| 1. |
- Aad, G, et al.
(author)
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Performance of the upgraded PreProcessor of the ATLAS Level-1 Calorimeter Trigger
- 2020
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In: Journal of Instrumentation. - : IOP Publishing. - 1748-0221. ; 15:11
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Journal article (peer-reviewed)abstract
- The PreProcessor of the ATLAS Level-1 Calorimeter Trigger prepares the analogue trigger signals sent from the ATLAS calorimeters by digitising, synchronising, and calibrating them to reconstruct transverse energy deposits, which are then used in further processing to identify event features. During the first long shutdown of the LHC from 2013 to 2014, the central components of the PreProcessor, the Multichip Modules, were replaced by upgraded versions that feature modern ADC and FPGA technology to ensure optimal performance in the high pile-up environment of LHC Run 2. This paper describes the features of the new Multichip Modules along with the improvements to the signal processing achieved. c 2020 CERN for the benefit of the ATLAS collaboration. Published by IOP Publishing Ltd on behalf of Sissa Medialab.
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| 2. |
- Aartsen, M. G., et al.
(author)
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Computational techniques for the analysis of small signals in high-statistics neutrino oscillation experiments
- 2020
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In: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 977
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Journal article (peer-reviewed)abstract
- The current and upcoming generation of Very Large Volume Neutrino Telescopes - collecting unprecedented quantities of neutrino events - can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as Monte Carlo weighting. In this work we present a staged approach to the generation of expected distributions of observables in order to overcome these challenges. By combining multiple integration and smoothing techniques which address limited statistics from simulation it arrives at reliable analysis results using modest computational resources.
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| 3. |
- Abbasi, R., et al.
(author)
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A convolutional neural network based cascade reconstruction for the IceCube Neutrino Observatory
- 2021
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In: Journal of Instrumentation. - : Institute of Physics Publishing (IOPP). - 1748-0221 .- 1748-0221. ; 16:7
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Journal article (peer-reviewed)abstract
- Continued improvements on existing reconstruction methods are vital to the success of high-energy physics experiments, such as the IceCube Neutrino Observatory. In IceCube, further challenges arise as the detector is situated at the geographic South Pole where computational resources are limited. However, to perform real-time analyses and to issue alerts to telescopes around the world, powerful and fast reconstruction methods are desired. Deep neural networks can be extremely powerful, and their usage is computationally inexpensive once the networks are trained. These characteristics make a deep learning-based approach an excellent candidate for the application in IceCube. A reconstruction method based on convolutional architectures and hexagonally shaped kernels is presented. The presented method is robust towards systematic uncertainties in the simulation and has been tested on experimental data. In comparison to standard reconstruction methods in IceCube, it can improve upon the reconstruction accuracy, while reducing the time necessary to run the reconstruction by two to three orders of magnitude.
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| 4. |
- Abbasi, R., et al.
(author)
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Framework and tools for the simulation and analysis of the radio emission from air showers at IceCube
- 2022
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In: Journal of Instrumentation. - : IOP Publishing Ltd. - 1748-0221 .- 1748-0221. ; 17:6
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Journal article (peer-reviewed)abstract
- The Surface Enhancement of the IceTop air-shower array will include the addition of radio antennas and scintillator panels, co-located with the existing ice-Cherenkov tanks and covering an area of about 1 km(2). Together, these will increase the sensitivity of the IceCube Neutrino Observatory to the electromagnetic and muonic components of cosmic-ray-induced air showers at the South Pole. The inclusion of the radio technique necessitates an expanded set of simulation and analysis tools to explore the radio-frequency emission from air showers in the 70 MHz to 350 MHz band. In this paper we describe the software modules that have been developed to work with time-and frequency-domain information within IceCube's existing software framework, IceTray, which is used by the entire IceCube collaboration. The software includes a method by which air-shower simulation, generated using CoREAS, can be reused via waveform interpolation, thus overcoming a significant computational hurdle in the field.
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| 5. |
- Abdelhamid, Hani Nasser, et al.
