Dislocations in the crystallites of nanocrystalline alpha-Fe - A molecular dynamics study

Molecular dynamics simulations are carried out in order to study the atomic structure of crystalline component, of nanocrystalline alpha-Fe when it is consolidated from small grains. A two-dimensional computational block is used to simulate the consolidation process. All the preset dislocations in the original grains glide out of them in the consolidation process, but new dislocations can generate when the grain size is large enough. It shows that dislocations exist in the consolidated material rather than in the original grains. Whether dislocations exist in the crystalline component of the resultant model nana-material depends upon grain size. The critical value of grain size for dislocation generation appears to be about 9 nm. This result agrees with experiments qualitatively.

Application of algal bioassays in the determination of eutrophic power of waste water (”Conclusions” only) [Translation from: 1g.Sanita pubbl. 31 257-267, 1975]

The best evidence for establishing the level of eutrophy of a water-body is its algal production which makes it possible to identify the type and the intensity of the eutrophication according to the kind and number of algal species present: when the number of algae exceeds half a million per litre then one speaks o an ”algal bloom”. The scope of the present research aims to verify if the alga Selenastrum capricornutum can be used as a test alga under our culture conditions and to determine the eutrophic level of the secondary effluent of a modern plant for the treatment of domestic discharge and to investigate the eventual ”limiting factors”. Finally this paper aims to study the effect on the secondary effluent of tertiary treatment carried out artificially in the laboratory.

San Francisco : a city reinvented by creative innovation

The aim of this paper is to analyse the recent evolution of the city of San Francisco to outline the major features that have made it possible this continuing process of creative innovation in the city. In order to meet this objective, the project is framed around answering two key research questions: (1) what are the main economic and social elements that characterise urban change in the city of San Francisco and (2) which is the role of public strategies in the continuing economic success of San Francisco. The paper concludes that the successful performance of San Francisco is the result of the actions taken by many agents in the city, but the role of public authorities, especially the City and County, must be stressed, both through direct intervention and by coordinating, fostering and supporting the private and non-profit sectors. This is especially relevant in a country like the US where private initiative has been seen in many occasions as the greatest driver of economic and social success. Yet, the performance of San Francisco City cannot be explained without the role played by the public sector, in coordination with the civil society

High sensitive NO2 gas sensor with low power consumption using selectively grown ZnO nanorods.

The noble gas sensor using multiple ZnO nanorods was fabricated with CMOS compatible process and sol-gel growth method on selective area and gas response characteristics to NO2 gas of the sensor device were investigated. We confirmed the sensors had high sensitive response denoted by the sensitivity of several tens for NO2 gas sensing and also showed pretty low power consumption close to 20 mW even though the recovery of resistance come up to almost the initial value.

Thermoelastic dissipation in MEMS/NEMS flexural mode resonators.

Understanding the energy dissipation mechanisms in single-crystal silicon MEMS/NEMS resonators are particularly important to maximizing an important figure of merit relevant for miniature sensor and signal processing applications: the Quality factor (Q) of resonance. This paper discusses thermoelastic dissipation (TED) as the dominant internal-friction mechanism in flexural mode MEMS/NEMS resonators. Criteria for optimizing the geometrical design of flexural mode MEMS/NEMS resonators are theoretically established with a view towards minimizing the TED for single-crystal silicon MEMS/NEMS flexural mode resonators.

Growth of carbon nanotubes on fully processed silicon-on-insulator CMOS substrates.

