Characterization, development and multiplexing of microsatellite markers in three commercially exploited reef fish and their application for stock identification

Thirty-four microsatellite loci were isolated from three reef fish species; golden snapper Lutjanus johnii, blackspotted croaker Protonibea diacanthus and grass emperor Lethrinus laticaudis using a next generation sequencing approach. Both IonTorrent single reads and Illumina MiSeq paired-end reads were used, with the latter demonstrating a higher quality of reads than the IonTorrent. From the 1–1.5 million raw reads per species, we successfully obtained 10–13 polymorphic loci for each species, which satisfied stringent design criteria. We developed multiplex panels for the amplification of the golden snapper and the blackspotted croaker loci, as well as post-amplification pooling panels for the grass emperor loci. The microsatellites characterized in this work were tested across three locations of northern Australia. The microsatellites we developed can detect population differentiation across northern Australia and may be used for genetic structure studies and stock identification.

A Multifaceted Study of Scedosporium boydii Cell Wall Changes during Germination and Identification of GPI-Anchored Proteins

International audience

Regulatory governance of ‘training markets’, ‘market failure’, and ‘quasi’ markets: historical dimensions of the post-initial training market in the Netherlands

This article examines regulatory governance of the post-initial training market in The Netherlands. From an historical perspective on policy formation processes, it examines market formation in terms of social, economic, and cultural factors in the development of provision and demand for post-initial training; the roles of stakeholders in the longterm construction of regulatory governance of the market; regulation of and public providers; policy responses to market failure; and tripartite division of responsibilities between the state, social partners, commercial and publicly-funded providers. Historical description and analysis examine policy narratives of key stakeholders with reference to: a) influence of societal stakeholders on regulatory decision-making; b) state regulation of the post-initial training market; c) public intervention regulating the market to prevent market failure; d) market deregulation, competition, employability and individual responsibility; and, e) regulatory governance to prevent ‘allocative failure’ by the market in non-delivery of post-initial training to specific target groups, particularly the low-qualified. Dominant policy narratives have resulted in limited state regulation of the supply-side, a tripartite system of regulatory governance by the state, social partners and commercial providers as regulatory actors. Current policy discourses address interventions on the demand-side to redistribute structures of opportunity throughout the life courses of individuals. Further empirical research from a comparative historical perspective is required to deepen contemporary understandings of regulatory governance of markets and the commodification of adult learning in knowledge societies and information economies. (DIPF/Orig.)

Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

Animal welfare issues have received much attention not only to supply farmed animal requirements, but also to ethical and cultural public concerns. Daily collected information, as well as the systematic follow-up of production stages, produces important statistical data for production assessment and control, as well as for improvement possibilities. In this scenario, this research study analyzed behavioral, production, and environmental data using Main Component Multivariable Analysis, which correlated observed behaviors, recorded using video cameras and electronic identification, with performance parameters of female broiler breeders. The aim was to start building a system to support decision-making in broiler breeder housing, based on bird behavioral parameters. Birds were housed in an environmental chamber, with three pens with different controlled environments. Bird sensitivity to environmental conditions were indicated by their behaviors, stressing the importance of behavioral observations for modern poultry management. A strong association between performance parameters and the behavior at the nest, suggesting that this behavior may be used to predict productivity. The behaviors of ruffling feathers, opening wings, preening, and at the drinker were negatively correlated with environmental temperature, suggesting that the increase of in the frequency of these behaviors indicate improvement of thermal welfare.

The identification and differentiation of the Candida parapsilosis complex species by polymerase chain reaction-restriction fragment length polymorphism of the internal transcribed spacer region of the rDNA

Currently, it is accepted that there are three species that were formerly grouped under Candida parapsilosis : C. parapsilosis sensu stricto, Candida orthopsilosis , and Candida metapsilosis . In fact, the antifungal susceptibility profiles and distinct virulence attributes demonstrate the differences in these nosocomial pathogens. An accurate, fast, and economical identification of fungal species has been the main goal in mycology. In the present study, we searched sequences that were available in the GenBank database in order to identify the complete sequence for the internal transcribed spacer (ITS)1-5.8S-ITS2 region, which is comprised of the forward and reverse primers ITS1 and ITS4. Subsequently, an in silico polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was performed to differentiate the C. parapsilosis complex species. Ninety-eight clinical isolates from patients with fungaemia were submitted for analysis, where 59 isolates were identified as C. parapsilosis sensu stricto, 37 were identified as C. orthopsilosis, and two were identified as C. metapsilosis. PCR-RFLP quickly and accurately identified C. parapsilosis complex species, making this method an alternative and routine identification system for use in clinical mycology laboratories.

