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The dispersion behaviour of solutes in flow is crucial to the design of chemical separation systems and microfluidics devices. These systems often rely on coupled electroosmotic and pressure-driven flows to transport and separate chemical species, making the transient dispersive behaviour of solutes highly relevant. However, previous studies of Taylor dispersion in coupled electroosmotic and pressure-driven flows focused on the long-term dispersive behaviour and the associated analyses cannot capture the transient behaviour of solute. Further, the radial distribution of solute has not been analysed. In the current study, we analyse the Taylor dispersion for coupled electroosmotic and pressure-driven flows across all time regimes, assuming a low zeta potential (electric potential at the shear plane), the Debye–Hückel approximation and a finite electric double layer thickness. We first derive analytical expressions for the effective dispersion coefficient in the long-time regime. We also derive an unsteady, two-dimensional (radial and axial) solute concentration field applicable in the latter regime. We next apply Aris’ method of moments to characterise the unsteady propagation of the mean axial position and the unsteady growth of the variance of the solute zone in all time regimes. We benchmark our predictions with Brownian dynamics simulations across a wide and relevant dynamical regime, including various time scales. Lastly, we derive expressions for the optimal relative magnitudes of electroosmotic versus pressure-driven flow and the optimum Péclet number to minimise dispersion across all time scales. These findings offer valuable insights for the design of chemical separation systems, including the optimisation of capillary electrophoresis devices and electrokinetic microchannels and nanochannels.
This study presents an automatic differentiation (AD)-based optimisation framework for flow control in compressible turbulent channel flows. Using a differentiable solver, JAX-Fluids, we designed fully differentiable boundary conditions that allow for the precise calculation of gradients with respect to boundary control variables. This facilitates the efficient optimisation of flow control methods. The framework’s adaptability and effectiveness are demonstrated using two boundary conditions: opposition control and tunable permeable walls. Various optimisation targets are evaluated, including wall friction and turbulent kinetic energy (TKE), across different time horizons. In each optimisation, there were around $4\times 10^4$ control variables and $3\times 10^{9}$ state variables in a single episode. Results indicate that TKE targeted opposition control achieves a more stable and significant reduction in drag, with effective suppression of turbulence throughout the channel. In contrast, strategies that focus directly on minimising wall friction were found to be less effective, exhibiting instability and increased turbulence in the outer region. The tunable permeable walls also show potential to achieve stable drag reduction through a ‘flux-inducing’ mechanism. This study demonstrates the advantages of AD-based optimisation in complex flow control scenarios and provides physical insight into the choice of the quantity of interest for improved optimisation performance.
Tropical peatlands are important global carbon sinks, and the ways they differ from adjacent forest ecosystems in environmental functions have not been well characterized. Our study investigated family-level floristic and soil differences between adjacent paired patches of intact waterlogged peat forests and kerangas (free-draining heath) forests in Brunei Darussalam. For each patch, we examined total and labile nutrient concentrations in soils, tree stand diversity and structural characteristics, functional traits of live leaves and leaf litter, and nutrient resorption during leaf senescence. We found that total nutrients were more abundant in peat and kerangas humus than in kerangas sand, while available nutrients were highest in kerangas humus, suggesting that anoxic conditions in peat soils impair mineralization of nutrients to available forms but do not lead to losses of nutrient capital. We also found significant compositional differences among those families that occur frequently in both peat and kerangas plots. Despite this, family-level measures of tree diversity and structural characteristics, including tree abundance and stand basal area, did not differ between forest types. Similarly, leaf and litter functional traits and nutrient resorption were invariant across forest types, indicating low plasticity of leaf characteristics associated with plant nutrition. This suggests that belowground carbon accumulation in peatlands is disconnected from aboveground plant community characteristics and is likely driven by belowground processes.
Suicidal and self-harming behaviours present a significant challenge for mental health services. Recent national guidelines advocate abandoning tools based on box-ticking and a move towards a personalised psychosocial assessment. This article examines evidence from theoretical and empirical research in this area and attempts to integrate it by introducing the source–problem–solution–motive (SPSM) model. The model, which builds on the contributions of other suicidologists, specially Jean Baechler, could be used as a framework for the assessment and management of these behaviours. The four stages of the model provide a comprehensive approach that enables an exploration of the internal logic of the behaviour. The model covers ‘because’ and ‘in-order-to’ motives. This allows a personalised approach, but also a structured one that can be taught and generalised.
