17628 research outputs found
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Numerical investigations into the comparison of hydrogen and gas mixtures storage within salt caverns
No full textSalt caverns, long used for natural gas storage to manage peak loads, are being considered for hydrogen storage as part of the shift towards greener fuels. This transition necessitates re-evaluating heat and fluid transport to ensure the suitability of storage sites. A comparative analysis between current (natural gas and compressed air) and prospective (hydrogen and gas mixtures) storage systems was conducted using a standardized historical cycle over thirty days to identify trends. Hydrogen exhibited the lowest cumulative temperature and pressure increase (17 °C, 0.40 MPa), but the greatest variability per cycle, with an average range of 26 °C and 1.6 MPa. This higher fluctuation could potentially limit its use in short-term cycles compared to natural gas. Moreover, hydrogen's storage capacity was found to be a third of natural gas's, at only 6.6 GWh for the cavern design and specified pressure limits. These findings indicate that while hydrogen presents a greener alternative, its high variability and lower storage capacity pose challenges for its use in existing infrastructure, highlighting the need for further research to optimize its storage and utilisation in energy systems
Creative Green Economy in Nepal: Policy Brief
No full textThe Creative Green Economy (CGE) prioritises investments in Nepal’s nature and culture-based sectors for an effective green transition towards net zero. This model encapsulates major exports/imports and high-value goods amounting to a significant portion of Nepal’s annual GDP. CGE advances the ‘made in Nepal’ cause with a focus on products inspired by the country’s nature and culture. Operationally it promotes people-centered business models that are capable of producing uniquely Nepali products and services through creativity and innovation, and development of sustainable business ideas that not only generate profits but also realise environmental, cultural and locality benefits.Research indicates a burgeoning national and international market for many of Nepal’s creative and natural products. But supply chains are fickle and current policies are not supportive. Recent developments across the education, industry and development sectors indicate a favorable environment to consider the impact of alternative models like the Creative Green Economy which are more effective at bridging multiple sector priorities and to add value, as well as support sustainable growth
Against Dystopias with Ecological Literacy
Get PDFThe longstanding dismissal of the ecological in civilisations that have developed dramatic ecology-altering and planetary boundary crossing technologies is at the crux of contemporary planetary polycrisis. Desirable and even viable futures depend on the design of new ways of living on the planet based on understanding humans in dynamic entanglement with the more-than-human context. Prioritising ecological relations is a fundamental break with assumptions of modernity and associated technologies, social practices, and future visions. We bring design and ecological knowledge together to describe foundational work in designing transitions to Ecocene Protopias, i.e., places of continuous ecological transition. As our springboard, we identify defuturing work in particular formulations of utopian thought. By describing future visions that accelerate ecological harms, we draw attention to the ecology-denying assumptions underlying techno-utopian stories and ideologies. This paper presents ecological literacy as a foundational critical and imaginative capacity to avoid dystopias emerging from traditions that dismiss the ecological. Sustainable and regenerative design practice depends on bolstering designers’ ecological literacies to enable more effective collective reimagining and redesigning future ways of living within planetary boundaries
Persistency and stability of a class of nonlinear forced positive discrete-time systems with delays
Get PDFPersistence, excitability and stability properties are considered for a class of nonlinear, forced, positive discrete-time systems with delays. As will be illustrated, these equations arise in a number of biological and ecological contexts. Novel sufficient conditions for persistence, excitability and stability are presented. Further, similarities and differences between the delayed equations considered presently and their corresponding undelayed versions are explored, and some striking differences are noted. It is shown that recent results for a corresponding class of positive, nonlinear delay-differential (continuous-time) systems do not carry over to the discrete-time setting. Detailed discussion of three examples from population dynamics is provided
Automated Sensor Node Malicious Activity Detection with Explainability Analysis
Get PDFCybersecurity has become a major concern in the modern world due to our heavy reliance on cyber systems. Advanced automated systems utilize many sensors for intelligent decision-making, and any malicious activity of these sensors could potentially lead to a system-wide collapse. To ensure safety and security, it is essential to have a reliable system that can automatically detect and prevent any malicious activity, and modern detection systems are created based on machine learning (ML) models. Most often, the dataset generated from the sensor node for detecting malicious activity is highly imbalanced because the Malicious class is significantly fewer than the Non-Malicious class. To address these issues, we proposed a hybrid data balancing technique in combination with a Cluster-based Under Sampling and Synthetic Minority Oversampling Technique (SMOTE). We have also proposed an ensemble machine learning model that outperforms other standard ML models, achieving 99.7% accuracy. Additionally, we have identified the critical features that pose security risks to the sensor nodes with extensive explainability analysis of our proposed machine learning model. In brief, we have explored a hybrid data balancing method, developed a robust ensemble machine learning model for detecting malicious sensor nodes, and conducted a thorough analysis of the model’s explainability
Improving the dichloro-dihydro-fluorescein (DCFH) assay for the assessment of intracellular reactive oxygen species formation by nanomaterials
