583 research outputs found
Direct numerical simulation of compressible turbulence in a counter-flow channel configuration
Counter-flow configurations, whereby two streams of fluid are brought together from opposite directions, are highly efficient mixers due to the high turbulence intensities that can be maintained. In this paper, a simplified version of the problem is introduced that is amenable to direct numerical simulation. The resulting turbulent flow problem is confined between two walls, with one non-zero mean velocity component varying in the space direction normal to the wall, corresponding to a simple shear flow. Compared to conventional channel flows, the mean flow is inflectional and the maximum turbulence intensity relative to the maximum mean velocity is nearly an order of magnitude higher. The numerical requirements and turbulence properties of this configuration are first determined. The Reynolds shear stress is required to vary linearly by the imposed forcing, with a peak at the channel centreline. A similar behaviour is observed for the streamwise Reynolds stress, the budget of which shows an approximately uniform distribution of dissipation, with large contributions from production, pressure-strain and turbulent diffusion. A viscous sublayer is obtained near the walls and with increasing Reynolds number small-scale streaks in the streamwise momentum are observed, superimposed on the large-scale structures that buffet this region. When the peak local mean Mach number reaches 0.55, turbulent Mach numbers of 0.6 are obtained, indicating that this flow configuration can be useful to study compressibility effects on turbulence
Tilt Induced Localization and Delocalization in the Second Landau Level
We have investigated the behavior of electronic phases of the second Landau
level under tilted magnetic fields. The fractional quantum Hall liquids at
2+1/5 and 2+4/5 and the solid phases at 2.30, 2.44, 2.57, and 2.70
are quickly destroyed with tilt. This behavior can be interpreted as a tilt
driven localization of the 2+1/5 and 2+4/5 fractional quantum Hall liquids and
a delocalization through melting of solid phases in the top Landau level,
respectively. The evolution towards the classical Hall gas of the solid phases
is suggestive of antiferromagnetic ordering
Proceed with caution: The need to raise the publication bar for microplastics research
This is an Accepted Manuscript. Embargo until December 12 2022.Plastic is a ubiquitous contaminant of the Anthropocene. The highly diverse nature of microplastic pollution means it is not a single contaminant, but a suite of chemicals that include a range of polymers, particle sizes, colors, morphologies, and associated contaminants. Microplastics research has rapidly expanded in recent years and has led to an overwhelming consideration in the peer-reviewed literature. While there have been multiple calls for standardization and harmonization of the research methods used to study microplastics in the environment, the complexities of this emerging field have led to an exploration of many methods and tools. While different research questions require different methods, making standardization often impractical, it remains import to harmonize the outputs of these various methodologies. We argue here that in addition to harmonized methods and quality assurance practices, journals, editors and reviewers must also be more proactive in ensuring that scientific papers have clear, repeatable methods, and contribute to a constructive and factual discourse on plastic pollution. This includes carefully considering the quality of the manuscript submissions and how they fit into the larger field of research. While comparability and reproducibility is critical in all fields, we argue that this is of utmost importance in microplastics research as policy around plastic pollution is being developed in real time alongside this evolving scientific field, necessitating the need for rigorous examination of the science being published.acceptedVersio
Microplastic and PTFE contamination of food from cookware
Microplastics are a prolific environmental contaminant that have been evidenced in human tissues. Human
uptake of microplastic occurs via inhalation of airborne fibres and ingestion of microplastic-contaminated foods
and beverages. Plastic and PTFE-coated cookware and food contact materials may release micro- and nano�plastics into food during food preparation. In this study, the extent to which non-plastic, new plastic and old
plastic cookware releases microplastics into prepared food is investigated. Jelly is used as a food simulant, un�dergoing a series of processing steps including heating, cooling, mixing, slicing and storage to replicate food
preparation steps undertaken in home kitchens. Using non-plastic cookware did not introduce microplastics to
the food simulant. Conversely, using new and old plastic cookware resulted in significant increases in micro�plastic contamination. Microplastics comprised PTFE, polyethylene and polypropylene particulates and fibrous
