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Causal AI for Smart Decision-Making: Driving Sustainability in Urban Mobility and Industry
No full textThe transition toward sustainable urban mobility and industrial efficiency requires decision-making tools that go beyond correlation-based analysis to uncover true cause-and-effect relationships. Traditional machine learning models, while effective for prediction, often act as "black boxes," lacking interpretability and failing to reveal the mechanisms underlying complex systems. To address these limitations, this dissertation introduces a modular Causal AI framework for smart decision-making, integrating causal discovery and inference with structured domain knowledge to enhance sustainability outcomes.
The framework is validated across three key domains: (1) urban CO2 emissions, (2) shared mobility demand, and (3) SME energy use. The first case study analyzes over 500,000 vehicles to uncover how engine performance and maintenance drive urban emissions. The second study examines shared bike systems, identifying causal impacts of weather patterns, station topology, and temporal demand fluctuations, supporting more adaptive fleet operations. The third applies the framework in a manufacturing SME, identifying the root causes of energy inefficiency and enabling targeted interventions to improve operational performance without compromising productivity.
This research advances the interpretability and actionability of AI in sustainability contexts by replacing opaque predictive models with transparent, evidence-based causal reasoning. Algorithms such as PC, FCI, GES, and DirectLiNGAM are employed alongside domain ontologies to uncover valid causal relationships and support decision-making. A hybrid approach also addresses feature selection, dimensionality reduction, and model explainability, making the methodology broadly applicable across diverse sustainability challenges.
While the framework demonstrates strong applicability, future work may focus on enhancing real-time scalability, adaptive ontology integration, and broader validation across domains such as electric mobility and smart energy systems. Overall, this thesis contributes a generalizable, interpretable Causal AI framework that enhances systemic understanding and supports sustainable transformation in policy, planning, and industrial decision-making
Production of an aspartyl proteinase from Mucor racemosus via solid-state fermentation. Applications in cheese manufacturing.
No full textIn recent years, solid-state fermentation [SFF] has gained the interest of the research community by showing remarkable developments in bioprocesses. It has emerged as a technology with the potential for producing microbial products such as pharmaceuticals, industrial enzymes, secondary metabolites, feed & food, and biofuels. Mucor racemosus CBS 381 was grown on optimized solid media (wheat bran) using the software, Design of Experiment (DoE). Based on laboratory-scale experiments the the SSF was scaled up by establishing a precisely controlled environment by utilizing Terrafors-IS Infors HT in-situ sterilizable rotating solid-state bioreactor. SSFs were introduced to predict the effect of shear forces caused by drum rotation on the overall biomass and enzyme production. Additionally, the aeration requirement and sensitivity of fungal growth and its effect on the final product were also investigated in combination with various moisture levels. Fermentations were performed with high and low moisture content i.e. 90% and 60% in combination with the flow rate of 1 and 2 L/min. Crude extract analysis via scale-up SSF with 60% moisture content and the airflow provided 1 L/min, exhibited ~570 U/mL milk-clotting activity with ~1600g biomass. However, the 2 L/min flow with 60% moisture content resulted in less biomass with reduced milk clotting activity. 90% moisture content with a 1 L /min Flow rate has resulted in enhanced biomass production i.e. ~1800 g and enzyme with the milk-clothing i.e. 558 U/mL. This study revealed that low moisture and low aeration levels lead to an increase in enzyme activity. Enzyme purification was accomplished via ion exchange chromatography using a DEAE Sepharose Fast Flow column. A threefold increase in the enzyme activity of the crude extract was observed. By using the enzyme, fresh cheese was manufactured on a pilot scale utilizing pasteurized cow milk. Various properties of the cheese were analysed
Coordination in smart energy systems? Contracting and pricing