Get PDFTo facilitate Safe and Sustainable by Design (SSbD) strategies during the development of nanomaterials (NMs), quick and easy in vitro assays to test for hazard potential at an early stage of NM development are essential. The formation of reactive oxygen species (ROS) and the induction of oxidative stress are considered important mechanisms that can lead to NM toxicity. In vitro assays measuring oxidative stress are therefore commonly included in NM hazard assessment strategies. The fluorescence-based dichloro-dihydro-fluorescein (DCFH) assay for cellular oxidative stress is a simple and cost-effective assay, making it a good candidate assay for SSbD hazard testing strategies. It is however subject to several pitfalls and caveats. Here, we provide further optimizations to the assay using 5-(6)-Chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate acetyl ester (CM-H2DCFDA-AE, referred to as DCFH probe), known for its improved cell retention.We measured the release of metabolic products of the DCFH probe from cells to supernatant, direct reactions of CM-H2DCFDA-AE with positive controls, and compared the commonly used plate reader-based DCFH assay protocol with fluorescence microscopy and flow cytometry-based protocols. After loading cells with DCFH probe, translocation of several metabolic products of the DCFH probe to the supernatant was observed in multiple cell types. Translocated DCFH products are then able to react with test substances including positive controls. Our results also indicate that intracellularly oxidized fluorescent DCF is able to translocate from cells to the supernatant. In either way, this will lead to a fluorescent supernatant, making it difficult to discriminate between intra- and extra-cellular ROS production, risking misinterpretation of possible oxidative stress when measuring fluorescence on a plate reader.The use of flow cytometry instead of plate reader-based measurements resolved these issues, and also improved assay sensitivity. Several optimizations of the flow cytometry-based DCFH ISO standard (ISO/TS 19006:2016) were suggested, including loading cells with DCFH probe before incubation with the test materials, and applying an appropriate gating strategy including live-death staining, which was not included in the ISO standard.In conclusion, flow cytometry- and fluorescence microscopy-based read-outs are preferred over the classical plate reader-based read-out to assess the level of intracellular oxidative stress using the cellular DCFH assay
FortisEDoS: A Deep Transfer Learning-Empowered Economical Denial of Sustainability Detection Framework for Cloud-Native Network Slicing
Get PDFNetwork slicing is envisaged as the key to unlocking revenue growth in 5G and beyond (B5G) networks. However, the dynamic nature of network slicing and the growing sophistication of DDoS attacks rises the menace of reshaping a stealthy DDoS into an Economical Denial of Sustainability (EDoS) attack. EDoS aims at incurring economic damages to service provider due to the increased elastic use of resources. Motivated by the limitations of existing defense solutions, we propose FortisEDoS, a novel framework that aims at enabling elastic B5G services that are impervious to EDoS attacks. FortisEDoS integrates a new deep learning-powered DDoS anomaly detection model, dubbed CG-GRU, that capitalizes on the capabilities of emerging graph and recurrent neural networks in capturing spatio-temporal correlations to accurately discriminate malicious behavior. Furthermore, FortisEDoS leverages transfer learning to effectively defeat EDoS attacks in newly deployed slices by exploiting the knowledge learned in a previously deployed slice. The experimental results demonstrate the superiority of CG-GRU in achieving higher detection performance of more than 92% with lower computation complexity. They show also that transfer learning can yield an attack detection sensitivity of above 91%, while accelerating the training process by at least 61%. Further analysis shows that FortisEDoS exhibits intuitive explainability of its decisions, fostering trust in deep learning-assisted systems
Franchisee well-being: The roles of entrepreneurial identity, autonomy perceptions, and franchisor management practices
Get PDFUsing two-level data drawn from franchisors and their franchisees, this paper explores how individual and work characteristics influence franchisee well-being. Franchising is an interesting context in which to examine well-being, given the boundary spanning nature of the franchisee role, both within the organization and across the employee-entrepreneur divide. Drawing on the Job-Demands Resource Model, we examine how a key tension in franchise systems – the desire for autonomy by franchisees and the need for standardization by franchisors – impacts franchisees' emotional exhaustion. We find that franchisees who self-identify as entrepreneurs and who are granted greater autonomy suffer less emotional exhaustion. Interestingly, our results also show that franchisees who are members of systems with strong operating routines (which should counteract autonomy perceptions) experience less emotional exhaustion, suggesting that routines can be important in reducing job demands. Our findings have a number of practical implications for franchisors. In particular, franchisors should favor franchisees with prior industry experience, which we found to be positively associated with franchisee mental well-being, and should not avoid entrepreneurial franchisees – as often suggested
Thought Experiments in Design Ethics
Get PDFHow is the designer to approach questions of responsibility, obligation, or right and wrong in relation to their role in creating, sustaining and altering the complex worlds which we inhabit together? Every design decision stands as the first teetering domino at the head of an infinitely complex fractal chain reaction of consequences, the full repercussions of which are ultimately unforeseeable. The moment of ethical crisis – being faced with a range of possible options and lacking a fully adequate knowledge of which path is best to choose – is an unavoidable component of the design process. Ethical theories, principles, codes and rules always lag one step behind the frontier of the new, the territory in which design operates. Recognising that ethical crisis is an integral reality of the design process, how can designers be best supported and equipped for this challenge? This paper explores one path towards this aim, presenting the case for the use of philosophical thought experiments as appropriate and useful devices for developing capacities for ethical thinking and for nurturing a transformed ethical mindset within practising designers. Thought experiments do not directly guide or provide knowledge or answers as to the ‘right’ thing to do in any given situation. Rather, the argument is presented here that thought experiments can stimulate productive conditions in which designers can learn not to ‘know ethics’ but to ‘think ethics’. By playing these mind games, the designer can exercise and strengthen their mental capacities for responding to ethical encounters within the complexity of real-world design practice
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