114 research outputs found
Dynamical Casimir Effect in Quantum Information Processing
We demonstrate, in the regime of ultrastrong matter-field coupling, the
strong connection between the dynamical Casimir effect (DCE) and the
performance of quantum information protocols. Our results are illustrated by
means of a realistic quantum communication channel and show that the DCE is a
fundamental limit for quantum computation and communication and that novel
schemes are required to implement ultrafast and reliable quantum gates.
Strategies to partially counteract the DCE are also discussed.Comment: 7 pages, 5 figure
DESIGN OF A LAMBDA CONFIGURATION IN ARTIFICIAL COHERENT NANOSTRUCTURES
The implementation of a three-level Lambda System in artificial atoms would allow to perform advanced control tasks typical of quantum optics in the solid state realm, with photons in the mu m/mm range. However hardware constraints put an obstacle since protection from decoherence is often conflicting with efficient coupling to external fields. We address the problem of performing conventional STImulated Raman Adiabatic Passage (STIRAP) in the presence of low-frequency noise. We propose two strategies to defeat decoherence, based on "optimal symmetry breaking" and dynamical decoupling. We suggest how to apply to the different implementations of superconducting artificial atoms, stressing the key role of non-Markovianity
A METABOLIC-LIKE CYCLE FOR SYNTHETIC APPLICATIONS
Systems Biocatalysis is a new approach consisting of organizing enzymes in vitro to generate an artificial metabolism for synthetic purposes. The interconversion of functional groups is the main objective of biocatalysis, and systems organizing a series of enzymes to achieve a multi-step reaction have been reported. The assembly of essentially the same enzymes utilized in Nature to drive the transformation of carbohydrates towards useful synthetic intermediates [1] has been referred to as an artificial metabolism. SysBiocat aims at a similar goal addressing the generalization and organization of group of enzymes (a tool-box) able to perform a series of reactions of general synthetic utility where the feasibility is connected with the obtainment of enzymes of wide substrate specificity or in a rich array of variable common catalytic functions. [2] As a demonstration of this concept, we have recently assembled a biochemical like cycle (Asp-cycle) connecting among them an unsaturated carboxylate (fumaric acid), an alpha-amino acid (L-aspartic acid), a keto acid (oxalacetic acid) and the corresponding alpha-hydroxyacid (D- or L-malic acid). [3]
In this view, the obtained cycle may be exploited by coupling it with synthetically relevant reactions which are driven to completion thanks to one or more irreversible steps in the reaction sequence.
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[1] W.D. Fessner, C. Walter, “Artificial metabolism”, Angew Chem Int Ed, 1992, 31, p. 614
[2] U. T. Bornscheuer, G. W. Huisman, R. J. Kazlauskas, S. Lutz, J. C. Moore, K. Robins, “Engineering The Third Wave Of Biocatalysis”, Nature, 2012, 485, p. 185
[3] D. Tessaro, L. Pollegioni, L. Piubelli, P. D’Arrigo, S. Servi, “Systems Biocatalysis: An Artificial Metabolism for Interconversion of Functional Groups”, ACS Catalysis, 2015, 5, p. 160
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection
Anomalies are rare and anomaly detection is often therefore framed as
One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC
techniques constrain the latent representations of normal motions to limited
volumes and detect as abnormal anything outside, which accounts satisfactorily
for the openset'ness of anomalies. But normalcy shares the same openset'ness
property, since humans can perform the same action in several ways, which the
leading techniques neglect. We propose a novel generative model for video
anomaly detection (VAD), which assumes that both normality and abnormality are
multimodal. We consider skeletal representations and leverage state-of-the-art
diffusion probabilistic models to generate multimodal future human poses. We
contribute a novel conditioning on the past motion of people, and exploit the
improved mode coverage capabilities of diffusion processes to generate
different-but-plausible future motions. Upon the statistical aggregation of
future modes, anomaly is detected when the generated set of motions is not
pertinent to the actual future. We validate our model on 4 established
benchmarks: UBnormal, HR-UBnormal, HR-STC, and HR-Avenue, with extensive
experiments surpassing state-of-the-art results.Comment: Accepted at ICCV202
