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

Synthesis of five-membered heterocycles by indirect electrochemical approach in "Green" media

Radical cyclization continues to be a central methodology for the preparation of natural products containing heterocyclic rings. Hence, some electrochemical results obtained by cyclic voltammetry and controlled-potential electrolysis in the study of electroreductive intramolecular cyclization of ethyl (2S, 3R)-2-bromo-3-propargyloxy-3-(2’,3’,4’,6’-tetra-O-acetyl-beta-D-glucopyranosyloxy) propanoate (1a), 2-bromo-3-allyloxy-3-(2’,3’,4’,6’-tetra-O-acetyl-beta-D-glucopyranosyloxy)propanoate (1b), 2-bromo-[1-(prop-2-yn-1-yloxy)propyl]benzene (1c) and [1-bromo-2-methoxy-2-(prop-2’-yn-1-yloxy)ethyl]benzene (1d) promoted by (1,4,8,11-tetramethyl-1,4,8,11-tetraazacyclotetradecane)nickel(I), [Ni(tmc)]+, electrogenerated at glassy carbon cathodes in ethanol and ethanol:water mixtures containing tetraalkylammonium salts, are presented. During controlled-potential electrolyses of solutions containing [Ni(tmc)]2+ and bromoalkoxylated compounds (1) catalytic reduction of the latter proceeds via one-electron cleavage of the carbon–bromine bond to form a radical intermediate that undergoes cyclization to afford the substituted tetrahydrofurans.

Quantum field theory approach to the optical conductivity of strained and deformed graphene

The computation of the optical conductivity of strained and deformed graphene is discussed within the framework of quantum field theory in curved spaces. The analytical solutions of the Dirac equation in an arbitrary static background geometry for one dimensional periodic deformations are computed, together with the corresponding Dirac propagator. Analytical expressions are given for the optical conductivity of strained and deformed graphene associated with both intra and interbrand transitions. The special case of small deformations is discussed and the result compared to the prediction of the tight-binding model.

An algorithmic approach to estimating the minimal number of periodic points for smooth self-maps of simply-connected manifolds

For a given self-map f of M, a closed smooth connected and simply-connected manifold of dimension m ≥ 4, we provide an algorithm for estimating the values of the topological invariant Dm r [f], which equals the minimal number of r-periodic points in the smooth homotopy class of f. Our results are based on the combinatorial scheme for computing Dm r [f] introduced by G. Graff and J. Jezierski [J. Fixed Point Theory Appl. 13 (2013), 63–84]. An open-source implementation of the algorithm programmed in C++ is publicly available at http://www.pawelpilarczyk.com/combtop/.

Transanal total mesorectal excision: a pure NOTES approach for selected patients.

Transanal total mesorectal excision: a pure NOTES approach for selected patients.

Holistic approach, tourism

Holistic refers to something that emphasizes the whole and the interdependence of its parts. It can be conceptualized as interdisciplinary: the claim that most social and economic phenomena cannot be fully understood or explained without adopting an approach that goes beyond the aims of a single scientific discipline.

Study of grapevine solute transporters involved in berry quality. A biochemical and molecular approach

Tese de Doutoramento em Biologia de Plantas

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

VET: a strategic approach for economic, organisational and personal development in EU countries

Vocational Education and Training (VET) is a continuous long-term process of economic, organisational and personal development. It envisions the construction of dynamic skills to improve performance, productivity and organisational, personal and social development. This article focuses on generating skills. It frames training as a process of work-linked training and as a primary source for generating skills whilst seeking to boost creativity. It sheds light upon the discussion pertaining to learning transfer as a necessary condition to structure performance and competitiveness. It highlights the Learning Transfer System Inventory (LTSI), because it allows to measure the effectiveness of training and it identifies the organisations' weaknesses. The data used were collected from the Eurostat Database.

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

A linear algebra approach to OLAP

Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.

Polyphasic approach including MALDI-TOF MS/MS analysis for identification and characterisation of Fusarium verticillioides in Brazilian corn kernels

Fusarium verticillioides is considered one of the most important global sources of fumonisin contamination in food and feed. Corn is one of the main commodities produced in the Northeastern Region of Brazil. The present study investigated potential mycotoxigenic fungal strains belonging to the F. verticillioides species isolated from corn kernels in 3 different Regions of the Brazilian State of Pernambuco. A polyphasic approach including classical taxonomy, molecular biology, MALDI-TOF MS and MALDI-TOF MS/MS for the identification and characterisation of the F. verticillioides strains was used. Sixty F. verticillioides strains were isolated and successfully identified by classical morphology, proteomic profiles of MALDI-TOF MS, and by molecular biology using the species-specific primers VERT-1 and VERT-2. FUM1 gene was further detected for all the 60 F. verticillioides by using the primers VERTF-1 and VERTF-2 and through the amplification profiles of the ISSR regions using the primers (GTG)5 and (GACA)4. Results obtained from molecular analysis shown a low genetic variability among these isolates from the different geographical regions. All of the 60 F. verticillioides isolates assessed by MALDI-TOF MS/MS presented ion peaks with the molecular mass of the fumonisin B1 (721.83 g/mol) and B2 (705.83 g/mol)

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Lipids under stress - a lipidomic approach for the study of mood disorders

The emerging field of lipidomics has identified lipids as key players in disease physiology. Their physicochemical diversity allows precise control of cell structure and signaling events through modulation of membrane prop- erties and trafficking of proteins. As such, lipids are important regulators of brain function and have been implicated in neurodegenerative and mood disorders. Importantly, environmental chronic stress has been associated with anxiety and depression and its exposure in rodents has been extensively used as a model to study these diseases. With the accessibility to modern mass- spectrometry lipidomic platforms, it is now possible to snapshot the extensively interconnected lipid network. Here, we review the fundamentals of lipid biology and outline a framework for the interpretation of lipidomic studies as a new approach to study brain pathophysiology. Thus, lipid profiling provides an exciting avenue for the identification of disease signatures with important implications for diagnosis and treatment of mood disorders.

A 3D computer assisted Orthopedic Surgery Planning approach based on planar radiography

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)