scholarly journals The Prompt Processing System and Data Quality Monitoring in the ProtoDUNE-SP Experiment

2019 ◽  
Vol 214 ◽  
pp. 01026
Author(s):  
Maxim Potekhin

The DUNE Collaboration is conducting an experimental program (named protoDUNE) which involves a beam test of two large-scale prototypes of the DUNE Far Detector at CERN operating in 2018-2019. The volume of data to be collected by the protoDUNE-SP (the single-phase detector) will amount to a few petabytes and the sustained rate of data sent to mass storage is in the range of a few hundred MB per second. After collection the data is committed to storage at CERN and transmitted to Fermi National Accelerator Laboratory in the US for processing, analysis and long-term preservation. The protoDUNE experiment requires substantial Data Quality Monitoring capabilities in order to ascertain the condition of the detector and its various subsystems. We present the design of the protoDUNE Prompt Processing System, its deployment at CERN and its performance during the data challenges and actual data taking.

2020 ◽  
Vol 245 ◽  
pp. 01007
Author(s):  
Maxim Potekhin

The DUNE Collaboration currently operates an experimental program based at CERN which includes a beam test and an extended cosmic ray run of two large-scale prototypes of the massive Liquid Argon Time Projection Chamber (LArTPC) for the DUNE Far Detector. The volume of data collected by the single-phase prototype (protoDUNE-SP) amounts to 3PB and the sustained rate of data sent to mass storage is O(100) MB/s. Data Quality Monitoring was implemented by directing a fraction of the data stream to the protoDUNE prompt processing system (p3s) which is optimized for continuous low-latency calculation of the vital detector metrics and various graphics including event displays. It served a crucial role throughout the life cycle of the experiment. We present our experience in leveraging the CERN computing environment and operating the system over an extended period of time, while adapting to evolving requirements and computing platform.


Urban Science ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 27
Author(s):  
Lahouari Bounoua ◽  
Kurtis Thome ◽  
Joseph Nigro

Urbanization is a complex land transformation not explicitly resolved within large-scale climate models. Long-term timeseries of high-resolution satellite data are essential to characterize urbanization within land surface models and to assess its contribution to surface temperature changes. The potential for additional surface warming from urbanization-induced land use change is investigated and decoupled from that due to change in climate over the continental US using a decadal timescale. We show that, aggregated over the US, the summer mean urban-induced surface temperature increased by 0.15 °C, with a warming of 0.24 °C in cities built in vegetated areas and a cooling of 0.25 °C in cities built in non-vegetated arid areas. This temperature change is comparable in magnitude to the 0.13 °C/decade global warming trend observed over the last 50 years caused by increased CO2. We also show that the effect of urban-induced change on surface temperature is felt above and beyond that of the CO2 effect. Our results suggest that climate mitigation policies must consider urbanization feedback to put a limit on the worldwide mean temperature increase.


Subject Asteroid mining. Significance The US firm Planetary Resources in April completed successful tests in orbit of technology it plans to use to prospect for natural resources on asteroids from 2020. Separately, the China Academy of Launch Vehicle Technology late last year announced long-term plans for large-scale asteroid mining. Meanwhile, US legislators have begun laying the legal foundations for a space mining industry. Significant technological challenges remain, but key technologies have already been demonstrated, making the industry a serious prospect. Impacts An investment bubble could follow dramatic early successes or technological breakthroughs. There may be international tension over ownership or priority of access unless new international legal frameworks are agreed in advance. Asteroid mining will not be a viable solution to terrestrial resource depletion for the foreseeable future.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Grady Ball ◽  
Peter Regier ◽  
Ricardo González-Pinzón ◽  
Justin Reale ◽  
David Van Horn

AbstractWildfires are increasing globally in frequency, severity, and extent, but their impact on fluvial networks, and the resources they provide, remains unclear. We combine remote sensing of burn perimeter and severity, in-situ water quality monitoring, and longitudinal modeling to create the first large-scale, long-term estimates of stream+river length impacted by wildfire for the western US. We find that wildfires directly impact ~6% of the total stream+river length between 1984 and 2014, increasing at a rate of 342 km/year. When longitudinal propagation of water quality impacts is included, we estimate that wildfires affect ~11% of the total stream+river length. Our results indicate that wildfire activity is one of the largest drivers of aquatic impairment, though it is not routinely reported by regulatory agencies, as wildfire impacts on fluvial networks remain unconstrained. We identify key actions to address this knowledge gap and better understand the growing threat to fluvial networks, water security, and public health risks.


Author(s):  
D.Saravanan , Et. al.

