Where and when to revegetate : a quantitative method for scheduling landscape reconstruction

Restoration of native vegetation is required in many regions of the world, but determining priority locations for revegetation is a complex problem. We consider the problem of determining spatial and temporal priorities for revegetation to maximize habitat for 62 bird species within a heavily cleared agricultural region, 11 000 km2 in area. We show how a reserve-selection framework can be applied to a complex, large-scale restoration-planning problem to account for multi-species objectives and connectivity requirements at a spatial extent and resolution relevant to management. Our approach explicitly accounts for time lags in planting and development of habitat resources, which is intended to avoid future population bottlenecks caused by delayed provision of critical resources, such as tree hollows. We coupled species-specific models of expected habitat quality and fragmentation effects with the dynamics of habitat suitability following replanting to produce species-specific maps for future times. Spatial priorities for restoration were determined by ranking locations (150-m grid cells) by their expected contribution to species habitat through time using the conservation planning tool, ‘‘Zonation.’’ We evaluated solutions by calculating expected trajectories of habitat availability for each species. We produced a spatially explicit revegetation schedule for the region that resulted in a balanced increase in habitat for all species. Priority areas for revegetation generally were clustered around existing vegetation, although not always. Areas on richer soils and with high rainfall were more highly ranked, reflecting their potential to support high-quality habitats that have been disproportionately cleared for agriculture. Accounting for delayed development of habitat resources altered the rank-order of locations in the derived revegetation plan and led to improved expected outcomes for fragmentation-sensitive species. This work demonstrates the potential for systematic restoration planning at large scales that accounts for multiple objectives, which is urgently needed by land and natural resource managers.

Screens : television's dispersed 'broadcast'

This chapter focuses on the television-like industries and viewing practices that have emerged on other screens. Through a discussion of the internet and mobile
media, it explores the developing relationships between the existing television
industry, the constellation of new media industries that have integrated video,
and the new audiences generated by these technologies and practices.

Scheduling of a parallel computation-bound application and sequential applications executing concurrently on a cluster - a case study.

Studies have shown that most of the computers in a non-dedicated cluster are often idle or lightly loaded. The underutilized computers in a non-dedicated cluster can be employed to execute parallel applications. The aim of this study is to learn how concurrent execution of a computation-bound and sequential applications influence their execution performance and cluster utilization. The result of the study has demonstrated that a computation-bound parallel application benefits from load balancing, and at the same time sequential applications suffer only an insignificant slowdown of execution. Overall, the utilization of a non-dedicated cluster is improved.

Television journalism : the cultural politics of contemporary current affairs interviewing

This thesis examined television current affairs interviewing to determine the influence of the cultural politics of Australian commercial and non-commercial networks. Marketplace pressures to rate highly was the major influence on commercial programs resulting in the use of shorter dramatic interviews, more celebrities, fewer politicians, hidden cameras and ambush interviews.

Agent-based heuristics to solve NP-hard scheduling problems

A novel agent-driven heuristic approach was developed to control the operational scheduling for a local manufacturer. This approach outperformed the traditional kanban control mechanism under numerous simulated benchmarking tests. Using this approach, the individual machine loading was reduced by, on average, 28%, with the loading spread reduced by 85%

Adaptive hierarchical scheduling policy for enterprise grid computing systems

In an enterprise grid computing environments, users have access to multiple resources that may be distributed geographically. Thus, resource allocation and scheduling is a fundamental issue in achieving high performance on enterprise grid computing. Most of current job scheduling systems for enterprise grid computing provide batch queuing support and focused solely on the allocation of processors to jobs. However, since I/O is also a critical resource for many jobs, the allocation of processor and I/O resources must be coordinated to allow the system to operate most effectively. To this end, we present a hierarchical scheduling policy paying special attention to I/O and service-demands of parallel jobs in homogeneous and heterogeneous systems with background workload. The performance of the proposed scheduling policy is studied under various system and workload parameters through simulation. We also compare performance of the proposed policy with a static space–time sharing policy. The results show that the proposed policy performs substantially better than the static space–time sharing policy.

An efficient adaptive scheduling policy for high-performance computing

The advent of commodity-based high-performance clusters has raised parallel and distributed computing to a new level. However, in order to achieve the best possible performance improvements for large-scale computing problems as well as good resource utilization, efficient resource management and scheduling is required. This paper proposes a new two-level adaptive space-sharing scheduling policy for non-dedicated heterogeneous commodity-based high-performance clusters. Using trace-driven simulation, the performance of the proposed scheduling policy is compared with existing adaptive space-sharing policies. Results of the simulation show that the proposed policy performs substantially better than the existing policies.

