Size- and orientation-selective Si nanowire growth : thermokinetic effects of naeoscale plasma chemistry

A multiscale, multiphase thermokinetic model is used to show the effective control of the growth orientation of thin Si NWs for nanoelectronic devices enabled by nanoscale plasma chemistry. It is shown that very thin Si NWs with [110] growth direction can nucleate at much lower process temperatures and pressures compared to thermal chemical vapor deposition where [111]-directed Si NWs are predominantly grown. These findings explain a host of experimental results and offer the possibility of energy- and matter-efficient, size- and orientation-controlled growth of [110] Si NWs for next-generation nanodevices.

An orientation to early childhood education for sustainability and research : framing the text

This publication arose from the interests of the chapter authors, ‘a small group of thoughtful people’ almost all of whom participated in one or both Transnational Dialogues in Research in Early Childhood Education for Sustainability, held in Stavanger, Norway in 2010 and Brisbane, Australia in 2011 (Refer Appendix 1 for list of participants). These meetings were the first time that a critical mass of researchers from vastly different parts of the globe - Norway, Sweden, Australia and New Zealand at the inaugural meeting, with additional participants from Korea, Japan and Singapore attending the second - had come together to debate, discuss and share ideas about research and theory in the emerging field of Early Childhood Education for Sustainability (ECEfS. Some of the researchers who joined these Transnational Dialogues, had met serendipitously at earlier conferences and meetings, or corresponded via email, but many had never met face-to-face. Now a significant number are contributing authors in this text. It is a testament to these researchers’ interest in this agenda that they mostly self-funded their travel and other costs to attend the Transnational Dialogues research meetings. While most chapter authors come from the field of early childhood education, a few are more aligned with education for sustainability/environmental education, while a much smaller number are already working at the intersection of early childhood education and education for sustainability. What we share as a group is a range of perspectives and orientations to research and to the research focus at the heart of this book - young children and their actual and potential capabilities as agents of change for sustainability. As researchers, regardless of experience and perspectives, participants knew they had something extra to offer - their expertise as researchers - providing scholarly insights into the work of practitioners, applying critically reflective lenses to curricula, pedagogies and assumptions, testing of ideas and theories, and presenting a sense for where ECEfS might fit or, indeed, go beyond norms and orthodoxies. This is a text, then, for both researchers and those whose primary interests lie in daily interactions with children, families and communities.

3,6-Di(furan-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione and bithiophene copolymer with rather disordered chain orientation showing high mobility in organic thin film transistors

Pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione or diketopyrrolopyrrole (DPP) is a useful electron-withdrawing fused aromatic moiety for the preparation of donor-acceptor polymers as active semiconductors for organic electronics. This study uses a DPP-furan-containing building block, 3,6-di(furan-2-yl)pyrrolo[3,4- c]pyrrole-1,4(2H,5H)-dione (DBF), to couple with a 2,2′-bithiophene unit, forming a new donor-acceptor copolymer, PDBFBT. Compared to its structural analogue, 3,6-di(thiophen-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione (DBT), DBF is found to cause blue shifts of the absorption spectra both in solution and in thin films and a slight reduction of the highest occupied molecular orbital (HOMO) energy level of the resulting PDBFBT. Despite the fact that its thin films are less crystalline and have a rather disordered chain orientation in the crystalline domains, PDBFBT shows very high hole mobility up to 1.54 cm 2 V-1 s-1 in bottom-gate, top-contact organic thin film transistors.

Exploring the effect of achievements on students attending university orientation

University orientation is a key event for new students that aids in the transition from a school to a university environment. A smartphone orientation application was built to aid students attending the event. Achievements were added to the application in an attempt to engage students further with the orientation activities and application. An exploratory field study was undertaken to evaluate the effect of the achievement system on participants attending orientation. Forty-six new students were recruited to test the orientation application. Twenty-six participants used a gamified version of the orientation application and twenty participants used a non-gamified version. While the gamification was generally well received, no impact on user experience was evident. Some effect on engagement with orientation activities was shown. Participants who used the gamified system reported the game elements as fun, but some negative issues arose, such as cheating.

A two-stage item recommendation method using probabilistic ranking with reconstructed tensor model

In a tag-based recommender system, the multi-dimensional correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

Amino group position dependent orientation of self-assembled monomolecular films of tetraaminophthalocyanatocobalt(II) on Au surfaces

