2023
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Publication Open Access Derivation of Bessel function closed-form solutions in zero dimensional φ4-field theory(Elsevier Ltd, 2022-02) Munasinghe, R. M.The integral is used as an introductory learning tool in the study of Quantum Field Theory and path integrals. Typically, it is analyzed via perturbation theory. Closed-form solutions have been quoted for which I could not find any derivation. Using a simple and elegant transformation, the close form solutions for the integral and its even positive integer moments can be obtained in terms of Bessel functions.Publication Open Access COMPARATIVE STUDY ON THE STORMWATER RETENTION OF ORGANIC WASTE SUBSTRATES BIOCHAR, SAWDUST AND WOOD BARK RETRIEVED FROM PSIDIUM GUAJAVA L. SPECIES(University of Montenegro, 2023) Kader, S.A; Jaufer, L; Bashir, O; Raimi, M. OThis research compares the stormwater retention performances of an organic waste growing medium extracted from the widely available Psidium guajavala L species in Sri Lanka. Rainfall gauges were manually constructed to outsource accurate precipitation data, and the study was conducted throughout the entire month of January 2023. A stormwater retention curve was constructed for the Biochar, Sawdust and Wood bark substrates and the hotspots were compared. Furthermore, the results were validated using a volumetric comparison of water retention. The experimental outcomes have shown that Biochar exhibits strong water retention ability and enables the overlaying vegetation to acquire nutrients without external obstacles. The main reason for this exceptional performance was biochar's low evaporation levels and high porosity. In contrast, Sawdust was found to be the worst performer in terms of water retention due to its high thermal conductivity. These experimental studies were rationalised by outsourcing the specimen from the same tree. Our recommendations suggest that the biochar manufacturing industry needs to be improved in the future since it provides a sustainable and effective alternative in terms of eco-friendly substrates.Publication Open Access Influence of Laboratory Synthesized Graphene Oxide on the Morphology and Properties of Cement Mortar(MDPI, 2023-01) Ganesh, S; Thambiliyagodage, C; Perera, S. V. T. J; Rajapakse, R.K.N.DThe introduction of Graphene Oxide (GO), a nanomaterial, has shown considerable promise in improving the mechanical properties of cement composites. However, the reasons for this improvement are not yet fully understood and demand further research. This study aims to understand the effect of laboratory-produced GO, using Tour’s method, on the mechanical properties and morphology of cement mortar containing GO. The GO was characterized using Fourier-transform infrared spectroscopy, X-ray Photoelectron Spectroscopy (XRD), X-ray powder diffraction, and Raman spectroscopy alongside Scanning electron microscopy (SEM). This study adopted a cement mortar with GO percentages of 0.02, 0.025, 0.03, 0.035, and 0.04 with respect to the weight of the cement. The presence of GO in cement mortar increased the density and decreased the consistency and setting times. At the optimum of 0.03% GO viscous suspension, the mechanical properties such as the 28-day compressive strength, splitting tensile strength, and flexural strength were enhanced by 41%, 83%, and 43%, respectively. In addition, Brunauer–Emmett–Teller analysis indicates an increase in surface area and volume of micropores of GO cement mortar, resulting in a decreased volume of mesopores. The improvement in properties was due to increased nucleation sites, calcium silicate hydrate (CSH) density, and a decreased volume of mesopores.Publication Open Access Fabrication of r-GO/GO/α-Fe2O3/Fe2TiO5 Nanocomposite Using Natural Ilmenite and Graphite for Efficient Photocatalysis in Visible Light(MDPI, 2023-01) Usgodaarachchi, L; Jayanetti, M; Thambiliyagodage, C; Liyanaarachchi, H; Vigneswaran, SHematite (α-Fe2O3) and pseudobrookite (Fe2TiO5) suffer from poor charge transport and a high recombination effect under visible light irradiation. This study investigates the design and production of a 2D graphene-like r-GO/GO coupled α-Fe2O3/Fe2TiO5 heterojunction composite with better charge separation. It uses a simple sonochemical and hydrothermal approach followed by L-ascorbic acid chemical reduction pathway. The advantageous band offset of the α-Fe2O3/Fe2TiO5 (TF) nanocomposite between α-Fe2O3 and Fe2TiO5 forms a Type-II heterojunction at the Fe2O3/Fe2TiO5 interface, which efficiently promotes electron-hole separation. Importantly, very corrosive acid leachate resulting from the hydrochloric acid leaching of ilmenite sand, was successfully exploited to fabricate α-Fe2O3/Fe2TiO5 heterojunction. In this paper, a straightforward synthesis strategy was employed to create 2D graphene-like reduced graphene oxide (r-GO) from Ceylon graphite. The