ICAPS 2022

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Stochastic modelling of Lotka-Volterra competition
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Ayesha, K. M. S.; De Silva, T. M. M.
The concept of stochasticity, which is based on probability theory, has played a vital role in describing the population fluctuations in most species. Demographic and environmental stochasticity are the main branches of stochasticity and occur due to the random nature of events and irregular or noisy dynamics, respectively. In particular, this study focuses on the concept of demographic stochasticity for studying the distribution of two competing populations. In the literature, the deterministic models of two competing populations have been studied, including the Lotka-Volterra competition model. Unlike prior work, we analyse the stochastic modelling of two competing populations where one population is subject to the Allee effect and understocking. The deterministic model of two competing populations, which is based upon the classical Lotka-Volterra competition model, is used to construct the corresponding continuous-time Markov chain (CTMC) and Ito stochastic differential equations (SDEs). Moreover, in the construction of CTMC and SDEs, demographic variability due to random birth and death have been applied to the populations, which is absent in the deterministic setting. In addition, the moments of the random variables in the populations based on the moment-generating functions of the transition probabilities are derived theoretically in such a way that the transition probabilities satisfy the forward Kolmogorov differential equations. Also, there is an infinite number of SDE models that correspond to the same ordinary differential equation system. In this study, we formulate two SDE models considering two different birth and death rates to see the variability in population interactions. The parameter values are taken from existing literature to justify the analytical results. The Euler-Maruyama numerical method is applied to simulate the numerical solutions of the Ito stochastic differential equations for comparing both types of stochastic models with the deterministic system numerically. From the numerical simulation, we have observed that the sample paths of the SDEs are closer to the solution of the deterministic model. Moreover, variabilities of the population interactions are highly correlated with the birth and death rates. In addition, for the chosen parameter values, though the populations coexist in the deterministic setting, we capture sudden population extinction in the stochastic setting. The study concludes that the theoretical results established in the deterministic setting may not be valid in the stochastic models due to random effects of the birth and death process embedded in the populations. Therefore, stochastic modelling with the Allee effect and stocking can significantly affect the competition outcomes and population interactions.
Attitudinal and behavioural changes in Coconut (Cocos nucifera) oil consumption with the occurrence of Aflatoxin contamination in Sri Lanka
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Sandupama, M. W. P.; Munasinghe, H. M. D. H.; Silva, M.
In the recent past, there was a serious controversy within the Sri Lankan community since certain imported coconut oil brands were detected unsafe for consumption as they exceeded the permissive aflatoxin levels. The present study investigates the noticeable changes in consumption patterns and behaviours as well as the degree of awareness of households on basic information regarding aflatoxin contamination. The survey study was conducted with the participation of 521 households representing Western and Southern provinces. A simple random sampling method was used as the sample design. Data were gathered using a self-administered questionnaire which was distributed through different media. Collected data were analyzed using the social science statistical program IBM SPSS 25, along with Microsoft Excel with Data Analysis Add-in. The results showed that 91.2% of respondents are aware of aflatoxin as a potential hazard, while only 42.8% were concerned about different aspects of aflatoxin contamination, up to a considerable level. Out of the coconut oil consumers, 12.6% did not have a proper idea about the reasons for the aflatoxin contamination. A few participants (1.6%) stated that aflatoxin has no adverse effect on human health, while the majority (91.6%) believed the main effect is the carcinogenic effect. Many agreed that buying a local reputed oil brand (54.6%) and preparing your own at household levels (66.8%) are the best control measures that can be taken at household levels. Although 93.3% of respondents showed a positive interest in learning more about this food safety concern, there is no significant association (p > 0.05) between the highest education level of the consumers and the awareness of aflatoxin contamination as per the cross-tabulation and Chi-square test. According to the Paired sample T-test, the purchasing places, factors affecting purchasing decisions, and the buying frequency have changed significantly (p < 0.05) based on the different perceptions regardless of educational level. But most of the consumers did not shift to an alternative oil instead of coconut oil, while 22% have started using different oils. The significant factor considered at the purchasing point was changed from brand to standards and specifications, and the concern for the nutritional attributes has also increased after the incident. There is no correlation between the factors that affected the purchasing decisions before and after the issue (p > 0.05). The study concluded that the majority of coconut oil consumers have a satisfactory awareness of the potential hazard of aflatoxin, and the consumption patterns and purchasing decisions have deviated significantly after the incident. The trends and habits rather than knowledge and greater awareness on the matter are seemed to be accountable for these behavioural changes. Therefore, the relevant authorities should induce consumer education campaigns to enhance the awareness of consumers on these food safety issues, which will lead them to assure health safety and confidence in coconut oil products. Moreover, quality and safety analyses of coconut oil manufactured on small, medium, and large scales will be conducted to gain in-depth knowledge as future projects align.
Predicting the execution time complexity of a computer program using Machine Learning
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) De Ranasinghe, I. M. M. P.; Munasinghe, L.
Performance enhancement of a computer program is an important aspect of today's world. The developers produce programs and there is a lack of accurate methods for predicting the execution time of a computer program prior to its execution in an executable environment. Predicting the execution time of a particular program before execution would be great to develop the program with the highest performance efficiency and the lowest execution latency. Theoretically, there are a lot of ways of calculating the complexity of a computer program. Mathematically it is impractical to find a universal method to compute the complexity of all types of programs. Therefore, this research introduces a Machine Learning based solution to predict an execution-time-based label for a given computer program. There are three main types of parameters in a computer program that affect the execution time, such as Static Code Features, Hypertext Transfer Protocol (HTTP) Calls, and the Hardware Performance of the execution environment. In this research, the Machine Learning (ML) model was trained for the parameters of the above types (Programs with Static Code & HTTP calls) by executing them on a fixed hardware infrastructure execution condition. We analysed the number of if conditions, methods, breaks, switches, loops, nested-loop-depth, frequencies, and the behaviour of HTTP calls, kind of features of a computer program in order to generate an accurate execution time complexity prediction label of a computer program. The label is forecasted based on five pre-defined complexity classes by considering the minimum and the maximum overall execution time of the considered dataset, such as Execution Time is Higher, Execution Time is High, Execution Time is Medium, Execution Time is Low, Execution Time is Lower. Further, in the collected dataset, the most prominent features which affect the complexity among the features that we considered are the number of HTTP calls and nested loop depth, followed by loops. Accuracy Score, Precision, Recall, and F1 Score values of the ML model were generated for the traditional classification algorithms such as Decision Tree Classifier, K Nearest Neighbour Classifier, Random Forest Classifier, Naive Bayes Classifier, Support Vector Classifier, and MLP Classifiers in order to verify the effectiveness of the model. The best accuracy score was achieved with an overall 88% by using the approach of Random Forest. The findings of this research can be optimized for implementing an Integrated Development Environment (IDE) plugin or a developer tool that can forecast the exact execution time of a given computer program live by integrating the specifications of the execution device. It will help developers to optimize a particular computer program and develop it for a minimum execution latency and enhance the performance of the program.
