980 research outputs found

    Novel neural-network architecture for continuous gravitational waves

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    The high computational cost of wide-parameter-space searches for continuous gravitational waves (CWs) significantly limits the achievable sensitivity. This challenge has motivated the exploration of alternative search methods, such as deep neural networks (DNNs). Previous attempts [1,2] to apply convolutional image-classification DNN architectures to all-sky and directed CW searches showed promise for short, one-day search durations, but proved ineffective for longer durations of around ten days. In this paper, we offer a hypothesis for this limitation and propose new design principles to overcome it. As a proof of concept, we show that our novel convolutional DNN architecture attains matched-filtering sensitivity for a targeted search (i.e., single sky-position and frequency) in Gaussian data from two detectors spanning ten days. We illustrate this performance for two different sky positions and five frequencies in the 20-1000 Hz range, spanning the spectrum from an "easy"to the "hardest"case. The corresponding sensitivity depths fall in the range of 82-86/ Hz. The same DNN architecture is trained for each case, taking between 4-32 hours to reach matched-filtering sensitivity. The detection probability of the trained DNNs as a function of signal amplitude varies consistently with that of matched filtering. Furthermore, the DNN statistic distributions can be approximately mapped to those of the F-statistic under a simple monotonic function

    Novel neural-network architecture for continuous gravitational waves

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    The high computational cost of wide-parameter-space searches for continuous gravitational waves (CWs) significantly limits the achievable sensitivity. This challenge has motivated the exploration of alternative search methods, such as deep neural networks (DNNs). Previous attempts to apply convolutional image-classification DNN architectures to all-sky and directed CW searches showed promise for short, one-day search durations, but proved ineffective for longer durations of around ten days. In this paper, we offer a hypothesis for this limitation and propose new design principles to overcome it. As a proof of concept, we show that our novel convolutional DNN architecture attains matched-filtering sensitivity for a targeted search (i.e., single sky-position and frequency) in Gaussian data from two detectors spanning ten days. We illustrate this performance for two different sky positions and five frequencies in the 201000Hz20 - 1000 \mathrm{Hz} range, spanning the spectrum from an ``easy'' to the ``hardest'' case. The corresponding sensitivity depths fall in the range of 8286/Hz82 - 86 / \sqrt{\mathrm{Hz}}. The same DNN architecture is trained for each case, taking between 4324 - 32 hours to reach matched-filtering sensitivity. The detection probability of the trained DNNs as a function of signal amplitude varies consistently with that of matched filtering. Furthermore, the DNN statistic distributions can be approximately mapped to those of the F\mathcal{F}-statistic under a simple monotonic function.Comment: 9 pages, 7 figure

    Sustainable Development and Best Management Practices in the Food Processing Industry

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    It is well known that sustainable development refers to meeting the needs and requirements of the present generation without compromising the ability of future generations to meet their own needs. This concept has become the core issues in the food processing industry as well. Food processing industry can be defined as the method and techniques used to transform raw ingredients into food for human consumption. The present paper is an attempt to study sustainable development that involves issues like organic farming, food safety and food quality. This paper highlights on the concept of green food system and the approach of good agricultural practices (GAP) which is a new concept that stresses on international quality standards, concerns and commitments about food production, food safety and security, environment sustainability of agriculture. Quality management is equally important in the food industry. Food processing is a capital intensive, water consuming and a polluting industry

    Rhizosphere dynamics of inoculated cyanobacteria and their growth-promoting role in rice crop

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    Nitrogen fixing cyanobacteria are the predominant flora in waterlogged paddy fields which contribute significantly towards nitrogen budgeting in these ecosystems. Their establishment and role in plant growth promotion and soil microbial activity is poorly known. Under greenhouse conditions, pots were inoculated with one of a set of twenty cyanobacterial strains isolated from the rhizosphere of diverse rice and wheat varieties. Several strains established in the soil and persisted up to the harvest stage in soil and roots, significantly enhancing soil microbial biomass carbon, available nitrogen, and related soil microbiological parameters, and increased grain yields and grain weight. This can help in selecting promising strains for developing carrier-based inoculants to promote the growth of crop and soil microflora, leading to enhanced soil fertility and crop yields

    INFLUENCE OF FIBRE VOLUME REINFORCEMENT IN DRILLING GFRP LAMINATES

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    This paper presents an investigation on the influence of fiber volume reinforcement on various aspects of machining. Drilling experiments were conducted to study the tool wear, surface finish, delamination factor and hole quality on GFRP composites. The work reports the variation of tool wear, surface roughness, hole quality, chip characteristics, delamination factor with the variation of fibre volume reinforcement. Results revealed that the increase in fiber percentage increased the tool wear, delamination factor, surface roughness value and decreased hole quality. Minimum surface roughness, tool wear and better hole quality was obtained for 30% fibre content composites. 70% Fibre content composites produced hazardous surface roughness. Pull out of fibres and fibril formation are significant in decreasing the hole quality and increased surface roughness. Increased tool – fibre interaction and thermal softening of the tool causes increased tool wear. In higher fibre content composites, extensive plasticity was absent consequently brittle ceramic fibres were fractured easily. Hence small segment type chips were obtained. The fibre pull out and fibrils present near the hole exit forms the remainder of the laminate causes increased damage zone near the hole exit. Hence high delamination factor was obtained

