Does gender inequality reduce growth in sub-Saharan African and Arab countries?

This paper uses 1974 to 2001 panel data for 31 sub-Saharan African and 10 Arab countries and Arellano–Bond estimations to empirically assess the impact on growth of an important indicator associated with MDG 3; namely the ratio of 15–24-year-old literate females to males. Our findings indicate that gender inequalities in literacy have a statistically significant negative effect that is robust to changes in the specification. In addition, it seems that gender inequality has a stronger effect on growth in Arab countries. Interestingly, we find that the interaction between openness to trade and gender inequality has a positive impact. This result suggests that trade-induced growth may be accompanied by greater gender inequalities.

Measuring the vulnerability of sub-national regions in South Africa

A small but growing literature has been concerned about the economic (and
environmental) vulnerability on the level of countries. Less attention is paid to the economic vulnerability of different regions within countries. By focusing on the vulnerability of subnational regions, this paper contributes to the small literature on the “vulnerability of place”. They authors see the vulnerability of place as being due to vulnerability in various domains, such as economic vulnerability, vulnerability of environment, and governance, demographic and health fragilities. They use a subnational data set on 354 magisterial districts from South Africa, recognize the potential relevance of measuring vulnerability on a subnational level, and construct a Local Vulnerability Index for the various districts. They condition this index on district per capita income and term this a Vulnerability Intervention Index, interpreting this as an indicator of where higher income per capita, often seen in the literature as a measure of resilience, will in itself be unlikely to reduce vulnerability.

Convergence among the sub-markets in Australian regional building and construction sector

Studies on market convergence are well considered in the literature. However, the majority of the previous research focused on housing markets and few studies have concentrated on construction markets. Owing to a simultaneously dramatic increase in the construction prices of the sub-markets in the building construction sector in Australia, this paper aims to identify the convergence among these markets, involving house construction market, other-residential building construction market, and non-residential building construction market. To achieve it the Granger causality test and generalized response function depending on the vector error correction model with the quarterly data of Australia’s eight states from 1998 to 2010 will be applied. Based upon the econometric tests, the price diffusion patterns among these construction markets have been identified. Research on the convergences of construction markets not only helps construction firms perform well in business operations and arbitrage activities, but also provides policy makers with useful information for enacting effective construction policies for national perspectives and approaches to infrastructure planning.

Knowledge on road information in sub-urban lane detection via multiple cue integration

Detection of lane boundaries of a road based on the images or video taken by a video capturing device in a suburban environment is a challenging task. In this paper, a novel lane detection algorithm is proposed without considering camera parameters; which robustly detects lane boundaries in real-time especially for sub-urban roads. Initially, the proposed method fits the CIE L*a*b* transformed road chromaticity values (that is a* and b* values) to a bi-variate Gaussian model followed by the classification of road area based on Mahalanobis distance. Secondly, the classified road area acts as an arbitrary shaped region of interest (AROI) in order to extract blobs resulting from the filtered image by a two dimensional Gabor filter. This is considered as the first cue of images. Thirdly, another cue of images was employed in order to obtain an entropy image. Moreover, results from the color based image cue and entropy image cue were integrated following an outlier removing process. Finally, the correct road lane points are fitted with Bezier splines which act as control points that can form arbitrary shapes. The algorithm was implemented and experiments were carried out on sub-urban roads. The results show the effectiveness of the algorithm in producing more accurate lane boundaries on curvatures and other objects on the road.

Sub-ppt detection limits for copper ions with Gly-Gly-His modified electrodes

An electrochemical metal ion sensor has been developed with a detection limit of less than 0.2 ppt by the covalent attachment of the tripeptide Gly-Gly-His as a recognition element to a 3-mercaptopropionic acid modified gold electrode.

Redox voltammetry of sub-parts per billion levels of Cu2+ at polyaspartate-modified gold electrodes

An electrochemical sensor for the detection of Cu2+ is reported which incorporates poly-l-aspartic acid (PLAsp) with 32–96 aspartate units as a selective ligand for the metal ion. PLAsp is covalently attached to a gold electrode modified with a monolayer of 3-mercaptopropionic acid using carbodiimide coupling via an N-hydroxysuccinimide (NHS) ester intermediate. The acid side groups and deprotonated peptide nitrogens on two aspartate moieties are thought to be primarily responsible for chelation of Cu2+, which remains bound when reduced to Cu+. A consequence of the multiple binding points that are available with a polypeptide is the low detection limit. The lowest concentration detected was 3 nM (0.2 ppb) achieved with Osteryoung square wave voltammetry. This detection limit compares favourably with that of ICP-OES and previously reported cysteine-modified electrodes. Analysis of tap and lake water samples using the PLAsp-modified electrode agreed well with ICP-OES analysis of the same samples.

Sensitivity analysis of a sub-wavelength localized surface plasmon resonance graphene biosensor

Localized surface plasmon resonance (LSPR) is a promising detection method for label-free sensing of biomolecules. In this paper, a multilayer design for a LSPR biosensor is presented. In the proposed design, a periodic array of dielectric grating is incorporated on top of a graphene layer in the biosensor. The aim is to improve sensitivity of the LSPR biosensor through monitoring biomolecular interactions of biotin-streptavidin. Sensitivity improvement is obtained for the proposed LSPR biosensor compared with conventional SPR counterparts. In addition, to optimize the design, we have investigated grating geometry including volume factor and grating depth. The outcome of this investigation identifies ideal functioning conditions corresponding to the best design parameters.