• 2018-07
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • Nevertheless of the different types


    Nevertheless, of the different types of scoring systems so far proposed, each of these [14], [29], [30] considered some aspects that could describe the fibrotic evolution, though none provided a quantitative assessment. Calvaruso et al. [8] showed that CPA had a better histological correlation with HVPG than Ishak stage. Similarly, Tsochatzis et al. [12] compared the performance of histological semi-quantitative and quantitative methods and found that CPA accurately sub-classified cirrhosis; it is the only independent predictor of clinical decompensation among the other histological systems described to date. Furthermore, in our study, the AUROC analysis revealed CPA values as the best means to identify fibrosis stage.
    Conflict of interest
    Introduction Design and optimization of processes using multifunctional molecules is of great importance to the chemical, petrochemical, pharmaceutical, cosmetics, food and orthopox industries. There is a need for simple, yet accurate, models able to cope with the requirements of the industry. Before the mid of the 1990's there were few reliable equation of state based approaches for the description of mixtures including strongly polar and associative molecules in broad ranges of temperature and pressure. The development of excess Gibbs energy mixing rules for equations of state provided some opportunities for modelling mixtures with polar compounds, but at the expense of having to use more parameters and in some cases having to re-estimate them. A good review on the use of excess Gibbs energy models in equations of state has been reported by Kontogeorgis and Coutsikos [1]. Based on Wertheim's ideas on association [2], [3], [4], [5] the Statistical Associating Fluid Theory (SAFT) [6], [7] EoS was developed and on its trail the CPA [8] model appeared as an alternative to model associating mixtures while keeping all the advantages, simplicity, and well known behaviour of cubic equations of state. The CPA can thus be seen as a special case of a cubic equation of state where associating components are involved. The CPA relevance as a simple, yet accurate, model for associative compounds has been growing since then, both in the academia and in the industry, although its use in the industry is still essentially limited to upstream oil and gas applications, where mixtures of water and hydrocarbons during production and the formation of hydrates in transportation are the most well-known applications of the model [9], [10]. Although CPA would be the right option to replace cubic equations of state in process simulators, up to until recently, not many commercial simulators implemented the model. This model can be found for example, in the physical properties package Multiflash™ and in the SPECS software from CERE at the Technical University of Denmark. So its use in process simulation was until recently limited to what could be achieved by using the CAPE-OPEN interface with these two packages. Nowadays, CPA is a well-established model in the literature and has been expanded to other fields of applications, as is the case of biodiesel [11], [12], [13], [14]. It is also gaining ground in the field of industrial simulators, being now available in the Petro-SIM™ and Hysys simulators, as well as in many in house simulators. The n-alkanols are a well-studied family with CPA. Various studies have been reported on their mixtures with other alkanols [15], [16], water [17], [18], amines [19] and hydrocarbons [16], [17], [18], [20], [21], [22], [23], as well as on other relevant properties of the pure compounds such as surface tension using a combined EoS/gradient theory approach [24]. Villiers et al. [25] have also studied the description of derivative properties for both n-alkanes and n-alcohols. Other CPA applications include the description of glycols with water and hydrocarbons [26], [27], [28], [29], [30], mixtures with organic acids [31], description of fluorocarbons [32] and the extension to some multifunctional compounds, as alkanolamines [33] and phenolic compounds [34], [35].