Solution of the Unanimity Rule on exponential, uniform and scalefree networks: A simple model for biodiversity collapse in foodwebs

We solve the Unanimity Rule on networks with exponential, uniform and scalefree degree distributions. In particular we arrive at equations relating the asymptotic number of nodes in one of two states to the initial fraction of nodes in this state. The solutions for exponential and uniform networks are exact, the approximation for the scalefree case is in perfect agreement with simulation results. We use these solutions to provide a theoretical understanding for experimental data on biodiversity loss in foodwebs, which is available for the three network types discussed. The model allows in principle to estimate the critical value of species that have to be removed from the system to induce its complete collapse.Comment: 4 pages, 3 fig

Understanding rate sensitivity in dual phase titanium alloys – a combined experimental and computational micro-pillar study

Titanium alloys are used as structural load bearing components in aeroengines. In service, these alloys are subjected to significant cyclic loading, with high thrust (i.e. stress) excursions during take-off, a load-hold during flight and unloading on landing. The load-hold has been shown to have a significant effect on the fatigue life performance of many dual phase titanium alloys, where a significant hold at maximum load can reduce the number of cycles to failure by an order of magnitude or more when compared with simple ‘saw-tooth’ load-unload fatigue cycle. This is known as the dwell debit. Recently, it has been demonstrated that failure is dominated by local microstructure in these alloys, including the presence of a rogue grain combination. During the load-hold, stress is shed from a ‘hard’ grain to a neighbour ‘soft’ grain and local regions of very high stress form [1]. Time dependent stress amplification at local microstructural regions during this load shedding process near the interface is thought to play a prominent role in facet formation. In practice this effect is mitigated by use of dwell insensitive alloys and careful maintenance schedules but management of this phenomena costs the aerospace industry significantly (~£100ms / year). The motivation of this study is to understand the dwell process and in particular to characterise fundamental mechanisms within dwell sensitive Ti-6Al-2Sn-4Zr-2Mo and dwell insensitive Ti-6Al-2Sn-4Zr-6Mo alloys [2]. These alloys have complex dual phase (alpha-HCP and beta-BCC) microstructures that make interpretation of large scale experimental macro-mechanical test specimens especially complicated. We have chosen to fabricate ‘simple’ single colony micro-pillars (~2μm in width and ~5μm in height) containing different internal microstructures of pure-alpha phase and mixed alpha+beta phase of particular crystallographic orientations to trigger (near-) single slip in ~uniaxial deformation. These micro-pillars have been tested in an Alemnis displacement controlled nanoindentation system within the SEM. Tests have been performed with variable strain rates and load-relaxation tests to extract out rate sensitivities of the different slip systems and to understand the role of the alpha and beta phases and local interfaces. To complement and aid interpretation of these tests we have performed crystal plasticity finite element modelling (CP-FEM), with the aim of gaining physical insight into these important micro-mechanical mechanisms. We will present our combined measurements of the different rate sensitivities of these individual slip systems in these alloys. These studies are performed within the EPSRC HexMat consortium (www.imperial.ac.uk/hexmat, EP/K034332/1) with the express aim of understanding component level performance in hexagonal alloys

Classification of the conditionally observable spectra exhibiting central symmetry

We show how in PT-symmetric 2J-level quantum systems the assumption of an upside-down symmetry (or duality) of their spectra simplifies their classification based on the non-equivalent pairwise mergers of the energy levels.Comment: 10 pp. 3 figure

Twinning anisotropy of tantalum during nanoindentation.

Unlike other BCC metals, the plastic deformation of nanocrystalline Tantalum (Ta) during compression is regulated by deformation twinning. Whether or not this twinning exhibits anisotropy was investigated through simulation of displacement-controlled nanoindentation test using molecular dynamics (MD) simulation. MD data was found to correlate well with the experimental data in terms of surface topography and hardness measurements. The mechanism of the transport of material was identified due to the formation and motion of prismatic dislocations loops (edge dislocations) belonging to the 1/2 (111) type and (100) type Burgers vector family. Further analysis of crystal defects using a fully automated dislocation extraction algorithm (DXA) illuminated formation and migration of twin boundaries on the (110) and (111) orientation but not on the (010) orientation and most importantly after retraction all the dislocations disappeared on the (110) orientation suggesting twinning to dominate dislocation nucleation in driving plasticity in tantalum. A significant finding was that the maximum shear stress (critical Tresca stress) in the deformation zone exceeded the theoretical shear strength of Ta (Shear modulus/2. π~10.03. GPa) on the (010) orientation but was lower than it on the (110) and the (111) orientations. In light of this, the conventional lore of assuming the maximum shear stress being 0.465 times the mean contact pressure was found to break down at atomic scale

