Synthesis and analysis of phase segregation of polystyrene-block-poly(methyl methacrylate) copolymer obtained by Steglich esterification from semitelechelic blocks of polystyrene and poly(methyl methacrylate)

Here, an alternative route to successfully synthesize polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) is reported. Steglich esterification was used as an effective, metal free approach for coupling carboxylic terminated PS and the hydroxyl end-functionalized PMMA chains obtained by nitroxide-mediated polymerization and atom transfer radical polymerization, respectively. α-Functionalization was obtained using 4,4′-azobis(4-cyanovaleric acid) and 2,2,2-tribromoethanol as initiators. The synthesis of PS-b-PMMA was confirmed by gel permeation chromatography and nuclear magnetic resonance (NMR), while the dependence of the diffusion coefficients of the polymers (PS, PMMA, PS/PMMA blend, and PS-b-PMMA) with their corresponding molecular weights was discussed based on the results of atomic force microscopy-based infrared spectroscopy, differential scanning calorimetry, and spectra of diffusion-ordered NMR spectroscopy. Differently from PS-b-PMMA, a partial segregation was observed for the PS/PMMA blend, affecting its thermal behavior and diffusion coefficient. The study here presented provides an easier and efficient strategy for the synthesis of PS-b-PMMA and new insights into the diffusion of polymers.     

Great cities look small

Great cities connect people; failed cities isolate people. Despite the fundamental importance of physical, face-to-face social ties in the functioning of cities, these connectivity networks are not explicitly observed in their entirety. Attempts at estimating them often rely on unrealistic over-simplifications such as the assumption of spatial homogeneity. Here we propose a mathematical model of human interactions in terms of a local strategy of maximizing the number of beneficial connections attainable under the constraint of limited individual travelling-time budgets. By incorporating census and openly available online multi-modal transport data, we are able to characterize the connectivity of geometrically and topologically complex cities. Beyond providing a candidate measure of greatness, this model allows one to quantify and assess the impact of transport developments, population growth, and other infrastructure and demographic changes on a city. Supported by validations of gross domestic product and human immunodeficiency virus infection rates across US metropolitan areas, we illustrate the effect of changes in local and city-wide connectivities by considering the economic impact of two contemporary inter- and intra-city transport developments in the UK: High Speed 2 and London Crossrail. This derivation of the model suggests that the scaling of different urban indicators with population size has an explicitly mechanistic origin.     

An evolutionary algorithm for the multi‐objective pick‐up and delivery pollution‐routing problem

The design of sustainable logistics solutions poses new challenges for the study of vehicle‐routing problems. The design of efficient systems for transporting products via a heterogeneous fleet of vehicles must consider the minimization of cost, emissions of greenhouse gases, and the ability to serve every customer within an available time slot. This phenomenon gives rise to a multi‐objective problem that considers the emission of greenhouse gases, the total traveling time, and the number of customers served. The proposed model is approached with an ε‐constraint technique that allows small instances to be solved and an evolutionary algorithm is proposed to deal with complex instances. Results for small instances show that all the points that approach the Pareto frontier found by the evolutionary algorithm are nondominated by any solution found by the multi‐objective model. For complex instances, nondominated solutions that serve most of the requests are found with low computational requirements.     

A mixed virtual element method for a nonlinear Brinkman model of porous media flow

In this work we introduce and analyze a mixed virtual element method for the two-dimensional nonlinear Brinkman model of porous media flow with non-homogeneous Dirichlet boundary conditions. For the continuous formulation we consider a dual-mixed approach in which the main unknowns are given by the gradient of the velocity and the pseudostress, whereas the velocity itself and the pressure are computed via simple postprocessing formulae. In addition, because of analysis reasons we add a redundant term arising from the constitutive equation relating the pseudostress and the velocity, so that the well-posedness of the resulting augmented formulation is established by using known results from nonlinear functional analysis. Then, we introduce the main features of the mixed virtual element method, which employs an explicit piecewise polynomial subspace and a virtual element subspace for approximating the aforementioned main unknowns, respectively. In turn, the associated computable discrete nonlinear operator is defined in terms of the \(\mathbb {L}^2\)-orthogonal projector onto a suitable space of polynomials, which allows the explicit integration of the terms involving deviatoric tensors that appear in the original setting. Next, we show the well-posedness of the discrete scheme and derive the associated a priori error estimates for the virtual element solution as well as for the fully computable projection of it. Furthermore, we also introduce a second element-by-element postprocessing formula for the pseudostress, which yields an optimally convergent approximation of this unknown with respect to the broken \(\mathbb {H}(\mathbf {div})\)-norm. Finally, several numerical results illustrating the good performance of the method and confirming the theoretical rates of convergence are presented.     

A graph-based cache for large-scale similarity search engines

Large-scale similarity search engines are complex systems devised to process unstructured data like images and videos. These systems are deployed on clusters of distributed processors communicated through high-speed networks. To process a new query, a distance function is evaluated between the query and the objects stored in the database. This process relays on a metric space index distributed among the processors. In this paper, we propose a cache-based strategy devised to reduce the number of computations required to retrieve the top-k object results for user queries by using pre-computed information. Our proposal executes an approximate similarity search algorithm, which takes advantage of the links between objects stored in the cache memory. Those links form a graph of similarity among pre-computed queries. Compared to the previous methods in the literature, the proposed approach reduces the number of distance evaluations up to 60%.