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This chapter introduces detailed mathematical modelling for diffusion-based molecular communication systems. Mathematical and physical aspects of diffusion are covered, such as the Wiener process, drift, first arrival time distributions, the effect of concentration, and Fick’s laws. Simulation of molecular communication systems is also discussed.
This chapter introduces detailed mathematical modelling for biological molecular communication systems, particularly for ligand–receptor systems. Models for chemical kinetics are introduced, including the master equation, and these are applied to membrane ion channels. Simulation of these systems is also discussed.
We model the slip length tribometer (SLT), originally presented by Pelz et al. (J. Fluid Mech., vol. 948, 2022, p. A8) in OpenFOAM. The plate tribometer is especially designed to simultaneously measure viscosity and slip length for lubrication gaps in the range of approximately 10 $\mathrm {\mu }$m at temperatures and surface roughnesses relevant to technical applications, with a temperature range of $-30$ to $100\,^\circ \mathrm {C}$ and surface roughness ranging from $10\ \mathrm {nm}$ to $1\ \mathrm {\mu }\mathrm {m}$. A simplified analytical model presented by Pelz et al. (J. Fluid Mech., vol. 948, 2022, p. A8) infers the slip length of the plate from the experimentally measured torque and the plate gap height. The present work verifies the analytical model using axisymmetric flow simulations and presents the effect of inlet on the numerical velocity profiles. The simulation results are in very good agreement with the results of the analytical model. The main conclusion drawn from this study is the validation of the Navier-slip boundary condition as an effective model for partial slip in computational fluid dynamics simulations and the negligible influence of the inlet on the fluid flow between the SLT's plates.
Anthrax is a bacterial zoonotic disease caused by Bacillus anthracis. We qualitatively examined facilitators and barriers to responding to a potential anthrax outbreak using the capability, opportunity, motivation behaviour model (COM-B model) in the high-risk rural district of Namisindwa, in Eastern Uganda. We chose the COM-B model because it provides a systematic approach for selecting evidence-based techniques and approaches for promoting the behavioural prompt response to anthrax outbreaks. Unpacking these facilitators and barriers enables the leaders and community members to understand existing resources and gaps so that they can leverage them for future anthrax outbreaks.
This was a qualitative cross-sectional study that was part of a bigger anthrax outbreak simulation study conducted in September 2023. We conducted 10 Key Informant interviews among key stakeholders. The interviews were audio recorded on Android-enabled phones and later transcribed verbatim. The transcripts were analyzed using a deductive thematic content approach through Nvivo 12.
The facilitators were; knowledge of respondents about anthrax disease and anthrax outbreak response, experience and presence of surveillance guidelines, availability of resources, and presence of communication channels. The identified barriers were; porous boarders that facilitate unregulated animal trade across, lack of essential personal protective equipment, and lack of funds for surveillance and response activities.
Generally, the district was partially ready for the next anthrax outbreak. The district was resourced in terms of human resources but lacked adequate funds for animal, environmental and human surveillance activities for anthrax and related response. The district technical staff had the knowledge required to respond to the anthrax outbreak but lacked adequate funds for animal, environmental and human surveillance for anthrax and related response. We think that our study findings are generalizable in similar settings and therefore call for the implementation of such periodic evaluations to help leverage the strong areas and improve other aspects. Anthrax is a growing threat in the region, and there should be proactive efforts in prevention, specifically, we recommend vaccination of livestock and further research for human vaccines.
Conceptual models of smectite hydration include planar (flat) clay layers that undergo stepwise expansion as successive monolayers of water molecules fill the interlayer regions. However, X-ray diffraction (XRD) studies indicate the presence of interstratified hydration states, suggesting non-uniform interlayer hydration in smectites. Additionally, recent theoretical studies have shown that clay layers can adopt bent configurations over nanometer-scale lateral dimensions with minimal effect on mechanical properties. Therefore, in this study we used molecular simulations to evaluate structural properties and water adsorption isotherms for montmorillonite models composed of bent clay layers in mixed hydration states. Results are compared with models consisting of planar clay layers with interstratified hydration states (e.g. 1W–2W). The small degree of bending in these models (up to 1.5 Å of vertical displacement over a 1.3 nm lateral dimension) had little or no effect on bond lengths and angle distributions within the clay layers. Except for models that included dry states, porosities and simulated water adsorption isotherms were nearly identical for bent or flat clay layers with the same averaged layer spacing. Similar agreement was seen with Na- and Ca-exchanged clays. While the small bent models did not retain their configurations during unconstrained molecular dynamics simulation with flexible clay layers, we show that bent structures are stable at much larger length scales by simulating a 41.6×7.1 nm2 system that included dehydrated and hydrated regions in the same interlayer.