From micro-cantilever testing to deformation patterning in HCP polycrystals

For several years now we have been using micro-scale cantilever bend tests to probe the considerable anisotropy of elastic and plastic deformation behaviour in the hexagonal packed metals Ti and Zr [1-3]. The wider aim of the work has been understanding and modeling the heterogeneous patterns of stress, strain and dislocation density that develop during deformation of HCP polycrystals. Crystal plasticity finite element analysis (CP-FEA) of representative volumes are used to simulate these deformation fields and enable modelling of representative volume elements to aid understanding of in-service component performance. Critical resolved shear stress (CRSS) values for the important slip systems are required inputs for the constitutive laws and populating these has been the aim of our micro-cantilever studies. We follow a well-established route of using a focused ion beam (FIB) to machine micro-cantilevers of triangular cross-section into the sample surface [1]. EBSD is used to identify grains in which cantilevers with suitable orientation can be cut so that the targeted slip systems can be activated individually. The samples are then passed to a nano-indenter with a nano-positioning stage and loaded, with the load point accurately located at the free end of the cantilever using an AFM-like scan with low contact force. Load-displacement data generated from the experiment are compared to CP-FEA simulations of the cantilever bending and the CRSS for each cantilever is varied until a good fit is achieved [1]. The CRSS data show a significant size effect, where smaller cantilevers are apparently stronger. This is very obvious at cantilever widths below ~5 µm but also persists to larger sizes. The size effect is found to be well represented by where is the effective CRSS measured for a cantilever of width , is the CRSS for bulk samples and is a constant representing the strength of the size effect [2]. During bending strains are largest near the built-in end at the top (tensile) and bottom (compressive) regions (twice as large at the bottom due to the orientation of the triangular section). Dislocations tend to be generated in these regions and propagate progressively in towards the neutral axis of the beam where they pile-up. The back-stress from these pile-ups acts against further dislocations being generated and moving to join the pile-up. This effect is seen in discrete dislocation plasticity simulations that inherently capture the size effect [3], but are not present in the length scale independent CP-FEA simulations, where the size effect is manifested instead as an apparent increase in CRSS for smaller cantilever width. This pile-up effect has been confirmed with post-mortem TEM observations of the dislocation pile-ups in Ti alloys [4,5]. Examples of cantilever studies in Ti and Zr alloys will be shown. We will also demonstrate that this approach generates CRSS values which allow the bulk flow stresses of macroscopic polycrystal aggregates to be determined, so enabling micromechanical studies to inform component level performance of industrial alloys [6]

Improving measurement of child abuse and neglect: a systematic review and analysis of national prevalence studies

Child maltreatment through physical abuse, sexual abuse, emotional abuse, neglect, and exposure to domestic violence, causes substantial adverse health, educational and behavioural consequences through the lifespan. The generation of reliable data on the prevalence and characteristics of child maltreatment in nationwide populations is essential to plan and evaluate public health interventions to reduce maltreatment. Measurement of child maltreatment must overcome numerous methodological challenges. Little is known to date about the extent, nature and methodological quality of these national studies. This study aimed to systematically review the most comprehensive national studies of the prevalence of child maltreatment, and critically appraise their methodologies to help inform the design of future studies

‘Can biomimetic principles coupled with advanced fabrication technologies and stimuli-responsive materials drive revolutionary advances in wearable and implantable biochemical sensors?’

Since the initial breakthroughs in the 1960’s and 70’s that led to the development of the glucose biosensor, the oxygen electrode, ion-selective electrodes, and electrochemical/optochemical diagnostic devices, the vision of very reliable, affordable chemical sensors and bio-sensors capable of functioning autonomously for long periods of time (years), and providing access to continuous streams of real-time data remains unrealized. This is despite massive investment in research and the publication of many thousands of papers in the literature. It is over 40 years since the first papers proposing the concept of the artificial pancreas, by combining the glucose electrode with an insulin pump. Yet even now, there is no chemical sensor/biosensor that can function reliably inside the body for more than a few days, and such is the gap in what can be delivered (days), and what is required (minimum 10 years) for implantable devices, it is not surprising that in health diagnostics, the overwhelmingly dominant paradigm for reliable measurements is single use disposable sensors. Realising disruptive improvements in chem/bio-sensing platforms capable of long-term (months, years) independent operation requires a step-back and rethinking of strategies, and considering solutions suggested by nature, rather than incremental improvements in available technologies