    Fulminant hepatitis in a tropical population: clinical course, cause, and early predictors of outcome

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    The profiles of patients with fulminant hepatic failure (FHF) from developing countries have not been reported earlier. The current study was conducted prospectively, at a single tertiary care center in India, to document the demographic and clinical characteristics, natural course, and causative profile of patients with FHF as well as to define simple prognostic markers in these patients. Four hundred twenty-three consecutive patients with FHF admitted from January 1987 to June 1993 were included in the study. Each patient's serum was tested for various hepatotropic viruses. Univariate Cox's regression for 28 variables, multivariate Cox's proportional hazard regression, stepwise logistic regression, and Kaplan-Meier survival analysis were done to identify independent predictors of outcome at admission. All patients presented with encephalopathy within 4 weeks of onset of symptoms. Hepatotropic viruses were the likely cause in most of these patients. Hepatitis A (HAV), hepatitis B (HBV), hepatitis D (HDV) viruses, and antitubercular drugs could be implicated as the cause of FHF in 1.7% (n = 7), 28% (n = 117), 3.8% (n = 16), and 4.5% (n = 19) patients, respectively. In the remaining 62% (n = 264) of patients the serological evidence of HAV, HBV, or HDV infection was lacking, and none of them had ingested hepatotoxins. FHF was presumed to be caused by non-A, non-B virus(es) infection. Sera of 50 patients from the latter group were tested for hepatitis E virus (HEV) RNA and HCV RNA. In 31 (62%), HEV could be implicated as the causative agent, and isolated HCV RNA could be detected in 7 (19%). Two hundred eighty eight (66%) patients died. Approximately 75% of those who died did so within 72 hours of hospitalisation. One quarter of the female patients with FHF were pregnant. Mortality among pregnant females, nonpregnant females, and male patients with FHF was similar (P > .1). Univariate analysis showed that age, size of the liver assessed by percussion, grade of coma, presence of clinical features of cerebral edema, presence of infection, serum bilirubin, and prothrombin time prolongation over controls at admission were related to survival (P < .01). The rapidity of onset of encephalopathy and cause of FHF did not influence the outcome. Cox's proportional hazard regression showed age ≥ 40 years, presence of cerebral edema, serum bilirubin ≥ 15 mg/dL, and prothrombin time prolongation of 25 seconds or more over controls were independent predictors of outcome. Ninety-three percent of the patients with three or more of the above prognostic markers died. The sensitivity, specificity, positive predictive value, and the negative predictive value of the presence of three or more of these prognostic factors for mortality was 93%, 80%, 86%, and 89.5%, respectively, with a diagnostic accuracy of 87.3%. We conclude that most of our patients with FHF might have been caused by hepatotropic viral infection, and non-A, non-B virus(es) seems to be the dominant hepatotropic viral infection among these patients. They presented with encephalopathy within 4 weeks of the onset of symptoms. Pregnancy, cause, and rapidity of onset of encephalopathy did not influence survival. The prognostic model developed in the current study is simple and can be performed at admission

    Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

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    Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70M>70 MM_\odot) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e0.30 < e \leq 0.3 at 0.330.33 Gpc3^{-3} yr1^{-1} at 90\% confidence level.Comment: 24 pages, 5 figure

    Open data from the third observing run of LIGO, Virgo, KAGRA and GEO

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    The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in April of 2019 and lasting six months, O3b starting in November of 2019 and lasting five months, and O3GK starting in April of 2020 and lasting 2 weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main dataset, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.Comment: 27 pages, 3 figure

    All-sky search for continuous gravitational waves from isolated neutron stars using Advanced LIGO and Advanced Virgo O3 data

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    We present results of an all-sky search for continuous gravitational waves which can be produced by spinning neutron stars with an asymmetry around their rotation axis, using data from the third observing run of the Advanced LIGO and Advanced Virgo detectors. Four different analysis methods are used to search in a gravitational-wave frequency band from 10 to 2048 Hz and a first frequency derivative from 108-10^{-8} to 10910^{-9} Hz/s. No statistically-significant periodic gravitational-wave signal is observed by any of the four searches. As a result, upper limits on the gravitational-wave strain amplitude h0h_0 are calculated. The best upper limits are obtained in the frequency range of 100 to 200 Hz and they are 1.1×1025{\sim}1.1\times10^{-25} at 95\% confidence-level. The minimum upper limit of 1.10×10251.10\times10^{-25} is achieved at a frequency 111.5 Hz. We also place constraints on the rates and abundances of nearby planetary- and asteroid-mass primordial black holes that could give rise to continuous gravitational-wave signals

    Search for gravitational waves from Scorpius X-1 with a hidden Markov model in O3 LIGO data

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