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Supervisory Efficiency and Collusion in a Multiple-Agent Hierarchy
We analyze a principal-supervisor-two-agent hierarchy with inefficient supervision. The su-pervisor may collects a wrong signal on each agent’s unobservable effort level. When reportingto the principal, the supervisor can collude with one or both agents to manipulate the signalin exchange for a bribe. In contract design, we identify a new trade-off between the loss fromsupervisor-agent collusion and the risk from inefficient supervision: Although allowing collu-sion makes shirking more attractive to the agents, it brings in a benefit because it can “correct”an incorrect negative signal when the agent has exerted effort. Such collusive supervision savesrisk premiums that the principal has to pay for incentive provision. We characterize the princi-pal’s optimal contract choice among no-supervision, collusion-proof, and collusive-supervisioncontracts. We show that the collusive-supervision contract dominates when the supervisory ef-ficiency is at an intermediate level
Noncommutative spaces and matrix embeddings on flat R^{2n+1}
We conjecture an embedding operator which assigns, to any 2n+1 hermitian
matrices, a 2n-dimensional hypersurface in flat (2n + 1)-dimensional Euclidean
space. This corresponds to precisely defining a fuzzy D(2n)-brane corresponding
to N D0-branes. Points on the emergent hypersurface correspond to zero
eigenstates of the embedding operator, which have an interpretation as coherent
states underlying the emergent noncommutative geometry. Using this
correspondence, all physical properties of the emergent D(2n)-brane can be
computed. We apply our conjecture to noncommutative flat and spherical spaces.
As a by-product, we obtain a construction of a rotationally symmetric flat
noncommutative space in 4 dimensions.Comment: 14 pages, no figures. v2: added references and a clarificatio
Bi-Directional Energy Cascades and the Origin of Kinetic Alfv\'enic and Whistler Turbulence in the Solar Wind
The observed sub-proton scale turbulence spectrum in the solar wind raises
the question of how that turbulence originates. Observations of keV energetic
electrons during solar quite-time suggest them as possible source of free
energy to drive the turbulence. Using particle-in-cell simulations, we explore
how free energy in energetic electrons, released by an electron two-stream
instability drives Weibel-like electromagnetic waves that excite wave-wave
interactions. Consequently, both kinetic Alfv\'enic and whistler waves are
excited that evolve through inverse and forward magnetic energy cascades.Comment: 12 pages, 5 figures, Submitted to Physical Review Letter
Nucleon and Delta resonances in K Sigma(1385) photoproduction from nucleons
The reaction mechanisms for photoproduction from the reaction
in the resonance energy region are
investigated in a hadronic model. Both contributions from and
resonances of masses around 2 GeV as given in the Review of Particle Data Group
and by the quark model predictions are included. The Lagrangians for describing
the decays of these resonances into are constructed with the
coupling constants determined from the decay amplitudes predicted by a quark
model. Comparing the resulting total cross section for the reaction with the preliminary data from the Thomas Jefferson
National Accelerator Facility, we find that the most important contributions
are from the two-star rated resonances , , and , as well as the missing resonance
predicted in the quark model. Predictions on the
differential cross section and photon asymmetry in this reaction are also
given.Comment: 13 pages, 6 figures, REVTeX, to appear in Phys. Rev.
Effects of initial state fluctuations on jet energy loss
The effect of initial state fluctuations on jet energy loss in relativistic
heavy-ion collisions is studied in a 2+1 dimension ideal hydrodynamic model.
Within the next-to-leading order perturbative QCD description of hard
scatterings, we find that a jet loses slightly more energy in the expanding
quark-gluon plasma if the latter is described by the hydrodynamic evolution
with fluctuating initial conditions compared to the case with smooth initial
conditions. A detailed analysis indicates that this is mainly due to the
positive correlation between the fluctuation in the production probability of
parton jets from initial nucleon-nucleon hard collisions and the fluctuation in
the medium density along the path traversed by the jet. This effect is larger
in non-central than in central relativistic heavy ion collisions and also for
jet energy loss that has a linear than a quadratic dependence on its path
length in the medium
Carbon nanomaterials as drug transporter for cancer therapy
There is a vigorous and growing research effort developing carbon nanotubes (CNTs) for medical applications. It is now known that nanocomposites of Single Wall Nanotubes (SWNTs) can be used to deliver anti-cancer drugs to cells. Also, SWNTs are efficient at converting near infrared (NIR) light to heat, and can do so in a cell, and so cancer cells can be targeted for destruction by NIR radiation, once the cells have taken up SWNTs. SWNTs are highly insoluble in water, but can be functionalized via physical or covalent attachment of solubilizing molecules and drugs of interest. Once this is done, they are readily taken up by cells. We found evidence that our CNT nanocomposites were found to enter cells via endocytosis (the mechanism cells use to take up nutrients); this agrees with earlier work by Dai and coworkers. Herein, we perform systematic study of the internalization, delivery and subcellular localization and possible adverse effects of SWNTs dispersed in culture media and SWNTs wrapped with different fluorescently labelled peptide (FLP-SWNTs) on Chinese hamster ovary (CHO) cells and SWNTs attached with anti-cancer drug on two common cancerous cell lines, human epithelial carcinoma cell line (HeLa) and colorectal cancer cell lines (WiDr)
Survey of grid resource monitoring and prediction strategies.
This literature focuses on grid resource monitoring and prediction, representative monitoring and prediction systems are analyzed and evaluated, then monitoring and prediction strategies for grid resources are summarized and discussed, recommendations are also given for building monitoring sensors and prediction models. During problem definition, one-step-ahead prediction is extended to multi-step-ahead prediction, which is then modeled with computational intelligence algorithms such as neural network and support vector regression. Numerical simulations are performed on benchmark data sets, while comparative results on accuracy and efficiency indicate that support vector regression models achieve superior performance. Our efforts can be utilized as direction for building online monitoring and prediction system for grid resources
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