Personal, social and environmental correlates of resilience to physical inactivity among women from socio-economically disadvantaged backgrounds

While sex and socio-economic disparities in physical activity have been well documented, not all disadvantaged women are inactive. This study aimed to examine correlates of achieving recommended levels of physical activity among women of low socio-economic position. In 2005, a population-based sample of 291 women with low educational attainment provided survey data on leisure time physical activity (LTPA). Participants reported potential personal (enjoyment and self-efficacy; barriers; intentions; guilt and priorities; routines and scheduling; occupational physical activity; television viewing), social (support from family/friends; social participation; sport/recreation club membership; dog ownership) and environmental (aesthetics; safety; local access; footpaths; interesting walks; busy roads to cross; heavy traffic) correlates of physical activity. Nearly 40% of participants achieved recommended LTPA (150 min week–1). Multivariable analyses revealed that higher levels of self-efficacy for walking [prevalence ratio (PR) 2.05, 95% confidence interval (CI) 1.19–3.53], higher enjoyment of walking (PR 1.48, 95% CI 1.04–2.12), greater intentions to be active (PR 1.97, 95% CI 1.12–3.45) and having set routines for physical activity (PR 1.91, 95% CI 1.18–3.09) were significantly associated with achieving recommended LTPA. Personal factors were the characteristics most strongly associated with achieving recommended levels of LTPA among women from socio-economically disadvantaged backgrounds.

Deleterious associations of sitting time and television viewing time with cardiometabolic risk biomarkers

We examined the associations of sitting time and television (TV) viewing time with continuously measured biomarkers of cardio-metabolic risk in Australian adults. Waist circumference, BMI, resting blood pressure, triglycerides, HDL cholesterol, fasting and 2-h postload plasma glucose, and fasting insulin were measured in 2,761 women and 2,103 men aged ≥30 years (mean age 54 years) without clinically diagnosed diabetes from the 2004-2005 Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Multivariate linear regression analyses examined associations of self-reported sitting time and TV viewing time (hours per day) with these biomarkers, adjusting for potential confounding variables. For both women and men, sitting time was detrimentally associated with waist circumference, BMI, systolic blood pressure, fasting triglycerides, HDL cholesterol, 2-h postload plasma glucose, and fasting insulin (all P < 0.05), but not with fasting plasma glucose and diastolic blood pressure (men only). With the exception of HDL cholesterol and systolic blood pressure in women, the associations remained significant after further adjustment for waist circumference. TV viewing time was detrimentally associated with all metabolic measures in women and all except HDL cholesterol and blood pressure in men. Only fasting insulin and glucose (men only) remained deleteriously associated with TV viewing time after adjustment for waist circumference. In women and men, sitting time and TV viewing time were deleteriously associated with cardio-metabolic risk biomarkers, with sitting time having more consistent associations in both sexes and being independent of central adiposity. Preventive initiatives aimed at reducing sitting time should focus on both nonleisure and leisure-time domains.

Identifying subgroups of U.S. adults at risk for prolonged television viewing to inform program development

Background
Although adverse health effects of prolonged TV viewing have been increasingly recognized, little population-wide information is available concerning subgroups at greatest risk for this behavior.

Purpose
This study sought to identify, in a U.S. population–derived sample, combinations of variables that defined subgroups with higher versus lower levels of usual TV-viewing time.

Methods
A total of 5556 adults from a national consumer panel participated in the mail survey in 2001 (55% women, 71% white, 13% black, and 11% Hispanic). Nonparametric risk classification analyses were conducted in 2008.

Results
Subgroups with the highest proportions of people watching >14 hours/week of TV were identified and described using a combination of demographic (i.e., lower household incomes, divorced/separated); health and mental health (i.e., poorer rated overall health, higher BMI, more depression); and behavioral (i.e., eating dinner in front of the TV, smoking, less physical activity) variables. The subgroup with the highest rates of TV viewing routinely ate dinner while watching TV and had lower income and poorer health. Prolonged TV viewing also was associated with perceived aspects of the neighborhood environment (i.e., heavy traffic and crime, lack of neighborhood lighting, and poor scenery).

Conclusions
The results can help inform intervention development in this increasingly important behavioral health area.