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An eco-evolutionary optimality model explains the acclimated temperature response of photosynthesis
No full textThe optimal temperature of net photosynthesis (
Topt) generally increases with plant growth temperature. Changes in Topt are associated with changes in the maximum carboxylation capacity at 25 °C (
Vcmax25) and the maximum electron transport rate at 25 °C (Jmax25). The ratio between Jmax25 and Vcmax25 declines with warming. Accurate representation of leaf-level photosynthetic responses to temperature is essential for realistic projections of the terrestrial carbon cycle and its response to ongoing climate changes. However, many land-surface models incorporate thermal acclimation through empirical approaches and through assigning distinct but static parameter values to plant functional types (PFTs). Eco-evolutionary optimality approaches provide a simpler way of modelling photosynthesis without recourse to PFTs. Here we use the sub-daily P model, an eco-evolutionary optimality-based model of photosynthesis that explicitly separates the instantaneous and acclimated responses of photosynthetic parameters to temperature to investigate how optimal temperature
changes with growth temperature, as represented by leaf or air temperature. We show that the simulated responses are consistent with observations from both controlled experiments and eddy-covariance flux tower data. We show that changes in Topt, and in the assimilation rate at Topt, are caused by changes in carboxylation capacity and electron transport rate that follow directly from the hypotheses underlying the model
Probabilistic learning and generation in deep sequence models
No full textDeep sequence models have achieved profound success across a wide range of data modalities. Despite exceptional predictive performance, the main concern of their deployment centers around the lack of uncertainty awareness. In contrast, probabilistic models quantify the uncertainty associated with unobserved variables with rules of probability. Notably, Bayesian methods leverage Bayes’ rule to express our belief of unobserved variables given some observed variables in a principled way. Since exact Bayesian inference is computationally infeasible at scale, approximate inference is required in practice. Two major bottlenecks of Bayesian methods, especially when applied in deep neural networks, are prior specification and approximation quality. In Chapter 3 and 4, we investigate how the architectures of deep sequence models themselves can be informative for specifying priors or choosing approximation methods in probabilistic models. We first develop an approximate Bayesian inference method tailored to the Transformer architecture based on the similarity between attention mechanism and sparse Gaussian process. Next, we exploit the long-range memory preservation capability of HiPPOs (High-order Polynomial Projection Operators) to construct an interdomain inducing point for Gaussian process, which successfully memorizes the history in online or continual learning. In addition to the progress of deep sequence models in predictive tasks, sequential generative models consisting of a sequence of latent variables (e.g., diffusion models), are popularized in the domain of deep generative models. Inspired by the explicit self-supervised signals for these latent variables in diffusion models, in Chapter 5, we explore the possibility of improving other deep generative models with self-supervised signals for their latent states, and investigate desired probabilistic structures over the sequence of latent states in sequential generation. Overall, this thesis leverages inductive biases in deep sequence models to design probabilistic inference or structure, which bridges the gap between deep sequence models and probabilistic models, leading to mutually reinforced improvement.Open Acces
Fabrication method of directional microstructure for high energy density, high power battery cathodes
No full textRechargeable batteries have attracted significant attention for electric transportation and storage of intermittent renewable energy. Conventional slurry coating makes random electrode microstructure with tortuous ion diffusion pathways that restrict capacity. We present a novel directional ice templating (DIT) method of making ultra-high mass loading (70 mg cm−2) LiNi0.8Mn0.1Co0.1O2 cathodes containing engineered electrode/electrolyte interface and aligned, fast ion diffusion channels to break the conventional energy-power trade-off. We investigated the effects of calendering to reduce electrode porosity while maintaining the interfacial vertical microstructure. Our results show a critical threshold of 30% calendering degree that exhibits the optimal combination of gravimetric and volumetric energy density, fast (dis)charging, and long-term cycling stability. The porosity of the calendered DIT cathode is compatible with that of the conventional slurry coated cathodes, but exhibits significantly higher energy densities of 367 Wh kg−1 and 779 Wh L−1 when the (dis)charge current is increased to 7 mA cm−2 vs. 102 Wh kg−1 and 215 Wh L−1 for the slurry coated electrodes in pouch cells. Further, we built an electrode processing instrument to demonstrate the scalability of the aqueous DIT method. The developments demonstrate the feasibility of extending the DIT approach toward industrial-scale sustainable electrode manufacturing for efficient energy storage
Prospective study of fibrosis in the lung endpoints (PROFILE): characteristics of an incident cohort of patients with idiopathic pulmonary fibrosis
No full textBackground: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive fibrotic lung disease. The PROFILE study was a prospective, observational cohort study designed to better define the natural history of IPF, understand disease biology and identify biomarkers to support disease management and enhance clinical trial design.
