Relationship between physical capacity and match performance in semiprofessional Australian rules football

This study investigated the relationship between physical performance and match performance in Australian Rules Football (ARF). Thirty-six semiprofessional ARF players participated in this study. Physical capacity was measured using a 3-km time trial. Match performance was measured throughout the 2013 season through 2 methods: direct game involvements (DGIs) per minute and a recording of coaches\u27 vote after the game. The main finding of the study was that 3-km time trial performance was a significant predictor of DGI per minute (p ≤ 0.05). In addition, the number of senior games played was also significant in predicting DGI per minute (p ≤ 0.05). Furthermore, the number of senior games significantly correlated with coaches\u27 votes (p ≤ 0.05). There were no significant relationships between 3-km time trial and coaches\u27 vote. The results highlight the importance of developing physical capacity in the preseason period; the players who were better performers in the 3-km time trial had a greater number of DGIs per minute. This information is important to consider in preseason planning to ensure sufficient time is dedicated to developing physical capacity in the training program, as it is directly associated with performance. In addition, this research also highlights the importance of playing experience in relation to team selection. Playing experience, as measured by the number of senior games played, had a significant relationship with both measures of match performance

Optimized shunting with mixed-usage tracks

We consider the planning of railway freight classification at hump yards, where the problem involves the formation of departing freight train blocks from arriving trains subject to scheduling and capacity constraints. The hump yard layout considered consists of arrival tracks of sufficient length at an arrival yard, a hump, classification tracks of non-uniform and possibly non-sufficient length at a classification yard, and departure tracks of sufficient length. To increase yard capacity, freight cars arriving early can be stored temporarily on specific mixed-usage tracks. The entire hump yard planning process is covered in this paper, and heuristics for arrival and departure track assignment, as well as hump scheduling, have been included to provide the neccessary input data. However, the central problem considered is the classification track allocation problem. This problem has previously been modeled using direct mixed integer programming models, but this approach did not yield lower bounds of sufficient quality to prove optimality. Later attempts focused on a column generation approach based on branch-and-price that could solve problem instances of industrial size. Building upon the column generation approach we introduce a direct arc-based integer programming model, where the arcs are precedence relations between blocks on the same classification track. Further, the most promising models are adapted for rolling-horizon planning. We evaluate the methods on historical data from the Hallsberg shunting yard in Sweden. The results show that the new arc-based model performs as well as the column generation approach. It returns an optimal schedule within the execution time limit for all instances but from one, and executes as fast as the column generation approach. Further, the short execution times of the column generation approach and the arc-indexed model make them suitable for rolling-horizon planning, while the direct mixed integer program proved to be too slow for this. Extended analysis of the results shows that mixing was only required if the maximum number of concurrent trains on the classification yard exceeds 29 (there are 32 available tracks), and that after this point the number of extra car roll-ins increases heavily

Case Study of Resilient Baton Rouge: Applying Depression Collaborative Care and Community Planning to Disaster Recovery.

BackgroundAddressing behavioral health impacts of major disasters is a priority of increasing national attention, but there are limited examples of implementation strategies to guide new disaster responses. We provide a case study of an effort being applied in response to the 2016 Great Flood in Baton Rouge.MethodsResilient Baton Rouge was designed to support recovery after major flooding by building local capacity to implement an expanded model of depression collaborative care for adults, coupled with identifying and responding to local priorities and assets for recovery. For a descriptive, initial evaluation, we coupled analysis of documents and process notes with descriptive surveys of participants in initial training and orientation, including preliminary comparisons among licensed and non-licensed participants to identify training priorities.ResultsWe expanded local behavioral health service delivery capacity through subgrants to four agencies, provision of training tailored to licensed and non-licensed providers and development of advisory councils and partnerships with grassroots and government agencies. We also undertook initial efforts to enhance national collaboration around post-disaster resilience.ConclusionOur partnered processes and lessons learned may be applicable to other communities that aim to promote resilience, as well as planning for and responding to post-disaster behavioral health needs