Metodología Demand Driven para mejora de servicio y reducción de costos

Actualmente, para la planeación de la cadena de suministro, las organizaciones utilizan métodos convencionales basados en modelos estadísticos que miran el pasado y no reconocen avances -- Con este estudio se busca proyectar el futuro estos procesos -- Para lograrlo se tiene en cuenta la metodología Demand Driven que, para cambiar esta situación, basa su teoría en la adaptación de la cadena logística para reaccionar ante la venta en tiempo real, mediante la organización de buffers o pequeñas cajas de inventario que según las características de la cadena tendrán distintas propiedades para garantizar siempre la disponibilidad de stock, al menor coste y cantidad posible -- Se pretende demostrar la metodología mediante un caso de empresa: la viabilidad del sistema para garantizar la reducción del capital invertido en inventarios, garantizando mayor flujo de capital para inversión en nuevos aspectos; se presupone mejora en servicio que se traduce en mayores ventas para la compañía y reducción de costos al tener menor nivel de inventarios -- Al realizar el ejemplo empresarial, este estudio entrega a los líderes de las organizaciones las herramientas necesarias para toma de decisiones sobre cambios estructurales en la forma de realizar su proceso de planeación y ventas operacionales en busca de adaptaciones a las necesidades del mercado cambiante y exigente en el que vivimos hoy, donde los consumidores buscan bajo costo, alta calidad y disponibilidad a la mano -- En este estudio se puede observar cómo se pueden incrementar los ingresos en un 20% con sólo mejorar el nivel de servicio y entregas a tiempo a los clientes

Household portfolio allocation, risk attitudes and credit constraints : evidence from the eurozone

Mestrado em Economia Monetária e Financeira

Corporate governance : value creation and performance in credit unions

In this study, we examine the relationship between good corporate governance practices and the creation of value/performance of credit unions from 2010 to 2012. The objective was to create and validate a corporate governance index for credit unions, and to then analyse the relationship between good governance practices and the creation of value/performance. The problem question is: do good corporate governance practices provide value creation for credit unions? The research started by creating indices from factor analysis to identify latent dependent variables related to value creation and performance; next indices were created from the principal component analysis for the creation of independent latent variables related to corporate governance. Finally, based on panel data from regression models, the influence of the variables and indices related to corporate governance on the indices of value creation and performance was verified. Based on the research, it became evident that the Corporate Governance Index (IGC) is mainly impacted by Executive Management, with 40.31% of the IGC value, followed by the Representation and Participation dimension, with 34.07% of the IGC value. The contribution for academics was the creation of the Corporate Governance Index (IGC) applied for credit unions. As for the contribution to the system of credit unions, the highlight was the effectiveness of the mechanisms for economic-financial and asset management adopted by BACEN, credit unions and OCEMG.