two-step process comprises oxidation of graphite to graphene oxide (GO) using the improved Hummer’s method, followed by controlled reduction of GO to r-GO using L-ascorbic acid. Before the reduction of GO to the r-GO, the surface of TF heterojunction was coupled with GO and was allowed for the controlled L-ascorbic acid reduction to yield r-GO/GO/α-Fe2O3/Fe2TiO5 nanocomposite. Under visible light illumination, the photocatalytic performance of the 30% GO/TF loaded composite material greatly improved (1240 Wcm−2). Field emission scanning electron microscopy (FE-SEM) and high-resolution transmission electron microscopy (HR-TEM) examined the morphological characteristics of fabricated composites. X-ray photoelectron spectroscopy (XPS), Raman, X-ray diffraction (XRD), X-ray fluorescence (XRF), and diffuse reflectance spectroscopy (DRS) served to analyze the structural features of the produced composites. © 2022 by the authors.Publication Embargo An exact stiffness matrix method for nanoscale beams(CRC Press/Balkema, 2023-01) Wijesinghe, R.A.R; De Silva, K. K. V.; Sapsathiarn, Y.; Rajapakse, N.Conventional continuum theories are inapplicable to nanoscale structures due to their high surface- to-volume ratios and the effects of surface energy and inter-atomic forces. Although atomistic simulations are more realistic and accurate for nanostructures, their use in practical situations is constrained by the high computational cost. Modified continuum methods accounting for the surface energy are therefore considered computationally efficient engineering approximations for nanostructures. The modified continuum theory of Gurtin and Murdoch accounting for the surface energy effects has received considerable attention in the literature. This paper focuses on developing an exact stiffness matrix method for nanoscale beams based on the Gurtin-Murdoch theory. Past research has presented a classical finite element formulation to analyze nanoscale beams using the Galerkin weighted residual method. The proposed approach is based on the analytical solutions to the governing partial differential equations of nanobeams. These governing equations are established by using the Gurtin-Murdoch continuum theory. The general analytical solutions are used to derive the exact stiffness matrix and mass matrix of a beam finite element in closed form. The study examines the static and time-harmonic dynamic response of thin nanoscale beams. Normalized deflections and bending moments under concentrated and distributed loads are obtained for aluminum and silicon thin beams subjected to simply supported, cantilevered and clamped-clamped edges. Our results were compared with the available solutions in the literature, and close agreement was observed. Therefore, the method presented in this study serves as an efficient and accurate scheme to analyze nanobeams under static and dynamic loading compared to the conventional finite element schemesPublication Embargo Consolidation settlement of vertically loaded pile groups in multilayered poroelastic soils(Elsevier Ltd, 2023-01) Senjuntichai, T; Sornpakdee, N; Keawsawasvong, S; Phulsawat, B; Rajapakse, R.K.N.D.Pile groups are commonly used as the foundations of many structures including those used in transportation infrastructures. Consolidation settlement of a pile foundation is an important design parameter. A theoretical model is developed in this study to estimate the consolidation settlement and axial load transfer of vertically loaded pile groups in multilayered poroelastic soils. The multilayered saturated soil is modeled according to Biot's poroelasticity theory. In order to determine quasi-static response of pile groups, the interaction problem is first formulated in the Laplace transform domain. Vertical displacement compatibility is enforced at the pile-soil interface to simulate the pile group-soil interaction. Axial deformation of each pile is represented by an exponential series with undetermined coefficients, which are obtained from a variational approach. Vertical displacement influence functions due to a buried uniform vertical load applied to the layered soil are required in the formulation. The application of an exact stiffness matrix method yields the required influence functions. Time-domain solutions are obtained by employing a numerical Laplace inversion method. Numerical results for time-dependent vertical stiffness and consolidation settlement are presented for different pile group configurations, layer profiles, pile elastic moduli and pile lengths.Publication Embargo Development of a risk model for different innovator types in textile and apparel industries(Emerald Publishing, 2023-01) Kumarapeli, U; Ratnayake, V; Jayawardana, S. SPurpose – Technological innovation is one of the strongest driving forces in the survival and growth of any organization, including textile and apparel industries. However, technological