay-CAFU scores were collected four times within three months. A total of 85 stroke survivors and 155 informal caregivers were recruited, with 58.1% of the caregivers were female. The stroke survivors had two caregivers on average. The mean (SD) scores for the three scales show a reduction, from 27.42 (12.73) in the first week to 17.77 (11.20) in the third month for MZBI, from 1.14 (0.94) to 0.62 (0.64) for instrumental activities of daily livings (IADL) of Malay-CAFU upset scale and 1.36 (1.00) to 0.78 (0.65) for activities of daily living (ADL) of Malay-CAFU upset scale in the same period. Stroke survivors may have several caregivers, usually their spouses or children. Within a short period, the caregiver’s burden was reduced. Early psychosocial support to alleviate the caregiver burden may be necessary.

: Mistrust, amplified by numerous artificial intelligence (AI) related incidents, has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods. Central to this issue is the black-box problem of AI, which impedes investments and fast becoming a legal hazard for users. Explainable AI (XAI) is a recent paradigm to tackle this challenge. Being the backbone of the industry, the prognostic and health management (PHM) domain has recently been introduced to XAI. However, many deficiencies, particularly lack of explanation assessment methods and uncertainty quantification, plague this young field. In this paper, we elaborate a framework on explainable anomaly detection and failure prognostic employing a Bayesian deep learning model to generate local and global explanations from the PHM tasks. An uncertainty measure of the Bayesian model is utilized as marker for anomalies expanding the prognostic explanation scope to include model’s confidence. Also, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of PHM-XAI publications. The quality of the explanation is finally examined employing local accuracy and consistency properties. The method is tested on real-world gas turbine anomalies and synthetic turbofan data failure prediction. Seven out of eight of the tested anomalies were successfully identified. Additionally, the prognostic outcome showed 19% improvement in statistical terms and achieved the highest prognostic score amongst best published results on the topic.

To quantify the time-varying reproduction number (Rt) for Malaysia using the COVID-19 incidence data., we used data the from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository. Day 1 was taken from the first assumed local transmission of COVID-19. Data was split into four intervals: a) Interval 1: from Day 1 to Day 10 MCO 1, b) Interval 2: from Day 1 to Day 10 MCO 2, c) Interval 3: from Day 1 to Day 10 MCO 3 and d) Interval 4: from Day 1 to Day 10 MCO 4. We estimated the Rt using the EpiEstim package. The means for Rt at Day 1, Day 5 and Day 10 for all MCOs ranged between 0.665 to 1.147. The average Rt gradually decreased in MCO 1 and MCO 2. However, Rt increased in MCO 3 before stabilized around 0.8 in MCO 4. MCO 1 and MCO 2 which were stricter coincide with the gradual reduction of Rt. However, the more relaxed MCO 3 and MCO 4 correspond to a slight increase in the Rt before it stabilized.

.Most of the accident cases at work are caused by unsafe behaviour. Scholars have thus extensively researched factors of safe behavior.Safety leadership is stated as the most effective factor in safety behaviour. Besides, safety knowledge and safety attitudes are also found to influence safety behaviour. The purpose of this paper is to investigate the nature of the relationship between safety leadership, safety knowledge, safety attitude, and safety behavior, which has been found to be limited or rare in previous research.A self-administered questionnaire was applied and was distributed randomly to 140 SME manufacturing workers and they were analysed using the structural equation modelling partial least squares (PLS-SEM). The results prove that safety leadership has a significant effect on safety knowledge, safety attitude, and safety behaviour, with safety knowledge and safety attitude mediating the safety leadership-safety behaviour relationship. Consequently, the results provide a more in-depth view of the relationship between safety leadership and safety knowledge-attitude-behaviour via adapting social-cognitive theory and social learning theory in solving safety issues in SME. This study also provides a starting point for researchers to better understand how effective safety leadership is provided by supervisors in terms of improving worker safety and safety knowledge-attitude-behaviour.

Stingless bee beekeeping provides new opportunities to improve the incomes of many households in Malaysia through the sale of honey and other bee products. While Heterotrigona itama is one of the most commonly cultured species of stingless bees, its behavior is not very well understood. Hence, we conducted this study to investigate the behavior of H. itama in exploiting food sources by ascertaining the nectar sugar concentration preferred by the bee. We also aimed to determine the preferred distance of food source from the bee hive. Our results suggest that H. itama prefers high sugar concentrations of 35% and above, and they would fly up to 7 m from the hive to collect food. We discuss how nectar concentration and food distance influence the number of bees exploiting food sources and the overall foraging pattern of H. itama.

Measurement of breast cancer burden and identification of its influencing factors help in the development of public health policy and strategy against the disease. This study aimed to examine the variability of the excess mortality of female breast cancer patients in the North East Region of Peninsular Malaysia. This retrospective cohort study was conducted using breast cancer data from the Kelantan Cancer Registry between 2007 and 2011, and Kelantan general population mortality data. The breast cancer cases were followed up for five years until 2016. Out of 598 cases, 549 cases met the study criteria and were included in the analysis. Modelling of excess mortality was conducted using Poisson regression. Excess mortality of breast cancer varied according to age group (50 years old and below vs above 50 years old, Adj. EHR: 1.47; 95% CI: 1.31, 4.09; P=0.004), ethnicity (Malay vs non-Malay, Adj. EHR: 2.31; 95% CI: 1.11, 1.96; P=0.008), and stage (stage III and IV vs. stage I and II, Adj. EHR: 5.75; 95% CI: 4.24, 7.81; P<0.001). In conclusion, public health policy and strategy aim to improve cancer survival should focus more on patients presented at age below 50 years old, Malay ethnicity, and at a later stage.

