MRC Laboratory of Molecular Biology
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Towards a value stream perspective of circular business models
No full textCircular business models could minimise material input into and leakage out of the economic system and play an essential role in utilising the resources and capabilities of the private sector for the transition to more sustainable economic development. Despite the growing prominence of the Circular Business Model concept in research and practice, there is still considerable uncertainty on how to implement these new circular business models in existing global supply chains. Equivalent haziness also lies on the value streams it creates. To address this gap, a comprehensive literature review on “circular economy” and “business models” was conducted by employing content analysis with detailed code trees. The results led to several findings. First, we identified the key conceptual dimensions of circular business models, their theoretical approaches, drives and barriers, sustainability trade-offs amongst triple bottom-line perspectives and types, and value streams within circular business models and their ecosystems. Then, we designed conceptual mind maps to analyse the relationships between categories, illustrating the positive and negative interactions between key stakeholders. Finally, we proposed a circular business model framework that brings the novelty of connecting value streams within circular business models and their ecosystems. It allows the assessment of the positive and negative interactions between the circular business model building blocks in a systematic way
Rainfall Runoff and Dissolved Pollutant Transport Processes Over Idealized Urban Catchments
No full textUrban stormwater runoff is often considered as one of the most significant contributors to water pollution. Particulates are commonly regarded as the primary form of pollutant transport in the urban environment, but the contribution from the dissolved pollutants can also be significant. This study aims to investigate the dissolved pollutant transport process over urban catchments, especially the effects of buildings and spatial distribution of pollutants. The concept of “exchange layer” has been adopted and an equation has been proposed to describe the release process of dissolved pollutant from the exchange layer to the runoff water. A horizontal two-dimensional water flow and pollutant transport model has been developed for predicting dissolved pollutant runoff based on the shallow water assumptions and the advection-diffusion equation. A series of laboratory experiments have been conducted to verify the proposed model. It has been demonstrated that both the rainfall runoff and the pollutant runoff can be predicted accurately. Buildings slow down the runoff and pollutant transport processes, especially when buildings are staggered. The non-uniform distribution of pollutants over the catchment greatly influences the pollutant transport process over the catchment. This work provides insight into the effects of buildings and initial pollutant distribution on the dissolved pollutant transport phenomenon, which can help better design the pollution mitigation strategies
Generalised Eddy Dissipation Concept for MILD combustion regime at low local Reynolds and Damköhler numbers. Part 2: Validation of the model
No full textThe generalised Eddy Dissipation Concept (EDC) developed in the first part of this article is thoroughly validated against twelve flames from the Delft and Adelaide jet-in-hot-coflow (JHC) burners. These flames emulate Moderate or Intense Low Oxygen Dilution (MILD) conditions. Modelling of turbulence-chemistry interactions in this regime is a non trivial problem and many standard combustion models may fail. Recent Direct Numerical Simulation studies revealed a distributed appearance of the reaction zone indicating non-flamelet regime, which justified the use of reactor type modelling approaches. Those kind of models are of empirical nature and are sometimes criticized for being dependent on a number of tunable parameters. Also, most of new concepts are validated against a limited number of experiments. In this study, using the same modelling setup, twelve flames with different jet Reynolds number, level of oxidizer dilution with various fuel mixture were simulated. It turned out that the generalised EDC model considerably improved predictions with respect to the standard model for all the considered flames. Even though the predictions of the other EDC extensions provided better results in some regions, only the proposed generalised approach could cover the broad tange of operating conditions, proving its “universality” and reliability
How to guard against fixation? Demonstrating individual vulnerability is more effective than warning about general risk
No full textAbstract: Creative behaviour can be inhibited by fixation and so reducing fixation is a focus of much creativity research. One of the most common methods of tackling fixation is to warn people of fixation risks and instruct them to avoid constrained problem framing and solution search. However, such treatments are often ineffective. One possible explanation for this is that people typically believe that they (as individuals) are less vulnerable to a specified risk than other people are (in general). If we really want to motivate people to guard against a risk we need to demonstrate that they, as individuals, are vulnerable to those risks. To study the effect of demonstrating individual vulnerability to fixation, we conducted an online experimental study using number and word tasks that both included a fixation ‘trap’. The first task was used to provide a 'demonstrated vulnerability' treatment (revealing participants’ own fixated behaviour) to the experimental group. This group outperformed those who received a comparable ‘asserted vulnerability’ treatment (a warning about general fixation effects) and also those in a control group. Researchers and practitioners developing creativity training and tools aimed at reducing fixation effects should consider the benefits of demonstrating individual vulnerability to fixation rather than, or in combination with, issuing warnings that people in general are vulnerable to fixation
Gene regulatory network inference from sparsely sampled noisy data
