Single-cell genomics is now producing an ever-increasing amount of datasets that, when integrated, could provide large-scale reference atlases of tissue in health and disease. Such large-scale atlases increase the scale and generalizability of analyses and enable combining knowledge generated by individual studies. Specifically, individual studies often differ regarding cell annotation terminology and depth, with different groups specializing in different cell type compartments, often using distinct terminology. Understanding how these distinct sets of annotations are related and complement each other would mark a major step towards a consensus-based cell-type annotation reflecting the latest knowledge in the field. Whereas recent computational techniques, referred to as 'reference mapping' methods, facilitate the usage and expansion of existing reference atlases by mapping new datasets (i.e. queries) onto an atlas; a systematic approach towards harmonizing dataset-specific cell-type terminology and annotation depth is still lacking. Here, we present 'treeArches', a framework to automatically build and extend reference atlases while enriching them with an updatable hierarchy of cell-type annotations across different datasets. We demonstrate various use cases for treeArches, from automatically resolving relations between reference and query cell types to identifying unseen cell types absent in the reference, such as disease-associated cell states. We envision treeArches enabling data-driven construction of consensus atlas-level cell-type hierarchies and facilitating efficient usage of reference atlases.

Physical adsorption and mechanical entrapment are two major causes of polymer retention in porous media. Physical adsorption is considered an equilibrium process and is often modeled by assuming a Langmuir isotherm. The outcome is a steady state pressure response because the permeability reduction is also accounted for by adsorption. However, some experimental data show gradual increase of pressure with time, implying that polymer retention is a time-dependent process. We discuss simultaneous effect of sorption and mechanical entrapment on the polymer retention in porous media. An exact solution for 1-D flow problem for the case of constant filtration coefficient and Langmuir-sorption isotherm, including explicit formulae for breakthrough concentration and pressure drop across the core is derived. The general model with a varying filtration coefficient was successfully matched with experimental data confirming the occurrence of simultaneous sorption with deep-bed filtration during polymer flow in porous media. In the absence of mechanical entrapment, the physical adsorption causes delay in the polymer front and does not affect the polymer concentration behind the front. Addition of mechanical entrapment results in slow recovery of the injected concentration at the outlet (for a varying filtration coefficient) or reaching to a steady state concentration, which is only a fraction of the injected concentration (for a constant filtration coefficient). Accurate assessment and quantification of the polymer retention requires both pressure and effluent concentration data at the outlet of the porous medium.

Simulation models for foam enhanced oil recovery are of two types: Those that treat foam texture or bubble size explicitly (population-balance models) and those that treat the effects of foam texture implicitly through a gas mobility-reduction factor. The implicit-Texture models all implicitly assume local equilibrium (LE) between the processes of foam creation and destruction. In published studies most populationbalance models predict rapid attainment of local-equilibrium as well, and some have been recast in LE versions. In this paper we compare population-balance and implicit-Texture (IT) models in two ways. First, we show the equivalence of the two approaches by deriving explicitly the foam texture and foam-coalescencerate function implicit in the IT models, and then show its similarity to that in population-balance models. Second, we compare the models based on their ability to represent a set of N₂ and CO₂ steady-state foam experiments and discuss the corresponding parameters of the different methods. Each of the IT models examined was equivalent to the LE formulation of a population-balance model with a lamella-destruction function that increases abruptly in the vicinity of the limiting capillary pressure Pc∗, as in current population-balance models. The relation between steady-state foam texture and water saturation or capillary pressure implicit in the IT models is essentially the same as that in the populationbalance models. The IT and population-balance models match the experimental data presented equally well. The IT models examined allow for flexibility in making the abruptness of the coalescence rate near Pc an adjustable parameter. Some allow for coarse foam to survive at high capillary pressure, and allow for a range of power-law non-Newtonian behavior in the low-quality regime. Thus the IT models that incorporate an abrupt change in foam properties near a given water saturation can be recast as LE versions of corresponding population-balance models with a lamella-destruction function similar to those in current PB models. The trends in dimensionless foam texture implicit in the IT models is similar to that in the PB models. In other words, both types of model, at least in the LE approximation, equally honor the physics of foam behavior in porous media.