A Century of American Economic Review : Insights on Critical Factors in Journal Publishing

By using information collected from numerous American Economic Review publications from the last 100 years, Torgler and Piatti examine the top publishing institutions to determine their most renowned AER papers based on citation success. Areas of interest include how often an individual can publish in the AER, how equally successful citations are distributed and who the top AER publishing authors are. The book explores what the level of cooperation is among authors and what drives systems such as the alphabetical name ordering. Torgler and Piatti critically examine the individual characteristics of AER authors, editors, editorial board members and referees and even tackle more intricate details such as the frequency of female publications in the AER. The authors observe and analyse the relationship between academic age and publication performance to see if there is any pattern on these factors and citation success. The book then goes on to analyse data concerning awards, and whether awards can increase the probability of publishing in the AER at a later stage

Synthesis of complementary RNA by RNA-dependent RNA polymerases in plant extracts is independent of an RNA primer

RNA-dependent RNA polymerase (RDR) activities were readily detected in extracts from cauliflower and broccoli florets, Arabidopsis thaliana (L.) Heynh callus tissue and broccoli nuclei. The synthesis of complementary RNA (cRNA) was independent of a RNA primer, whether or not the primer contained a 3′ terminal 2′-O-methyl group or was phosphorylated at the 5′ terminus. cRNA synthesis in plant extracts was not affected by loss-of-function mutations in the DICER-LIKE (DCL) proteins DCL2, DCL3, and DCL4, indicating that RDRs function independently of these DCL proteins. A loss-of-function mutation in RDR1, RDR2 or RDR6 did not significantly reduce the amount of cRNA synthesis. This indicates that these RDRs did not account for the bulk RDR activities in plant extracts, and suggest that either the individual RDRs each contribute a fraction of polymerase activity or another RDR(s) is predominant in the plant extract. © CSIRO 2008.

Child sexual abuse in China : a meta-analysis of 27 studies

Objective: To examine whether Chinese studies of child sexual abuse (CSA) in the general population show lower prevalence rates than other international studies, and whether certain features of these studies may help to account for variation in estimates. Methods: A meta-analysis and meta-regression were conducted on 27 studies found in the English and Chinese language peer reviewed journals that involved general populations of students or residents, estimated CSA prior to age 18, and specified rates for males or females individually. Results: Estimates for Chinese females were lower than the international composites. For total CSA for females, the Chinese pooled estimate was 15.3% (95% CI = 12.6–18.0) based on the meta-analysis of 24 studies, lower than the international estimate (Stoltenborgh, van IJzendoorn, Euser, & Bakermans-Kranenburg, 2011) but not significantly. For contact CSA for females, the pooled estimate was 9.5% (95% CI = 7.5–11.5), based on 16 studies, significantly lower than the international prevalence. For penetrative CSA for females, the pooled estimate was 1% (95% CI = 0.7–1.3), based on 15 studies, significantly lower than the international estimate of 15.1%. Chinese men reported significantly less penetrative CSA but significantly more total CSA than international estimates; while contact CSA reported by Chinese and international males appeared to be roughly equivalent. Chinese CSA prevalence estimates were lower in studies from urban areas and non-mainland areas (Hong Kong and Taiwan), and in surveys with larger and probability samples, multiple sites, face-to-face interview method and when using less widely used instruments. Conclusions: The findings to date justify further research into possible cultural and sociological reasons for lower risk of contact and penetrative sexual abuse of girls and less penetrative abuse of boys in China. Future research should examine sociological explanations, including patterns of supervision, sexual socialization and attitudes related to male sexual prowess. Practice implications: The findings suggest that future general population studies in China should use well validated instruments, avoid face-to-face interview formats and be careful to maintain methodological standards when sampling large populations over multiple sites.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

Establishing definitions and modeling public transport travel time variability

Public transport travel time variability (PTTV) is essential for understanding deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyses the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and researching the transit systems.

Predicting voltage unbalance impacts of plug-in electric vehicles penetration in residential low-voltage distribution networks

Plug-in electric vehicles will soon be connected to residential distribution networks in high quantities and will add to already overburdened residential feeders. However, as battery technology improves, plug-in electric vehicles will also be able to support networks as small distributed generation units by transferring the energy stored in their battery into the grid. Even though the increase in the plug-in electric vehicle connection is gradual, their connection points and charging/discharging levels are random. Therefore, such single-phase bidirectional power flows can have an adverse effect on the voltage unbalance of a three-phase distribution network. In this article, a voltage unbalance sensitivity analysis based on charging/discharging levels and the connection point of plug-in electric vehicles in a residential low-voltage distribution network is presented. Due to the many uncertainties in plug-in electric vehicle ratings and connection points and the network load, a Monte Carlo-based stochastic analysis is developed to predict voltage unbalance in the network in the presence of plug-in electric vehicles. A failure index is introduced to demonstrate the probability of non-standard voltage unbalance in the network due to plug-in electric vehicles.

Sampling designs on stream networks using the pseudo-Bayesian approach

Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable.