Three Essays on Intensive Care Unit Capacity Planning

The Intensive Care Unit (ICU) is a resource-intensive, costly environment. Data gathered from patients during their stay in the ICU has traditionally been used for clinical purposes, but can have a significant impact on healthcare capacity planning and patient flow. There is a need to study how metrics collected in Canadian ICUs, such as the Multiple Organ Dysfunction Syndrome (MODS) score and the Nine Equivalents of Nursing Manpower Use Score (NEMS) can be used to improve capacity planning decisions. Using discrete-event simulation, statistical, survival and machine learning models, I have built long- and short-term capacity planning models to help hospital administrators better manage patient flows in the ICU. This dissertation consists of three essays that explore the use of these metrics in ICU capacity planning. In the first essay, I study the incorporation of the nursing manpower score NEMS into a discrete-event simulation model to estimate optimal long-term capacity levels of critical care beds in both Level 3 (ICU) and Level 2 (step-down) units. Using data from London Health Sciences Centre (LHSC) University Hospital, I demonstrate the benefits of simulating patients’ daily NEMS changes as triggers for transfer to a step-down unit. This essay also examines ways in which transfer to a step-down unit may improve patient length of stay (LOS), flow and costs. In the second essay, I demonstrate that the ICU LOS literature shows the predominance of multiple linear regression models for individual patients’ ICU LOS and outcome predictions (e.g., death, discharge, long stay). Using data from LHSC’s two ICUs, I compare the performances of well known statistical models with contemporary supervised machine learning models in predicting such outcomes. I show that there is no dominant model in terms of individual patients’ LOS predictions, but that outcome prediction (death, discharge, long stay) performance can be improved by using supervised machine learning techniques. In the third essay, I build on the use of NEMS to simulate realistic ICU LOS for long term capacity planning, and on the use of NEMS and MODS to predict individual ICU LOS in order to improve short-term capacity planning. First, I fit a parametric survival model called the Accelerated Failure Time (Weibull AFT) model with LHSC’s UH data. Then I analyze the model’s hazard rates, event time ratios and LOS, both at the time of the patient’s arrival in the ii ICU and after 3 days’ stay. Finally, I generate daily patient survival probabilities and pool them to predict future expected ICU occupancy rates. Using survival probability pooling for short term capacity planning is a novel use of the ATF model, and may be used to accurately predict ICU occupancy

Scenario-guided policy planning in Uganda

Using socio-economic scenarios in policy formulation allows for an anticipatory approach to governance processes and the formulation of policies/plans that take into account future uncertainty To fully benefit from the dividends of scenario planning in the Ugandan context, there is need to build the scenario-guided planning capacity of both public and private sectors. There is need for follow up and continuous engagement with government officials responsible after the review process to enable inclusion of recommendations generated into the final policy documents. In some cases, the abstract nature of national policy statements limits the level of detail, hence detailed scenario guided recommendations and information may not easily fit in the existing policy formats. The approach is new and requires extra awareness creation not only for the government officers who draft policies but also for other major policy actors such as the political leadership who approve the policies

Public health in India : an overview

Public health services, which reduce a population's exposure to disease through such measures as sanitation and vector control, are an essential part of a country's development infrastructure. In the industrial world and East Asia, systematic public health efforts raised labor productivity and life expectancies well before modern curative technologies became widely available, and helped set the stage for rapid economic growth and poverty reduction. The enormous business and other costs of the breakdown of these services are illustrated by the current global epidemic of avian flu, emanating from poor poultry-keeping practices in a few Chinese villages. For various reasons, mostly of political economy, public funds for health services in India have been focused largely on medical services, and public health services have been neglected. This is reflected in a virtual absence of modern public health regulations and of systematic planning and delivery of public health services. Various organizational issues also militate against the rational deployment of personnel and funds for disease control. There is strong capacity for dealing with outbreaks when they occur, but not to prevent them from occurring. Impressive capacity also exists for conducting intensive campaigns, but not for sustaining these gains on a continuing basis after the campaign. This is illustrated by the near eradication of malaria through highly organized efforts in the 1950s, and its resurgence when attention shifted to other priorities such as family planning. This paper reviews the fundamental obstacles to effective disease control in India and indicates new policy thrusts that can help overcome these obstacles.Health Monitoring&Evaluation,Health Economics&Finance,Brown Issues and Health,Public Sector Management and Reform,Rural Development Knowledge&Information Systems