We present a model that locates the source of vagueness as the speaker’s inability to perfectly perceive the world. We show that the agents will communicate clearly about the world as the sender perceives it. However, the implied meaning about the actual world will be vague. Vagueness is characterized by probability distributions that describe the degree to which a statement is likely to be true. Hence, we provide micro-foundations for truth-degree functions as an equilibrium consequence of the sender’s perception technology and his optimal, non-vague communication in the perceived world – connecting the epistemic and truth-degree approaches to vagueness.
Anthuroid isopods in the genus Mesanthura (52 valid species) typically have a body with conspicuous dorsal pigmentation, with differences in the female pigmentation pattern being one of the main characters used to distinguish species. Five Mesanthura species have been reported to date from Japan. Here, we describe Mesanthura solsp. nov. from Irabu Island and Okinawa main island, Okinawa, Japan, and illustrate its sexual dimorphism in colour pattern, with conspecificity between males and females confirmed with molecular data. We provide a description of Mesanthura miyakoensis based on specimens collected from Kochi, Shikoku, Japan. We present the first records of Mesanthura cinctula and Mesanthura nigrodorsalis, following their original descriptions. Finally, we provide partial sequences of the 16S rRNA gene for these four species and present a phylogenetic tree based on the sequences.
History is littered with unfulfilled promises that emerging technologies – from radios to televisions, and from computers to mobile phones – would completely transform teaching and learning. Now the same promises are being made of generative artificial intelligence (AI). This presentation argues that we should not be focusing on educational revolution, but instead on educational evolution. Education is a complex social, cultural, and political endeavour, serving multiple purposes and multiple stakeholders, and technology is just one of many elements in this large ecosystem.
Focusing on the context of language teaching and learning, this presentation discusses what has changed technologically, and suggests what could and should change educationally. It shows that ChatGPT and a range of other generative AI tools can contribute to language and literacy development in a number of ways, but that we need to be wary of their pedagogical, social, and environmental risks. Educators must develop the AI literacy necessary to take a more nuanced view of generative AI, and we must help our students to do the same.
This paper is based on a keynote presentation delivered at the English Australia Conference in Perth, Australia, on 12 September 2024, with some elaborations for the written version alongside minor updates to reflect more recent developments and publications.
We perform a comprehensive linear non-modal stability analysis of the Rayleigh–Bénard convection with and without a Poiseuille/Couette flow in Oldroyd-B fluids. In the absence of shear flow, unlike the Newtonian case in which the perturbation energy decays monotonically with time, the interaction between temperature gradient and polymeric stresses can surprisingly cause a transient growth up to 104. This transient growth is maximized at the Hopf bifurcation when the stationary instability dominant in the weakly elastic regime transitions to the oscillatory instability dominant in the strongly elastic regime. In the presence of a Poiseuille/Couette flow, the streamwise-uniform disturbances may achieve the greatest energy amplification, and similar to the pure bounded shear flows, Gmax ∝ Re2 and tmax ∝ Re, where Gmax is the maximum energy growth, tmax the time to attain Gmax, Re the Reynolds number. It is noteworthy that there exist two peaks during the transient energy growth at high-Re cases. Different from the first one which is less affected by the temperature gradient and elasticity, the second peak, at which the disturbance energy is the largest, is simultaneously determined by the temperature gradient, elasticity and shear intensity. Specifically, the polymeric stresses field absorbs energy from the temperature field and base flow, which is partially transferred into the perturbed hydrodynamic field eventually, driving the transient amplification of the perturbed wall-normal vorticity.
This paper presents the development and implementation of a comprehensive system for acquiring telemetry from Alsat-2A and Alsat-2B satellites, whose orbits are phased 180 degrees apart, utilising the CDM600 demodulator. Integral to this system is an automatic learning module leveraging machine learning algorithms to optimise circular polarisation selection based on reception conditions. The software segment manages the demodulator, user interface, and coordinates the machine learning algorithm, drawing insights from historical polarisation data to construct predictive models for optimal polarisation selection. Through the integration of machine learning, this system aims to enhance telemetry signal reception quality, contributing to the success (Alsat-2A was launched on 12 July 2010, and Alsat-2B on 26 September 2016) of satellite missions.
