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Publication Open Access Integrating industry 4.0 and 5.0 technologies in luxury fashion retail interiors: A systematic review of digital transformation, sensory design, and brand storytelling(Elsevier Ltd, 2026-05-12) Ratnayake, Janitha C; Jayasuriya, N; Suraweera, T; De Silva, LEmerging developments in Industry 4.0 and Industry 5.0 are transforming the cultural, sensory, and experiential character of luxury fashion retail interiors. These changes, driven by artificial intelligence, the Internet of Things, augmented and virtual reality, influence how individuals perceive space, form emotional connections, and engage with brand narratives across both physical and digitally enriched environments. Against this backdrop, this review aims to systematically synthesise how Industry 4.0 and Industry 5.0 technologies intersect with sensory experience, spatial design, and narrative expression in luxury fashion retail interiors, addressing the tendency of prior reviews to examine digital technologies or experiential aspects of retail in isolation. The study adopts a systematic literature review approach guided by the SPIDER framework and the PRISMA protocol. Fifty peer reviewed publications published between 2014 and 2025 were analysed to examine how digital transformation, sensory experience, and narrative expression intersect within luxury retail culture. The thematic analysis identified three closely connected areas: branding and customer experience, the interior environment of luxury stores, and the integration of advanced technologies within retail spaces. Together, these themes illustrate how contemporary luxury interiors operate as culturally expressive and emotionally charged settings shaped by new forms of technological mediation. Building on these insights, the study introduces the Multi-Layered Integration Framework, which explains the interaction between digital systems, spatial atmospheres, and brand storytelling in the creation of culturally responsive and human-centred retail interiors. The review contributes to the social sciences and humanities by demonstrating how emerging technologies reshape sensory engagement, symbolic identity, and cultural expression in luxury retail settings, while offering an expanded understanding of human experience within digitally influenced interior environments.Publication Open Access Determinants of under-five mortality in Africa: evidence from a two-decade panel analysis for public health policy(BioMed Central Ltd, 2026-06-17) Rathnasekara, H; Jayathilaka, RBackground: Child survival is a critical indicator for a nation’s health and its progress is important in attaining the Sustainable Development Goals. Understanding the regional and country-specific dynamic and interplay of various determinants of under-five child mortality is vital for the African continent, which remains one of the most vulnerable regions for child mortality globally. Methods: This study investigates the association of economic, health-related, social and demographic, environmental, and infrastructure-related factors with under-five child mortality. It integrates generalisable regional associations using a standard fixed-effects panel model and examines illustrative country-specific associations of the selected determinants through multiple linear regression, based on a balanced panel dataset of 45 countries over a 22-year period. Results: Fixed-effect analysis reveals that the diphtheria-tetanus-pertussis (DTP) immunisation and total fertility rate (TFR) are robust regional determinants of under-five mortality across specifications. While health expenditure, sanitation services, and malaria incidence show significant associations in the baseline model, these findings are sensitive to the inclusion of year fixed effects, suggesting they are influenced by broader temporal trends or common regional shocks rather than serving as stable independent factors within the study period. Conclusion: Regional analysis, which controls for unobserved country-specific heterogeneity over an extended period and is complemented by country-specific analysis, facilitates the formulation of policy implications at both national and international levels. Recommended policy measures include increasing immunisation coverage, implementing malaria control programmes, strengthening community health infrastructure, enhancing girls’ education, promoting widespread access to modern family planning, and improving sanitation services. These strategies are expected to contribute to the progress toward Sustainable Development Goal 3.2 in the African region.Item Embargo Ai-Based Urine Microscopy Image Analysis for Predicting Urinary Tract and Renal Diseases(Institute of Electrical and Electronics Engineers, 2026-05-29) Senanayake, K; Panagoda, P; Dharmapriya, S; Chathurya, R; Wijendra, D; De Silva, H; Jayawardana, DThe manual microscopic examination of urine is a crucial step in diagnosis of urinary tract and renal diseases. However, the process is time-consuming and operator dependent. Most of the existing automated urinalysis techniques only consider the microscopic examination of individual components or the black-box-based prediction models. There is a lack of a comprehensive framework that incorporates the microscopic examination of the microscopic components with the clinical diagnostic logic. In this regard, the present work proposes an artificial intelligence-based urinalysis system for the microscopic examination of the components in the urine sample to generate diagnostic outcomes. In the proposed system, the microscopic components like white blood cells, red blood cells, bacteria, yeast, crystals, and casts are detected and analyzed to generate the diagnostic outcomes for the diagnosis of urinary tract infection, kidney stone risk, hematuria causes, and casts-related renal diseases. In the proposed system, efficient lightweight models ensure precision and