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MSS414 - Topics in Pure Mathematics (Manifolds and Topology)
Get PDFFirst Semester Examination 2023/2024 Academic Sessio
Abundance And Distribution Of Plastic Debris In Beach Sediment And Seawater Of The Northern Straits Of Malacca
Get PDFPlastics account for 60% - 80% of marine debris worldwide and Malaysia is the top three plastic polluter country in the world through river pathway to marine environment in 2021. A comprehensive database of the status of plastic pollution in Malaysia is needed to help in achieving better management of plastics, such as the plan in Malaysia’s Roadmap toward Zero-Single-Use Plastics 2018-2030 and Plastics Sustainability Roadmap 2021-2030. This study aims to record the abundance of macro- (> 2.5 cm) and meso-plastic (0.5 – 2.5 cm) debris at selected beaches and microplastics (<0.5 cm) at selected sea surface in the northern Straits of Malacca. All study sites are publicly accessible beaches (Pulau Songsong, Teluk Aling, and Pulau Gazumbo) except Pulau Lembu which is in a Marine Protected Area (MPA). The debris was collected from predetermined transects on the beach and categorised according to its size, form and economic market segments in Malaysia. Most of the macro- (53 – 75% of total mass; p=0.0277, α<0.05) and meso-plastics (53 – 80% of the total number) were accumulated at the backshore area. Public beaches such as Pulau Gazumbo (7.32 ± 9.90 g/m2) and Pulau Songsong (9.77 ± 11.35 g/m2) recorded the highest mass of macroplastics per area by zone. Teluk Aling recorded the lowest mass of macroplastics per area by zone (3.58 ± 3.21 g/m2) but the highest in mesoplastic (0.56 ± 0.60 item/m2). By number, the highest number of macroplastics per area by zone was found at Teluk Aling (1.10 ± 1.29 item/m2) and Pulau Lembu (1.19 ± 0.30 item/m2), while the lowest was found at Pulau Gazumbo (0.44 ± 0.61 item/m2)
Layered Metal Hydroxides Exfoliation Assisted By Sugar Molecules And Physicochemical Characterisation Of The Nanosheets
Get PDFThe exfoliation of layered metal hydroxides is highly favourable for the formation of single layer layered double hydroxide (LDH) and layered zinc hydroxide (LZH) nanosheets due to their unique chemical, thermal, optics, and biological properties. In this study, the exfoliation of layered double hydroxide (LDH) and layered zinc hydroxide (LZH) were performed using sugar molecules as an exfoliating agent in DMSO and water. The X-ray diffraction (XRD) suggest that LDH were successfully exfoliated and formed single layer nanosheet, indicated by the formation of single peaks. It is demonstrated that XRD patterns of LDH using 1g sucrose in DMSO via co-precipitation, reconstruction, and hydrothermal show the best diffraction pattern with only a single peak formed in all the exfoliated samples. The structural information of the exfoliated LDH in three different phases is further studied using XRD to reveal the extent of the exfoliation process. We examined the crystalline phase of LDH in different stages of liquid exfoliation; suspension, semi-dry suspension and dried solid samples. XRD data shows one broad peak for all the LDH exfoliated samples at 2θ = 23.9,22.4, and 22.3° respectively, which correspond to the characteristic (003) basal reflection of LDH single layers. These single peaks indicate the formation of LDH nanosheets. On the other hand, only XRD pattern of LZH exfoliated with 1g sucrose in water via hydrothermal exhibit the single peak while co-precipitation and reconstruction are not. Thus, only hydrothermal method in LZH indicates formation of nanosheets
Synthesis, Characterization And Theoretical Studies Of Chalcone And Ethynylated Schiff-base Derivatives For Potential Light Emitting Applications
Get PDFThe photophysical and electrochemical characteristics of organic materials are being studied actively to enhance charge transport for high-performance OLEDs. Inspired by highly π-conjugated organic materials, two series of new compounds featuring of donor-pi-acceptor (D-π-A) configuration namely chalcone derivatives (1-6) and ethynylated Schiff-base derivatives (7-12) compounds were succesfully designed and synthesized using Claisen-Schmidt condensation and Schiff-base condensation methods, respectively. The crystal structures of all compounds were solved and refined using single-crystal X-ray diffraction analysis. Density Functional Theory (DFT) calculations confirmed the optimized molecular geometries are comparable to the experimental results. The crystal packing diagrams of all compounds revealed intermolecular interactions including C—H···O, N—H···N, C—H···π and π···π interactions, which contribute to charge transfer and structural stability. The functional groups and molecule’s chemical structure of all compounds were quantitatively identified by Fourier Transform Infrared (FTIR) and 1H and 13C Nuclear Magnetic Resonance (NMR) spectroscopy analyses, respectively. The UV-Vis spectra revealed that all compounds exhibit maximum absorption wavelengths within the semiconductor range, with values between 2.52 and 2.94 eV for compounds (1-6) and 2.73 to 2.85 eV for compounds (7-12)
An Alternative In Silico Method To Predict Passive Membrane Permeability Of Potential Spsb2-Inos Inhibitor
