scholarly journals Five new real-time detections of fast radio bursts with UTMOST

2019 ◽  
Vol 488 (3) ◽  
pp. 2989-3002 ◽  
Author(s):  
W Farah ◽  
C Flynn ◽  
M Bailes ◽  
A Jameson ◽  
T Bateman ◽  
...  
Keyword(s):  
Real Time ◽  
Detection System ◽  
Temporal Structure ◽  
High Time Resolution ◽  
Fast Radio Burst ◽  
Scattering Time ◽  
Turn Over ◽  
Temporal Broadening ◽  
Very High

Abstract We detail a new fast radio burst (FRB) survey with the Molonglo Radio Telescope, in which six FRBs were detected between 2017 June and 2018 December. By using a real-time FRB detection system, we captured raw voltages for five of the six events, which allowed for coherent dedispersion and very high time resolution (10.24 $\mu$s) studies of the bursts. Five of the FRBs show temporal broadening consistent with interstellar and/or intergalactic scattering, with scattering time-scales ranging from 0.16 to 29.1 ms. One burst, FRB181017, shows remarkable temporal structure, with three peaks each separated by 1 ms. We searched for phase-coherence between the leading and trailing peaks and found none, ruling out lensing scenarios. Based on this survey, we calculate an all-sky rate at 843 MHz of $98^{+59}_{-39}$ events sky−1 d−1 to a fluence limit of 8 Jy ms: a factor of 7 below the rates estimated from the Parkes and ASKAP telescopes at 1.4 GHz assuming the ASKAP-derived spectral index α = −1.6 (Fν ∝ να). Our results suggest that FRB spectra may turn over below 1 GHz. Optical, radio, and X-ray follow-up has been made for most of the reported bursts, with no associated transients found. No repeat bursts were found in the survey.

scholarly journals Usefulness of real-time PCR in long-term follow-up of follicular lymphoma patients.

2007 ◽  
Vol 54 (1) ◽  
pp. 135-142 ◽  
Author(s):  
Andrzej Tysarowski ◽  
Anna Fabisiewicz ◽  
Ewa Paszkiewicz-Kozik ◽  
Jadwiga Kulik ◽  
Jan Walewski ◽  
...  
Keyword(s):  
Follicular Lymphoma ◽  
Real Time ◽  
Real Time Pcr ◽  
Residual Disease ◽  
Fusion Gene ◽  
Detection System ◽  
Breakpoint Region ◽  
Long Term Follow Up

The aim of this study was to evaluate the usefulness of quantitative real-time PCR (RQ-PCR) for the monitoring of molecular remission in follicular lymphoma (FL) patients during long-term follow-up. RQ-PCR by the use of TaqMan detection system is a sensitive tool to monitor minimal residual disease (MRD) in FL through amplification of the t(14;18) fusion gene during and post-therapy. In most cases the breakpoint region occurs within the major breakpoint region (MBR). Among 75 patients diagnosed with FL, cells harboring the fusion gene BCL2/JH were found in peripheral blood of 31 patients (41%). We further monitored 30 of these patients in a period varying from 6 months to 5 years by RQ-PCR. In our study the level indicating the possibility of the presence of MRD was established at more than five t(14;18)-positive cells in the background of 83,000 normal cells. The results of this work also confirmed that the presence of MRD detected by RQ-PCR is an indication for careful observation of patients because of a higher risk of disease recurrence.

scholarly journals A real-time fast radio burst: polarization detection and multiwavelength follow-up

2014 ◽  
Vol 447 (1) ◽  
pp. 246-255 ◽  
Author(s):  
E. Petroff ◽  
M. Bailes ◽  
E. D. Barr ◽  
B. R. Barsdell ◽  
N. D. R. Bhat ◽  
...  
Keyword(s):  
Real Time ◽  
Radio Burst ◽  
Fast Radio Burst ◽  
Polarization Detection

67-LB: Clinical Cost Offset Analysis Comparing Real-Time CGM (RTCGM) with SMBG Based on the COMISAIR 3-Year Follow-Up Study

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 67-LB
Author(s):  
JAN SOUPAL ◽  
JOHN J. ISITT ◽  
GEORGE GRUNBERGER ◽  
MARTIN PRAZNY ◽  
CHRISTOPHER PARKIN ◽  
...  
Keyword(s):  
Real Time ◽  
Follow Up Study ◽  
Cost Offset

EVALUASI KESESUAIAN PELAKSANAAN PROBITY AUDIT PADA BPKP PUSAT DENGAN PEDOMAN PROBITY AUDIT PENGADAAN BARANG/JASA PEMERINTAH

INFO ARTHA ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 17-34
Author(s):  
Fadlil Usman
Keyword(s):  
Public Sector ◽  
Real Time ◽  
Procurement Process ◽  
Assessment Activity