Using tools from computable analysis, we develop a notion of effectiveness for general dynamical systems as those group actions on arbitrary spaces that contain a computable representative in their topological conjugacy class. Most natural systems one can think of are effective in this sense, including some group rotations, affine actions on the torus and finitely presented algebraic actions. We show that for finitely generated and recursively presented groups, every effective dynamical system is the topological factor of a computable action on an effectively closed subset of the Cantor space. We then apply this result to extend the simulation results available in the literature beyond zero-dimensional spaces. In particular, we show that for a large class of groups, many of these natural actions are topological factors of subshifts of finite type.
This article examines two major recent CCTV documentaries on the Third Front and its afterlives. The Big Third Front (2017) and Vicissitudes of the Third Front (2016) construct strong narratives about the Third Front during the Mao era, depicting it as a heroic struggle against nature which was forced upon China by foreign enemies. However, both documentaries encounter difficulties in adhering to the usual presentation of the Deng era as a resoundingly successful transformation. Vicissitudes ambivalently characterizes the Deng era as one of relative decline in contrast to the glorious early years of the Third Front and the flourishing present. The Big Third Front, meanwhile, conflates historical footage of the 1950s–1990s in a way that undermines the usual official division of PRC history into Mao and reform eras. This paper concludes by suggesting that academic focus on the Third Front can serve as a methodological tool for complicating the periodization of PRC history.
Open rotors can play a critical role towards transitioning to a more sustainable aviation by providing a fuel-efficient alternative. This paper considers the sensitivity of an open-rotor engine to variations of three operational parameters during take-off, focusing on both aerodynamics and aeroacoustics. Via a sensitivity analysis, insights to the complex interactions of aerodynamics and aeroacoustics can be gained. For both the aerodynamics and aeroacoustics of the engine, numerical methods have been implemented. Namely, the flowfield has been solved using unsteady Reynolds Averaged Navier Stokes and the acoustic footprint of the engine has been quantified through the Ffowcs Williams-Hawking equations. The analysis has concluded that the aerodynamic performance of the open rotor can decisively be impacted by small variations of the operational parameters. Specifically, blade loading increased by 9.8% for a 5% decrease in inlet total temperature with the uncertainty being amplified through the engine. In comparison, the aeroacoustic footprint of the engine had more moderate variations, with the overall sound pressure level increasing by up to 2.4dB for a microphone lying on the engine axis and aft of the inlet. The results signify that there is considerable sensitivity in the model and shall be systematically examined during the design or optimisation process.
Conducting clinical trials is often complex and involves many individuals from a variety of services, each with a specific role in ensuring its successful implementation. Although an experienced clinical trialist may anticipate many of the challenges, others may be unexpected and detrimental to the successful completion of a study. We describe the use of simulation during preparation for initiation of a randomized clinical trial of a new preparation of antiseizure medication in neonates with seizures. The process of identification of stakeholders and roles, scenario development, and identification of challenges are described. Lessons learned included the potential benefits of simulation exercises, simulation challenges, and challenges associated with the study itself. We posit that going through the steps of a study, rather than merely reading them from a manual of procedures, will help identify potential barriers, complexities, and contingencies that are not readily apparent and may result in fewer protocol deviations and violations.
In research environments and laboratories e.g. for material sciences the in- and output of simulation data is manually managed. Therefore, physical experiments as well as simulations might be carried out several times, learnings are not systematically gathered, and experiments do not systematically build on learnings from data. This paper proposes to engage an ontology in conjunction with a simulation to use data from already carried out experiments and on that basis predict material behaviour under certain condition and plan further physical experiments.
The Earth’s radiation balances are being altered by a number of changes in the composition of the atmosphere, and as a consequence the climate system is being ‘forced’, almost certainly in the direction of higher temperatures. In earlier chapters we examined the physics of the processes involved. What are likely to be the effects of such changes? The only way to answer questions such as this is to model the Climate System in sufficient detail. Firstly, we need to model the atmosphere, something we have been doing for half a century to forecast the weather. Because of the significant exchanges of both heat and water between the ocean and the atmosphere, it is clearly necessary to couple an ocean model. Ice sheets are likely to be affected by warming, as they are one of the key feedback processes just mentioned. The land surface also has significant interactions on various timescales.
