157082 research outputs found
Sort by
Mean stability and between-session reliability of cycling biomechanics variables in elite pursuit cyclists
No full textThe purpose of this study was to determine the number of crank revolutions required to obtain stable mean values of sagittal plane biomechanics variables, and the between-session reliability of these variables, whilst cyclists used an aerodynamic position. Eighteen elite cyclists completed a 3-min maximal bout on a cycling ergometer. Lower-limb kinematic and kinetic data were captured using 2D motion capture and force pedals. Raw data were filtered using a 4th order Butterworth low-pass filter (6 hz) and interpolated to 100 points per revolution. The middle 60 revolutions of each trial were extracted and 37 discrete and 15 time-series variables were calculated. Mean stability was assessed in all participants, and between-session reliability was analysed in a subset of 11 participants. Sequential averaging indicated more revolutions to stability than iterative intra-class correlation coefficients. Crank kinetics were more stable than joint kinematics and kinetics. For stable discrete and time-series variables, 30 and 38 revolutions are recommended, respectively. Between-day reliability for all variables was moderate to excellent, and good to excellent for crank kinetics and joint kinematics variables. Hip flexion-extension and ankle dorsiflexion kinetics were least reliable. Researchers and applied practitioners should consider these findings when planning, and interpreting results from, cycling biomechanics interventions
High-contrast random systems of PDEs: Homogenization and spectral theory
No full textWe develop a qualitative homogenization and spectral theory for elliptic systems of partial differential equations in divergence form with highly contrasting (i.e. non-uniformly elliptic) random coefficients. The focus of this paper is on the behavior of the spectrum as the heterogeneity parameter tends to zero; in particular, we show that in general one does not have Hausdorff convergence of spectra. The theoretical analysis is complemented by several explicit examples, showcasing the wider range of applications and physical effects of systems with random coefficients, when compared with systems with periodic coefficients or with scalar operators (both random and periodic)
Ordering groups and the Identity Problem
No full textThe Identity Problem — deciding if the subsemigroup generated by a given finite set of elements of a group contains the identity element — is shown in this paper to correspond, for certain classes, to decision problems about ordering groups. Notably, the Identity Problem for a torsion-free nilpotent group corresponds both to the problem of deciding if a given finite set of elements extends to the positive cone of a left-order on the group, and to the Word Problem for a related lattice-ordered group.A new (independent) proof is given of the decidability of the Identity and Subgroup Problems for every finitely presented nilpotent group (initially proved by Shafrir in 2024), establishing also the decidability of the Word Problem for a family of lattice-ordered groups. In contrast, it is shown that the related Fixed-Target Submonoid Membership Problem is undecidable in nilpotent groups.Decidability of the Normal Identity Problem (with ‘subsemigroup’ replaced by ‘normal subsemigroup’) for free nilpotent groups is established using the (known) decidability of the Word Problem for certain lattice-ordered groups. Connections between orderability and the Identity Problem for a class of torsion-free metabelian groups are also explored
Design-of-experiments based Modeling & Optimization of LGA Cooling Crystallization via Continuous Oscillatory Baffled Crystallizer
No full textA novel data-driven modeling and optimization method is proposed in this paper for cooling crystallization of L-glutamic acid (LGA) via a continuous oscillatory baffled crystallizer (COBC), based on the design of experiments (DoEs) for the main operating conditions of zone temperature setting and volume net flowrate. The crystal size distribution (CSD) can be effectively predicted by constructing a data-mapping model with double-layer basis functions, where the first layer is composed of wavelet basis functions for reshaping the steady-state CSD in each operating zone of COBC, and the second layer consists of polynomial basis functions for reflecting the nonlinear relationship between the above operating conditions and the corresponding CSD in each zone. Furthermore, a comprehensive cost function related to the desired crystal size, the distribution variance of product crystals and throughput is introduced to design an optimization method for the above operating conditions. A guaranteed convergence particle swarm optimization (GCPSO) algorithm is offered to solve the nonconvex optimization problem based on the established CSD prediction model. Experimental results on the continuous crystallization of LGA demonstrate that the above cost function and the desired crystal product yield can be improved over 23% and 9%, respectively, in comparison with all tests by DoEs
Follow Me:A Study on the Dynamics of Alignment Between Humans and LLM-Based Social Robots
No full textWhile robots are perceived as reliable in delivering factual data, their ability to achieve meaningful alignment with humans during subjective interactions remains unclear. Gaining insights into this alignment is vital to integrating robots more deeply into decision-making frameworks and enhancing their roles in social interactions. This study examines the impact of personality-prompted large language models (LLMs) on alignment in human-robot interactions. Participants interacted with a Furhat robot under two conditions: a baseline control condition and an experimental condition using personality prompts designed to simulate distinct personality traits through the LLM. Alignment was assessed by measuring changes in similarity between participants’ rankings and the robot’s rankings of factual (objective) and contestable (subjective) concepts before and after interaction. The findings indicate that participants aligned more with the robot on objective, factual concepts than on subjective, contestable ones, regardless of personality prompts. These results suggest that the current personality prompting method may be insufficient to significantly influence alignment in subjective interactions. This may be attributed to the conveyed traits lacking sufficient impact or the limitations of current system capabilities, which may not yet be advanced enough to foster the desired influence on participants’ perceptions.</p
