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Utilisation Of Superheated Steam And Torrefacto Roasting On Quality Attributes Of Black Seed (Nigella Sativa) For Beverage Application
(2024-09)
Veeriah, Harivaindaran K.
Nigella sativa, known as black seed, has many health benefits and is typically roasted prior to consumption. This causes detrimental quality loss, thus, an innovative method such as superheated steam (SHS) and torrefacto roasting may be advantageous. This research aims to develop a beverage from SHS torrefacto (TR) roasted black seeds. In the first phase, SHS was applied to black seeds at 150℃, 200℃ and 250℃ for 10, 15, and 20 mins at each temperature then compared to convection roasting at the same parameters for lipid oxidation, proximate, antioxidants, and essential oils. Results indicated that SHS roasted seeds yielded more oil (24.83 % vs only 23.23 % oil for convection) and had better peroxide value (highest value for convection, 84.00 versus SHS, 48.00 meq O2/kg of oil), p-anisidine value (highest value; for convection, 28.36 versus SHS, 23.73), FRAP values (SHS; 327 to 435 mM FeSO4/g sample, convection; 301 to 356 mM FeSO4/g sample), and DPPH scavenging capacity (SHS; 92.45 to 69.97 % inhibition, convection; 92.08 to 65.81 % inhibition). Results also indicate unsuitable extraction method and poor seed quality since oil oxidative analysis results were all above standard acceptable levels. Convection roasting also caused loss of thymoquinone, an important characteristic component of black seed essential oil. In the second phase, black seeds were TR and SHS roasted at 220℃ for 10 min. This roasting time and temperature was derived via response surface methodology for maximum antioxidant capacity.
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
(2024-09)
Guo, Yueling
In the current development of Artificial Intelligence, Satisfiability plays a crucial role as a symbolic language of Artificial Intelligence for the transparency of black box models. However, the main problem of existing Satisfiability is the lack of combined logical rule, so the benefits of combined logical rule have not yet been investigated. The rule namely Y-Type Random 2-Satisfiability is proposed by combining the systematic and non-systematic logical rule. Next, the newly proposed logical rule as the symbolic instruction was implemented into the Discrete Hopfield Neural Network to govern the neurons of the network. Experimental results demonstrated the compatibility of the proposed logical rule and the Discrete Hopfield Neural Network. Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. During the retrieval phase, a new activation function and Swarm Mutation were proposed to ensure the diversity of the neuron states. The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. The developed logic mining will be used to analyze the Alzheimer's Disease Neuroimaging Initiative dataset.
Explaining Eating Disorder Behaviour Among Chinese University Students Using The Extended Theory Of Planned Behaviourexplaining Eating Disorder Behaviour Among Chinese University Students Using The Extended Theory Of Planned Behaviour
(2024-09)
Gao, Zeng
Adolescents’ unhealthy eating leads to them to adopt certain measures such as a diet, fasting and other behaviours that are likely to reduce body weight. The measures in turns lead to eating disorders and series of complications, such as impaired digestive system function, endocrine disorders, amenorrhea, hypoglycaemia, malnutrition, or physiological damage to various organ systems, and even life-threatening. It will affect the physical and mental health of the young and incurs high medical costs in one's country. In the long term it will be a physical and mental health issue that will increase medical expenses to treat it. Therefore, using the Theory of Planned Behaviour, this study was conducted to identify the factors that influence eating disorders among university students in the province of Gansu, China. Data was analysed using IBM SPSS and PROCESS 4.0 to answer all research questions developed. Results showed that there was significant difference in attitude towards physical activity, subjective norm, perceived behavioural control, body shape, self-esteem, and intention to engage in physical activities. between gender and body mass index (BMI). Gender and BMI also moderate the relationship between intention, body shape, self-esteem, and eating disorder. However, different gender and BMI in different attitudes (AT), subjective norms (SN), perceived behavioural control (PBC), body shape (BS), self-esteem (SE), and intention (IN) scores have significance. Family incomes only have a significant in self-esteem (SE).
