Role of Interfacial Carbon layer in the Thermal Diffusivity/Conductivity of Silicon Carbide Fiber-Reinforced Reaction-Bonded Silicon Nitride Matrix Composites

The role of an interfacial carbon coating in the heat conduction behavior of a uniaxial silicon carbide nitride was investigated. For such a composite without an interfacial carbon coating the values for the thermal conductivity transverse to the fiber direction agreed very well with the values calculated from composite theory using experimental data parallel to the fiber direction, regardless of the ambient atmosphere. However, for a composite made with carbon-coated fibers the experimental values for the thermal conductivity transverse to the fiber direction under vacuum at room temperature were about a factor of 2 lower than those calculated from composite theory assuming perfect interfacial thermal contact. This discrepancy was attributed to the formation of an interfacial gap, resulting from the thermal expansion mismatch between the fibers and the matrix in combination with the low adhesive strength of the carbon coating. In nitrogen or helium the thermal conductivity was found to be higher because of the contribution of gaseous conduction across the interfacial gap. On switching from vacuum to nitrogen a transient effect in the thermal diffusivity was observed, attributed to the diffusion-limited entry of the gas phase into the interfacial gap. These effects decreased with increasing temperature, due to gap closure, to be virtually absent at 1000°C.     

Applying black-box testing to UML/OCL database models

Most Unified Modeling Language (UML) computer-aided software engineering tools have been insufficient in the development process because they provide little support for conceptual model testing. Model testing aims to ensure the correctness of a UML/OCL class diagram, or, in other words, that a given class diagram can perfectly meet the user’s requirements. This study proposes the validation of class diagrams with black-box testing, a technique used to test software without focusing on the software’s implementation or structure. An approach is proposed for the automatic transformation of the constraints of a UML/OCL class diagram into test cases. Following the creation of the test cases, they are executed with JUnit and the results produced are shown to the tester. To demonstrate the applicability of this approach, an effectiveness evaluation and an efficiency evaluation are performed here. Evaluation studies show that all faults included in a class diagram have been detected within an efficient time.     

A study on the factors for improving the ethanol production from Jerusalem artichoke by Kluyveromyces fragilis

This study is to investigate the factors influencing the alcohol production byKluyveromyces fragilis using the juice of Jerusalem Artichoke tubers. The cell growth rate and ethanol production rate were stimulated by aeration and by the addition of unsaturated fatty acids and the cell mass production and the ethanol production were substantially improved. It was found that oxygen and unsaturated fatty acids added played a decisive role on the increase of alcohol tolerance of yeast.     

Hybrid optical-digital method for local-displacement analysis by use of a phase-space representation

A method for evaluating the local deformation or displacement of an object in speckle metrology is described. The local displacements of the object in one direction are digitally coded in a one-dimensional specklegram. By optically performing the local spectrum of this pattern, one simultaneously achieves information about the local displacement and its spatial position. The good performance of this technique is demonstrated with computer-generated test signals.     

Comparison of molecular changes in lung cancers in HIV-positive and HIV-indeterminate subjects

CONTEXT: Human immunodeficiency virus (HIV) infection has been associated with an increasing incidence of malignancy, and HIV-infected persons have an increased incidence of primary lung carcinoma compared with the general population. OBJECTIVE: To investigate the molecular changes present in HIV-associated lung tumors and compare them with those present in lung carcinomas arising in HIV-indeterminate subjects ("sporadic tumors"). DESIGN: Convenience sample. SUBJECTS: Archival tissues from 11 HIV-positive persons and from 35 persons of indeterminate HIV status. SETTING: University-based medical centers and affiliated hospitals. MAIN OUTCOME MEASURES: Analysis of frequency of loss of heterozygosity (LOH) and microsatellite alteration (MA) using polymerase chain reaction and 16 polymorphic microsatellite markers at 8 chromosomal regions frequently deleted in lung cancer. Presence of HIV and human papillomavirus (HPV) sequences. RESULTS: The overall frequency of LOH at all chromosomal regions tested and the frequencies at most of the individual regions were similar in the 2 groups. Frequency of MA present in the HIV-associated tumors (0.18) was 6-fold higher than in sporadic tumors (0.03) (P<.001). At least 1 MA was present in 10 (91%) of 11 HIV-associated tumors vs 17 (48%) of 35 sporadic tumors (P=.02). Molecular changes were independent of tumor stage and gender. HIV and HPV sequences were not detected in the HIV-associated lung carcinomas. CONCLUSIONS: Microsatellite alterations, which reflect widespread genomic instability, occur at greatly increased frequency in HIV-associated lung carcinomas. Although the mechanism underlying the development of increased MAs is unknown, it may play a crucial role in the development of many HIV-associated tumors.     