innovation inherits a wide array of risks due to the uncertainty involved in it. In-depth research reveals the existence of a significant relationship between innovation failures and the approach used to innovate, that is, the organization’s innovator type. However, quantitative evidence supporting this concern is still lacking. Hence, the purpose of this paper is to bridge the existing gap in the literature on effective management of technological innovation risk factors and the innovator type of textile and apparel industries. Design/methodology/approach – The risk factors related to technological innovations are identified under different innovator types. Analytic network process (ANP) has been used to evaluate the contribution of risk factors according to the innovator type of the organization. Data was gathered through the literature review and structured and semi structured interviews with textile and apparel industry experts. The contribution of risk factors was determined through priorities, derived according to the ANP using Super Decision software. Findings – Contribution of risk factors takes different values according to innovator type. This provides comprehensive knowledge on developing a risk management strategy according to the innovator type of the organization. Furthermore, this provides insight into the fact that a generalized risk management strategy will not be effective and sensible for all innovator types. Originality/value – The findings provide a thorough understanding of developing a customized risk management strategy by determining the “most to least” criticality of risks based on the innovator type of the organization. Furthermore, findings can be used to adopt the most appropriate innovator type based on the organization’s key competencies. Moreover, this guides the organization in making the best use of internal resources during risk management. Furthermore, this provides insight into the risk factors that must be addressed prior to embarking on new innovative approachesPublication Open Access Wetland Water Level Prediction Using Artificial Neural Networks—A Case Study in the Colombo Flood Detention Area, Sri Lanka(MDPI, 2023-01) Jayathilake, T; Sarukkalige, R; Hoshino, Y; Rathnayake, UHistorically, wetlands have not been given much attention in terms of their value due to the general public being unaware. Nevertheless, wetlands are still threatened by many anthropogenic activities, in addition to ongoing climate change. With these recent developments, water level prediction of wetlands has become an important task in order to identify potential environmental damage and for the sustainable management of wetlands. Therefore, this study identified a reliable neural network model by which to predict wetland water levels over the Colombo flood detention area, Sri Lanka. This is the first study conducted using machine learning techniques in wetland water level predictions in Sri Lanka. The model was developed with independent meteorological variables, including rainfall, evaporation, temperature, relative humidity, and wind speed. The water levels measurements of previous years were used as dependent variables, and the analysis was based on a seasonal timescale. Two neural network training algorithms, the Levenberg Marquardt algorithm (LM) and the Scaled Conjugate algorithm (SG), were used to model the nonlinear relationship, while the Mean Squared Error (MSE) and Coefficient of Correlation (CC) were used as the performance indices by which to understand the robustness of the model. In addition, uncertainty analysis was carried out using d-factor simulations. The performance indicators showed that the LM algorithm produced better results by which to model the wetland water level ahead of the SC algorithm, with a mean squared error of 0.0002 and a coefficient of correlation of 0.99. In addition, the computational efficiencies were excellent in the LM algorithm compared to the SC algorithm in terms of the prediction of water levels. LM showcased 3–5 epochs, whereas SC showcased 34–50 epochs of computational efficiencies for all four seasonal predictions. However, the d-factor showcased that the results were not within the cluster of uncertainty. Therefore, the overall results suggest that the Artificial Neural Network can be successfully used to predict the wetland water levels, which is immensely important in the management and conservation of the wetlandsPublication Open Access Trends and Variabilities in Rainfall and Streamflow: A Case Study of the Nilwala River Basin in Sri Lanka(MDPI, 2023-01) Panditharathne, R; Gunathilake, M. B; Chathuranika, I.M; Rathnayake, U; Babel, M. S; Jha, M. KRainfall is one of the dominating climatic parameters that affect water availability. Trend analysis is of paramount significance to understand the behavior of hydrological and climatic variables over a long timescale. The main aim