Uncovering the Progress of Planning for Vulnerability to Sea-Level Rise & Coastal Storms: A Plan Evaluation of Norfolk, VA & New York City

In response to recent storms like Superstorm Sandy and sea-level rise influenced by climate change, cities, particularly those located at the coast, have taken initiative to combat these growing threats with adaptive urban planning. Although civilians residing in susceptible neighborhoods are often the most vulnerable socioeconomically, there has been minimal evidence that planning has accounted for the characteristics of vulnerability. This thesis evaluates the recent planning efforts and vulnerability of Norfolk, VA and New York City to gauge the progress being made toward reducing citizen vulnerability and raising adaptability and preparedness. The most recent peer-reviewed research is consulted to forge the evaluation framework and also to recognize breakthroughs and conformity. After analyzing the performance of the sets of planning documents in both cities, it is evident that the ability to effectively plan for the public’s vulnerability is contingent in part on inter-governmental capacity, but more specifically on disaster experience

Evaluation of Coordinated Ramp Metering (CRM) Implemented By Caltrans

Coordinated ramp metering (CRM) is a critical component of smart freeway corridors that rely on real-time traffic data from ramps and freeway mainline to improve decision-making by the motorists and Traffic Management Center (TMC) personnel. CRM uses an algorithm that considers real-time traffic volumes on freeway mainline and ramps and then adjusts the metering rates on the ramps accordingly for optimal flow along the entire corridor. Improving capacity through smart corridors is less costly and easier to deploy than freeway widening due to high costs associated with right-of-way acquisition and construction. Nevertheless, conversion to smart corridors still represents a sizable investment for public agencies. However, in the U.S. there have been limited evaluations of smart corridors in general, and CRM in particular, based on real operational data. This project examined the recent Smart Corridor implementation on Interstate 80 (I-80) in the Bay Area and State Route 99 (SR-99, SR99) in Sacramento based on travel time reliability measures, efficiency measures, and before-and-after safety evaluation using the Empirical Bayes (EB) approach. As such, this evaluation represents the most complete before-and-after evaluation of such systems. The reliability measures include buffer index, planning time, and measures from the literature that account for both the skew and width of the travel time distribution. For efficiency, the study estimates the ratio of vehicle miles traveled vs. vehicle hour traveled. The research contextualizes before-and-after comparisons for efficiency and reliability measures through similar measures from another corridor (i.e., the control corridor of I-280 in District 4 and I-5 in District 3) from the same region, which did not have CRM implemented. The results show there has been an improvement in freeway operation based on efficiency data. Post-CRM implementation, travel time reliability measures do not show a similar improvement. The report also provides a counterfactual estimate of expected crashes in the post-implementation period, which can be compared with the actual number of crashes in the “after” period to evaluate effectiveness

EVALUATION OF EXISTING CLIMATE-CHANGE ADAPTATION PLANS FOR MUNICIPALITIES IN MEXICO: PROPOSITION OF A “SUSTAINABLE MAC-WATER FRAMEWORK” THAT CONSIDERS VULNERABILITY TO IMPACTS ON WATER RESOURCES

This paper presents a sustainable adaptive capacity framework for water management for municipalities, named Sustainable MAC-Water framework, after assessing the strengths and weaknesses of adaptive capacity in Mexico and its municipalities. It provides municipalities with an instrument to help them create sustainable adaptive capacity plans (Sustainable MAC plans) to prevent adverse impacts on water resources and related sectors. It is based on a study of policy instruments crafted by the Intergovernmental Panel on Climate Change (IPCC) and the Government of Mexico, and literature on adaptive capacity, assessment, and planning. The Sustainable MAC-Water framework recommends the establishment of a Reactive Barriers Removal Plan (RBRP), support measures in reaction to the negative impacts of adaptive measure, and an Integrative Social-Stakeholder Engagement Strategy (iSSE) along with adaptation plans. It also requires transparent leadership and the incorporation of health dimensions. There five components are additional requisites to build strong and resilient adaptive capacity and forms Sustainable Adaptive Indicators