The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Limitations and improvements to the risk assessment process in Olive Oil Mills: the views of OSH practitioners

Although most of the accidents occurred in Olive Oil Mill (OOM) resulted from “basic” risks, there is a need to apply adequate tools to support risk decisions that can meet the specificities of this sector. This study aims to analyse the views of Occupational, Safety & Health (OSH) practitioners about the risk assessment process in OOM, identifying the key difficulties inherent to the risk assessment process in these sector, as well as identifying some improvements to the current practice. This analysis was based on a questionnaire that was developed and applied to 13 OSH practitioners working at OOM. The results showed that the time available to perform the risk assessment is the more frequent limitation. They believe that the methodologies available are not an important limitation to this process. However, a specific risk assessment methodology, that includes acceptance criteria adjusted to the OOM reality, using risk metrics supported on the frequency of accidents and workdays lost, were indicated as being also an important contributions improve the process. A semi-quantitative approach, complemented with the use of the sector accident statistics, can be a good solution for this sector. However, further strategies should also be adopted, mainly those that can lead to an easy application of the risk assessment process.

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.

To be or not to be a pseudogene: a molecular epidemiological approach to the mclx genes and its impact in tuberculosis

Tuberculosis presents a myriad of symptoms, progression routes and propagation patterns not yet fully understood. Whereas for a long time research has focused solely on the patient immunity and overall susceptibility, it is nowadays widely accepted that the genetic diversity of its causative agent, Mycobacterium tuberculosis, plays a key role in this dynamic. This study focuses on a particular family of genes, the mclxs (Mycobacterium cyclase/LuxR-like genes), which codify for a particular and nearly mycobacterial-exclusive combination of protein domains. mclxs genes were found to be pseudogenized by frameshift-causing insertion(s)/deletion(s) in a considerable number of M. tuberculosis complex strains and clinical isolates. To discern the functional implications of the pseudogenization, we have analysed the pattern of frameshift-causing mutations in a group of M. tuberculosis isolates while taking into account their microbial-, patient- and disease-related traits. Our logistic regression-based analyses have revealed disparate effects associated with the transcriptional inactivation of two mclx genes. In fact, mclx2 (Rv1358) pseudogenization appears to be primarily driven by the microbial phylogenetic background, being mainly related to the Euro-American (EAm) lineage; on the other hand, mclx3 (Rv2488c) presents a higher tendency for pseudogenization among isolates from patients born on the Western Pacific area, and from isolates causing extra-pulmonary infections. These results contribute to the overall knowledge on the biology of M. tuberculosis infection, whereas at the same time launch the necessary basis for the functional assessment of these so far overlooked genes.

Gender, sex and sexuality in two open access communication journals published in Portugal: a critical overview of current discursive practices

The links between gender, sex and sexuality and their relevance are theoretically and politically problematic (Richardson, 2007). One of the difficulties in understanding their interconnections is that these terms are often used differently and ambiguously by different authors (and even by the same authors). This article reports the results of an analysis of the articles published in open access communication journals with known impact factor, edited in Portugal and published between 2005 and 2012. The diverse conceptualisations of those three basic concepts and of their (inter)relationships within communication research are identified. The complexity and the intricate (and often implicit) nature of both the meanings of these categories and their relationships underlie and justify our attention and further research. What the findings suggest about the current communication research into gender issues published in the two journals surveyed is that the ‘Gender differences discourse’ (Sunderland, 2004) is the most pervasive discourse (also) in academic practice. Additionally, they show that gender and sex are mainly taken for a fact, not a question that is worth being studied. The editors of these journals, as well as the scholars submitting manuscripts, need to be more aware of the traditional nature of the theoretical and methodological choices that they make regarding gender- and sex-related issues, as well as of the relative lack of attention to sexuality as a research subject.

Listening to the public: enacting power : citizen access, Standing and influence in public participation discourses

Public participation in environmental governance is typically associated with citizen access to power despite many closures and limitations having been identified in participatory processes. This article proposes an analytical framework to analyse discursive practices involved in public consultation processes. Critical Discourse Analysis is used to examine and appraise citizens’ access, standing and influence. We apply that framework to a ‘notice and comment’ process on a hydroelectric power plan in Portugal and show that it was discursively managed to justify the decision of constructing 10 large dams and to reject critical or alternative views. Citizens’ access, standing and influence were constrained through diverse discursive practices which (re)produced very unequal power relationsbetween policy proponents and participating individuals. More generally, the article illustrates the potential of Critical Discourse Analysis to assess voice(s) in policy processes. Focusing on argumentative, interactional and rhetorical levels, and how they are interwoven in public consultation discourses, the proposed framework is conceivably applicable in other studies.