Enhancing the management and monitoring of oil and gas processes demands developing precise predictive analytics techniques. Over the past two years, oil and its prediction have advanced significantly using conventional and modern Machine Learning techniques. Several review articles detail the developments in predictive maintenance and technical and non-technical aspects of influencing the uptake of big data. The absence of references for machine learning techniques impacts the effective optimization of predictive analytics in the oil and gas sector. This review paper offers readers thorough information on the latest machine learning methods utilized in this industry's predictive analytical modelling. The review covers forms of Machine Learning techniques used in predictive analytic modelling from 2021 to 2023 (91 articles). It provides an overview of the details of the papers that were reviewed, comprising of the model’s categories, the data's temporality, field, and name, the dataset's type, predictive analytics (classification or clustering or prediction), the models' input and output parameters, performance metrics, optimal model, and benefits and its drawbacks. Additionally, suggestions for future research directions are provided to raise the potential of the associated knowledge and increase the accuracy of oil and gas predictive analytics models.

Immunomodulation as means of immunotherapy has been studied in major research and clinical laboratories for many years. T-Regulatory (Treg) cell therapy is one of the modulator used in immunotherapy approaches. Similarly, nuclear receptor peroxisome proliferator activated receptor gamma (PPARγ) has extensively been shown to play a role as an immuno-modulator during inflammation. Given their mutual roles in downregulating the immune response, current study examined the influence of PPARγ ligands i.e thiazolidinedione (TZD) class of drugs on Foxp3 expression and possible crosstalk between PPARγ and nTreg cells of NOD and NOR mice. Results showed that TZD drug, ciglitazone and natural ligand of PPARγ 15d-prostaglandin downregulated Foxp3 expression in activated nTreg cells from both NOD and NOR mice. Interestingly, addition of the PPARγ inhibitor, GW9662 further downregulated Foxp3 expression in these cells from both mice. We also found that PPARγ ligands negatively regulate Foxp3 expression in activated nTreg cells via PPARγ-independant mechanism(s). These results demonstrate that both natural and synthetic PPARγ ligands capable of suppressing Foxp3 expression in activated nTreg cells of NOD and NOR mice. This may suggest that the effect of PPARγ ligands in modulating Foxp3 expression in activated nTreg cells is different from their reported effects on effector T cells. Given the capability to suppress foxp3 gene, it is possible to be tested as immunomodulators in cancer-related studies.

Hb Adana is a non-deletional α-thalassaemia variant, due to mutations in α1- or α2-globin codon 59 (αCD59) that produce unstable α-globin. Clinical appearance can range from silent carrier to blood transfusion reliance, hepatosplenomegaly, skeletal deformities, and spinal cord compression. Despite the importance of Hb Adana inheritance, this Hb variant is challenging to study since molecular tests are scarce and routine diagnosis can be missed. This study explored the distribution of Hb Adana among local high school students and evaluate the hematological parameters and haemoglobin analysis of Hb Adana in this region of Malaysia. This retrospective study included 13,721 blood samples from high school students enrolled in Malaysia's National Thalassaemia Screening Program at Hospital Raja Perempuan Zainab II (HRPZ II). Multiplex Gap PCR was used to detect deletional α-thalassaemia. Common non-deletional α-thalassaemia was detected using multiplex ARMS PCR. Evaluable data were retrieved from the HRPZ II database. Results: A total of 2327 subjects exhibited common deletional (n=1037, 44.6%) and non-deletional (n=1290, 55.4%) α-thalassaemia. Hb Constant Spring was the most frequent non-deletional α-thalassaemia. Thirty-one participants (1.33%) had αCD59α/αα and one (0.04%) had αCD59α/-α3.7. The 32 Hb Adana subjects were 87.5% Malay, and 12.5% Orang Asli. Additionally, seven cases of HbE/Hb Adana were discovered. The haemoglobin level in heterozygous Hb Adana ranged from mild anaemia to normal, 95.0 g/L to 153.0 g/L. The MCV and MCH were approximately 73 fL and 23 pg, respectively. Conclusions: We have denoted the distribution of alpha thalassaemia mutation patterns among high school students in Kelantan, Northeast Peninsular of Malaysia. Our observation showed Hb Adana was rarely uncommon in our region and the co-inheritance with an α-gene deletion generates α+-thalassaemia; with HbE, α0-thalassaemia. All heterozygous Hb Adana exhibited low MCVs and MCHs.

The use of low-intensity ultrasound has gotten surprising consideration over the last decade as a method for enhancing the catalytic activity of the enzyme. Ultrasounds have the potential to significantly influence the activity of the enzymatic processes, provided that the energy input is not too high to inactivate the enzyme. By providing the variation in parameters, various physical and chemical effects can be attained that can enhance the enzymatic reaction. Ultrasonic reactors are known for their application in bioprocesses. However, the potential of their applications is still limited broadly due to the lack of proper information about their operational and performance parameters. In this review, the detailed information about ultrasonic reactors is provided by defining the different types of reactors, number and position of ultrasonic transducers. Also, it includes the mechanism of intensification and influence of ultrasonic parameters (intensity, duty cycle and frequency) and enzymatic factors (enzyme concentration, temperature and pH) on the catalytic activity of enzyme during ultrasound treatment.