No full textThis thesis studies energy system integration, that is mechanisms coordinating electricity sector with the broader energy system. More specifically, it utilizes microeconomic modeling and academic insights from industrial and institutional economics to develop coordination mechanisms capable of addressing flawed stakeholder coordination occurring within the electricity sector and at its interface to other energy sectors. This cumulative dissertation consists of five papers that together cover all three layers of energy system integration. Paper 1 addresses the whole-network optimization layer and asks whether independent operators of electricity networks have an incentive to cooperate in optimizing their interconnected networks. It demonstrates an incentive problem in power network operator interactions that turns these into game-theoretical problems like prisoner’s dilemma and chicken game. This makes optimization of electricity network as a single system difficult. Papers 2, 3 and 4 explore the whole-chain optimization layer of energy system integration which focuses at coordination between electricity network and power generation, storage, and consumption. Paper 2 evaluates the economic efficiency of administrative network congestion management, that is addressing network congestion by an administrative rule, and provides a policy advice on an efficient design. Paper 4 provides a similar result for market-based alternatives, where network congestion is addressed by market-based coordination between network and network users. Paper 3 reviews the empirical experience with such market-based type of congestion management. Paper 5 is concerned with the cross-system optimization layer. Aiming to provide a policy advice on a coherent institutional framework governing investment in the future hydrogen infrastructure, which is expected to be dispersed across multiple energy sectors, it reviews and evaluates current governance proposals raised by the European institutions
Development of Phytoextract from Food Waste for Sustainable Aerosol Disinfection Technology
No full textThe rapid increase in food production waste, totalling 1.3 billion tons annually, significantly contributes to greenhouse gas emissions. Bioeconomy strategies are needed to utilize this waste and mitigate environmental impacts sustainably. Repurposing food waste as a source of phytoextracts rich in bioactive compounds can serve industries as sustainable food, hygiene, and pharmaceutical alternatives.
This thesis explores the development of antimicrobial phytoextracts from food production waste—such as hot trub (HT), coffee silverskin (CSS), lemon peel (LP), and broad bean shell (BBS)—as alternatives to synthetic chemicals for aerosol hygiene disinfection. The phytoextracts, characterized using advanced analytical techniques (UHPLC-ESI-QTOF-MS, NMR, NanoDSF and FTIR), exhibited significant antibacterial activity against pathogens like Listeria monocytogenes and Staphylococcus aureus, primarily due to bioactive polyphenols.
The phytoextracts were successfully converted into aerosol formulations and tested for efficacy in reducing bacterial contamination on surfaces and in the air, achieving up to 98% reduction in bacteria, yeast, and mould. These results align with commercial disinfectant standards, demonstrating the feasibility of using these extracts for disinfection.
The study also employed green extraction methods, maintaining phytoextracts' chemical integrity and antibacterial activity. Additionally, the extracts showed promising antidiabetic and antioxidant Sum Parameters activities and were free of cytotoxic effects, further expanding their applications. Protein extracts from BBS were also analyzed, revealing valuable peptides that could be used in various industries.
However, further optimization is necessary for commercialization, reducing aerosol particle size, and conducting safety tests. The study highlights the untapped potential of food waste streams as valuable sources of bioactive compounds with diverse applications across multiple industries
Computational Insights into Light Harvesting in Photosystem II Antenna Complexes
No full textPhotosynthesis is an essential process through which sunlight is converted into chemical energy, sustaining virtually all life on Earth. In the specific case of oxygenic photosynthesis, Photosystem II (PSII) plays a pivotal role as a major component of the photosynthetic machinery, responsible for the initial light absorption and generating molecular oxygen. This process involves numerous protein-pigment complexes within PSII. The photosynthetic apparatus is rich in colored pigments, which not only make it visually appealing but also crucial for capturing and transporting sunlight through excitation energy transfer. Due to the large size of these proteins and the electronic complexity of the pigment molecules embedded in the membrane, multiscale quantum-classical methods are essential for studying the processes. The protein environment significantly influences the tuning of the excitation energy of the pigments, thereby establishing an energy funnel in such systems. This thesis aims to deepen our understanding of the lightharvesting process in the antenna complexes of PSII. To achieve this, a multiscale approach is employed. This involves using the density functional tight-binding (DFTB) method to perform ground state molecular dynamics within a quantum mechanics/molecular mechanics (QM/MM) framework, coupled to an electrostatic classical environment. Following this, the time-dependent extension of the long-range-corrected DFTB is applied to obtain the excitation energies of each pigment molecule, within a QM/MM setting. This method generates essential excitonic parameters such as site energies, couplings, and spectral densities, which are utilized to model the spectroscopic properties. Furthermore, the calculated results have been compared with experimental data, showing great agreement for the antenna complexes in PSII. This alignment ensures the robustness of the methods, validating their use for studying light harvesting in both plant and cyanobacterial systems
