Comparison of handoff resource allocation strategies through the state-dependent rejection scheme

2001 ◽  
pp. 323-334 ◽  
Author(s):  
Francisco Barceló
Keyword(s):  
Resource Allocation ◽  
The State ◽  
State Dependent ◽  
Allocation Strategies

scholarly journals The State-Dependent Resource Allocation Hypothesis: Implications for the Foraging Ecology and Life History of Migratory Ungulates in the GYE

2015 ◽  
Vol 38 ◽  
pp. 54-57
Author(s):  
Matthew Kauffman ◽  
Kevin Monteith ◽  
Brett Jesmer
Keyword(s):  
Resource Allocation ◽  
Life History ◽  
Energy Expenditure ◽  
Energy Intake ◽  
Foraging Behavior ◽  
Mule Deer ◽  
High Energy ◽  
The State ◽  
Nutritional State ◽  
State Dependent

Understanding the behavioral and physiological responses of animals to environmental stressors is vital to our comprehension of their ecology and life history. The life-history strategy of ungulates is for females to prioritize survival over reproductive effort to maximize life-long fitness (Stearns 1992, Eberhardt 2002, Bårdsen et al. 2008). Consequently, an individual’s reproductive decisions are expected to be dependent on nutritional state (Bårdsen et al. 2008). Researchers have long assumed that individuals reduce their metabolism and energy expenditure to conserve nutritional reserves (i.e., fat and protein) during winter because winter has been demonstrated to be a period of energetic loss for temperate ungulates. Recent research, however, has shown that mule deer (Odocoileus hemionus) in a poor nutritional state are capable of increasing their nutritional reserves over winter (Monteith et al. 2013), and hormone analysis of moose (Alces alces; Jesmer et al. in review) indicates that animals with low nutritional reserves have high energy expenditure and energy intake. Therefore, regulation of nutritional state through plasticity in foraging behavior may allow animals to cope with resource shortages. We refer to this notion, wherein animals alter their energy intake and expenditure via foraging behavior as the State-Dependent Resource Allocation Hypothesis (Figure 1). In 2014 we proposed to apply state-of-the-art nutritional, isotopic, and hormone analyses to test the State-Dependent Resource Allocation Hypothesis (SRAH) in migratory mule deer within the Greater Yellowstone Ecosystem.

ANALYSIS OF MEASURES TO REDUCE ECOLOGICAL AND ECONOMIC DAMAGE FROM AUTOMOBILE TRANSPORT

2020 ◽  
Author(s):  
V.N. Kurdyukov ◽  
◽  
T.V. Lebedeva ◽  
Keyword(s):  
Resource Allocation ◽  
Negative Impact ◽  
The State ◽  
Point Of View ◽  
Motor Vehicles ◽  
Economic Damage ◽  
Agriculture Education

The article considers common classifications of measures to reduce environmentaleconomic damage from motor vehicles. Classification from the point of view of control impact is proposed, which allows to take into account relations between the state and citizens in the field of reduction of negative impact of motor vehicles on the environment. The analysis of the classification made it possible to identify areas of activity for improving the efficiency of management impacts, taking into account the incentives of citizens to comply with the requirements of the legislation and to create conditions for their exceeding. Increasing the efficiency of resource allocation in the Territory will allow the released funds to be allocated to the development of industry, agriculture, education and science.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

scholarly journals On Uncertainty Relations and Entanglement Detection with Mutually Unbiased Measurements

2015 ◽  
Vol 22 (01) ◽  
pp. 1550005 ◽  
Author(s):  
Alexey E. Rastegin
Keyword(s):  
The State ◽  
Uncertainty Relations ◽  
Trade Off ◽  
Entropic Uncertainty Relations ◽  
Finite Dimensional ◽  
State Dependent ◽  
Entanglement Detection

We formulate some properties of a set of several mutually unbiased measurements. These properties are used for deriving entropic uncertainty relations. Applications of mutually unbiased measurements in entanglement detection are also revisited. First, we estimate from above the sum of the indices of coincidence for several mutually unbiased measurements. Further, we derive entropic uncertainty relations in terms of the Rényi and Tsallis entropies. Both the state-dependent and state-independent formulations are obtained. Using the two sets of local mutually unbiased measurements, a method of entanglement detection in bipartite finite-dimensional systems may be realized. A certain trade-off between a sensitivity of the scheme and its experimental complexity is discussed.

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