In this changing world, we all are surrounded by the surmountable risk of getting injured. Amongst various risk factors, major burns are the most distressing and catastrophic. Burn wounds are not easy to heal via natural healing process and ultimately ended up with scar formation. If the degree of burn is high then the loss of tissue and its function is very common. To fasten-up the natural burn wound healing; zinc, an essential trace element is found to be very much effective. But due to its’ particle size limitation, less contact with wounded cells and tissues, and high inherent toxicity restrict its use. Needlessly, zinc is an element with dual action i.e. both antimicrobial and wound healing it is a prime choice to apply its aptitude in burn wound healing. To overcome the documented limitations zinc has converted to nanoparticle form. Zinc oxide nanoparticles, in particular, have attained ample of interest due to their unique properties and potential antimicrobial activity along with wound healing activity which makes it promising for the healing of topical burn wounds. Plant mediated green synthesis of nano-metal oxide particles is gaining a lot of significance due to its simplicity, eco-friendliness and extensive antimicrobial activity and recommended as an appealing substitute to not only physical methods but also chemical methods avoiding the use of the high rate of toxic chemicals and extreme surroundings. This study includes ZnO NPs role in burn wound healing with Phyto-mediated synthesis methods to provide evidence of their potential applications. Additionally, it provides an overview of traditional methods used for the synthesis of ZnO nanoparticles and characterization techniques to obtain information concerning the size, shape and optical properties along with toxicity and safety concern of ZnO NPs and its biomedical applications.

Hospital Pulau Pinang is the general hospital in Malaysia which targeting energy savings of 10% within five years from 2015 and other sustainability targets such as 3-star Energy Management Gold Standard and Green Building Certification. The targets are beneficial for the hospital itself to establish the Smart Building Program to improve its energy efficiency concurrent with the green policy of the Ministry of Health Malaysia and Sustainable Development Goals by the United Nations. This paper reviews the background of Hospital Pulau Pinang energy data , energy consumption trending, energy-saving trending, and energy conservation measures taken for the hospital from 2015 to December 2021.The yearly energy consumption baseline taken in 2016 was 27,496,731.00 kWh. It reduced significantly to 21,356,063 kWh in 2021 due to energy conservation measures. As a result, Hospital Pulau Pinang has achieved energy-saving about 16% at approximately RM7.3 million reduction in operational expenditure. The main objective of this paper is to provide further potential energy savings by studying the energy reduction by implementing solar photovoltaics using the simulation method. The simulation method can predict that Hospital Pulau Pinang can achieve another 5,130,000 kWh energy savings annually. This type of simulation has never been done before at a public hospital, and it will give further enhancing strategies to the Smart Building Program itself. Furthermore, the potential of smart building can be maximized to the next level by simulation, which helps the hospital energy committee make the potential decision on the energy-saving investment.

Nodes in wireless sensor networks (WSN) are characterized particularly by their limited power and memory capabilities. Limited memory is an important parameter as it defines the size of the operating system and the processing code. As established previously, energy and memory efficiency is the most important evaluation factors of WSNs as they are directly related to data loss and network lifetime. However, based on our simulation results, memory efficiency determines the selection or abandon of nodes by the botmaster for the propagation of bots in an IoT infrastructure. Consequently, the node’s memory efficiency determined the spread of bots in the network and provides defense actors with an insight of the botmaster behavior for mitigation of the attack. Conventional botnet propagation and mitigation models did not consider the impact of node’s memory efficiency in the IoT platform. To address this gap, we build IoT-SIEF, a novel propagation model with forensic capability that will analyze command and control propagation behavior based on the perspective of the node’s memory efficiency. IoT-SIEF model used to explore the dynamics of propagation using numerical simulation with more than 50% outperform other models in mitigating the number of secondary bots. Consequently, it can serve as a basis for assisting the planning, design, and defense of such networks from the investigator's point of view.

The present study examined the volatile composition and antimicrobial and gastrointestinal activity of the essential oils of Elettaria cardamomum (L.) Maton harvested in India (EC-I) and Guatemala (EC-G). Monoterpene were present in higher concentration in EC-I (83.24%) than in EC-G (73.03%), whereas sesquiterpenes were present in higher concentration in EC-G (18.35%) than in EC-I (9.27%). Minimum inhibitory concentrations (MICs) of 0.5 and 0.1 mg/mL were demonstrated against Pseudomonas aeruginosa in EC-I and EC-G, respectively, whereas MICs of 0.125 and 1 mg/mL were demonstrated against Escherichia coli in EC-I and EC-G, respectively. The treatment with control had the highest kill-time potential, whereas the treatment with oils had shorter kill-time. EC-I was found to be more potent in the castor oil-induced diarrhoea model than EC-G. At 100 and 200 mg/kg, EC-I exhibited 40% and 80% protection, respectively, and EC-G exhibited 20% and 60% protection, respectively, in mice, whereas loperamide (positive control) exhibited 100% protection. In the in vitro experiments, EC-I inhibited both carbachol (CCh, 1 µM) and high K+ (80 mM)-induced contractions at significantly lower concentrations than EC-G. Thus, EC-I significantly inhibited P. aeruginosa and E. coli and exhibited more potent antidiarrheal and antispasmodic effects than EC-G.

Salmonella sp. is a globally prevalent organism responsible for causing salmonellosis, a foodborne illness. Salmonella Typhimurium represents a type of Salmonella sp. not associated with typhoid fever but capable of causing stomach and intestinal inflammation or severe infection. In the present study, 150 uncharacterized proteins of S. Typhimurium were randomly selected from UniProtKB and analyzed using TMHMM, PROSITE, STRING, DEG, and BLASTp. Results indicated that 32 uncharacterized proteins (21%) were predicted to be transmembrane proteins involved in various biological pathways. Among them, 30 transmembrane proteins were predicted to be essential and non-host homologous. This study's findings suggest their potential as drug targets against salmonellosis.