LC-MS Based Profiling of Peptides and Proteins of Common Legumes in Sri Lanka and Evaluation of their Bioactive Potential
No full textThe popularity of plant-based proteins, especially legumes has experienced a remarkable surge in recent years, due to the heightened awareness health benefits, concerns on animal welfare, environmental sustainability, and advancements in food technology. Apart from their nutritional value, many of the encrypted peptide sequences have shown remarkable bioactivities. However, most of the legume crops consumed worldwide are not evaluated for protein profile and bioactive potential, except for soya beans, peas, and lentils. The lack of scientific evidence has become a major barrier in successful utilization of these legumes. Also, there are many chemical and physiological barriers which limit the protein digestion such as protease inhibitors and complex structural diversity. So, this study was planned to evaluate the amino acid profile, presence of bioactive peptide sequences and improving the digestibility of proteins from common legumes cultivated in Sri Lanka, including pigeon pea-Cajanus cajan, green gram- Vigna radiata, cowpea - Vigna unguiculata, black gram - Vigna mungo and horse gram- Macrotyloma uniflorum. Extraction with acid, alkaline, salt, alcohol and TRIS buffers were compared for the yield and the diversity of protein profile. Digested protein extracts with trypsin, chymotrypsin and pepsin were analysed by LC-ESI-MS. Peptide sequencing was performed with PEAKS software to identify proteins, post-translational modifications, and amino acid profile. The peptide fragments identified from trypsin, pepsin and chymotrypsin hydrolysates were screened with different in-silico approaches and in vitro bioassays. Also, the effect of domestic processing methods including soaking, gemination, boiling and roasting on the digestibility of green gram proteins was evaluated. Results showed that the alkaline extraction is effective in extracting an optimum protein yield with most diverse and balanced protein profile, comprising storage, enzyme, and other functional proteins. Most of the cultivars tested show similar storage protein profiles, but there were significant differences in functional proteins important in abiotic stress management. Also, seed storage proteins show extensive post-translational modifications, which serves as another level of protection and functionalities such as dormancy release and metabolic resumption. They also have balanced essential amino acid profile, except for Methionine (M) and tryptophane (W). All legumes exhibited significant potential in antioxidant and antibacterial properties, and trypsin mediated digestion is more successful in generating bioactive peptides. Boiling and roasting enhanced the digestibility of legume proteins, which can be attributed to the removal of protease inhibitors, unfolding of globular storage proteins and alterations in secondary structures into less ordered conformations
A Moving Belt System for the Continuous Recovery of Bioproducts Utilizing Composite Fibrous Adsorbent
No full textA novel composite fabric-based adsorbent is presented, in the form of an elastic and robust woven fabric belt following the general designs observed in known horizontal flat belt conveyors. The adsorbent was a strong cation-exchanger functionalized by sulphopropyl (SP) made of nylon 6 reaching a static binding capacity equal to 107.3 mg/g. Moreover, excellent dynamic binding capacity (DBC) values (54.5 mg/g) was tested even when operated at high flow rates (480 cm/h).
In a subsequent step, a continuous protein purification system based on the true moving bed concept, namely moving adsorption belt system, is presented. The composite adsorbent was embedded into a bench-scale prototype, permitting performance studies with a model protein (lysozyme). Results indicated that the moving belt system could recover lysozyme with a productivity up to 0.5 mg/cm2/h. Subsequently, a monoclonal antibody (Humira) was recovered from unclarified CHO_K1 cell line culture with high purity as judged by reducing SDS-PAGE, high purification factor (5.8), and in a single step confirming the suitability and selectivity of the purification procedure.