of the present study was to identify trends and analyze existing linkages between rainfall and streamflow in the Nilwala River Basin (NRB) of Southern Sri Lanka. An investigation of the trends, detection of change points and streamflow alteration, and linkage between rainfall and streamflow were carried out using the Mann–Kendall test, Sen’s slope test, Pettitt’s test, indicators of hydrological alteration (IHA), and Pearson’s correlation test. Selected rainfall-related extreme climatic indices, namely, CDD, CWD, PRCPTOT, R25, and Rx5, were calculated using the RClimdex software. Trend analysis of rainfall data and extreme rainfall indices demonstrated few statistically significant trends at the monthly, seasonal, and annual scales, while streamflow data showed non-significant trends, except for December. Pettitt’s test showed that Dampahala had a higher number of statistically significant change points among the six rainfall stations. The Pearson coefficient correlation showed a strong-to–very-strong positive relationship between rainfall and streamflow. Generally, both rainfall and streamflow showed non-significant trend patterns in the NRB, suggesting that rainfall had a higher impact on streamflow patterns in the basin. The historical trends of extreme climatic indices suggested that the NRB did not experience extreme climates. The results of the present study will provide valuable information for water resource planning, flood and disaster mitigation, agricultural operations planning, and hydropower generation in the NRB.Publication Open Access Projected Water Levels and Identified Future Floods: A Comparative Analysis for Mahaweli River, Sri Lanka(IEEE, 2023-01) Rathnayake, N; Rathnayake, U; Chathuranika, I; Dang, T. L; Hoshino, YThe Rainfall-Runoff (R-R) relationship is essential to the hydrological cycle. Sophisticated hydrological models can accurately investigate R-R relationships; however, they require many data. Therefore, machine learning and soft computing techniques have taken the attention in the environment of limited hydrological, meteorological, and geological data. The accuracy of such models depends on the various parameters, including the quality of inputs and outputs and the used algorithms. However, identifying a perfect algorithm is still challenging. This study develops a fuzzy logic-based algorithm called Cascaded-ANFIS to accurately predict runoff based on rainfall. The model was compared against three regression algorithms: Long Short-Term Memory, Grated Recurrent Unit, and Recurrent Neural Networks. These algorithms have been selected due to their outstanding performances in similar studies. The models were tested on the Mahaweli River, the longest in Sri Lanka. The results showcase that the Cascaded-ANFIS-based model outperforms the other algorithms. The correlation coefficient of each algorithm’s predictions was 0.9330, 0.9120, 0.9133, 0.8915, 0.6811, 0.6811, and 0.6734 for the Cascaded-ANFIS, LSTM, GRU, RNN, Linear, Ridge, and Lasso regression models respectively. Hence, this study concludes that the proposed algorithm is 21% more accurate than the second-best LSTM algorithm. In addition, Shared Socio-economic Pathways (SSP2-4.5 and SSP5-8.5 scenarios) were used to generate future rainfalls, forecast the near-future and mid-future water levels, and identify potential flood events. The future forecasting results indicate a decrease in flood events and magnitudes in both SSP2-4.5 and SSP5-8.5 scenarios. Furthermore, the SSP5-8.5 scenario shows drought weather from May to August yearly. The results of this study can effectively be used to manage and control water resources and mitigate flood damages.Publication Open Access Minimizing Liability of the COVID-19 Pandemic on Construction Contracts—A Structural Equation Model for Risk Mitigation of Force Majeure Impacts(MDPI, 2023-01) Chadee, A. A; Gallage, S; Martin, H. H; Rathnayake, U; Ray, I; Kumar, B; Sihag, PA pandemic is a force majeure event, and contracting parties can invoke conditions under force majeure to minimize liability for unforeseen, uncontrollable, and unavoidable circumstances. This study develops a conceptual model to assist in the management of delays and cost overruns due to force majeure events arising from the construction sector in Small Island Developing States (SIDS). A critical case study analysis of past epidemics and pandemics was conducted to develop a survey questionnaire for administration to construction professionals in Trinidad and Tobago. Based on the empirical data of 65 construction professionals, the structural equation model shows that there are strong causal effects from the implications of COVID-19 and force majeure events, which in turn have a dire impact on the construction industry. The leading implication of COVID-19 is the drastic increases in the cost of materials. Also, granting an extension of time to contractors was