Influence of Lean and Green on supply chain performance: an interpretive structural modelling model

This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

Projeto de estrutura variante de um edifício de escritórios em Lisboa

Trabalho de Projecto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

Projeto de fundações e estrutura de um edifício de 3 pisos em Lisboa, destinado a habitação

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

Projeto de estrutura variante de um edifício de habitação na zona de Lisboa

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

Projeto de fundações e estrutura de um edifício em Lisboa

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas

Designing next generation car washing machines with rotary brushes

Tese de Doutoramento - Leaders for Technical Industries (LTI) - MIT Portugal

Definição de indicadores para estimar custos de projeto e análise paramétrica dos eurocódigos estruturais

Dissertação de mestrado integrado em Engenharia Civil

The anabolic androgenic steroid fluoxymesterone inhibits 11β-hydroxysteroid dehydrogenase 2-dependent glucocorticoid inactivation.

Anabolic androgenic steroids (AAS) are testosterone derivatives used either clinically, in elite sports, or for body shaping with the goal to increase muscle size and strength. Clinically developed compounds and nonclinically tested designer steroids often marketed as food supplements are widely used. Despite the considerable evidence for various adverse effects of AAS use, the underlying molecular mechanisms are insufficiently understood. Here, we investigated whether some AAS, as a result of a lack of target selectivity, might inhibit 11β-hydroxysteroid dehydrogenase 2 (11β-HSD2)-dependent inactivation of glucocorticoids. Using recombinant human 11β-HSD2, we observed inhibitory effects for several AAS. Whereas oxymetholone, oxymesterone, danazol, and testosterone showed medium inhibitory potential, fluoxymesterone was a potent inhibitor of human 11β-HSD2 (half-maximal inhibitory concentration [IC(50)] of 60-100nM in cell lysates; IC(50) of 160nM in intact SW-620, and 530nM in MCF-7 cells). Measurements with rat kidney microsomes and lysates of cells expressing recombinant mouse 11β-HSD2 revealed much weaker inhibition by the AAS tested, indicating that the adverse effects of AAS-dependent 11β-HSD2 inhibition cannot be investigated in rats and mice. Furthermore, we provide evidence that fluoxymesterone is metabolized to 11-oxofluoxymesterone by human 11β-HSD2. Structural modeling revealed similar binding modes for fluoxymesterone and cortisol, supporting a competitive mode of inhibition of 11β-HSD2-dependent cortisol oxidation by this AAS. No direct modulation of mineralocorticoid receptor (MR) function was observed. Thus, 11β-HSD2 inhibition by fluoxymesterone may cause cortisol-induced MR activation, thereby leading to electrolyte disturbances and contributing to the development of hypertension and cardiovascular disease.

Activity of ancestral restriction factors against ancient retroviruses

Analysis of TRIM5α and APOBEC3G genes suggests that these two restriction factors underwent strong positive selection throughout primate evolution. This pressure was possibly imposed by ancient exogenous retroviruses, of which endogenous retroviruses are remnants. Our study aims to assess in vitro the activity of these factors against ancient retroviruses by reconstructing their ancestral gag sequences, as well as the ancestral TRIM5α and APOBEC3G for primates. Based on evolutionary genomics approach, we reconstructed ancestors of the two largest families of human endogenous retroviruses (HERV), namely HERV-K and HERV-H, as well as primate ancestral TRIM5α and APOBEC3G variants. The oldest TRIM5α sequence was the catarhinne TRIM5α, common ancestor of Old World monkeys and hominoids, dated from 25 million years ago (mya). From the oldest, to the youngest, ancestral TRIM5α variants showed less restriction of HIV-1 in vitro [1]. Likewise three ancestral APOBEC3Gs sequences common to hominoids (18 mya), Old World monkeys, and catarhinnes (25 mya) were reconstructed. All ancestral APOBEC3G variants inhibited efficiently HIV-1Δvif in vitro, compared to modern APOBEC3Gs. The ability of Vif proteins (HIV-1, HIV-2, SIVmac and SIVagm) to counteract their activity tallied with the residue 128 on ancestral APOBEC3Gs. Moreover we are attempting to reconstruct older ancestral sequences of both restriction factors by using prosimian orthologue sequences. An infectious onemillion- years-old HERV-KCON previously reconstituted was shown to be resistant to modern TRIM5α and APOBEC3G [2]. Our ancestral TRIM5α and APOBEC3G variants were inactive against HERV-KCON. Besides we reconstructed chimeric HERV-K bearing ancestral capsids (up to 7 mya) that resulted in infectious viruses resistant to modern and ancestral TRIM5α. Likewise HERV-K viruses bearing ancestral nucleocapsids will be tested for ancestral and modern APOBEC3G restriction. In silico reconstruction and structural modeling of ancestral HERV-H capsids resulted in structures homologous to that of the gammaretrovirus MLV. Thus we are attempting to construct chimeric MLV virus bearing HERV-H ancestral capsids. These chimeric ancestral HERVs will be tested for infectivity and restriction by ancestral TRIM5α. Similarly chimeric MLV viruses bearing ancestral HERV-H nucleocapsids will be reconstructed and tested for APOBEC3G restriction.