Methods: Individuals with an incident diagnosis of IPF were recruited between 2010 and 2017 across two co-ordinating centres in the UK. Demographics, clinical measurements and blood samples were obtained at baseline, and 1, 3, 6, 12, 24, 36 months. Disease progression events were defined as death or relative FVC decline>10% at 12 months. Survival estimates were modelled using cox proportional hazards; longitudinal lung function decline was estimated using mixed
effect models, specified with restricted cubic splines, a random intercept for participant and random effect for study visit. All models were adjusted for baseline age, sex and continuous baseline percent predicted forced vital capacity (ppFVC).
Results: A total of 632 participants were recruited, 77.1% were male and mean age at enrolment was 70.4 years (SD 8.4). Mean baseline ppFVC was 79.5% (SD 19.2), mean percent predicted DLCO (ppDLCO) was 45.7% (SD 15.1). A total of 304 (48.1%) participants met disease progression criteria at 1 year. Median survival was 3.7 years (95%CI 3.3; 4.0). More severe baseline
physiology, 12-month relative lung function decline ≥10%, older age, and short telomeres were independent risk factors for mortality. Twelve-month estimated change in ppFVC was -5.28% (95%CI -6.34; -4.22) with an average FVC decline of 186.9ml (95%CI -225.4.0; -148.5), 12-
month estimated change in ppDLCO was -3.35% (95%CI -4.30; -2.40).
Conclusion: The PROFILE cohort confirms that untreated, IPF is inexorable progressive and inevitably fatal with a poor median survival from diagnosis
Three-dimensional numerical simulations of product changeover: miscible and immiscible displacements in circular tubes
No full textWe perform three-dimensional simulations of miscible and immiscible displacements in a cylindrical pipe. For the miscible case, both laminar and turbulent displacement regimes are considered, and our numerical framework uses direct numerical simulation (DNS) and a Large Eddy Simulation (LES) approach based on a Lilly–Smagorinsky model. The dynamics of the flow are governed by the Navier–Stokes equations, coupled with a convective-diffusion equation for the concentration of the more viscous fluid when considering the miscible cases. For the immiscible laminar cases, we perform two-phase DNS considering both pinned and moving contact lines to capture the full range of immiscible dynamic behaviours. The pinned contact line reflects stationary interfaces constrained by surface heterogeneity, while the moving contact line accounts for dynamic interfacial motion influenced by viscous and capillary forces. This study shows that the viscosity contrasts between the two fluids play a significant role in determining the efficiency of ‘cleaning’ of a pipe containing an initially highly viscous resident fluid. When the viscosity of the displaced fluid is low, the laminar displacement flow is efficient in cleaning the pipe; however, when the viscosity increases, the laminar displacement becomes inadequate. Our numerical predictions in the turbulent regime showed that more efficient cleaning is achieved when the viscosity contrast between the two fluids is large. Lastly, our results reveal that the dynamics of a moving contact line can impact both the efficiency and the pattern of cleaning within the pipe
Gut microbial diversity impacts carbohydrate fermentation by children with severe acute malnutrition
No full textAfrican children suffering from severe acute malnutrition (SAM) have a disrupted gut microbiome and low short-chain fatty acids (SCFAs). These are linked to persistently high mortality and morbidity rates. Supplementing recovery feeding regimes with suitable fermentable carbohydrate may improve outcomes in SAM. We adapted in vitro colon models to investigate the ability of children with SAM to utilize four carbohydrate substrates: milk powders (with and without human milk-like oligosaccharides), chickpea-enriched feed, and inulin. All substrates, except inulin, were fermented to produce SCFAs. The inability to utilize inulin ex vivo, a widely used prebiotic, is attributed to low microbial diversity, enriched with Proteobacteria. Stool samples obtained after partial anthropometric recovery showed increased microbial diversity and higher levels of GH32 enzyme family, responsible for inulin metabolism. These findings can inform the design of future therapeutic feeds for the treatment of SAM, where inulin has been found ineffective during initial hospitalization. Alternative carbohydrates appear to be more effective in supporting gut recovery during both the initial and later treatment phases
Piezomagnetic devices based on antiperovskite nitride thin films
No full textPiezomagnetic coupling properties of manganese-based (Mn-based) nitride antiperovskites, Mn3XN (X=Ni, Ga, Sn), offer control of magnetism by electric field. This study suggests a device structure consisting of antiferromagnetic and ferroelectric/piezoelectric materials that can induce a net magnetisation in the antiferromagnetic material Mn3XN by means of a physical effect termed the piezomagnetic effect.
In this study, epitaxial thin films of Mn3XN were deposited on different single-crystal substrates. The research results show a clear correlation between the induced magnetisation and biaxial strain, compressive or tensile, given by the lattice mismatch between film and substrate. The induced magnetisation increases with the increase of the biaxial strain. Also, the Néel temperature (TN) of the Mn3NiN film is found to be strongly dependent on the biaxial strain. A change in TN of approximately 60 K is achieved by a biaxial strain of ±2.5%. In addition, the largest in-plane saturation magnetisation of 0.38 B/f.u. is obtained from the Mn3NiN film. The same saturation magnetisation is acquired in Mn3GaN film, whereas high saturation magnetisation of 0.6 B/f.u. is achieved in Mn3SnN film under a compressive strain of -0.18%.
