73 research outputs found

    Method for Implementing Optical Phase Adjustment

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    A method has been developed to mechanically implement the optical phase shift by adjusting the polarization of the pump and probe beams in an NMOR (nonlinear magneto-optical rotation) magnetometer as the proper phase shift is necessary to induce self-oscillation. This innovation consists of mounting the pump beam on a ring that surrounds the atomic vapor sample. The propagation of the probe beam is perpendicular to that of the pump beam. The probe beam can be considered as defining the axis of a cylinder, while the pump beam is directed radially. The magnetic field to be measured defines a third vector, but it is also taken to lie along the cylinder axis. Both the pump and probe beams are polarized such that their electric field vectors are substantially perpendicular to the magnet field. By rotation of the ring supporting the pump beam, its direction can be varied relative to the plane defined by the probe electric field and the magnetic field to be measured

    Nonlinear Faraday Rotation and Superposition-State Detection in Cold Atoms

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    We report on the first observation of nonlinear Faraday rotation with cold atoms at a temperature of ~100 uK. The observed nonlinear rotation of the light polarization plane is up to 0.1 rad over the 1 mm size atomic cloud in approximately 10 mG magnetic field. The nonlinearity of rotation results from long-lived coherence of ground-state Zeeman sublevels created by a near-resonant light. The method allows for creation, detection and control of atomic superposition states. It also allows applications for precision magnetometry with high spatial and temporal resolution.Comment: 5 pages, 6 figure

    Search for plant biomagnetism with a sensitive atomic magnetometer

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    We report what we believe is the first experimental limit placed on plant biomagnetism. Measurements with a sensitive atomic magnetometer were performed on the Titan arum (Amorphophallus titanum) inflorescence, known for its fast bio-chemical processes while blooming. We find that the surface magnetic field from these processes, projected along the Earth's magnetic field, and measured at the surface of the plant, is less then ~0.6uG.Comment: 5 pages, 5 figures, to be published - modified one sentence in abstract + reformatted fi

    The relation between dynamics and star formation in barred galaxies

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    We analyze optical and near-infrared data of a sample of 11 barred spiral galaxies, in order to establish a connection between star formation and bar/spiral dynamics. We find that 22 regions located in the bars, and 20 regions in the spiral arms beyond the end of the bar present azimuthal color/age gradients that may be attributed to star formation triggering. Assuming a circular motion dynamic model, we compare the observed age gradient candidates with stellar populations synthesis models. A link can then be established with the disk dynamics that allows us to obtain parameters like the pattern speed of the bar or spiral, as well as the positions of resonance radii. We subsequently compare the derived pattern speeds with those expected from theoretical and observational results in the literature (e.g., bars ending near corotation). We find a tendency to overestimate bar pattern speeds derived from color gradients in the bar at small radii, away from corotation; this trend can be attributed to non-circular motions of the young stars born in the bar region. In spiral regions, we find that ~ 50% of the color gradient candidates are "inverse", i.e., with the direction of stellar aging contrary to that of rotation. The other half of the gradients found in spiral arms have stellar ages that increase in the same sense as rotation. Of the 9 objects with gradients in both bars and spirals, six (67%) appear to have a bar and a spiral with similar Omega_p, while three (33%) do not.Comment: Accepted for publication in Ap

    Detection of the A189G mtDNA heteroplasmic mutation in relation to age in modern and ancient bones.

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    International audienceThe aim of this study was to demonstrate the presence of the A189G age-related point mutation on DNA extracted from bone. For this, a peptide nucleic acid (PNA)/DNA sequencing method which can determine an age threshold for the appearance of the mutation was used. Initially, work was done in muscle tissue in order to evaluate the sensitivity of the technique and afterwards in bone samples from the same individuals. This method was also applied to ancient bones from six well-preserved skeletal remains. The mutation was invariably found in muscle, and at a rate of up to 20% in individuals over 60 years old. In modern bones, the mutation was detected in individuals aged 38 years old or more, at a rate of up to 1%, but its occurrence was not systematic (only four out of ten of the individuals over 50 years old carried the heteroplasmy). For ancient bones, the mutation was also found in the oldest individuals according to osteologic markers. The study of this type of age-related mutation and a more complete understanding of its manifestation has potentially useful applications. Combined with traditional age markers, it could improve identification accuracy in forensic cases or in anthropological studies of ancient populations

    Serum CA 19-9 as a Marker of Resectability and Survival in Patients with Potentially Resectable Pancreatic Cancer Treated with Neoadjuvant Chemoradiation

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    Purpose The role of carbohydrate antigen (CA) 19-9 in the evaluation of patients with resectable pancreatic cancer treated with neoadjuvant therapy prior to planned surgical resection is unknown. We evaluated CA 19-9 as a marker of therapeutic response, completion of therapy, and survival in patients enrolled on two recently reported clinical trials. Patients and Methods We analyzed patients with radiographically resectable adenocarcinoma of the head/uncinate process treated on two phase II trials of neoadjuvant chemoradiation. Patients without evidence of disease progression following chemoradiation underwent pancreaticoduodenectomy (PD). CA 19-9 was evaluated in patients with a normal bilirubin level. Results We enrolled 174 patients, and 119 (68%) completed all therapy including PD. Pretreatment CA 19-9 <37 U/ml had a positive predictive value (PPV) for completing PD of 86% but a negative predictive value (NPV) of 33%. Among patients without evidence of disease at last follow-up, the highest pretreatment CA 19-9 was 1,125 U/ml. Restaging CA 19-9 <61 U/ml had a PPV of 93% and a NPV of 28% for completing PD among resectable patients. The area under the receiver-operating characteristics curve of pretreatment and restaging CA 19-9 levels for completing PD was 0.59 and 0.74, respectively. We identified no association between change in CA 19-9 and histopathologic response (P = 0.74). Conclusions Although the PPV of CA 19-9 for completing neoadjuvant therapy and undergoing PD was high, its clinical utility was compromised by a low NPV. Decision-making for patients with resectable PC should remain based on clinical assessment and radiographic staging.PublishedN/

    Deep anomaly detection in horizontal axis wind turbines using Graph Convolutional Autoencoders for Multivariate Time series

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    Wind power is one of the fastest-growing renewable energy sectors instrumental in the ongoing decarbonization process. However, wind turbines are subjected to a wide range of dynamic loads which can cause more frequent failures and downtime periods, leading to ever-increasing attention to effective Condition Monitoring strategies. In this paper, we propose a novel unsupervised deep anomaly detection framework to detect anomalies in wind turbines based on SCADA data. We introduce a promising neural architecture, namely a Graph Convolutional Autoencoder for Multivariate Time series, to model the sensor network as a dynamical functional graph. This structure improves the unsupervised learning capabilities of Autoencoders by considering individual sensor measurements together with the nonlinear correlations existing among signals. On this basis, we developed a deep anomaly detection framework that was validated on 12 failure events occurred during 20 months of operation of four wind turbines. The results show that the proposed framework successfully detects anomalies and anticipates SCADA alarms by outperforming other two recent neural approaches
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