Storage v. production: challenges for reservoir modelling and simulation practitioners
No full textThe rising interest in subsurface CO2 storage makes new calls on reservoir modelling skills, most of which have been developed for hydrocarbon production scenarios. The question for practitioners is: to what extent can the familiar production tools be transferred to the world of storage? In this paper, areas requiring attention are highlighted and high-resolution models are used to compare the behaviour of simulators for production v. storage for two reservoir analogue examples. It is concluded that modelling for storage makes a significant call on multi-scale modelling, to a much greater extent than in production scenarios, and the simplification or omission of reservoir heterogeneities (sometimes tolerable in production scenarios) are much less tolerable when modelling storage. Key static model heterogeneities include the modelling of faults as 3D features, the inclusion of fine-scale reservoir permeability contrasts and the avoidance of net reservoir cut-offs. For dynamic models, use of equation of state is necessary for storage in depleted fields, and correct representation of hysteretic effects of plume migration are a requirement for modelling in aquifers (always) and depleted fields (usually). Modelling for storage, especially for saline aquifers, sets the challenge of modelling volumes previously considered to be at exploration scale, but with an effective resolution more typical of production scales
Direct Quantification of Coal Pore Dynamics during Methane Depletion via Low-Field Nuclear Magnetic Resonance
No full textThis study presents a novel low-field nuclear magnetic resonance (LF-NMR) framework to directly quantify sorption-induced pore strain and pore compressibility in coal reservoirs and thereby provides key parameters for predicting permeability during coalbed methane (CBM) production. Three coal samples of varying ranks (high-, middle-, and low-rank) were subjected to controlled methane adsorption/desorption and confining stress experiments under constant effective stress. By correlating transverse relaxation time (T2) spectra with methane phase dynamics, we resolved adsorbed gas (micropores) and free gas (mesopores, macropores, fractures) contributions, enabling real-time tracking of pore deformation. Analysis on the measurements reveals that the sorption-induced pore volumetric strain displays a linear relationship with adsorption gas content, ranging from 0.0108 to 0.0613 g·cm–3; the range of pore compressibility variation was calculated using an exponential relationship between transport pore volume and effective stress, and it ranges from 0.0509 to 0.0902 MPa–1. These two factors directly characterize the volumetric strain of the methane transport space within the coal reservoir, providing a direct, assumption-free approach to characterize pore-scale mechanics, particularly for heterogeneous coal reservoirs
Interference Mitigation in Multibeam Satellite Networks as an Optimal Sublattice Problem
No full textResource distribution in radio networks aims at maximizing spectrum utilization while minimizing interference. In this paper, we consider the problem of uniform radio resource distribution on a periodic grid. We formulate the problem as finding the sublattice configuration that maximises the distance between adjacent resources, crucial for reducing interference and improving throughput performance. Leveraging concepts from lattice theory and discrete geometry, we present an enumerative, parallelizable algorithm to explore all possible sublattices and efficiently identify the optimal configurations. Additionally, we investigate the existence and properties of scaled-rotated sublattices, exploring how different lattice geometries impact optimal solutions. Numerical results demonstrate the effectiveness of the proposed algorithm and highlight insights into optimal sublattice design for various lattice structures. Furthermore, the results are applied to the identification of the beam layout in a fixed multibeam geostationary satellite. Numerical results show that the spectral efficiency of the optimised sublattice is higher than all other sublattices. This work thus advances the field of radio resource distribution and offers practical implications for improving satellite network performance
Integrating molecular pathogenesis and predictive modelling in granulomatous amoebic encephalitis due to Acanthamoeba: a digital twin framework for personalised therapy
No full textHigh Moisture Extrusion Based Texturization and Functional Modulation of Pea Protein Isolate through Integration with Cultivated Beef
No full textThe increasing global demand for meat can be sustainably leveraged by alternative protein, but the inferior quality of current plant-based meat analogues has somewhat disillusioned consumers. Small inclusion level of cultivated beef (CB) to bulk pea protein isolate in the high moisture extrusion (HME) showed a process unlock how to modulate the texture and instrumental sensory properties of the hybrid pea protein extrudates. Such novel co-extrusion delivered improved physicochemical and flavour properties as well as imparted distinct change in texture and microstructure. A comparison between hybrid pea protein extrudates with 10% CB (E-PCB10) and 2% CB (E-PCB2) showed a clear enhancement of the water holding (∼16.7-fold) and oil holding (∼67-fold) capacities in E-CPB10 and the instrumental sensory analyses also showed up to 30% reduction of key off-flavour markers of pea protein in E-PCB10 along with reduction in bitterness and astringency. E-PCB10 and E-PCB2 exhibit different microstructure compared to E-PPI, and E-PCB10 showed increased hardness, resilience, cohesiveness and chewiness as well as the mechanical strength. The scanning electron microscopy of extrudates revealed that higher concentrations of cultivated beef disrupted the pea protein matrix and the laminar structure in E-PPI becomes less easy to discern in E-PCB2 and E-PCB10. The increasing percentage of CB leads to a more enhanced protein-protein cross-linking in E-PCB10. These findings demonstrated for the first time that an addition of as little as 2% and 10% of cultivated beef can modulate the texture and microstructure of pea protein extrudate. This could lead to a promising texturization process for plant protein via microstructure modulation, reducing off-taste, and enhancing functional features to develop high-quality, hybrid alternative protein-based meat analogue
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!