Distance measurement sensor with PIN-photodiode and bridge circuit

The presented integrated optical distance measurement sensor works on the time-of-flight principle. The distance information is obtained from the correlation of received light and the transmitted signal. The PIN-bridge circuit concept ensures suppression of background light by equally charging and discharging the capacitor within one period, while integrating the wanted signal. The advantages of the included PIN-photodiode are high bandwidth f/sub 3 dB/>1.35 GHz together with high responsivity R=0.36 A/W at 660 nm. A single distance measurement is performed in 2 ms. With averaging, an accuracy of better than 1% is achieved for distances up to 3.7 m. Effective pixel size is 250/spl times/200 /spl mu/m/sup 2/ having a fill-factor of /spl sim/16%. The sensor was manufactured in a 0.6-/spl mu/m BiCMOS process.     

Investigations on transient directional solidification under microgravity on sounding rocket missions

Transient growth conditions are common to a variety of technical solidification processes and lead to modified materials properties. In directional solidification the microstructure at the solid-liquid interface of an alloy is a result of the interaction of diffusive and convective heat and mass transport in the bulk and of interface and thermophysical properties. We have carried out experiments under diffusive conditions without convection in microgravity during the sounding rocket missions TEXUS-36 and 40. The used transparent alloy succinonitrile-acetone freezes like metals and the solidification process was observed in-situ. Within a gradient furnace the solid-liquid interface is forced to move accelerated and to transform from planar into cellular and dendritic structures. The dynamics of the planar interface and of the spacing and the amplitude of diffusive grown cells and dendrites were observed directly with cameras and analyzed. A comparison of the TEXUS-40 results to predictions taken from a macroscopic thermal model, a coupled heat-mass transfer model and a phase-field model was carried out. A good agreement is found for the planar interface dynamics for the coupled heat-mass transfer model and the phase-field model, when using additional information from the thermal modelling. In the cellular and dendritic growth regime typical microstructure features can be reproduced by the phase-field model. The experimental results thus serve as important bench-marks for the validation of numerical models describing time-dependent solidification processes.     

Complex‐Shaped Cellulose Composites Made by Wet Densification of 3D Printed Scaffolds

Cellulose is an attractive material resource for the fabrication of sustainable functional products, but its processing into structures with complex architecture and high cellulose content remains challenging. Such limitation has prevented cellulose‐based synthetic materials from reaching the level of structural control and mechanical properties observed in their biological counterparts, such as wood and plant tissues. To address this issue, a simple approach is reported to manufacture complex‐shaped cellulose‐based composites, in which the shaping capabilities of 3D printing technologies are combined with a wet densification process that increases the concentration of cellulose in the final printed material. Densification is achieved by exchanging the liquid of the wet printed material with a poor solvent mixture that induces attractive interactions between cellulose particles. The effect of the solvent mixture on the final cellulose concentration is rationalized using solubility parameters that quantify the attractive interparticle interactions. Using X‐ray diffraction analysis and mechanical tests, 3D printed composites obtained through this process are shown to exhibit highly aligned microstructures and mechanical properties significantly higher than those obtained by earlier additively manufactured cellulose‐based materials. These features enable the fabrication of cellulose‐rich synthetic structures that more closely resemble the exquisite designs found in biological materials grown by plants in nature.     

Oxidative capacity and hemolytic activity of settled dust from moisture‐damaged schools

Exposure to moisture‐damaged indoor environments is associated with adverse respiratory health effects, but responsible factors remain unidentified. In order to explore possible mechanisms behind these effects, the oxidative capacity and hemolytic activity of settled dust samples (n = 25) collected from moisture‐damaged and non‐damaged schools in Spain, the Netherlands, and Finland were evaluated and matched against the microbial content of the sample. Oxidative capacity was determined with plasmid scission assay and hemolytic activity by assessing the damage to isolated human red blood cells. The microbial content of the samples was measured with quantitative PCR assays for selected microbial groups and by analyzing the cell wall markers ergosterol, muramic acid, endotoxins, and glucans. The moisture observations in the schools were associated with some of the microbial components in the dust, and microbial determinants grouped together increased the oxidative capacity. Oxidative capacity was also affected by particle concentration and country of origin. Two out of 14 studied dust samples from moisture‐damaged schools demonstrated some hemolytic activity. The results indicate that the microbial component connected with moisture damage is associated with increased oxidative stress and that hemolysis should be studied further as one possible mechanism contributing to the adverse health effects of moisture‐damaged buildings.     

