10,768 research outputs found
Responsibility modulates neural mechanisms of outcome processing : an ERP study
The role of personal responsibility in decision-making and its influence on the outcome evaluation process have been investigated relatively rarely in cognitive neuroscience. The present event-related brain potential (ERP) study manipulated the subjective sense of responsibility by modifying outcome controllability in a gambling task. Participants reported a higher sense of responsibility and produced a larger fERN when they were told that the game was 'controllable' compared with when they were told that the game was 'uncontrollable.' In addition, fERN amplitude was correlatedwith individual self-reports of personal responsibility over the outcomes. These results indicate that self-attribution of responsibility associated with different degrees of controllability affects the outcome evaluation process and fERN amplitude
The possible molecular state and its radiative decay
Recently, several exotic bosons have been confirmed as multi-quark states,
but there are violent disputes about their inner structures, namely if they are
molecular states or tetraquarks, or even mixtures of the two structures. It
would be interesting to experimentally search for non-strange four-quark states
with open charm or bottom which are lighter than or .
Reasonable arguments indicate that they are good candidates of pure molecular
states or because pions are the lightest boson. Both and
bound states do not decay via strong interaction. The molecule
may decay into by radiating a photon, whereas molecule can only
decay via weak interaction. In this paper we explore the mass spectra of
molecular statesby solving the corresponding B-S equation. Then the rate of
radiative decay is calculated
and our numerical results indicate that the processes can be measured by the
future experiment. We also briefly discuss the case, due to the
constraint of the final state phase space, it can only decay via weak
interaction.Comment: 12 pages, 3 figures, 3 table
Universal Boundary Entropies in Conformal Field Theory: A Quantum Monte Carlo Study
Recently, entropy corrections on nonorientable manifolds such as the Klein
bottle are proposed as a universal characterization of critical systems with an
emergent conformal field theory (CFT). We show that entropy correction on the
Klein bottle can be interpreted as a boundary effect via transforming the Klein
bottle into an orientable manifold with nonlocal boundary interactions. The
interpretation reveals the conceptual connection of the Klein bottle entropy
with the celebrated Affleck-Ludwig entropy in boundary CFT. We propose a
generic scheme to extract these universal boundary entropies from quantum Monte
Carlo calculation of partition function ratios in lattice models. Our numerical
results on the Affleck-Ludwig entropy and Klein bottle entropy for the
-state quantum Potts chains with show excellent agreement with the
CFT predictions. For the quantum Potts chain with , the Klein bottle
entropy slightly deviates from the CFT prediction, which is possibly due to
marginally irrelevant terms in the low-energy effective theory.Comment: 10 pages, 4 figures. Published versio
Probing and Interaction at LHC
Many new physics models predict the existence of TeV-scale charged gauge
boson together with Higgs boson(s). We study the
interaction and explore the angular distribution of charged lepton to
distinguish from in process at the LHC. It is found that a new type forward-backward
asymmetry() relating to the angle between the direction of the charged
lepton in rest frame and that of the reconstructed in laboratory
frame is useful to investigate the properties of interaction. We
analyze the Standard Model backgrounds and develop a set of cuts to highlight
the signal and suppress the backgrounds at LHC. We find that can reach
0.03(-0.07) for () production at TeV
Real is not True: Backdoor Attacks Against Deepfake Detection
The proliferation of malicious deepfake applications has ignited substantial
public apprehension, casting a shadow of doubt upon the integrity of digital
media. Despite the development of proficient deepfake detection mechanisms,
they persistently demonstrate pronounced vulnerability to an array of attacks.
It is noteworthy that the pre-existing repertoire of attacks predominantly
comprises adversarial example attack, predominantly manifesting during the
testing phase. In the present study, we introduce a pioneering paradigm
denominated as Bad-Deepfake, which represents a novel foray into the realm of
backdoor attacks levied against deepfake detectors. Our approach hinges upon
the strategic manipulation of a delimited subset of the training data, enabling
us to wield disproportionate influence over the operational characteristics of
a trained model. This manipulation leverages inherent frailties inherent to
deepfake detectors, affording us the capacity to engineer triggers and
judiciously select the most efficacious samples for the construction of the
poisoned set. Through the synergistic amalgamation of these sophisticated
techniques, we achieve an remarkable performance-a 100% attack success rate
(ASR) against extensively employed deepfake detectors.Comment: BigDIA 202
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