157082 research outputs found
Sort by
The deep structure of the Pernambuco Plateau, Northeast Brazil, and its implications for Equatorial Atlantic rifting
No full textThe Pernambuco Plateau Basin (PPB) of northeastern Brazil contains an important record of continental rifting at the boundary between the major South Atlantic basins and the Equatorial Atlantic Gateway (EAG). The geology and structure of the PPB is described using high quality long-offset multi-channel seismic data. The deep seismic imaging reported here shows that the PPB is not thick continental crust with a thin sediment veneer but thinned continental crust with half grabens in which sediment thicknesses reaches in excess of 3 km. Within these deep grabens we find large halokinetic structures in the form of salt diapirs and pillows that root into the early syn-rift. Sub-marine volcanic edifices are also clearly imaged, the oldest of which have bases close to the syn-to-post rift transition. We discuss the PPB evolution integrating the implications of the newly observed evidence for syn-rift salt deposition and early post-rift sub-marine volcanic activity as well as a reanalysis of recent plate models. The proposed best fit model has PPB rifting in the Aptian and early Albian, with final break-up relatively late in the Albian
A Novel Spatio-Temporal Rate-Splitting-based Power Allocation Optimization Strategy for RIS-assisted 6G MU-MISO Communication Systems
No full textReconfigurable intelligent surfaces (RISs) can dynamically adjust phase shifts to achieve scalability in networks, while rate-splitting multiple access (RSMA) can dynamically allocate spectrum and power resources according to the communication needs of IoT devices and reduce the energy consumption of the system. Therefore, the integration of RIS and RSMA can not only enhance the performance of IoT communication systems, but also reduces wastage of limited resources. This paper proposes a novel spatio-temporal rate-splitting-based power allocation optimization strategy for RIS-assisted multi-user (MU) systems to maximize channel capacity and energy efficiency gains. Leveraging the proposed spatio-temporal minimum mean squared error (STMMSE) principle and the rate splitting-based optimal power consumption (RS-OPC) method, the approach considers the Cramér-Rao bound for channel errors and derives expressions for maximizing channel capacity and obtaining the optimal solution. The proposed method selectively adjusts power values for different users and transmission types of symbols to achieve optimal power allocation objectives, thereby ensuring communication quality while optimizing channel capacity. This offers communication systems a higher configurability and resource optimization. Extensive simulation results including channel capacity, energy efficiency (EE) and spectral efficiency (SE) validate the effectiveness of the proposed method
A novel deep eutectic solvent-based liquid membrane for the extraction of glycerol from crude biodiesel
No full textThis study used deep eutectic solvent (DES) as the liquid membrane in a bulk liquid membrane system (BLM) to remove glycerol from waste cooking oil-based biodiesel. The DES was prepared from choline chloride and tetraethylene glycol at a molar ratio of 1:5. Diethyl ether was employed as a novel strip phase for the glycerol in BLM. The effects of the DES: biodiesel ratio, stirring speed, and extraction time on the extraction and stripping efficiencies were investigated. The results showed that BLM could give better glycerol removal from biodiesel than mechanical shaking. Increasing the DES: biodiesel ratio, stirring speed, and extraction time can enhance glycerol removal from the feed phase, achieving purified biodiesel that complies with biodiesel international standards. The purified biodiesel met the ASTM D6751 and EN 14214 international standards requirement for glycerol content of less than 0.24% under the following conditions of DES: biodiesel ratio of 1:1, stirring speed of 200 rpm, and extraction time of 240 min. The transport mechanisms of glycerol in the system were postulated based on two consecutive irreversible first-order extraction and stripping. The kinetic study shows that the extraction and stripping processes in this system could be explained by a first-order kinetic model, as the experimental results fitted into the model showed R2 values of 0.98, 0.97, and 0.97 for the feed phase, membrane phase, and strip phase, respectively. The extraction and stripping rate constants (k1 and k2) were 0.0031 and 0.0019 min−1, respectively.</p
Systems thinking for sustainability: shifting to a higher level of systems consciousness
No full textThe grand challenges encapsulated in the seventeen UN Sustainable Development Goals to be achieved by 2030, are complex, messy and interconnected. Fulfilling these goals necessitates a shift in mindset from ego-to-ecosystems awareness and an imperative for stakeholder collaboration. Systems thinking is crucial to address sustainability challenges and an agenda for sustainable development. While some management approaches, like Doughnut Economics and Circular Economy, have roots in systems thinking, there is limited research into system thinking for sustainability. Nevertheless, the authors suggest we can learn from many systems-based contributions in the environmental science/studies literature that address ecological/Earth issues (e.g., Gaia, autopoiesis) and the Operational Research/Systems literature rich in a tradition of engaging communities in analysis and taking action. We ask, “How can systems thinking help businesses to meaningfully engage their stakeholders in a shared sense of purpose, value and impact?” The “systemic sustainability” framework (SSF) is proposed to address this, extending Laszlo’s concept and incorporating traditional systems thinking principles. The SSF emphasises that organisations and their stakeholders engage at four levels of systems awareness, reflecting on organisational purpose, and balancing organisational viability with planetary pressures. Interdependence, legitimacy and thrivability are highlighted as critical concepts in systems thinking for sustainability
Root Exudation Facilitates Water Infiltration and Rewetting of Dry Soil
