From slum to suburbia : examining a spectrum of planned and unplanned urban morphology in humid sub-tropical regions of the world

The current rapid urban growth throughout the world manifests in various ways and historically cities have grown, similarly, alternately or simultaneously between planned extensions and organic informal settlements (Mumford, 1989). Within cities different urban morphological regions can reveal different contexts of economic growth and/or periods of dramatic social/technological change (Whitehand, 2001, 105). Morpho-typological study of alternate contexts can present alternative models and contribute to the present discourse which questions traditional paradigms of urban planning and design (Todes et al, 2010). In this study a series of cities are examined as a preliminary exploration into the urban morphology of cities in ‘humid subtropical’ climates. From an initial set of twenty, six cities were selected: Sao Paulo, Brazil; Jacksonville, USA; Maputo, Mozambique; Kanpur, India; Hong Kong, China; and Brisbane, Australia. The urban form was analysed from satellite imagery at a constant scale. Urban morphological regions (types) were identified as those demonstrating particular consistant characteristics of form (density, typology and pattern) different to their surroundings when examined at a constant scale. This analysis was correlated against existing data and literature discussing the proliferation of two types of urban development, ‘informal settlement’ (defined here as self-organised communities identifiable but not always synonymous with ‘slums’) and ‘suburbia’ (defined here as master planned communities of generally detached houses prevalent in western society) - the extreme ends of a hypothetical spectrum from ‘planned’ to ‘spontaneous’ urban development. Preliminary results show some cities contain a wide variety of urban form ranging from the highly organic ‘self-organised’ type to the highly planned ‘master planned community’ (in the case of Sao Paulo) while others tend to fall at one end of the planning spectrum or the other (more planned in the cases of Brisbane and Jacksonville; and both highly planned and highly organic in the case of Maputo). Further research will examine the social, economical and political drivers and controls which lead to this diversity or homogeneity of urban form and speculates on the role of self-organisation as a process for the adaptation of urban form.

Weight bias on psychological and physical health

It is a round table discussion article. "Weight bias refers to negative weight-related attitudes and beliefs, expressed in a range of forms towards individuals who are overweight or obese. Consequences of weight bias could be very significant to the individuals which may predispose them to additional weight gain. This brief literature review discusses the concept of weight bias and its impact on psychological and physical health on overweight and obese individuals..."

'It ain't over till it's over' : Yogi Berra bias on prediction markets

The recent expansion of prediction markets provides a great opportunity to test the market efficiency hypothesis and the calibration of trader judgements. Using a large database of observed prices, this article studies the calibration of prediction markets prices on sporting events using both nonparametric and parametric methods. While only minor bias can be observed during most of the lifetime of the contracts, the calibration of prices deteriorates very significantly in the last moments of the contracts’ lives. Traders tend to overestimate the probability of the losing team to reverse the situation in the last minutes of the game.

Jackknife for bias reduction in predictive regressions

One of the fundamental econometric models in finance is predictive regression. The standard least squares method produces biased coefficient estimates when the regressor is persistent and its innovations are correlated with those of the dependent variable. This article proposes a general and convenient method based on the jackknife technique to tackle the estimation problem. The proposed method reduces the bias for both single- and multiple-regressor models and for both short- and long-horizon regressions. The effectiveness of the proposed method is demonstrated by simulations. An empirical application to equity premium prediction using the dividend yield and the short rate highlights the differences between the results by the standard approach and those by the bias-reduced estimator. The significant predictive variables under the ordinary least squares become insignificant after adjusting for the finite-sample bias. These discrepancies suggest that bias reduction in predictive regressions is important in practical applications.

Spectrum sensing, detection and optimisation in cognitive radio for non-stationary primary user signals

Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

Experimental observations of rapid maize streak virus evolution reveal a strand-specific nucleotide substitution bias

Background. Recent reports have indicated that single-stranded DNA (ssDNA) viruses in the taxonomic families Geminiviridae, Parvoviridae and Anellovirus may be evolving at rates of ∼10-4 substitutions per site per year (subs/site/year). These evolution rates are similar to those of RNA viruses and are surprisingly high given that ssDNA virus replication involves host DNA polymerases with fidelities approximately 10 000 times greater than those of error-prone viral RNA polymerases. Although high ssDNA virus evolution rates were first suggested in evolution experiments involving the geminivirus maize streak virus (MSV), the evolution rate of this virus has never been accurately measured. Also, questions regarding both the mechanistic basis and adaptive value of high geminivirus mutation rates remain unanswered. Results. We determined the short-term evolution rate of MSV using full genome analysis of virus populations initiated from cloned genomes. Three wild type viruses and three defective artificial chimaeric viruses were maintained in planta for up to five years and displayed evolution rates of between 7.4 × 10-4 and 7.9 × 10-4 subs/site/year. Conclusion. These MSV evolution rates are within the ranges observed for other ssDNA viruses and RNA viruses. Although no obvious evidence of positive selection was detected, the uneven distribution of mutations within the defective virus genomes suggests that some of the changes may have been adaptive. We also observed inter-strand nucleotide substitution imbalances that are consistent with a recent proposal that high mutation rates in geminiviruses (and possibly ssDNA viruses in general) may be due to mutagenic processes acting specifically on ssDNA molecules. © 2008 Walt et al; licensee BioMed Central Ltd.