Probity audit is an independence assessment activity to ensure the goods/services procurement processes have been implemented consistently appropriate with the principle of upholding integrity, uprightness, honesty and fulfill certain occur legislation aimed for improving the accountability for the use of public sector fund. Probity audit is done in real time simultaneously with the goods/services procurement process. This study aims to evaluate the suitability of the implementation of probity audit conducted by BPKP Headquarter as agency that initiated the implementation of probity audit in Indonesia compared with the Probity audit Guidelines for Procurement of Goods/Services as criteria. The results of this study indicate that the implementation of probity audit conducted by BPKP Headquarter has been implemented adequately, but there are activities that do not fit the criteria, especially in the activities of the determination of the scope of the audit, the preparation of working papers and the follow-up monitoring of the audit results. Probity audit merupakan kegiatan penilaian (independen) untuk memastikan bahwa proses pengadaan barang/jasa telah dilaksanakan secara konsisten sesuai dengan prinsip penegakan integritas, kebenaran, kejujuran dan memenuhi ketentuan perundangan yang berlaku yang bertujuan meningkatkan akuntabilitas penggunaan dana sektor publik. Probity audit dilakukan secara real time yaitu bersamaan dengan pelaksanaan pengadaan barang/jasa. Penelitian ini bertujuan untuk melakukan evaluasi kesesuaian pelaksanaan probity audit yang dilakukan oleh BPKP Pusat selaku instansi yang menginisiasi pelaksanaan probity audit di Indonesia dibandingkan dengan kriteria berupa Pedoman Probity audit Pengadaan Barang/Jasa Pemerintah. Hasil dari penelitian ini menunjukkan bahwa pelaksanaan probity audit yang dilakukan oleh BPKP Pusat sudah dilaksanakan secara memadai, namun masih terdapat hal yang belum sesuai dengan kriteria terutama dalam kegiatan penentuan ruang lingkup audit, penyusunan kertas kerja dan pemantauan terhadap tindak lanjut hasil audit.

Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks

2020 ◽  
Vol 16 (5) ◽  
pp. 584-591 ◽  
Author(s):  
Muhammad Hanif Ahmad Nizar ◽  
Chow Khuen Chan ◽  
Azira Khalil ◽  
Ahmad Khairuddin Mohamed Yusof ◽  
Khin Wee Lai
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Heart Disease ◽  
Aortic Valve ◽  
Real Time ◽  
Convolutional Neural Networks ◽  
Valvular Heart Disease ◽  
Detection System ◽  
Processing Unit ◽  
Real Time Detection

Background: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular heart disease. However, the images from echocardiogram are poor in comparison to Computerized Tomography and Magnetic Resonance Imaging scan. This study proposes the development of Convolutional Neural Networks (CNN) that can function optimally during a live echocardiographic examination for detection of the aortic valve. An automated detection system in an echocardiogram will improve the accuracy of medical diagnosis and can provide further medical analysis from the resulting detection. Methods: Two detection architectures, Single Shot Multibox Detector (SSD) and Faster Regional based Convolutional Neural Network (R-CNN) with various feature extractors were trained on echocardiography images from 33 patients. Thereafter, the models were tested on 10 echocardiography videos. Results: Faster R-CNN Inception v2 had shown the highest accuracy (98.6%) followed closely by SSD Mobilenet v2. In terms of speed, SSD Mobilenet v2 resulted in a loss of 46.81% in framesper- second (fps) during real-time detection but managed to perform better than the other neural network models. Additionally, SSD Mobilenet v2 used the least amount of Graphic Processing Unit (GPU) but the Central Processing Unit (CPU) usage was relatively similar throughout all models. Conclusion: Our findings provide a foundation for implementing a convolutional detection system to echocardiography for medical purposes.

Neurological manifestation in severe hypothyroidism in pregnancy

2020 ◽  
Vol 13 (12) ◽  
pp. e238069
Author(s):  
Aparna Sharma ◽  
Nilofar Noor ◽  
Vatsla Dadhwal
Keyword(s):  
Peripheral Neuropathy ◽  
Facial Palsy ◽  
Caesarean Delivery ◽  
Thyroid Stimulating Hormone ◽  
Neurological Manifestations ◽  
Second Trimester ◽  
Pituitary Hyperplasia ◽  
Very High ◽  
In Pregnancy

Neurological manifestations of hypothyroidism include peripheral neuropathy and pituitary hyperplasia. However, these associations are rarely encountered during pregnancy. We report a case of a known hypothyroid with very high thyroid stimulating hormone (TSH) values (512 μIU/mL) in the second trimester. At 24 weeks she developed facial palsy and pituitary hyperplasia which responded to a combination of steroids and thyroxine. She had caesarean delivery at 35 weeks and 3 days gestation in view of pre-eclampsia with severe features and was discharged on oral antihypertensives and thyroxine. On follow-up at 5 months, TSH normalised and pituitary hyperplasia showed a greater than 50% reduction in size. To our knowledge, this is the first reported case of facial palsy and pituitary hyperplasia associated with hypothyroidism during pregnancy.

scholarly journals Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3635 ◽  
Author(s):  
Guoming Zhang ◽  
Xiaoyu Ji ◽  
Yanjie Li ◽  
Wenyuan Xu
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Real Time ◽  
Condition Monitoring ◽  
Resource Constraints ◽  
Detection System ◽  
Stable Operation ◽  
Detection Accuracy ◽  
Monitoring Method ◽  
Dsp Processors

As a critical component in the smart grid, the Distribution Terminal Unit (DTU) dynamically adjusts the running status of the entire smart grid based on the collected electrical parameters to ensure the safe and stable operation of the smart grid. However, as a real-time embedded device, DTU has not only resource constraints but also specific requirements on real-time performance, thus, the traditional anomaly detection method cannot be deployed. To detect the tamper of the program running on DTU, we proposed a power-based non-intrusive condition monitoring method that collects and analyzes the power consumption of DTU using power sensors and machine learning (ML) techniques, the feasibility of this approach is that the power consumption is closely related to the executing code in CPUs, that is when the execution code is tampered with, the power consumption changes accordingly. To validate this idea, we set up a testbed based on DTU and simulated four types of imperceptible attacks that change the code running in ARM and DSP processors, respectively. We generate representative features and select lightweight ML algorithms to detect these attacks. We finally implemented the detection system on the windows and ubuntu platform and validated its effectiveness. The results show that the detection accuracy is up to 99.98% in a non-intrusive and lightweight way.

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