A dynamic decision-support tool, was utilized to evaluate how the potential of the moving belt system various across a range of scale (50 to 5000 kg/year) from an economic perspective. The comparison of cost of goods per gram (COG/g) demonstrates that moving belt system cannot offer a better manufacturing cost comparing to protein A chromatography when the production scale was smaller than 5000 kg/year. At production scale of 5000 kg/year, both capture processes offer similar COG/g values. The most effective way to narrow the difference in COG/g is to increase the DBC of the moving belt process 4 times.
Certain adoption barriers were observed during processing and the possible optimization approaches were introduced. Inherently, scale-up is relatively easy to be fulfilled if moving adsorption system is utilized for purification
Monitoring Biological Processes Based on Supramolecular Host-Guest Interactions
No full textThe thesis comprises three main sections, in which the central theme revolves around the supramolecular reporter pairs. The first and second sections aim to design intricate coupled reactions, namely supramolecular tandem enzyme membrane assays and supramolecular membrane enzyme assays, achieving the simulation of continuous physiological processes. In the supramolecular tandem enzyme membrane assays section, we describe the usage of two supramolecular reporter pairs, with one set located inside the vesicles and the other set positioned outside the vesicles, to mimic the simple process of digestion and absorption.
The second section, the supramolecular tandem membrane enzyme assays, focuses on simulating the processes of cellular uptake and metabolism using a single set of reporter pair located within the vesicles. In the uptake process, the transport of substrates across the vesicle membrane is monitored by the internal reporter pair calix[4]arene•luciginin (CX4•LCG) or cucurbit[7]uril•berberine (CB7•BE). Similarly, the metabolic process is monitored by the same reporter pair within the vesicles, monitoring the enzymatic conversion of the substrates.
The third section represents an intriguing exploration of the effects of variations in the vesicle surface microenvironment on the interactions between supramolecular hosts and guests. The aim is to gain a deeper understanding of the mechanisms underlying the regulation of cell signaling transduction, transmembrane transport, and sensing processes, which are governed by the dynamic and complex presence of proteins, saccharides, and other molecules on the cell surface
A Framework for Enabling Synergic Interactions Between Omnichannel and Product Lifecycle Management Platform Inspired by System Dynamics Approach
No full textThe rapid rise of new technologies, such as mobile phones, social networks, and increased internet access, has created new opportunities for retailers to expand through omnichannel strategies, which aim to provide a seamless customer experience across different channels. While omnichannel can offer benefits and competitive advantages, it faces challenges like price inconsistencies and poor information sharing. Despite its growing recognition, its integration with Product Lifecycle Management (PLM) is underexplored.
This thesis investigates the overlap and mutual effects of omnichannel and PLM, particularly emphasizing the importance of data and knowledge sharing between them. As research into data analytics in omnichannel evolves, tracking and tracing mechanisms in PLM become increasingly critical. The main objective of this study is to develop a bi-directional framework connecting omnichannel and PLM using a System Dynamics approach. This framework aims to incorporate omnichannel mechanisms into PLM and provide cause-and-effect analysis to better understand the operational role of omnichannel within PLM.
Additionally, the research introduces an approach to integrate Business-to-Business (B2B) aspects from PLM with Business-to-Customer (B2C) elements through omnichannel strategies. Leveraging omnichannel's influence on touchpoints like influencers and social media, this approach helps companies align consumer behavior with strategic goals, boosting competitiveness. Ultimately, this thesis aims to bridge the gap between omnichannel and PLM, driving a shift in consumer behavior and strengthening the integration of B2B and B2C in retail
Analyzing deliberation and collective action problems in environmental governance: a case study of an aquaculture policy program
No full textAddressing environmental governance challenges necessitates collaboration among diverse societal actors to collectively develop and modify rules, norms, and social structures. A significant obstacle in environmental governance lies in the problems of institutional fit, where the existing governance arrangements may be mismatched with the specific social-ecological conditions at the local level. This misalignment poses a hurdle to effective and sustainable environmental management. Collective action’s theoretical lens is used in this study to navigate the varied interests, goals, and perspectives involved, aiming to comprehend the different factors influencing collaboration in the management of shared resources. Recognizing that collective action is inherently difficult, this dissertation focuses on the importance of deliberation to facilitate discussions on the risks, benefits, values, and capacities of different actors