An Architecture for Human‐Guided Autonomy: Team TROOPER at the DARPA Robotics Challenge Finals

Recent robotics efforts have automated simple, repetitive tasks to increase execution speed and lessen an operator's cognitive load, allowing them to focus on higher‐level objectives. However, an autonomous system will eventually encounter something unexpected, and if this exceeds the tolerance of automated solutions, there must be a way to fall back to teleoperation. Our solution is a largely autonomous system with the ability to determine when it is necessary to ask a human operator for guidance. We call this approach human‐guided autonomy. Our design emphasizes human‐on‐the‐loop control where an operator expresses a desired high‐level goal for which the reasoning component assembles an appropriate chain of subtasks. We introduce our work in the context of the DARPA Robotics Challenge (DRC) Finals. We describe the software architecture Team TROOPER developed and used to control an Atlas humanoid robot. We employ perception, planning, and control automation for execution of subtasks. If subtasks fail, or if changing environmental conditions invalidate the planned subtasks, the system automatically generates a new task chain. The operator is able to intervene at any stage of execution, to provide input and adjustment to any control layer, enabling operator involvement to increase as confidence in automation decreases. We present our performance at the DRC Finals and a discussion about lessons learned.     

Template-based quadrilateral meshing

Generating quadrilateral meshes is a highly non-trivial task, as design decisions are frequently driven by specific application demands. Automatic techniques can optimize objective quality metrics, such as mesh regularity, orthogonality, alignment and adaptivity; however, they cannot make subjective design decisions. There are a few quad meshing approaches that offer some mechanisms to include the user in the mesh generation process; however, these techniques either require a large amount of user interaction or do not provide necessary or easy to use inputs. Here, we propose a template-based approach for generating quad-only meshes from triangle surfaces. Our approach offers a flexible mechanism to allow external input, through the definition of alignment features that are respected during the mesh generation process. While allowing user inputs to support subjective design decisions, our approach also takes into account objective quality metrics to produce semi-regular, quad-only meshes that align well to desired surface features.     

Template-based quadrilateral mesh generation from imaging data

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a quadrilateral one. The triangle-to-quadrilateral conversion makes use of template meshes of triangles. To ensure good element quality, the conversion step is followed by a smoothing step, which is based on a new optimization-based procedure. We show several examples of meshes generated by our approach, and present a thorough experimental evaluation of the quality of the meshes given as examples.     

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.     

Query-based learning for aerospace applications

Models of real-world applications often include a large number of parameters with a wide dynamic range, which contributes to the difficulties of neural network training. Creating the training data set for such applications becomes costly, if not impossible. In order to overcome the challenge, one can employ an active learning technique known as query-based learning (QBL) to add performance-critical data to the training set during the learning phase, thereby efficiently improving the overall learning/generalization. The performance-critical data can be obtained using an inverse mapping called network inversion (discrete network inversion and continuous network inversion) followed by oracle query. This paper investigates the use of both inversion techniques for QBL learning, and introduces an original heuristic to select the inversion target values for continuous network inversion method. Efficiency and generalization was further enhanced by employing node decoupled extended Kalman filter (NDEKF) training and a causality index (CI) as a means to reduce the input search dimensionality. The benefits of the overall QBL approach are experimentally demonstrated in two aerospace applications: a classification problem with large input space and a control distribution problem.