6,883 research outputs found
Kinematic Basis of Emergent Energetics of Complex Dynamics
Stochastic kinematic description of a complex dynamics is shown to dictate an
energetic and thermodynamic structure. An energy function emerges
as the limit of the generalized, nonequilibrium free energy of a Markovian
dynamics with vanishing fluctuations. In terms of the and its
orthogonal field , a general vector field
can be decomposed into , where
.
The matrix and scalar , two additional characteristics to the
alone, represent the local geometry and density of states intrinsic to
the statistical motion in the state space at . and
are interpreted as the emergent energy and degeneracy of the motion, with an
energy balance equation ,
reflecting the geometrical . The
partition function employed in statistical mechanics and J. W. Gibbs' method of
ensemble change naturally arise; a fluctuation-dissipation theorem is
established via the two leading-order asymptotics of entropy production as
. The present theory provides a mathematical basis for P. W.
Anderson's emergent behavior in the hierarchical structure of complexity
science.Comment: 7 page
Finger-gate manipulated quantum transport in a semiconductor narrow constriction with spin-orbit interactions and Zeeman effect
The authors investigate quantum transport in a narrow constriction fabricated
by narrow band gap semiconductor materials with spin-orbit (SO) couplings. We
consider the Rashba-Dresselhaus (RD) spin-orbit interactions (SOIs) and the
Zeeman effect induced by an in-plane magnetic field along the transport
direction. The interplay of the RD-SOI and the Zeeman effect may induce a
SOI-Zeeman gap and influence the transport properties. We demonstrate that an
attractive scattering potential may induce electron-like quasi-bound-state
feature and manifest the RD-SOI-Zeeman induced Fano line-shape in conductance.
Furthermore, a repulsive scattering potential may induce hole-like
quasi-bound-state feature on the subband top of the lower spin branch.Comment: 10 pages, 9 figure
Mechanically induced pseudo-magnetic fields in the excitonic fine structures of droplet epitaxial quantum dots
We present numerical investigations based on the Luttinger-Kohn four-band theory and, accordingly, establish a quantitatively valid model of the
excitonic fine structures of droplet epitaxial GaAs/AlGaAs quantum dots under
uni-axial stress control. In the formalisms, stressing a photo-excited quantum
dot is equivalent creating a pseudo-magnetic field that is directly coupled to
the pseudo-spin of the exciton doublet and tunable to tailor the polarized fine
structure of exciton. The latter feature is associated with the
valence-band-mixing of exciton that is especially sensitive to external stress
in inherently unstrained droplet epitaxial GaAs/AlGaAs quantum dots and allows
us to mechanically design and prepare any desired exciton states of QD photon
sources prior to the photon generation.Comment: 7 figure
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FAM129B, an antioxidative protein, reduces chemosensitivity by competing with Nrf2 for Keap1 binding.
BackgroundThe transcription factor Nrf2 is a master regulator of antioxidant response. While Nrf2 activation may counter increasing oxidative stress in aging, its activation in cancer can promote cancer progression and metastasis, and confer resistance to chemotherapy and radiotherapy. Thus, Nrf2 has been considered as a key pharmacological target. Unfortunately, there are no specific Nrf2 inhibitors for therapeutic application. Moreover, high Nrf2 activity in many tumors without Keap1 or Nrf2 mutations suggests that alternative mechanisms of Nrf2 regulation exist.MethodsInteraction of FAM129B with Keap1 is demonstrated by immunofluorescence, colocalization, co-immunoprecipitation and mammalian two-hybrid assay. Antioxidative function of FAM129B is analyzed by measuring ROS levels with DCF/flow cytometry, Nrf2 activation using luciferase reporter assay and determination of downstream gene expression by qPCR and wester blotting. Impact of FAM129B on in vivo chemosensitivity is examined in mice bearing breast and colon cancer xenografts. The clinical relevance of FAM129B is assessed by qPCR in breast cancer samples and data mining of publicly available databases.FindingsWe have demonstrated that FAM129B in cancer promotes Nrf2 activity by reducing its ubiquitination through competition with Nrf2 for Keap1 binding via its DLG and ETGE motifs. In addition, FAM129B reduces chemosensitivity by augmenting Nrf2 antioxidative signaling and confers poor prognosis in breast and lung cancer.InterpretationThese findings demonstrate the important role of FAM129B in Nrf2 activation and antioxidative response, and identify FMA129B as a potential therapeutic target. FUND: The Chang Gung Medical Foundation (Taiwan) and the Ministry of Science and Technology (Taiwan)
