Variation in fatty acid composition of the different acyl lipids in seed oils from fourSesamum species

Seeds from different collections of cultivatedSesamum indicum Linn. and three related wild species [specifically,S. alatum Thonn.,S. radiatum Schum and Thonn. andS. angustifolium (Oliv.) Engl.] were studied for their oil content and fatty acid composition of the total lipids. The wild seeds contained less oil (ca. 30%) than the cultivated seeds (ca. 50%). Lipids from all four species were comparable in their total fatty acid composition, with palmitic (8.2–12.7%), stearic (5.6–9.1%), oleic (33.4–46.9%) and linoleic acid (33.2–48.4%) as the major acids. The total lipids from selected samples were fractionated by thin-layer chromatography into five fractions: triacylglycerols (TAG; 80.3–88.9%), diacylglycerols (DAG; 6.5–10.4%), free fatty acids (FFA; 1.2–5.1%), polar lipids (PL; 2.3–3.5%) and steryl esters (SE; 0.3–0.6%). Compared to the TAG, the four other fractions (viz, DAG, FFA, PL and SE) were generally characterized by higher percentages of saturated acids, notably palmitic and stearic acids, and lower percentages of linoleic and oleic acids in all species. Slightly higher percentages of long-chain fatty acids (20∶0, 20∶1, 22∶0 and 24∶0) were observed for lipid classes other than TAG in all four species. Based on the fatty acid composition of the total lipids and of the different acyl lipid classes, it seems thatS. radiatum andS. angustifolium are more related to each other than they are to the other two species.     

Activation of Ni/A12O3 catalysts through modification of the Al2O3 support

The effect of alumina pretreatment on the performance of alumina supported nickel catalysts was demonstrated in gas phase hydrogenation of toluene to methylcyclohexane. The state of the alumina was changed from pure to pure phase through various heat treatments in air. The catalysts were prepared from vapor phase by saturating the accessible binding sites on the pretreated alumina with the nickel precursor. The highest number of active sites for hydrogenation was observed for catalysts prepared on alumina having an incomplete phase transition and a / alumina phase ratio between 0.5 and 10. Results from temperature programmed desorption (TPD) studies revealed that a maximum in weakly chemisorbed hydrogen as well as in total amount of desorbed hydrogen was found for the same catalysts. By hydrogen chemisorption studies the total hydrogen uptake was found to correlate with the observed hydrogenation maximum. It is suggested that both the chemical and physical properties of the alumina influence the activity. An optimal metal-support interaction and structural defects on the alumina due to the phase transition can explain the observed maximum in the number of active sites and in hydrogen uptake.     

Analysis of Technology Potential of a Metal-based Latent Heat Storage for Backup Process Steam Supply

An analysis of technology potential of a metal-based high temperature latent heat storage for the application of process steam backup for industrial parks in Germany was carried out. To investigate the integration of the storage into a process steam network, dynamic process simulations were performed. Furthermore, the analysis includes ecological and economical calculations for various fuel types of industrial power plants, plant sizes and auxiliary fuels. Basis of all calculations is an extensive research conducted on the industrial parks in Germany with a dedicated power plant and process steam utilization.     

The real-time,high-resolution x-ray video microscopy of solidification in aluminum alloys

The directional solidification of thin alloy sheets in a Bridgman furnace has been studied by x-radiography using high-brilliance synchrotron x-radiation in combination with a low-noise, fast-readout camera. Spatial resolutions down to 1.5 μm and a temporal resolution of about 0.15 s have permitted real-time video microscopy of microstructural evolution during columnar and equiaxed dendrite growth and eutectic and monotectic growth. The technique has also allowed for direct observations of important solidification phenomena such as dendrite fragmentation and porosity formation, primarily in aluminium alloys. As a result, insights have been gained into mechanisms of dendrite fragmentation, criteria for dendrite tip kinetics and interface stability during transient growth, and microstructure formation mechanisms during monotectic solidification. The results are expected to be important for validation of dendrite growth models. This paper presents a review of the technique as well as examples of images obtained during solidification of aluminum alloys.     

