Simulation-Based Optimization of a Multiple Gas Feed Sweetening Process.

For an energy-intensive sweetening process, it is common that sour gases from different sources are sent to a single sweetening plant in industries. In our previous work, a multiple gas feed sweetening process was proposed, which can simultaneously improve the purity of H2S and reduce the energy consumption of the plant. This study aims to develop the superstructure of that process and use a simulation-based optimization framework with Aspen HYSYS as the process simulator and particle swarm optimization algorithm as the optimizer. In addition, by taking full advantage of the robustness of the built-in algorithm of the simulator, the convergence of the model is improved; meanwhile, simplification of the process and reduction of the optimization time are accessible with the proposed design specifications and assumptions. For a convergence-difficult column, a stepwise convergence adjustment was used to ensure their convergence. Based on this, the robustness and effectiveness of the method is proven through a case study, and it can also provide guidance for model selection, process simplification, and optimization of the same type of absorption process.

Modified Group Contribution Scheme to Predict the Glass-Transition Temperature of Homopolymers through a Limiting Property Dataset.

Previous studies on glass-transition temperature (T g) prediction mainly focus on developing diverse methods with higher regression accuracy, but very little attention has been paid to the dataset. Generally, a large range of T g values of a specified polymer could be found in the literature but which one should be selected into a dataset merely depends on the implicit preference rather than a recognized and clear criterion. In this paper, limiting glass-transition temperature (T g(∞)), a constant value obtained at the infinite number-average molecular weight M n, was validated to be an adequate bridge index in the T g prediction models. Furthermore, a new dataset containing 198 polymers was established to predict T g(∞) using the improved group contribution method and it showed a good correlation (R 2 = 0.9925, adjusted R 2 = 0.9894). The method could also generate T g-M n curves by introducing the T g(∞) function and provide more information to polymer scientists and engineers for material selection, product design, and synthesis.

Bayesian analysis of immigration in Europe with generalized logistic regression.

The number of immigrants moving to and settling in Europe has increased over the past decade, making migration one of the most topical and pressing issues in European politics. It is without a doubt that immigration has multiple impacts, in terms of economy, society and culture, on the European Union. It is fundamental to policy-makers to correctly evaluate people's attitudes towards immigration when designing integration policies. Of critical interest is to properly discriminate between subjects who are favourable towards immigration from those who are against it. Public opinions on migration are typically coded as binary responses in surveys. However, traditional methods, such as the standard logistic regression, may suffer from computational issues and are often not able to accurately model survey information. In this paper we propose an efficient Bayesian approach for modelling binary response data based on the generalized logistic regression. We show how the proposed approach provides an increased flexibility compared to traditional methods, due to its ability to capture heavy and light tails. The power of our methodology is tested through simulation studies and is illustrated using European Social Survey data on immigration collected in different European countries in 2016-2017.

Asymmetry of the dorsal anterior cingulate cortex: evidences from multiple modalities of MRI.

The dorsal anterior cingulate cortex (dACC) has been consistently implicated in cognitive control processes. Many studies have found higher fractional anisotropy (FA) in the left anterior cingulum bundle (aCB) than in the right. However, the asymmetry of gray matter density (GMD) is not clear. Using multiple modalities of MRI, we investigated both FA and GMD in the dACC in two independent groups of healthy participants (50 per group, 18-24 years old, half males and half females). Consistent with previous findings, the mean FA of the left aCB was significantly higher than that of the right. Males showed higher FA in the bilateral aCB than females. Voxel-based analysis of GMD in the dACC presented a region-specific significant asymmetry: right > left in the lower part (around callosal sulcus) but left > right in the upper part (around cingulate sulcus). No significant sex effect was found for GMD in the dACC. All these results were almost the same across the two independent groups. The complex pattern of asymmetry in GMD may imply highly differentiated functions of the dACC. Future fine-scale structural and diffusion MRI studies and a battery of cognitive behavioral measurements are needed to fully elucidate the asymmetry of the dACC.