This article looks at how artificial intelligence can help expect the hourly consolidation of air toxinSulphur ozone, element matter (PM2.5), and Sulphur dioxide. As one of the most excellently procedures, AI can efficiently prepare a model on a large amount of data by using large-scale streamlining computations. Even thoughseveral works use AI to predict air quality, most of the earlier studies are limited to long-term data and easilyinstruct regular relapse designs (direct or nonlinear) to expect the hourly air pollution focus. This paper suggestsadvanced analysis to simulate the hourly environmental change focus based on previous days' weather-related data by calculating the expectation for more than 24 hours as an execute multiple tasks learning (MTL) issue. This allows us to choose a suitable model with a variety of regularization strategies. We suggest a useful regularization that maintains the assumption patterns of concurrent hours to be nearby to each other, and we evaluate it to a few common MTL expect completion such as normal Frobenius standard regularization, normal atomicregularization, and '2,1-standard regularization. Our tests revealed that the suggested boundary declining concepts and constant hour-related regularizations outperform open product relapse models and regularizations in terms of execution.


2022 ◽  
Vol 8 ◽  
Author(s):  
Piero L. F. Mazzini ◽  
Cassia Pianca

Prolonged events of anomalously warm sea water temperature, or marine heatwaves (MHWs), have major detrimental effects to marine ecosystems and the world's economy. While frequency, duration and intensity of MHWs have been observed to increase in the global oceans, little is known about their potential occurrence and variability in estuarine systems due to limited data in these environments. In the present study we analyzed a novel data set with over three decades of continuous in situ temperature records to investigate MHWs in the largest and most productive estuary in the US: the Chesapeake Bay. MHWs occurred on average twice per year and lasted 11 days, resulting in 22 MHW days per year in the bay. Average intensities of MHWs were 3°C, with maximum peaks varying between 6 and 8°C, and yearly cumulative intensities of 72°C × days on average. Large co-occurrence of MHW events was observed between different regions of the bay (50–65%), and also between Chesapeake Bay and the Mid-Atlantic Bight (40–50%). These large co-occurrences, with relatively short lags (2–5 days), suggest that coherent large-scale air-sea heat flux is the dominant driver of MHWs in this region. MHWs were also linked to large-scale climate modes of variability: enhancement of MHW days in the Upper Bay were associated with the positive phase of Niño 1+2, while enhancement and suppression of MHW days in both the Mid and Lower Bay were associated with positive and negative phases of North Atlantic Oscillation, respectively. Finally, as a result of long-term warming of the Chesapeake Bay, significant trends were detected for MHW frequency, MHW days and yearly cumulative intensity. If these trends persist, by the end of the century the Chesapeake Bay will reach a semi-permanent MHW state, when extreme temperatures will be present over half of the year, and thus could have devastating impacts to the bay ecosystem, exacerbating eutrophication, increasing the severity of hypoxic events, killing benthic communities, causing shifts in species composition and decline in important commercial fishery species. Improving our basic understanding of MHWs in estuarine regions is necessary for their future predictability and to guide management decisions in these valuable environments.


BioScience ◽  
2020 ◽  
Vol 70 (4) ◽  
pp. 353-364
Author(s):  
Tian-Yuan Huang ◽  
Martha R Downs ◽  
Jun Ma ◽  
Bin Zhao

Abstract The scale of ecological research is getting larger and larger. At such scales, collaboration is indispensable, but there is little consensus on what factors enable collaboration. In the present article, we investigated the temporal and spatial pattern of institutional collaboration within the US Long Term Ecological Research (LTER) Network on the basis of the bibliographic database. Social network analysis and the Monte Carlo method were applied to identify the characteristics of papers published by LTER researchers within a baseline of papers from 158 leading ecological journals. Long-term and long-distance collaboration were more frequent in the LTER Network, and we investigate and discuss the underlying mechanisms. We suggest that the maturing infrastructure and environment for collaboration within the LTER Network could encourage scientists to make large-scale hypotheses and to ask big questions in ecology.


Significance The current oil industry downturn has not led to the same sort of industry mega-mergers that previous down cycles have produced. However, as oil prices stabilise at 45-50 dollars per barrel and a return to 30-dollar oil looks less likely, the strongest US shale producers are initiating deals that position them to take advantage of the price recovery. Impacts Despite the broader industry downturn, the US shale sector remains an attractive long-term investment for many investors. Large-scale megaprojects are likely to fall out of favour as companies shift spending to smaller short-cycle investments, such as shale. Oilfield service companies will benefit from increased activity as stronger companies buy up weaker drillers.


Subject Tracking progress on Power Africa. Significance US President Barack Obama's five-year Power Africa initiative announced in June 2013 faces growing criticism for slow progress as it approaches its halfway point in December. The US Overseas Private Investment Corporation (OPIC) announced 'critical milestones' for commitments only last month for four flagship projects, two large-scale wind schemes in Kenya and thermal power plants in Senegal and Ghana. Impacts Power Africa will stand as a test of whether infrastructure deficits can be plugged by combining private capital with public guarantees. Private investment will not materialise in sufficient quantities so long as it operates within inefficient state-monopolised sectors. Inefficiencies such as gas-supply problems and subsidies will further undermine the effect of private investment operating on the margins.


Sign in / Sign up

Export Citation Format

Share Document