COVID-19, previously known as “2019 novel coronavirus”, is a newly discovered virus which causes severe acute respiratory syndrome, similar to corona virus 2 (SARS-CoV-2), which has spread widely through human to human contact and was declared a pandemic by the WHO in March 2020. To cope with this pandemic many countries have adopted nationwide lockdowns which restrict nonessential activities and encourage their populations to avoid public transport, work from hone wherever possible, and to maintain social distancing at all times. While the severity of these shutdowns has varied with country, large geographic regions of the world (including China, India, Iran, Italy, Spain, and the USA) have all been severely affected, not just in the loss of human life, but also in terms of the financial impacts the lockdowns will have on their countries future prosperityIt was previously reported that a number of environmental factors, including humidity and temperature, played an important role in development and spread of the SARS-Corona Virus infection with the virus retaining viability for over 5 days at temperatures between 22–25^oC and relative humidity (RH) of 40–50%. Whereas, elevated temperatures and higher RH (38^oC, and >95% RH) decreased virus viability (Kroumpouzos et al., 2020). The spread of COVID-19 started in low temperature areas of China, with major outbreaks subsequently occurring in Iran, Japan, Northern Italy and South Korea. These new virus epicenters all had similar temperature and latitude, along the 30-50^◦N” zone. Subsequently, the virus was spread to regions of elevated temperature, such as India, the Middle East and Thailand, due to international travel (Kroumpouzos et al., 2020).The aim of this study was to consider the environmental impact of COVID-19, including water pollution. The paper is divided into four sections. In the first section the current literature related to COVID-19 is reviewed. In the second section a recent update on COVID-19 globally is presented, followed by a descriptive impact on the environment in the third section and finally in the fourth section the COVID-19 related worldwide environmental impact is discussed. Since COVID-19 is a currently an active pandemic with no end in sight, while constructive conclusions can only be made on the limited data currently, which may be prone to high errors. However, these conclusions may provide some preliminary suggestions for assisting in assessing spreading patterns of COVID-19 across the globe, and may be of long-term significances with respect to assessing the environmental impact of lockdown policies due to COVID-19 worldwide.

Despite increased global interest in the impacts of natural disasters on tourism, less study executes exploring how tourism sensitivity is addressed at the destination level. Generating a link between tourism and natural disaster management is vital in places that rely heavily on tourism and are prone to natural hazards. Ranau, Sabah (Malaysia) is one of the disaster-prone tourists' destination area. Hence, this paper applies the case study of Ranau earthquake 2015 to explore tourism sensitivity towards natural disasters. A qualitative of in-depth interview is applied to acquire information needed from the Ranau tourism entrepreneurs and operators. To analyse the qualitative data, a thematic analysis is conducted. Overall findings show that tourism activity in Ranau are identified to be sensitive towards the 2015 earthquake with a significant percentage of sensitivity level on two elements. These elements are known as Source and Power. The Source element includes tourism products, size of business, development, and natural disasters management with a significant sensitivity compared to the Power element (social capital). This provides insight to the need of specific tourism system adaptation as response to the earthquake and considering the integration of natural disaster management into tourism development to enhance long term sustainability.

Background: Paracetamol may be use as antipyretic agent for the treatment of fever, as well as an analgesic in the treatment of mild to moderate pain on post vaccination in infants. The use of Paracetamol during fever may be or may not be recommended since it may alter natural human body immune response although it may reduce pain. Objectives: This study described the relevancy of Paracetamol use post infants vaccination based on data collection systematic review analyses. This study aims to describe the effectiveness of breastfeeding in reducing pain and Paracetamol in reducing fever and pain post infants vaccination. Data Sources and Study Selection: Electronic literature search by hand searching six (6) databases which include Ovid LWW Total Access Collection and Medline, CINAHL (Cumulative Index to Nursing and Alled Health Literature) Plus with Fulltext, Science Direct, Proquest Dissertations and Theses, Proquest Education Journal and Proquest Health and Medical Complete. Additionally, manual reference checks of all articles on Paracetamol and breastfeeding post infants vaccination published in English Language between 1978 and 2017. Two level of screening were used on 9614 citations which include screening of abstracts and titles followed by full text screening. Data Synthesis: Data synthesis were tabulated into study characteristics, quality and effects. Authors of trials were not contacted for further details or provision of original data if the published report contained insufficient information. The study findings, as reported by the authors, were included in this review. The data in this research cannot be pool due to not enough data regarding odd ratio or relative risk as well as confidence interval in each study. Results: Systematic review of breastfeeding included three (3) studies from 9614 of database searching. The reviews of all these three (3) studies found significant benefit from breastfed in pain score and duration of crying as well as behavioral changes. None study stated the unbeneficial of breastfeeding before, during and after immunization. Meanwhile, systematic review of Paracetamol effectiveness included four (4) studies from 1177 of database searching. The reviews of two (2) studies found significant benefit from prophylaxis Paracetamol in fever and only one (1) study found significant benefit from prophylaxis Paracetamol in fussiness. On the other hand, there was one (1) study found not signifiant benefit from prophylaxis Paracetamol in fever. Other than that, there were two (2) studies evaluate the safety of prophylactic Paracetamol which revealed different outcomes, in which study by Prymula et. al. in 2009 found that antibody responses to several antigens were reduced significantly, and the other study by Uhari et. al. in 1988 found that antibody titres to DTP bacteria of placebo and PCM not differ significantly. Thus, Paracetamol seems to be not relevant post infants vaccination and breastfeeding was found to be beneficial post infants vaccination. Conclusions: The relevancy of giving Paracetamol post all types of vaccination may be questionable since the safety issue of this intervention may be arised. Breastfeeding before, during and after immunization are recommended for pain reduction as it was proved effectively. Finally, in deciding Paracetamol to be of rational use following infants immunization, it may need for further research which include in depth quantitative and qualitative studies to identify specific problem and causes regarding this issue.