effectiveness in identifying various biological entities. White blood cells are detected with a mAP@0.5 score of 0.96, yeast with over 0.94, and crystals with more than 0.91, yielding a classification accuracy of 99.41% for crystals. The system detects microscopic elements like casts with a mAP@0.5 score of 0.80. The system also incorporates auxiliary clinical data to enhance diagnostic results for various diseases.Publication Embargo Spatial distribution and hydrological influences of microplastic contamination in the upstream reach of the ambathale water treatment plant intake, Sri Lanka(Springer Science and Business Media, 2026-08-07) Rathnayake, D; Miguntanna, N; Rathnayake, UMicroplastic contamination has emerged as a global environmental concern, with rivers serving as important pathways for the accumulation and transport of these particles. This study investigated the spatial distribution of microplastic contamination and the influence of hydrological and physicochemical factors on microplastic occurrence in the upstream reach of the Ambathale Water Treatment Plant intake along the Kelani River, Sri Lanka. Water samples were collected from four locations within the study area, including three upstream sites and one downstream site. Microplastics were detected at all sampling locations, with Kelaniya recorded the highest microplastic concentration (20.08 ± 10.19 mg/L), while Ambathale had the lowest (9.12 ± 3.89 mg/L). Three main microplastic types were identified: fibers, fragments, and films. Fibers and fragments were the most abundant microplastic types across all sampling locations, while films occurred at comparatively lower concentrations. Statistical analyses revealed a significant positive correlation between river water level and microplastic concentration (r = 0.883, p = 0.001), indicating the importance of hydrological conditions in microplastic transport. Fiber and film concentrations exhibited particularly strong positive relationships with water-level fluctuations (r = 0.940 and r = 0.904, respectively; p < 0.01). Furthermore, positive associations between microplastic abundance and suspended solids suggest that particulate matter plays an important role in the transport and distribution of microplastics within the river system. The findings demonstrate significant spatial variability in microplastic contamination and highlight the influence of hydrological processes on microplastic occurrence and transport in the Kelani River. This study provides baseline information for future monitoring and contributes to a better understanding of microplastic dynamics in tropical freshwater environments.Publication Open Access CALCOM: An integrated techno-economic and life-cycle environmental framework for electric vehicle assessment in Sri Lanka(Elsevier B.V., 2026-08-01) Abeygunawardena, N; Wijayapala, A; Jathunga, TElectric vehicle (EV) adoption is accelerating worldwide, creating a need for comprehensive frameworks that assess economic feasibility and environmental performance. This study presents a context-adaptive levelized cost of mileage (CALCOM) framework to evaluate the economic and environmental performance of battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), and internal combustion engine vehicles (ICEVs) under Sri Lankan conditions. The framework integrates discounted life-cycle cost (LCC), net present value (NPV), and greenhouse gas (GHG) emissions into a unified assessment model. Real-world operational ad cost data were collected from owners representing Nissan Leaf (BEV), Toyota Aqua (HEV), and Toyota Vitz (ICEV). The analysis included purchase cost, energy consumption, maintenance, battery replacement, salvage value, and environmental costs over a 10-year ownership period. The BEV achieved the lowest levelized cost of mileage of 0.080 USD/km which further decreased to 0.050 USD/km under renewable charging. Life-cycle GHG emissions were 59% lower than those of ICEV. Sensitivity analysis identified electricity price, annual distance travelled, and charging efficiency as the primary determinants of BEV competitiveness. Threshold analysis indicated that BEVs remain economically attractive when domestic electricity tariffs are maintained below 0.32 USD/kWh. The findings demonstrate that BEVs offer the greatest economic and environmental benefits and offer evidence-based guidance for policies supporting electric mobility in developing countries.Publication Embargo Fusion of Lean Six Sigma-DMAIC Tools and Techniques into Construction Variation Management: Barriers and Strategies(American Society of Civil Engineers (ASCE), 2026-11-01) Shashini, T.W.K.N; Jayanetti, J.K.D.D.T; Disaratna, V; Ranadewa, T; Perera, B.A.K.SVariations in construction projects pose a significant challenge to achieving successful project outcomes. Lean Six Sigma has the potential to manage variations in the construction industry. This study aims to explore the fusion of lean Six Sigma (LSS)-Define, Measure, Analyze, Improve, and Control (DMAIC) tools and techniques into construction practice to manage variations. Adopting a pragmatic stance and a qualitative approach, empirical data were collected through a three-round Delphi expert survey using semistructured interviews, with the data analyzed through content analysis. The findings reveal that 25 LSS-DMAIC techniques and tools can be effectively applied to manage variations in the construction sector. In addition, 17 barriers and 21 strategies were identified, and a mapping was undertaken to align each barrier with suitable strategies. This research addresses a gap in existing literature by extending investigations of LSS-DMAIC in construction to the specific context of managing variations, identifying barriers to implementation, and proposing strategies, an area that has not been explicitly examined previously. By investigating the barriers to implementing LSS-DMAIC and by suggesting tailor-made strategies for overcoming each barrier, the study