(author)
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CelloZIFPaper : Cellulose-ZIF hybrid paper for heavy metal removal and electrochemical sensing
- 2022
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In: Chemical Engineering Journal. - : Elsevier BV. - 1385-8947 .- 1873-3212. ; 446
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Journal article (peer-reviewed)abstract
- The processing of hierarchical porous zeolitic imidazolate frameworks (ZIF-8) into a cellulose paper using sheet former Rapid-Kothen (R.K.) is reported. The procedure is a promising route to overcome a significant bottleneck towards applying metal-organic frameworks (MOFs) in commercial products. ZIF-8 crystals were integrated into cellulose pulp (CP) or TEMPO (2,2,6,6-tetramethylpiperidine-1-oxyl radical)-oxidized cellulose nanofibrils (TOCNF) following an in-situ or ex-situ process; the materials were denoted as CelloZIFPaper_In Situ and CelloZIFPaper_Ex Situ, respectively. The materials were applied as adsorbents to remove heavy metals from water, with adsorption capacities of 66.2-354.0 mg/g. CelloZIFPaper can also be used as a stand-alone working electrode for the selective sensing of toxic heavy metals, for instance, lead ions (Pb2+), using electrochemical-based methods with a limit of detection (LOD) of 8 mu M. The electrochemical measurements may advance 'Lab-onCelloZIFPaper' technologies for label-free detection of heavy metal ions.
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| 6. |
- Abdelhamid, Hani Nasser, 1986-, et al.
(author)
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Cellulose-Based Materials for Water Remediation : Adsorption, Catalysis, and Antifouling
- 2021
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In: Frontiers in Chemical Engineering. - : Frontiers Media SA. - 2673-2718. ; 3
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Research review (peer-reviewed)abstract
- Cellulose-based materials have been advanced technologies that used in water remediation. They exhibit several advantages being the most abundant biopolymer in nature, high biocompatibility, and contain several functional groups. Cellulose can be prepared in several derivatives including nanomaterials such as cellulose nanocrystals (CNCs), cellulose nanofibrils (CNFs), and TEMPO (2,2,6,6-tetramethylpiperidine-1-oxyl radical)-mediated oxidized cellulose nanofibrils (TOCNF). The presence of functional groups such as carboxylic and hydroxyls groups can be modified or grafted with organic moieties offering extra functional groups customizing for specific applications. These functional groups ensure the capability of cellulose biopolymers to be modified with nanoparticles such as metal-organic frameworks (MOFs), graphene oxide (GO), silver (Ag) nanoparticles, and zinc oxide (ZnO) nanoparticles. Thus, they can be applied for water remediation via removing water pollutants including heavy metal ions, organic dyes, drugs, and microbial species. Cellulose-based materials can be also used for removing microorganisms being active as membranes or antibacterial agents. They can proceed into various forms such as membranes, sheets, papers, foams, aerogels, and filters. This review summarized the applications of cellulose-based materials for water remediation via methods such as adsorption, catalysis, and antifouling. The high performance of cellulose-based materials as well as their simple processing methods ensure the high potential for water remediation.
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| 7. |
- Abdelhamid, Hani Nasser, et al.
(author)
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Cellulose-zeolitic imidazolate frameworks (CelloZIFs) for multifunctional environmental remediation : Adsorption and catalytic degradation
- 2021
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In: Chemical Engineering Journal. - : Elsevier BV. - 1385-8947 .- 1873-3212. ; 426
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Journal article (peer-reviewed)abstract
- The crystal growth of zeolitic imidazolate frameworks (ZIFs) on biopolymers such as cellulose is a promising method for obtaining hybrid materials that combinenatural and synthetic materials. Cellulose derivative viz. 2,2,6,6-tetramethylpiperidine-1-oxylradical (TEMPO)-mediated oxidized nanocellulose (TOCNF) was used to modulate the crystal growth of ZIF-8 (denoted as CelloZIF-8) and ZIF-L (CelloZIF-L). The synthesis procedure occurred in water at room temperature with and without NaOH. The reaction parameters such as the sequence of the chemical's addition and reactant molar ratio were investigated. The phases formed during the crystal growth were monitored. The data analysis ensured the presence of zinc hydroxide nitrate nanosheets modified TOCNF during the crystallization of CelloZIFs. These phases were converted to pure phases ofCelloZIF-8 and CelloZIF-L. The resultant CelloZIFs materials were used for the adsorption ofcarbon dioxide (CO2), metal ions, and dyes. The materials exhibited high selectivity with reasonable efficiency (100%) toward the adsorption of anionic dyes such as methyl blue (MeB). They can also be used as a catalyst for dye degradation via hydrogenation with an efficiency of 100%. CelloZIF crystals can be loaded into a filter paper for simple, fast, and selective adsorption of MeB from a dye mixture. The materials are recyclable for five cycles without significant loss of their performance. The mechanisms of adsorption and catalysis were also investigated.
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| 8. |
- Abram, Emese, et al.
