19672 research outputs found
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Heartware as a driver for campus sustainability: Insights from an action-oriented exploratory case study
No full textLiterature on campus sustainability transitions is mainly focused on the hardware and software approaches, with less attention on the so-called ‘heartware’ approach. Heartware refers to the internal and voluntary motivation of the campus community itself to establish long-term collaboration and collective efforts for sustainability. The paper addresses this gap through an action-oriented exploratory case study research in applying the heartware approach for a long-term water conservation initiative at the University of Malaya campus in Malaysia. The case study research employed a triangulation of five types of data sources (documentation, archival records, direct observation, physical artifacts and participant observation) and two analysis techniques (iterative explanation building and time-series analysis). The case study demonstrated that the heartware approach can be an essential driver for campus sustainability, with suggestions on three ways it can be exercised: (1) Community-shared values that can inspire collective and voluntary action on campus; (2) Role of volunteers within the campus community, at various levels of power, in galvanizing efforts; (3) Heartware driven adaptive governance - where the campus community is able to self-maneuver in mediating conflicts that can possibly block long term action. The paper concludes that there can be aspirational ways to view our campuses: as a living community with concerned citizens, rather than just a complex organization to be managed. This might open up more rooted solutions for campus sustainability than what is currently available
The implementation of the milk al-manfaah concept in Malaysia: Reference to the group settlement area land act (1960)
No full textThis article will discuss the success of the joint-venture between the Federal Goevrnment and the State Government in their effort to develop the agricultural land through the concept of’milk al-manfaah’. Therefore, the Group Settlement Land Act (1960) has been formulated in the Parliament. Through this Act, every settler is granted 10 acres of farm lands by means of the al-manfaah milk. The benefit ownership concept has been practised widely in the law history of the Islamic land by the Uthmaniyyah government named as the miri land. The same concept has been of practice in Egypt as well as several other Islamic countries. Based on the land Federal Constitution, it is located under the jurisdiction of the state government, whereas FELDA serves as a government agency. Through the 1960 Land Act, the Federal Government is permitted to perform land duties before the ownership is issued by the State Government. Based on the milk al-manfaah concept, FELDA has successfully developed 447,578 hectares of land in Malaysia
Moment Properties And Quadratic Estimating Functions For Integer-Valued Time Series Models
No full textRecently, there has been a growing interest in integer-valued time series models. In this paper, using a martingale difference, we prove a general theorem on the moment properties of a class of integer-valued time series models. This theorem not only contains results in the recent literature as special cases but also has the advantage of a simpler proof. In addition, we derive the closed form expressions for the kurtosis and skewness of the models. The results are very useful in understanding the behaviour of the processes involved and in estimating the parameters of the models using quadratic estimating functions (QEF). Specifically, we derive the optimal function for the integer-valued GARCH (p, q) known as INGARCH (p, q) model. Simulation study is carried out to compare the performance of QEF estimates with corresponding maximum likelihood (ML) and least squares (LS) estimates for the INGARCH (1,1) model with different sets of parameters. Results show that the QEF estimates produce smaller standard errors than the ML and LS estimates for small sample size and are comparable to the ML estimates for larger sample size. For illustration, we fit the 108 monthly strike data to INGARCH (1, 1) models via QEF, ML and LS methods, and show the applicability of QEF method in practice
Design optimisation of high sensitivity MEMS piezoresistive intracranial pressure sensor using Taguchi approach
No full textMEMS piezoresistive pressure sensors have been contemporarily used to measure intracranial pressure. Since an intracranial signal is of the pulsating type, the microsensor must be very sensitive to detect these changes. The sensitivity of the existing MEMS piezoresistive intracranial pressure sensors are in the range of 2 µV/V/mmHg to 0.17 mV/V/mmHg. Factors influencing the sensitivity and linearity of the sensor include the diaphragm thickness, the shape and placement of the piezoresistors, and the doping concentration. This paper will discuss the incorporation of these factors, which were tested to obtain higher sensitivity silicon-based piezoresistive intracranial pressure sensor, while maintaining the linearity of the sensor. In order to achieve this objective, the Taguchi robust design method of L27 orthogonal array was employed. The sensing outputs of these designs, with different combinations of factors were determined through simulations using COMSOL Multiphysics. The results indicated that the diaphragm thickness and perpendicular piezoresistors play important roles in the sensitivity performance of the MEMS piezoresistive intracranial pressure sensor. The findings also showed that the doping concentration of the piezoresistors have significant effect on the linearity performance of the sensor. Consequently, the design that consolidated the 3-turns (perpendicular) and 0-turn (parallel) meander shaped piezoresistors of 1017 cm−3 dopant concentration on a 2 μm diaphragm thickness was found to be the optimum design, with sensitivity of 0.1272 mV/V/mmHg and linearity of 99%. This design has been proven to be an improved version for the small diaphragm piezoresistive intracranial pressure sensor
UV-B irradiation effects on pigments and cytological behaviour of callus in sainfoin (Onobrychis viciifolia Scop.)