Discomfort glare in open plan green buildings

This study presents the largest-known, investigation on discomfort glare with 493 surveys collected from five green buildings in Brisbane, Australia. The study was conducted on full-time employees, working under their everyday lighting conditions, all of whom had no affiliation with the research institution. The survey consisted of a specially tailored questionnaire to assess potential factors relating to discomfort glare. Luminance maps extracted from high dynamic range (HDR) images were used to capture the luminous environment of the occupants. Occupants who experienced glare on their monitor and/or electric glare were excluded from analysis leaving 419 available surveys. Occupants were more sensitive to glare than any of the tested indices accounted for. A new index, the UGP was developed to take into account the scope of results in the investigation. The index is based on a linear transformation of the UGR to calculate a probability of disturbed persons. However all glare indices had some correlation to discomfort, and statistically there was no difference between the DGI, UGR and CGI. The UGP broadly reflects the demographics of the working population in Australia and the new index is applicable to open plan green buildings.

Rapid yet accurate speech indexing using dynamic match lattice spotting

The support for typically out-of-vocabulary query terms such as names, acronyms, and foreign words is an important requirement of many speech indexing applications. However, to date many unrestricted vocabulary indexing systems have struggled to provide a balance between good detection rate and fast query speeds. This paper presents a fast and accurate unrestricted vocabulary speech indexing technique named Dynamic Match Lattice Spotting (DMLS). The proposed method augments the conventional lattice spotting technique with dynamic sequence matching, together with a number of other novel algorithmic enhancements, to obtain a system that is capable of searching hours of speech in seconds while maintaining excellent detection performance

The power of percent

Which statistic would you use if you were writing the newspaper headline for the following media release: "Tassie’s death rate of deaths arising from transport-related injuries was 13 per 100,000 people, or 50% higher than the national average”? (Martain, 2007). The rate “13 per 100,000” sounds very small whereas “50% higher” sounds quite large. Most people are aware of the tendency to choose between reporting data as actual numbers or using percents in order to gain attention. Looking at examples like this one can help students develop a critical quantitative literacy viewpoint when dealing with “authentic contexts” (Australian Curriculum, Assessment and Reporting Authority [ACARA], 2013a, p. 37, 67). The importance of the distinction between reporting information in raw numbers or percents is not explicitly mentioned in the Australian Curriculum: Mathematics (ACARA, 2013b, p. 42). Although the document specifically mentions making “connections between equivalent fractions, decimals and percentages” [ACMNA131] in Year 6, there is no mention of the fundamental relationship between percent and the raw numbers represented in a part-whole fashion. Such understanding, however, is fundamental to the problem solving that is the focus of the curriculum in Years 6 to 9. The purpose of this article is to raise awareness of the opportunities to distinguish between the use of raw numbers and percents when comparisons are being made in contexts other than the media. It begins with the authors’ experiences in the classroom, which motivated a search in the literature, followed by a suggestion for a follow-up activity.

Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

A probabilistic framework to monitor a multi-mode outdoor robot

This paper presents an approach to autonomously monitor the behavior of a robot endowed with several navigation and locomotion modes, adapted to the terrain to traverse. The mode selection process is done in two steps: the best suited mode is firstly selected on the basis of initial information or a qualitative map built on-line by the robot. Then, the motions of the robot are monitored by various processes that update mode transition probabilities in a Markov system. The paper focuses on this latter selection process: the overall approach is depicted, and preliminary experimental results are presented

Enhanced locomotion control for a planetary rover

This article presents an approach to improve and monitor the behavior of a skid-steering rover on rough terrains. An adaptive locomotion control generates speeds references to avoid slipping situations. An enhanced odometry provides a better estimation of the distance travelled. A probabilistic classification procedure provides an evaluation of the locomotion efficiency on-line, with a detection of locomotion faults. Results obtained with a Marsokhod rover are presented throughout the paper

Analysis of traffic injury severity in Dhaka, Bangladesh

This research identifies roadway, traffic, and environmental factors that influence the injury severity of road traffic crashes in Dhaka. Dhaka provides a rather unusual driving risk environment to study, since virtually anyone can obtain a drivers’ license and very little traffic enforcement and fines are given when drivers violate traffic rules. To examine this city with presumed heightened crash severity risk, police reported crash data from 2007 to 2011 containing about 2714 road traffic crashes were collected. The injury severity of traffic crashes—recorded as either fatal, serious injury, or property damage only—were modeled using an ordered Probit model. Significant factors increasing the probability of fatal injuries include crashes along highways (65%), absence of a road divider (80%), crashes during night time (54%), and vehicle-pedestrian collisions (367%); whereas two-way traffic configuration (21%), and traffic police controlled schemes (41%) decrease the probability of fatalities. Both similarities and differences of the findings between crash risk in Dhaka and developed countries are discussed in policy relevant terms.

Cortisol shifts financial risk preferences

Risk taking is central to human activity. Consequently, it lies at the focal point of behavioral sciences such as neuroscience, economics, and finance. Many influential models from these sciences assume that financial risk preferences form a stable trait. Is this assumption justified and, if not, what causes the appetite for risk to fluctuate? We have previously found that traders experience a sustained increase in the stress hormone cortisol when the amount of uncertainty, in the form of market volatility, increases. Here we ask whether these elevated cortisol levels shift risk preferences. Using a double-blind, placebo-controlled, cross-over protocol we raised cortisol levels in volunteers over eight days to the same extent previously observed in traders. We then tested for the utility and probability weighting functions underlying their risk taking, and found that participants became more risk averse. We also observed that the weighting of probabilities became more distorted among men relative to women. These results suggest that risk preferences are highly dynamic. Specifically, the stress response calibrates risk taking to our circumstances, reducing it in times of prolonged uncertainty, such as a financial crisis. Physiology-induced shifts in risk preferences may thus be an under-appreciated cause of market instability.