EARLY MOTHER-INFANT RELATIONSHIPS OF MACACA-THIBETANA AT MT-EMEI CHINA

Quantitative data on early mother-infant relationships in the Tibetan macaque was collected during the first 23 weeks of infant life in spring, 1987, at Mt. Emei, China. During the first week of life, infants spent 98.3% of their time in ventroventral contact with their mothers. This contact rapidly decreased to 33.8% by the 4th week and thereafter to 0.85% by the 23rd week. Nipple contact decreased relatively slowly from 89.7% to 62.9% within the first 4 weeks of infant life and to 19.8% by the 23rd week. Ventrolateral and ventrodorsal contact appeared by the 2nd week, mean-while, maternal restraining behavior appeared, and reached a peak by the 3rd week. The mother neither encouraged nor discouraged her infant's independence during 4-8th weeks. Maternal rejection of the infant was first observed when the infant was 11 weeks old and continued thereafter.

Ecodesign innovation: Is 'early' always 'best'?

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.

EARLY FLOWERING4 recruitment of EARLY FLOWERING3 in the nucleus sustains the Arabidopsis circadian clock

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.

Disentangling the Complexity of Early-Stage Technology Acquisitions

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.

Technology confidence in early stage development of medical devices

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.

Observation of early to full covering stages of ethylene-based CVD of graphene

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.

A unifying resolution-independent formulation for early vision

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.

Product life trade-offs: what if products fail early?

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.

Simulating early adoption of alternative fuel vehicles for sustainability

We quantify the conditions that might trigger wide spread adoption of alternative fuel vehicles (AFVs) to support energy policy. Empirical review shows that early adopters are heterogeneous motivated by financial benefits, environmental appeal, new technology, and vehicle reliability. A probabilistic Monte Carlo simulation model is used to assess consumer heterogeneity for early and mass market adopters. For early adopters full battery electric vehicles (BEVs) are competitive but unable to surpass diesels or hybrids due to purchase price premium and lack of charging availability. For mass adoption, simulations indicate that if the purchase price premium of a BEV closes to within 20% of an in-class internal combustion engine (ICE) vehicle, combined with a 60% increase in refuelling availability relative to the incumbent system, BEVs become competitive. But this depends on a mass market that values the fuel economy and CO2 reduction benefits associated with BEVs. We also find that the largest influence on early adoption is financial benefit rather than pro-environmental behaviour suggesting that AFVs should be marketed by appealing to economic benefits combined with pro-environmental behaviour to motivate adoption. Monte Carlo simulations combined with scenarios can give insight into diffusion dynamics for other energy demand-side technologies. © 2012 Elsevier Inc.