765 research outputs found
Physician Incentive Management in University Hospitals: Inducing Efficient Behavior Through the Allocation of Research Facilities
The imperative to improve healthcare efficiency is now stronger than ever. Rapidly increasing healthcare demand and the prospect of healthcare cost exploding require that measures be taken to make healthcare organizations become more efficiency-aware. Alignment of organizational interests is therefore important. One of the main hurdles to overcome is the provision of the right incentives to healthcare workers, in particular physicians.
In this research we investigate the incentive system for physicians in university hospitals. We present an inquiry held in a large university hospital in the Netherlands and show that non-financial incentives receive significantly more support among physicians than financial incentives. Over 95 percent of the physicians indicated they derive more work stimulus from research possibilities or scientific status than from wage. Over 80 percent of the physicians also indicated they prefer to be able to do more research. We therefore identified a broad class of non-financial incentives aimed at physicians in university hospitals: research facilities.
The main tradeoff in using research facilities within an incentive system is between efficient resource utilization and inducement effects. This thesis constructs a principal-multi-agent model where agents engage in both care and research and which includes heterogeneity and private information. We study how research facilities incentives can be used to improve hospital performance if the current wage system is left intact. We show that research facilities are optimally used as incentives for both care and research activities, and that the hospital offers different contracts depending on physician ability and valuation. Moreover, if physicians need to reveal their valuations for research facilities, the hospital finds it optimal to allow physicians to make a rent. We discuss some implications of extending the theoretical results to practice
Entanglement, Mixedness, and Spin-Flip Symmetry in Multiple-Qubit Systems
A relationship between a recently introduced multipartite entanglement
measure, state mixedness, and spin-flip symmetry is established for any finite
number of qubits. It is also shown that, within those classes of states
invariant under the spin-flip transformation, there is a complementarity
relation between multipartite entanglement and mixedness. A number of example
classes of multiple-qubit systems are studied in light of this relationship.Comment: To appear in Physical Review A; submitted 14 May 200
Hamiltonian BRST-anti-BRST Theory
The hamiltonian BRST-anti-BRST theory is developed in the general case of
arbitrary reducible first class systems. This is done by extending the methods
of homological perturbation theory, originally based on the use of a single
resolution, to the case of a biresolution. The BRST and the anti-BRST
generators are shown to exist. The respective links with the ordinary BRST
formulation and with the -covariant formalism are also established.Comment: 34 pages, Latex fil
Entanglement study of the 1D Ising model with Added Dzyaloshinsky-Moriya interaction
We have studied occurrence of quantum phase transition in the one-dimensional
spin-1/2 Ising model with added Dzyaloshinsky-Moriya (DM) interaction from bi-
partite and multi-partite entanglement point of view. Using exact numerical
solutions, we are able to study such systems up to 24 qubits. The minimum of
the entanglement ratio R \tau 2/\tau 1 < 1, as a novel estimator of
QPT, has been used to detect QPT and our calculations have shown that its
minimum took place at the critical point. We have also shown both the
global-entanglement (GE) and multipartite entanglement (ME) are maximal at the
critical point for the Ising chain with added DM interaction. Using matrix
product state approach, we have calculated the tangle and concurrence of the
model and it is able to capture and confirm our numerical experiment result.
Lack of inversion symmetry in the presence of DM interaction stimulated us to
study entanglement of three qubits in symmetric and antisymmetric way which
brings some surprising results.Comment: 18 pages, 9 figures, submitte
Entanglement Sharing in the Two-Atom Tavis-Cummings Model
Individual members of an ensemble of identical systems coupled to a common
probe can become entangled with one another, even when they do not interact
directly. We investigate how this type of multipartite entanglement is
generated in the context of a system consisting of two two-level atoms
resonantly coupled to a single mode of the electromagnetic field. The dynamical
evolution is studied in terms of the entanglements in the different bipartite
partitions of the system, as quantified by the I-tangle. We also propose a
generalization of the so-called residual tangle that quantifies the inherent
three-body correlations in our tripartite system. This enables us to completely
characterize the phenomenon of entanglement sharing in the case of the two-atom
Tavis-Cummings model, a system of both theoretical and experimental interest.Comment: 11 pages, 4 figures, submitted to PRA, v3 contains corrections to
small error
Impact of extreme weather events frequency and intensity in shaping phytoplankton communities
Lake habitats and communities can often be correlated with general morphometric and geographic
characteristics such as depth, latitude, altitude, or watershed area. Further, communities are typically
correlated with average environmental conditions such as seasonal temperature and nutrient levels. The
frequency and intensity of extreme weather events (rain and wind) are typically not encompassed by average
environmental descriptors, yet, can modify the physical habitats of lakes, significantly influencing
phytoplankton growth and survival. We tested the hypothesis that lakes with a higher frequency and intensity
of extreme weather events have a functionally different phytoplankton assemblage from lakes with a lower
frequency of extreme weather events. We compiled long-term (mean = 20±13 years, range 0.6-44 years)
phytoplankton datasets for 22 lakes across a wide gradient of altitude, latitude, depth, and trophic state. We
classified the phytoplankton genera into morpho-functional groups and C-S-R strategists, and compared
among lake phytoplankton assemblages’ characteristics across the gradient of wind and rain conditions
experienced by the lakes. We discuss how the frequency of extreme weather events can affect phytoplankton
functional groups, the dominance of differing life history strategies and ultimately community structure. The
frequency and intensity of extreme events is expected to increase with climate change, with the potential to
drive shifts in phytoplankton composition
Separability and entanglement in 2x3xN composite quantum systems
The separability and entanglement of quantum mixed states in \Cb^2 \otimes
\Cb^3 \otimes \Cb^N composite quantum systems are investigated. It is shown
that all quantum states with positive partial transposes and rank
are separable.Comment: Latex, 15 page
A global dataset on weather, lake physics, and phytoplankton dynamics
We compiled data from over 30 lakes across the globe to address how storms influence thermal structure
and phytoplankton community dynamics mediated by lake conditions and functional traits. In addition to
(generally) fortnightly phytoplankton samples (mean ± SD temporal coverage across all lakes = 20 ± 13 years),
the dataset includes limnological variables from standard long-term monitoring programs (24 ± 15 years
coverage), daily weather observations (16 ± 10 years coverage) and, when available, high-frequency lake
water temperature and water chemistry profiles (12 ± 7 years coverage). All data have been standardized to
similar formats and include complete metadata. We used the dataset to develop an R-package
(“algaeClassify”), which assigns phytoplankton genus/species information to multiple functional trait groups,
and here we provide a summary of ongoing research using the dataset to investigate: 1) the influence of storm
events on seasonal phytoplankton succession, 2) the impact of storms on lake thermal structure, and 3)
whether lake phytoplankton communities are shaped by long-term patterns in disturbance frequency and
intensity. We give an overview on how to access these data, and we further highlight the opportunities the
dataset provides for asking both basic and applied questions in limnology, ecology, climate change, and lake
management
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