Isoindigo dye incorporated copolymers with naphthalene and anthracene: promising materials for stable organic field effect transistors

In this paper, we report the design and synthesis of isoindigo based low band gap polymer semiconductors, poly{N,N′-(2-octyldodecyl)-isoindigo-alt- naphthalene} (PISD-NAP) and poly{N,N′-(2-octyldodecyl)-isoindigo-alt- anthracene} (PISD-ANT). A series of donor-acceptor (D-A) copolymers can be prepared where donor and acceptor conjugated blocks can be attached alternately using organometallic coupling. In these polymers, an isoindigo dye acceptor moiety has been attached alternately with naphthalene and anthracene donor comonomer blocks by Suzuki coupling. PISD-NAP and PISD-ANT exhibit excellent solution processibility and good film-forming properties. Gel permeation chromatography exhibits a higher molecular mass with lower polydispersity. UV-vis-NIR absorption of these polymers exhibits a wide absorption band ranging from 300 nm to 800 nm, indicating the low band gap nature of the polymers. Optical band gaps calculated from the solid state absorption cutoff value for PISD-NAP and PISD-ANT are around 1.80 eV and 1.75 eV, respectively. Highest occupied molecular orbital (HOMO) values calculated respectively for PISD-NAP and PISD-ANT thin films on glass substrate by photoelectron spectroscopy in air (PESA) are 5.66 eV and 5.53 eV, indicative of the good stability of these materials in organic electronic device applications. These polymers exhibit p-channel charge transport characteristics when used as the active semiconductor in organic thin-film transistor (OTFT) devices in ambient conditions. The highest hole mobility of 0.013 cm2 V-1 s-1 is achieved in top contact and bottom-gate OTFT devices for PISD-ANT, whereas polymer PISD-NAP exhibited a hole mobility of 0.004 cm2 V -1 s-1. When these polymer semiconductors were used as a donor and PC71BM as an acceptor in OPV devices, the highest power conversion efficiency (PCE) of 1.13% is obtained for the PISD-ANT polymer.

Commitment to internationalisation : an extension of the internationalisation process model

Notwithstanding the interest over many years by scholars in modeling the internationalization of the firm, the initial transition for the firm from domestic to international operations remains under-researched. We identify the behavioral factors that are important at the pre-internationalization state and discuss how they may interrelate to influence a decision to commit to internationalization through export commencement. We study export commitment by proposing and constructing an index that incorporates the factors that influence a firm’s propensity to commit to export activities. Utilizing the items from this index in a logistic regression analysis, we distinguish between the pre-internationalization characteristics of exporting and non-exporting firms to better understand the key influences in export commitment. Implications are discussed.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

Investigations of dielectric monitoring on an energised transformer oil–paper insulation system

Frequency domain spectroscopy (FDS) is being used to assess the insulation condition of oil–paper power transformers. However, it has to date only been implemented on de-energised transformers, which requires the transformers to be shut down for an extended period and may cause significant costs. To solve this issue, a newly improved monitoring method based on the FDS principle is proposed to implement the dielectric measurement on energised transformers. Moreover, a chirp waveform excitation and its novel processing method are introduced. Compared with the conventional FDS results, dielectric results from the energised insulation system have higher tanδ values because of the increased losses. To further understand the insulation ageing process, the effects of the geometric capacitance are removed from the measured imaginary admittance of the insulation system to enhance the ageing signature. The resulting imaginary admittance is then shown to correlate well with the central time constant in return voltage measurements results. The proposed methods address the issues on techniques used on energised transformers and provide a clue for on-line FDS diagnostic application.

Controlling the surface roughness of epitaxial SiC on silicon

The surface of cubic silicon carbide (3C-SiC) hetero-epitaxial films grown on the (111) surface of silicon is a promising template for the subsequent epitaxial growth of III-V semiconductor layers and graphene. We investigate growth and post-growth approaches for controlling the surface roughness of epitaxial SiC to produce an optimal template. We first explore 3C-SiC growth on various degrees of offcut Si(111) substrates, although we observe that the SiC roughness tends to worsen as the degree of offcut increases. Hence we focus on post-growth approaches available on full wafers, comparing chemical mechanical polishing (CMP) and a novel plasma smoothening process. The CMP leads to a dramatic improvement, bringing the SiC surface roughness down to sub-nanometer level, though removing about 200 nm of the SiC layer. On the other hand, our proposed HCl plasma process appears very effective in smoothening selectively the sharpest surface topography, leading up to 30% improvement in SiC roughness with only about 50 nm thickness loss. We propose a simple physical model explaining the action of the plasma smoothening.

Multiliteracies pedagogy : creating claymations with adolescent, post-beginner English language learners

In addressing literacy in high school education, it is important to foreground the particular issues faced by growing numbers of English Language Learners (ELLs). In our increasingly culturally and linguistically diverse classrooms, this is a matter for all literacy teachers, as well as ELL specialists. In Australia, teachers of ELLs are experimenting with Multiliteracies pedagogy which provides rich opportunities to explore language learning experiences and outcomes that stretch beyond exercises in reproduction in written and oral modes only. This paper documents the practice of a high school teacher who uses a claymation project, producing a movie by stop-motion filming of clay figures, with a class of low-level English literacy learners. Drawing on observations of three particular students, the paper outlines a number of possibilities of this approach for English language learners. These include increased individual agency; enhanced engagement through collaboration; and the opportunity to explore various elements of multimodal text design.