The popularity of functional gummies has increased, which is evident from the growing line of functional gummies from almost every nutraceutical companies. Sensory evaluation serves the purpose of determining which brand of functional gummy would capture the largest market share. Texture profile analysis was used to determine the mechanical properties of functional gummies. The brands of functional gummies that came under the scope of this study were denoted as Brand A, B, C, D, E, F and G. Fourier Transform Infrared Spectroscopy was utilised to detect organic material and functional groups in the functional gummies. Texture profile analysis gave valuable insights into the gummies’ mechanical properties which are cohesiveness, springiness, hardness, gumminess, and chewiness. Amongst the gummies that were studied, Brand F gummy has the highest value of cohesiveness of 0.92. Brand A gummy has a high springiness value of 1.0. Brand B gummy possesses the highest value of hardness, gumminess and chewiness of 12 532.2 g, 7617.6 N, and 6256.8 J, respectively. Qualitative sensory evaluation reveals that Brand G gummy has the best aesthetic qualities in terms of colour and appearance. Brand B gummy tastes the best while brand A gummy claims the top spot for gumminess and chewiness. Overall, the respondents in this study preferred brand A gummy over other brands.

Picrasma javanica Blume or also known as Picrasma nepalensis or Picrasma philippinensis is a plant belongs to the Simaroubaceae family, which is known for its secondary metabolites namely quassinoids with various pharmacological properties including antitumor, antimalarial and antiviral. The plant traditionally used as medicine for different diseases in Myanmar, Thailand and Indonesia. The purpose of this study is to discern the phytochemical constituents and pharmacological activities of Picrasma javanica. The background, phytochemical constituents and pharmacological benefits of Picrasma javanica were reviewed and supported from previous studies, including in vivo and in vitro studies. The literature used in the review comprises of published books, journals, reviews and articles published from the year of 1969 to 2018, which are available in ScienceDirect, PubMed, Scopus and GoogleScholar. Chemical structures presented in this paper are either drawn with ACD/ChemSketch. Picrasma javanica possesses several phytochemical constituents, including quassinoids, alkaloids and triterpenoids. Compounds of the plant were isolated and studied for their pharmacological activities such as antimalarial, antiproliferative, antiviral, antimicrobial and membrane stabilising activity. Most importantly, these studies showed that the key players for the pharmacological benefits are quassinoids and alkaloids present in the plant.Picrasma javanica indeed has therapeutic potentials which may be beneficial for people. However, further extensive studies must be done on the plant as the detailed information on its pharmacological activities are still lacking.

With the objective of studying the influence of elicitors on growth, yield and quality of kalmegh we carried out an investigation for two consecutive years. Nine treatments with three replications were laid out in CRD design. Chitosan, Yeast extract, Jasmonic acid and Salicylic acid were evaluated at different concentrations. CHT 1000 ppm exhibited highest plant height (73.91 cm) and secondary branches (29.07) at the time of harvest. Primary branches and number of leaves per plant were highest in CHT 1000 ppm (26.36; 88.32) which were on par with SA 200 ppm (26.28; 81.51). Plant spread was highest in SA 200 ppm (35.46 cm2) which was on par with CHT 1000 ppm (35.11 cm2). CHT and SA sprays were recorded with on par results for yield parameters but highest fresh (42.34 g) and dry (18.30) herbage yield per plant were exhibited with SA 200 ppm. Highest total chlorophyll (4.459 mg g-1) and total andrographolides (3.494%) content were recorded in SA 200 ppm spray. Significant and positive improvement in growth, yield and quality of kalmegh was noticed with Salicylic acid spray @ 200 ppm at 30 and 60 DAS signifying its use in cultivation of kalmegh for high productivity, quality and better returns for farmers.

Background Globally the average age of the worlds’ population of older persons continues to upsurge and social support becomes increasingly relevant. Overall, in Malaysia, social support and networking prevalence was found to be lower among older persons at 30.76%. In view of the scarce data on social support and its association with smoking status and its associated factors among the older Malaysian population this study was conducted. Methods Data from the National Health and Morbidity (NHMS) 2018 survey on health of older Malaysian adults was analyzed. This was a cross sectional population-based study using a two-stage stratified random sampling design. Elderly population aged 60 years and above was selected. Data were collected were sociodemographic characteristics, smoking status, and social support. A validated Malay language, interviewer-administered questionnaire of 11-item Duke Social Support Index was applied for assessing social support among the elderly. A complex sampling design analysis was used for the descriptive statistics. The associated risk factors for social support were identified using Multiple Logistic Regression analysis. Results A total of 3923 elderly respondents participated in the study. The prevalence of good social support was significantly higher among the 60-69 years old respondents compared to the > 80 years old (73.1%, 95% CI :69.3% -76.5% vs 50.1 %, 95% CI:41.7 %- 58.6%).Multivariate logistic regression analysis showed that the odds of poor social support were 1.7 times (aOR: 1.72 % ,95%CI: 1.19 -2.48) higher for the respondents aged > 80 years old, than those aged 60-69 years. Respondents with no formal education were 1.93 higher odds of poor social support than the respondents with tertiary education (aOR: 1.93%, 95%CI: 1.13,3.30). Respondents with income < RM 1000 were 1.94 times more likely to have poor social support compared to respondents with income > RM 3000 (aOR: 1.94, 95% CI : 1.21 -3.13). Former smokers have good social support compared to current smokers (73.6% ,95% CI: 67.7-78.7 vs 65.1 %, 95%CI:58.4 -71.2). For current smokers, the odds of poor social support were 42.0% higher than for non-smokers (aOR: 1.42, 95% CI: 1.05 -1.91. Conclusion There is poor social support among the older persons who are current smokers, advancing age, no formal education and low income However, further longitudinal studies are needed to determine the exact effects of the studied variables. These findings could assist the policymakers to develop strategies at the national level to enhance social support among the older smokers to ensure cessation of smoking.

