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Pictorial health warnings on cigarette packs: Compliance and public understanding among adults in Malacca, Peninsular Malaysia / 'Ainun Mardhiah Meor Amir Hamzah
No full textPictorial health warnings (PHWs) on cigarette packs, is one of the tobacco-free initiatives,
targeting smokers and non-smokers. Since its implementation in Malaysia in 2009, little
is known whether the PHWs on Malaysian cigarette packs comply with the PHW
indicators, and well-understood by the public. Objectives: This study compared the
prevalence of legal and illicit cigarettes in Malacca and the compliance level of PHWs
with the Malaysian law and Framework Convention on Tobacco Control (FCTC)
requirements between cigarette’s brands and variants, its legal status, types of Point of
Sales (POS), and locations; also explored the public’s understanding and
recommendations to improve the existing PHWs in Malaysia, among adults. Methods:
This multi-mode research consisted of a quantitative and qualitative study. PHW
compliance level of each cigarette pack was assessed using a modified protocol from the
International Tobacco Pack Surveillance System (TPSS) involving 52 multi-types
cigarette points of sale in urban and rural area in Malacca. Four Focus Group Discussions
(FGDs) involving 24 adults (including non-smokers, smokers and ex-smokers) were
conducted to elicit the public’s understanding and recommendations related to the
existing PHWs. Data were analysed using the SPSS Ver 20.0 and Atlas.ti ver 8.0. Results:
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Of 121 variants of cigarettes, i) the majority of cigarettes obtained were legal cigarettes
(83.5%), ii) 84.3% complied with the requirement to display the gazetted PHWs , iii)
94.2% complied with five requirement indicators, namely, having PHWs present on the
packs, PHWs printed in full colour, PHW printed on the designated location, having the
correct label elements and text elements & size, mainly contributed by legal cigarettes,
iv) more than half of the cigarette variants showed a high compliance level to the overall
12 PHW indicators, contributed by the legal cigarette variants, those sold in the petrol
stations, and in the urban areas ( p<0.05), v) The overall PHW compliance level and
scores differ between cigarette brands and within variants of the same brand (not
statistically significant), also between cigarettes legal status, types of POS and cigarettes
sold in urban and locations (p<0.05), vi) Adults in this study easily understood PHWs
showing effects on the lung and those related to oral health; contributed to early and
frequent exposure of those effects via the education system, health programs conducted
in school and social media. Gaps observed in the knowledge of smoking effects,
misunderstanding, and misperceptions for PHWs, related explicitly to gangrene and
pregnancy-related images. Our participants perceived the existing PHWs effective only
to non-smokers and non-chronic smokers. vii) the existing PHWs in Malaysia were
effective than those from other ASEAN countries. However, there were weaknesses
arising from the images, form, contents, desensitisations of Malaysian PHWs, etc., that
affect its impact. Conclusion: Legal cigarettes, those sold other than at grocery stores,
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and in the urban areas showed higher compliance with the requirements of both Malaysian
law and FCTC. As the public were unable to comprehend the existing PHWs fully, the
stakeholders need to actively address various aspects to strengthen and improve PHWs
effectiveness in the future.
