7,941 research outputs found
Symmetry breaking effects upon bipartite and multipartite entanglement in the XY model
We analyze the bipartite and multipartite entanglement for the ground state
of the one-dimensional XY model in a transverse magnetic field in the
thermodynamical limit. We explicitly take into account the spontaneous symmetry
breaking in order to explore the relation between entanglement and quantum
phase transitions. As a result we show that while both bipartite and
multipartite entanglement can be enhanced by spontaneous symmetry breaking deep
into the ferromagnetic phase, only the latter is affected by it in the vicinity
of the critical point. This result adds to the evidence that multipartite, and
not bipartite, entanglement is the fundamental indicator of long range
correlations in quantum phase transitions.Comment: 13 pages, 19 figures, comments welcome. V2: small changes, published
versio
Neural control of postural responses during perturbations to balance while changing direction
The Transition Between Quantum Coherence and Incoherence
We show that a transformed Caldeira-Leggett Hamltonian has two distinct
families of fixed points, rather than a single unique fixed point as often
conjectured based on its connection to the anisotropic Kondo model. The two
families are distinguished by a sharp qualitative difference in their quantum
coherence properties and we argue that this distinction is best understood as
the result of a transition in the model between degeneracy and non-degeneracy
in the spectral function of the ``spin-flip'' operator.Comment: some typos corrected and a reference adde
A combined approach for comparative exoproteome analysis of Corynebacterium pseudotuberculosis
Background: Bacterial exported proteins represent key components of the host-pathogen interplay. Hence, we
sought to implement a combined approach for characterizing the entire exoproteome of the pathogenic
bacterium Corynebacterium pseudotuberculosis, the etiological agent of caseous lymphadenitis (CLA) in sheep and
goats.
Results: An optimized protocol of three-phase partitioning (TPP) was used to obtain the C. pseudotuberculosis
exoproteins, and a newly introduced method of data-independent MS acquisition (LC-MSE) was employed for
protein identification and label-free quantification. Additionally, the recently developed tool SurfG+ was used for in
silico prediction of sub-cellular localization of the identified proteins. In total, 93 different extracellular proteins of
C. pseudotuberculosis were identified with high confidence by this strategy; 44 proteins were commonly identified
in two different strains, isolated from distinct hosts, then composing a core C. pseudotuberculosis exoproteome.
Analysis with the SurfG+ tool showed that more than 75% (70/93) of the identified proteins could be predicted as
containing signals for active exportation. Moreover, evidence could be found for probable non-classical export of
most of the remaining proteins.
Conclusions: Comparative analyses of the exoproteomes of two C. pseudotuberculosis strains, in addition to
comparison with other experimentally determined corynebacterial exoproteomes, were helpful to gain novel
insights into the contribution of the exported proteins in the virulence of this bacterium. The results presented
here compose the most comprehensive coverage of the exoproteome of a corynebacterial species so far
A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses
Within the realm of privacy-preserving machine learning, empirical privacy
defenses have been proposed as a solution to achieve satisfactory levels of
training data privacy without a significant drop in model utility. Most
existing defenses against membership inference attacks assume access to
reference data, defined as an additional dataset coming from the same (or a
similar) underlying distribution as training data. Despite the common use of
reference data, previous works are notably reticent about defining and
evaluating reference data privacy. As gains in model utility and/or training
data privacy may come at the expense of reference data privacy, it is essential
that all three aspects are duly considered. In this paper, we first examine the
availability of reference data and its privacy treatment in previous works and
demonstrate its necessity for fairly comparing defenses. Second, we propose a
baseline defense that enables the utility-privacy tradeoff with respect to both
training and reference data to be easily understood. Our method is formulated
as an empirical risk minimization with a constraint on the generalization
error, which, in practice, can be evaluated as a weighted empirical risk
minimization (WERM) over the training and reference datasets. Although we
conceived of WERM as a simple baseline, our experiments show that,
surprisingly, it outperforms the most well-studied and current state-of-the-art
empirical privacy defenses using reference data for nearly all relative privacy
levels of reference and training data. Our investigation also reveals that
these existing methods are unable to effectively trade off reference data
privacy for model utility and/or training data privacy. Overall, our work
highlights the need for a proper evaluation of the triad model utility /
training data privacy / reference data privacy when comparing privacy defenses
Diffusion in the Continuous-Imaginary-Time Quantum World-Line Monte Carlo Simulations with Extended Ensembles
The dynamics of samples in the continuous-imaginary-time quantum world-line
Monte Carlo simulations with extended ensembles are investigated. In the case
of a conventional flat ensemble on the one-dimensional quantum S=1 bi-quadratic
model, the asymmetric behavior of Monte Carlo samples appears in the diffusion
process in the space of the number of vertices. We prove that a local
diffusivity is asymptotically proportional to the number of vertices, and we
demonstrate the asymmetric behavior in the flat ensemble case. On the basis of
the asymptotic form, we propose the weight of an optimal ensemble as
, where denotes the number of vertices in a sample. It is shown
that the asymmetric behavior completely vanishes in the case of the proposed
ensemble on the one-dimensional quantum S=1 bi-quadratic model.Comment: 4 pages, 2 figures, update a referenc
A TESTING BATTERY ON BALANCE AND PERFORMANCE SYMMETRY FOR TEAM SPORTS â AN EXAMPLE FROM ICE HOCKEY
The purpose of this study was to develop and apply an injury and performance screening programme for team sports and exemplify this for ice hockey. A set of four tests including landing, jumping and turning was employed and performance and balance related symmetry was extracted from force plate data and velocity measures in a test group of 28 elite ice hockey players. In this team, certain exercises showed a reflection of individual injury history while players showed a high symmetry for single leg landing task. This may be an effect of the specific training this group of athletes had undergone prior to the tests. Currently, we are assessing other teams who followed different training programs and apply these tests as a longitudinal screening tool. While final results are still outstanding, the potential of this approach was discussed
Editorial: Fungi as cell factories: Genetic engineering and applications
Wherever they are foundâon nearly any substrate on Earthâfungal organisms have a key role in promoting the homeostasis of the ecosystems. They are important decomposers in the soil food web due to their role in converting organic matter that is hard to digest into forms that other organisms can use. Fungi are not only beneficial for natural processes but have also become crucial players in engineered bioprocesses within the new bioeconomy due to their functionally diverse capacities. Fungi encompass a large group of organisms, ranging from well-studied species (e.g., Saccharomyces cerevisiae) to more complex filamentous fungi, including mushroom-forming species. Several fungal species have shown amenability to genetic engineering and large-scale production, but many are yet to be explored
ASSESSING KINEMATICS AND KINETICS OF HIGH-SPEED RUNNING USING INERTIAL MOTION CAPTURE: A PRELIMINARY ANALYSIS
The purpose of this study was to determine whether inertial motion capture (IMC) in combination with musculoskeletal modeling is a suitable method to assess lower limb kinematics and kinetics during high-speed running. Optical motion capture (OMC), IMC and ground reaction forces (GRF) were used as input for musculoskeletal models. Kinematics showed excellent correlations (knee: Ï=0.98, rRMSE=21.0%, hip: Ï=0.95, rRMSE=18.5 %, ankle: Ï=0.93, rRMSE=46.6%). The ground reaction force predictions showed varying results (anteroposterior: Ï=0.77, rRMSE=33.4%, mediolateral: Ï=0.04, rRMSE=69.1%, vertical: Ï=0.78, rRMSE=25.7%). The examined IMC and musculoskeletal modeling approach was proven a useful alternative to OMC and force plates for outdoor measurements in high-speed running
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