No full textThe complexity of biological systems is encoded in gene regulatory networks. Unravelling this intricate web is a fundamental step in understanding the mechanisms of life and eventually developing efficient therapies to treat and cure diseases. The major obstacle in inferring gene regulatory networks is the lack of data. While time series data are nowadays widely available, they are typically noisy, with low sampling frequency and overall small number of samples. This paper develops a method called BINGO to specifically deal with these issues. Benchmarked with both real and simulated time-series data covering many different gene regulatory networks, BINGO clearly and consistently outperforms state-of-the-art methods. The novelty of BINGO lies in a nonparametric approach featuring statistical sampling of continuous gene expression profiles. BINGO’s superior performance and ease of use, even by non-specialists, make gene regulatory network inference available to any researcher, helping to decipher the complex mechanisms of life
Mitigating the impact of factories on the landscape: An assessment and design support tool
No full textBeing widely responsible for environmental degradation, industry represents a key asset to manage for a more sustainable and healthier living environment. However, factories affect more than just the physical sphere of the landscape, also impacting social and economic spheres as their intense perceptual-aesthetic interferences with the scenery can disturb neighbors and damage corporate images. In the recent past, policy-makers, practitioners and communities have demonstrated that the harmonization of industry with the landscape can produce several positive effects. In this framework, multicriteria systems to assess the impact have been developed, but they are mainly focused on reducing negative environmental effects rather than perceptual ones, while a holistic approach appears to be needed. Therefore, a method of analyzing how facilities interfere with the landscape is proposed, along with the development of a set of strategies to lessen detrimental effects on the physical, perceptual-aesthetic and social/cultural dimensions of the landscape. This paper presents the main outputs of the research, including the structure of the assessment system and a catalog of case studies selected for good design practices, from which general mitigation tactics have been retrieved. The result is a protocol composed of an assessment system and a design support tool available to companies and designers to be inspired by
(RE)BCO coated conductors with BHO exhibiting promising in-field critical current performance up to fields of 31.2 T: A significant step forward towards the development of all (RE)BCO large field magnets
No full textGeometric ergodicity in a weighted sobolev space
No full textFor a discrete-time Markov chain X = [X(t)] evolving on Rl with transition kernel P, natural, general conditions are developed under which the following are established: (i) The transition kernel P has a purely discrete spectrum, when viewed as a linear operator on a weighted Sobolev space L v,1∞ of functions with norm, ∥f ∥ v,1 = sup x∈Rl max [[pipe]f (x) [pipe], [pipe] ∂1f (x) [pipe],..., [pipe] ∂lf (x) [pipe] ], where v: Rl →[1, ∞) is a Lyapunov function and ∂i:= ∂/∂xi. (ii) The Markov chain is geometrically ergodic in L v,1∞: There is a unique invariant probability measure π and constants B 0 such that, for each f ∈ L v,1∞, any initial condition X(0) = x, and all t ≥ 0: [pipe] Ex [f (X(t))]-π(f) [pipe] ≤ B∥f ∥ v,1e -δt v(x), ∥∇Ex [f (X(t))]∥ 2 ≤ B∥f ∥ v,1e -δt v(x), where π(f) = ∫ f dπ. (iii) For any function f ∈ L v,1∞ there is a function h ∈ L v,1∞ solving Poisson's equation: h-Ph = f-π(f). Part of the analysis is based on an operator-theoretic treatment of the sensitivity process that appears in the theory of Lyapunov exponents. Relationships with topological coupling, in terms of the Wasserstein metric, are also explored
Multi-objective optimal power flow solutions using a constraint handling technique of evolutionary algorithms
No full textIn power systems, optimal power flow (OPF) is a complex and constrained optimization problem in which quite often multiple and conflicting objectives are required to be optimized. The traditional way of dealing with multi-objective OPF (MOOPF) is the weighted sum method which converts the multi-objective OPF into a single-objective problem and provides a single solution from the set of Pareto solutions. This paper presents MOOPF study applying multi-objective evolutionary algorithm based on decomposition (MOEA/D) where a set of non-dominated solutions (Pareto solutions) can be obtained in a single run of the algorithm. OPF is formulated with two or more objectives among fuel (generation) cost, emission, power loss and voltage deviation. The other important aspect in OPF problem is about satisfying power system constraints. As the search process adopted by evolutionary algorithms is unconstrained, for a constrained optimization problem like OPF, static penalty function approach has been extensively employed to discard infeasible solutions. This approach requires selection of a suitable penalty coefficient, largely done by trial-and-error, and an improper selection may often lead to violation of system constraints. In this paper, an effective constraint handling method, superiority of feasible solutions (SF), is used in conjunction with MOEA/D to handle network constraints in MOOPF study. The algorithm MOEA/D-SF is applied to standard IEEE 30-bus and IEEE 57-bus test systems. Simulation results are analyzed, especially for constraint violation and compared with recently reported results on OPF
Neutron clustering as a driver of Monte Carlo burn-up instability
No full textCoupled Monte Carlo neutronics and depletion problems have been noted to produce non-physical power oscillations for large, spatially-decoupled problems. Previously these oscillations have been attributed to ‘numerical instability’ – this work proposes that a prominent contributor to this phenomenon is neutron clustering during the Monte Carlo simulation, resulting in a poor estimate of the transport solution. This is demonstrated using insights from recent work on clustering and applying it to standard practice for Monte Carlo/depletion problems by performing simulations with the same number of histories – both total histories and only active histories – but different numbers of particles and cycles. The results demonstrate that neutron clustering appears to trigger instabilities in the problems considered and strongly affects Monte Carlo neutronics/depletion simulations