Keywords: PHW, Compliance, Understanding, Effectiveness, Public
Contamination status and ecological risk of heavy metals in surface sediment of Kelantan river and its nearshore area, Malaysia / Pooveneswary Nagaiah
No full textA study on contamination status and ecological risk of heavy metal in surface sediment at selected sites of Kelantan river and its nearshore area was carried out. 10 samples along Kelantan river and 25 samples from nearshore were analyzed using Inductively Coupled Plasma Optical Emission (ICP-OES) to determine heavy metal concentrations. Sediment samples were also analyzed for particle size compositions, total organic matter, and pH content. The average concentrations for As, Cd, Cr, Cu, Mn, Ni, Pb, Zn were 7.38, 1.31, 17.71, 11.40, 507.15, 5.97, 22.61, 32.95 mg/kg for riverine and 14.14, 4.59, 29.79, 14.07, 389.96, 9.65, 62.21, 41.04 mg/kg for nearshore samples, respectively. The potential ecological risk index (PERI) showed station Bekok, Manek Urai, RH under considerable risks followed by station Pasir Mas as moderate risk. The pollution load index (PLI) classified four nearshore sites (KW10, KW17, KW18, KW37) as polluted. The geo-accumulation index (Igeo) categorised moderate contamination for Cd and Pb. The enrichment factor (EF) along river categorised extremely high enrichment for Cd, and significant enrichment for As, Pb and Mn while Pb and As were under very high and significant enrichment at nearshore areas. Pb, Cu, Zn, As, Ni and Cr, showed significant correlations with each other
Development of quality assessment methods for wood images / Heshalini Rajagopal @ Ramasamy
No full textImage Quality Assessment (IQA) is a vital element in improving the efficiency of an automatic recognition system of various wood species. There is a need to develop a No- Reference Image Quality Assessment (NR-IQA) system as a perfect and distortion free wood images may be impossible to be acquired in the dusty and dark environment in timber factories. Many IQAs which focus on some image of interest such as natural images have been proposed. However, an IQA specifically for wood images have not been proposed so far. Hence, this thesis proposes two No-Reference IQA (NR-IQA) metrics, Modified BRISQUE Wood Image Quality Assessment (MBW-IQA) and GLCM and Gabor Wood Image Quality Assessment (GGW-IQA) to assess the quality of wood images. Firstly, Support Vector Machine (SVM) Regression (SVR) was trained using Generalized Gaussian Distribution (GGD) and Asymmetric Generalized Gaussian Distribution (AGGD) features calculated for wood images together with the mean opinion score (MOS) obtained from subjective evaluation to develop the MBW-IQA. Secondly, SVR was trained using Gray Level Co-Occurrence Matrix (GLCM) and Gabor features calculated for wood images together with the MOS to develop the GGW-IQA metric. The MBW-IQA and GGW-IQA metrics are compared with one of the established NR-IQA metrics, namely, Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE), Deep Neural Network IQA (deepIQA), Deep Bilinear Convolution Neural Network (DBCNN) and five Full Reference-IQA (FR-IQA) metrics known as MSSIM, SSIM, FSIM, IWSSIM and GMSD. Results shows that the GGW-IQA outperforms the MBW-IQA, BRISQUE, deepIQA, DB-CNN and all the FR-IQA metrics. Moreover, the GGW-IQA metric is beneficial in wood industry as a distortion free reference image is not needed to evaluate the wood images
Research on concentrated photovoltaic thermal and daylighting (CPVTD) systems using round and flat optical fibers / Afshin Aslian
No full textConcentrated photovoltaic and thermal (CPVT) system is proposed. The system concentrates the sunlight and implements solar cells in focal point of a concentrator. Heat collector is located behind the cells and transmits the heat to a heat exchanger. The system has high efficiency in direct sunlight. So, a sun tracker is required as a subsystem. By integrating the function of daylighting to the CPVT system, the functionality of system improves, and the developed system can be deployed in residential buildings. In this research substance-field (Su-Field) and functional analysis of Teoriya Resheniya Izobretatelskikh Zadach (TRIZ) are applied to develop a comprehensive model of problem in integrating three functions i.e. electricity, heat and light into a developed system. The model of concentrated photovoltaic-thermal and daylighting (CPVTD) solar energy system for residential buildings is presented through integrating light function to a CPVT system.
Developing a CPVTD system for residential building is a fine process that requires satisfying several design considerations such as total efficiency, thermal, electrical and daylighting performance with significant innovations and improvements. Since a CPVTD is a complex system that consists of combination of different components, the design considerations are interconnected and often conflicting. As a result, multi-variable optimization is often required for increasing the total efficiency, reducing bulk of system, improving reliability and durability and minimizing the total cost.
