The investigation of α→β phase transition in poly(vinylidene fluoride) (PVDF)

The phase transition from the non-polar α-phase to the polar β-phase of poly(vinylidene fluoride) (PVDF) has been investigated using micro-Raman spectroscopy, which is advantageous for being a non-destructive technique. Films of α-PVDF were subjected to stretching under controlled rates and at 80°C, the transition to β-PVDF being monitored by the decrease in the Raman band at 794 cm-1 characteristic of the α-phase, with the concomitant increase in the 839 cm-1 band characteristic of the β-phase. Poling with negative corona discharge was found to affect the a-PVDF morphology improving the Raman bands related to this crystalline phase. This effect is minimized for films stretched to higher ratios. Significantly, corona-induced effects could not be observed with the other experimental techniques, viz. X-ray diffraction and infrared spectroscopy.

Initial concentration profile influence on migration measurements from plastic packaging: A simulation study

Migration of components from plastic packaging into foodstuffs or into medicines is a very important issue, concerning public health. Using experimental techniques, like gas chromatography-mass spectrometry, these essays measure total migration and specific migration of components from plastic packaging. This work presents an explanation and applications of a numerical technique tool for this measurement, allowing the comprehension of the diffusion process and the estimate of component migration in difficult or impractical measurements. As an application example, the non-uniform influence of initial concentration profile on the migration is presented, demonstrating the necessity of this profile determination for high quality considerations on involved metrology.

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.

Caracterização de vidros preparados com resíduos de indústria de galvanostegia

Pós-graduação em Física - IGCE

Predição computacional de promotores em Xanthomonas axonopodis pv. citri

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A teoria do funcional da densidade na caracterização de fases intermetálicas ordenadas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Efeito da colocação de um ponto simples em tendão flexor de coelho em região vascularizada e avascularizada: análise da propriedades mecânicas e histopatológicas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Bioinformática estrutural aplicada ao estudo de enzimas da via metabólica do ácido chiquímico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estrutura e propriedades de filmes finos ferroelétricos do sistema PZT

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Simulações por dinâmica molecular fine-e coarse-grained das interações intermoleculares entre peptídeos antimicrobianos da família Mastoparano e membranas modelo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo das propriedades ópticas, linear e não linear, e elétrica dos vidros da família Li2O-TeO2-WO3

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Exotic Bose-Einstein condensates: binary mixtures and dipolar gases

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudos estruturais com fosfolipases A2 isoladas de venenos de serpentes dos gêneros Bothrops e Crotalus

Pós-graduação em Ciências Biológicas (Genética) - IBB

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Metodologia computacional baseada em DFT, para compreensão de processos eletródicos em fases intermetálicas ordenadas

Pós-graduação em Ciência e Tecnologia de Materiais - FC