1,998 research outputs found
AGATA: Performance of -ray tracking and associated algorithms
AGATA is a modern -ray spectrometer for in-beam nuclear structure
studies, based on -ray tracking. Since more than a decade, it has been
operated performing experimental physics campaigns in different international
laboratories (LNL, GSI, GANIL). This paper reviews the obtained results
concerning the performances of -ray tracking in AGATA and associated
algorithms. We discuss -ray tracking and algorithms developed for
AGATA. Then, we present performance results in terms of efficiency and
peak-to-total for AGATA. The importance of the high effective angular
resolution of -ray tracking arrays is emphasised, e.g. with respect to
Doppler correction. Finally, we briefly touch upon the subject of -ray
imaging and its connection to -ray tracking
Discrete transverse superconducting modes in nano-cylinders
Spatial variation in the superconducting order parameter becomes significant
when the system is confined at dimensions well below the typical
superconducting coherence length. Motivated by recent experimental success in
growing single-crystal metallic nanorods, we study quantum confinement effects
on superconductivity in a cylindrical nanowire in the clean limit. For large
diameters, where the transverse level spacing is smaller than superconducting
order parameter, the usual approximations of Ginzburg-Landau theory are
recovered. However, under external magnetic field the order parameter develops
a spatial variation much stronger than that predicted by Ginzburg-Landau
theory, and gapless superconductivity is obtained above a certain field
strength. At small diameters, the discrete nature of the transverse modes
produces significant spatial variations in the order parameter with increased
average magnitude and multiple shoulders in the magnetic response.Comment: 10 pages, 8 figure
General rules for bosonic bunching in multimode interferometers
We perform a comprehensive set of experiments that characterize bosonic
bunching of up to 3 photons in interferometers of up to 16 modes. Our
experiments verify two rules that govern bosonic bunching. The first rule,
obtained recently in [1,2], predicts the average behavior of the bunching
probability and is known as the bosonic birthday paradox. The second rule is
new, and establishes a n!-factor quantum enhancement for the probability that
all n bosons bunch in a single output mode, with respect to the case of
distinguishable bosons. Besides its fundamental importance in phenomena such as
Bose-Einstein condensation, bosonic bunching can be exploited in applications
such as linear optical quantum computing and quantum-enhanced metrology.Comment: 6 pages, 4 figures, and supplementary material (4 pages, 1 figure
Automated computer-based detection of encounter behaviours in groups of honeybees.
Honeybees form societies in which thousands of members integrate their behaviours to act as a single functional unit. We have little knowledge on how the collaborative features are regulated by workers' activities because we lack methods that enable collection of simultaneous and continuous behavioural information for each worker bee. In this study, we introduce the Bee Behavioral Annotation System (BBAS), which enables the automated detection of bees' behaviours in small observation hives. Continuous information on position and orientation were obtained by marking worker bees with 2D barcodes in a small observation hive. We computed behavioural and social features from the tracking information to train a behaviour classifier for encounter behaviours (interaction of workers via antennation) using a machine learning-based system. The classifier correctly detected 93% of the encounter behaviours in a group of bees, whereas 13% of the falsely classified behaviours were unrelated to encounter behaviours. The possibility of building accurate classifiers for automatically annotating behaviours may allow for the examination of individual behaviours of worker bees in the social environments of small observation hives. We envisage that BBAS will be a powerful tool for detecting the effects of experimental manipulation of social attributes and sub-lethal effects of pesticides on behaviour
Unraveling Moral Reasoning in Amyotrophic Lateral Sclerosis: How Emotional Detachment Modifies Moral Judgment
In the last decade, scientific literature provided solid evidence of cognitive deficits in amyotrophic lateral sclerosis (ALS) patients and their effects on end-life choices. However, moral cognition and judgment are still poorly investigated in this population. Here we aimed at evaluating both socio-cognitive and socio-affective components of moral reasoning in a sample of 28 ALS patients. Patients underwent clinical and neuropsychological evaluation including basic cognitive and social cognition measures. Additionally, we administered an experimental task including moral dilemmas, with instrumental and incidental conditions. Patients’ performances were compared with a control group [healthy control (HC)], including 36 age-, gender-, and education-matched healthy subjects. Despite that the judgment pattern was comparable in ALS and HC, patients resulted less prone to carry out a moral transgression compared to HC. Additionally, ALS patients displayed higher levels of moral permissibility and lower emotional arousal, with similar levels of engagement in both instrumental and incidental conditions. Our findings expanded the current literature about cognitive deficits in ALS, showing that in judging moral actions, patients may present non-utilitarian choices and emotion flattening. Such a decision-making profile may have relevant implications in applying moral principles in real-life situations and for the judgment of end-of-life treatments and care in clinical settings
Characterization of Large Volume 3.5 x 8 inches LaBr3:Ce Detectors
The properties of large volume cylindrical 3.5 x 8 inches (89 mm x 203 mm)