Interleukin-33 (IL-33), a member of the IL-1 cytokine family has been recently associated with the development of autoimmune diseases, including SLE. IL-33 is an alarmin and a pleiotropic cytokine that affects various types of immune cells via binding to its receptor, ST2. In this study, we determine the impact of intraperitoneal IL-33 treatments in young lupus, NZB/W F1 mice. Mice were treated from the age of 6 to 11 weeks. We then assessed the proteinuria level, renal damage, survival rate, and anti-dsDNA antibodies. The induction of regulatory B (Breg) cells and changes in gene expression were also examined. In comparison to the control group, young NZB/W F1 mice administered with IL-33 had a better survival rate as well as reduced proteinuria level and lupus nephritis. IL-33 treatments significantly induced IgM anti-dsDNA antibody, IL-10 expressing Breg cells, and alternatively induced M2 macrophage gene signatures. These results imply that IL-33 exhibit regulatory roles during lupus onset via the expansion of protective IgM anti-dsDNA as well as regulatory cells such as Bregs and M2 macrophages.

Bipolar plates significantly contribute in the development of the polymer electrolyte membrane (PEM) fuel cells technology due to their ability to produce high electrical conductivity based on type of materials used. Mismatching of inappropriate materials and manufacture may lead to the inferior performance of PEM fuel cells. Hence, material development was determined crucial to balance the overall performance of PEM fuels including the mechanical properties and electrical conductivity of the materials. Studies on conductive polymer composites (CPCs) offered filler orientation as an alternative method to enhance the overall performance of bipolar plate. Filler orientations permit an excellent conductivity network formation while controlling the filler alignment based on required applications. This paper reviewed various studies of filler orientations including materials used and methods of manufacture of CPC materials for the effective development of bipolar plate.

This study generalized the best copula to characterize the joint probability distribution between rainfall severity and duration in Peninsular Malaysia using two dimensional copulas. Specifically, to construct copulas, Inference Function for Margins (IFM) and Canonical Maximum Likelihood (CML) methods were specially exploited. For the purpose of achieving copula fitting, the derived rainfall variables by making use of the Standardized Precipitation Index (SPI) were fitted into several distributions. Five copulas, namely Gaussian, Clayton, Frank, Joe and Gumbel were put to the tests to establish the best data fitted copula. The tests produced acknowledged and satisfactory results of copula fitting for rainfall severity and duration. Surveying the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), only three copulas produced a better fit for parametric and semi parametric approaches. Finally, two consistency tests were conducted and the results had shown that Frank Copula produced consistent results.

User experience and user requirements are two independent approaches. User requirements address the customer's requirements and expectations for the solution, whereas user experience encompasses all aspects of how the user interacts with and uses the software. The software product should be easy to use and has usable features. Moreover, the additional value for the software is if the product has an attractive design or working environment that is in line with user behaviors, it can occur if integrate software requirements and user experience. Integration escalates developer productivity by focusing on features that meet the user's needs and expectations. That integration improves efficiency in software development by identifying and addressing problems that may arise during the development process, saving developer time and effort in developing software. The usage context of integration of user experience and user requirements in UX Journey contributes increase developer productivity and self-efficacy in developing software by focusing development on features that match the user needs, as well as increasing efficiency in overcoming problems that arise during the development process. UX Journey makes developers feel more confident in their ability to develop quality software.

This study assesses the impact of militarization, industrialization, technological innovation, and energy consumption on CO2 emissions in NATO countries, divided into "traditional" (Group 1) and "new member" states (Group 2), using data from 1985 to 2019. It identifies heterogeneity in effects and dependencies between the groups. Employing Pedroni and Kao panel cointegration tests, a long-term equilibrium relationship among the variables is confirmed. The analysis, using panel ARDL and GMM methods, reveals distinct outcomes for each group. In Group 1, military spending and energy consumption significantly increase CO2 emissions, while industrialization and technological innovation reduce them. Conversely, in Group 2, technological innovation and energy consumption raise emissions, whereas military spending and industrialization decrease them. The findings suggest Group 1 should strategize military expenditure and energy consumption to cut emissions, whereas Group 2 should focus on eco-friendly technology and efficient energy use to achieve environmental sustainability.