Comparative study of recycled papers to be used as an alternative for food packaging: quality assessment and heavy metal migration testing
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Indunil, G. M.; Bandra, W. R. T. W. R.
The permanence and durability of recycled papers are important as virgin papers are chosen for the definitive end-use. The main objective of this study was to assess the paper quality of recycled papers used as an alternative for food packaging. Three types of recycled papers, Brown Kraft papers (R1), Yellow Kraft papers (R2), and White papers (R3), were collected. Physical parameters; grammage, thickness, burst strength, tensile strength, water absorptiveness, chemical parameters; pH and optical parameters; opacity, brightness, and whiteness of the selected papers were tested using standard methods. At first, sample papers were subjected to accelerated ageing by keeping them in a closed ageing chamber at 50 % relative humidity and 90°C (ASTM D4714 method). Samples were tested after accelerated ageing of 3 days, 7 days, 14 days, 21 days, and 28 days, similar to the natural ageing of 0, 384 days, 2.5 yrs., 3.5 yrs., 4.9 yrs., 7.4 yrs., and 9.8 yrs., respectively. Heavy metal migration test was done to evaluate the suitability of the recycled papers as food packaging material. Five different food types, burgers, pizza, Sausages, candy, and chocolates, were selected, and 500 g of each food type was wrapped with 2 dm2 sized recycled papers stated above and kept for 72 hours in normal laboratory conditions. Three replicates were used for each food type. The presence of heavy metals in food samples was extracted using a 3% (v/v) metal¬ free solution of acetic acid for 24 hours at 40℃. At the end of the treatment, contact liquid was collected and analyzed for heavy metals using atomic absorption spectroscopy (AAS). The presence of heavy metals in food packaging materials was compared with four different food packaging standards. Opacity has increased in all the recycled papers with accelerated ageing. Other parameters showed a decreasing trend over time. All three types of recycled papers failed the water absorptiveness test after accelerated ageing on day 3. Changes in pH varied from alkaline to neutral (pH 9.1 to 7.4) in recycled papers over time. In conclusion, all the recycled papers are not suitable for printing and writing as they fail water absorptiveness. As parameter changes can be observed after accelerated ageing of 21 days in recycled papers, they can be used as archival or artist’s paper for 7.4 years without discolouring or deteriorating. The Recycled papers produced in this study can be recommended for food packaging as they show the highest permanence in terms of tensile and burst strength. However, as recycled papers fail the water absorptiveness, it is recommended to use them to pack dry food. The available amounts of heavy metals present Cu, Zn, Mn, and Cr are not exceeded within the EU, EC, EPA, and SLS food packaging standards for recycled papers. Ni was not detected in R1, R2, and R3 recycled papers. However, according to the Council of Europe standard, it exceeds the permissible Pb level in food packaging materials. When considering the migration of heavy metals from recycled papers into food, R1, R2, and R3 recycled papers can be recommended for food packaging as per the EPA, EC, and SLS standards without further treatments. Food items with high levels of fatty acids facilitate the higher migration of heavy metals compared to food items with lower fatty acid levels.
Atmospheric chemical composition of bulk precipitation in different regions of Gampaha District
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Edirisinghe, E. A. C. P; Deeyamulla, M. P.
Wet and dry deposition, both referred to as bulk precipitation, are the two methods of removing gases and particulates from the atmosphere. This research primarily focuses on bulk precipitation analysis to evaluate the pollution sources and the extent of seasonal characteristics of precipitation for air quality monitoring in the vicinity of Kerawalapitiya-Yughadhanavi Power Plant, the largest oil-fired power plant, and Sapugaskanda Oil Refinery, the single largest oil refinery in Sri Lanka. During the northeast and first intermonsoon seasons, 30 rainwater samples were collected over a five-month period from November 2021 to March 2022, in Kerawalapitiya (site A), Sapugaskanda (site B), and Kadawatha (site C), all densely populated and heavily industrialized areas, and Keragala (background site D), a rural area in Gampaha district where anthropogenic influence is minimal. Based on volume weighted mean (VWM) pH variation, Kadawatha area showed acidic precipitation (5.21±0.3) during the study period, while sites A (6.81±0.3), B (5.75±0.8) and D (6.12±0.2) had alkaline pH values. The neutralization factors (NFs) for the major cations (Na+, K+, Mg2+,Ca2+, and NH4+) in the precipitation indicated that higher levels of Na+ and NH4+ contributed to the neutralization of the acidic components at sites A and D, respectively. The VWM concentrations of ionic species were determined by ion chromatography followed the order of Na+> Ca2+>SO42-> Mg2+>NO3->Cl->NH4+>K+>Br-> F- in Kerawalapitiya, NO3->SO42->Ca2+>Na+> Cl-> K+> NH4+>Mg2+> Br->F- in Sapugaskanda and SO42->NO3->Na+> K+>Cl->Ca2+>Mg2+>Br->F- in Kadawatha. Nevertheless, Keragala showed a relatively low ionic composition, and it was in the order of NO3->NH4+>Na+>Cl->Ca2+>K+> SO42->Mg2+>Br->F-. There was a reduction in the VWM SO42- concentration in the Sapugaskanda site compared to a previous study done in this area in 2021. This may be due to the time-to-time shutdown of the Sapugaskanda oil refinery during the study period for the first time since 1969. Enrichment factors (EFs) associated with the sea (EFsea)and crust (EFcrust) confirmed that the Cl- ions at all four sites were marine in origin, although Ca2+, K+, and SO42- were not from marine sources. In addition, the values of EFsea and EFcrust for SO42- and NO3- showed greater than 1 in all four sites. This may be due to human activities in the study area. Also, Mg2+ has a significant contribution from both marine and soil at sites B, C, and D, while it is of anthropogenic origin at site-A. VWM metal concentrations determined by ICP-MS revealed that all sites had higher values for Al, Mg, K, and Zn, but lower concentrations of Cd, As, Co, and Cr. The results of this study further confirmed that rainwater analysis is an indirect indicator of air quality in a given area.