Gender bias in schooling : the case for Bhutan

Differing parental considerations for girls and boys in households are a primary cause of the gender gap in school enrolment and educational attainment in developing countries, particularly in Sub-Saharan Africa and South Asia. While a number of studies have focused on the inequality of educational opportunities in South Asia, little is known about Bhutan. This study uses recent household expenditure data from the Bhutan Living Standard Survey to evaluate the gender gap in the allocation of resources for schooling. The findings, based on cross-sectional as well as household fixed-effect approaches, suggest that girls are less likely to enrol in school but are not allocated fewer resources once they are enrolled.

Assessment bias : physical activity questionnaire assessment inadvertently influences patients’ desire to be ‘more physically active’

Evaluating physical activity is important for public health population research and evaluating lifestyle interventions among targeted groups. Self-reported questionnaires are frequently used to evaluate physical activity in a variety of contexts where resource or pragmatic limitations prohibit the use of more sophisticated approaches. However, prior research in the use of other patient reported outcomes in healthcare settings has highlighted that simply completing a questionnaire may change a patients’ behaviour or responses to subsequent questions. This methodology study aimed to examine whether completing a standard physical activity questionnaire altered patients responses to two related questions a) whether they are ‘sufficiently physically active’ and b) whether they desire ‘to be more physically active.’

Children with autistic spectrum disorder have an associated risk of depression

Over recent years there has been an increase in the literature examining youth with Autism Spectrum Disorders (ASD). The growth in this area of research has highlighted a significant gap in our understanding of suitable interventions for people with ASD and the treatment of co-occurring psychiatric disorders.1-3 Children with ASD are at increased risk of experiencing depressive symptoms and developing depression; however with very few proven interventions available for preventing and treating depression in children with ASD, there is a need for further research in this area.

A known-groups evaluation of the Response Bias Scale in a neuropsychological setting

We evaluated the Minnesota Multiphasic Personality Inventory-Second Edition (MMPI-2) Response Bias Scale (RBS). Archival data from 83 individuals who were referred for neuropsychological assessment with no formal diagnosis (n = 10), following a known or suspected traumatic brain injury (n = 36), with a psychiatric diagnosis (n = 20), or with a history of both trauma and a psychiatric condition (n = 17) were retrieved. The criteria for malingered neurocognitive dysfunction (MNCD) were applied, and two groups of participants were formed: poor effort (n = 15) and genuine responders (n = 68). Consistent with previous studies, the difference in scores between groups was greatest for the RBS (d = 2.44), followed by two established MMPI-2 validity scales, F (d = 0.25) and K (d = 0.23), and strong significant correlations were found between RBS and F (rs = .48) and RBS and K (r = −.41). When MNCD group membership was predicted using logistic regression, the RBS failed to add incrementally to F. In a separate regression to predict group membership, K added significantly to the RBS. Receiver-operating curve analysis revealed a nonsignificant area under the curve statistic, and at the ideal cutoff in this sample of >12, specificity was moderate (.79), sensitivity was low (.47), and positive and negative predictive power values at a 13% base rate were .25 and .91, respectively. Although the results of this study require replication because of a number of limitations, this study has made an important first attempt to report RBS classification accuracy statistics for predicting poor effort at a range of base rates.

The correlation between electric field emission phenomenon and Schottky contact reverse bias characteristics in nanostructured systems

Two different morphologies of nanotextured molybdenum oxide were deposited by thermal evaporation. By measuring their field emission (FE) properties, an enhancement factor was extracted. Subsequently, these films were coated with a thin layer of Pt to form Schottky contacts. The current-voltage (I-V) characteristics showed low magnitude reverse breakdown voltages, which we attributed to the localized electric field enhancement. An enhancement factor was obtained from the I-V curves. We will show that the enhancement factor extracted from the I-V curves is in good agreement with the enhancement factor extracted from the FE measurements.

A comparison of forward and reverse bias operation in a Pt/nanostructured ZnO Schottky diode based hydrogen sensor

A hydrogen gas sensor based on Pt/nanostructured ZnO Schottky diode has been developed. Our proposed theoretical model allows for the explanation of superior dynamic performance of the reverse biased diode when compared to the forward bias operation. The sensor was evaluated with low concentration H2 gas exposures over a temperature range of 280°C to 430°C. Upon exposure to H2 gas, the effective change in free carrier concentration at the Pt/structured ZnO interface is amplified by an enhancement factor, effectively lowering the reverse barrier, producing a large voltage shift. The lowering of the reverse barrier permits a faster response in reverse bias operation, than in forward bias operation.

Spectrum sensing optimisation for dynamic primary user signal

We propose a multi-layer spectrum sensing optimisation algorithm to maximise sensing efficiency by computing the optimal sensing and transmission durations for a fast changing, dynamic primary user. Dynamic primary user traffic is modelled as a random process, where the primary user changes states during both the sensing period and transmission period to reflect a more realistic scenario. Furthermore, we formulate joint constraints to correctly reflect interference to the primary user and lost opportunity of the secondary user during the transmission period. Finally, we implement a novel duty cycle based detector that is optimised with respect to PU traffic to accurately detect primary user activity during the sensing period. Simulation results show that unlike currently used detection models, the proposed algorithm can jointly optimise the sensing and transmission durations to simultaneously satisfy the optimisation constraints for the considered primary user traffic.