Critical CHD is associated with morbidity and mortality, worsened by delayed diagnosis. Paediatric residents are front-line clinicians, yet identification of congenital CHD remains challenging. Current exposure to cardiology is limited in paediatric resident education. We evaluated the impact of rapid cycle deliberate practice simulation on paediatric residents’ skills, knowledge, and perceived competence to recognise and manage infants with congenital CHD.
Methods:
We conducted a 6-month pilot study. Interns rotating in paediatric cardiology completed a case scenario assessment during weeks 1 and 4 and participated in paired simulations (traditional debrief and rapid cycle deliberate practice) in weeks 2–4. We assessed interns’ skills during the simulation using a checklist of “cannot miss” tasks. In week 4, they completed a retrospective pre-post knowledge-based survey. We analysed the data using summary statistics and mixed effect linear regression.
Results:
A total of 26 interns participated. There was a significant increase in case scenario assessment scores between weeks 1 and 4 (4, interquartile range 3–6 versus 8, interquartile range 6–10; p-value < 0.0001). The percentage of “cannot miss” tasks on the simulation checklist increased from weeks 2 to 3 (73% versus 83%, p-value 0.0263) and from weeks 2–4 (73% versus 92%, p-value 0.0025). The retrospective pre-post survey scores also increased (1.67, interquartile range 1.33–2.17 versus 3.83, interquartile range 3.17–4; p-value < 0.0001).
Conclusion:
Rapid cycle deliberate practice simulations resulted in improved recognition and initiation of treatment of simulated infants with congenital CHD among paediatric interns. Future studies will include full implementation of the curriculum and knowledge retention work.
Collecting network data directly from network members can be challenging. One alternative involves inferring a network from observed groups, for example, inferring a network of scientific collaboration from researchers’ observed paper authorships. In this paper, I explore when an unobserved undirected network of interest can accurately be inferred from observed groups. The analysis uses simulations to experimentally manipulate the structure of the unobserved network to be inferred, the number of groups observed, the extent to which the observed groups correspond to cliques in the unobserved network, and the method used to draw inferences. I find that when a small number of groups are observed, an unobserved network can be accurately inferred using a simple unweighted two-mode projection, provided that each group’s membership closely corresponds to a clique in the unobserved network. In contrast, when a large number of groups are observed, an unobserved network can be accurately inferred using a statistical backbone extraction model, even if the groups’ memberships are mostly random. These findings offer guidance for researchers seeking to indirectly measure a network of interest using observations of groups.
This rather long chapter constitutes part of the hike in our walk/hike/stroll set-up. We introduce the reader to the basics of stochastics (representing both probability and statistics) necessary for the more technical discussions on risk later. The path followed starts from probability space (a theoretical concept we quickly leave aside); we then move to the notion of a random variable and,, its distribution function, including the most important discrete as well as continuous examples. Historical examples as well as pedagogical ones are always included in order to support the understanding of the new concepts introduced. These examples often show that there is more to randomness than meets the eye. For the applications discussed later, we will measure statistical uncertainty through the concept of confidence intervals. These can be based either on some asymptotic theory involving the famous bell curve, the normal distribution, or on some form of resampling known under the name of bootstrapping. Further, we add some tools that are very important for measuring and communicating risk; these include the concepts of return periods and quantile functions.
A procedure for structural investigations by X-ray diffraction of mixed-layer structures incorporating swelling layers has been developed. For each sample, specimens saturated with different cations (Na, Mg, and Ca), are analyzed both as air-dried and as glycolated. One structural model fitting all the observed patterns then provides the structure of the sample. Samples tested include: Mite-smectite (I-S) minerals from Kazachstan (a rectorite), Dolna Ves in Slovakia, Kinnekulle in Sweden, the North Sea, and Scania in Sweden. The fitting of the patterns of the Kazachstan rectorite demonstrated that the instrumental parameters applied in the modeling were correct. For the I-S minerals from Slovakia and Kinnekulle the observed patterns were fitted with one two-component I-S model. However, the Ca-saturated and air-dried specimen of the Kinnekulle bentonites had two types of swelling interlayers. For the Slovakian I-S with Reichweite = 2, an alternative two-phase I-S plus I–V (V = vermiculite) model fitted the experimental X-ray diffraction patterns equally well. The I-S mineral from Scania is in fact a three-component I-T-S (T = tobelite) and the North Sea sample is a four-component I-S-V-V, one type of the swelling layers having swelling characteristics intermediately between smectite and vermiculite. In addition to layer types and distribution, interlayer compositions, such as the amount of interlayer glycol and water and of fixed and exchangeable cations, were determined.
