A fully-coupled algorithm with implicit surface tension treatment for interfacial flows with large density ratios

ABSTRACT: The stability of most surface-tension-driven interfacial flow simulations is governed by the capillary time-step constraint. This concerns particularly small-scale flows and, more generally, highly-resolved liquid-gas simulations with moderate inertia. To date, the majority of interfacial-flow simulations are performed using an explicit surface-tension treatment, which restrains the performance of such simulations. Recently, an implicit treatment of surface tension able to breach the capillary time-step constraint using the volume-of-fluid (VOF) method was proposed, based on a fully-coupled pressure-based finite-volume algorithm. To this end, the interface-advection equation is incorporated implicitly into the linear flow solver, resulting in a tight coupling between all implicit solution variables (colour function, pressure, velocity). However, this algorithm is limited to uniform density and viscosity fields. Here, we present a fully-coupled algorithm for interfacial flows with implicit surface tension applicable to interfacial flows with large density and viscosity ratios. This is achieved by solving the continuity and momentum equations in conservative form, whereby the density is treated implicitly with respect to the colour function, and the advection term of the interface-advection equation is discretised using the THINC/QQ algebraic VOF scheme, yielding a consistent discretisation of the advective terms. This new algorithm is tested by considering representative surface-tension-dominated interfacial flows, including the Laplace equilibrium of a stationary droplet and the three-dimensional Rayleigh-Plateau instability of a liquid filament. The presented results demonstrate that interfacial flows with large density and viscosity ratios can be simulated and energy conservation is ensured, even with a time step larger than the capillary time-step constraint, provided that other time-step restrictions are satisfied

Tau levels in platelets isolated from Huntington's disease patients serve as a biomarker of disease severity

ABSTRACT: Tau is a microtubule protein that is known to be hyperphosphorylated and to aggregate in several chronic neurodegenerative disorders. In many cases, in particular in Alzheimer’s disease, the degree of tau pathology has been demonstrated to correlate with cognitive deficits and/or decline. In Huntington’s disease (HD), a dominantly inherited neurodegenerative disorder, both cognitive impairments and abnormal tau expression have been reported to occur, along with the accumulation of the mutant huntingtin protein. In this respect, tau has been shown to be present in the cerebrospinal fluid of individuals with HD and to increase with disease progression. However, how this relates to changes in tau found in the periphery is largely unknown. In this study, we collected blood samples from patients with HD and isolated multiple blood components including plasma, platelets, and peripheral blood mononuclear cells to measure their tau levels and subsequently correlate these to cognitive impairments and disease stage. Our results suggest that the amount of tau, particularly N-terminal tau (NTA-tau) and total tau (t-tau), is elevated in all assayed blood components and that the quantity of tau within platelets, specifically, is strongly correlated with disease severity

A digital transformation project portfolio management model for underground mines

ABSTRACT: This paper addresses the difficulties mining companies face in planning their digital transformation. Based on the literature on project portfolio management and digital transformation, we propose a project portfolio management model adapted to the mining industry that aims at aligning the value of the digital transformation projects with the desired strategic outcomes of the Smart Mine. This paper focuses on the initiative’s identification phase, divided into portfolio, program, and project levels. The model, which has not been tested yet, follows the academic and industrial best practices to answer the mining specificities, including risk management, communication and stakeholder management, and change management

Gravitational search algorithm swarm based drone reconnaissance for target detection in unknown environment

ABSTRACT: Target detection in an unknown environment is a crucial aspect of reconnaissance using a swarm of unmanned aerial vehicles (UAVs). An efficient target detection technique is required to minimize the number of iterations for searching and maximize the coverage area with respect to the number of iterations and detected targets. This paper proposes a gravitational search algorithm (GSA) swarm-based UAV reconnaissance scheme to detect targets in an unknown environment. Additionally, different GSA-based searching methods are analyzed to identify the most efficient one with the minimum number of iterations and maximum coverage. Extensive simulations are performed, and the results of the proposed scheme are compared with existing search schemes. The results demonstrate that the proposed GSA swarm-based detection scheme requires fewer iterations and provides greater area coverage than existing UAV reconnaissance schemes for target detection in an unknown environment

Assessing the climate benefits of afforestation in the Canadian Northern Boreal and Southern Arctic

ABSTRACT: Afforestation greatly influences several earth system processes, making it essential to understand these effects to accurately assess its potential for climate change mitigation. Although our understanding of forest-climate system interactions has improved, significant knowledge gaps remain, preventing definitive assessments of afforestation's net climate benefits. In this review, focusing on the Canadian northern boreal and southern arctic, we identify these gaps and synthesize existing knowledge. The review highlights regional realities, Earth's climatic history, uncertainties in biogeochemical (BGC) and biogeophysical (BGP) changes following afforestation, and limitations in current assessment methodologies, emphasizing the need to reconcile these uncertainties before drawing firm conclusions about the climate benefits of afforestation. Finally, we propose an assessment framework which considers multiple forcing components, temporal analysis, future climatic contexts, and implementation details. We hope that the research gaps and assessment framework discussed in this review inform afforestation policy in Canada and other circumpolar nations