Green fabrication of lanthanum doped zinc oxide nanoparticles (La-ZnONPs) via pineapple extract: Effects of calcination temperature on photocatalytic properties

Disposal of pineapple waste is one of the main concern towards sustainability of an environment. In this work, the usage of pineapple waste in the synthesis of Zinc oxide nanoparticles (ZnONPs) could assist to reduce the waste and give us chance to utilize the waste in a useful manner. ZnONPs were produced via green approach employing the extract derived from pineapple waste peels, serving as reducing and stabilizing agent. This article demonstrates the effect of calcination temperatures on the La as a dopant for ZnONPs fabrication. Doping of the materials facilitated the nanoparticles to increase their stability by incorporation of some rare earth metals such as La. The materials (La-ZnONPs) with different calcination temperature were fabricated by co-precipitation method and thoroughly characterized by various spectroscopic techniques like Fourier Transform Infrared Spectroscopy (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopy – Energy Dispersive X-ray (SEM-EDX), and UV-Vis. Morphologically evidence given in SEM images that hexagonal shape converted into unique tiny flower images as the dopant added and calcination temperature increased wherein a gradual decrease from 27.83 to 23.02nm in crystallite size was noted with correspondence of rise at calcination temperature in doped La-ZnONPs. The lowest bandgap energy (3.11) with highest surface area along with the lowest crystallite size was obtained for La-ZnONPs calcined at a temperature of 600°C

Layar Hijrahku

Di ufuk waktu yang merangkap Maghrib, ku panjatkan doa kepada Khalikul alam, bersama pengajaran yang kujadikan karib, pelayaran setahun bermalam-malam, ada badai,ada tenang, ada luka yang mendalam, ada syukur yang menenangkan. Di tengah pelayaran kehidupan, aku hanyut kadangkala, buta tak nampak ribut di depan, layar robek kerana alpa, kompas iman keliru arah, namun kasih-Nya dengan ibrah, sentiasa meniup angin pulang tidak menyerah

Kolaborasi UAD–UII–FTKKP UMPSA jayakan CSR di SMART Kuantan

KUANTAN, 17 Jun 2025 - Sekolah Menengah Abdul Rahman Talib (SMART) Kuantan telah menjadi lokasi pelaksanaan program tanggungjawab sosial korporat (CSR) anjuran bersama delegasi Universitas Ahmad Dahlan (UAD) dan Universitas Islam Indonesia (UII), dengan kerjasama strategik daripada Fakulti Teknologi Kejuruteraan Kimia dan Proses (FTKKP), Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) yang bertindak sebagai jambatan penghubung antara institusi pendidikan tinggi dari Indonesia dan sekolah angkat UMPSA. Menurut Pensyarah FTKKP, Ts. Dr. Azizul Helmi Sofian, program itu melibatkan seramai 60 pelajar Tingkatan 4 SMART Kuantan dalam pelbagai aktiviti interaktif berasaskan kemahiran dan inovasi

Nano-enhanced biocarriers: Ferric oxide-modified chitosan and calcium alginate beads for improved fermentation efficiency and reusability in a bubble column bioreactor

Chitosan beads (CB) and calcium alginate beads (CAB) are widely used for immobilizing Saccharomyces cerevisiae in fermentation, but their low mechanical strength and limited surface area reduce ethanol yield. To overcome these limitations, ferric oxide (Fe₂O₃) nanoparticles were incorporated into CB and CAB to enhance both mechanical strength and surface area. The modified carriers were employed for Saccharomyces cerevisiae immobilization in a bubble column bioreactor under semi-batch fermentation conditions at 35 °C, an air flow rate of 0.01 L/min, and pH 4.0 for 15 h. The Fe₂O₃ nanoparticles incorporation significantly improved the rupture forces of CB and CAB, increasing from 2 ± 0.05 N to 8 ± 0.5 N and 2 ± 0.05 N to 9 ± 0.07 N, respectively. The surface area of CB increased from 18 ± 0.3 m2/g to 48 ± 0.2 m2/g, while CAB increased from 2 ± 0.2 m2/g to 50 ± 0.1 m2/g, leading to enhanced cell adsorption from 1.13 × 10⁸ to 1.10 × 10⁹ cells/mL Consequently, ethanol yield improved from 37 ± 0.28% to 45 ± 1.23%. Unlike unmodified CB and CAB, which exhibited significant rupture after five reuse cycles, the modified beads retained their structural integrity and activity, demonstrating their durability for yeast immobilization and reuse. This approach offers a promising strategy for enhancing fermentation efficiency and carrier stability in ethanol production

The Malay Rulers: Their Position and Article 38(4)

MALAYSIA is a monarchy that safeguards constitutional supremacy. Despite their prominent status in the nation, the role of the Malay Rulers remains a topic of scholarly inquiry and public discourse. Their involvement in defining the rule of law is crucial, especially in addressing modern constitutional challenges. The evolving landscape of Malaysian society, shaped by exposure to foreign doctrines, political conflicts, and religious diversity, presents new challenges for the Malay Rulers and the Conference of Rulers at the federal level. Understanding their constitutional roles and responsibilities requires a right interpretation of their existence, position, and influence in the nation’s governance