Mobilizing Greater Crop and Land Potentials Sustainably

The supply side of the food security engine is the way we farm. The current engine of conventional tillage farming is faltering and needs to be replaced. This presentation will address supply side issues of agriculture to meet future agricultural demands for food and industry using the alternate no-till Conservation Agriculture (CA) paradigm (involving no-till farming with mulch soil cover and diversified cropping) that is able to raise productivity sustainably and efficiently, reduce inputs, regenerate degraded land, minimise soil erosion, and harness the flow of ecosystem services. CA is an ecosystems approach to farming capable of enhancing not only the economic and environmental performance of crop production and land management, but also promotes a mindset change for producing ‘more from less’, the key attitude towards sustainable production intensification. CA is now spreading globally in all continents at an annual rate of 10 Mha and covers some 157 Mha of cropland. Today global agriculture produces enough food to feed three times the current population of 7.21 billion. In 1976, when the world population was 4.15 billion, world food production far exceeded the amount necessary to feed that population. However, our urban and industrialised lifestyle leads to wastage of food of some 30%-40%, as well as waste of enormous amount of energy and protein while transforming crop-based food into animal-derived food; we have a higher proportion of people than ever before who are obese; we continue to degrade our ecosystems including much of our agricultural land of which some 400 Mha is reported to be abandoned due to severe soil and land degradation; and yields of staple cereals appear to have stagnated. These are signs of unsustainability at the structural level in the society, and it is at the structural level, for both supply side and demand side, that we need transformed mind sets about production, consumption and distribution. CA not only provides the possibility of increased crop yields for the low input smallholder farmer, it also provides a pro-poor rural and agricultural development model to support agricultural intensification in an affordable manner. For the high output farmer, it offers greater efficiency (productivity) and profit, resilience and stewardship. For farming anywhere, it addresses the root causes of agricultural land degradation, sub-optimal ecological crop and land potentials or yield ceilings, and poor crop phenotypic expressions or yield gaps. As national economies expand and diversify, more people become integrated into the economy and are able to access food. However, for those whose livelihoods continue to depend on agriculture to feed themselves and the rest of the world population, the challenge is for agriculture to produce the needed food and raw material for industry with minimum harm to the environment and the society, and to produce it with maximum efficiency and resilience against abiotic and biotic stresses, including those arising from climate change. There is growing empirical and scientific evidence worldwide that the future global supplies of food and agricultural raw materials can be assured sustainably at much lower environmental and economic cost by shifting away from conventional tillage-based food and agriculture systems to no-till CA-based food and agriculture systems. To achieve this goal will require effective national and global policy and institutional support (including research and education).

Simulation of the nutrient supply in fracture healing

The healing process for bone fractures is sensitive to mechanical stability and blood supply at the fracture site. Most currently available mechanobiological algorithms of bone healing are based solely on mechanical stimuli, while the explicit analysis of revascularization and its influences on the healing process have not been thoroughly investigated in the literature. In this paper, revascularization was described by two separate processes: angiogenesis and nutrition supply. The mathematical models for angiogenesis and nutrition supply have been proposed and integrated into an existing fuzzy algorithm of fracture healing. The computational algorithm of fracture healing, consisting of stress analysis, analyses of angiogenesis and nutrient supply, and tissue differentiation, has been tested on and compared with animal experimental results published previously. The simulation results showed that, for a small and medium-sized fracture gap, the nutrient supply is sufficient for bone healing, for a large fracture gap, non-union may be induced either by deficient nutrient supply or inadequate mechanical conditions. The comparisons with experimental results demonstrated that the improved computational algorithm is able to simulate a broad spectrum of fracture healing cases and to predict and explain delayed unions and non-union induced by large gap sizes and different mechanical conditions. The new algorithm will allow the simulation of more realistic clinical fracture healing cases with various fracture gaps and geometries and may be helpful to optimise implants and methods for fracture fixation.

Improved detection and tracking of objects in surveillance video

Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

Innovation and the city : a macromarketing approach to industry development

Purpose – The purpose of this paper is to propose and demonstrate the relevance of marketing systems, notably the process of product management and innovation, to urban development challenges. Design/methodology/approach – A macromarketing perspective is adopted to construe the city as a product and begin the application of the innovation process to urban management, following the steps commonly proposed for successful innovation in product management. An example of the application of the initial new product development steps of idea generation and opportunity identification is presented. Findings – The innovation process provides guidelines and checkpoints that enable corporations to improve the success rate of their development initiatives. Cities, like corporations, need to innovate in order to maintain their image and functionality, to provide a myriad benefits to their stakeholders and, thereby, to survive and grow. The example here shows how the preliminary NPD steps of idea generation and opportunity identification enrich the process of identifying and analysing new industry opportunities for a city. Practical implications – By conceptualising the city as a multifaceted product, the disciplined planning and evaluation processes pertinent to NPD success become relevant and helpful to practitioners responsible for urban planning, urban development and change. Originality/value – The paper shows how pertinent concepts and processes from marketing can be effectively applied to urban planning and economic development initiatives.