Improved real-time imaging spectrometer
An improved AOTF-based imaging spectrometer that offers several advantages over prior art AOTF imaging spectrometers is presented. The ability to electronically set the bandpass wavelength provides observational flexibility. Various improvements in optical architecture provide simplified magnification variability, improved image resolution and light throughput efficiency and reduced sensitivity to ambient light. Two embodiments of the invention are: (1) operation in the visible/near-infrared domain of wavelength range 0.48 to 0.76 microns; and (2) infrared configuration which operates in the wavelength range of 1.2 to 2.5 microns
When Crowdsourcing Meets Mobile Sensing: A Social Network Perspective
Mobile sensing is an emerging technology that utilizes agent-participatory
data for decision making or state estimation, including multimedia
applications. This article investigates the structure of mobile sensing schemes
and introduces crowdsourcing methods for mobile sensing. Inspired by social
network, one can establish trust among participatory agents to leverage the
wisdom of crowds for mobile sensing. A prototype of social network inspired
mobile multimedia and sensing application is presented for illustrative
purpose. Numerical experiments on real-world datasets show improved performance
of mobile sensing via crowdsourcing. Challenges for mobile sensing with respect
to Internet layers are discussed.Comment: To appear in Oct. IEEE Communications Magazine, feature topic on
"Social Networks Meet Next Generation Mobile Multimedia Internet
Noninvasive prediction of Blood Lactate through a machine learning-based approach.
We hypothesized that blood lactate concentration([Lac]blood) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [Lac]blood noninvasively during constant work rate (CWR) exercise of various intensities. 31 healthy participants were recruited and each underwent 4 cardiopulmonary exercise tests: one incremental and three CWR tests (low: 35% of peak work rate for 15 min, moderate: 60% 10 min and high: 90% 4 min). At the end of each CWR test, venous blood was sampled to determine [Lac]blood. 31 trios of CWR tests were employed to construct the mathematical model, which utilized exponential regression combined with Taylor expansion. Good fitting was achieved when the conditions of low and moderate intensity were put in one model; high-intensity in another. Standard deviation of fitting error in the former condition is 0.52; in the latter is 1.82 mmol/liter. Weighting analysis demonstrated that, besides heart rate, respiratory variables are required in the estimation of [Lac]blood in the model of low/moderate intensity. In conclusion, by measuring noninvasive cardio-respiratory parameters, [Lac]blood during CWR exercise can be determined with good accuracy. This should have application in endurance training and future exercise industry
Dominant channels of exciton spin relaxation in photoexcited self-assembled (In,Ga)As quantum dots
We present a comprehensive theoretical investigation of spin relaxation processes of excitons in photoexcited self-assembled quantum dots. The exciton spin relaxations are considered between dark- and bright-exciton states via the channels created by various spin-admixture mechanisms, including electron Rashba and Dresselhaus spin- orbital couplings (SOCs), hole linear and hole cubic SOCs, and electron hyperfine interactions, incorporated with single- and double-phonon processes. The hole-Dresselhaus SOC is identified as the dominant spin-admixture mechanism, leading to relaxation rates as fast as ∼10−2 ns−1, consistent with recent observations. Moreover, due to significant electron-hole exchange interactions, single-phonon processes are unusually dominant over two-phonon ones in a photoexcited dot even at temperatures as high as 15 K
Supervised Collective Classification for Crowdsourcing
Crowdsourcing utilizes the wisdom of crowds for collective classification via
information (e.g., labels of an item) provided by labelers. Current
crowdsourcing algorithms are mainly unsupervised methods that are unaware of
the quality of crowdsourced data. In this paper, we propose a supervised
collective classification algorithm that aims to identify reliable labelers
from the training data (e.g., items with known labels). The reliability (i.e.,
weighting factor) of each labeler is determined via a saddle point algorithm.
The results on several crowdsourced data show that supervised methods can
achieve better classification accuracy than unsupervised methods, and our
proposed method outperforms other algorithms.Comment: to appear in IEEE Global Communications Conference (GLOBECOM)
Workshop on Networking and Collaboration Issues for the Internet of
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