This paper thoroughly describes the decomposition procedure, using the example of DECOMPXR (Lanson 1990). The steps of the decomposition procedure are: 1) preliminary data processing; 2) decomposition; 3) validation of results; and 4) use of the results. The use of decomposition is restricted to the separation of contributions from various phases. The effect of preliminary data processing steps (data smoothing, background stripping) on profile shape is shown to be limited and their implementation is detailed. Potential experimental limitations such as peak symmetry, experimental reproducibility or discrimination are equally minor. A logical decomposition process starts from the definition of the angular range to be fitted, proceeds with the determination of the number of elementary peaks to be fitted and ends with the check for results consistency.
Numerical data processing is a powerful tool for the accurate identification of monophases, because of the additional parameters available to constrain XRD profile simulation. Ultimately, however, the match over the whole angular range of both the experimental and the simulated patterns remains the only valid way to characterize the phases present in the sample. Additionally, the decomposition procedure permits both the identification of complex clay mineral assemblages and the characterization of their evolution. This step constrains, and may help to determine, the reaction mechanisms of a transformation; and, as a consequence, to characterize and to model the kinetics of this transformation.
Decomposition of complex X-ray diffraction profiles is used on well characterized (image analysis of transmission electron micrographs, X-ray fluorescence chemical analyses) diagenetic samples from the Paris basin. The simultaneous occurrence of three “illitic” phases (mixed-layer illite/smectite or I/S, poorly crystallized illite, and mica-like phase) is shown on the various diffraction peaks of the 2–50 °2θ CuKα (44–1.8 Å) range. However, because of theoretical and experimental constraints, it is easier to perform the decomposition routine in the 5–11 °2θ CuKα (17.6–8.0 Å) range. The identification (i.e., illite content and mean coherent scattering domain size) of the various phases is performed by comparing the associated elementary peak characteristics (position, full width at half maximum intensity) with simulated X-ray patterns. When available, the characteristics obtained from the various angular regions are mutually consistent; however, the precise structures of smectite and illite end-members, on the one hand, and the structure of I/S crystallites, on the other hand, are not well known. Consequently, on some angular regions, there is a discrepancy between the characteristics obtained on experimental and calculated X-ray profiles. The definition of more realistic simulation hypotheses for I/S minerals, and for other interstratified clay minerals, would make this powerful and reliable tool to describe X-ray patterns a precise and sensitive identification tool even for complex clay parageneses.
Complex X-ray diffraction (XRD) profiles are described crystallographically by simulating XRD peaks for each phase, and adding the various elementary patterns to fit the experimental X-ray pattern. X-ray patterns of a ground muscovite and three polyphasic diagenetic I/S samples are fitted with this powerful, but time-consuming, technique. In the 6°–10°2θ CuKα range, the asymmetry of the muscovite peak is related to a very broad coherent scattering domain size (CSDS) distribution; for the I/S samples the even greater asymmetry is due to the presence of several phases with close, but distinct crystallographic characteristics (I/S, illite, and detrital mica).
A simulation-decomposition approach for modelling XRD patterns is introduced to describe quickly and accurately the various clay minerals (essentially mixed-layer illite/smectite and illite) present in a sedimentary series, and to follow their individual evolution during diagenesis. The theory for these simulations is described briefly. The influence of mixed-layer heterogeneity (the distribution of CSDS, and the distribution of smectite content) on the shape of X-ray peaks is shown theoretically to be minimal. Indeed, for both CSDS and smectite content, the important parameter for peak shape appears to be the mean value of the distribution and not its width and/or its shape. The theoretical limitations of the decomposition method are presented. Minor experimental limitations (reproducibility, experimental peak shape, discrimination) make this method a powerful and reliable tool to describe X-ray patterns. The method is used to show the simultaneous occurrence of three “illitic” phases in a sedimentary series from the Paris Basin. The respective evolution of the three phases is clearly evidenced by using this decomposition method. However, the precise identification of these different phases remains difficult to determine because of the difference in peak width between simulated and experimental X-ray patterns.
Chapter 5 treats the fundamentals of small-scale fading and the propagation mechanisms that cause multipath, doppler spread, time dispersion, and distortions to transmitted signals in the radio propagation channel. Detailed theoretical derivations and explanations for the small-scale channel impairments are presented with numerous examples. Flat and frequency selective fading, as well as fast and slow fading, are defined and analyzed. Key distributions found in the real world, such as Raleigh fading, Rician fading, and the classical Clarke and Gans model for multipath, are presented. Shape factor theory shows how the classical small-scale fading results may be replicated with excellent accuracy using the first thee Fourier coefficients of the spatial distribution of energy arriving at an antenna.