the main risk variable under the force majeure conditions. From the results, the measurement model verifies that events under force majeure and its perceived implications strongly influence the construction industry, and proposes that force majeure contractual clauses require explicit treatment of the periodic reoccurrence of pandemics to avoid conflicts among contracting parties. This research explores and builds on new avenues from the latest COVID-19 scholarship to better understand existing impacts on the construction industry, and consequently add to the novel body of knowledge on the implications of pandemics on construction contracts. Overall, this research provides a risk-guidance framework for construction professionals and academia to mitigate unforeseen, uncontrollable, and unavoidable risks on construction projectsPublication Open Access Evaluation of the Impact of Land Use Changes on Soil Erosion in the Tropical Maha Oya River Basin, Sri Lanka(MDPI, 2023-01) Palliyaguru, C; Basnayake, V; Makumbura, R. K; Gunathilake, M. B; Muttil, N; Wimalasiri, E. M; Rathnayake, USoil degradation is a serious environmental issue in many regions of the world, and Sri Lanka is not an exception. Maha Oya River Basin (MORB) is one of the major river basins in tropical Sri Lanka, which suffers from regular soil erosion and degradation. The current study was designed to estimate the soil erosion associated with land use changes of the MORB. The Revised Universal Soil Loss Equation (RUSLE) was used in calculating the annual soil erosion rates, while the Geographic Information System (GIS) was used in mapping the spatial variations of the soil erosion hazard over a 30-year period. Thereafter, soil erosion hotspots in the MORB were also identified. The results of this study revealed that the mean average soil loss from the MORB has substantially increased from 2.81 t ha−1 yr−1 in 1989 to 3.21 t ha−1 yr−1 in 2021, which is an increment of about 14.23%. An extremely critical soil erosion-prone locations (average annual soil loss > 60 t ha−1 yr−1) map of the MORB was developed for the year 2021. The severity classes revealed that approximately 4.61% and 6.11% of the study area were in high to extremely high erosion hazard classes in 1989 and 2021, respectively. Based on the results, it was found that the extreme soil erosion occurs when forests and vegetation land are converted into agricultural and bare land/farmland. The spatial analysis further reveals that erosion-prone soil types, steep slope areas, and reduced forest/vegetation cover in hilly mountain areas contributed to the high soil erosion risk (16.56 to 91.01 t ha−1 yr−1) of the MORB. These high soil erosional areas should be prioritized according to the severity classes, and appropriate land use/land cover (LU/LC) management and water conservation practices should be implemented as recommended by this study to restore degraded lands.Publication Open Access Modelling the Implications of Delayed Payments on Contractors’ Cashflows on Infrastructure Projects(Salehan Institute of Higher Education, 2023-01-01) Chadee, A; Ali, H; Gallage, S; Rathnayake, UThe consideration of payments to contractors is not only a legal obligation but a necessity for assuring the continuity and completion of a construction project. However, consistent payments to facilitate project cash flows are uncommon in the construction industry. Within the context of a small island developing state, this paper aims to uncover leading risks factors contributing to implications of delayed payments, on contractors’ cash flows and uncover causalities and effects on relationships among these factors. A two-tiered quantitative approach was adopted. Firstly, a compiled list of delay factors was collated from the literature review. Semi-structured interviews were conducted with experienced construction professionals to determine the factors’ relevance and applicability in Trinidad and Tobago. A closed-ended survey questionnaire was subsequently developed and administered to primary construction stakeholders. Secondly, the responses obtained were collated, validated, and ranked using the relative importance index. A confirmatory factor analysis (CFA) was carried out using SPSS, and thereafter, SPSS Amos was used to determine the best-fit Structural Equation Model (SEM). The results strongly indicate that the issue of delayed payments is very prevalent within public sector projects. Unstable political climates and the delay in employers’ issuance of variation orders were found to be the main causes of delayed payments within the industry. Delays in sub-contractor and supplier payments as well as an increase in the contractor’s debt were the leading effects of delayed payments on the contractor’s cash flows. Based on these findings, a risk response framework was outlined to assist small to medium-contracting enterprises to cope with payment