Characterization of a plant-derived peptide displaying water clarifying and antimicrobial activities

SUMMARY Drinking water is currently a scarce world resource, the preparation of which requires complex treatments that include clarification of suspended particles and disinfection. Seed extracts of Moringa oleifera Lam., a tropical tree, have been proposed as an environment- friendly alternative, due to their traditional use for the clarification of drinking water. However, the precise nature of the active components was unknown. Here, we show that recombinant or synthetic forms of a cationic seed polypeptide mediate efficient sedimentation of suspended mineral particles and bacteria. Unexpectedly, the polypeptide was also found to possesses a bactericidal activity capable of disinfecting heavily contaminated water. Furthermore, the polypeptide has been shown to efficiently kill several pathogenic bacteria, including antibiotic-resistant isolates of Pseudomona, Streptococcus and Legionella species. Structural modeling of the peptide coupled to the functional analysis of synthetic peptide derivatives delineated distinct structural determinants for the flocculation and antibacterial activities. Our results suggest that a glutamine-rich portion of the polypeptide is involved in the sedimentation process; alternatively, the antibacterial activity depends on a amphiphilic loop. Assembly of multiple copies of this loop into a branched peptide derivative strongly enhances antibacterial activity without displaying hemolytic effect. In conclusion, this polypeptide displays the unprecedented feature of combining efficient water purification and disinfectant properties indicating different molecular mechanisms involved in each case. This work not only identified the features responsible for these activities but also provides useful information that has implications for the further development of this cationic polypeptide as a potent antibacterial agent. RESUME L'eau potable est actuellement une ressource limitée dans le monde. La production d'eau propre à la consommation exige des traitements complexes, incluant la clarification des particules en suspension ainsi que sa désinfection par des additifs chimiques. Les extraits de la graine d'un arbre tropical, Moringa oleifera, sont utilisés traditionnellement en Afrique afin de clarifier l'eau. Quoique la nature exacte des composants actifs était inconnue, on a pu mettre en évidence un polypeptide cationique contenu dans ces graines, capable de sédimenter de manière efficace des particules minérales en suspension ainsi que des bactéries. Ce travail a aussi mis en évidence que ce polypeptide a une activité bactéricide, permettant une désinfection d'eau fortement contaminée. De plus, nous avons démontré que ce polypeptide est efficace contre de nombreuses souches bactériennes pathogènes, également celles résistantes aux antibiotiques comme Pseudomonas, Streptococcus et Legionella. L'analyse de la structure moléculaire de ce polypeptide, couplée à son analyse fonctionnelle a mis en évidence deux domaines structuraux distinct, un pour l'activité de floculation et l'autre pour l'activité antibactérienne. Nos résultats suggèrent que le domaine riche en glutamine est impliqué dans le processus de sédimentation et que l'activité antimicrobienne dépend d'un domaine formant une boucle amphiphilique. En ramifiant plusieurs copies de cette boucle on a pu augmenter de manière significative l'activité antibactérienne. En conclusion, nous avons pu démontrer que ce polypeptide à la capacité unique de combiner des propriétés de purification et de désinfection de l'eau, ce qui implique des mécanismes moléculaires distincts pour ces deux activités. Ce travail a permis d'identifier les domaines du polypeptide qui sont responsables de ses activités et offre une perspective pour le développement d'un nouvel agent antimicrobien.

Diagnostic techniques applied in geostatistics for agricultural data analysis

The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.