(author)
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Spectrophotometric examination of the optical effects of monolithic multilayered zirconia with different substrates
- 2020
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In: Advances in Applied Ceramics. - : Informa UK Limited. - 1743-6753 .- 1743-6761. ; 119:5-6, s. 261-266
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Journal article (peer-reviewed)abstract
- The goal of this study is to examine specific optical effects of multilayered and coloured monolithic zirconia considering thickness and substrates of different colours using one of the most advanced spectrophotometers of the world. Multilayered zirconia specimens were used for the study with the thickness range of 0.5-2.5 mm and six types of substrate materials and three types of metal substrates. Measurements were carried out at Budapest Technical University with a PerkinElmer (R) Lambda1050UV/Vis/NIR spectrophotometer. The substrate colour and the thickness of zirconia affects the optical results, with special regard to colour perceptibility and acceptability. Monochromatic and multilayer zirconia show both similarities and discrepancies in behaviour, i.e. spectral reflectance and Delta E. Owing to the multi-coloured characteristics of multilayered zirconia the optical effect of the substrate less predictable than in the case of monochromatic zirconia thus requiring more detailed planning and implementation.
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| 9. |
- Abu-Omar, Mahdi M., et al.
(author)
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Guidelines for performing lignin-first biorefining
- 2021
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In: Energy & Environmental Science. - : Royal Society of Chemistry (RSC). - 1754-5692 .- 1754-5706. ; 14:1, s. 262-292
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Research review (peer-reviewed)abstract
- The valorisation of the plant biopolymer lignin is now recognised as essential to enabling the economic viability of the lignocellulosic biorefining industry. In this context, the lignin-first biorefining approach, in which lignin valorisation is considered in the design phase, has demonstrated the fullest utilisation of lignocellulose. We define lignin-first methods as active stabilisation approaches that solubilise lignin from native lignocellulosic biomass while avoiding condensation reactions that lead to more recalcitrant lignin polymers. This active stabilisation can be accomplished by solvolysis and catalytic conversion of reactive intermediates to stable products or by protection-group chemistry of lignin oligomers or reactive monomers. Across the growing body of literature in this field, there are disparate approaches to report and analyse the results from lignin-first approaches, thus making quantitative comparisons between studies challenging. To that end, we present herein a set of guidelines for analysing critical data from lignin-first approaches, including feedstock analysis and process parameters, with the ambition of uniting the lignin-first research community around a common set of reportable metrics. These guidelines comprise standards and best practices or minimum requirements for feedstock analysis, stressing reporting of the fractionation efficiency, product yields, solvent mass balances, catalyst efficiency, and the requirements for additional reagents such as reducing, oxidising, or capping agents. Our goal is to establish best practices for the research community at large primarily to enable direct comparisons between studies from different laboratories. The use of these guidelines will be helpful for the newcomers to this field and pivotal for further progress in this exciting research area.
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| 10. |
- A'Campo, Willeke, et al.
(author)
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Arctic Tundra Land Cover Classification on the Beaufort Coast Using the Kennaugh Element Framework on Dual-Polarimetric TerraSAR-X Imagery
- 2021
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In: Remote Sensing. - : MDPI AG. - 2072-4292. ; 13:23
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Journal article (peer-reviewed)abstract
- Arctic tundra landscapes are highly complex and are rapidly changing due to the warming climate. Datasets that document the spatial and temporal variability of the landscape are needed to monitor the rapid changes. Synthetic Aperture Radar (SAR) imagery is specifically suitable for monitoring the Arctic, as SAR, unlike optical remote sensing, can provide time series regardless of weather and illumination conditions. This study examines the potential of seasonal backscatter mechanisms in Arctic tundra environments for improving land cover classification purposes by using a time series of HH/HV TerraSAR-X (TSX) imagery. A Random Forest (RF) classification was applied on multi-temporal Sigma Nought intensity and multi-temporal Kennaugh matrix element data. The backscatter analysis revealed clear differences in the polarimetric response of water, soil, and vegetation, while backscatter signal variations within different vegetation classes were more nuanced. The RF models showed that land cover classes could be distinguished with 92.4% accuracy for the Kennaugh element data, compared to 57.7% accuracy for the Sigma Nought intensity data. Texture predictors, while improving the classification accuracy on the one hand, degraded the spatial resolution of the land cover product. The Kennaugh elements derived from TSX winter acquisitions were most important for the RF model, followed by the Kennaugh elements derived from summer and autumn acquisitions. The results of this study demonstrate that multi-temporal Kennaugh elements derived from dual-polarized X-band imagery are a powerful tool for Arctic tundra land cover mapping.
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