In this research we focused on optical components and heat sink of a CPVTD system. These components are imaging dish, secondary concentrator, optical fiber and heat sink. These components are the main components that convert sunlight to electricity, hot water and daylight. A novel secondary concentrator, a new rectangular optical fiber, and a compact energy conversion device “that we name hear” a receiver is designed and fabricated. In a compact energy conversion device, we can split the bulk of transmitted light for different purposes, i.e. electrical power conversion, heat and daylighting. A glass rectangular optical fiber designed for transmitting sunlight. The fiber simulated, fabricated and tested as a medium for transmitting sunlight from focal point to photovoltaic cells in the compact energy conversion device. A receiver of CPVTD with round optical fiber is fabricated and tested. The results show that using optical fiber as a medium in receiver reduced the temperature of multi-junction cells and increased the distance between the cells. Therefore, the surface of heatsink increased, and heat exchange between fluid and heat sink enhanced
Recommendation of experts in community question answering using tag relationship / Anitha Anandhan
No full textCommunity Question Answering (CQA) systems are discussion platforms for sharing knowledge rapidly through question and answer posts on social media. However, there was dissatisfaction due to slow response and low-quality answers from the crowded information. Most of the existing studies focused on expert recommendation based on available information. Still, the challenge is to find the specific domain-related experts based on user preferences for their questions. Experts are the users who post high-quality answers based on tag metadata in CQA. This condition requires experts to respond to the inquiries posted on community-based websites. Hence, this study aims to find the experts using related archive posts, users, score and tag metadata in CQA. Most CQA questions are posted with multiple tags. The co-occurrence of tags is essential for recommendation purposes as it shows the user’s interest in multiple domains, leading to high-quality answers and reducing waiting time. This study proposed the Tag Relationship Expert Recommendation (TRER) method to create the user profile by extracting the user’s interest. Similar posts are retrieved from the archive and used to rank and recommend experts for the selected domain using the input question tokens. The implicit tag relationship has been integrated into the proposed method to predict multiple domain and users relatedness. A similar user’s tag-to-tag relationship based on user preferences is utilised to recommend the specific and relevant domain experts for the input questions. Findings depict that TRER improves the performance of expert recommendations topredict the relevant and similar interest users based on the input questions by incorporating Question Answer (QA) space. Moreover, the tag relationship of the user effectively helps to find the experts with specific domain knowledge to answer the input questions posted by technical and academic professionals. The findings indicate that the TRER method outperformed baseline methods
Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
No full textThis dissection aims to develop and deploy a multicriteria support system framework to provide a structured decision-making process. The proposed approach can be furthered categorized into two distinct stages: forecasting modeling and optimization modeling. Artificial neural network (ANN) has been widely used in forecasting tasks. However, due to some drawbacks, an advanced technique was employed in this study. The proposed method involves using a convolutional neural network (CNN) with a feature extraction ability to learn from the hydrological dataset efficiently. With the aid of deep architecture, a highly abstracted representation of the inputs time series with a high level of interpretation is formed at each subsequent CNN layer. Besides, through integration of wavelet transform (WT), the performance of the forecasting model can be improved. WT can be used to preprocessing the hydrological dataset into a set of decomposed wavelet components. These components are served inputs for the CNN model. The developed models were applied to three different case studies to evaluate the performance of the models. The results showed that the proposed model could capture patterns of the monthly and daily interval of the hydrological time series. Apart from that, having low values in four of the performance criteria: RMSE, MAE, NSE, and RSR, have further strengthened the credibility of the results. As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. These operational rules were based on the reservoir with a multi-purpose objective: hydropower and intrusion of saltwater. The results indicated that the hydropower generated by the proposed algorithm could produce an evenly distributed high amount of