Measurement of mechanical properties in a 316L stainless steel welded joint

The aim of this study was to measure the mechanical properties of weld material taken from a single weld bead laid down on a 316L steel plate. Due to the low available volume of weld material, microsamples with a total length of 5.5 mm were used. The Digital Image Correlation method (DIC), which enables measurement of mechanical properties of very small samples, was employed for the strain measurements in a uniaxial tensile test. Samples were cut out from three different zones of the specimen: plate, weld, and the heat affected zone. The material from heat affected zone showed the highest value of the Ultimate Tensile Strength (UTS) (580 ± 7 MPa) and yield strength (339 ± 6 MPa). Plate material had lower UTS (559 ± 5 MPa) and yield strength (304 ± 7 MPa). The lowest values of UTS (526 ± 6 MPa) and yield strength (291 ± 8 MPa) have been revealed for the weld. The values obtained for UTS, yield strength and elongation to failure for the plate material were compared with data obtained using standard test specimens. No significant differences between results obtained for the microsamples and standard samples have been found.     

Bioinspired Computational Framework for Enhancing Creativity, Optimality, and Robustness in Design

This paper presents results of transdisciplinary research on the development of a bioinspired computational framework for engineering design. This framework is intended to support design by addressing three critical design objectives, including novelty, optimality, and robustness. It provides several computational models and methods, which are inspired by fundamental processes occurring in nature, and discusses their potential for enhancing design. They include models and methods for evolutionary, developmental, and coevolutionary design. Their use is illustrated with examples from the area of steel structural design ranging from a simple cantilever beam design problem to a much more complex problem of designing wind bracings in tall buildings. The paper also shows how several methods and models can be integrated and form a coherent bioinspired computational framework for engineering design.     

Determination of EEG activity propagation: pair-wise versus multichannel estimate

Performance of different estimators describing propagation of electroencephalogram (EEG) activity, namely: Granger causality, directed transfer function (DTF), direct DTF (dDTF), short-time DTF (SDTF), bivariate coherence, and partial directed coherence are compared by means of simulations and on the examples of experimental signals. In particular, the differences between pair-wise and multichannel estimates are studied. The results show unequivocally that in most cases, the pair-wise estimates are incorrect and a complete set of signals involved in a given process has to be used to obtain the correct pattern of EEG flows. Different performance of multivariate estimators of propagation depending on their normalization is discussed. Advantages of multivariate autoregressive model are pointed out.     

Business owners' action planning and its relationship to business success in three African countries.

A model of business success was developed with motivational resources (locus of control, self-efficacy, achievement motivation, and self-reported personal initiative) and cognitive resources (cognitive ability and human capital) as independent variables, business owners' elaborate and proactive planning as a mediator, and business size and growth as dependent variables. Three studies with a total of 408 African micro and small-scale business owners were conducted in South Africa, Zimbabwe, and Namibia. Structural equation analyses partially supported the hypotheses on the importance of psychological planning by the business owners. Elaborate and proactive planning was substantially related to business size and to an external evaluation of business success and was a (partial) mediator for the relationship between cognitive resources and business success. The model carries important implications for selection, training, and coaching of business owners. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Abstracting for Dimensionality Reduction in Text Classification

There is a growing interest in efficient models of text mining and an emergent need for new data structures that address word relationships. Detailed knowledge about the taxonomic environment of keywords that are used in text documents can provide valuable insight into the nature of the subject matter contained therein. Such insight may be used to enhance the data structures used in the text data mining task as relationships become usefully apparent. A popular scalable technique used to infer these relationships, while reducing dimensionality, has been Latent Semantic Analysis. We present a new approach, which uses an ontology of lexical abstractions to create abstraction profiles of documents and uses these profiles to perform text organization based on a process that we call frequent abstraction analysis. We introduce TATOO, the Text Abstraction TOOlkit, which is a full implementation of this new approach. We present our data model via an example of how taxonomically derived abstractions can be used to supplement semantic data structures for the text classification task.     

Graphoepitaxy of High‐Quality GaN Layers on Graphene/6H–SiC

The implementation of graphene layers in gallium nitride (GaN) heterostructure growth can solve self‐heating problems in nitride‐based high‐power electronic and light‐emitting optoelectronic devices. In the present study, high‐quality GaN layers are grown on patterned graphene layers and 6H–SiC by metalorganic chemical vapor deposition. A periodic pattern of graphene layers is fabricated on 6H–SiC by using polymethyl methacrylate deposition and electron beam lithography, followed by etching using an Ar/O₂ gas atmosphere. Prior to GaN growth, an AlN buffer layer and an Al_0.2Ga_0.8N transition layer are deposited. The atomic structures of the interfaces between the 6H–SiC and graphene, as well as between the graphene and AlN, are studied using scanning transmission electron microscopy. Phase separation of the Al_0.2Ga_0.8N transition layer into an AlN and GaN superlattice is observed. Above the continuous graphene layers, polycrystalline defective GaN is rapidly overgrown by better quality single‐crystalline GaN from the etched regions. The lateral overgrowth of GaN results in the presence of a low density of dislocations (≈10⁹ cm⁻²) and inversion domains and the formation of a smooth GaN surface.     