A Hybrid Color Quantization Algorithm Incorporating a Human Visual Perception Model

Color quantization is a common image processing technique where full color images are to be displayed using a limited palette of colors. The choice of a good palette is crucial as it directly determines the quality of the resulting image. Standard quantization approaches aim to minimize the mean squared error (MSE) between the original and the quantized image, which does not correspond well to how humans perceive the image differences. In this article, we introduce a color quantization algorithm that hybridizes an optimization scheme based with an image quality metric that mimics the human visual system. Rather than minimizing the MSE, its objective is to maximize the image fidelity as evaluated by S‐CIELAB, an image quality metric that has been shown to work well for various image processing tasks. In particular, we employ a variant of simulated annealing with the objective function describing the S‐CIELAB image quality of the quantized image compared with its original. Experimental results based on a set of standard images demonstrate the superiority of our approach in terms of achieved image quality.     

Open to a Select Few? Matching Partners and Knowledge Content for Open Innovation Performance

The purpose of the paper is to illuminate the costs and benefits of crossing firm boundaries in inbound open innovation (OI) by determining the relationships among partner types, knowledge content and performance. The empirical part of the study is based on a survey of OI collaborations answered by R&D managers in 415 Italian, Finnish and Swedish firms. The results show that the depth of collaboration with different partners (academic/consultants, value chain partners, competitors and firms in other industries) is positively related to innovation performance, whereas the number of different partners and size have negative effects. The main result is that the knowledge content of the collaboration moderates the performance outcomes and the negative impact of having too many different kinds of partners. This illustrates how successful firms use selective collaboration strategies characterized by linking explorative and exploitative knowledge content to specific partners, to leverage the benefits and limit the costs of knowledge boundary crossing processes.     

SleepExplorer: a visualization tool to make sense of correlations between personal sleep data and contextual factors

Getting enough quality sleep is a key part of a healthy lifestyle. Many people are tracking their sleep through mobile and wearable technology, together with contextual information that may influence sleep quality, like exercise, diet, and stress. However, there is limited support to help people make sense of this wealth of data, i.e., to explore the relationship between sleep data and contextual data. We strive to bridge this gap between sleep-tracking and sense-making through the design of SleepExplorer, a web-based tool that helps individuals understand sleep quality through multi-dimensional sleep structure and explore correlations between sleep data and contextual information. Based on a two-week field study with 12 participants, this paper offers a rich understanding on how technology can support sense-making on personal sleep data: SleepExplorer organizes a flux of sleep data into sleep structure, guides sleep-tracking activities, highlights connections between sleep and contributing factors, and supports individuals in taking actions. We discuss challenges and opportunities to inform the work of researchers and designers creating data-driven health and well-being applications.     

Improved Quality Output through Computer‐Based Training: An Automotive Assembly Field Study

In this article, two field experiments, conducted in an automotive assembly plant, evaluate how computer‐based training of operational sequences and related quality information can support the assembly performance of the operators. The experiments were performed during the launch of a new vehicle. A comparison was made of learning progress and quality performance between a reference group of operators that only had regular training and a test group for which some of the regular training was replaced with individual computer‐based training. Both quantitative measures of the quality output and questionnaires and observations were used to evaluate the effects of computer‐based training. The results show a clear positive difference in learning progress and improvements in quality output for the test group compared with the reference group. This combined with positive attitudes expressed by the operators and their team leaders shows that this type of training is an effective way to train operators during launches of new vehicles in automotive production.     

(Approximate) Uncertain Skylines

Given a set of points with uncertain locations, we consider the problem of computing the probability of each point lying on the skyline, that is, the probability that it is not dominated by any other input point. If each point’s uncertainty is described as a probability distribution over a discrete set of locations, we improve the best known exact solution. We also suggest why we believe our solution might be optimal. Next, we describe simple, near-linear time approximation algorithms for computing the probability of each point lying on the skyline. In addition, some of our methods can be adapted to construct data structures that can efficiently determine the probability of a query point lying on the skyline.