YSN-ASM International Scientific Virtual Conference (ISVC) 2021 – Abstracts

This is the compilation of accepted abstracts from YSN-ASM International Scientific Virtual Conference (ISVC) 2021 organised on 29 March - 1 April 2021.

A Systematic Literature Review of Multi-Criteria Analysis Model Methods on Sustainability Weighting for Ethanol Plant

The sustainability weighting is crucial as it is practically implemented into sustainability evaluation, especially in industrial development. Sustainability is about the interconnection between three aspects of sustainability impact such as economic impact, environmental impact, and social impact. Multi-Criteria Analysis (MCA) model play important roles to measure the weighting for each impact according to the scenario and criteria selected based on scientific rules and robust statistical methods. However, there were insufficient studies on the existing literature sustainability weighting model from MCA method for the ethanol plant. Hence, the present paper demonstrates a systematic literature review of MCA model methods on sustainability weighting for the ethanol plant. There are two steps involved in systematic literature reviews: formulation of the research question and systematic searching strategies consisting of identification, screening, eligibility, quality appraisal, data abstraction and analysis. The review is based on leading databases; Scopus – ScienceDirect, Springer, Taylor and Francis, and one supporting database – Google Scholar. From the review, the preferable MCA weighting model for sustainability evaluation of ethanol plants is ‘integrated Analytical Hierarchy Process (AHP)’ rather than ‘standalone AHP’. The paper offered a significant contribution to the body of knowledge and sustainability evaluation purposes.

Trends in clinical prediction models of stroke outcomes research outputs: a bibliometric analysis

Stroke is one of the leading causes of death and disability globally. Clinical models have been reported to predict stroke outcomes and thus, potentially guide clinical decisions. This study aimed to describe the global trends of research in clinical prediction models of stroke outcomes. A bibliometric analysis was conducted on clinical prediction models of stroke outcomes publications reported in Scopus from 2010 to 2019. Bibliographic data were extracted, quantitatively analysed, and visualized using VOSviewer software. A total of 6,364 publications were included in the final analysis. The number of published studies had steadily increased since 2010. “Stroke” and “Journal of Stroke and Cerebrovascular Diseases” were the journal with the most publications and citations. The most cited publications were by Lip et al. (2010) and Berkhemer et al. (2015). The United States of America (USA), China together with their institutions contributed most to the pool of publications in the field. Our study showed a steady increasing research activity in the clinical prediction of stroke outcomes since 2010, with saturation in recent years. The top articles were published in high-quality stroke-related journals and by high-income countries. There is a need to reinforce research capacities in the field by developing collaborative networks.

The Sensory Evaluation of Choy Sum (Brassica chinensis L. var. parachinensis) Grown with Mineral and Organic Fertiliser in Kampar, Perak, Malaysia

Consumers perceive organic vegetables as better in taste and quality compared to conventional vegetables. Therefore, this study aims to determine the sensory difference of choy sum (Brassica chinensis L. var. parachinensis) grown with organic fertiliser and mineral fertiliser without the input of synthetic pesticides. A survey was carried out to determine Malaysian consumer sensory perception on organic and conventional leafy vegetables. The choy sum was planted in a Complete Randomised Block Design (CRBD), with input of organic fertiliser (T1, rate: 1500kg/4046m2) and mineral fertiliser (T2, rate: 63kg/4046m2) in a 7-day interval. It was harvested for sensory evaluation at maturity. Seventy-five untrained panellists were selected for the sensory test. The moisture content was analysed using oven drying method, while the sugar and colour analysis was carried out using a brix refractometer and a spectrophotometer, respectively. The survey confirmed that most consumers believe that the sensory attributes of organic vegetables are better than conventional vegetables. However, sensory evaluation shows that there is no significant difference (P > 0.05) in all sensory attributes tested except for greenness. T2 were significantly greener (P < 0.05) than T1. There were also no significant differences (P > 0.05) found between the treatments in the sugar, moisture and colour analysis.