LaBr3:Ce scintillation detectors coupled to the Hamamatsu R10233-100SEL
photo-multiplier tube were investigated. These crystals are among the largest
ones ever produced and still need to be fully characterized to determine how
these detectors can be utilized and in which applications. We tested the
detectors using monochromatic gamma-ray sources and in-beam reactions producing
gamma rays up to 22.6 MeV; we acquired PMT signal pulses and calculated
detector energy resolution and response linearity as a function of gamma-ray
energy. Two different voltage dividers were coupled to the Hamamatsu
R10233-100SEL PMT: the Hamamatsu E1198-26, based on straightforward resistive
network design, and the LABRVD, specifically designed for our large volume
LaBr3:Ce scintillation detectors, which also includes active semiconductor
devices. Because of the extremely high light yield of LaBr3:Ce crystals we
observed that, depending on the choice of PMT, voltage divider and applied
voltage, some significant deviation from the ideally proportional response of
the detector and some pulse shape deformation appear. In addition, crystal
non-homogeneities and PMT gain drifts affect the (measured) energy resolution
especially in case of high-energy gamma rays. We also measured the time
resolution of detectors with different sizes (from 1x1 inches up to 3.5x8
inches), correlating the results with both the intrinsic properties of PMTs and
GEANT simulations of the scintillation light collection process. The detector
absolute full energy efficiency was measured and simulated up to gamma-rays of
30 Me
Exploring functional regression for dynamic modeling of shallow landslides in South Tyrol, Italy
Shallow landslides are ubiquitous hazards in mountainous regions worldwide that arise from an interplay of static predisposing factors and dynamic preparatory and triggering conditions. Modeling shallow landslides at regional scales has leveraged data-driven approaches to separately investigate purely spatial landslide susceptibility and temporally varying conditions. Yet, the joint assessment of shallow landslides in space and time using data-driven methods remains challenging. Furthermore, dynamic factors have been typically included in data-driven landslide models as scalar predictors by employing aggregated descriptors over time (e.g., mean, maximum, or total precipitation over a defined time window), where many choices are possible for the considered time scales and aggregation operators. Therefore, incorporating the time-varying behavior of dynamic factors remains difficult.This study addresses these challenges by exploring Functional Generalized Additive Models (FGAMs) to predict the occurrence of shallow landslides in space and time within the Italian province of South Tyrol (7,400 km²). In contrast to conventional techniques, we test the benefits of using functional predictors to describe dynamic factors (e.g., precipitation and temperature) leading to landslide events. In other words, we evaluate dynamic factors as collections of measurements over time (i.e., time series). To do so, our approach uses a binomial FGAM to analyze the statistical associations between the static factors (scalar predictors), the dynamic weather conditions prior to a potential landslide occurrence (functional predictors), and the occurrence of shallow landslides in space and time.Potential outcomes of this novel approach show an overview of the added value of using functional predictors for space and time shallow landslide modeling. These research findings are positioned within the context of the PROSLIDE project, which has received financial support from the Research Südtirol/Alto Adige 2019 research program of the Autonomous Province of Bozen/Bolzano – Südtirol/Alto Adige
Neurofunctional Correlates of Ethical, Food-Related Decision-Making
Citation: Cherry, J. B. C., Bruce, J. M., Lusk, J. L., Crespi, J. M., Lim, S. L., & Bruce, A. S. (2015). Neurofunctional Correlates of Ethical, Food-Related Decision-Making. Plos One, 10(4), 16. doi:10.1371/journal.pone.0120541For consumers today, the perceived ethicality of a food's production method can be as important a purchasing consideration as its price. Still, few studies have examined how, neurofunctionally, consumers are making ethical, food-related decisions. We examined how consumers' ethical concern about a food's production method may relate to how, neurofunctionally, they make decisions whether to purchase that food. Forty-six participants completed a measure of the extent to which they took ethical concern into consideration when making food-related decisions. They then underwent a series of functional magnetic resonance imaging (fMRI) scans while performing a food-related decision-making (FRDM) task. During this task, they made 56 decisions whether to purchase a food based on either its price (i.e., high or low, the "price condition") or production method (i.e., with or without the use of cages, the "production method condition"), but not both. For 23 randomly selected participants, we performed an exploratory, whole-brain correlation between ethical concern and differential neurofunctional activity in the price and production method conditions. Ethical concern correlated negatively and significantly with differential neurofunctional activity in the left dorsolateral prefrontal cortex (dlPFC). For the remaining 23 participants, we performed a confirmatory, region-of-interest (ROI) correlation between the same variables, using an 8-mm3 volume situated in the left dlPFC. Again, the variables correlated negatively and significantly. This suggests, when making ethical, food-related decisions, the more consumers take ethical concern into consideration, the less they may rely on neurofunctional activity in the left dlPFC, possibly because making these decisions is more routine for them, and therefore a more perfunctory process requiring fewer cognitive resources
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