Probability distributions of number of children and maternal age at various order births using age-specific fertility rates by birth order

In this study, a simple analytical framework to find the probability distributions of number of children and maternal age at various order births by making use of data on age-specific fertility rates by birth order was proposed. The proposed framework is applicable to both the period and cohort fertility schedules. The most appealing point of the proposed framework is that it does not require stringent assumptions. The proposed framework has been applied to the cohort birth order-specific fertility schedules of India and its different regions and period birth order-specific fertility schedules, including the United States of America, Russia, and the Netherlands, to demonstrate its usefulness.

Spatial and temporal drivers of small mammal distributions in a semi-arid environment : the role of rainfall, vegetation and life-history

A key task in ecology is to understand the drivers of animal distributions. In arid and semi-arid environments, this is challenging because animal populations show considerable spatial and temporal variation. An effective approach in such systems is to examine both broad-scale and long-term data. We used this approach to investigate the distribution of small mammal species in semi-arid ‘mallee’ vegetation in south-eastern Australia. First, we examined broad-scale data collected at 280 sites across the Murray Mallee region. We used generalized additive mixed models (GAMMs) to examine four hypotheses concerning factors that influence the distribution of individual mammal species at this scale: vegetation structure, floristic diversity, topography and recent rainfall. Second, we used long-term data from a single conservation reserve (surveyed from 1997 to 2012) to examine small mammal responses to rainfall over a period spanning a broad range of climatic conditions, including record high rainfall in 2011. Small mammal distributions were strongly associated with vegetation structure and rainfall patterns, but the relative importance of these drivers was species-specific. The distribution of the mallee ningaui Ningaui yvonneae, for example, was largely determined by the cover of hummock grass; whereas the occurrence of the western pygmy possum Cercartetus concinnus was most strongly associated with above-average rainfall. Further, the combination of both broad-scale and long-term data provided valuable insights. Bolam's mouse Pseudomys bolami was uncommon during the broad-scale survey, but long-term surveys showed that it responds positively to above-average rainfall. Conceptual models developed for small mammals in temperate and central arid Australia, respectively, were not, on their own, adequate to account for the distributional patterns of species in this semi-arid ecosystem. Species-specific variation in the relative importance of different drivers was more effectively explained by qualitative differences in life-history attributes among species.

Large-scale sampling reveals the spatio-temporal distributions of the jellyfish Aurelia aurita and Cyanea capillata in the Irish Sea

At-sea distributions of large scyphozoan jellyfish across the Irish Sea were studied using visual surface counts from ships of opportunity. Thirty-seven surveys were conducted along two >100 km long transects between Ireland and the UK from April to September in 2009 and 2010. Five species were recorded but only Aurelia aurita and Cyanea capillata were frequently observed. The first formal description of the seasonal changes in the abundances and distributions of these two species in the study area is provided. The highest densities of these species were more likely to be found ~30 km offshore, but large aggregations were present both in coastal and offshore waters. Evidence for aggregations of medusae along physical discontinuities was provided by coupling jellyfish observations with simultaneous records of environmental parameters. The value of surveys from ships of opportunity as cost-effective semi-quantitative tools, to develop local knowledge on jellyfish abundance, distribution, and phenology is discussed.

Effect of weighted vest suit worn during daily activities on running speed, jumping power, and agility in young men

Effect of weighted vest suit worn during daily activities on running speed, jumping power, and agility in young men. J Strength Cond Res 26(11): 3030-3035, 2012-Previous weighted vest interventions using exercise in addition to hypergravity have been successful in improving postural balance and power production capacity. The purpose of this study was to investigate if hypergravity alone in daily activities excluding sporting activities is effective in improving neuromuscular performance in young adults. Eight male subjects (age = 32 [SD: 6] years, height = 178 [5] cm, and body mass = 81 [8] kg) wore weighted vests 3 d.wk-1 for 3 weeks during waking hours, excluding sporting activities. Control group comprised 9 male subjects (age = 32 [6] years, height = 179 [5] cm, and body mass = 83 [9] kg). Performance was assessed with countermovement jump (body mass normalized peak power), figure-of-8 running test (running time), and running velocity test at baseline and at the end of the intervention. At baseline, the groups did not differ from each other (multivariate analysis of variance [MANOVA] p = 0.828). A significant group × time interaction (MANOVA F = 5.1, p = 0.015) was observed for performance variables. Analysis of covariance indicated that the intervention improved the figureof- 8 running time (p = 0.016) (22.2 vs. 0.5%), whereas normalized peak power (0.0 vs. 1.6%) and running velocity (1.3 vs. 0.1%) were unaffected (p ≥ 0.095). Wearing weighted vests was effective in slightly improving agility-related performance in young men. Because the effect was small, applying hypergravity only during exercise probably suffices. It appears that a proper volume and intensity of hypergravity could be in the order of 5-10% body weight vest worn during up to 50% of the training sessions for a period of 3-4 weeks.

