3,215 research outputs found
Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective
Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as ‘A.I. neuroprediction,’ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed
Testing Verlinde's emergent gravity in early-type galaxies
Verlinde derived gravity as an emergent force from the information flow,
through two-dimensional surfaces and recently, by a priori postulating the
entanglement of information in 3D space, he derived the effect of the
gravitational potential from dark matter (DM) as the entropy displacement of
dark energy by baryonic matter. In Emergent Gravity (EG) this apparent DM
depends only on the baryonic mass distribution and the present-day value of the
Hubble parameter. In this paper we test the EG proposition, formalized by
Verlinde for a spherical and isolated mass distribution, using the central
velocity dispersion, and the light distribution in a sample of 4260
massive and local early-type galaxies (ETGs) from the SPIDER sample. Our
results remain unaltered if we consider the sample of 807 roundest field
galaxies. We derive the predictions by EG for the stellar mass-to-light ratio
(M/L) and the Initial Mass Function (IMF), and compare them with the same
inferences derived from a) DM-based models, b) MOND and c) stellar population
models. We demonstrate that, consistently with a classical Newtonian framework
with a DM halo component, or alternative theories of gravity as MOND, the
central dynamics can be fitted if the IMF is assumed non-universal. The results
can be interpreted with a IMF lighter than a standard Chabrier at low-,
and bottom-heavier IMFs at larger . We find lower, but still
acceptable, stellar M/L in EG theory, if compared with the DM-based NFW model
and with MOND. The results from EG are comparable to what is found if the DM
haloes are adiabatically contracted and with expectations from spectral
gravity-sensitive features. If the strain caused by the entropy displacement
would be not maximal, as adopted in the current formulation, then the dynamics
of ETGs could be reproduced with larger M/L. (abridged)Comment: 12 pages, 2 figures, submitted to MNRAS. The updated manuscript
presents significantly altered conclusions, after discovering an internal bug
in an older version of the Mathematica package, leading to incorrect
numerical results when calculating the derivatives of Gamma function
Robustness of the transition against compositional and structural ageing in S/F/S heterostructures
We have studied the temperature induced thermodynamic transition in
Nb/PdNi/Nb Superconductor/Ferromagnetic/Superconductor (SFS) heterostructures
by microwave measurements of the superfluid density. We have observed a shift
in the transition temperature with the ageing of the heterostructures,
suggesting that structural and/or chemical changes took place. Motivated by the
electrodynamics findings, we have extensively studied the local structural
properties of the samples by means of X-ray Absorption Spectroscopy (XAS)
technique, and the compositional profile by Time-of-Flight Secondary Ion Mass
Spectrometry (ToF-SIMS). We found that the samples have indeed changed their
properties, in particular for what concerns the interfaces and the composition
of the ferromagnetic alloy layer. The structural and compositional data are
consistent with the shift of the transition toward the behaviour of
heterostructures with different F layers. An important emerging indication to
the physics of SFS is the weak relevance of the ideality of the interfaces:
even in aged samples, with less-than-ideal interfaces, the temperature-induced
transition is still detectable albeit at a different critical F
thickness.Comment: 11 pages, 9 figures, accepted for publication on Phys. Rev. B,
http://journals.aps.org/prb
Cognitive dissonance induction as an “inoculator” against negative attitudes towards victims
The “belief in a just world” and the related “justice motive” can be construed as a fundamental drive-in people's life. Paradoxically this “justice motive” may motivate people to be unfair by assigning blame to objectively innocent victims. In two experimental studies, we address the possibility that inducing cognitive dissonance can reduce the assigning of blame to innocent victims. Study 1 (n = 71) consisted of a 2 × 2 design in which participants were randomly assigned to two types of induction (Dissonance induction/Awareness Induction Only condition) and two victims' background conditions (innocent victim v non-innocent victim). In Study 2 (n = 171) 3 types of induction were compared (Dissonance Induction/Awareness Induction/Control condition) with all victims' scenarios considering them innocent. Study 1 showed that innocent victims were less negatively evaluated in the Dissonance Induction condition compared to the Awareness Only Induction condition; non-innocent victims were not differently evaluated in both conditions. Study 2 showed that innocent victims were less negatively evaluated in the Dissonance Induction condition compared to the Awareness Induction condition and the Control condition. Overall, findings suggest that cognitive dissonance induction can be an effective mechanism to reduce assigning blame to innocent victims.info:eu-repo/semantics/acceptedVersio