energy increases the reliability of the reservoir system. However, under the circumstances of water deficiency, the hydropower output is significantly reduced. When deriving the optimal operating rule, a hedging rule was applied to attenuate the effect of limited water supply. Furthermore, the efficiency of the proposed algorithm was assessed using some reservoir performance indices such as resilience and reliability. Besides, a Bayesian uncertainty analysis was carried out to quantify the model output behaviors due to derivation from the uncertainty in the input parameters. A Bayesian method for CNN using TensorFlow Probability was used in this study. By utilizing the probabilistic model, the aleatoric and epistemic uncertainty can be addressed. In addition, the confidence level was built using the percentile-t-method (or bootstrap-t-method). The proposed technique was then tested on a dataset obtained from the same hydrological stations used when the forecasting modeling. According to the simulated results, the proposed model can provide a statistical distribution of the forecasted quantity. Besides, the Monte-Carlo simulations demonstrated that all the values lie within the 95% confidence level. Therefore, the network reliability increased as it revealed the uncertainty in the forecasted values
Theoretically engineered DARPins targetting DENV-2 envelope protein / Chong Wei Lim
No full textInfectious diseases caused by dengue virus (DENV) have been threatening human health worldwide particularly tropical and sub-tropical regions. Infected population, as reported by WHO, reach 390 million yearly and the global incidence of dengue has tremendously grown. Specific drugs for treating dengue are under development while several antibodies bound to domain III (DIII) envelope (E) protein of DENV were found to prevent the viral entry process. In this study, the potential of Designed Ankyrin Repeat Proteins (DARPins), one of the non-immunoglobulin protein scaffolds, mimicking the binding interactions of antibodies and DIII of DENV envelope (E) protein was explored. Selected DARPins retrieved from the Protein Data Bank were docked to the epitope of domain III as recognised by antibodies under the HADDOCK web server. Representative docked complexes then underwent molecular dynamics simulations (MDs) with AMBER forcefield ff14SB to study their molecular properties. Binding affinity of DARPins to DIIIs was elucidated by free energy calculation using Molecular Mechanics–Poisson- Boltzmann Surface Area/Generalized Born Surface Area (MM-PPSA/GBSA) protocols while the important residues for protein-protein interactions were identified by further decomposing the binding free energy per residue basis. DARPin residues found with unfavourable energy within the binding vicinity then underwent computational site direct mutagenesis. Improved and engineered DARPins in complexed with DIII were simulated under the same parameters for free energy calculations. Gaussian Network Model (GNM), an elastic network model, was then used to investigate the dynamics of the proteins in terms of global mode shape and their dynamic cross-correlations. Global mode shape was observed corresponding to binding free energy, in which a low binding free energy was accompanied by a lower mode shape, or lower mobility. The simulated techniques provide valuable tools in understanding the structural dynamics and energy contribution in designing the DARPins in their binding to the E protein of DENV-2. The protein-protein complexes with different binding activities can clearly be identified by evaluating the binding free energy and global mode shape of the structures from the long timescale MDs
Digital protection of power converters employed in doubly-fed induction generator and induction motor using wavelet transform / Ukashatu Abubakar
No full textThis work comprises two sections, firstly, the execution of an alternative to crowbar for the DFIG-based wind energy conversion system (WECS) is proposed. The deployed crowbar protection scheme is based on a digital algorithm oriented to utilize the d-q axis of the 3-Φ rotor currents. The application of wavelet transforms enables the effective capture, of essential information contained in the high frequency current signals. The crowbar functions to protect the rotor side converter (RSC) from damage, against the high inrush current during short or open circuit fault in the rotor or at the grid. The working of the traditional crowbar is usually characterized with the absorption of reactive power from the grid, which is considered undesirable for the topology presented herein. Furthermore, the presented digital crowbar can discriminate between the actual fault occurrence and momentarily transient. Additionally, the flexibility of wavelet packet transform (WPT) predisposes it to be incorporated within the rotor controller structure and adapted to work as crowbar. The developed d-q WPT-based digital crowbar is capable of generating a faster trip signal with shorter restoration time of ≤7.