Mn3NiN piezomagnetic device demonstrates the deterministic switching of magnetisation via electric field at low temperature, even in the absence of an external magnetic field. A large magnetocapacitance (MC) effect of 1400% is found in the Mn3GaN piezomagnetic device with respect to a DC bias of -1.5 V and a magnetic field of 7 T. The large MC effect originates from the piezomagnetic effect provided by the strained antiferromagnetic layer MGN induced by the underlying ferroelectric layer BST under the DC electric field.
The piezomagnetic effect is experimentally demonstrated, particularly in heterostructure devices. The work demonstrates the realisation of modulation of magnetic moments by the electric field by means of the piezomagnetic effect in conjunction with the ferroelectric effect.Open Acces
Hormone replacement therapy and the risk of asthma attacks: population-based cohort study
No full textBackground
Women experience higher rates and greater severity of asthma after puberty, suggesting that sex hormones play a key role in airway disease. Hormone replacement therapy (HRT), which acutely alters circulating sex hormone levels, provides a useful model to examine their effects on asthma attacks. We sought to examine the association between HRT use and asthma attacks.
Methods
We obtained a cohort of women with asthma, aged 45 to 60 years, using nationwide U.K. primary care health records linked to hospital and mortality data, 2004-2020, to compare HRT-users to non-users. We applied inverse-probability of treatment weighting and Cox proportional
hazards, accounting for demographics, asthma severity and comorbidities; stratifying by potential modifiers: body mass index (BMI), blood eosinophil count, smoking and HRT-type (oestrogen-only, progesterone-only and combined).
Results
182,010 women were eligible for the study, of whom 9,663 were incident HRT users and 172,347 were non-users. Median age was 52 years (IQR: 50-55 years). HRT-users and non-users were broadly similar in terms of BMI, smoking history but non-users had slightly higher proportions residing in more deprived areas, with more comorbidities, higher reliever use and asthma attacks in the year before study entry, but lower use of preventer inhalers. After applying weighting, there was no association found between HRT use and asthma attacks (weighted-HR 0.97, 95% CI 0.90-1.04). There was no modification of that association by blood eosinophil level, BMI, smoking history or HRT-type.
Conclusion
Hormone replacement therapy use is not associated with asthma attacks
in women with established asthma aged 45 to 60 years old
When is the R = 1 epidemic stability threshold meaningful?
No full textThe effective reproduction number R is a predominant statistic for tracking the transmissibility of infectious diseases and informing public health policies. An estimated R=1 is universally interpreted as indicating epidemic stability and is a critical threshold for deciding whether infections will grow (R>1) or fall (R<1). We demonstrate that this threshold, which is typically
computed over coarse spatial scales, seldom signifies stability because those scales regularly average stochastic infections from groups with heterogeneous transmission characteristics. Groups with falling and rising infections counteract and early-warning signals from resurging groups are obscured by noisy fluctuations from stable groups with larger infections. We prove
that an estimated R=1 is consistent with a vast space of epidemiologically diverse scenarios, often leading to false-positive stability signals that diminish its predictive and policymaking value. In contrast, we show that a popular, alternative definition of transmissibility, relating to the next-generation matrix of the groups, overcorrects this issue and yields false-negative stability signals by maximising sensitivity to stochasticity. We find that a recently developed statistic, E, derived from R using experimental design theory, rigorously constrains the space of scenarios corresponding to stability, while limiting noise sensitivity. We establish E=1 as a
more practical and meaningful real-time stability threshold
The Untapped Potential: How Managerial Capabilities Drive Supply Chain Resilience
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose – This study investigates how managerial dynamic capabilities, including entrepreneurial leadership and social capital, contribute to supply chain resilience through supply chain integration. We further explore whether supply chain flexibility moderates this relationship.
Design/ Methodology/Approach – This study applies the dynamic capabilities view and resource orchestration theory to analyze the antecedents of supply chain resilience. Using a time-lagged survey and structural equation modeling, we generate robust insights that enhance the field's understanding of how managerial capabilities influence the supply chain resilience.
Findings – This study examines how managerial dynamic capabilities, entrepreneurial leadership and managerial social capital, influence supply chain integration, which in turn mediates the relationship between these capabilities and supply chain resilience. We further find support for the moderating role of supply chain flexibility on the integration-resilience link.
Originality/Value – This paper advances the understanding of supply chain resilience by demonstrating the critical role of managerial dynamic capabilities as its microfoundation. We specifically illuminate how entrepreneurial leadership and social capital foster supply chain integration, a key mechanism for building resilience