particles, ranging 13â318 Îźm. Assuming a meal was prepared daily per the prescribed methodology, new and old
plastic cookware may be contributing 2409â4964 microplastics per annum into homecooked food. The health
implications of ingesting microplastics remains unclear
Network dynamics with a nested node set: sociability in seven villages in Senegal
We propose two complementary ways to deal with a nesting structure in the node set of a networkâsuch a structure may be called a multilevel network, with a node set consisting of several groups. First, withinâgroup ties are distinguished from betweenâgroup ties by considering them as two distinct but interrelated networks. Second, effects of nodal variables are differentiated according to the levels of the nesting structure, to prevent ecological fallacies. This is elaborated in a study of two repeated observations of a sociability network in seven villages in Senegal, analyzed using the Stochastic Actorâoriented Model
Bayesian Exponential Random Graph Models with Nodal Random Effects
We extend the well-known and widely used Exponential Random Graph Model
(ERGM) by including nodal random effects to compensate for heterogeneity in the
nodes of a network. The Bayesian framework for ERGMs proposed by Caimo and
Friel (2011) yields the basis of our modelling algorithm. A central question in
network models is the question of model selection and following the Bayesian
paradigm we focus on estimating Bayes factors. To do so we develop an
approximate but feasible calculation of the Bayes factor which allows one to
pursue model selection. Two data examples and a small simulation study
illustrate our mixed model approach and the corresponding model selection.Comment: 23 pages, 9 figures, 3 table
Invisible Iterations: How Formal and Informal Organization Shape Knowledge Networks for Coordination
AbstractThis study takes a network approach to investigate coordination among knowledge workers as grounded in both formal and informal organization. We first derive hypotheses regarding patterns of knowledgeâsharing relationships by which workers pass on and exchange tacit and codified knowledge within and across organizational hierarchies to address the challenges that underpin contemporary knowledge work. We use survey data and apply exponential random graph models to test our hypotheses. We then extend the quantitative network analysis with insights from qualitative interviews and demonstrate that the identified knowledgeâsharing patterns are the microâfoundational traces of collective coordination resulting from two underlying coordination mechanisms which we label âinvisible iterationsâ and âbringing in the big gunsâ. These mechanisms and, by extension, the associated knowledgeâsharing patterns enable knowledge workers to perform in a setting that is characterized by complexity, uncertainty and ambiguity. Our research contributes to theory on the interplay between formal and informal organization for coordination by showing how selfâdirected, informal action is supported by the formal organizational hierarchy. In doing so, it also extends understanding of the role that hierarchy plays for knowledgeâintensive work. Finally, it establishes the collective need to coordinate work as a previously overlooked driver of knowledge network relationships and network patterns.</jats:p
Optimal treatment allocations in space and time for on-line control of an emerging infectious disease
A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulationâoptimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America
Networked international politics
Network theory and methods are becoming increasingly used to study the causes and consequences of conflict. Network analysis allows researchers to develop a better understanding of the causal dynamics and structural geometry of the complex web of interdependencies at work in the onset, incidence, and diffusion of conflict and peace. This issue features new theoretical and empirical research demonstrating how properly accounting for networked interdependencies has profound implications for our understanding of the processes thought to be responsible for the conflict behavior of state and non-state actors. The contributors examine the variation in networks of states and transnational actors to explain outcomes related to international conflict and peace. They highlight how networked interdependencies affect conflict and cooperation in a broad range of areas at the center of international relations scholarship. It is helpful to distinguish between three uses of networks, namely: (1) as theoretical tools, (2) as measurement tools, and (3) as inferential tools. The introduction discusses each of these uses and shows how the contributions rely on one or several of them. Next, Monte Carlo simulations are used to illustrate one of the strengths of network analysis, namely that it helps researchers avoid biased inferences when the data generating process underlying the observed data contains extradyadic interdependencies. </jats:p
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