Drinking water treatment plant sludge as a potential adsorbent for the removal of Cadmium in wastewater
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Rajakaruna, R. M. A. S. D.; Sewwandi, B. G. N.
Water pollution by heavy metals is a critical environmental issue that causes the deterioration of both human and ecosystem health. Cadmium (Cd2+) is a heavy metal that is non-biodegradable and bioaccumulated through food chains. It also acts as a severe human carcinogen. Adsorption is an effective wastewater treatment method for removing heavy metals from wastewater which is limited due to the high cost of conventional adsorbents. In Sri Lanka, drinking water treatment plant sludge is being produced in large quantities and disposed on landfills without proper usage and exacerbating solid waste problems. The present study investigated the potential of using drinking water treatment plant sludge for the removal of Cd2+ by adsorption from wastewater. The effect of pH, initial Cd2+ concentration, and contact time on adsorption of Cd2+ onto drinking water treatment plant sludge was examined. Adsorption isotherm studies and kinetic studies were carried out to describe the adsorption mechanism of Cd2+ onto drinking water treatment plant sludge. The Langmuir and Freundlich isotherm models were used for isotherm studies. The pseudo first-order and pseudo second-order models were used in kinetic studies. The experiments on effect of pH on adsorption of Cd2+ in the range of pH 3 - 8 showed that adsorption is maximum when medium is basic (pH 7-8). The experiments on effect of initial Cd2+ concentration on adsorption showed that with the increase in initial Cd2+ concentration (2.5 – 100 mg L-1), the adsorption capacity of drinking water treatment plant sludge increased reaching to a maximum adsorption capacity of 14.6 mg g-1. Cd2+ was well fitted to the Langmuir isotherm model indicating monolayer adsorption on a homogeneous adsorbent surface with identical active sites. The experiments on effect of contact time on adsorption showed that adsorption of Cd2+ onto drinking water treatment plant sludge increased with the increase in contact time and then reached the equilibrium within 4 hours of contact time. The kinetic studies showed that adsorption of Cd2+ onto drinking water treatment plant sludge was well described by both pseudo first-order model (R2= 0.9633) and pseudo second-order model (R2=0.9334) indicating that both chemical and physical adsorption contribute to the adsorption of Cd2+ onto drinking water treatment plant sludge. Therefore, this study proves that drinking water treatment plant sludge is an effective, low-cost adsorbent for removing Cd2+ in wastewater. Therefore, future studies are required to be conducted on the field scale application of drinking water treatment plant sludge which will be beneficial for cost-effective wastewater treatment, especially in developing countries.
Hypoglycemic effect and antioxidant effect of pressured water extracts of Alpinia
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) De Silva, P. H. U. W.; Jayawardena, B. M.
Diabetes mellitus is a chronic metabolic condition that accounts for 1.5 million deaths annually worldwide. Since oral hypoglycemic medicines have adverse effects, there is a growing interest in employing herbal remedies for diabetes mellitus. Alpinia calcarata, a medicinally important plant from the Zingiberaceae family that grows in tropical climates like Sri Lanka and India, has a range of therapeutic uses. The rhizome of the plant has been used as a traditional systemic medicine in Sri Lanka for respiratory tract conditions, including asthma, cough, and bronchitis, as well as for inflammatory conditions like arthritis and metabolic disorder like diabetes mellitus. Since antioxidant activity inhibits hypoglycemic related complications, if A. calcarata rhizomes contain phytochemicals with antioxidant activities, it would be beneficial for diabetic patients. Therefore, the objective of this study was to investigate the hypoglycemic activity and antioxidant activity of low pressurised water extract (LPWE) and medium pressurised water extract (MPWE) of dried A. calcarata rhizomes. Phytochemicals in the ground rhizome of A. calcarata were extracted into the water by low pressurised water extraction method (0.098 MPa, 200 mL for 10 minutes) and medium pressurised water extraction method (0.103 MPa, 121°C, 100 mL for 20 minutes). The hypoglycemic effect was determined by performing the α- amylase inhibitory assay and glucose uptake by Yeast cells assay for three glucose concentrations (5 mM, 10 mM, and 25 mM). According to the results of α-amylase inhibitory assay, the IC50 values of LPWE and MPWE were 166.8 ± 0.1 μg/mL and 152.1 ± 0.1 μg/mL, respectively. The glucose uptake by Yeast cell assay has revealed that the rate of glucose uptake by the plasma membrane of the yeast cell in all three glucose concentrations (5 mM, 10 mM, and 25 mM), was linear and the percent increase in the glucose uptake by the yeast cells was found to be inversely proportional to the glucose concentration. The antioxidant ability was assessed by performing the Ferric reducing antioxidant power (FRAP) assay, and by comparing the absorbance changes at 593 nm in both pressured water extracts with a standard series of ferrous ions (100-1000 μM). The FRAP value of MPWE exhibited a higher FRAP value than that of LPWE and both LPWE and MPWE were proportionate to their concentrations. Altogether, the results revealed that the LPWE and MPWE of dried A. calcarata rhizomes may have both hypoglycemic and antioxidant activities. Additionally, the current study suggests that preparing MPWE is a more effective way than preparing LPWE for obtaining more hypoglycemic phytochemicals from the dried rhizome of A. calcarata.
Design of heat sink and simulation of electronic cooling of power transistor circuit
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Gunasinghe, L. M.; Samaranayake, W. J. M.; Hansameenu, W. P. T.