A flat-plate unglazed solar water heater (SWH) with polymer thermal absorber was developed and tested. Polymer thermal absorber as a viable alternative to metal thermal absorber that is found in most SWH systems. The performance of this polymer SWH system is measured based on inlet and outlet water temperature, water flowrate, ambient air temperature and solar irradiance. The polymer thermal absorbers are hollow Polyvinyl Chloride (PVC) pipes with 20mm external diameter and 3 mm thick, painted in black to enhance radiation absorption. The pipes are arranged in a rectangular spiral inward-outward opposing-flow (RSioof). The collector pipes are placed in a 1 m2 square enclosure with bottom insulation and reflective surface for better radiation capture. Water circulation is a closed loop with a 16-liter uninsulated storage tank, driven by a pump and controlled by valves to maintain a mass flow rate of 0.00031 to 0.00034 kg/s. The test was conducted under partially clouded sky from 9 am to 5 pm, with solar irradiance between 105 and 1003 W/m2 and 27-36oC ambient air temperature. The SHW produced outlet hot water at 65oC by mid-day and maintained the storage temperature at 63oC until the end of test duration. Photo-thermal energy conversion was recorded with 23% maximum value. Results indicate that a flat plate solar water heater with polymer thermal absorber in RSioof design can be an effective alternative to the metal thermal absorber solar water heater and can be further optimized with glazing and tube sizing.

To build a stable power factor and high output accuracy, it should use balanced active and reactive power, also used ultrasonic PWM was used with the frequencies (20–500 kHz). I also used a three-phase dynamic load at the output system and was connected to the compound splicing (CS) system this is a novelty. An oscillator circuit with 4Ghz as a microcontroller is a novelty, and designing ADC is utilized to increase accuracy, as well as contribute to the reduction of loss brought on by the characteristics of voltage source inverters (VSI), such as dead time determined by the excess voltage or voltage drop in the inverter, circumstances abnormal to the load current, such as short circuit current in the production phase, and so forth. The innovation relates to the inverter's load sensing circuit, current smoothing during operation, reaction, spontaneous power factor enhancement of the inverter, and correction of reactive power of passive devices. This invention contributes to the advancement of D.C to A.C power converter by the achievement of extremely low losses, excellent precision, and lightweight construction. Additionally, the accuracy ranges from 99%, and the total harmonic distortion (THD) of the voltage and current is (0.1%-0.8%). We Power MOSFET are used, along with FPGA to improve control over the creation of ultrasonic PWM signals, the programmable peripheral interface (PPI) 8255A for regulatory work. The marks serve as proof of this.

RNA-guided genomic transcriptional regulation tools, namely Clustered Regularly Interspaced Short Palindromic Repeats interference (CRISPRi) and CRISPR-mediated gene activation (CRISPRa), are a powerful technology for the field of functional genomics. Deriving from the CRISPR/Cas9 system, both systems comprise a catalytically dead Cas9 (dCas9) and a single guide RNA (sgRNA). This type of dCas9 is incapable of cleaving DNA but retains its ability to specifically bind to DNA. The binding of the dCas9/sgRNA complex to a target gene results in transcriptional interference. The CRISPR/dCas9 system has been explored as a tool for transcriptional modulation and genome imaging. Despite its potential applications and benefits, the challenges and limitations faced by the CRISPR/dCas9 system include the off-target effects, PAM sequence requirement, efficient delivery methods, and the CRISPR/dCas9-interfered crops being labeled as genetically modified organisms in several countries. This review highlights the progression of CRISPR/dCas9 technology as well as its applications and potential challenges in crop improvement.

Antibiotic resistance among bacterial pathogens is recognized as a major threat to human health worldwide. The emergence of multidrug-resistant bacteria can also be found in the community settings, apart from hospital environment, which indicates that reservoirs of antibiotic resistance genes do exist outside the hospital. The growth of antibiotic resistance is a consequence of bacterial adaptations in response to selective pressures. To survive in this hostile environment, bacteria develop defence mechanisms such as chemical modification of antibiotics, enzyme-catalysed antibiotic degradation, altered permeability, antibiotic efflux, mutation of target sites and biofilm formation, resulting in resistance to nearly all currently available antibiotics used in the clinical practice. The present review summarizes insights into the molecular mechanisms underlying the antibiotic resistance which is useful for planning strategies to combat antibiotic resistance and devise innovative therapeutic tools to fight against multidrug-resistant bacterial species.

Solar pavement technology has numerous benefits for advanced life and environmental protection, including reduced fossil fuel usage, reduction harmful emissions from conventional electricity generation and handy reliable electricity via solar energy. This paper aims to find an alternative for cost effective renewable energy sources is in conjunction with the principles of sustainability. This research studies whether the application of thermal energy harvesting road pavement using sustainable conductive piping such as stainless steel, copper, and aluminium are feasible in Malaysia. The scope of the paper is to optimize the suitable parameters for different materials of thermal energy harvester such as pipe material, pipe depth inserted into pavement, types of pipe arrangement, pipe spacing, and flow rate for maximum thermal energy extraction using numerical simulation. The simulation is testing under engineering software ANSYS Workbench 19.2 (Fluent) and Solidworks 2020 to develop project prototype from optimize thermal energy harvester. Thus, serpentine copper pipe shows the highest heat efficiency which is 32.22% with the temperature outlet of 327.35K (54.21°C) at the pipe located at 50 mm from the surface pavement with the pipe spacing of 80 mm centre-to-centre.