The Role of Autophagy and Mitophagy in Huntington’s Disease

Huntington’s disease (HD) is an inherited autosomal-dominant neurodegenerative disorder that occurs due to mutations in the polyglutamine expansions of the Huntingtin protein (Htt). HD is characterised by the loss of cognitive and motor functions, as well as the development of emotional and psychiatric disturbances. The HD pathology is manifested through the cellular changes that arise due to the toxic functions of mutant Htt (mHtt). Autophagy is a lysosomal pathway that functions to remove damaged intracellular components while mitophagy is a selective form of autophagy involving mitochondria; and PINK1/Parkin-mediated mitophagy is the most well-understood pathway. Mitochondrial dysfunction and defects in mitophagy can be linked to the pathogenesis of HD. Previous research has shown that the presence of mHtt hinders mitophagy; while PINK1/Parkin-mediated mitophagy provides neuroprotection in HD. Hence, this review discusses the roles and regulations of mitophagy, along with an overview of mitophagy in HD.

Effect of Sodium Hydroxide/Urea/Deionised Water Solution Ratio on the Solubility of Oil Palm Empty Fruit Bunches Extracted Biocellulose

Biocellulose extracted from oil palm empty fruit bunches (OPEFB) is attracting increased research interest in versatile applications as an alternative material to synthetic cellulose. Normally, biocellulose needs to undergo dissolution prior its applications. Among all explored solvents to dissolve biocellulose, aqueous sodium hydroxide (NaOH)/urea solution is gaining increased attention. OPEFB biocellulose solubility in NaOH/urea/deionised (DI) water solution has not been fully studied by researchers. This study aimed to investigate the solubility of OPEFB biocellulose in NaOH/urea/DI water solution by manipulating the NaOH/urea/DI water solution ratio and weight percentage of OPEFB biocellulose. Results indicated that increasing the NaOH/urea/DI water solution ratio increased the solubility of OPEFB biocellulose. Further increased NaOH/urea/DI water solution ratio resulted in decreased solubility. Meanwhile, increased OPEFB biocellulose weight percentage decreased the solubility of OPEFB biocellulose in NaOH/urea/DI water solution. The highest solubility of 70.89%±1.85% was exhibited by 7% NaOH/12% urea/81% DI water (w/w) solution and 1 w/v% OPEFB biocellulose. This study on OPEFB biocellulose solubility in NaOH/urea/DI water solution can promote cost-effective and wide utilisation of the abundantly available OPEFB for the synthesis of cellulose fibres, films, and hydrogels in the textile, packaging, and biomedical industries.

The Water Quality and Nutrients Status in the Dungun River Basin, Terengganu

This study investigated the spatial variation of nitrogen (N)-based and phosphorus (P)-based nutrients together with water quality parameters (temperature, pH, dissolved oxygen, biological oxygen demand, chemical oxygen demand and total suspended solids) in the Dungun River basin, Terengganu. The Water Quality Index (WQI) of the river was applied according to the Malaysian Department of Environment (DOE-WQI) and classified based on the Malaysian National Water Quality Standard (NWQS). Results showed that the major source of nutrients and water quality deterioration in the basin was most likely due to the effluent discharged from the nearby palm oil factory. The overall WQI mean value obtained was 85.44%, which indicated that the Dungun River basin was in a clean condition and categorised into Class II based on the NWQS classification. The overall mean mass N:P ratio was 19.8:1 which indicated that the algal growth was generally controlled by the P-based nutrients. Based on this study, it is suggested continuous monitoring necessary to be carried out for proper management of this river basin.