Complex model calibration through emulation, a worked example for a stochastic epidemic model

Uncertainty quantification is a formal paradigm of statistical estimation that aims to account for all uncertainties inherent in the modelling process of real-world complex systems. The methods are directly applicable to stochastic models in epidemiology, however they have thus far not been widely used in this context. In this paper, we provide a tutorial on uncertainty quantification of stochastic epidemic models, aiming to facilitate the use of the uncertainty quantification paradigm for practitioners with other complex stochastic simulators of applied systems. We provide a formal workflow including the important decisions and considerations that need to be taken, and illustrate the methods over a simple stochastic epidemic model of UK SARS-CoV-2 transmission and patient outcome. We also present new approaches to visualisation of outputs from sensitivity analyses and uncertainty quantification more generally in high input and/or output dimensions

Next generation autonomous sensing platforms based on biomimetic principles

Imagine a world in which issues related to long-term (months to years) reliability of chem/bio-sensing platforms have been solved, and devices capable of carrying out complex chem/bio-functions in an autonomous manner are ubiquitously available. The potential impact of these technologies socially and economically is enormous, and the demand will be universal, driven by an infinite range of applications. Devices will perform complex analytical measurements while located in remote and environmentally hostile locations, such as the deep oceans, or inside the human body. Their capabilities will go far beyond those of existing devices; chemical sensors, biosensors, lab-on-chip (LOC) systems or autonomous analysers, that cannot deliver the price-performance required for reliable long-term (years) autonomous in-situ operation. Revolutionary device improvements are required to meet this vision, and it is becoming clear that these improvements require a fundamental move towards devices based on bio-inspired approaches. For example, future instrument fluidics will have a much more active role beyond the current tasks of transporting samples, mixing reagents, and cleaning. Much like the circulation systems in living entities, these circulation systems will perform advanced functions, like using mobile micro-scaled biomimetic agents to detect, spontaneously migrate to, and repair damaged channels or fluidic components in order to maintain functional integrity of the device. These strategies, if successful, will be broadly disruptive across many application domains, from chronic disease management to environmental monitoring. In this paper, I will present ideas and strategies through which this exciting vision might be advanced via an exciting combination of stimuli-responsive materials, emerging technologies for precise control of 3D materials morphology (to nanoscale dimensions), and state of the art characterization and visualization techniques

From molecules to devices: can we create disruptive technologies based on 3D functionality at multiple dimensions to solve global challenges?

Since the initial breakthroughs in the 1960’s and 70’s that led to the development of the glucose biosensor, the oxygen electrode, ion-selective electrodes, and electrochemical/optochemical diagnostic devices, the vision of very reliable, affordable chemical sensors and bio-sensors capable of functioning autonomously for long periods of time (years), and providing access to continuous streams of real-time data remains unrealized. This is despite massive investment in research and the publication of many thousands of papers in the literature. It is over 40 years since the first papers proposing the concept of the artificial pancreas, by combining the glucose electrode with an insulin pump. Yet even now, there is no chemical sensor/biosensor that can function reliably inside the body for more than a few days, and such is the gap in what can be delivered (days), and what is required (minimum 10 years) for implantable devices, it is not surprising that in health diagnostics, the overwhelmingly dominant paradigm for reliable measurements is single use disposable sensors. Realising disruptive improvements in chem/bio-sensing platforms capable of long-term (months, years) independent operation requires a step-back and rethinking of strategies, and considering solutions suggested by nature, rather than incremental improvements in available technologies. Through developments in 3D fabrication technologies in recent years, we can now build and characterize much more sophisticated 3D platforms than was previously possible. Furthermore also we can use hybrid materials – mixtures of organic and inorganic materials, create regions of differing polarity and hydrophobicity, mix passive and binding behaviours, regions of differing flexibility/rigidity, hardness/softness. In addition, we can integrate materials that can switch between these characteristics – selecting when and where these behaviours exist. In this talk, I will present a series of examples of biomimetic microfluidic building blocks that exhibit photoswitchable characteristics such as programmed microvehicle movement (chemotaxis), switchable binding and release, switchable actuation (e.g. valving), and photodetection. These building blocks can be in turn integrated into microfluidic systems with hitherto unsurpassed functionalities that can contribute to bridging the gap between what is required for many applications, and what we can currently deliver. These disruptive advances should open the way to long-term implantable devices that can monitor, report and assist the management of an individual’s personal health. A key development will be the integration of self-diagnosis and self-repair capabilities to extend their useful lifetime