Thermal plasma technique is becoming prominent in the treatment of variety of waste ranging from municipal solid waste, incinerator residue, hospital waste, electronics waste and industrial sludge. Application of the new treatment technology to petroleum sludge requires information on the nature and characteristics of the sludge that will be use to optimize the treatment system. In this investigation, petroleum sludge obtained from Petronas Melaka was characterized for its physical and chemical features. Proximate and ultimate analysis as well as determination of elemental composition were carried out. The sludge was found to contain high moisture (78.91%), low ash (5.06%), low volatiles (5.52%) and high fixed carbon (10.51%). The sludge has a TOC of 54.48% and HHV of 23.599MJ/kg. Despite the high moisture content, the higher heating value (HHV) is high when compared to literature values. The high value of HHV may be associated with the high fixed carbon, low ash content and high value of TOC. The apparent density of the sludge is slightly lower. Fourteen heavy metals are detected in significant quantities. Proper waste management that will safely dispose the sludge is required. The waste disposal technique should take into cognizant the possibility of leaching of heavy metals into ground water on one hand and the gasification of lighter ones on the other.

Influential Observations, which are outliers in x direction, y direction or both, remain a hitch in classical regression model fitting. Spatial regression model, with peculiar nature of outliers due to their local nature, is not free from the effect of such influential observations. Researchers have adapted some classical regression techniques to the spatial models and yielded satisfactory results. However, masking or/and swamping remain stumbling block to such methods. We obtained the spatial representation of the classical regression measures of diagnostic in general spatial model. Commonly used diagnostic measure in spatial diagnostic, the Cook's distance, is compared to some robust methods, Hi2 (using robust and non-robust measures), and classification based on generalized residuals and diagnostic generalized potentials, ISRs-Posi and ESRs-Posi, with the help of the obtained spatial prediction residuals and the spatial leverage term. Results of simulation and applications to real data have shown the advantage of the ISRs-Posi and ESRs-Posi due to classification of outliers over Cook's distance and non-robust Hsi12, which suffer from masking, and robust Hsi22 which suffer from swamping in general spatial model.

This paper discusses the development process regarding a group of four Augustana College seniors' research. The project is a mobile app for Android built-in Android Studio called Augustana Health and Dining. This application will improve the dining experience at Augustana College, provide additional health metrics for personal use and promote healthier lifestyles. The app features the menus of various on-campus dining areas, with calories, allergens, and other essential food information. It also includes a profile section that will display campus meal credits and a calorie counting metric that can be used to track calories consumed to display this information to users so they can make more informed choices on their meals and health.

Abstract: The COVID-19 pandemic has disrupted global energy markets and caused significant socio-economic impacts worldwide. The pandemic has also impacted the energy sector, with demand for energy reducing due to lockdowns and reduced economic activity. Hence, this paper aims to provide a comprehensive and analytical review of the impact of COVID-19 on the energy sector and discuss the potential role of artificial intelligence (AI) in mitigating some of these effects. This review examines the changes in energy demand patterns resulting from the pandemic and the implications for the energy industry, including the shifts in policymaking, communication, digital technology, energy conversion, environmental, energy market, and power system operation. The analysis of the energy pattern is discussed according to the timeframes which include pre-, mid-, and post-pandemic periods. Furthermore, we explore how AI can be used to improve energy efficiency, optimize energy use, and reduce energy wastages. The potential for AI to contribute to developing more efficient and sustainable energy systems has also been addressed. Lastly, we highlighted AI’s challenges, which play a significant role in the energy sector's response to the COVID-19 pandemic. The recommendations for AI applications in the energy sector for the transition to a more sustainable energy future are outlined. Information corroborated in this review is expected to provide important guidelines for crafting future research areas and directions in preparing the energy sector for any unforeseen circumstances or pandemic-like situations.

The resource curse indicates that economic growth performs poorly in countries with significant natural resources. Nevertheless, certain countries rich in energy managed to protect their resource riches in the long run. It is necessary to enforce effective policies in resource-rich countries to fully leverage the advantages which can come from the abundance of natural resources. This study aimed to evaluate how oil-rich countries would avoid resource flows by successful fiscal and management policies. By taking the guidance of Norway and implementing fiscal policy focused on tax rules on its oil management, it is proposed that oil-exporting countries benefit significantly. The framework attempts to mitigate this resource curse and utilise oil revenues in the interest of the country.

The COVID-19 pandemic creates anxiety among hospitalised SARS-CoV-2 patients. Therefore, this study aims to determine the prevalence of anxiety and its associated factors among stable inpatient COVID-19 patients in Malaysia. A cross-sectional study was conducted using a web-based online survey involving 401 patients from Malaysia's leading COVID-19 hospitals from 15th April until 30th June 2020 who were chosen using quota sampling. General Anxiety Disorders 7 items (GAD-7), Coping Orientation to Problems Experienced Inventory (Brief-COPE) and Socio-demographic profile questionnaire were used. Descriptive analysis and multiple logistic regression were performed using SPSS v23 to determine the prevalence of anxiety and its associated factors. The results showed that prevalence of anxiety was 7.0%. Multiple logistic regression analysis revealed that female (p < 0.05), fear of infection (p < 0.05), lack of information (p < 0.05), maladaptive coping mechanism of behavioural disengagement (p < 0.001) and self-blame (p < 0.001) were significantly associated with anxiety. Whereas adaptive coping mechanisms via instrumental support (p < 0.001) was a significant protective predictor of anxiety. COVID-19 infection has had a significant influence on the mental health of patients. Findings in our study provides baseline findings on prevalence of anxiety among stabilized COVID-19 inpatient in Malaysia. Despite the relative low prevalence, the data has the potential to improve the present mental health monitoring system and the deployment of suitable treatments in dealing with similar circumstances