Heat sinks are utilized in industrial equipment to disperse surplus heat from heat-generating components to the surrounding environment. In recent years, efforts have been made to develop mechanical or electronic devices that are lighter, smaller, and more affordable. Heat dissipation from the heat sink is a major issue that many researchers are attempting to address. In this work, a traditional heat sink design technique of computer power supplies, which is extending fin topology, is used with four power transistors. This study attempts to improve the cooling of power transistor circuits by designing a new heat sink attached to four power transistors and seeing how the joule heating profile of the power transistor circuit and heat sink are changed. COMSOL Multiphysics version 5.6 software is used to graphically design the heat sink, four-transistor circuit and simulate the heat profile of the design. An electric currents interface and a heat transfer in solids interface are included in the Multiphysics interface. The multiphysics couplings add electromagnetic power dissipation as a heat source and investigate the joule heating and the temperature distribution on power transistors without the heat sink and with the heat sink. Transistors without the new heat sink get heated more than the transistors with the new heat sink with the same applied current density to the circuit board. It shows that joule heating is minimized with the new heat sink design. Here, the results of several studies of a new geometrical 3D model that focus on four power transistors attached to an aluminium heat sink are discussed. The results show the impact of the heat sink area and surface-to-ambient radiation to the power transistors and the circuit board. Based on the simulation results, four transistors become very cooled with the new heat sink design. How the heat-sink thermal performance is affected by shapes and space between fins is also reviewed. It could be observed that in the proposed design, the joule heating was reduced remarkably.
Electrochemical conversion of graphite to graphene oxide and electrophoretic deposition of graphene oxide
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Rifka, A. R. F.; De Silva, D. S. M.
Graphene and graphene oxide (GO) have gained huge importance in multiple fields, including chemistry and physics due to the desirable and incomparable properties which they possess. Practical applications of graphene and graphene related materials (GRM) such as graphene and GO is a progressive topic in the research world. Various methods are available for the synthesis of graphene and GO. Conventional chemical methods have the drawbacks of the evolution of toxic gases, which are highly expensive and environmentally unfriendly. Current approaches targeted on increasing the yield of GO synthesis with minimal environmental effects using vein graphite obtained from Bogalapathala, Sri Lanka. The electrochemical methods are much more favoured since they are scalable, high yielding, cost effective and less time consuming. In this work, an electrochemical synthesis method was followed in the production of GO by oxidizing graphite and subsequently, its electrophoretic deposition was carried out on various substrates. During the first part of the research, electrochemical exfoliation of graphite to GO was carried out using (NH4)2SO4 solution as the electrolyte. Initially, a cylindrical graphite pellet was made using graphite powder and was covered with a cellulose bag. Electrolysis was carried out by using the prepared graphite pellet as the anode and carbon electrode as the cathode. Various experimental conditions were tested to find out the optimum conditions which give rise to an efficient electrolysis with a maximum production yield of GO. Concentration of (NH4)2SO4 was varied from 0.5 M to 1.0 M, electrochemical exfoliation time was varied from 1 to 8 hours, applied voltage was varied as 5 V, 10 V and 15 V, the temperature was varied from 30 ℃ to 50 ℃ and mechanical stirring speed was varied from 100 rpm to 300 rpm. The second part of the research is based on the electrophoretic deposition of GO. This was carried out by using Pt as one terminal and glass-FTO or the stainless steel substrate as the counter terminal. The process was carried out using a mixture of N,N- DMF and MgCl2.6H2O as the dispersion medium. The GO coatings were annealed at 350 ℃ under N2 atmosphere as the post electrophoretic deposition treatments. The experiments resulted in a maximum yield of 59.25% of GO. The UV-Visible, the FTIR spectra and XRD diffractograms obtained confirmed the formation of GO. The two main factors which cause the exfoliation of graphite are; intercalation of ions between the adjacent layers of graphite and the expansion of graphite induced by the evolution of gases at the electrodes. This research revealed that the GO can be effectively synthesized using a (NH4)2SO4 electrolyte (1 M) under an applied voltage of 15 V, at a temperature of 50 ℃ with mechanical stirring (300 rpm) for 8 hours. Moreover, a uniform coating of GO was deposited on the glass-FTO and stainless steel substrates in both organic and inorganic suspension media of N,N- DMF and MgCl2.6H2O, respectively. This communication brings a viable method of synthesizing GO from vein graphite, using an environmentally benign and less costly method, into the spotlight.
The potential use of aquaculture pond sludge and fish waste to produce Eisenia fetida (Lumbricidae), Vermiwash: an approach towards sustainable aquaculture and fisheries industry of Sri Lanka
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Madhusanki, F. H. S.; Epa, U. P. K.
Pond bottom sludge and fish waste are considered as major environmental pollutants in the aquaculture and fish processing industries and managing them are necessary to reduce their negative environmental impacts. In pond aquaculture practices, different amounts of nutrients are generated depending on the culture conditions and biological processes of fish and the environment. In the present study, aquaculture sludge and fish waste were used as bedding materials to produce vermiwash using Eisenia fetida. Under field conditions, vermiwash was prepared using three combinations of substrates, including (i) cow dung & Gliricidia leaves (control as industrial practice), (ii) cow dung & aquaculture sludge and (iii) cow dung & fish waste in a 2: 1 ratio and three replicates from each combination. E. fetida (250 earthworms per 6 kg of bedding materials) were introduced to each vermiwash preparation unit and fresh vermiwash samples were collected weekly after 15 days of introducing E. fetida to experimental units for four consecutive weeks. Chemical parameters including pH, conductivity, chemical oxygen demand (COD), total nitrogen (TN), orthophosphate (Ortho-P) and total potassium of vermiwash samples were measured. A germination test was conducted using Phaseolus vulgaris seeds with experimental vermiwash samples extracted in the fourth week. After three months, the number of earthworms in vermiwash units was counted to assess their survival ability. TN in aquaculture sludge vermiwash (0.22±0.20%) was comparatively higher than the fish waste (0.09±0.04%) and the control (0.16 ± 0.15%). However, TN among the control and treatment vermiwash solutions were not significantly different (P = 0.783). P. vulgaris seeds treated with aquaculture sludge vermiwash had the highest percentage of seed germination (63.3%). The germination of seeds (%) in the distilled water was 61.7% and 47.2 % in the control. The lowest seed germination was observed in the fish waste vermiwash (33.7%). The number of E. fetida in vermiwash preparation units of the control and aquaculture sludge increased by 49.2% and 33.3%, respectively, from the initial introduction. Higher mortality of E. fetida was observed in the fish waste vermiwash preparation, and only 9.2% of E. fetida survived at the end of the experiment. It can be concluded that, aquaculture sludge can successfully be used as a bedding material for vermiwash production as it supports the multiplication of E. fetida which also contains higher TN content and higher seed germination of P. vulgaris. Except for the low K level, aquaculture sludge vermiwash is chemically comparable with the control vermiwash. However, fish waste was not suitable to prepare vermiwash in the proportions tested in this study as E. fetida couldn’t multiply and survive in this bedding material. The seed germination in fish waste vermiwash treated P. vulgaris seeds is also low. Aquaculture sludge can successfully be used as a bedding material for vermiwash production as it supports the multiplication of E. fetida, contains comparatively higher TN content and increases the seed germination (%) of P. vulgaris.
