Automatic ultrastructure segmentation of reconstructed cryoEM maps of icosahedral viruses.

We present an automatic algorithm to segment all the local and global asymmetric units of a three-dimensional density map of icosahedral viruses. This approach is readily applicable to the structural analysis of a broad range of virus structures that are reconstructed using cryo-electron microscopy (cryo-EM) technique. Our algorithm includes three major steps operating on the three dimensional density map: the detection of critical points of the volumetric density function, the detection of global and local symmetry axes, and, finally, the boundary segmentation of all the asymmetric units. We demonstrate the efficacy of our algorithm and report our results on several experimental volumetric datasets, consisting of both reconstructed cryo-EM molecular density maps taken from the European Bioinformatics Institute archive, as well our own synthetically generated (blurred) maps calculated from X-ray resolution molecular structural data taken from the Protein Data Bank.     

Carbohydrate content of potato (Solanum tuberosum L.) tubers treated with Isopropyl-N (3-chlorophenyl) carbamate under different storage conditions

Post harvest application of Isopropyl-N (3-chlorophenyl) carbamate considerably reduced the degradation of starch when potato tubers were stored in an evaporative cooling chamber. The starch degraded at a faster rate when tubers were kept under refrigerated and room storage conditions.     

Modeling of in situ monitored laser reflectance during MOCVD growth of HgCdTe

An effective way to in situ monitor the metalorganic chemical vapor deposition (MOCVD) of HgCdTe/CdTe/ZnTe on GaAs or GaAs/Si substrates is presented. Specular He-Ne laser reflectance was used to in situ monitor the growth rates, layer thickness, and morphology for each layer in the grown multilayer structure. In situ monitoring has enabled precise measurements of ZnTe nucleation and CdTe buffer layer thicknesses. Monitoring the constancy of reflectance during the thicker CdTe buffer growth where absorption in the CdTe reduces reflectance to just the surface component has led to optimum buffer growth ensuring good quality of subsequently grown HgCdTe. During the interdiffused multilayer process (IMP) HgCdTe growth, because multiple interfaces are present within the absorption length, a periodic reflectance signal is maintained throughout this growth cycle. A theoretical model was developed to extract IMP layer thicknesses from in situ recorded experimental data. For structures that required the growth of a larger band gap HgCdTe cap layer on top of a smaller band gap active layer, in situ monitored reflectance data allowed determination of alloy composition in the cap layer as well. Continuous monitoring of IMP parameters established the stability of growth conditions, translating into depth uniformity of the grown material, and allowed diagnosis of growth rate instabilities in terms of changes in the HgTe and CdTe parts of the IMP cycle. A unique advantage of in situ laser monitoring is the opportunity to perform “interactive” crystal growth, a development that is a key to real time MOCVD HgCdTe feedback growth control.     

A comparison of statistical relational learning and graph neural networks for aggregate graph queries

Statistical relational learning (SRL) and graph neural networks (GNNs) are two powerful approaches for learning and inference over graphs. Typically, they are evaluated in terms of simple metrics such as accuracy over individual node labels. Complex aggregate graph queries (AGQ) involving multiple nodes, edges, and labels are common in the graph mining community and are used to estimate important network properties such as social cohesion and influence. While graph mining algorithms support AGQs, they typically do not take into account uncertainty, or when they do, make simplifying assumptions and do not build full probabilistic models. In this paper, we examine the performance of SRL and GNNs on AGQs over graphs with partially observed node labels. We show that, not surprisingly, inferring the unobserved node labels as a first step and then evaluating the queries on the fully observed graph can lead to sub-optimal estimates, and that a better approach is to compute these queries as an expectation under the joint distribution. We propose a sampling framework to tractably compute the expected values of AGQs. Motivated by the analysis of subgroup cohesion in social networks, we propose a suite of AGQs that estimate the community structure in graphs. In our empirical evaluation, we show that by estimating these queries as an expectation, SRL-based approaches yield up to a 50-fold reduction in average error when compared to existing GNN-based approaches.

     

Effect of coupling agents on thermal and electrical properties of mica/epoxy composites

The influence of 3-aminopropyltriethoxysilane, 3-glycidyloxypropyltrimethoxysilane, and neoalkoxytric(dioctyl pyrophosphato)zirconate on thermal expansion behavior, dielectric strength, and arc resistance of mica/epoxy composites has been investigated. The addition of mica up to 30% resulted in the reduction of thermal expansion with respect to neat resin. However, the coefficient of linear thermal expansion of 30% mica treated with aminosilane was the least among the various coupling agent-coated filler/epoxy composites. Mica (30%)/epoxy composites showed the highest dielectric strength values (26 kV/mm), but the highest arc resistance was obtained in zirconate-treated mica (30%)/epoxy composite. © 1995 John Wiley & Sons, Inc.     

Comparison of two scaling approaches for the development of biomechanical multi-body human models

Dimensional scaling approaches are widely used to develop multi-body human models in injury biomechanics research. Given the limited experimental data for any particular anthropometry, a validated model can be scaled to different sizes to reflect the biological variance of population and used to characterize the human response. This paper compares two scaling approaches at the whole-body level: one is the conventional mass-based scaling approach which assumes geometric similarity; the other is the structure-based approach which assumes additional structural similarity by using idealized mechanical models to account for the specific anatomy and expected loading conditions. Given the use of exterior body dimensions and a uniform Young’s modulus, the two approaches showed close values of the scaling factors for most body regions, with 1.5 % difference on force scaling factors and 13.5 % difference on moment scaling factors, on average. One exception was on the thoracic modeling, with 19.3 % difference on the scaling factor of the deflection. Two 6-year-old child models were generated from a baseline adult model as application example and were evaluated using recent biomechanical data from cadaveric pediatric experiments. The scaled models predicted similar impact responses of the thorax and lower extremity, which were within the experimental corridors; and suggested further consideration of age-specific structural change of the pelvis. Towards improved scaling methods to develop biofidelic human models, this comparative analysis suggests further investigation on interior anatomical geometry and detailed biological material properties associated with the demographic range of the population.     

Bioenergy,food security and poverty reduction: trade-offs and synergies along the water–energy–food security nexus

This article provides a review of trade-offs and synergies of bioenergy within the water–energy–food security nexus, with emphasis on developing countries. It explores the links of bioenergy with food security, poverty reduction, environmental sustainability, health, and gender equity. It concludes that applying the nexus perspective to analyses of bioenergy widens the scope for achieving multiple-win outcomes along the above aspects.     

A Balanced Approach to IT Transformation

The continuous improvement strategies necessary in today's climate of random change mandate that IT organizations transform the way they relate to other business units, deploy new technology, and organize and develop their people. Crafting an individualized transformation program that balances efforts in each of these areas will help IT managers add value to the bottom line while achieving real gains in customer service and productivity.