Abstract
DUNE is a cutting-edge experiment aiming to study neutrinos in detail, with a special focus on the flavor oscillation mechanism. The prototype of the DUNE Far Detector Single Phase TPC ...(ProtoDUNE-SP) was built and operated at CERN with a full set of reconstruction tools. To implement these reconstruction tools, Pandora, a multi-algorithm framework, has been developed. A large number of these algorithms, some of them being exploiting traditional clustering, detector physics and deep learning approaches, have been applied to images to gradually build up a picture out of singular events. One of such algorithms is the Pandora slicing algorithm which aims to partition the detector hits of an event in sets called slices. Each slice represents a single interaction in the detector and should identify all the hits related to the interacting particle and its subsequent decay products. We expect the order of tens of slices per event in ProtoDUNE-SP. In this paper we present a deep learning approach to the problem, designing a model able to outperform the state-of-the-art slicing algorithm which is currently implemented within Pandora. We assess the performance of our tool in terms of efficiency and accuracy, while exploiting hardware accelerating setups. The ultimate goal is to incorporate this deep learning approach in the Pandora reconstruction tool.
Perivascular, subdural meningeal and choroid plexus macrophages are non-parenchymal macrophages that mediate immune responses at brain boundaries. Although the origin of parenchymal microglia has ...recently been elucidated, much less is known about the precursors, the underlying transcriptional program and the dynamics of the other macrophages in the central nervous system (CNS). It was assumed that they have a high turnover from blood-borne monocytes. However, using parabiosis and fate-mapping approaches in mice, we found that CNS macrophages arose from hematopoietic precursors during embryonic development and established stable populations, with the notable exception of choroid plexus macrophages, which had dual origins and a shorter life span. The generation of CNS macrophages relied on the transcription factor PU.1, whereas the MYB, BATF3 and NR4A1 transcription factors were not required.
Electronic and photonic fiber devices that can sustain large elastic deformation are becoming key components in a variety of fields ranging from healthcare to robotics and wearable devices. The ...fabrication of highly elastic and functional fibers remains however challenging, which is limiting their technological developments. Simple and scalable fiber‐processing techniques to continuously codraw different materials within a polymeric structure constitute an ideal platform to realize functional fibers and devices. Despite decades of research however, elastomeric materials with the proper rheological attributes for multimaterial fiber processing cannot be identified. Here, the thermal drawing of hundreds‐of‐meters long multimaterial optical and electronic fibers and devices that can sustain up to 500% elastic deformation is demonstrated. From a rheological and microstructure analysis, thermoplastic elastomers that can be thermally drawn at high viscosities (above 103 Pa s), allowing the encapsulation of a variety of microstructured, soft, and rigid materials are identified. Using this scalable approach, fiber devices combining high performance, extreme elasticity, and unprecedented functionalities, allowing novel applications in smart textiles, robotics, or medical implants, are demonstrated.
Superelastic multimaterial electronic and photonic fibers are fabricated via thermal drawing. Thermoplastic elastomers with the proper rheological properties to be codrawn with a variety of functional materials, including liquid metals and nanocomposites, are identified. This provides a novel approach for the scalable fabrication of advanced stretchable electronic and photonic devices with unprecedented functionalities.
Unambiguous detection of the tidal disruption of a star would allow an assessment of the presence and masses of supermassive black holes in quiescent galaxies. It would also provide invaluable ...information on bulge-scale stellar processes (such as two-body relaxation) via the rate at which stars are injected into the tidal sphere of influence of the black holes. This rate, in turn, is essential to predict gravitational radiation emission by compact object inspirals. The signature of a tidal disruption event is thought to be a fallback rate for the stellar debris on to the black hole that decreases as t
−5/3. This mass flux is often assumed to yield a luminous signal that decreases in time at the same rate. In this paper, we calculate the monochromatic light curves arising from such an accretion event. Differently from previous studies, we adopt a more realistic description of the fallback rate and of the super-Eddington accretion physics. We also provide simultaneous light curves in optical, ultraviolet (UV) and X-rays. We show that, after a few months, optical and UV light curves scale as t
−5/12, and are thus substantially flatter than the t
−5/3 behaviour, which is a prerogative of the bolometric light curve, only. At earlier times and for black hole masses <107 M⊙, the wind emission dominates: after reaching a peak of 1041-1043 erg s−1 at roughly a month, the light curve decreases steeply as ∼t
−2.6, until the disc contribution takes over. The X-ray band, instead, is the best place to detect the t
−5/3'smoking gun' behaviour, although it is displayed only for roughly a year, before the emission steepens exponentially.