Sampling and analysis of Microplastics in the coastal area from the Estuary of Kelani River to the Estuary of Mahaoya
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Weerasekara, P. G. Y. W.; De Silva, D. S. M.; De Silva, R. C. L; Amarathunga, A. A. D.
Plastic particles that are less than 5 mm in dimension are referred to as microplastics (MPs). The formation of MPs can occur either by fragmentation of macroplastics (secondary MPs) or the production of micro-sized plastics (primary MPs) for intended applications. MPs have been identified as an emerging threat to the environment. MP pollution in marine environments around the globe is severe, and enough precautions have not been taken so far for its prevention. The focus of this study was to adopt suitable methods to collect and separate MPs from beach sediment and seawater samples and to identify their presence and the type by the optical microscopy and FTIR-ATR spectroscopic techniques, respectively. Therein, the distribution, types and abundance of MPs along the western coast from the Estuary of the Kelani River to the Estuary of Mahaoya in Sri Lanka were investigated while selecting nine sites along a stretch of 42 km (Hendala, Wattala, Uswetakeiyawa, Sarakkuwa, Bopitya, Dungalpitiya, Morawala, Browns beach and Estuary of Mahaoya). Random sampling was employed to collect a minimum of 8 sediment samples from each site within a 100 m area stretch in the intertidal zone of the beach during October and December 2021. Water samples were also collected parallel to the sediments from the ocean surface. A digestion method was tested and validated using KOH and Methanol. Sodium bromide was used as the density separator to extract MPs from sediment samples as an efficient method. The analysis revealed the presence of MPs in different colours (blue coloured fragments, blue and white coloured fibers, and white and yellow pellets and foams). The FTIR analysis revealed that most of the MPs found were thermoplastic polymers of polyethylene (PE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET) while some are thermosetting polymers of phenol formaldehyde (PF). Amid the 81 water samples analyzed, the mean abundance varied from 161 items/L (in Hendala) to 2 items/L (in Kepungoda and Browns Beach). Among, the 166 sediments samples analyzed, the mean abundance of MPs varied from 656 items/m2 (in Estuary of Mahaoya) to 3 items/m2 (in Dungalpitiya). The MPs found were identified in different shapes as fragments (80.15%), pellets (14.88%), fibers (2.7%) and foams (2.48%). The FTIR analysis revealed that the beach sediments are mainly contaminated with PE (65.27%) and PP (15.28%) while surface seawater is dominated by PE (60.87%) and PP (4.34%).
Development of an eco-friendly and cost-effective novel preparation of herbal textile – An Ayurvastra
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Nishan, S. P. A. S.; Wickramasinghe, M. R. M.
Ayurveda is an ancient system of medicine that focuses on the preventive or prophylactic and curative aspects of health. ‘Ayurvastra’ is a combination of the words ‘Ayuh’ and ‘Vastra’. Ayuh refers to long life and Vastra means clothing. The process of developing medicinally treated fabric involving Ayurveda to preserve health in an eco-friendly manner is a great way of adopting a healthy life. Ayurveda has endless scope to capture the global market for Ayurveda products. Foreign currency earnings by Ayurveda in 2020 was US$ 4571.7 million. The objectives of this project were to develop a novel preparation of Ayuvastra treated by herbal raw materials with natural dyeing process to provide human friendly textiles to preserve natural health of people, to introduce eco-friendly manufacturing process of herbal extracts treated clothes for modern textile industry instead of chemical dyeing process and to enhance the trend of use of herbal treated fabrics in Sri Lankan textile industry targeting with international fabric market. In this study, the pharmaceutical analysis of selected herbal raw materials (Aralu- Terminalia chebula, Neem- Azadirachta indica, Turmeric- Curcuma longa, Lime-, Citrus aurantifolia) were reviewed from previous research articles. Reviewed pharmaceutical analysis of bioactive ingredients of selected plants’ raw materials showed anti- septic, anti-allergic, antifungal, anti-inflammatory, antimicrobial, and immunomodulatory in antioxidant properties. The sample was prepared following several cryogenic procedures. Selected cotton graige fabric was bleached with lime juice and the gumming process was conducted by immersion in Aralu decoction, then soaked into filtered Neem and Turmeric decoction, and heated under mild flame while being stirred. The medicinally treated cloth was washed by diluted decoction to remove additional colour and dried in air. As per reviewed data, it can be concluded that Ayurvastra can be used for skin infections, eczema, hypertension, asthma, diabetes and a broad range of diseases and it is based on the therapeutic effect of used herbal raw materials for manufacturing. Further, pharmaceutical analysis will be conducted to evaluate therapeutic efficacy of medicinally treated fabrics.
In-vivo growth control of Aspergillus flavus on stored rice using microencapsulated cinnamon leaf oil
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Kumarathunga, P. G. J. D.; Wickramarachchi, S. R.