Sociospatial distribution of access to facilities for moderate and vigorous intensity physical activity in Scotland by different modes of transport

Background People living in neighbourhoods of lower socioeconomic status have been shown to have higher rates of obesity and a lower likelihood of meeting physical activity recommendations than their more affluent counterparts. This study examines the sociospatial distribution of access to facilities for moderate or vigorous intensity physical activity in Scotland and whether such access differs by the mode of transport available and by Urban Rural Classification. Methods A database of all fixed physical activity facilities was obtained from the national agency for sport in Scotland. Facilities were categorised into light, moderate and vigorous intensity activity groupings before being mapped. Transport networks were created to assess the number of each type of facility accessible from the population weighted centroid of each small area in Scotland on foot, by bicycle, by car and by bus. Multilevel modelling was used to investigate the distribution of the number of accessible facilities by small area deprivation within urban, small town and rural areas separately, adjusting for population size and local authority. Results Prior to adjustment for Urban Rural Classification and local authority, the median number of accessible facilities for moderate or vigorous intensity activity increased with increasing deprivation from the most affluent or second most affluent quintile to the most deprived for all modes of transport. However, after adjustment, the modelling results suggest that those in more affluent areas have significantly higher access to moderate and vigorous intensity facilities by car than those living in more deprived areas. Conclusions The sociospatial distributions of access to facilities for both moderate intensity and vigorous intensity physical activity were similar. However, the results suggest that those living in the most affluent neighbourhoods have poorer access to facilities of either type that can be reached on foot, by bicycle or by bus than those living in less affluent areas. This poorer access from the most affluent areas appears to be reversed for those with access to a car.

Univariate and multivariate process yield indices based on location-scale family of distributions

Several measures of process yield, defined on univariate and multivariate normal process characteristics, have been introduced and studied by several authors. These measures supplement several well-known Process Capacity Indices (PCI) used widely in assessing the quality of products before being released into the marketplace. In this paper, we generalise these yield indices to the location-scale family of distributions which includes the normal distribution as one of its member. One of the key contributions of this paper is to demonstrate that under appropriate conditions, these indices converge in distribution to a normal distribution. Several numerical examples will be used to illustrate our procedures and show how they can be applied to perform statistical inferences on process capability.

Development of an exposure database and surveillance system for use by practicing OSH professionals

This report summarizes the development of an occupational exposure database and surveillance system for use by health and safety professionals at Rocky Flats Environmental Technology Site (RFETS), a former nuclear weapons production facility. The site itself is currently in the cleanup stage with work expected to continue into 2006. The system was developed with the intent of helping health and safety personnel not only to manage and analyze exposure monitoring data, but also to identify exposure determinants during the highly variable cleanup work. Utilizing a series of focused meetings with health and safety personnel from two of the major contractors at RFETS, core data elements were established. These data elements were selected based on their utility for analysis and identification of exposure determinants. A task-based coding scheme was employed to better define the highly variable work. The coding scheme consisted of a two-tiered hierarchical list with a total of 34 possible combinations of work type and task. The data elements were incorporated into a Microsoft Access database with built-in data entry features to both promote consistency and limit entry choices to enable stratified analyses. In designing the system, emphasis was placed on the ability of end users to perform complex analyses and multiparameter queries to identify trends in their exposure data. A very flexible and user-friendly report generator was built into the system. This report generator allowed users to perform multiparameter queries using an intuitive system with very little training. In addition, a number of automated graphical analyses were built into the system, including ex posure levels by any combination of building, date, employee, job classification, type of contaminant, work type or task, exposure levels over time, exposure levels relative to the permissible exposure limit (PELS), and distributions of exposure levels. Both of these interfaces, allow the user to ''drill down'' or gradually narrow query criteria to identify specific exposure determinants. A number of other industrial hygiene processes were automated by the use of this database. Exposure calculations were coded into the system to allow automatic calculation of time-weighted averages and sample volumes. In addition, a table containing all the PELs and other relevant occupational exposure limits was built into the system to allow automatic comparisons with the current standards. Finally, the process of generating reports for employee notification was automated. The implementation of this system demonstrates that an integrated database system can save time for a practicing hygienist as well as provide useful and more importantly, timely information to guide primary prevention efforts.