Active Targeting Using HER‐2‐Affibody‐Conjugated Nanoparticles Enabled Sensitive and Specific Imaging of Orthotopic HER‐2 Positive Ovarian Tumors

Despite advances in cancer diagnosis and treatment, ovarian cancer remains one of the most fatal cancer types. The development of targeted nanoparticle imaging probes and therapeutics offers promising approaches for early detection and effective treatment of ovarian cancer. In this study, HER‐2 targeted magnetic iron oxide nanoparticles (IONPs) are developed by conjugating a high affinity and small size HER‐2 affibody that is labeled with a unique near infrared dye (NIR‐830) to the nanoparticles. Using a clinically relevant orthotopic human ovarian tumor xenograft model, it is shown that HER‐2 targeted IONPs are selectively delivered into both primary and disseminated ovarian tumors, enabling non‐invasive optical and MR imaging of the tumors as small as 1 mm in the peritoneal cavity. It is determined that HER‐2 targeted delivery of the IONPs is essential for specific and sensitive imaging of the HER‐2 positive tumor since we are unable to detect the imaging signal in the tumors following systemic delivery of non‐targeted IONPs into the mice bearing HER‐2 positive SKOV3 tumors. Furthermore, imaging signals and the IONPs are not detected in HER‐2 low expressing OVCAR3 tumors after systemic delivery of HER‐2 targeted‐IONPs. Since HER‐2 is expressed in a high percentage of ovarian cancers, the HER‐2 targeted dual imaging modality IONPs have potential for the development of novel targeted imaging and therapeutic nanoparticles for ovarian cancer detection, targeted drug delivery, and image‐guided therapy and surgery.     

Metadata requirements for digital museum environments

We describe a system which addresses all the processes involved in digitally acquiring, modelling, storing, manipulating and creating virtual exhibitions from 3D museum artefacts. More specifically, we examine the significance of metadata in enabling and supporting all of these processes and describe the extensive facilities provided for authoring, maintaining and managing metadata. The development of the system has been heavily influenced by factors relating to interoperability, standards, museum best practice and feedback from two museum pilot sites. Finally, we briefly consider the system in the wider context of applications such as virtual learning environments and distributed repositories of archives.     

Activating response codes by stimuli in the neglected visual field.

The ability of 2 patients with a clinical deficit of extinction to process stimuli presented contralaterally to their lesions was tested with 2 variants of the flanker task. The patients saw 2 colored stimuli, 1 of which appeared in the center of the visual field and the other either on the ipsior contralateral side. In the peripheral report task, the patients had to report the color of the peripheral stimulus. In the center report task, the patients had to report the color of the central stimulus. The patients were much slower in the peripheral report task when the target was presented contralaterally to their lesion. By contrast, the responses in the center report task were equally influenced by ipsi- and contralateral flankers. The findings indicate that the patients were not impaired in the perceptual processing or the activation of response codes for contralateral stimuli. Their impairment is related to processes needed for generation of overt responses. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Light‐Driven Proton Transfer for Cyclic and Temporal Switching of Enzymatic Nanoreactors

Temporal activation of biological processes by visible light and subsequent return to an inactive state in the absence of light is an essential characteristic of photoreceptor cells. Inspired by these phenomena, light‐responsive materials are very attractive due to the high spatiotemporal control of light irradiation, with light being able to precisely orchestrate processes repeatedly over many cycles. Herein, it is reported that light‐driven proton transfer triggered by a merocyanine‐based photoacid can be used to modulate the permeability of pH‐responsive polymersomes through cyclic, temporally controlled protonation and deprotonation of the polymersome membrane. The membranes can undergo repeated light‐driven swelling–contraction cycles without losing functional effectiveness. When applied to enzyme loaded‐nanoreactors, this membrane responsiveness is used for the reversible control of enzymatic reactions. This combination of the merocyanine‐based photoacid and pH‐switchable nanoreactors results in rapidly responding and versatile supramolecular systems successfully used to switch enzymatic reactions ON and OFF on demand.