Branding and planning urban knowledge precincts : insights from Brisbane, Australia

Purpose: The paper aims to investigate urban knowledge precincts from the angle of urban planning and place branding. Scope: The paper focuses on urban knowledge precinct development experiences of Brisbane, Australia. Method: The paper uses literature review, policy and content analyses and field observation methods to explore Brisbane’s urban knowledge precincts. Results: The paper reveals insights from Brisbane’s urban knowledge precincts development journey. Recommendations: The paper suggests further research on the topic of branding and planning urban knowledge precincts. Conclusions: The paper reveals that urban knowledge precincts are the nexus of knowledge-based urban development and Brisbane’s precincts potentially provide a competitive edge to the city in the global knowledge economy era.

An urban design perspective to classify knowledge precincts : a typological analysis of global best practices

Purpose: The paper seeks to investigate emerging knowledge precincts under the urban design lens in order to identify recurrent spatial patterns of urban forms and functions to gather an understanding of physical aspects that contribute to the creation of place quality. Scope: This paper focuses on the physical design and layout of specific precincts. Although socio-economic and other factors come into play imparting the distinctiveness; this paper only focuses on the spatial dimensions. Method: The research first develops a design typology framework through the lead of literature, and then utilizes it to identify recurrent elements in knowledge precinct design in order to develop taxonomy of patterns and layouts. Results: The research reported in this paper provides preliminary insights into the various form and functional factors playing role in the design of knowledge precincts and evaluates the elements that contribute to the success of these urban interventions. Recommendations: The paper recommends the use of particular design-based solutions in order to enhance the place making in knowledge precincts. Conclusions: The study concludes that despite the locational, regulatory and other contextual differences, the underlying driving principle of providing place quality to people leads to the emergence of identifiable spatial patterns across the knowledge precincts.

Innate transcriptional networks activated in bladder in response to uropathogenic Escherichia coli drive diverse biological pathways and rapid synthesis of IL-10 for defense against bacterial urinary tract infection

Early transcriptional activation events that occur in bladder immediately following bacterial urinary tract infection (UTI) are not well defined. In this study, we describe the whole bladder transcriptome of uropathogenic Escherichia coli (UPEC) cystitis in mice using genome-wide expression profiling to define the transcriptome of innate immune activation stemming from UPEC colonization of the bladder. Bladder RNA from female C57BL/6 mice, analyzed using 1.0 ST-Affymetrix microarrays, revealed extensive activation of diverse sets of innate immune response genes, including those that encode multiple IL-family members, receptors, metabolic regulators, MAPK activators, and lymphocyte signaling molecules. These were among 1564 genes differentially regulated at 2 h postinfection, highlighting a rapid and broad innate immune response to bladder colonization. Integrative systems-level analyses using InnateDB (http://www.innatedb.com) bioinformatics and ingenuity pathway analysis identified multiple distinct biological pathways in the bladder transcriptome with extensive involvement of lymphocyte signaling, cell cycle alterations, cytoskeletal, and metabolic changes. A key regulator of IL activity identified in the transcriptome was IL-10, which was analyzed functionally to reveal marked exacerbation of cystitis in IL-10–deficient mice. Studies of clinical UTI revealed significantly elevated urinary IL-10 in patients with UPEC cystitis, indicating a role for IL-10 in the innate response to human UTI. The whole bladder transcriptome presented in this work provides new insight into the diversity of innate factors that determine UTI on a genome-wide scale and will be valuable for further data mining. Identification of protective roles for other elements in the transcriptome will provide critical new insight into the complex cascade of events that underpin UTI.

Escherichia coli 83972 expressing a P fimbriae oligosaccharide receptor mimic impairs adhesion of Uropathogenic E. coli

Urinary tract infections (UTIs) caused by uropathogenic Escherichia coli (UPEC) are a significant health concern, exacerbated by the rapid emergence of multidrug resistant strains refractory to antibiotic treatment. P fimbriae are strongly associated with upper urinary tract colonization due to specific binding to α-D-galactopyranosyl-(1-4)-β-D-galactopyranoside receptors in the kidneys. Thus, inhibiting P-fimbrial adhesion may reduce the incidence of UPEC-mediated UTI. E. coli 83972 is an asymptomatic bacteriuria isolate successfully used as a prophylactic agent to prevent UTI in human studies. We constructed a recombinant E. coli 83972 strain displaying a surface-located oligosaccharide P fimbriae receptor mimic that bound to P-fimbriated E. coli producing any of the 3 PapG adhesin variants. The recombinant strain, E. coli 83972:: lgtCE, impaired P fimbriae–mediated adhesion to human erythrocytes and kidney epithelial cells. Additionally, E. coli 83972::lgtCE impaired urine colonization by UPEC in a mouse UTI model, demonstrating its potential as a prophylactic agent to prevent UTI.

Impact of al passivation and cosputter on the structural property of β-FeSi2 for Al-Doped β-FeSi2/ n -Si(100) based solar cells application

The aluminum (Al) doped polycrystalline p-type β-phase iron disilicide (p-β-FeSi2) is grown by thermal diffusion of Al from Al-passivated n-type Si(100) surface into FeSi2 during crystallization of amorphous FeSi2 to form a p-type β-FeSi 2/n-Si(100) heterostructure solar cell. The structural and photovoltaic properties of p-type β-FeSi2/n-type c-Si structures is then investigated in detail by using X-ray diffraction, Raman spectroscopy, transmission electron microscopy analysis, and electrical characterization. The results are compared with Al-doped p-β-FeSi2 prepared by using cosputtering of Al and FeSi2 layers on Al-passivated n-Si(100) substrates. A significant improvement in the maximum open-circuit voltage (Voc) from 120 to 320 mV is achieved upon the introduction of Al doping through cosputtering of Al and amorphous FeSi2 layer. The improvement in Voc is attributed to better structural quality of Al-doped FeSi2 film through Al doping and to the formation of high quality crystalline interface between Al-doped β-FeSi2 and n-type c-Si. The effects of Al-out diffusion on the performance of heterostructure solar cells have been investigated and discussed in detail.