Development of wearable sensing platforms is essential for the advancement of continuous health monitoring and point-of-care testing. Eccrine sweat pH is an analyte that can be noninvasively measured ...and used to diagnose and aid in monitoring a wide range of physiological conditions. Surface-enhanced Raman scattering (SERS) offers a rapid, optical technique for fingerprinting of biomarkers present in sweat. In this paper, a mechanically flexible, nanofibrous, SERS-active substrate was fabricated by a combination of electrospinning of thermoplastic polyurethane (TPU) and Au sputter coating. This substrate was then investigated for suitability toward wearable sweat pH sensing after functionalization with two commonly used pH-responsive molecules, 4-mercaptobenzoic acid (4-MBA), and 4-mercaptopyridine (4-MPy). The developed SERS pH sensor was found to have good resolution (0.14 pH units for 4-MBA; 0.51 pH units for 4-MPy), with only 1 μL of sweat required for a measurement, and displayed no statistically significant difference in performance after 35 days (p = 0.361). Additionally, the Au/TPU nanofibrous SERS pH sensors showed fast sweat-absorbing ability as well as good repeatability and reversibility. The proposed methodology offers a facile route for the fabrication of SERS substrates which could also be used to measure a wide range of health biomarkers beyond sweat pH.
Magnetic excitations in infinite-layer nickelates Lu, H.; Rossi, M.; Nag, A. ...
Science (American Association for the Advancement of Science),
07/2021, Letnik:
373, Številka:
6551
Journal Article
Recenzirano
Odprti dostop
Looking for magnetic clues
Thin films of the neodymium nickelate NdNiO
2
doped with strontium have recently been found to be superconducting. This materials class bears structural and electronic ...similarities to the famed cuprate superconductors, but how far the analogy goes remains unclear. Lu
et al.
used resonant inelastic x-ray scattering to look for magnetism, which exists in the cuprates, in Nd
1-x
Sr
x
NiO
2
films (see the Perspective by Benckiser). The authors observed magnetic modes in the undoped compound that had a doping evolution consistent with the behavior of a doped Mott insulator.
Science
, abd7726, this issue p.
213
; see also abi6855, p.
157
Resonant inelastic x-ray scattering is used to probe the magnetic excitations in Nd
1−
x
Sr
x
NiO
2
films.
The discovery of superconductivity in infinite-layer nickelates brings us tantalizingly close to a material class that mirrors the cuprate superconductors. We measured the magnetic excitations in these nickelates using resonant inelastic x-ray scattering at the Ni
L
3
-edge. Undoped NdNiO
2
possesses a branch of dispersive excitations with a bandwidth of approximately 200 milli–electron volts, which is reminiscent of the spin wave of strongly coupled, antiferromagnetically aligned spins on a square lattice. The substantial damping of these modes indicates the importance of coupling to rare-earth itinerant electrons. Upon doping, the spectral weight and energy decrease slightly, whereas the modes become overdamped. Our results highlight the role of Mottness in infinite-layer nickelates.
The search continues for nickel oxide-based materials with electronic properties similar to cuprate high-temperature superconductors
. The recent discovery of superconductivity in the doped ...infinite-layer nickelate NdNiO
(refs.
) has strengthened these efforts. Here, we use X-ray spectroscopy and density functional theory to show that the electronic structure of LaNiO
and NdNiO
, while similar to the cuprates, includes significant distinctions. Unlike cuprates, the rare-earth spacer layer in the infinite-layer nickelate supports a weakly interacting three-dimensional 5d metallic state, which hybridizes with a quasi-two-dimensional, strongly correlated state with Formula: see text symmetry in the NiO
layers. Thus, the infinite-layer nickelate can be regarded as a sibling of the rare-earth intermetallics
, which are well known for heavy fermion behaviour, where the NiO
correlated layers play an analogous role to the 4f states in rare-earth heavy fermion compounds. This Kondo- or Anderson-lattice-like 'oxide-intermetallic' replaces the Mott insulator as the reference state from which superconductivity emerges upon doping.
