48 resultados para Early Devonian


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This paper explores ecodesign within the product development process (PDP), particularly focusing on the design stages. Previous research has highlighted the early stages as the 'best' place to integrate environmental issues. Here the early stage hypothesis is explored from the perspective of the industrial design department - the early stage designers. Being located at the earliest possible design stages of product development would mean that, were the hypothesis to hold true, industrial design would be the 'best' place to locate ecodesign. Empirical research was conducted with the Industrial Design Centre (IDC) of a global Electrical and Electronic goods manufacture. It used a qualitative, inductive research methodology, based on two 'live' design concept projects, participant observation within the department, and on several semi-structured interviews. Throughout this paper, the empirical work is compared and contrasted to ecodesign literature, specifically to models of ecodesign innovation and the product development process. Beginning by exploring of the early stage hypothesis, the paper concludes with a conceptual model of early stage ecodesign for the context in question.

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The plant circadian clock is proposed to be a network of several interconnected feedback loops, and loss of any component leads to changes in oscillator speed. We previously reported that Arabidopsis thaliana EARLY FLOWERING4 (ELF4) is required to sustain this oscillator and that the elf4 mutant is arrhythmic. This phenotype is shared with both elf3 and lux. Here, we show that overexpression of either ELF3 or LUX ARRHYTHMO (LUX) complements the elf4 mutant phenotype. Furthermore, ELF4 causes ELF3 to form foci in the nucleus. We used expression data to direct a mathematical position of ELF3 in the clock network. This revealed direct effects on the morning clock gene PRR9, and we determined association of ELF3 to a conserved region of the PRR9 promoter. A cis-element in this region was suggestive of ELF3 recruitment by the transcription factor LUX, consistent with both ELF3 and LUX acting genetically downstream of ELF4. Taken together, using integrated approaches, we identified ELF4/ELF3 together with LUX to be pivotal for sustenance of plant circadian rhythms. © 2012 American Society of Plant Biologists.

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While tools have been developed to assist firms' decision making for bringing known products and components into the supply chain, fewer tools are available to guide the acquisition of earlier-stage technologies, which is a riskier proposition due to higher technological and market uncertainties. Through synthesis of literature in technology sourcing, open innovation, alliances, mergers and acquisitions, outsourcing, and technology and knowledge transfer and consultation with industry, this paper identifies critical issues that decision makers should consider before making an early-stage technology acquisition. Sixteen questions emerge to guide decision making, comprising internal, technology, and partner assessments. These questions allow a firm to disentangle the complexity of early-stage technology acquisitions and select the most appropriate targets.

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Innovation is a critical factor in ensuring commercial success within the area of medical technology. Biotechnology and Healthcare developments require huge financial and resource investment, in-depth research and clinical trials. Consequently, these developments involve a complex multidisciplinary structure, which is inherently full of risks and uncertainty. In this context, early technology assessment and 'proof of concept' is often sporadic and unstructured. Existing methodologies for managing the feasibility stage of medical device development are predominantly suited to the later phases of development and favour detail in optimisation, validation and regulatory approval. During these early phases, feasibility studies are normally conducted to establish whether technology is potentially viable. However, it is not clear how this technology viability is currently measured. This paper aims to redress this gap through the development of a technology confidence scale, as appropriate explicitly to the feasibility phase of medical device design. These guidelines were developed from analysis of three recent innovation studies within the medical device industry.

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Scalable growth is essential for graphene-based applications. Recent development has enabled the achievement of the scalability by use of chemical vapor deposition (CVD) at 1000°C with copper as a catalyst and methane as a precursor gas. Here we report our observation of early stage of graphene growth based on an ethylene-based CVD method, capable of reducing the growth temperature to 770°C for monolayer graphene growth on copper. We track the early stages of slow growth under low ethylene flow rate and observe the graphene domain evolution by varying the temperature and growth time. Temperature-dependence of graphene domain density gives an apparent activation energy of 1.0 eV for nucleation.

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We present a model for early vision tasks such as denoising, super-resolution, deblurring, and demosaicing. The model provides a resolution-independent representation of discrete images which admits a truly rotationally invariant prior. The model generalizes several existing approaches: variational methods, finite element methods, and discrete random fields. The primary contribution is a novel energy functional which has not previously been written down, which combines the discrete measurements from pixels with a continuous-domain world viewed through continous-domain point-spread functions. The value of the functional is that simple priors (such as total variation and generalizations) on the continous-domain world become realistic priors on the sampled images. We show that despite its apparent complexity, optimization of this model depends on just a few computational primitives, which although tedious to derive, can now be reused in many domains. We define a set of optimization algorithms which greatly overcome the apparent complexity of this model, and make possible its practical application. New experimental results include infinite-resolution upsampling, and a method for obtaining subpixel superpixels. © 2012 IEEE.

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Increasing product life allows the embodied emissions in products to be spread across a longer period but can mean that opportunities to improve use-phase efficiency are foregone. In this paper, a model that evaluates this trade-off is presented and used to estimate the optimal product life for a range of metal-intensive products. Two strategies that have potential to save emissions are explored: (1) adding extra embodied emissions to make products more sturdy, increasing product life, and (2) increasing frequency of use, causing early product failure to take advantage of improvements in use-phase efficiency. These strategies are evaluated for two specific case studies (long-life washing machines and more frequent use of vehicles through car clubs) and for a range of embodied and use-phase intensive products under different use-phase improvement rate assumptions. Particular emphasis is placed on the fact that products often fail neither at their design life nor at their optimal life. Policy recommendations are then made regarding the targeting of these strategies according to product characteristics and the timing of typical product failure relative to optimal product life.