The "refoldability" of selected proteins in ionic liquids as a stabilization criterion, leading to a conjecture on biogenesis

The folding of proteins is usually studied in dilute aqueous solutions of controlled pH, but it has recently been demonstrated that reversible unfolding can occur in other media. Particular stability is conferred on the protein (folded or unfolded) when the process occurs in ‘protic ionic liquids’ (pILs) of controlled proton activity. This activity (‘effective pH’) is determined by the acid and base components of the pIL and is characterized in the present study by the proton chemical shift of the N–H proton. Here we propose a ‘refoldability’ or ‘refolding index’ (RFI) metric for assessing the stability of folded biomolecules in different solvent media, and demarcate high RFI zones in hydrated pIL media using ribonuclease A and hen egg white lysozyme as examples. Then we show that, unexpectedly, the same high RFIs can be obtained in pIL media that are 90% inorganic in character (simple ammonium salts). This leads us to a conjecture related to the objections that have been raised to ‘primordial soup’ theories for biogenesis, objections that are based on the observation that all the bonds involved in biomacromolecule formation are hydrolyzed in ordinary aqueous solutions unless specifically protected. The ingredients for primitive ionic liquids (NH3, CO, HCN, CO2, and water) were abundant in the early earth atmosphere, and many experiments have shown how amino acids could form from them also. Cyclical concentration in evaporating inland seas could easily produce the type of ambient-temperature, non-hydrolyzing, media that we have demonstrated here may be hospitable to biomolecules, and that may be actually encouraging of biopolymer assembly. Thus a plausible variant of the conventional ‘primordial soup’ model of biogenesis is suggested.

Rock slope risk analysis based on non-linear failure criterion

The probability of failure of a rock slope is generally estimated by using the Limit Equilibrium Method (LEM) in conjunction with a reliability analysis. Although the LEM is relatively simple and time efficient, recent studies have indicated that using the LEM may overestimate the factor of safety by 21%, when based on a non-linear failure criterion. Fortunately, the solutions presented by Li et al. (2008, 2009) can provide more accurate evaluations for rock slope stability as the numerical upper and lower bound limit analysis methods (2002a, 2002b, 2005) were employed. The advantages of these methods are used in this study to assess the rock slope probability of failure. The motivation is that with more accurate methods to evaluate the factor of safety, more economic designs can be performed.

Enhancing fuzzy inference system based criterion-referenced assessment with an application

An important and difficult issue in designing a Fuzzy Inference System (FIS) is the specification of fuzzy sets, and fuzzy rules. The aim of this paper is to demonstrate how an additional qualitative information, i.e., monotonicity property, can be exploited and extended to be part of an FIS designing procedure (i.e., fuzzy sets and fuzzy rules design). In this paper, the FIS is employed as an alternative to the use of addition in aggregating the scores from test items/tasks in a Criterion-Referenced Assessment (CRA) model. In order to preserve the monotonicity property, the sufficient conditions of the FIS is proposed. Our proposed FIS based CRA procedure can be viewed as an enhancement for the FIS based CRA procedure, where monotonicity property is preserved. We demonstrate the applicability of the proposed approach with a case study related to a laboratory project assessment task at a university, and the results indicate the usefulness of the proposed approach in the CRA domain.

A critical evaluation and comparison of two formative measures of system quality using criterion variables

Evaluating the validity of formative variables has presented ongoing challenges for researchers. In this paper we use global criterion measures to compare and critically evaluate two alternative formative measures of System Quality. One model is based on the ISO-9126 software quality standard, and the other is based on a leading information systems research model. We find that despite both models having a strong provenance, many of the items appear to be non-significant in our study. We examine the implications of this by evaluating the quality of the criterion variables we used, and the performance of PLS when evaluating formative models with a large number of items. We find that our respondents had difficulty distinguishing between global criterion variables measuring different aspects of overall System Quality. Also, because formative indicators “compete with one another” in PLS, it may be difficult to develop a set of measures which are all significant for a complex formative construct with a broad scope and a large number of items. Overall, we suggest that there is cautious evidence that both sets of measures are valid and largely equivalent, although questions still remain about the measures, the use of criterion variables, and the use of PLS for this type of model evaluation.

Incremental criterion prediction of personality facets over factors: obtaining unbiased estimates and confidence intervals

 Many researchers have argued that higher order models of personality such as the Five Factor Model are insufficient, and that facet-level analysis is required to better understand criteria such as well-being, job performance, and personality disorders. However, common methods in the extant literature used to estimate the incremental prediction of facets over factors have several shortcomings. This paper delineates these shortcomings by evaluating alternative methods using statistical theory, simulation, and an empirical example. We recommend using differences between Olkin-Pratt adjusted r-squared for factor versus facet regression models to estimate the incremental prediction of facets and present a method for obtaining confidence intervals for such estimates using double adjusted-. r-squared bootstrapping. We also provide an R package that implements the proposed methods.