This paper describes the growth of Carbon Nanotubes (CNTs) both aligned and non-aligned on fully processed CMOS substrates containing high temperature tungsten metallization. While the growth method has been demonstrated in fabricating CNT gas sensitive layers for high temperatures SOI CMOS sensors, it can be employed in a variety of applications which require the use of CNTs or other nanomaterials with CMOS electronics. In our experiments we have grown CNTs both on SOI CMOS substrates and SOI CMOS microhotplates (suspended on membranes formed by post-CMOS deep RIE etching). The fully processed SOI substrates contain CMOS devices and circuits and additionally, some wafers contained high current LDMOSFETs and bipolar structures such as Lateral Insulated Gate Bipolar Transistors. All these devices were used as test structures to investigate the effect of additional post-CMOS processing such as CNT growth, membrane formation, high temperature annealing, etc. Electrical characterisation of the devices with CNTs were performed along with SEM and Raman spectroscopy. The CNTs were grown both at low and high temperatures, the former being compatible with Aluminium metallization while the latter being possible through the use of the high temperature CMOS metallization (Tungsten). In both cases we have found that there is no change in the electrical behaviour of the CMOS devices, circuits or the high current devices. A slight degradation of the thermal performance of the CMOS microhotplates was observed due to the extra heat dissipation path created by the CNT layers, but this is expected as CNTs exhibit a high thermal conductance. In addition we also observed that in the case of high temperature CNT growth a slight degradation in the manufacturing yield was observed. This is especially the case where large area membranes with a diameter in excess of 500 microns are used.

Coarse-level object recognition using interlevel products of complex wavelets

This paper introduces the Interlevel Product (ILP) which is a transform based upon the Dual-Tree Complex Wavelet. Coefficients of the ILP have complex values whose magnitudes indicate the amplitude of multilevel features, and whose phases indicate the nature of these features (e.g. ridges vs. edges). In particular, the phases of ILP coefficients are approximately invariant to small shifts in the original images. We accordingly introduce this transform as a solution to coarse scale template matching, where alignment concerns between decimation of a target and decimation of a larger search image can be mitigated, and computational efficiency can be maintained. Furthermore, template matching with ILP coefficients can provide several intuitive "near-matches" that may be of interest in image retrieval applications. © 2005 IEEE.

Semantic Discriminant mapping for classification and browsing of remote sensing textures and objects

We present a new approach based on Discriminant Analysis to map a high dimensional image feature space onto a subspace which has the following advantages: 1. each dimension corresponds to a semantic likelihood, 2. an efficient and simple multiclass classifier is proposed and 3. it is low dimensional. This mapping is learnt from a given set of labeled images with a class groundtruth. In the new space a classifier is naturally derived which performs as well as a linear SVM. We will show that projecting images in this new space provides a database browsing tool which is meaningful to the user. Results are presented on a remote sensing database with eight classes, made available online. The output semantic space is a low dimensional feature space which opens perspectives for other recognition tasks. © 2005 IEEE.

Restoration of images and 3D data to higher resolution by deconvolution with sparsity regularization

Image convolution is conventionally approximated by the LTI discrete model. It is well recognized that the higher the sampling rate, the better is the approximation. However sometimes images or 3D data are only available at a lower sampling rate due to physical constraints of the imaging system. In this paper, we model the under-sampled observation as the result of combining convolution and subsampling. Because the wavelet coefficients of piecewise smooth images tend to be sparse and well modelled by tree-like structures, we propose the L0 reweighted-L2 minimization (L0RL2 ) algorithm to solve this problem. This promotes model-based sparsity by minimizing the reweighted L2 norm, which approximates the L0 norm, and by enforcing a tree model over the weights. We test the algorithm on 3 examples: a simple ring, the cameraman image and a 3D microscope dataset; and show that good results can be obtained. © 2010 IEEE.

Convex approaches to model wavelet sparsity patterns

Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix produces a linear mixing of the simple Markovian dependency structure. This leads to reconstruction problems that are non-convex optimizations. Past work has dealt with this issue by resorting to greedy or suboptimal iterative reconstruction methods. In this paper, we propose new modeling approaches based on group-sparsity penalties that leads to convex optimizations that can be solved exactly and efficiently. We show that the methods we develop perform significantly better in de-convolution and compressed sensing applications, while being as computationally efficient as standard coefficient-wise approaches such as lasso. © 2011 IEEE.