7,100 research outputs found

    Development of a Classical Force Field for the Oxidised Si Surface: Application to Hydrophilic Wafer Bonding

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    We have developed a classical two- and three-body interaction potential to simulate the hydroxylated, natively oxidised Si surface in contact with water solutions, based on the combination and extension of the Stillinger-Weber potential and of a potential originally developed to simulate SiO2 polymorphs. The potential parameters are chosen to reproduce the structure, charge distribution, tensile surface stress and interactions with single water molecules of a natively oxidised Si surface model previously obtained by means of accurate density functional theory simulations. We have applied the potential to the case of hydrophilic silicon wafer bonding at room temperature, revealing maximum room temperature work of adhesion values for natively oxidised and amorphous silica surfaces of 97 mJ/m2 and 90mJ/m2, respectively, at a water adsorption coverage of approximately 1 monolayer. The difference arises from the stronger interaction of the natively oxidised surface with liquid water, resulting in a higher heat of immersion (203 mJ/m2 vs. 166 mJ/m2), and may be explained in terms of the more pronounced water structuring close to the surface in alternating layers of larger and smaller density with respect to the liquid bulk. The computed force-displacement bonding curves may be a useful input for cohesive zone models where both the topographic details of the surfaces and the dependence of the attractive force on the initial surface separation and wetting can be taken into account

    Opportunities for improving waterlogging tolerance in cereal crops—Physiological traits and genetic mechanisms

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    Waterlogging occurs when soil is saturated with water, leading to anaerobic conditions in the root zone of plants. Climate change is increasing the frequency of waterlogging events, resulting in considerable crop losses. Plants respond to waterlogging stress by adventitious root growth, aerenchyma formation, energy metabolism, and phytohormone signalling. Genotypes differ in biomass reduction, photosynthesis rate, adventitious roots development, and aerenchyma formation in response to waterlogging. We reviewed the detrimental effects of waterlogging on physiological and genetic mechanisms in four major cereal crops (rice, maize, wheat, and barley). The review covers current knowledge on waterlogging tolerance mechanism, genes, and quantitative trait loci (QTL) associated with waterlogging tolerance-related traits, the conventional and modern breeding methods used in developing waterlogging tolerant germplasm. Lastly, we describe candidate genes controlling waterlogging tolerance identified in model plants Arabidopsis and rice to identify homologous genes in the less waterlogging-tolerant maize, wheat, and barley

    A novel grading biomarker for the prediction of conversion from mild cognitive impairment to Alzheimer's disease

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    OBJECTIVE: Identifying mild cognitive impairment (MCI) subjects who will progress to Alzheimer's disease is not only crucial in clinical practice, but also has a significant potential to enrich clinical trials. The purpose of this study is to develop an effective biomarker for an accurate prediction of MCI-to-AD conversion from magnetic resonance (MR) images. METHODS: We propose a novel grading biomarker for the prediction of MCI-to-AD conversion. First, we comprehensively study the effects of several important factors on the performance in the prediction task including registration accuracy, age correction, feature selection and the selection of training data. Based on the studies of these factors, a grading biomarker is then calculated for each MCI subject using sparse representation techniques. Finally, the grading biomarker is combined with age and cognitive measures to provide a more accurate prediction of MCI-to-AD conversion. RESULTS: Using the ADNI dataset, the proposed global grading biomarker achieved an area under the receiver operating characteristic curve (AUC) in the range of 79%-81% for the prediction of MCI-to-AD conversion within 3 years in 10-fold cross validations. The classification AUC further increases to 84%-92% when age and cognitive measures are combined with the proposed grading biomarker. CONCLUSION: The obtained accuracy of the proposed biomarker benefits from the contributions of different factors: a tradeoff registration level to align images to the template space; the removal of the normal aging effect; selection of discriminative voxels; the calculation of the grading biomarker using AD and normal control groups; the integration of sparse representation technique and the combination of cognitive measures. SIGNIFICANCE: The evaluation on the ADNI dataset shows the efficacy of the proposed biomarker and demonstrates a significant contribution in accurate prediction of MCI-to-AD conversion

    Detection of embryo mortality and hatch using thermal differences among incubated chicken eggs

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    Accurate diagnosis of both the stage of embryonic mortality and the hatch process in incubated eggs is a fundamental component in troubleshooting and hatchery management. However, traditional methods disturb incubation, destroy egg samples, risk contamination, are time and labour-intensive and require specialist knowledge and training. Therefore, a new method to accurately detect embryonic mortality and hatching time would be of significant interest for the poultry industry if it could be done quickly, cheaply and be fully integrated into the process. In this study we have continuously measured individual eggshell temperatures and the corresponding micro-environmental air temperatures throughout the 21 days of incubation using standard low-cost temperature sensors. Moreover, we have quantified the thermal interaction between eggs and air by calculating thermal profile changes (temperature drop time, drop length and drop magnitude) that allowed us to detect four categories of egg status (infertile/early death, middle death, late death and hatch) during incubation. A decision tree induction classification model accurately (93.3%) predicted the status of 105 sampled eggs in comparison to the classical hatch residue breakout analyses. With this study we have provided a major contribution to the optimisation of incubation processes by introducing an alternative method for the currently practiced hatch residue breakout analyses.status: publishe

    Data-Feedthrough Faults in Circuits using Unclocked Storage Elements

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    Some faults in storage elements (SEs) do not manifest as stuck-at-0/1 faults. These include data-feedthrough faults that cause the SE cell to exhibit combinational behaviour. The authors investigate the implications of such faults on the behaviour of circuits using unclocked SEs. It is shown that effects of data-feedthrough faults at the behavioural level are different from those due to stuck-at faults, and therefore tests generated for the latter may be inadequat
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