Poor storage conditions of rice lead to fungal infestation associated with severe health problems in humans. Aspergillus flavus is one of the significant storage fungus responsible for producing aflatoxins on stored grains. The use of cinnamon leaf oil (CNO) as an antifungal agent has gained great interest because of its low mammalian toxicity, high efficacy and availability. However, the direct application of CNO possesses many drawbacks, such as loss of bioactivity due to volatilization and degradation of active compounds and contribution to unpleasant taste and odour of foods. Microencapsulation is an efficient technique that can be used to overcome those drawbacks and obtain controlled release. This study aimed to determine the in-vivo growth control of A. flavus on rice by CNO-chitosan microcapsules (CNO-CS-MCs). CNO was encapsulated within biodegradable polymeric chitosan by ionotropic gelation method with sodium tripolyphosphate as the crosslinking agent. CNO was obtained from the local market and characterized using Gas Chromatography-Mass Spectrometry (GC-MS). Rice samples (Bg 11-11) were obtained from Rice Research Institute, Bathalagoda, Sri Lanka. Aspergillus flavus was isolated from stored rice and tentatively identified as A. flavus using morphological features and DNA sequencing. The minimum inhibitory dose and minimum lethal dose of free CNO and microencapsulated CNO against A. flavus were evaluated under in-vivo conditions. The GC-MS analysis of CNO showed the presence of eugenol (56.49 %), -caryophyllene (9.03 %), benzyl benzoate (8.43 %) and linalool (6.0 %) as the major constituents. Free CNO mixed with rice grains showed 100±0.00 % growth inhibition (visible) of A. flavus at 2 mg of oil (minimum inhibitory dose) and there was no revival of the growth of the fungus treated with ≥ 5 mg (minimum lethal dose) of oil, in PDA media. Both minimum inhibitory and minimum lethal doses of CNO-CS-MCs treated rice samples were higher than that of free CNO. The minimum inhibitory dose of CNO-CS-MCs mixed with rice grains was 5 mg and the minimum lethal dose was 12.5 mg, whereas those were 10 and 17.5 mg, respectively, in treatments with CNO-CS-MCs sachets. Both CNO and CNO-CS-MCs were fungistatic and fungicidal against A. flavus. This study indicated the potential of using microencapsulated CNO as a natural antifungal agent against the A. flavus.
Diversity of midgut symbiotic bacteria in Aedes mosquito genera: A meta-analysis
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Kumari, J. Y.; Amarasinghe, L. D.; Udayanga, N. W. B. A. L.; Ranasinghe, H. A. K.
The gut bacterial composition of mosquitos has the capability of altering mosquito pathogen transmission through numerous mechanisms, which is useful in novel transmission control strategies. Therefore, understanding the diversity of gut bacteria in different mosquito genera is highly important. The present analysis was carried out to evaluate the variations in gut-bacteria in field-caught Aedes adult mosquitos from different geographical locations. A literature survey was conducted to identify quantitative data related to the midgut bacterial abundance in Aedes, using standard search terms and keywords. The collected data were arranged at the bacterial class level and were subjected to a square-root transformation. A resemblance matrix was constructed based on the Bray-Curtis resemblance. Cluster analysis followed by the Analysis of Similarities (ANOSIM) and Distance based Redundancy Analysis (dbRDA) were used for data analysis. Gut bacterial abundance from six different countries; Netherlands, USA, Sri Lanka, India, Brazil, and Panama, were used in the study. A total of 12 bacterial classes, were recorded and bacterial classes of Alphaproteobacteria and Gammaproteobacteria accounted for the highest abundance in Aedes mosquitoes from most of the countries. Interestingly, Aedes mosquitoes from Brazil, India and Sri Lanka, did not report the abundance of Alphaproteobacteria in their gut contents. Based on the Bray-Curtis similarity-based cluster analysis, four major clusters were identified at a similarity level of 48.9%, based on the overall abundance of bacterial classes. Aedes mosquitoes of Sri Lanka and India formed one cluster, sharing a similarity of 81.6%, while Brazil and Panama formed another cluster. Meanwhile, Aedes mosquitoes from Netherland and USA formed two separate clusters. The statistical significance of aforementioned clustering status was further verified by the Analysis of Similarities (ANOSIM), which reported a Global R value of 0.96. The clustering status suggested by the cluster analysis was further verified by the findings of the dbRDA. As indicated by the loadings of the dbRDA axes, the abundance of Gammaproteobacteria and Bacilli bacterial classes were found to be responsible for the similarity between gut bacterial diversity in Aedes mosquitoes from India and Sri Lanka. Further studies on the gut-microbial diversity of Aedes mosquitoes are recommended to support the implementation of novel vector control strategies in Sri Lanka.
Medicinal plant identification and plant disease classification
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Senanayake, M. M. V.; De Silva, N. M. T.
Today, with the development of technology, most manual methods are replaced by automated computer systems to ease the lives of human beings. Plant identification and disease classification are two major agricultural research areas focusing on introducing computerized systems rather than manual methods. Many researchers used various identification and classification techniques to identify and classify plants and diseases using computer-based systems because human classification errors lead to risk and high costs. When it comes to medicinal plants, most people recognize them by their knowledge and experience. But there is a lack of people who know how to identify those valuable plants. Therefore, most of the time, it needs an expert in the field for the correct identification of medicinal plants and diseases. In this study, a medicinal plant identification and disease classification system is implemented, which can help any person who needs support in identifying medicinal plants and classifying diseased medicinal plants. This study targeted the design of herbal plant identification and classification of diseased leaves, with improvements to the existing systems. This work consists of two parts: medicinal plant identification and medicinal plant disease classification. Medicinal plant leaf images were taken as input for the models of this study. There is no standard database for medicinal plants in Sri Lanka. Thus, two datasets were collected separately for medicinal plant identification (dataset 1) and their disease classification (dataset 2). Each dataset consists of images of five different medicinal plants. But finding the diseased leaf images of plants was challenging and all the collected images of medicinal plant diseases for this research were fungi. The disease name of the medicinal plant is not very significant in traditional or Ayurvedic medicine. Therefore, five different medicinal plants were classified into two types as healthy and fungi including the plant type which leads to 10-class classification. Total images of dataset 1 are 2000, and dataset 2 are 2269. With the help of the literature review and various experiments, deep learning models were implemented according to the Convolution Neural Network (CNN) architecture and transfer learning separately. CNN models were assessed with and without image pre-processing methods, such as converting RGB colours to grayscale and applying image filters to remove noise. Eleven layers were used to build CNN model for identifying medicinal plants, while 14 layers were used to classify diseases. In transfer learning, MobileNet V2, Inception V3, and VGG 16 models were used to retrain the two datasets of this study. Here, a new block of layers is trained on top of the existing models to classify five classes of dataset 1 and ten classes of dataset 2. Furthermore, a comparison between CNN and transfer learning was carried out with four types of performance measurement matrices. Transfer learning models outperformed CNN models for medicinal plant identification with 99.5% accuracy for MobileNet V2 and their disease classification with 90% accuracy for VGG 16.