No full textPurpose: This study aims to determine the appropriate irradiation dose for induction of somaclonal variation in mass of unorganized parenchyma cells derived from sainfoin (Onobrychis viciifolia) tissues. Design/methodology/approach: To investigate the feasibility of UV-B irradiation (312 nm), seeds and callus of sainfoin were exposed to five different intensities (20-100 per cent) for evaluating the effectiveness of phytochemical constituents and cellular behaviour. Findings: Although percentage of seed viability reduced in 20 per cent intensity of UV-B irradiation compared with control seeds, the germination speed significantly enhanced from 3.58 to 5.42. The spectrophotometer analysis confirmed that concentrations of chlorophyll (a and b) decreased after UV-B exposure as compared with control callus. Also, carotenoid content showed significant differences among treated calli. Flavonoid and phenolic contents were observed to gradually increase when the non-irradiated callus subjected to 40 and 60 per cent intensities of UV-B irradiation, respectively. Observation on cellular behaviour such as determination of nuclear and cell areas, mitotic index and chromosomal aberrations were also detected to change in different intensities of UV-B irradiation. Fragmented and aneuploidy aberrations were only observed in exposed cells with more than 40 per cent intensity of UV-B irradiation. Originality/value: In reality, radiocytological evaluation was proven to be essential in deducing the effectiveness of UV-B irradiation to induce somaclonal variation in callus tissue of sainfoin
Incorporation of expanded vermiculite lightweight aggregate in cement mortar
No full textThis investigation presents an evaluation of the properties of cement mortars containing expanded vermiculite as partial sand replacement. When the expanded vermiculite was included at 30% and 60% replacement levels, the flow diameter was higher compared to the plain mortar without expanded vermiculite. The porous lightweight nature of the expanded vermiculite also contributed to the reduction in the unit weight and compressive strength of mortars, as well as increased water absorption. Although weight loss of the expanded vermiculite mortars subjected to elevated temperature was increased, the expanded vermiculite had positive effect in providing heat resistance and thermal stability to the mortars, observed by the reduction of compressive strength loss of mortars upon exposure to elevated temperatures
Lung disease classification using GLCM and deep features from different deep learning architectures with principal component analysis
No full textLung disease classification is an important stage in implementing a Computer Aided Diagnosis (CADx) system. CADx systems can aid doctors as a second rater to increase diagnostic accuracy for medical applications. It has also potential to reduce waiting time and increasing patient throughput when hospitals high workload. Conventional lung classification systems utilize textural features. However textural features may not be enough to describe properties of an image. Deep features are an emerging source of features that can combat the weaknesses of textural features. The goal of this study is to propose a lung disease classification framework using deep features from five different deep networks and comparing its results with the conventional Gray-level Co-occurrence Matrix (GLCM). This study used a dataset of 81 diseased and 15 normal patients with five levels of High Resolution Computed Tomography (HRCT) slices. A comparison of five different deep learning networks namely, Alexnet, VGG16, VGG19, Res50 and Res101, with textural features from Gray-level Co-occurrence Matrix (GLCM) was performed. This study used a K-fold validation protocol with K = 2, 3, 5 and 10. This study also compared using five classifiers; Decision Tree, Support Vector Machine, Linear Discriminant Analysis, Regression and k-nearest neighbor (k-NN) classifiers. The usage of PCA increased the classification accuracy from 92.01% to 97.40% when using k-NN classifier. This was achieved with only using 14 features instead of the initial 1000 features. Using SVM classifier, a maximum accuracy of 100% was achieved when using all five of the deep learning features. Thus deep features show a promising application for classifying diseased and normal lungs