Quantum hypergraph states Rossi, M; Huber, M; Bruß, D ...
New journal of physics,
11/2013, Letnik:
15, Številka:
11
Journal Article
Recenzirano
Odprti dostop
We introduce a class of multiqubit quantum states which generalizes graph states. These states correspond to an underlying mathematical hypergraph, i.e. a graph where edges connecting more than two ...vertices are considered. We derive a generalized stabilizer formalism to describe this class of states. We introduce the notion of k-uniformity and show that this gives rise to classes of states which are inequivalent under the action of the local Pauli group. Finally we disclose a one-to-one correspondence with states employed in quantum algorithms, such as Deutsch-Jozsa's and Grover's.
Most forms of chemotherapy employ mechanisms involving induction of oxidative stress, a strategy that can be effective due to the elevated oxidative state commonly observed in cancer cells. However, ...recent studies have shown that relative redox levels in primary tumors can be heterogeneous, suggesting that regimens dependent on differential oxidative state may not be uniformly effective. To investigate this issue in hematological malignancies, we evaluated mechanisms controlling oxidative state in primary specimens derived from acute myelogenous leukemia (AML) patients. Our studies demonstrate three striking findings. First, the majority of functionally defined leukemia stem cells (LSCs) are characterized by relatively low levels of reactive oxygen species (termed “ROS-low”). Second, ROS-low LSCs aberrantly overexpress BCL-2. Third, BCL-2 inhibition reduced oxidative phosphorylation and selectively eradicated quiescent LSCs. Based on these findings, we propose a model wherein the unique physiology of ROS-low LSCs provides an opportunity for selective targeting via disruption of BCL-2-dependent oxidative phosphorylation.
► LSC are prospectively isolated from the bulk tumor on the basis of low ROS levels ► Metabolic dependencies discriminating LSCs, bulk tumor, and normal HSCs are described ► BCL-2 is identified as a regulator of LSC mitochondrial respiration ► BCL-2 pharmacologic inhibitors demonstrate LSC-specific targeting
Human leukemia stem cells upregulate BCL-2 expression as a result of relying on oxidative phosphorylation to produce energy and can therefore be targeted with BCL-2 inhibitors.
Digital twins have advanced fast in various industries, but are just emerging in postharvest supply chains. A digital twin is a virtual representation of a certain product, such as fresh ...horticultural produce. This twin is linked to the real-world product by sensors supplying data of the environmental conditions near the target fruit or vegetable. Statistical and data-driven twins quantify how quality loss of fresh horticultural produce occurs by grasping patterns in the data. Physics-based twins provide an augmented insight into the underlying physical, biochemical, microbiological and physiological processes, enabling to explain also why this quality loss occurs.
We identify what the key advantages are of digital twins and how the supply chain of fresh horticultural produce can benefit from them in the future.
A digital twin has a huge potential to help horticultural produce to tell its history as it drifts along throughout its postharvest life. The reason is that each shipment is subject to a unique and unpredictable set of temperature and gas atmosphere conditions from farm to consumer. Digital twins help to identify the resulting, largely uncharted, postharvest evolution of food quality. The benefit of digital twins particularly comes forward for perishable species and at low airflow rates. Digital twins provide actionable data for exporters, retailers, and consumers, such as the remaining shelf life for each shipment, on which logistics decisions and marketing strategies can be based. The twins also help diagnose and predict potential problems in supply chains that will reduce food quality and induce food loss. Twins can even suggest preventive shipment-tailored measures to reduce retail and household food losses.
•We highlight differences between physics-based and data-driven digital twins.•Digital twins help tailor supply chains to maximize shelf life and reduce food losses.•Digital twins convert sensor data to predict postharvest evolution of food quality.•Digital twins provide actionable data for exporters, retailers and consumers.•Validation is essential to guarantee future trust in digital twins.
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