Determining the delay factors for reconstructed mega-project’s phases and the associated challenges / Basem Adnan Al Khatib
Get PDFIn recent decades, the construction industry has developed rapidly. Delays in construction projects are a common phenomenon throughout industry. It was and remains one of the most important challenges negatively affecting not only this industry but also the economy. Many studies were conducted to identify the delay factors in new construction projects in different regions, but very few have focused on finding an explanation for the delay causes in reconstruction projects. The study aims to conduct a comprehensive analysis of the delay factors in mega reconstruction projects which took place recently in the Middle East, namely Mataf Expansion Project in Mecca, Saudi Arabia. This project consists of two main parts, nonhistorical and historical and it clarifies the difficulties facing this type of reconstruction projects, which combine demolition and construction works at the same time while the project is under operation. In order to achieve the study goal, twenty-nine interviews were held with the experts working on the project to identify the delay factors and ninety-three questionnaires were distributed by hand to sort them. The results showed that these factors could be divided into three groups: the first one is related to the demolition phase and the second is related to construction phase, while the last is related to overall reconstruction duration. In addition, it has been observed that the materials challenges are considered the major delay factor in the historical building of this project. The questionnaire results were analyzed and delay factors were sorted in a descending order according to the relative importance index (RII). The three main factors affecting the overall reconstruction project duration were site conditions and constraints, electrical and mechanical rerouting works, and design constructability and modification. Finally, recommendations were provided to bridge or reduce the negative impacts of the delay factors in future reconstruction projects
Cytotoxic and anti-migration properties of proteins from Pleurotus tuber-regium (Fr.) Singer and Termitomyces heimii Natarajan against human breast MDA-MB-231 and colon HCT-116 cancer cells / Erlina Abdullah
No full textThe discovery and identification of new safe drugs that are specifically cytotoxic against cancer cells becomes an important target in cancer research. Increasing number of cancer deaths around the world are associated with metastasis and lack of specificity and effectiveness of current treatment. In developed countries such as Korea, Japan and China, mushrooms have been used for centuries for medicinal purposes against cancer. Numerous studies have reported the vast medicinal values of proteins isolated from mushrooms including anti-tumour and anti-cancer effects. The present study aims to investigate the potential of protein extracts from two Basidiomycetes species which are Pleurotus tuber-regium (Fr.) Singer (sclerotium and fruiting bodies) and Termitomyces heimii Natarajan (fruiting bodies) for anti-tumour effects as well as the mechanism of action against targeted cancer cells. Protein extraction from P. tuber-regium sclerotium, P. tuber-regium fruiting bodies and T. heimii fruiting bodies were conducted using ammonium sulphate precipitation technique. The protein fractions were determined based on different salt/ammonium sulphate concentration at 30%, 60% and 90%. All protein fractions of were assessed for cytotoxicity towards breast cancer cell lines (MDA-MB-231), colorectal cancer cell lines (HCT-116) and normal lung cell lines (MRC-5) in MTT assay. Potential protein extracts were identified based on the IC50 values and selectivity index (SI) on both cancer cells and normal cells. IC50 values are the extract concentrations required to inhibit half of the cells growth and SI values are the measure of safety level of drugs/compounds/extracts against normal cells as referred to cancer cells. Extracts with IC50 values less than 20 μg/ml are considered to be actively cytotoxic against target cells after 48-72 hours of incubation time, while SI value greater than 3 indicates potential selectivity of extracts or compounds towards cancer cells as compared to the normal cells. The most promising protein extract was PS60 of P. tuber-regium sclerotium with the lowest IC50 value (IC50=0.75±0.57 μg/ml) against MDA-MB-231 cells and with minimum cytotoxicity towards the normal lung cells (MRC-5) at SI value of 14. Cellular migration through tissues is one of the important events in metastasis. Ability of the mushroom protein extracts to inhibit such migration was evaluated using the scratch wound assay. Cytotoxicity and anti-migration (MCA) effects on cancer cells were best exhibited by PS60 of P. tuber-regium sclerotium with MCA reading ranging between 5.6581±0.2015 nm/h and 5.4142±0.6916 nm/h. The purification of PS60 (P. tuber-regium sclerotium) using LCMS-Q-TOF MS, had successfully isolated several different proteins, two of which are identified as kinesin-like protein and keratin type 1, cytoskeletal 10.PS60 was then further evaluated for apoptotic effects. PS60 was shown to exert cytotoxic effects associated with the induction of apoptosis and cell cycle arrest in MDA-MB-231 cells at G1/G0 and S-phase. In conclusion, PS60 protein of P. tuber-regium sclerotium have good potential to be developed into novel anti-tumour drugs against breast cancer