Systems Thinking and Scenario Planning: Application in the Clothing Sector

Industrial sectors that operate in uncertain environments - with demand variability, product seasonality and different industrialisation structures - need studies that enable identification and forecast trends. Therefore, the development of competitiveness extends beyond a company’s individual performance. Collective action, whether toward consumer markets, supplier markets, competitors and substitutes, can reinforce or help reformulate the current practices of an organisation, besides providing better results in the development of strategies and competitive positioning. Thus, clothing, the sector addressed in this work, is characterised by a long, fragmented, heterogeneous production chain, the competitiveness of which is linked to product differentiation. Therefore, the use of systemic approaches to study this sector is effective. In this sense, this research aims at adapting Systems Thinking and Scenario Planning (STSP) so that it supports the development and planning process in a given sector. Thus, this research applies STSP adapted to an analysis of the clothing sector in the northern region of Rio Grande do Sul State, Brazil. As a result, in academic terms, this research proposed and validated a method for analysing industrial sectors of the clothing industry. In the sectoral context, this research identified elements that leverage the sector’s competitiveness, besides generating knowledge and learning aimed at strengthening the sectoral structure identified, and fostering the formation of a new clothing cluster.     

Historical review and redescription of three poorly known species of the catfish genus Trichomycterus from south-eastern Brazil (Siluriformes: Trichomycteridae)

ABSTRACT

This study is primarily directed to the most poorly known species of the genus Trichomycterus, comprising five nominal species (T. florensis, T. immaculatus, T. nigricans, T. paquequerensis and T. santaeritae) endemic to south-eastern Brazil. One of them, T. nigricans, is the type species of the genus, involved in taxonomic problems for over 150 years. A detailed historical review, accompanied by examination of type specimens and recent collections, revealed that the correct type locality of T. nigricans is in the vicinity of Rio de Janeiro, not Santa Catarina as commonly appears in the literature; specimens previously misidentified as T. nigricans from Santa Catarina belong to a possibly undescribed species of the genus Cambeva; T. paquequerensis is a synonym of T. immaculatus, and T. florensis is a synonym of T. santaeritae; and the hypothesis that T. santaeritae is closely related to the Amazon Sarcoglanidinae is refuted. The three valid species are redescribed. These species are members of a clade also including T. caipora that is highly supported by molecular data, diagnosed by a pronounced posterior maxillary process and caudal fin emarginate at least in larger specimens. A subclade comprising T. caipora, T. nigricans and T. santaeritae is diagnosed by a long maxilla and a bifid anterior extremity of hypobranchial 3.     

Non-random coextinctions in phylogenetically structured mutualistic networks

The interactions between plants and their animal pollinators and seed dispersers have moulded much of Earth's biodiversity. Recently, it has been shown that these mutually beneficial interactions form complex networks with a well-defined architecture that may contribute to biodiversity persistence. Little is known, however, about which ecological and evolutionary processes generate these network patterns. Here we use phylogenetic methods to show that the phylogenetic relationships of species predict the number of interactions they exhibit in more than one-third of the networks, and the identity of the species with which they interact in about half of the networks. As a consequence of the phylogenetic effects on interaction patterns, simulated extinction events tend to trigger coextinction cascades of related species. This results in a non-random pruning of the evolutionary tree and a more pronounced loss of taxonomic diversity than expected in the absence of a phylogenetic signal. Our results emphasize how the simultaneous consideration of phylogenetic information and network architecture can contribute to our understanding of the structure and fate of species-rich communities.     

Ranbp2 haploinsufficiency mediates distinct cellular and biochemical phenotypes in brain and retinal dopaminergic and glia cells elicited by the Parkinsonian neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)

Many components and pathways transducing multifaceted and deleterious effects of stress stimuli remain ill-defined. The Ran-binding protein 2 (RanBP2) interactome modulates the expression of a range of clinical and cell-context-dependent manifestations upon a variety of stressors. We examined the role of Ranbp2 haploinsufficiency on cellular and metabolic manifestations linked to tyrosine-hydroxylase (TH(+)) dopaminergic neurons and glial cells of the brain and retina upon acute challenge to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), a parkinsonian neurotoxin, which models facets of Parkinson disease. MPTP led to stronger akinetic parkinsonism and slower recovery in Ranbp2 (+/-) than wild-type mice without viability changes of brain TH(+)-neurons of either genotype, with the exception of transient nuclear atypia via changes in chromatin condensation of Ranbp2 (+/-) TH(+)-neurons. Conversely, the number of wild-type retinal TH(+)-amacrine neurons compared to Ranbp2 (+/-) underwent milder declines without apoptosis followed by stronger recoveries without neurogenesis. These phenotypes were accompanied by a stronger rise of EdU(+)-proliferative cells and non-proliferative gliosis of GFAP(+)-Müller cells in wild-type than Ranbp2 (+/-) that outlasted the MPTP-insult. Finally, MPTP-treated wild-type and Ranbp2 (+/-) mice present distinct metabolic footprints in the brain or selective regions thereof, such as striatum, that are supportive of RanBP2-mediated regulation of interdependent metabolic pathways of lysine, cholesterol, free-fatty acids, or their β-oxidation. These studies demonstrate contrasting gene-environment phenodeviances and roles of Ranbp2 between dopaminergic and glial cells of the brain and retina upon oxidative stress-elicited signaling and factors triggering a continuum of metabolic and cellular manifestations and proxies linked to oxidative stress, and chorioretinal and neurological disorders such as Parkinson.     

