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Several complex factors appear to determine how HIV affects refugees, including pre-crisis HIV prevalence in refugee and host populations, interaction between refugees and host populations, camp health and information services, and exposure to violence [ 1, 5, 14].
To test the hypotheses that differences in HIV prevalence among injection drug users (IDUs) could be explained by different level variables such as individual injection practices, the type of drug(s) injected, average duration of drug use, structure of IDU populations, interaction within social networks of IDUs or a combination of these factors.
Observations from prior studies 19 24–26 led us to formulate the hypotheses that differences in HIV prevalence will be explained by different level variables such as: individual injection practices, the type of drug(s) injected, average duration of drug use, percentage of men and women in particular IDU populations, interaction within social networks of IDUs or a combination of these factors.
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I picked up a master's degree from Harvard and moved to Cornell to finish my Ph.D. Modeling populations' interactions with land-use patterns.
Dr Nicolas Galtier, CNRS-Université Montpellier II Laboratoire "Genome, Populations, Interactions, Adaptation", Montpellier, France This manuscript analyses the molecular evolution of the essential rbcL gene in three gymnosperm families.
In bifurcation problems, Buchanan [4] has studied Turing instability in a pioneer/climax population interaction model.
In Cox regression analysis of the overall population, interaction term obstructive CAD × DM resulted in non-significance.
As depicted in Fig. 1, the factors influencing wildfire ignition potential are grouped as "global" (population interaction) and "local" (parameters of transportation corridors) variables.
The ignition potential due to population interaction is modeled using gravity model following Sadasivuni et al. (2013) as below: ϕ P o p = α P D 2 (2a).
Variables and parameters used in the models of susceptible prey-infected prey-predator population interaction are given by Chattopadhyay et al. [11], Table 2, where r=3,qquad K=45,qquad beta=0.05,qquad mu=0.24,qquad theta=0.4, qquad delta=0.09.
Here we explore the regional archaeological record using different components of lithic technological systems to track the transmission of cultural information and the extent of population interaction within and between different climatic regions.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com