Analysis of Upwelling Events in the Southern South China Sea Using Multi-Mission Satellite Altimeter

Upwelling is a vital ocean behaviour, especially for the Fisheries Industry, where upwelling will help to detect fish ground at a particular ocean area. However, the study of upwelling is minimal and not well understood due to some reasons and constraints, such as limited observation. Upwelling lacks a comprehensive in-situ observation system where it relies on limited information collected from the ground-truthing execution such as ships, buoys, and current meter. This study aims to analyse the upwelling pattern in the southern region of the South China Sea by using a multi-mission satellite altimeter. In order to derive the physical oceanography that involves upwelling, such as sea surface height (SSH), Mean Dynamic Topography (MDT), and the Sea Level Anomaly (SLA), the Radar Altimeter Database System is used. Five Satellite Altimeter mission is used in this study, which is JASON-2, JASON-3, CYROSAT2, SARAL, SENTINAL3A from 2013 to 2017. Validation is made using a statistical method showing a good correlation between Altimetry data and Tidal Data at tide gauge, which is 0.84 to 0.97, respectively. Also, monthly altimetry derived Geostrophic Current was assessed by analysing the current pattern where it shows a similarity with a previous study where the current velocity is 0.5ms-1 to 2ms-1. From the result, eddies can be seen in the seasonal and monthly Absolute Geostrophic Ocean Current (AGOC) map, indicating the present presence of upwelling. In conclusion, this study will benefit other researchers in terms of both upwelling and eddy studies.

Ni(II) Butylmethyldithiocarbamate: Physico-Chemical Properties, X-Ray Crystallography, DFT and Anti-Corrosion Screening in Different Acids

In industrial sectors, pickling and acid cleaning are mutual processes where acid solutions, such as hydrochloric acid (HCl) and sulfuric acid (H2SO4), are used to eliminate the corrosion products yielded on metal surfaces; thus, improving the performance of the machineries. However, the usage of the acid could lead to another metal deterioration. Dithiocarbamate inhibitor is defined as an organic compound that has good corrosion inhibition properties that can work as an inhibitor in an acid environment. Dithiocarbamate (DTC) assists by reducing acid reactiveness which prohibits metal dissolution in the acid. In this study, the Ni(II) N-butylmethyldithiocarbamate (Ni[BuMedtc]2) complex was synthesised by using an in-situ method and characterised by elemental analyser, attenuated total reflection Fourier transform infrared (ATR-FTIR), ultraviolet-visible (UV-Vis) spectroscopy and X-ray crystallographic study, and the chemical properties of the Ni[BuMedtc]2 complex was successfully calculated by the Discrete Fourier Transform (DFT) approach. The experimental results which were obtained through the weight-loss analysis method in two different acids – 1 M HCl and 1 M H2SO4 – indicated that the inhibition efficiency increased as the inhibitor concentration increased. The outcome showed that the Ni[BuMedtc]2 performed better as an inhibitor in 1 M HCl as compared to in1 M H2SO4 to protect the metal exterior because H2SO4 is more corrosive due to the excessive presence of H+.

Prediction of Intensive Care Cases for COVID-19 Pandemic in Malaysia: An Artificial Neural Networks Approach

Coronavirus 2019 (COVID-19) pandemic in Malaysia is a part of the ongoing worldwide pandemic. The emergence of COVID-19 has led to high demand for intensive care services worldwide. However, the severity of COVID-19 patients that need intensive care unit (ICU) treatments requires details investigation. This study aims to predict the number of ICU cases due to COVID-19 disease in Malaysia. The prediction was done based on the data related to new, recovered, and treated cases which were collected from the website of the Ministry of Health Malaysia started from April until August 2020. Artificial Neural Networks Multilayers Perceptron Backpropagation (ANN-MLP-BPP) model was developed for predicting ICU cases based on the usage of the real set of data. The ANN-MLP-BPP model was validated by splitting the data into 80% for training and 20% for testing. The results show that with the increase in the number of undertreated cases, the number of predicted ICU will also be increased. The predicted ICU admission is almost equivalent to a 1 percent increment of the number of cases undertreated. These findings may help the frontline physicians in planning and handling the facilities management during the COVID-19 pandemic situation in the future.