Cross-delisting, financial constraints and investment sensitivities

We investigate the impact of cross-delisting on firms’ financial constraints and investment sensitivities. We find that firms that cross-delisted from a U.S. stock exchange face stronger post-delisting financial constraints than their cross-listed counterparts, as measured by investment-to-cash flow sensitivity. Following a delisting, the sensitivity of investment-to-cash flow increases significantly and firms also tend to save more cash out of cash flows. Moreover, this increase appears to be primarily driven by informational frictions that constrain access to external financing. We document that information asymmetry problems are stronger for firms from countries with weaker shareholders protection and for firms from less developed capital markets.

Assessing the production of jet mix columns using alkali activated waste based on mechanical and financial performance and CO2 (eq) emissions

Recent research has proved the potential of alkaline activated fly-ash for soil stabilisation. However, such studies have not focused on the link between financial, mechanical and environmental aspects of this solution, but only on their absolute mechanical properties. The present paper characterises the mechanical behaviour of a large spectrum of activator-ash-soil combinations used to build jet mixing columns, analysing also the cost and CO2 (eq) emissions. The concern with these two vectors forced a decrease in the quantity of stabilising agent added to the soil, relatively to previous research, and the effects of such low quantities have not yet been published. However, the results clearly showed a significant improve in strength, still well above the average values expected when improving the stressstrain behaviour of a weak soil. Uniaxial compressive strength tests were used to assess the effects of the fly-ash percentage, the alkalieash ratio and the water content. The carbon calculator recently developed by the European Federation of Foundation Contractors and the Deep Foundations Institute was used to quantify the CO2 (eq) emissions associated with this technique. The financial cost was estimated based on the experience of a major Portuguese contractor. For comparison purposes, soil cement mixtures were also analysed, using similar conditions and tools used for the soil-ash analysis. Results showed that the cement and ash solutions are very similar in terms of overall performance, with some advantage of the former regarding financial cost, and a significant advantage of the latter regarding the CO2 (eq) emissions. This new grout, although it is in an embryonic stage, it has the potential for broader developments in the field.

Financial stress and sovereign debt composition

"Published online: 19 Oct 2015"

The real economic effects of cross-delistingfrom the united states: evidence on post-operating performance, financial constraints and stock crash risk

Tese de Doutoramento em Ciências Empresariais.

Changes in institutional governance and management of higher education in Laos: National University of Laos

PhD thesis in Educational Sciences (specialization in Politics of Education).

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.