On some properties of weighted averaging with variable weights

Density-based means have been recently proposed as a method for dealing with outliers in the stream processing of data. Derived from a weighted arithmetic mean with variable weights that depend on the location of all data samples, these functions are not monotonic and hence cannot be classified as aggregation functions. In this article we establish the weak monotonicity of this class of averaging functions and use this to establish robust generalisations of these means. Specifically, we find that as proposed, the density based means are only robust to isolated outliers. However, by using penalty based formalisms of averaging functions and applying more sophisticated and robust density estimators, we are able to define a broader family of density based means that are more effective at filtering both isolated and clustered outliers. © 2014 Elsevier Inc. All rights reserved.

Predicting avian distributions to evaluate spatiotemporal overlap with locust control operations in eastern Australia.

Locusts and grasshoppers cause considerable economic damage to agriculture worldwide. The Australian Plague Locust Commission uses multiple pesticides to control locusts in eastern Australia. Avian exposure to agricultural pesticides is of conservation concern, especially in the case of rare and threatened species. The aim of this study was to evaluate the probability of pesticide exposure of native avian species during operational locust control based on knowledge of species occurrence in areas and times of application. Using presence-absence data provided by the Birds Australia Atlas for 1998 to 2002, we developed a series of generalized linear models to predict avian occurrences on a monthly basis in 0.5 degrees grid cells for 280 species over 2 million km2 in eastern Australia. We constructed species-specific models relating occupancy patterns to survey date and location, rainfall, and derived habitat preference. Model complexity depended on the number of observations available. Model output was the probability of occurrence for each species at times and locations of past locust control operations within the 5-year study period. Given the high spatiotemporal variability of locust control events, the variability in predicted bird species presence was high, with 108 of the total 280 species being included at least once in the top 20 predicted species for individual space-time events. The models were evaluated using field surveys collected between 2000 and 2005, at sites with and without locust outbreaks. Model strength varied among species. Some species were under- or over-predicted as times and locations of interest typically did not correspond to those in the prediction data set and certain species were likely attracted to locusts as a food source. Field surveys demonstrated the utility of the spatially explicit species lists derived from the models but also identified the presence of a number of previously unanticipated species. These results also emphasize the need for special consideration of rare and threatened species that are poorly predicted by presence-absence models. This modeling exercise was a useful a priori approach in species risk assessments to identify species present at times and locations of locust control applications, and to discover gaps in our knowledge and need for further focused data collection.

Non-homogeneous volatility correlations in the bivariate multifractal model

In this paper, we consider an extension of the recently proposed bivariate Markov-switching multifractal model of Calvet, Fisher, and Thompson [2006. "Volatility Comovement: A Multifrequency Approach." Journal of Econometrics {131}: 179-215]. In particular, we allow correlations between volatility components to be non-homogeneous with two different parameters governing the volatility correlations at high and low frequencies. Specification tests confirm the added explanatory value of this specification. In order to explore its practical performance, we apply the model for computing value-at-risk statistics for different classes of financial assets and compare the results with the baseline, homogeneous bivariate multifractal model and the bivariate DCC-GARCH of Engle [2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models." Journal of Business & Economic Statistics 20 (3): 339-350]. As it turns out, the multifractal model with heterogeneous volatility correlations provides more reliable results than both the homogeneous benchmark and the DCC-GARCH model. © 2014 Taylor & Francis.