delays, both locally and internationally. This research contributes to the advancement of construction management knowledge by informing construction professionals and policy makers of the implications of delaying approved payments, the consequential causes and effects, and a risk response technique to mitigate the negative effects on contractors’ cash flows.Publication Open Access A Graph Pointer Network-Based Multi-Objective Deep Reinforcement Learning Algorithm for Solving the Traveling Salesman Problem(MDPI, 2023-01-13) Perera, J; Liu, S.H; Mernik, M; Črepinšek, M; Ravber, MTraveling Salesman Problems (TSPs) have been a long-lasting interesting challenge to researchers in different areas. The difficulty of such problems scales up further when multiple objectives are considered concurrently. Plenty of work in evolutionary algorithms has been introduced to solve multi-objective TSPs with promising results, and the work in deep learning and reinforcement learning has been surging. This paper introduces a multi-objective deep graph pointer network-based reinforcement learning (MODGRL) algorithm for multi-objective TSPs. The MODGRL improves an earlier multi-objective deep reinforcement learning algorithm, called DRL-MOA, by utilizing a graph pointer network to learn the graphical structures of TSPs. Such improvements allow MODGRL to be trained on a small-scale TSP, but can find optimal solutions for large scale TSPs. NSGA-II, MOEA/D and SPEA2 are selected to compare with MODGRL and DRL-MOA. Hypervolume, spread and coverage over Pareto front (CPF) quality indicators were selected to assess the algorithms’ performance. In terms of the hypervolume indicator that represents the convergence and diversity of Pareto-frontiers, MODGRL outperformed all the competitors on the three well-known benchmark problems. Such findings proved that MODGRL, with the improved graph pointer network, indeed performed better, measured by the hypervolume indicator, than DRL-MOA and the three other evolutionary algorithms. MODGRL and DRL-MOA were comparable in the leading group, measured by the spread indicator. Although MODGRL performed better than DRL-MOA, both of them were just average regarding the evenness and diversity measured by the CPF indicator. Such findings remind that different performance indicators measure Pareto-frontiers from different perspectives. Choosing a well-accepted and suitable performance indicator to one’s experimental design is very critical, and may affect the conclusions. Three evolutionary algorithms were also experimented on with extra iterations, to validate whether extra iterations affected the performance. The results show that NSGA-II and SPEA2 were greatly improved measured by the Spread and CPF indicators. Such findings raise fairness concerns on algorithm comparisons using different fixed stopping criteria for different algorithms, which appeared in the DRL-MOA work and many others. Through these lessons, we concluded that MODGRL indeed performed better than DRL-MOA in terms of hypervolumne, and we also urge researchers on fair experimental designs and comparisons, in order to derive scientifically sound conclusions.Publication Open Access Is the best option still in low adoption? An investigation on factors affecting the adoption of online school education in rural areas in Sri Lanka(Springer, 2023-01-22) Weerasena, A; Jayathilaka, RThis research investigates rural area students’ online adoption during the fourth wave of the coronavirus 2019 (COVID-19) pandemic. The main objective of this study was to identify the factors affecting the adoption of online education in rural areas in Sri Lanka. This case study was carried out based on data gathered from the online survey during the pandemic covering 16 districts in Sri Lanka. Using the ordered probit regression model through the stepwise technique, the study investigates the factors affecting the adoption of online education in rural areas in Sri Lanka. According to the results generated, attitude, perceived use, awareness, and new technology adoption have a positive impact on student adoption of online education in Sri Lanka. Online education so far is one of the effective and feasible solutions for providing education in a pandemic situation in any country. These findings are helpful for responsible educational institutions to address and contribute to key issues such as low perceived use, poor attitude, low awareness, and poor technology adoption. The study will also assist policymakers in preparing a roadmap, at the policy level with the perceived benefits of online education during similar future crises in Sri Lanka.Publication Open Access Determining the influence of LPI, GCI and IR on FDI: A study on the Asia and Pacific Region(PLoS ONE, 2023-02) Wannisinghe, P; Jayakody, S; Rathnayake, S; Wijayasinghe, D; Jayathilaka, R; Madhavika, NCompetitiveness Index (GCI) and Interest Rates (IR) on Foreign Direct Investment (FDI) for the Asia & Pacific region. The study is original as extensive evidence on the impact of LPI, GCI and IR on FDI in the Asia & Pacific region are examined initially. For the years 2007, 2010, 2012, 2014, 2016 and 2018, data was gathered for 33 nations in the Asia and Pacific area. Data analysis was performed using a panel regression model and multiple linear regression. The findings of the study reveal that LPI, GCI and IR are the three major factors influencing FDI inflows into the economies. However, the impact of these factors varies from country to country. The results concluded that LPI positively impacts FDI in India, Korea, Lebanon, and Oman. In contrast, a negative influence was observed for China, Kuwait and the Philippines. GCI positively impacts FDI in China, Korea, Kuwait, Pakistan and the Philippines, while a negative impact was observed in Armenia, India, Lebanon. Furthermore, IR has a positive impact on FDI flows in China and Egypt while in Korea and Lebanon, a negative impact was observed. Therefore, policymakers should focus more on improving the infrastructural requirements and macroeconomic factors while considering the other country-level variables that influence the FDI in flowPublication Open Access Recent Advances in Chitosan-Based Applications—A Review(MDPI, 2023-03-03) Thambiliyagodage, C; Jayanetti, M; Mendis, A; Ekanayake, G; Liyanaarachchi, H; Liyanaarachchi, SChitosan derived from chitin has gathered much interest as a biopolymer due to its known and possible broad applications. Chitin is a nitrogen-enriched polymer abundantly present in the exoskeletons of arthropods, cell walls of fungi, green algae, and microorganisms, radulae and beaks of molluscs and cephalopods, etc. Chitosan is a promising candidate for a wide variety of applications due to its macromolecular structure and its unique biological and physiological properties, including solubility, biocompatibility, biodegradability, and reactivity. Chitosan and its derivatives have been known to be applicable in medicine, pharmaceuticals, food, cosmetics, agriculture, the textile and paper industries, the energy industry, and industrial sustainability. More specifically, their use in drug delivery, dentistry, ophthalmology, wound dressing, cell encapsulation, bioimaging, tissue engineering, food packaging, gelling and coating, food additives and preservatives, active biopolymeric nanofilms, nutraceuticals, skin and hair care, preventing abiotic stress in flora, increasing water availability in plants, controlled release fertilizers, dye-sensitised solar cells, wastewater and sludge treatment, and metal extraction. The merits and demerits associated with the use of chitosan derivatives in the above applications are elucidated, and finally, the key challenges and future perspectives are discussed in detail.Publication Open Access Online Harassment in Sri Lanka: A Thematic Analysis(MDPI, 2023-03-15) Harasgama, K.S; Jayamaha, S: Online harassment has become a growing menace worldwide for which every nation is trying to find a solution. Existing literature demonstrates that online harassment is widespread in diverse forms and so is its impact on the victims. Despite the lack of any comprehensive studies in this area, there is sufficient evidence to demonstrate the prevalence of online harassment in Sri Lanka and the need to find effective solutions to it. In such circumstances, this study aims to understand the nature of online harassment in the Sri Lankan context using qualitative research methodology. To that end, the study uses thematic analysis for analysing the data collected through semi-structured interviews. The thematic analysis was employed for the study as it assists in classifying complex qualitative data into different and simplified themes for better understanding and interpretation of such data. Among other findings, the analysis revealed three global themes, namely the motives of the perpetrators, the impact on victims, and remedies. Under each global theme, the study revealed various organising and basic themes, also indicating that the motives of the perpetrators and the impact on the victims are closely connected. It further reveals that impacts could be extremely serious, ranging from helplessness to suicidal thoughts, humiliation to broken relationships, and even having adverse impacts on the careers of victims. The study also found that the available remedies are not systematic or strong enough to meet the expectations of the victims. Thus, we conclude that the threat from online harassment in Sri Lanka is similar to that in any other country, requiring immediate and well-planned legal and policy responses, as exposed by the key themes identified in the study.Publication Open Access Reducing Cost Overrun in Public Housing Projects: A Simplified Reference Class Forecast for Small Island Developing States(MDPI, 