Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.     

Color and COD retention by nanofiltration membranes

In the present study the application of the nanofiltration process was investigated mainly in the retention ofcolor and chemical oxygen demand (COD) present in textile industry wastewater. Nanofiltration experiments were carried out in a pilot unit, operating in crossflow. Three different types of spiral wound membranes, DK 1073, NF 45 and MPS 31 were used simultaneously in the same unit. The results of the tests showed that for color retention, the values were around 99% for the DK 1073 and NF 45 membranes and the 87% for COD retention for the DK 1073. The permeate flux for the different wastewaters varied from 30.5 to 70 L/h.m². Fouling was observed in all membranes due to the accumulation of molecular species close to the filtering surface. The process was efficient and promising for the reuse of wastewater from this type of industry.     

A modified consensus approach to mutagenesis inverts the cofactor specificity of Bacillus stearothermophilus lactate dehydrogenase

Lactate dehydrogenase from Bacillus stearothermophilus is specific for NAD+. There have been several attempts to alter the cofactor specificity of this enzyme, but these have yielded enzymes with relatively low activities that still largely prefer NAD+. A modified consensus approach was used to create a library of phylogenetically preferred amino acids situated near the cofactor binding site, and variants were screened for their ability to utilize NMN+. A triple mutant (Mut31) was discovered that proved to be more catalytically efficient than wild-type. Mut31 was also better at utilizing NAD+ than the wild-type enzyme and was weakly active with NADP+ and NMN+. An analysis of single amino acid substitutions suggested that all three mutations worked in a concerted fashion to yield robust cofactor utilization. When two previously identified amino acid substitutions were introduced into the Mut31 background, the resultant quintuply substituted enzyme not only utilized NADP+ far better than the wild-type enzyme, it actually inverted its preference for NAD+ and NADP+.     

Thermal dehydrochlorination of pure PVC polymer: Part I—thermal degradation kinetics by thermogravimetric analysis

Thermal degradation of PVC occurs in two stages, with each stage subdivided into two substages. The first refers to the dehydrochlorination, where hydrochloric acid is formed, and giving polyene structures. Hitherto, the degradation mechanism and action of hydrochloric acid as a catalyst during the dehydrochlorination stage are poorly known. Recently, the importance of the tacticity has gained attention for its influence on the dehydrochlorination mechanism. The present work focused on the dehydrochlorination stage, studying the molecular structure by FTIR analysis and the kinetic parameters by TGA analysis in Nitrogen atmosphere, based on three mathematical methods: Friedman, Kissinger, and Flynn-Wall-Ozawa. The sample was a pure homopolymer obtained by suspension polymerization. The dehydrochlorination kinetics follows a first order reaction model and occurs by nucleation and growth. The dehydrochlorination begins with the loss of very labile chlorine atoms present in defective and isotactic molecular segments. The formed HCl acts as a catalyst in the degradation. Following 40% conversion, a drop in Ea is observed. After that, chlorine atoms present in syndiotactic and atactic sequences, are released and, added to the large number of polyene chain sequences, and an increase in Ea is observed up to 60% conversion, where the dehydrochlorination stage is concluded.     

Estimating vulnerability to risks: an application in a biofuel supply chain

In the present work, we propose a theoretical model to identify and prioritize risks involved in a biofuel supply chain. We adopt a set of indicators associated with determinant factors of the supply chain to identify risks that are characterized through a risk matrix. We consider the five largest world biodiesel producers and included China due to its global market importance and potential impacts of its growth on the environment and society. To determine the impacts and the probability of occurrence of risks, we use the Canberra distance, as metrics. To facilitate the analysis and interpretation, a convenient manner is to express the results in terms of matrices. To exemplify the potentiality of the scheme and for the sake of simplicity, a more comprehensive discussion is focused on the Brazilian case, restricted to the Technology and Innovation, and Integration, Logistics and Infrastructure determining factors (dimensions) of the biodiesel supply chain. Concerning these determining factors, the Brazilian biodiesel chain shows strong vulnerability when compared with developed and developing countries, despite that the evolution of the data over recent years indicates small improvements in Integration, Logistics and Infrastructure dimension. Although in this work the calculations are restricted to the Canberra distance, the present approach may be applied to other distances to compare or validate the results. This work presents a contribution to model vulnerability to risks, providing to policy makers and stakeholders a tool to design, analyze and improve sustainability system by measuring its risks. The study of the contribution of each indicator suggests corrections to be taken and which indicators should be prioritized.     

A novel induction motor control scheme using IDA-PBC

A new control scheme for induction motors is proposed in the present paper, applying the interconnection and damping assignment-passivity based control （IDA-PBC） method. The scheme is based exclusively on passivity based control, without restricting the input frequency as it is done in field oriented control （FOC）. A port-controlled Hamiltonian （PCH） model of the induction motor is deduced to make the interconnection and damping of energy explicit on the scheme. The proposed controller is validated under computational simulations and experimental tests using an inverter prototype.     

Scientific productivity paradox: The case of China's S&T system

Summary In 1985 China began the reform of its Science & Technology (S&T) sector inherited from the planned economy. To disclose the impact of the drawn-out reform on the efficiency of the whole sector, we measure the scientific productivity of China's S&T institutes. The analysis is based on R&D input and output data at the country aggregate and provincial level. We utilize Polynomial Distributed Lag model to uncover the structure of the lag between R&D input and output. The findings reveal that the growth rate of scientific productivity of China's S&T institutes has been negative since the 1990s.     

GaiaDoc： A Tool Focused on Business Requirements for Code Documentation with a CMMI Compliant and RUP Based on Requirement Flow

Aiming to fill a gap in traditional methods of source code documentation, which focus mainly on the API （application programming interface） documentation for other programmers, this article presents a new approach for business requirements, mapping them through a set of annotations. These annotations, in turn, are interpreted by the GaiaDoc tool, which is specified in this paper and is able to generate documentation in form of use case specifications in a language and format easily understandable by the project stakeholders. Along with the GaiaDoc tool proposal, a RUP （rational unified process） based requirements flow is developed to fit with its needs and it is validated through CMMI （capability maturity model integration） requirement process areas and a case study of the proposed methodology＇s application is presented before the final considerations.