Sedimentology and depositional environment of neoproterozoic stromatolitic limestones of Langrial and Miranjani areas, Lesser Himalayas, Pakistan
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Ali, S. H.; Ali, S. F.; Shoukat, N.; Wahid, A.; Bashir, Y.; El-Aal, A. K. A.
Stromatolites are a helpful tool in predicting age, depositional environment and correlation of stratigraphic sequences over vast continents. Stromatolites are the signature of the Neoproterozoic age (1 billion years – 538.8 million years) to about 300 million years. This study highlights the detailed study of two stromatolitic limestone (Langrial and Miranjani) units of Hazara Formation, Lesser Himalayas, Pakistan, at various scales from outcrop, macroscopic and microscopic levels. These stromatolitic limestones are well known, but detailed sedimentological work was not present. The rock types of the two units were differentiated based on their field examination using hand lens, testing with 10% diluted solution of HCl for carbonate rocks, as well as the stratigraphic column of the area. The field photographs taken were geo-referenced by Picasa software V. 3.9. Almost 500 field photographs were taken during the study. Petrographic thin sections of thirty rock samples were made based on facies types. The facies of the limestone units of the Hazara Formation were determined using section measurement. The limestone is grey nodular limestone, with no observed sedimentary structures. The nodules are about 5-10 cm. The limestone beds are about 40-110 cm thick. There are four types of facies present in this formation, namely, carbonate mudstone facies, stromatolitic facies, nodular limestone facies, and thin to thick-bedded limestone. The facies indicate a variety of depositional environments. Petrography reveals that the limestone is dominantly micritic in nature. It also shows that the limestone is parallel laminated, non-laminated, with no bivalves, foraminifera or recognizable fossils. It also shows the presence of feldspar, quartz and clay minerals. Here, in the Hazara Mountains, limestone units are bounded by turbidites, which are deep sea deposits. However, these stromatolitic limestones form in a very shallow marine environment like tidal flats in modern environments. Such stromatolitic limestones also occur in Neoproterozoic rocks of Sri Lanka, Nepal and India. Their study can help understand the occurrence of these limestone deposits in highly deformed Lesser Himalayas and the palaeogeography of the Indian Plate.
Mapping of well water and soil parameters in a selected Grama Niladhari division of Gampaha district
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Pathirana, H. P. K. V. T.; De Silva, R. C. L.
This study intends to fill an essential knowledge gap in the field of environmental information in Sri Lanka, by providing a reliable data bank supporting the information of existing chemical species of two important components, well water and soil. Further, this study would provide reference information for future work and aid in explaining the changes that would occur due to the changes in chemical composition of the environment. Thalawathuhenpita North Grama Niladhari division was selected as the initial site of study and sampling was done from 23 locations, where two representative samples of each soil and well water were collected from each site. All chemicals, instruments and glassware used were from recognized chemical supply companies. This study investigates several important well water quality parameters such as pH determined by a pH meter, well water hardness and Calcium content using complexometric titrations, nitrate content using a spectrometric analysis, Iron content using a colorimetric analysis, and soil quality parameters such as active pH using a pH meter, water-soluble and exchangeable cations (Na+, K+) using a flame photometer and water-soluble and exchangeable Ca2+ using complexometric titration, organic matter content using a redox titration, iron content and nitrate content were determined similar to well water analysis. The readings were duplicated and reported as means ± standard deviation, and contour maps were produced using Surfer ® (Golden Software, LLC). Maps depict the scope of variation of the determined parameters within the selected area and highlight that it is crucial to monitor the environmental resources chemically in a regular manner to address the environmental problems that may occur in the future. The mapping of the entire country on a fixed and frequent basis will give environmentalists, scientists and policymakers information about a given environment and thus make monitoring and policy making of an area easy.
Comparison of sensitivity of Lemna perpusilla (minute duckweed) to chromium, nickel, and zinc ions
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Ariyawansha, J. M. M. S.; Pathiratne, A.