Toxin bioportides: exploring toxin biological activity and multifunctionality

Toxins have been shown to have many biological functions and to constitute a rich source of drugs and biotechnological tools. We focus on toxins that not only have a specific activity, but also contain residues responsible for transmembrane penetration, which can be considered bioportides—a class of cell-penetrating peptides that are also intrinsically bioactive. Bioportides are potential tools in pharmacology and biotechnology as they help deliver substances and nanoparticles to intracellular targets. Bioportides characterized so far are peptides derived from human proteins, such as cytochrome c (CYCS), calcitonin receptor (camptide), and endothelial nitric oxide synthase (nosangiotide). However, toxins are usually disregarded as potential bioportides. In this review, we discuss the inclusion of some toxins and molecules derived thereof as a new class of bioportides based on structure activity relationship, minimization, and biological activity studies. The comparative analysis of the amino acid residue composition of toxin-derived bioportides and their short molecular variants is an innovative analytical strategy which allows us to understand natural toxin multifunctionality in vivo and plan novel pharmacological and biotechnological products. Furthermore, we discuss how many bioportide toxins have a rigid structure with amphiphilic properties important for both cell penetration and bioactivity.     

Snake venom thrombin-like enzymes: from reptilase to now

The snake venom thrombin-like enzymes (SVTLEs) comprise a number of serine proteases functionally and structurally related to thrombin. Until recently, only nine complete sequences of this subgroup of the serine protease family were known. Over the past 5 years, the primary structure of several SVTLEs has been characterized, and now this family includes several members. Of particular interest is their possible use in pathologies such as thrombosis. The aim of the present review is to summarize the state of the art concerning the evolutionary, structural and biological features of the SVTLEs.Received 16 August 2003; received after revision 26 September 2003; accepted 1 October 2003     

A high-velocity black hole on a Galactic-halo orbit in the solar neighbourhood

Only a few of the dozen or so known stellar-mass black holes have been observed away from the plane of the Galaxy. Those few could have been ejected from the plane as a result of a 'kick' received during a supernova explosion, or they could be remnants of the population of massive stars formed in the early stages of evolution of the Galaxy. Determining their orbital motion should help to distinguish between these options. Here we report the transverse motion (in the plane of the sky) for the black-hole X-ray nova XTE J1118+480 (refs 2, 3, 4, 5), from which we derive a large space velocity. This X-ray binary system has an eccentric orbit around the Galactic Centre, like most objects in the halo of the Galaxy, such as ancient stars and globular clusters. The properties of the system suggest that its age is comparable to or greater than the age of the Galactic disk. Only an extraordinary 'kick' from a supernova could have launched the black hole into an orbit like this from a birthplace in the disk of the Galaxy.     

Serotype-independent pneumococcal vaccines

Streptococcus pneumoniae remains an important cause of disease with high mortality and morbidity, especially in children and in the elderly. The widespread use of the polysaccharide conjugate vaccines in some countries has led to a significant decrease in invasive disease caused by vaccine serotypes, but an increase in disease caused by non-vaccine serotypes has impacted on the overall efficacy of these vaccines on pneumococcal disease. The obvious solution to overcome such shortcomings would be the development of new formulations that provide serotype-independent immunity. This review focuses on the most promising approaches, including protein antigens, whole cell pneumococcal vaccines, and recombinant bacteria expressing pneumococcal antigens. The protective capacity of these vaccine candidates against the different stages of pneumococcal infection, including colonization, mucosal disease, and invasive disease in animal models is reviewed. Some of the human trials that have already been performed or that are currently ongoing are presented. Finally, the feasibility and the possible shortcomings of these candidates in relation to an ideal vaccine against pneumococcal infections are discussed.     

Probability distributions,trading strategies and leverage: an application of Gaussian mixture models

The purpose of this paper is twofold. Firstly, to assess the merit of estimating probability density functions rather than level or classification estimations on a one‐day‐ahead forecasting task of the EUR/USD time series. This is implemented using a Gaussian mixture model neural network, benchmarking the results against standard forecasting models, namely a naïve model, a moving average convergence divergence technical model (MACD), an autoregressive moving average model (ARMA), a logistic regression model (LOGIT) and a multi‐layer perceptron network (MLP). Secondly, to examine the possibilities of improving the trading performance of those models with confirmation filters and leverage. While the benchmark models perform best without confirmation filters and leverage, the Gaussian mixture model outperforms all of the benchmarks when taking advantage of the possibilities offered by a combination of more sophisticated trading strategies and leverage. This might be due to the ability of the Gaussian mixture model to identify successfully trades with a high Sharpe ratio. Copyright © 2004 John Wiley & Sons, Ltd.