makes both theoretical and practical contributions. It provides a framework for on the applicability of LSS-DMAIC in developing countries while offering construction managers context-specific solutions to enhance project outcomes and improve stakeholder satisfaction.Publication Open Access Drivers of carbon emissions in G7 economies: Evidence on energy use, globalisation, urbanisation, industrialisation and innovation(Elsevier Ltd, 2026-08-26) Weerasinghe, L; Vithanage, N; Rupasinghe, D; Keesha, C; Jayathilaka, RRising CO2 emissions remain a major sustainability challenge, particularly in advanced economies that account for a considerable share of historical emissions. This study examines the key determinants of CO₂ emissions in G7 countries by jointly considering globalisation, energy consumption, urbanisation, industrialisation, and technological innovation. Using a balanced panel dataset for Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States over the period 1997–2023, the analysis applies panel regression techniques and country-specific multiple linear regressions to capture both common effects and heterogeneity across economies. The results indicate that energy consumption is a robust driver of CO₂ emissions across the G7. Technological innovation contributes to emission reduction at the panel level; however, its effect becomes statistically insignificant in country-specific estimations, reflecting cross-country differences in innovation structures and policy environments. Globalisation significantly increases emissions in Canada, while its influence is negligible elsewhere. Urbanisation shows a mitigating effect only in the United States, and industrialisation increases emissions in Canada and Italy but reduces emissions in Japan. Overall, the findings highlight that decarbonisation strategies in advanced economies should prioritise the transition to clean energy while strengthening innovation-oriented climate policies tailored to country-specific contexts.Item Embargo Machine Learning-Based Early Detection Of Autism Using Multimodal Conversational Features(Institute of Electrical and Electronics Engineers Inc., 2026-06-26) Haturusinghe, R; Gunathilake, B; Abeysundara, S; Senadeera, S; Thelijjagoda, S; Jayalath, TEarly and reliable screening for autism spectrum disorder (ASD) remains challenging in low-resource and high-variance conversational settings. This paper presents an end-to-end multimodal screening system that analyzes child-caregiver interaction data from audio recordings, CHAT-format transcripts, and text inputs to estimate ASD likelihood and provide clinician-facing explanations. The system integrates three feature families: pragmatic-conversational, acoustic-prosodic, and syntactic-semantic, supporting component-wise classification and late-fusion strategies with modality-aware weighting. Beyond prediction, the platform provides transcript-level behavioral annotations, global and local feature attributions, and counterfactual what-if analysis. Experiments on cross-validated ASDBank data show multimodal fusion achieving 87.2% accuracy (ROC-AUC 0.92), outperforming unimodal baselines by 2-4%.Publication Open Access Performance Enhancement of Cooperative NOMA in Satellite Communication Through Combining Techniques(Institute of Electrical and Electronics Engineers Inc., 2026) Ashwini K; Singh, A; Jagadeesh V.K; Shenoy, R; Jayakody, D. N.KThis article studies the analysis of the key performance parameters in the proposed cooperative Non-Orthogonal Multiple Access (NOMA) system considering the satellite network. NOMA can be coupled with standard relaying procedures to increase the overall capabilities of the wireless communication system. The system under consideration consists of two users, one near and a far user, and a satellite. The paper explores by using a Decode and Forward (DF) relaying mechanism at the user closer to the satellite, which will forward the signal received from the satellite user that is distant from it. In separate case studies, the far user combines the direct and indirect transmission signals using Maximal Ratio Combining (MRC) and Selection Combining (SC) techniques. The expressions for outage, average Bit Error Rate (BER), and capacity are derived for MRC and SC methods. It is also derived and approximated, and closed-form expressions are obtained. The simulation results of these analytical expressions reveal that the MRC method of combining outperforms the SC technique in terms of outage, BER, and ergodic capacity.Publication Open Access Biochemical shifts in Chlorella vulgaris via post-stationary magnesium sulfate stress: optimizing biomass for advanced bio-fertilizers(Frontiers Media SA, 2026-06-09) Dodangodage, C. A; Kasturiarachchi, J. C; Perera, T.A; Rajapakshe, S.D; Niyangoda, S.S; Halwatura, R.USustainable agriculture requires bio-fertilizers that improve both nutrient efficiency and soil resilience. Microalgae are promising candidates; however, conventional optimization using sodium chloride (NaCl) stress introduces phytotoxic sodium residues that limit soil application. To address this, a biphasic cultivation strategy for Chlorella vulgaris was developed using magnesium sulfate (MgSO4) as a dual-function stressor. Following the onset of a nitrogen-limited stationary phase (Day 18), the addition of 0.4 g L-¹ MgSO4 induced intracellular macromolecular accumulation. Biomass increased by 44.8% (2.810 ± 0.090 g L-¹), driven by intracellular densification, with enrichment in both total carbohydrate (42.15 ± 2.10%) and lipid (36.24 ± 1.11%) fractions. Substituting NaCl with MgSO4 eliminates the risk of sodium-induced phytotoxicity upon soil application, while simultaneously pre-loading the biomass with essential secondary macronutrients. Overall, this study demonstrates that targeted MgSO4-induced metabolic shifts can generate high-density, functionally enhanced, sodium-free microalgal biomass to serve as a potential bio-fertilizer feedstock.