Contracting Skeletal Kinematic Embeddings for Anomaly Detection
Detecting the anomaly of human behavior is paramount to timely recognizing
endangering situations, such as street fights or elderly falls. However,
anomaly detection is complex, since anomalous events are rare and because it is
an open set recognition task, i.e., what is anomalous at inference has not been
observed at training. We propose COSKAD, a novel model which encodes skeletal
human motion by an efficient graph convolutional network and learns to COntract
SKeletal kinematic embeddings onto a latent hypersphere of minimum volume for
Anomaly Detection. We propose and analyze three latent space designs for
COSKAD: the commonly-adopted Euclidean, and the new spherical-radial and
hyperbolic volumes. All three variants outperform the state-of-the-art,
including video-based techniques, on the ShangaiTechCampus, the Avenue, and on
the most recent UBnormal dataset, for which we contribute novel skeleton
annotations and the selection of human-related videos. The source code and
dataset will be released upon acceptance.Comment: Submitted to Patter Recognition Journa
Repetition Versus Noiseless Quantum Codes For Correlated Errors
We study the performance of simple quantum error correcting codes with
respect to correlated noise errors characterized by a finite correlation
strength. Specifically, we consider bit flip (phase flip) noisy quantum memory
channels and use repetition and noiseless quantum codes. We characterize the
performance of the codes by means of the entanglement fidelity as function of
the error probability and degree of memory. Finally, comparing the entanglement
fidelities of repetition and noiseless quantum codes, we find a threshold for
the correlation strength that allows to select the code with better
performance.Comment: few changes, 14 page
Expanding the natural history of CASK-related disorders to the prenatal period
Aim To assess whether microcephaly with pontine and cerebellar hypoplasia (MICPCH) could manifest in the prenatal period in patients with calcium/calmodulin-dependent serine protein kinase (CASK) gene disorders. Method In this international multicentre retrospective study, we contacted a CASK parents' social media group and colleagues with expertise in cerebellar malformations and asked them to supply clinical and imaging information. Centiles and standard deviations (SD) were calculated according to age by nomograms. Results The study consisted of 49 patients (44 females and 5 males). Information regarding prenatal head circumference was available in 19 patients; 11 out of 19 had a fetal head circumference below -2SD (range -4.1SD to -2.02SD, mean gestational age at diagnosis 20 weeks). Progressive prenatal deceleration of head circumference growth rate was observed in 15 out of 19. At birth, 20 out of 42 had a head circumference below -2SD. A total of 6 out of 15 fetuses had a TCD z-score below -2 (range -5.88 to -2.02). Interpretation This study expands the natural history of CASK-related disorders to the prenatal period, showing evidence of progressive deceleration of head circumference growth rate, head circumference below -2SD, or small TCD. Most cases will not be diagnosed according to current recommendations for fetal central nervous system routine assessment. Consecutive measurements and genetic studies are advised in the presence of progressive deceleration of head circumference growth rates or small TCD
Case report: A novel pathogenic FRMD7 variant in a Turner syndrome patient with familial idiopathic infantile nystagmus
Infantile idiopathic nystagmus (IIN) is an oculomotor disorder characterized by involuntary bilateral, periodic ocular oscillations, predominantly on the horizontal axis. X-linked IIN (XLIIN) is the most common form of congenital nystagmus, and the FERM domain-containing gene (FRMD7) is the most common cause of pathogenesis, followed by mutations in GPR143. To date, more than 60 pathogenic FRMD7 variants have been identified, and the physiopathological pathways leading to the disease are not yet completely understood. FRMD7-associated nystagmus usually affects male patients, while it shows incomplete penetrance in female patients, who are mostly asymptomatic but sometimes present with mild ocular oscillations or, occasionally, with clear nystagmus. Here we report the first case of a patient with Turner syndrome and INN in an XLIIN pedigree, in which we identified a novel frameshift mutation (c.1492dupT) in the FRMD7 gene: the absence of one X chromosome in the patient unmasked the presence of the familial genetic nystagmus
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