The implementation of long-short term memory for tourism industry in Malaysia

Across the world, tourism is known as the largest contributor towards economy and the fastest developing industry. It has the capability of generating income, creating job opportunities and help people to understand the culture diversity of other countries. Therefore, tourism demand forecasting is really needed to help the practitioners involved as well as government in pricing setting, in assessing future requirements of capacity to fulfil the customers’ demand or in making wise decisions on whether to explore new market or not. This study focuses on tourism demand forecasting based on the number of tourist arrival using recurrent neural network (RNN), which is long-short term memory (LSTM) model. The data used in this study is historical data of number of tourist arrivals in Malaysia before the onset of Movement Control Order (MCO) starting from January 2000 to February 2020 due to the COVID-19 outbreak. The data set was divided into two subsets, training and testing data sets based on ratio 80:20. The objective of this study is to determine an accurate forecasting model especially in tourism industry in Malaysia. The forecast evaluation implemented to predict the error of each model are Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) and the analyses for this model was performed by using Python software. Based on the results obtained, the LSTM model was considered as one of the accurate prediction methods for tourism demand in Malaysia due to the least error produced. It is hoped that these results can help the government as well as practitioners in tourism industry to make a right judgement and formulate better tourism plans in order to minimize any consequences in the future

Associate Professor Dr. Mohd Herwan Sulaiman: Innovator in Electrical Engineering and Artificial Intelligence

PEKAN, 14 March 2025 – In the world of electrical engineering and artificial intelligence (AI), the name Associate Professor Dr. Mohd Herwan Sulaiman is increasingly recognised as an active researcher in power system optimisation and AI innovations in the energy sector. Hailing from Johor, he currently serves as the Deputy Dean (Research and Postgraduate Studies) at the Faculty of Electrical and Electronics Engineering Technology (FTKEE), Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA)

Shallow shotgun sequencing of healthcare waste reveals plastic-eating bacteria with broad-spectrum antibiotic resistance genes

The burgeoning crises of antimicrobial resistance and plastic pollution are converging in healthcare settings, presenting a complex challenge to global health. This study investigates the microbial populations in healthcare waste to understand the extent of antimicrobial resistance and the potential for plastic degradation by bacteria. Our metagenomic analysis, using both amplicon and shallow shotgun sequencing, provided a comprehensive view of the taxonomic diversity and functional capacity of the microbial consortia. The viable bacteria in healthcare waste samples were analyzed employing full-length 16S rRNA sequencing, revealing a diverse bacterial community dominated by Firmicutes and Proteobacteria phyla. Notably, Proteus mirabilis VFC3/3 and Pseudomonas sp. VFA2/3 were detected, while Stenotrophomonas maltophilia VFV3/2 surfaced as the predominant species, holding implications for the spread of hospital-acquired infections and antimicrobial resistance. Antibiotic susceptibility testing identified multidrug-resistant strains conferring antimicrobial genes, including the broad-spectrum antibiotic carbapenem, underscoring the critical need for improved waste management and infection control measures. Remarkably, we found genes linked to the breakdown of plastic that encoded for enzymes of the esterase, depolymerase, and oxidoreductase classes. This suggests that specific bacteria found in medical waste may be able to reduce the amount of plastic pollution that comes from biological and medical waste. The information is helpful in formulating strategies to counter the combined problems of environmental pollution and antibiotic resistance. This study emphasises the importance of monitoring microbial communities in hospital waste in order to influence waste management procedures and public health policy. The findings highlight the need for a multidisciplinary approach to mitigate the risks associated with antimicrobial resistance and plastic waste, especially in hospital settings where they intersect most acutely

Photocatalysis of dyes: operational parameters, mechanisms, and degradation pathway

Photocatalysis is an advanced oxidation process (AOP) that has significant attention to the degradation of organic pollutants. Although most literature on photocatalysis mainly focuses on the basic photocatalytic mechanisms, photocatalyst designs, and operational parameters, this research aims to delve deeply into the various process parameters and mechanisms under different conditions. It explores intermediates produced by dye photocatalysis and the proposed degradation pathways. This review systematically analysed relevant literature based on various databases, studying various process parameters and mechanisms as well as utilising analytical techniques (spectroscopy and chromatography) to synthesise key themes and findings in photocatalysis. This review revealed significant advancements in photocatalysis, highlighting the photocatalytic process has 4 domain steps in degradation pathways, including demethylation, ring shortening, ring opening, and mineralisation. Previous studies indicated the emergence of new peaks at 331 nm and 370 nm in UV-Vis analysis for MB, while hypsochromic shifts for RhB were attributed to the processes of demethylation and de-ethylation, respectively. In short, this review underscores the potential of dye photocatalysis to revolutionise green analytical practices and emphasises the importance of sustainable approaches in analytical methodologies, focusing on innovative and eco-friendly analytical methods aligned with the scope of the journal

Email spam classification based on deep learning methods: A review

Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. This review aims to identify the various deep learning techniques used for email spam, their effectiveness, and areas for future research. By synthesizing the outcomes of pertinent studies, this review delineates the strengths and drawbacks of various approaches, offering valuable insights into the challenges that must be tackled to enhance the precision and efficacy of email spam classification