Scaling relations and baryonic cycling in local star-forming galaxies: II. Gas content and star-formation efficiency
Assessments of the cold-gas reservoir in galaxies are a cornerstone for understanding star-formation processes and the role of feedback and baryonic cycling in galaxy evolution. Here we exploit a sample of 392 galaxies (dubbed MAGMA, Metallicity and Gas for Mass Assembly), presented in a recent paper, to quantify molecular and atomic gas properties across a broad range in stellar mass, Mstar, from ∼107 - 1011 M⊙. First, we find the metallicity (Z) dependence of the conversion factor for CO luminosity to molecular H2 mass αCO to be shallower than previous estimates, with αCO∝ (Z/Z⊙)-1.55. Second, molecular gas mass MH2 is found to be strongly correlated with Mstar and star-formation rate (SFR), enabling predictions of MH2 good to within ∼0.2 dex; analogous relations for atomic gas mass MHI and total gas mass Mgas are less accurate, ∼0.4 dex and ∼0.3 dex, respectively. Indeed, the behavior of atomic gas mass MHI in MAGMA scaling relations suggests that it may be a third, independent variable that encapsulates information about the circumgalactic environment and gas accretion. If Mgas is considered to depend on MHI, together with Mstar and SFR, we obtain a relation that predicts Mgas to within ∼0.05 dex. Finally, the analysis of depletion times and the scaling of MHI/Mstar and MH2/Mstar over three different mass bins suggests that the partition of gas and the regulation of star formation through gas content depends on the mass regime. Dwarf galaxies (Mstar∝ 3 × 109 M⊙) tend to be overwhelmed by (H » I) accretion, and despite short τH2 (and thus presumably high star-formation efficiency), star formation is unable to keep up with the gas supply. For galaxies in the intermediate Mstar "gas-equilibrium"bin (3 × 109 M⊙ ≲ Mstar ≲ 3 × 1010 M⊙), star formation proceeds apace with gas availability, and H I and H2 are both proportional to SFR. In the most massive "gas-poor, bimodality"regime (Mstar ≳ 3 × 1010 M⊙), H I does not apparently participate in star formation, although it generally dominates in mass over H2. Our results confirm that atomic gas plays a key role in baryonic cycling, and is a fundamental ingredient for current and future star formation, especially in dwarf galaxies
Scaling relations and baryonic cycling in local star-forming galaxies: II. Gas content and star-formation efficiency
Assessments of the cold-gas reservoir in galaxies are a cornerstone for
understanding star-formation processes and the role of feedback and baryonic
cycling in galaxy evolution. Here we exploit a sample of 392 galaxies (dubbed
MAGMA, Metallicity and Gas for Mass Assembly), presented in a recent paper, to
quantify molecular and atomic gas properties across a broad range in stellar
mass, Mstar, from Msun. First, we find the metallicity
() dependence of alpha_CO to be shallower than previous estimates, with
alpha_CO. Second, molecular gas mass MH2 is found
to be strongly correlated with Mstar and star-formation rate (SFR), enabling
predictions of MH2 good to within 0.2 dex. The behavior of atomic gas
mass MHI in MAGMA scaling relations suggests that it may be a third,
independent variable that encapsulates information about the circumgalactic
environment and gas accretion. If Mgas is considered to depend on MHI, together
with Mstar and SFR, we obtain a relation that predicts Mgas to within
0.05 dex. Finally, the analysis of depletion times and the scaling of
MHI/Mstar and MH2/Mstar over three different mass bins suggests that the
partition of gas and the regulation of star formation through gas content
depends on the mass regime. Dwarf galaxies tend to be overwhelmed by (HI)
accretion, while for galaxies in the intermediate Mstar "gas-equilibrium" bin,
star formation proceeds apace with gas availability. In the most massive
"gas-poor, bimodality" galaxies, HI does not apparently participate in star
formation, although it generally dominates in mass over H2. Our results confirm
that atomic gas plays a key role in baryonic cycling, and is a fundamental
ingredient for current and future star formation, especially in dwarf galaxies.