In recent times, the pollution of tropical aquatic ecosystems due to heavy metals has become a great issue. The major sources of heavy metal pollution in aquatic ecosystems are effluents from metal-based industries and municipal wastewater. Duck weeds (Lemna species) are widely used in the treatment of wastewater and sewage effluents as they have the ability to absorb nutrients in the wastewater effectively. The species, Lemna minor and L. gibba generally represent temperate areas while L. perpusilla is native to Southeast Asia. Objective of the present study was to compare the sensitivity of L. perpusilla to chromium (Cr), nickel (Ni), and zinc (Zn) ions under tropical temperature exposure based on standard laboratory ecotoxicity tests. Growth reduction of L. perpusilla under Cr, Ni, and Zn exposure was assessed using a standard ecotoxicity procedure with a range of metal ion concentrations (Cr6+: 0, 12, 30, 60, 90 and 120 mg/L; Ni2+: 0, 0.03, 0.06, 0.15, 0.30 and 0.60 mg/L; Zn2+: 0, 0.1, 0.25, 0.5, 1.0 and 2.0 mg/L). Toxicity thresholds of Cr6+, Ni2+ and Zn2+ for the duckweed L. perpusilla under tropical temperature exposure (27°C - 29°C) were estimated based on multiple endpoints (total number of fronds, percentage of green fronds and green frond area). Triplicate test vessels were used for each concentration and the controls. The average specific growth rate and percent inhibition growth rate for each treatment and control replicate were determined. Metal contents in the exposure media were analytically verified using atomic absorption spectrophotometry. One way ANOVA followed by Dunnett’s test was used to estimate the lowest observed effect concentration (LOEC) for each endpoint. Effective concentrations of metals at different percentile effect levels (EC50, EC20, EC10 and EC5) were estimated through nonlinear regression modelling using USEPA Toxicity Relationship Analysis Program software. Based on different endpoints used for the toxicity assessments, lowest observed adverse effect concentrations (7 day LOAEC) for growth reduction of L. perpusilla for Cr6+, Ni2+, and Zn2+ were estimated as 21 mg/L, 0.06 mg/L, and 0.26 mg/L, respectively. For growth reduction of L. perpusilla, the most sensitive 7-day effective concentration for 10% effect (EC10) for Cr6+, Ni2+, and Zn2+ were 21 mg/L, 0.021 mg/L, and 0.2 mg/L, respectively. In conclusion, the sensitivity of L. perpusilla to the three metal ions followed the decreasing order: Ni2+ > Zn2+ > Cr6+. This study revealed that L. perpusilla is more sensitive to Ni2+ than Cr6+ and Zn2+. Of the three metals tested, Cr6+ exposure could be most tolerated by L. perpusilla.
Modelling extreme motor insurance claims with extreme value theory: A case study from Sri Lanka
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Appuhamy, P. A. D. A. N.; Boralessa, N. K.
In recent years, the motor insurance business has grown significantly in Sri Lanka due to the excessive importation of vehicles. However, the large volumes of vehicles on the road increase the risk of occurrence of extreme claims, which undermine the profit and sustainability of the business. In response to this, researchers attempted to model the extreme claims as accurate information on the tail is critical to determine the appropriate level of insurance premium, reserves and re-insurance, which assures a profitable business. The objective of this study is to identify the best fit model for extreme motor insurance claims. The motor claims obtained from one of the pioneer insurance companies in Sri Lanka from July to December 2021 were considered for this study. The Peak Over Threshold (POT) approach of the Extreme Value Theory was utilized for modelling, which approximates the excess claim amounts over a sufficiently high threshold as the Generalized Pareto Distribution (GPD). The claim amounts at 20 percentiles between 79% and 98%, which covers the range of values proposed in the literature for sufficiently high thresholds, were considered as tentative thresholds to find the optimal that separates extremes from bulk. Then the excess amounts over each of these tentative thresholds were modelled separately as GPD using four different parameter estimation methods, viz. Maximum Likelihood Estimation (MLE), Method of Moment (MOM), Unbiased Probability Weighted Moment (UPWM) and Biased Probability Weighted Moment (BPWM) to identify the best in case of the dearth of information for the tail. Next, the accuracies of the fitted GPDs at each tentative threshold for each parameter estimation method were evaluated by calculating the Mean Squared Errors (MSEs). Then MSEs were compared to select the optimal threshold and the best parameter estimation method, which yielded the best fit model for tail data. The threshold and the parameter estimation method with minimum MSE were selected as the optimal threshold and the best parameter estimation method, respectively and the GPD fitted under these conditions was selected as the best. The validity of modelling as the GPD was tested using the bootstrap goodness of fit. It was revealed that the amount of motor claims varied from Rs. 2,167.00 to 193,065.00 during the study period. Moreover, the motor claims were positively skewed with a skewness of 2.45 and leptokurtic, which confirms heavy-tailed. The minimum MSE was attained at the threshold of 91% (Rs. 61,056.00) with the BPWM method. There were 47 claims above 91% identified as extremes which can be best described by GPD with shape and scale parameters of 1.02 and 92.09, respectively. The p-value (0.997>0.05) of the bootstrap test confirms the GPD with a positive shape parameter for extreme motor claims. Findings confirm the existing results in the literature that PWM methods are preferred when the shape parameter is positive and less than or equal to 1 and the sample size for modelling is small. The information on tail helps to review existing strategies for better management of risk due to such extreme claims in future.
Comparison between the Machine Learning Algorithms to determine the suitable input features for personal theft, sexual assault, and house burglary victimization prediction
(Faculty of Science, University of Kelaniya Sri Lanka, 2022) Lakshan, W. S. V.; Weerakoon, W. A. C.
The crime-related predictions can be vastly supported by most of the available supervised machine learning models. The possibility of becoming a victim increases daily in each crime category. The main difficulty is to find how severe the impact is upon the victim after the crime. Here, the Random Forest, Support Vector Machine (SVM), K-Nearest Neighbour (KNN) algorithm, and Neural Network models were compared with the use of available features found from a secondary dataset to build a better prediction model, which has been implemented in four main phases over two aspects based on the possibility of becoming a victim and severity of the crime. The available features were used as the inputs for phase I and Principal Component Analysis and correlation tests were performed to identify the appropriate and essential feature combinations for the rest of the phases. The pre-processed datasets were used to implement and train the models. Moreover, the Random Forest model was proven to be the most efficient model with an accuracy of 85.33% in phase four when comparing the accuracy levels of the models over different phases, while the KNN and Neural Network models obtained an accuracy of over 70% and SVM obtained the least accuracy in the same phase. In phase one, the Random Forest algorithm was executed with a precision of 76%, while KNN and Neural Network model obtained around 70%. The final outputs obtained for phase four showed that factors such as age, year, gender, race, and relationship with the perpetrator will be the most suitable features to build an accurate machine learning model for victimization prediction. The mentality level of the offender and intention of doing it has the main impact on the severity level. Also, authorities need to keep track of the fact whether it is a repeat offence or not, the main offender or not and the contribution of the offender to support better information inputs for the prediction models. This study developed a victimization prediction model with reference to personal theft, sexual assault, and house burglary. This would be a step forward from previous research works of rule-based victimization possibility index prediction for small victim clusters. Further, new features were identified in the last phase, which can be used to develop models to predict criminal behaviour after sending them back to the society. This will greatly benefit the authorized bodies to monitor them and reduce the possibility of victimization.