Multi-layer Radiation Shielding Design For Compact Proton Therapy System Using Monte Carlo Simulation
(2024-09)
Aliyah, Fitrotun
Proton therapy has emerged as a highly effective treatment for various cancers due to its precision in targeting tumor cells while minimizing radiation exposure to surrounding healthy tissues. However, the design of compact proton therapy facilities poses significant challenges, particularly in terms of shielding requirements, cost, and environmental impact. This study aims to develop a novel shielding design for proton therapy systems that complies with regulatory dose limits while reducing the overall cost and footprint by utilizing alternative materials through a multilayer structure model. The research begins with the characterization of natural aggregate and steel slag as potential alternative materials for concrete admixture, then continues with experimental evaluations of radiation attenuation properties using PuBe, LINAC, and CT-Scan as radiation sources. To further develop and optimize the shielding design, the study employed Monte Carlo simulations using the Particle and Heavy Ion Transport code System (PHITS). These simulations facilitated the creation of innovative shielding configurations, incorporating both single-layer and multilayer structures composed of Portland concrete (PC), steel slag concrete (SSC) , iron (Fe), borated polyethylene (BPE), and recycled high-density polyethylene (HDPE). The experiment results demonstrate that steel slag concrete offers superior radiation shielding performance compared to conventional concrete. The PHITS simulation results demonstrate that the material combination model of PC-SSC on the treatment room wall and PC-SSC-Fe-HDPE on the Maze 1 wall is the optimal configuration with ambient dose equivalent rate value ranging from 13 to 773 mSv/year.
Intrinsic self-healable and recyclable rubbers based on ionic crosslinked network
(2023-08-01)
Mohd Hafiz Bin Zainol
In modern technologies, rubbers play a significant role to serve various main manufacturing industrial products, for instance vehicles tires, damping systems, wearable electronics, safety gears and many more. In order to fabricate a component which offers high toughness, great damping properties, chemical and thermal stability, rubbers need to be chemically crosslinked through vulcanization process. However, vulcanized rubber with permanent covalent crosslinked network cannot be reprocessed, reshaped or recycled. As a result, waste rubber products have become a serious threat towards ecological and environmental systems. This problem has driven towards emerging of a self-healing rubber technology which has the ability to restore the damage and can be recycled and reprocessed at the same time. The work carried out started with investigation of the potential of self-healing non polar natural rubber (NR) based on zinc thiolate ionic network. The Zn2+ is a potential metal ion candidate for formation of reversible ionic network, thus self-healing ability, recyclability and reprocessing ability would be achievable. In the next work stage, carboxylated nitrile butadiene rubber (XNBR) was chosen to investigate self-healing ability for polar rubber. The strategy is to generate massive Zn2+ salt bonding between zinc thiolate and COOH group on XNBR in order to create electrostatic interaction that allow thermo reversible ionic network. For NR, the samples achieved 100% self-recovery within 10 minutes at room temperature. Evidence for reversible metal thiolate ionic networks was provided by Fourier Transform Infra-Red (FTIR) and swelling density. Followed by mechanical performance assessment which include tensile test, tear strength, fatigue lifespan and creep behaviour. As for the recycled and reprocessed assessment, the vulcanised rubber was recycled and reprocessed for few times and the tensile test, scanning electron microscope (SEM) and welding test were evaluated. Interestingly the rubber was able to be reprocessed for three times and recovered its initial mechanical performance up to 60%. For XNBR, the sample achieved 97.87% self-recovery within 10 minutes at 150ºC. Evidence for thermo reversible ionic network was provided by FTIR and swelling density assessment. Followed by mechanical performance assessment which include tensile test, tear strength, fatigue lifespan and creep behaviour. As for recycle and reprocessing assessment, the results showed that XNBR were able to be reprocessed for three times with significant mechanical performance recovery up to 70%. From the work carried in this research, it was found that NR self-healing rubber enables more potential for final application as the healing occur at room temperature. For potential application stage, NR self-healing rubber was chosen as candidate material for puncture proof application. The self-healing natural rubber was able to recover the puncture spot ranging from 0.8 mm to 2 mm nail diameter at 100% recovery rate throughout pressure test, temperature test, repeatability test and stability test. Evidence for healed punctured spot was provided by SEM. Both self-healing NR and XNBR had exhibit significant performance on self-healing capabilities and mechanical properties. While on puncture-proof application, self-healing NR had shown a promising performance throughout all the test that has been conducted in this research.