Application of TiO2 nanoparticles for eco-friendly biodiesel production from waste olive oil
No full textAn environmentally benign, simple, and efficient process has been developed for biodiesel production from waste olive oil in the presence of a catalytic amount of TiO2 nanoparticles at 120°C with a conversion of 91.2% within 4 h. The present method affords nontoxic and noncorrosive medium, high yield of biodiesel, clean reaction, and simple experimental and isolation procedures. The catalyst can be recycled by simple filtration and reused without any significant reduction in its activity
Projections of the Healthcare Costs and Disease Burden due to Hepatitis C Infection under Different Treatment Policies in Malaysia, 2018–2040
No full textIntroduction: The World Health Organisation (WHO) has set ambitious goals to reduce the global disease burden associated with, and eventually eliminate, viral hepatitis. Objective: To assist with achieving these goals and to inform the development of a national strategic plan for Malaysia, we estimated the long-term burden incurred by the care and management of patients with chronic hepatitis C virus (HCV) infection. We compared cumulative healthcare costs and disease burden under different treatment cascade scenarios. Methods: We attached direct costs for the management/care of chronically HCV-infected patients to a previously developed clinical disease progression model. Under assumptions regarding disease stage-specific proportions of model-predicted HCV patients within care, annual numbers of patients initiated on antiviral treatment and distribution of treatments over stage, we projected the healthcare costs and disease burden [in disability-adjusted life-years (DALY)] in 2018–2040 under four treatment scenarios: (A) no treatment/baseline; (B) pre-2018 standard of care (pegylated interferon/ribavirin); (C) gradual scale-up in direct-acting antiviral (DAA) treatment uptake that does not meet the WHO 2030 treatment uptake target; (D) scale-up in DAA treatment uptake that meets the WHO 2030 target. Results: Scenario D, while achieving the WHO 2030 target and averting 253,500 DALYs compared with the pre-2018 standard of care B, incurred the highest direct patient costs over the period 2018–2030: US952 million, which was 12% higher than the estimated total cost of scenario C. Conclusions: The scale-up to meet the WHO 2030 target may be achievable with appropriately high governmental commitment to the expansion of HCV screening to bring sufficient undiagnosed chronically infected patients into the treatment pathway
Evaluating the critical strain energy release rate of bioactive glass coatings on Ti6Al4V substrates after degradation
No full textIt has been reported that the adhesion of bioactive glass coatings to Ti6Al4V reduces after degradation, however, this effect has not been quantified. This paper uses bilayer double cantilever (DCB) specimens to determine G IC and G IIC , the critical mode I and mode II strain energy release rates, respectively, of bioactive coating/Ti6Al4V substrate systems degraded to different extents. Three borate-based bioactive glass coatings with increasing amounts of incorporated SrO (0, 15 and 25 mol%) were enamelled onto Ti6Al4V substrates and then immersed in de-ionized water for 2, 6 and 24 h. The weight loss of each glass composition was measured and it was found that the dissolution rate significantly decreased with increasing SrO content. The extent of dissolution was consistent with the hypothesis that the compressive residual stress tends to reduce the dissolution rate of bioactive glasses. After drying, the bilayer DCB specimens were created and subjected to nearly mode I and mode II fracture tests. The toughest coating/substrate system (one composed of the glass containing 25 mol% SrO) lost 80% and 85% of its G IC and G IIC , respectively, in less than 24 h of degradation. The drop in G IC and G IIC occurred even more rapidly for other coating/substrate systems. Therefore, degradation of borate bioactive glass coatings is inversely related to their fracture toughness when coated onto Ti6A4V substrates. Finally, roughening the substrate was found to be inconsequential in increasing the toughness of the system as the fracture toughness was limited by the cohesive toughness of the glass itself