Get PDFThe SPRY (SPla and the RYanodine Receptor) domain of the SOCS (Suppressors of Cytokine Signalling)-box protein 2 (SPSB2) was found to be responsible for the proteasomal degradation of inducible nitric oxide synthase (iNOS). The knockdown of SPSB2 in mice was found to increase iNOS expression and enhance the killing of persistent pathogens such as Mycobacterium tuberculosis, suggesting that inhibitor of SPSB2-iNOS interaction is a potential anti-infective agent. To date, several peptidic SPSB2-iNOS inhibitors have been reported. These peptides (including CP2), however, were found to have poor cell permeability, resulting in their poor activities in live macrophages. Therefore, this study aimed to propose a potential cell-permeable inhibitor of SPSB2-iNOS via in silico approach. To achieve the aim, a new bicyclic peptide, CPP9CP2 was designed, and molecular dynamics (MD) simulations were used to predict its membrane permeability. Conventional molecular dynamics (MD) analysis techniques for predicting peptide translocation, such as comparing free energy profiles (PMF) and evaluating the relationship between water pore formation and peptide penetration efficiency from steered MD simulations, were applied to three cell-penetrating peptides (TAT, CPP1, and CPP9) and one known non-cell-permeable peptide, YDEGE. However, these methods proved less effective in accurately reproducing reported in vitro experimental results. Specifically, despite YDEGE being non-cell-permeable, it did not show the highest PMF value and formed water pores similarly to TAT and CPP9, making it difficult to distinguish between genuine pore formation and simulation artifacts
Phytochemistry Of Calophyllum Havilandii P.F. Stevens And Calophyllum Lowei Planch. & Triana And Their Biological Activities
Get PDFPlants from the genus Calophyllum (Calophyllaceae) is a treasure trove of various interesting phytochemicals with impressive structural diversity. These phytochemical constituents were often discovered as derivatives in the classes of phenolics, such as xanthones, coumarins, chromanones, phloroglucinols, and flavonoids. Many of them are proven to exhibit wide range of pharmacological as well as biological activities, such as cytotoxic, anti-viral, anti-inflammatory, and anti-microbial. In this study, the process of extraction, isolation, and characterization of phytochemicals were conducted on the stem bark of two endemic Malaysian Calophyllum species from Sarawak, namely Calophyllum havilandii and Calophyllum lowei. All of the isolated phytochemicals were characterized and elucidated using extensive spectroscopic techniques such as MS, IR, UV, and NMR
Characterization Of Lignocellulosic Film Made Of Unbleached Pulp Solutions And Cellulose Nanowhisker From Oil Palm Empty Fruit Bunch
Get PDFStudies of bio-nanocomposites using sustainable green materials from biomass waste are presently gain the attention worldwide. Lignocellulosic biomass in the form of plant materials offers the most abundant renewable resource in replacing traditional fossil resources. In the present study, lignocellulosic biomass films were prepared directly from oil palm empty fruit bunch OPEFB pulp solutions in DMAc/LiCl without additional film-forming additives incorporated with 1%, 3%, and 5% via solvent casting method using various types of OPEFB CNW isolated using different types of delignification treatment and then casted into films. Mechanical behaviour, morphological properties, thermal properties, and functionality groups and the effect of adding the OPEFB CNW into the bio-nanocomposites films were then evaluated by infrared spectroscopy (FTIR), contact angle, mechanical analysis, X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric (TGA) and differential scanning calorimeter (DSC). The semi-transparent film with a yellowish colour was obtained due to the presence of lignin. The results showed good compatibility of lignocellulosic material and CNW which is responsible for the increasing in mechanical properties of the film. This also led to less hydrophilicity of the film as the filler loading increasing and no big difference between the effects of two types of CNW used. FTIR analysis spectra show a similar pattern with only different in the intense and broadening of the peaks
Flood Prediction Based On Deep Learning Networks With Variational Mode Decomposition
Get PDFClimate change increases the frequency of extreme weather events, causing river overflow floods that threaten human safety and ecosystems. Traditional flood prediction models face challenges due to fluctuations in water levels from topography and rainfall, leading to less accurate forecasts. This thesis aims to enhance flood prediction accuracy by developing and evaluating three new machine learning models that incorporate data decomposition, feature selection, and parameter optimization. The first two models use water level data for each hour. The first model utilizes hydrological data by integrating the Variational Mode Decomposition (VMD) method to reduce disturbances, along with Directional Bidirectional Long Short-Term Memory (BiLSTM) optimized with attention for forecasting purposes. The second model enhances prediction effectiveness by incorporating meteorological data specifically rainfall, humidity, and wind speed. This model emphasizes the benefits of VMD component classification and feature selection by considering water level changes to categorize Intrinsic Mode Functions (IMFs) obtained from the VMD method and using feature selection through the Pearson correlation method. The third model uses an optimized Gated Recurrent Unit - Temporal Convolutional Network (GRU-TCN) to forecast daily data at point estimates and confidence intervals. This model improves Kernel Density Estimate (KDE) predictions to assess forecast uncertainty more accurately and enhance model reliability. These three proposed models can overcome the weaknesses of traditional methods by utilizing real data from the Yangtze River station