Self-assembled monomolecular films of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) and 2,9,16,23-tetraaminophthalocyanatocobalt(II) (4β-CoIITAPc) on Au surfaces were prepared by spontaneous adsorption from solution. These films were characterized by cyclic voltammetry and Raman spectroscopy. Both the surface coverage (Γ) and intensity of the in-plane stretching bands obtained from Raman studies vary for these monomolecular films, indicating different orientations adopted by them on Au surfaces. The 4α-CoIITAPc-modified electrode exhibits an E1/2 of 0.35 V, while the 4β-CoIITAPc-modified electrode exhibits an E1/2 of 0.19 V, corresponding to the CoII/CoIII redox couple in 0.1 M H2SO4. The Γ estimated from the charge associated with the oxidation of Co(II) gives (2.62 ± 0.10) × 10-11 mol cm-2 for 4α-CoIITAPc and (3.43 ± 0.14) × 10-10 mol cm-2 for 4β-CoIITAPc. In Raman spectral studies, the intensity ratio between in-plane phthalocyanine (Pc) stretching and the Au−N stretching was found to be 6.6 for 4β-CoIITAPc, while it was 1.6 for 4α-CoIITAPc. The obtained lower Γ and intensity ratio values suggest that 4α-CoIITAPc adopts nearly a parallel orientation on the Au surface, while the higher Γ and intensity ratio values suggest that 4β-CoIITAPc adopts a perpendicular orientation. The electrochemical reduction of dioxygen was carried out using these differently oriented Pc's in phosphate buffer solution (pH 7.2). Both the Pc's catalyze the reduction of dioxygen; however, the 4α-CoIITAPc-modified electrode greatly reduces the dioxygen reduction overpotential compared to 4β-CoIITAPc-modified and bare Au electrodes.

Tensor reduction for user profiling in personalized recommender systems

User profiling is the process of constructing user models which represent personal characteristics and preferences of customers. User profiles play a central role in many recommender systems. Recommender systems recommend items to users based on user profiles, in which the items can be any objects which the users are interested in, such as documents, web pages, books, movies, etc. In recent years, multidimensional data are getting more and more attention for creating better recommender systems from both academia and industry. Additional metadata provides algorithms with more details for better understanding the interactions between users and items. However, most of the existing user/item profiling techniques for multidimensional data analyze data through splitting the multidimensional relations, which causes information loss of the multidimensionality. In this paper, we propose a user profiling approach using a tensor reduction algorithm, which we will show is based on a Tucker2 model. The proposed profiling approach incorporates latent interactions between all dimensions into user profiles, which significantly benefits the quality of neighborhood formation. We further propose to integrate the profiling approach into neighborhoodbased collaborative filtering recommender algorithms. Experimental results show significant improvements in terms of recommendation accuracy.

Thermal behavior of kaolinite–urea intercalation complex and molecular dynamics simulation for urea molecule orientation

The thermal behavior of kaolinite–urea intercalation complex was investigated by thermogravimetry–differential scanning calorimetry (TG–DSC), X-ray diffraction (XRD), and fourier transform infrared spectroscopy (FTIR). In addition, the interaction mode of urea molecules intercalated into the kaolinite gallery was studied by means of molecular dynamics simulation. Three main mass losses were observed at 136 °C, in the range of 210–270 °C, and at 500 °C in the TG–DSC curves, which were, respectively, attributed to (1) melting of the surface-adsorbed urea, (2) removal of the intercalated urea, and (3) dehydroxylation of the deintercalated kaolinite. The three DSC endothermic peaks at 218, 250, and 261 °C were related to the successive removals of intercalated urea with three different distribution structures. Based on the angle between the dipole moment vector of urea and the basal surface of kaolinite, the three urea models could be described as follows: (1) Type A, the dipole moment vector is nearly parallel to the basal surface of kaolinite; (2) Type B, the dipole moment vector points to the silica tetrahedron with the angle between it and the basal surface of kaolinite ranging from 20°to 40°; and (3) Type C, the dipole moment vector is nearly perpendicular to the basal surface of kaolinite. The three distribution structures of urea molecules were validated by the results of the molecular dynamics simulation. Furthermore, the thermal behavior of the kaolinite–urea intercalation complex investigated by TG–DSC was also supported by FTIR and XRD analyses.

Effects of layer orientation of CFRP strengthened steel hollow members

This paper reveals the effects of layer orientation on structural behaviour of three layers configured (LHL, HHL, LLH) CFRP strengthened circular hollow section (CHS) members subjected to bending. The beams were loaded to failure under four-point bending. The structural behaviour of the CFRP strengthened tubular steel beams with various layer orientations were presented in terms of failure load, stiffness, composite beam action and modes of failure. The LHL and LLH layers oriented strengthened beams perform slightly better than HHL layers oriented strengthened beams. The LHL and LLH layers oriented treated beams showed very similar structural behaviour.

A tensor-based morphometry study of genetic influences on brain structure using a new fluid registration method

We incorporated a new Riemannian fluid registration algorithm into a general MRI analysis method called tensor-based morphometry to map the heritability of brain morphology in MR images from 23 monozygotic and 23 dizygotic twin pairs. All 92 3D scans were fluidly registered to a common template. Voxelwise Jacobian determinants were computed from the deformation fields to assess local volumetric differences across subjects. Heritability maps were computed from the intraclass correlations and their significance was assessed using voxelwise permutation tests. Lobar volume heritability was also studied using the ACE genetic model. The performance of this Riemannian algorithm was compared to a more standard fluid registration algorithm: 3D maps from both registration techniques displayed similar heritability patterns throughout the brain. Power improvements were quantified by comparing the cumulative distribution functions of the p-values generated from both competing methods. The Riemannian algorithm outperformed the standard fluid registration.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Mapping the regional influence of genetics on brain structure variability - A Tensor-Based Morphometry study

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.