Uncertainties in the determination of pyrrolizidine alkaloid levels in naturally contaminated honeys and comparison of results obtained by different analytical approaches

The contamination of honey with hepatotoxic pyrrolizidine alkaloids (PAs) is a well-known hazard for food safety. While management strategies and controls of the honey industry aim to reduce the PA levels, uncertainties remain with regard to the safety of regionally produced and marketed honey. In addition, a previous study showed large differences of results obtained after various periods of storage and apparent differences between the analytical results of different laboratories. Therefore, this study aimed at examining these uncertainties by monitoring the impact of storage on the PA and PA N-oxide (PANO) content of two freshly harvested honeys and on possible demixing effects caused by pollen settling. Additionally, three analytical approaches – target analysis with matrix-matched calibration or standard addition and a sum parameter method – were applied for a comparative analysis of 20 honeys harvested in summer 2016. All samples originated from Schleswig-Holstein in Northern Germany where the PA plant Jacobaea vulgaris is currently observed on a massive scale. The results of the time series analyses showed that PANO levels markedly decreased within a few weeks and practically reached the LOD 16 weeks after harvest. Tertiary PAs, by contrast, remained stable and did not increase as a consequence of PANO decrease. The experiments on a putative demixing, which may result in a heterogeneous distribution of PAs/PANOs, revealed that there was no such effect during storage of up to 12 weeks. A comparison of the PA/PANO levels obtained by different analytical approaches showed that in some cases the sum parameter method yielded much higher levels than the target approaches, whereas in other cases, the target analysis with standard addition found higher levels than the other two methods. In summary, the results of this study highlight uncertainties regarding the validity and comparability of analytical results and consequently regarding health risk assessment.     

Sourcing in or out: Implications for social capital and knowledge sharing

The sharing of knowledge between a firm and its internal or external service suppliers has become an important element of contemporary sourcing arrangements. Moreover, the knowledge based view (KBV) has long suggested that due to stronger cognitive links within firms, internal compared to external service provision creates better conditions for knowledge sharing. Empirical evidence for this claim is however scarce, and the KBV does not explain the mechanisms for more knowledge sharing in internal sourcing in detail. Moreover, there is now some evidence to suggest that firms’ relationships with external sourcing partners are becoming more similar to those with captive centres, which represent a less traditional form of insourcing setting. To scrutinize the possible knowledge sharing advantages of internal sourcing in more depth, we turn to social capital (SC) research. There are some theoretical claims that SC and knowledge sharing are stronger within than between firms, and there is ample evidence that SC facilitates knowledge sharing. Our survey results suggest that the extent of knowledge sharing and SC are indeed stronger in a captive than in an external sourcing mode, and that structural (tie strength), cognitive (shared understanding), and relational (trust) aspects of SC mediate the effect of sourcing mode on the extent of knowledge sharing. By contrast, network stability (a structural aspect) mediated knowledge sharing only indirectly, by reinforcing the other SC aspects. We highlight important contributions to research and practice of IS outsourcing and social capital.     

A Petri net based design engine for manufacturing systems

Support for the efficient design and operation of complex manufacturing systems requires an integrated modelling, analysis, and control methodology as well as its implementation in a software tool. In this paper the Petri net based design engine TimeNET is presented for this task. Petri nets are able to capture the characteristic features of manufacturing systems in a concise form. A subclass of coloured Petri nets is used, which has been developed especially for the application area of manufacturing. Structure and work plans are modelled separately. Stochastic as well as deterministic and more general distributions are adopted for the firing times of transitions. Fundamental questions about system properties can be answered using qualitative analysis. For an efficient performance and dependability prediction, different evaluation techniques are proposed: direct numerical analysis, approximate analysis, and simulation. Finally, the model can be used to evaluate different control strategies and to control the manufacturing system directly. There is no need to change the modelling methodology, thus avoiding additional effort, for example for model conversion. In the paper this necessary steps are described using an application example.     

Cluster-grouping: from subgroup discovery to clustering

We introduce the problem of cluster-grouping and show that it can be considered a subtask in several important data mining tasks, such as subgroup discovery, mining correlated patterns, clustering and classification. The algorithm CG for solving cluster-grouping problems is then introduced, and it is incorporated as a component in several existing and novel algorithms for tackling subgroup discovery, clustering and classification. The resulting systems are empirically compared to state-of-the-art systems such as CN2, CBA, Ripper, Autoclass and CobWeb. The results indicate that the CG algorithm can be useful as a generic local pattern mining component in a wide variety of data mining and machine learning algorithms.