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Cardiovascular risk in MASLD: what multiple lines of evidence reveal
Get PDFMetabolic dysfunction-associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD) is a consequential and increasingly prevalent manifestation of the obesity epidemic. While the natural history of MASLD may progress to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis and, in some cases, cirrhosis, most patients with MASLD do not die from liver-related complications but rather from cardiovascular events.[1] This strong epidemiological association has fuelled an ongoing debate in hepatology and cardiology: does MASLD independently increase cardiovascular risk beyond established risk factors, or is it primarily a manifestation of shared risk pathways? This paper discusses relevant evidence from multiple angles to argue that MASLD presently cannot be considered an independent CV risk factor but that patients with MASLD represent a high-risk group who should be screened for CV risk factors to allow for holistic risk reduction.
Substantial effort has been devoted to this question[2], [3] - arguably far more than it warrants - since, regardless of its independence, optimal care necessitates holistic cardiovascular risk assessment and risk factor management
Co-mapping future scenarios and uncertainties amid climate crisis: A collective study of coastal towns and the Port of Tyne
Get PDFThis study investigates the transformative potential of post-industrial coastal towns surrounding the Port of Tyne by integrating the values and priorities of local communities. Focusing on underutilised brownfield sites, it develops innovative regeneration strategies that address entrenched regional disparities rooted in historical inequalities, political instability and policy inertia. By analysing the evolving role of the port within the energy system, and situating the coastal communities within the broader context of energy transition policies, this research develops a conceptual framework centred on socio-ecological transition. This framework underpins a series of participatory planning interventions, comprising walking ethnographies, participatory GIS, scenario building in shaping alternative urban futures, and strategy mapping to facilitate the desired systemic shift. The resulting strategies are consolidated into a practical regeneration toolkit designed for strategic sites across South Tyneside and North Tyneside. The Port of Tyne and its surrounding communities provide an in-depth case study, demonstrating how various actors can influence the development of an energy-inclusive port-urban environment. Importantly, the research reveals how local narratives, imbued with emotional and experiential dimensions, challenge and reframe dominant policy discourses, asserting the legitimacy of lived knowledge in planning processes. The research contributes a replicable model for inclusive and equitable renewal, offering actionable insights for other coastal and post-industrial regions. It advocates for policy and investment mechanisms that prioritise community resilience and agency, ensuring that the energy transition is both sustainable and socially inclusive
Poroelasticity derived from the microstructure for intrinsically incompressible constituents
No full textWe provide a new derivation of the quasi-static equations of Biot’s poroelasticity from the microstructure via the asymptotic (periodic) homogenisation method (AHM) by assuming intrinsic incompressibility of both an isotropic, linear elastic solid and a low Reynolds’ number Newtonian fluid, in a small deformations regime. This is done by starting from a fluid–structure interaction (FSI) problem between the two phases at the pore scale, and by introducing both a solid and a fluid pressure, as both phases are equipped with an incompressibility constraint. Upscaling by the AHM then results in the expected Biot’s equation at the macroscopic scale, with coefficients which are to be computed by solving non-standard periodic cell problems at the pore scale. These latter differ from the ones arising from classical derivations of poroelasticity via the AHM, which are typically obtained by assuming that the elastic phase is compressible, and are characterised by a saddle point structure which is inherited from the equations governing the original FSI problem. The proposed approach, which is new and cannot be derived as a particular case of existing formulations, means that the poroelastic governing equations for intrinsic incompressible phases are obtained without performing any “a posteriori” assumption on the macroscale coefficients, as these latter are typically employed based on physical arguments rather than following from a rigorous analysis of the properties of the pore scale cell problems. The advantages of the current formulation for incompressible solids are as follows. (a) The formulation is derived for two genuinely incompressible phases and in particular for an incompressible solid, which means that a reduced number of input parameters is required to compute the effective stiffness. In the case of pore scale isotropy, this means that only the shear modulus is to be provided. (b) The pore scale cell problems can be solved without approximating the pore scale elastic properties to that of an incompressible solid, i.e. in the case of isotropy, no additional errors are to be introduced by utilising approximate values of the Poisson’s ratio (which in a compressible formulation can be close to, but not identical to, 0.5)
Enhancing single-temporal semantic and dual-temporal change perception for remote sensing change detection
No full textFedRand: A Federated Random Forest Learning Technique for Anomaly Detection in IoT Networks
No full textFederated Learning (FL) is an emerging distributed machine learning (ML) technique distinguished by non-independent and identically distributed (Non-IID) data, statistical heterogeneity, and an expected large number of participating clients to collaboratively train a shared model without fusing the training data into one centralized server. State-of-the-art FL research focuses on gradient-based models, which is not suitable for ML-based intrusion detection systems that utilize tree-based learning methods such as Random Forest. Adapting a typical gradient-based FL method to a tree-based training technique is non-trivial, as ensembling trees and aggregating decision trees from different random forests across clients can be computationally, spatially, and temporally intensive. To overcome these challenges, this paper proposes FedRand, a novel adaptive Federated Random Forest Aggregation Learning Technique for Anomaly Detection in Internet of Things (IoT) networks. This paper thoroughly examines a suite of novel tree selection and aggregation strategies within a federated learning framework, ensuring robust model accuracy, accelerated aggregation, and global model convergence. We believe that this work opens up a promising solution for federated tree-based learning techniques
Natural aging-free Fe-Mn-Al-Ni-Mo single-crystal shape memory alloys via bifunctional Mo-segregation engineering
No full textFe-Mn-Al-Ni based shape memory alloys (SMAs) are able to exhibit
superelasticity in a wide range of temperatures, and their superelastic stresses are extremely low temperature dependent, which holds potential applications in inclement fields such as deep space. However, the difficulty in obtaining large single crystals and the shortcoming of natural aging in this alloy system are hindering their practical application. Based on this, an ultra-large Fe-Mn-Al-Ni-Mo single-crystal SMA with nearly zero natural aging effect was successfully fabricated in this work via bifunctional
Mo-segregation engineering. Firstly, at elevated temperatures, the grain boundary segregation of Mo atoms in this alloy effectively facilitated the abnormal grain growth during cyclic heat treatment. Based on this, a large-scale Fe-Mn-Al-Ni-Mo singlecrystal bar with a diameter of approximately 15.5 mm and a length of approximately 95 mm was obtained. Meanwhile, the Mo atoms with a low diffusion coefficient
effectively hindered the coarsening of coherent B2 nanoprecipitates during natural aging. This led to the Fe-Mn-Al-Ni-Mo single crystals close to [001] orientation to exhibit a huge superelastic strain of 8.5% even after 1.5 years of natural aging. In contrast, B2 nanoprecipitates in the Mo-free Fe-Mn-Al-Ni SMA grew from ~7.7 to ~10.1 nm after natural aging for 1.5 years. This study provides a unique insight into the development of high-performance functional alloys using elemental segregation
engineering
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