No full textThe way plant roots facilitate water infiltration in soil may be just as important as the efficiency with which the root system in turn extracts it from the soil. Here we studied the mechanisms through which the root system facilitates water infiltration through a dry soil layer. Dye tracing experiments were conducted in model soil microcosms to characterise how root growth and exudation affect the permeability of dry layers of the model soil. Results showed that the growth of plant roots through the dry layers of an artificial soil increased the water infiltration rate. In the absence of roots, dissolved root exudates had a significant effect on water infiltration but penetration of the dry layer by a needle did not. We conclude that in dry soil, root architecture and root exudation act synergistically to increase soil hydraulic conductivity, and this may help decrease the water lost by evaporation. This mechanism could be used to select root traits that match the soil and climate, thereby improving water use efficiency in agriculture
NLP verification:towards a general methodology for certifying robustness
No full textMachine learning has exhibited substantial success in the field of natural language processing (NLP). For example, large language models have empirically proven to be capable of producing text of high complexity and cohesion. However, at the same time, they are prone to inaccuracies and hallucinations. As these systems are increasingly integrated into real-world applications, ensuring their safety and reliability becomes a primary concern. There are safety critical contexts where such models must be robust to variability or attack and give guarantees over their output. Computer vision had pioneered the use of formal verification of neural networks for such scenarios and developed common verification standards and pipelines, leveraging precise formal reasoning about geometric properties of data manifolds. In contrast, NLP verification methods have only recently appeared in the literature. While presenting sophisticated algorithms in their own right, these papers have not yet crystallised into a common methodology. They are often light on the pragmatical issues of NLP verification, and the area remains fragmented. In this paper, we attempt to distil and evaluate general components of an NLP verification pipeline that emerges from the progress in the field to date. Our contributions are twofold. First, we propose a general methodology to analyse the effect of the embedding gap - a problem that refers to the discrepancy between verification of geometric subspaces, and the semantic meaning of sentences which the geometric subspaces are supposed to represent. We propose a number of practical NLP methods that can help to quantify the effects of the embedding gap. Second, we give a general method for training and verification of neural networks that leverages a more precise geometric estimation of semantic similarity of sentences in the embedding space and helps to overcome the effects of the embedding gap in practice.</p
Crowdedness, Mispricing, Crashes, and Spikes
No full textThis study proposes “reflexive crowdedness” as a mechanism through which order flow can become toxic at ultra-high frequencies (UHFs). Crowdedness, a coordination problem arising from the inability of traders to accurately gauge competition, leads to significant unbalanced mispricing in the form of liquidity costs. This mispricing is amplified by (reflexive) feedforward loops between liquidity and price components and can accumulate rapidly when high-speed traders engage. We develop an empirical framework to examine this mechanism in UHF trading. Results on trades of Dow 30 stocks show that reflexive crowdedness triggers speculative algorithmic trading and drives order flow toxicity and market instability at high frequencies. We formulate a UHF measure of reflexive crowdedness and find it predicts various UHF phenomena, including flash crashes and spikes, more reliably than price volatility and the Volume Synchronised Probability of Informed Trading (VPIN). This makes this measure highly relevant to investors, traders, market operators, and regulators
AI-Powered Simulations for Experiential Marketing Education
No full textThis study examines the role of AI-based simulators in experiential marketing education. By designing an interactive conceptual model, it is shown how the combination of intelligent algorithms with experiential learning theory can enhance student engagement, improve marketing decision analysis, and personalize the learning path. The benefits, challenges, and implementation dimensions of this technology are also analyzed, and suggestions are made for effective utilization in the higher education system
Exploring novel thiazole-based minor groove binding agents as potential therapeutic agents against pathogenic Acanthamoeba castellanii
No full textDue to limited advances in diagnosis and targeted therapy, as well as poor understanding of pathophysiology, infections due to Acanthamoeba have remained a medical concern. With their ability to selectively bind to DNA sequences, minor groove binders have emerged as useful therapeutic agents against parasitic infections. Herein, 6 novel thiazole-based minor groove binders were synthesized. Purification of intermediate compounds was accomplished by utilising silica gel column chromatography, while thin-layer chromatography was utilised to monitor reactions. The purification of the final products was achieved using liquid chromatography. Confirmation of structures was achieved by NMR spectroscopy and mass spectrometry. All compounds were evaluated against pathogenic A. castellanii via in vitro assays. At micromolar concentrations, selected minor groove binder derivatives revealed potent effects against (i) A. castellanii trophozoites as observed using amoebicidal assays, (ii), against A. castellanii cysts as observed using excystation assays, and (iii) against A. castellanii-mediated host cell death utilising human cerebrovascular endothelial cells, but (iv) showed limited effects against host cells alone, using cytotoxicity assays. The binding interaction between minor groove binders and DNA was studied using isothermal titration calorimetry and molecular docking simulations to provide insights into their binding affinity and mode of interaction. The findings of our study underscore the therapeutic value of thiazole-based minor groove binders as potent agents against A. castellanii, demonstrating effective antiamoebic activity with a low propensity for human cell damage, thus supporting their further development as antiamoebic agents.</p
Access Repository Dashboard
Do you manage Heriot Watt Pure? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!