2023-04-10) Chadee, A; Martin, H; Gallage, S; Rathnayake, UInaccuracies in cost estimation on construction projects is a contested topic in praxis. Among the leading explanations for cost overrun (CO), factors accounting for large variances in actual cost are shown to have psychological or political roots. The context of public sector social housing projects (PSSHPs) in Small Island Developing States (SIDS) is positioned with similar CO challenges. This study is the fifth phase of a series of research projects on the vulnerability of PSSHPs to COs, and the need to de-risk cost estimates. The aim of this study is to present a simple and practical application of Reference Class Forecasting (RCF), a promising solution utilizing an “outside view” approach, as an effective control to reduce the variance of forecasted cost inaccuracies. Using a sample set of 82 housing projects, a reference class of 23 projects was selected based on properties such as design-build procurement type and local contractor involvement. A probability distribution was then established for this reference class, and required cost uplifts to be applied were based on the level of risk a housing agency is willing to accept for PSSHPs. Finally, the accuracy of the reference class was tested using a recently completed project. The results showed that the RCF method, based on a 50th percentile risk acceptance of CO, provides a closer estimate to the actual costs of the project as compared to the contracted costs. This empirical study is the first to undertake and implement RCF in the 52 SIDS and presents the first instance of practical RCF in public housing projects worldwide, thus providing a platform for improvement in future PSSHPs’ budget forecasting. The research can be applied to lessen societal and economic welfare losses as well as significant financial risks for governments. The implementation of practical safeguards, such as RCF, together with contemporary standard project controls, provides immediate advantages for enhancing accuracy in present forecasting approaches against financial risks. It allows for improved value derived from social infrastructure projects, improved supply of public housing, and consequently progress for these nations towards achieving their sustainable development goals.Publication Open Access Risk Evaluation of Cost Overruns (COs) in Public Sector Construction Projects: A Fuzzy Synthetic Evaluation(MDPI, 2023-04-22) Chadee, A.A; Martin, H.H; Gallage, S; Banerjee, K.S; Roopan, R; Rathnayake, U; Ray, IIn the Small Island Developing States (SIDS), public sector infrastructure projects (PSIPs) fail to both meet targeted performance metrics and deliver on the intended benefits to society. In terms of the cost performance metric, cost overruns (COs) beyond the initial contract value are more of a norm than a unique occurrence. Therefore, to ensure economic sustainability for SIDS, and value for money on PSIPs, there is a need to investigate and evaluate the risk impacts on COs. The purpose of this research was to identify and evaluate the perceived cost overrun risk factors that are within the primary project stakeholders’ sphere of control, and to reduce the ongoing ambiguities that exist in the prioritization of these risks. This was achieved by extracting critical risk factors from selected comparative studies in developing countries to formulate a closed-ended questionnaire to be administered to construction professionals in Trinidad and Tobago. Thereafter, the process of fuzzy synthetic evaluation (FSE) was used to develop a risk model based on three tiers of risks: 11 critical risk factors, 3 critical risk groupings (CRGs) and an overall risk level (ORL). The results showed that the two highest-ranked critical risks were project funding problems and variations by client. The leading critical risk grouping was client-related risk (5.370), followed by professionalrelated risk (4.815) and physical risk (4.870). The ORL was 5.068. Based on the FSE’s linguistic scaling, the CRGs and the ORL are perceived to be high risks in PSIPs. This research adds to the CO body of knowledge in primarily three ways. Firstly, the study extends the comparative assessment previously undertaken in scholarship into the context of SIDS to build on the generalizability of this context-specific phenomenon. Secondly, the FSE evaluation undertaken provides a practical tool to be promoted for use in SIDS’ construction industry among practitioners to focus and prioritize the critical risks in the planning phases and improve on contemporary risk practices in the execution phases of projects. Finally, this quantitative model approach is recommended to supplement the traditional qualitative risk management practices adopted in SIDS, thus contributing towards the overall improved economic sustainability and viability of PSIPs.
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