(abridged for arXiv)Comment: 22 pages, 15 figures, 2 appendices, accepted for publication in
Astronomy & Astrophysic
Testing Convolutional Neural Networks for finding strong gravitational lenses in KiDS
Convolutional Neural Networks (ConvNets) are one of the most promising
methods for identifying strong gravitational lens candidates in survey data. We
present two ConvNet lens-finders which we have trained with a dataset composed
of real galaxies from the Kilo Degree Survey (KiDS) and simulated lensed
sources. One ConvNet is trained with single \textit{r}-band galaxy images,
hence basing the classification mostly on the morphology. While the other
ConvNet is trained on \textit{g-r-i} composite images, relying mostly on
colours and morphology. We have tested the ConvNet lens-finders on a sample of
21789 Luminous Red Galaxies (LRGs) selected from KiDS and we have analyzed and
compared the results with our previous ConvNet lens-finder on the same sample.
The new lens-finders achieve a higher accuracy and completeness in identifying
gravitational lens candidates, especially the single-band ConvNet. Our analysis
indicates that this is mainly due to improved simulations of the lensed
sources. In particular, the single-band ConvNet can select a sample of lens
candidates with purity, retrieving 3 out of 4 of the confirmed
gravitational lenses in the LRG sample. With this particular setup and limited
human intervention, it will be possible to retrieve, in future surveys such as
Euclid, a sample of lenses exceeding in size the total number of currently
known gravitational lenses.Comment: 16 pages, 10 figures. Accepted for publication in MNRA
Comparative analysis of the effects of olive oil hydroxytyrosol and its 5-S-lipoyl conjugate in protecting human erythrocytes from mercury toxicity
Oxidative stress is one of the underlying mechanisms of the toxic effects exerted by mercury (Hg) on human health. Several antioxidant compounds, including the olive oil phenol hydroxytyrosol (HT), were investigated for their protective action. Recently, we have reported that 5-S-lipoylhydroxytyrosol (Lipo-HT) has shown increased antioxidant activities compared to HT and exerted potent protective effects against reactive oxygen species (ROS) generation and oxidative damage in human hepatocellular carcinoma HepG2 cell lines. In this study, the effects of Lipo-HT and HT on oxidative alterations of human erythrocytes induced by exposure to 40 μM HgCl2 were comparatively evaluated. When administered to the cells, Lipo-HT (5–20 μM) proved nontoxic and it decreased the Hg-induced generation of ROS, the hemolysis, and the depletion of intracellular GSH levels. At all tested concentrations, Lipo-HT exhibited higher ability to counteract Hg-induced cytotoxicity compared to HT. Model studies indicated the formation of a mercury complex at the SH group of Lipo-HT followed by a redox reaction that would spare intracellular GSH. Thus, the enhanced erythrocyte protective action of Lipo-HT from Hg-induced damage with respect to HT is likely due to an effective chelating and reducing ability toward mercury ions. These findings encourage the use of Lipo-HT in nutraceutical strategies to contrast heavy metal toxicity in humans
Morphology of the Io Plasma Torus From Juno Radio Occultations
The jovian moon Io disperses about 1 ton/s of material in the planetary magnetosphere, mainly by sublimation of SO2 from the surface and by its intense volcanic activity. The ejected material supplies the plasma cloud surrounding Jupiter known as Io Plasma Torus (IPT). The radio communication between Juno and the Earth DSN station crosses the IPT near the closest approach. Being a dispersive medium, the IPT introduces a path delay in the signal, which can be analyzed to retrieve the density distribution of electrons. We used radio tracking data from the first 25 orbits to investigate the morphology of the IPT and its variability. We adopted a static and axisymmetric model for the electron density and we updated it including temporal and longitudinal variability. We found that our best fit model must include both variabilities, even though on average the morphology of the IPT agrees with previous analyses. Our results suggest that the density of the outer region of the IPT fluctuates over 50% the average value over a typical time scale of about 420 days
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