Well-preserved specimens of the xanthid crab Lathahypossia aculeata (Busulini, Tessier, and Visentin, 1984) coming from middle Eocene volcanoclastites at Main quarry (Vicenza, Northeast Italy) are housed in three Museums in the Veneto region. Their exoskeletons, mainly chelipeds and thoracic sternum, are significantly encrusted by serpulid tubes assigned to the new species Propomatoceros lathahypossiae. Serpulids belong to the genus Propomatoceros, which has until now ranged from the Triassic to the Cretaceous; this record of the genus is the first in the Cenozoic. The abundance, frequency, and distribution pattern of the serpulid specimens on the different parts of the exoskeleton of the crabs were investigated, shedding light on the ecology/behavior of the encrusting species. Finally, the settlement and growth of serpulids related to sex, size, and molting cycle of the crabs were discussed, hypothesizing on the type of symbiotic relationship among the encrusters and their host.
Accacoeliid digeneans associated with fish of the family Molidae exhibit enigmatically high taxonomic diversity. However, the phylogenetic relationships between species within this digenean taxon are poorly understood. In the present study, the first nuclear 28S rRNA gene, ITS2 region of nuclear DNA, and mitochondrial cox1 gene sequence datasets were obtained for two members of the Accacoeliidae, a type and only species of the genus Odhnerium Yamaguti 1934 and an unidentified Accacladocoelium sp. collected from Mola mola (Linnaeus, 1758) off Iturup Island. Analyses of molecular differentiation and phylogenetic relationships indicate that Accacladocoelium sp. is a sister species to Accacladocoelium nigroflavum (Rudolphi, 1819). The genus Odhnerium is closely related to Tetrochetus Looss, 1912, on the 28S rRNA gene-based phylogenetic tree. Results of phylogenetic analysis based on both the mitochondrial cox1 gene and the concatenated ribosomal ITS2 region and cox1 gene of mtDNA show that the genus Odhnerium is close to the A. nigroflavum + Accacladocoelium sp. clade. In turn, the genus Accacladocoelium does not have monophyletic status in the trees reconstructed from these data.
Technical progress is considered a key element in the fight against climate change. It may take the form of technological breakthroughs, that is, shocks that induce significant leaps in the stock of knowledge. We use an endogenous growth framework with directed technical change to analyze the climate impact of such shocks. Two production subsectors coexist: one subsector is fossil-based, using a non-renewable resource, and yields carbon emissions; the other subsector uses a clean, renewable resource. At a given date, the economy benefits from an exogenous technology shock. We fully characterize the general equilibrium and analyze how the shock modifies the economy’s trajectory. The overall effect on carbon emissions basically depends on the substitutability between the production subsectors, the initial state of the economy, and the nature and size of the shock. We notably show that green technology shocks induce higher short-term carbon emissions when the two subsectors are gross complements, but also in numerous cases when they are gross substitutes.
Narratives and studies of Latino partisanship often emphasize Democratic identification, but some have recently suggested a shift towards Republicans. We address these by examining Latino party identification over a 34-year period, leveraging 35 national surveys with a total of over 103,000 Latino respondents along with Census data to create post-stratified survey weights to correct for biases. We emphasize changing partisanship over time by nativity, birth cohorts, and by national origin. From 2000 to 2012, we observed a slight overall increase in Democratic identification and a decrease in Republican identification, but this was driven by foreign-born Latinos. After 2012, we see declining Democratic identification overall, greater Republican identification among foreign-born and older native-born Latinos, and accelerating Independent identification among native-born Millennial and Gen Z Latinos. These results show that generational turnover and differences by nativity challenge extant theories of Latino partisan change over time.
Feigenbaum universality is shown to occur in subcritical shear flows. Our testing ground is the counter-rotation regime of the Taylor–Couette flow, where numerical calculations are performed within a small periodic domain. The accurate computation of up to the seventh period-doubling bifurcation, assisted by a purposely defined Poincaré section, has enabled us to reproduce the two Feigenbaum universal constants with unprecedented accuracy in a fluid flow problem. We have further devised a method to predict the bifurcation diagram up to the accumulation point of the cascade based on the detailed inspection of just the first few period-doubling bifurcations. Remarkably, the method is applicable beyond the accumulation point, with predictions remaining valid, in a statistical sense, for the chaotic dynamics that follows.