14,412 research outputs found
Naturalness, dark matter, and the muon anomalous magnetic moment in supersymmetric extensions of the standard model with a pseudo-Dirac gluino
We study the naturalness, dark matter, and muon anomalous magnetic moment in
the Supersymmetric Standard Models (SSMs) with a pseudo-Dirac gluino (PDGSSMs)
from hybrid and term supersymmetry (SUSY) breakings. To obtain the
observed dark matter relic density and explain the muon anomalous magnetic
moment, we find that the low energy fine-tuning measures are larger than about
30 due to strong constraints from the LUX and PANDAX experiments. Thus, to
study the natural PDGSSMs, we consider multi-component dark matter and then the
relic density of the lighest supersymmetric particle (LSP) neutralino is
smaller than the correct value. We classify our models into six kinds: (i) Case
A is a general case, which has small low energy fine-tuning measure and can
explain the anomalous magnetic moment of the muon; (ii) Case B with the LSP
neutralino and light stau coannihilation; (iii) Case C with Higgs funnel; (iv)
Case D with Higgsino LSP; (v) Case E with light stau coannihilation and
Higgsino LSP; (vi) Case F with Higgs funnel and Higgsino LSP. We study these
Cases in details, and show that our models can be natural and consistent with
the LUX and PANDAX experiments, as well as explain the muon anomalous magnetic
moment. In particular, all these cases except the stau coannihilation can even
have low energy fine-tuning measures around 10.Comment: 19 pages, 18 figure
Functional Bias and Spatial Organization of Genes in Mutational Hot and Cold Regions in the Human Genome
The neutral mutation rate is known to vary widely along human chromosomes,
leading to mutational hot and cold regions. We provide evidence that categories
of functionally-related genes reside preferentially in mutationally hot or cold
regions, the size of which we have measured. Genes in hot regions are biased
toward extra-cellular communication (surface receptors, cell adhesion, immune
response, etc.) while those in cold regions are biased toward essential
cellular processes (gene regulation, RNA processing, protein modification,
etc.). From a selective perspective, this organization of genes could minimize
the mutational load on genes that need to be conserved and allow fast evolution
for genes that must frequently adapt. We also analyze the effect of gene
duplication and chromosomal recombination, which contribute significantly to
these biases for certain categories of hot genes. Overall, our results show
that genes are located non-randomly with respect to hot and cold regions,
offering the possibility that selection acts at the level of gene location in
the human genome.Comment: 17 pages, 6 figures, 2 tables. accepted to PLOS Biology, Feb. 2004
issu
Automatically Generating Searchable Fingerprints For WordPress Plugins Using Static Program Analysis
This thesis introduces a novel method to automatically generate fingerprints for WordPress plugins. Our method performs static program analysis using Abstract Syntax Trees (ASTs) of WordPress plugins. The generated fingerprints can be used for identifying these plugins using search engines, which have support critical applications such as proactively identifying web servers with vulnerable WordPress plugins. We have used our method to generate fingerprints for over 10,000 WordPress plugins and analyze the resulted fingerprints. Our fingerprints have also revealed 453 websites that are potentially vulnerable. We have also compared fingerprints for vulnerable plugins and those for vulnerability-free plugins
Entanglement in the anisotropic Heisenberg XYZ model with different Dzyaloshinskii-Moriya interaction and inhomogeneous magnetic field
We investigate the entanglement in a two-qubit Heisenberg XYZ system with
different Dzyaloshinskii-Moriya(DM) interaction and inhomogeneous magnetic
field. It is found that the control parameters (, and )
are remarkably different with the common control parameters (,
and ) in the entanglement and the critical temperature, and these
x-component parameters can increase the entanglement and the critical
temperature more efficiently. Furthermore, we show the properties of these
x-component parameters for the control of entanglement. In the ground state,
increasing (spin-orbit coupling parameter) can decrease the critical
value and increase the entanglement in the revival region, and
adjusting some parameters (increasing and , decreasing and
) can decrease the critical value to enlarge the revival
region. In the thermal state, increasing can increase the revival
region and the entanglement in the revival region (for or ), and
enhance the critical value to make the region of high entanglement
larger. Also, the entanglement and the revival region will increase with the
decrease of (uniform magnetic field). In addition, small
(nonuniform magnetic field) has some similar properties to , and with
the increase of the entanglement also has a revival phenomenon, so that
the entanglement can exist at higher temperature for larger .Comment: 8 pages, 8 figure
A robot arm simulation with a shared memory multiprocessor machine
A parallel processing scheme for a single chain robot arm is presented for high speed computation on a shared memory multiprocessor. A recursive formulation that is derived from a virtual work form of the d'Alembert equations of motion is utilized for robot arm dynamics. A joint drive system that consists of a motor rotor and gears is included in the arm dynamics model, in order to take into account gyroscopic effects due to the spinning of the rotor. The fine grain parallelism of mechanical and control subsystem models is exploited, based on independent computation associated with bodies, joint drive systems, and controllers. Efficiency and effectiveness of the parallel scheme are demonstrated through simulations of a telerobotic manipulator arm. Two different mechanical subsystem models, i.e., with and without gyroscopic effects, are compared, to show the trade-off between efficiency and accuracy
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The stochastic mortality modeling and the pricing of mortality/longevity linked derivatives
The Lee-Carter mortality model provides the very first model for modeling the mortality rate with stochastic time and age mortality dynamics. The model is constructed modeling the mortality rate to incorporate both an age effect and a period effect. The Lee-Carter model provides the fundamental set up currently used in most modern mortality modeling. Various extensions of the Lee-Carter model include either adding an extra term for a cohort effect or imposing a stochastic process for mortality dynamics. Although both of these extensions can provide good estimation results for the mortality rate, applying them for the pricing of the mortality/ longevity linked derivatives is not easy. While the current stochastic mortality models are too complicated to be explained and to be implemented, transforming the cohort effect into a stochastic process for the pricing purpose is very difficult. Furthermore, the cohort effect itself sometimes may not be significant. We propose using a new modified Lee-Carter model with a Normal Inverse Gaussian (NIG) Lévy process along with the Esscher transform for the pricing of mortality/ longevity linked derivatives. The modified Lee-Carter model, which applies the Lee-Carter model on the growth rate of mortality rates rather than the level of mortality rates themselves, performs better than the current mortality rate models shown in Mitchell et al (2013). We show that the modified Lee-Carter model also retains a similar stochastic structure to the Lee-Carter model, so it is easy to demonstrate the implication of the model. We proposed the additional NIG Lévy process with Esscher transform assumption that can improve the fit and prediction results by adapting the mortality improvement rate. The resulting mortality rate matches the observed pattern that the mortality rate has been improving due to the advancing development of technology and improvements in the medical care system. The resulting mortality rate is also developed under a martingale measure so it is ready for the direct application of pricing the mortality/longevity linked derivatives, such as q-forward, longevity bond, and mortality catastrophe bond. We also apply our proposed model along with an information theoretic optimization method to construct the pricing procedures for a life settlement. While our proposed model can improve the mortality rate estimation, the application of information theory allows us to incorporate the private health information of a specific policy holder and hence customize the distribution of the death year distribution for the policy holder so as to price the life settlement. The resulting risk premium is close to the practical understanding in the life settlement market.Information, Risk, and Operations Management (IROM
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