On the Structure of Amorphous Mesoporous Silica Nanoparticles by Aberration‐Corrected STEM

Mesoporous silica materials have demonstrated a vast spectrum of applications, stimulating an intensive field of study due to their potential use as nanocarriers. Nonetheless, when produced at the nanoscale, their structural characterization is hindered due to the re‐arrangement of the pores. To address this issue, this work combines molecular dynamics simulations with electron microscopy computer simulations and experimental results to provide an insight into the structure of amorphous mesoporous silica nanoparticles. The amorphous silica model is prepared using a simple melt‐quench molecular dynamics method, while the reconstruction of the mesoporous nanoparticles is carried out using a methodology to avoid false symmetry in the final model. Simulated scanning transmission electron microscopy images are compared with experimental images, revealing the existence of structural domains, created by the misalignment of the pores to compensate the surface tension of these spherical nanoparticles.     

Influence of the silica matrix on the formation of α-alumina in a mullite–alumina composite from a diphasic precursor

In mullite–alumina composite precursors, interaction between the silica matrix and the fine -alumina texture strongly influences the precursor phase transformation, the nucleation and the crystal geometry both of the mullite and of the -alumina. The mullite–alumina composite precursor calcined at 1000 °C has a layered structure probably derived from the layered texture of the -alumina. The phase transition of this layered texture is retarded by the presence of the silica matrix and a metastable mullite phase is formed before nucleation of -alumina. By leaching away the silica matrix, the remaining layered texture is readily transformed into very fine, thin -alumina platelets by calcination at 1000 °C. This seems to be one reason for the appearance of elongated mullite grains in a pure mullite matrix and the platelet shaped -alumina grains in the mullite–alumina composite prepared from diphasic precursors. © 1998 Chapman & Hall     

Two-channel switched reluctance starter/generator results

Measured data and simulation results for a two-channel experimental switched-reluctance-motor (SRM)-based aircraft engine starter/generator system are presented. The two channels of the system provide power to two separate and independent loads. The results presented document the performance capability of this system with both channels operating simultaneously. Both measured and predicted system performance are presented and compared. In addition, operating characteristics that are unique to this SRM-based system are described. Of particular interest are the interactions between the two separate channels when one channel experiences a load transient and the other channel does not. The source of channel interactions is described, and measured data is provided. The issue of clearing load faults is also addressed. Design results for adding this capability to the experimental system are described     

BirdVis: visualizing and understanding bird populations

Birds are unrivaled windows into biotic processes at all levels and are proven indicators of ecological well-being. Understanding the determinants of species distributions and their dynamics is an important aspect of ecology and is critical for conservation and management. Through crowdsourcing, since 2002, the eBird project has been collecting bird observation records. These observations, together with local-scale environmental covariates such as climate, habitat, and vegetation phenology have been a valuable resource for a global community of educators, land managers, ornithologists, and conservation biologists. By associating environmental inputs with observed patterns of bird occurrence, predictive models have been developed that provide a statistical framework to harness available data for predicting species distributions and making inferences about species-habitat associations. Understanding these models, however, is challenging because they require scientists to quantify and compare multiscale spatialtemporal patterns. A large series of coordinated or sequential plots must be generated, individually programmed, and manually composed for analysis. This hampers the exploration and is a barrier to making the cross-species comparisons that are essential for coordinating conservation and extracting important ecological information. To address these limitations, as part of a collaboration among computer scientists, statisticians, biologists and ornithologists, we have developed BirdVis, an interactive visualization system that supports the analysis of spatio-temporal bird distribution models. BirdVis leverages visualization techniques and uses them in a novel way to better assist users in the exploration of interdependencies among model parameters. Furthermore, the system allows for comparative visualization through coordinated views, providing an intuitive interface to identify relevant correlations and patterns. We justify our design decisions and present case studies that show how BirdVis has helped scientists obtain new evidence for existing hypotheses, as well as formulate new hypotheses in their domain.     

Discovering implicit intention-level knowledge from natural-language texts

In this paper, we propose a new approach to automatic discovery of implicit rhetorical information from texts based on evolutionary computation methods. In order to guide the search for rhetorical connections from natural-language texts, the model uses previously obtained training information which involves semantic and structural criteria. The main features of the model and new designed operators and evaluation functions are discussed, and the different experiments assessing the robustness and accuracy of the approach are described. Experimental results show the promise of evolutionary methods for rhetorical role discovery.     

Fixed-point DSP implementation of nonlinear controller for large gap electromagnetic suspension system

Electromagnetic suspension systems are inherently nonlinear and often face hardware limitation when digitally controlled. The main contributions of this paper are: the design of a nonlinear H_∞ controller, including dynamic weighting functions, applied to a large gap electromagnetic suspension system and the presentation of a procedure to implement this controller on a fixed-point DSP, through a methodology able to translate a floating-point algorithm into a fixed-point algorithm by using l_∞ norm minimization due to conversion error. Experimental results are also presented, in which the performance of the nonlinear controller is evaluated specifically in the initial suspension phase.     

Going Beyond Telecenters to Foster the Digital Inclusion of Older People in Brazil: Lessons Learned from a Rapid Ethnographical Study

Telecenters take on a prominent role within the current information and communications technology (ICT) ecosystem in Brazil. They are seen by a great many as a key means to foster the digital inclusion of the older population in the country. This paper draws upon a rapid ethnographic study conducted with 78 older people in a center that teaches computer classes to seniors in Brazil. The results show that providing older people with technological infrastructures is not enough to strengthen their digital inclusion if their basic and non-instrumental needs are not taken into consideration in defining educational activities to be carried out in public centers. Participants’ basic needs when it comes to interacting with ICT, such as coping with accessibility issues, were dynamic, whilst non-instrumental needs, fulfilled by using these technologies, such as interacting with relevant others, remained fairly constant throughout the study. Drawing on the results of the study, strategies for fostering the digital inclusion and well-being of older people in Brazil that go beyond telecenters are suggested.     

Supporting Unified Distributed Management and Autonomic Decisions: Design,Implementation and Deployment

Nowadays, the prevailing use of networks based on traditional centralized management systems reflects on a fast increase of the management costs. The growth in the number of network equipments and services reinforces the need to distribute the management responsibilities throughout the network devices. In this approach, each device executes common network management functionalities, being part of the overall network management platform. In this paper, we present a Unified Distributed Network Management (UDNM) framework that provides a unified (wired and wireless) management network solution, where further different network services can take part of this infrastructure, e.g., flow monitoring, accurate routing decisions, distributed policies dissemination, etc. This framework is divided in two main components: (A) Situation awareness, which sets up initial information through bootstrapping, discovery, fault-management process and exchange of management information; (B) Autonomic Decision System (ADS) that performs distributed decisions in the network with incomplete information. We deploy the UDNM framework in a testbed which involves two cities (\(\approx\)250 km between), different standards (IEEE 802.3, IEEE 802.11 and IEEE 802.16e) and network technologies, such as, wired virtual grid, wireless ad-hoc gateways, ad-hoc mobile access devices. The UDNM framework integrates management functionalities into the managed devices, proving to be a lightweight and easy-respond framework. The performance analysis shows that the UDNM framework is feasible to unify devices management functionalities and to take accurate decisions on top of a real network.