Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.

Integrated pulp and paper mill planning and scheduling

This article describes a real-world production planning and scheduling problem occurring at an integrated pulp and paper mill (P&P) which manufactures paper for cardboard out of produced pulp. During the cooking of wood chips in the digester, two by-products are produced: the pulp itself (virgin fibers) and the waste stream known as black liquor. The former is then mixed with recycled fibers and processed in a paper machine. Here, due to significant sequence-dependent setups in paper type changeovers, sizing and sequencing of lots have to be made simultaneously in order to efficiently use capacity. The latter is converted into electrical energy using a set of evaporators, recovery boilers and counter-pressure turbines. The planning challenge is then to synchronize the material flow as it moves through the pulp and paper mills, and energy plant, maximizing customer demand (as backlogging is allowed), and minimizing operation costs. Due to the intensive capital feature of P&P, the output of the digester must be maximized. As the production bottleneck is not fixed, to tackle this problem we propose a new model that integrates the critical production units associated to the pulp and paper mills, and energy plant for the first time. Simple stochastic mixed integer programming based local search heuristics are developed to obtain good feasible solutions for the problem. The benefits of integrating the three stages are discussed. The proposed approaches are tested on real-world data. Our work may help P&P companies to increase their competitiveness and reactiveness in dealing with demand pattern oscillations. (C) 2012 Elsevier Ltd. All rights reserved.

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012

Effects of extrusion, lipid concentration and purity on physico-chemical and biological properties of cationic liposomes for gene vaccine applications

We developed cationic liposomes containing DNA through a conventional process involving steps of (i) preformation of liposomes, (ii) extrusion, (iii) drying and rehydration and (iv) DNA complexation. Owing to its high prophylactic potentiality against tuberculosis, which had already been demonstrated in preclinical assays, we introduced modifications into the conventional process towards getting a simpler and more economical process for further scale-up. Elimination of the extrusion step, increasing the lipid concentration (from 16 to 64 mM) of the preformed liposomes and using good manufacturing practice bulk lipids (96-98% purity) instead of analytical grade purity lipids (99.9-100%) were the modifications studied. The differences in the physico-chemical properties, such as average diameter, zeta potential, melting point and morphology of the liposomes prepared through the modified process, were not as significant for the biological properties, such as DNA loading on the cationic liposomes, and effective immune response in mice after immunisation as the control liposomes prepared through the conventional process. Beneficially, the modified process increased productivity by 22% and reduced the cost of raw material by 75%.

Asynchronous teams for joint lot-sizing and scheduling problem in flow shops

The integrated production scheduling and lot-sizing problem in a flow shop environment consists of establishing production lot sizes and allocating machines to process them within a planning horizon in a production line with machines arranged in series. The problem considers that demands must be met without backlogging, the capacity of the machines must be respected, and machine setups are sequence-dependent and preserved between periods of the planning horizon. The objective is to determine a production schedule to minimise the setup, production and inventory costs. A mathematical model from the literature is presented, as well as procedures for obtaining feasible solutions. However, some of the procedures have difficulty in obtaining feasible solutions for large-sized problem instances. In addition, we address the problem using different versions of the Asynchronous Team (A-Team) approach. The procedures were compared with literature heuristics based on Mixed Integer Programming. The proposed A-Team procedures outperformed the literature heuristics, especially for large instances. The developed methodologies and the results obtained are presented.

Processing and mechanical properties evaluation of glass fiber-reinforced PTFE laminates

A specific manufacturing process to obtain continuous glass fiber-reinforced RIFE laminates was studied and some of their mechanical properties were evaluated. Young's modulus and maximum strength were measured by three-point bending test and tensile test using the Digital Image Correlation (DIC) technique. Adhesion tests, thermal analysis and microscopy were used to evaluate the fiber-matrix adhesion, which is very dependent on the sintering time. The composite material obtained had a Young's modulus of 14.2 GPa and ultimate strength of 165 MPa, which corresponds to approximately 24 times the modulus and six times the ultimate strength of pure RIFE. These results show that the RIFE composite, manufactured under specific conditions, has great potential to provide structural parts with a performance suitable for application in structural components. (C) 2012 Elsevier Ltd. All rights reserved.

Biotechnological Utilization of Biodiesel-Derived Glycerol for the Production of Ribonucleotides and Microbial Biomass

Ten yeast strains were evaluated concerning their capabilities to assimilate biodiesel-derived glycerol in batch cultivation. The influence of glycerol concentration, temperature, pH and yeast extract concentration on biomass production was studied for the yeast selected. Further, the effect of agitation on glycerol utilization by the yeast Hansenula anomala was also studied. The yeast H. anomala CCT 2648 showed the highest biomass yield (0.30 g g(-1)) and productivity (0.19 g L-1 h(-1)). Citric acid, succinic acid, acetic acid and ethanol were found as the main metabolites produced. The increase of yeast extract concentration from 1 to 3 g L-1 resulted in high biomass production. The highest biomass concentration (21 g L-1), yield (0.45 g g(-1)) and productivity (0.31 g L-1 h(-1)), as well as ribonucleotide production (13.13 mg g(-1)), were observed at 700 rpm and 0.5 vvm. These results demonstrated that glycerol from biodiesel production process showed to be a feasible substrate for producing biomass and ribonucleotides by yeast species.

Guava pomace: a new source of anti-inflammatory and analgesic bioactives

Abstract Background Guava pomace is an example of the processing waste generated after the manufacturing process from the juice industry that could be a source of bioactives. Thus, the present investigation was carried out in order to evaluate the anti-inflammatory and antinociceptive potential and determinate the main phenolic compounds of a guava pomace extract (GPE). Methods The anti-inflammatory activity was evaluated by carrageenan, dextran, serotonin, histamine-induced paw edema and neutrophils migration in the peritoneal cavity models. Acetic acid-induced abdominal writhing and formalin test were performed to investigate the antinociceptive effects. In addition, the content of total phenolic and of individual phenolic compounds was determined by GC/MS. Results GPE showed anti-inflammatory activity by carrageenan, dextran, serotonin, histamine-induced paw edema and neutrophils migration in the peritoneal cavity models (p < 0.05). GPE also demonstrated antinociceptive activity by acetic acid-induced abdominal writhing and formalin test (p < 0.05). The total phenolic value was 3.40 ± 0.09 mg GAE/g and epicatechin, quercetin, myricetin, isovanilic and gallic acids were identified by GC/MS analysis. Conclusions The presence of bioactive phenolic compounds as well as important effects demonstrated in animal models suggest that guava pomace could be an interesting source of anti-inflammatory and analgesic substances.