| 1. |
- Kaviani, Ayoub, et al.
(author)
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Mantle-flow diversion beneath the Iranian plateau induced by Zagros’ lithospheric keel
- 2021
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In: Scientific Reports. - : Nature. - 2045-2322. ; 11:1
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Journal article (peer-reviewed)abstract
- Previous investigation of seismic anisotropy indicates the presence of a simple mantle flow regime beneath the Turkish-Anatolian Plateau and Arabian Plate. Numerical modeling suggests that this simple flow is a component of a large-scale global mantle flow associated with the African superplume, which plays a key role in the geodynamic framework of the Arabia-Eurasia continental collision zone. However, the extent and impact of the flow pattern farther east beneath the Iranian Plateau and Zagros remains unclear. While the relatively smoothly varying lithospheric thickness beneath the Anatolian Plateau and Arabian Plate allows progress of the simple mantle flow, the variable lithospheric thickness across the Iranian Plateau is expected to impose additional boundary conditions on the mantle flow field. In this study, for the first time, we use an unprecedented data set of seismic waveforms from a network of 245 seismic stations to examine the mantle flow pattern and lithospheric deformation over the entire region of the Iranian Plateau and Zagros by investigation of seismic anisotropy. We also examine the correlation between the pattern of seismic anisotropy, plate motion using GPS velocities and surface strain fields. Our study reveals a complex pattern of seismic anisotropy that implies a similarly complex mantle flow field. The pattern of seismic anisotropy suggests that the regional simple mantle flow beneath the Arabian Platform and eastern Turkey deflects as a circular flow around the thick Zagros lithosphere. This circular flow merges into a toroidal component beneath the NW Zagros that is likely an indicator of a lateral discontinuity in the lithosphere. Our examination also suggests that the main lithospheric deformation in the Zagros occurs as an axial shortening across the belt, whereas in the eastern Alborz and Kopeh-Dagh a belt-parallel horizontal lithospheric deformation plays a major role.
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| 2. |
- Ayoub, Ali, et al.
(author)
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Effect of plasticizers and polymer blends for processing softwood kraft lignin as carbon fiber precursors
- 2021
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In: Cellulose. - : Springer Science and Business Media LLC. - 0969-0239 .- 1572-882X. ; 28:2, s. 1039-1053
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Journal article (peer-reviewed)abstract
- Plasticizers depress the glass transition temperature (T-g) of polymers and produce a flowable material at lower temperatures. The use of plasticizers to depress T-g of lignin is important, since at high processing temperatures lignin crosslinks, making it intractable. The goal of this study was to assess plasticizers and polymer blends for the ability to retard a commercial softwood kraft lignin from crosslinking and also serve as thermal and rheological property modifiers during thermal processing in the attempt to produced moldable and spinnable lignin for lignin and carbon fiber products. The T-g of the lignin and the lignin mixed with various amounts of plasticizers and with different thermo-mechanical mixing were determined using differential scanning calorimetry. The T-g and the change in heat capacity at the glass transition (Delta C-p) decreased and increased, respectively, about linearly within this plasticizers range with increased plasticizer weight percentage. Gel permeation chromatography results for extruded lignin as well as extruded lignin-plasticizer blends with glycerol, N-allyurea, citric acid with and without sodium hypophosphite, and oleic acid indicate that the presence of these materials reduced the rate of molecular weight increase at temperatures between 100 and 200 degrees C. Continuous, homogenous films and fibers could be produced by thermal processing with plasticized lignin samples and plasticized lignin-polymer blends, but not with lignin alone. These fibers could be carbonized, yielding up to about 50% of carbon. The present findings have shown the advantages of plasticizers in thermally processing a commercial softwood kraft lignin.
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| 3. |
- Kaviani, Ayoub, et al.
(author)
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SKS splitting observations across the Iranian plateau and Zagros: the role of lithosphere deformation and mantle flow
- 2020
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Conference paper (peer-reviewed)abstract
- We used more than one decade of core-refracted teleseismic shear (SKS) waveforms recorded atmore than 160 broadband seismic stations across the Iranian plateau and Zagros to investigateseismic anisotropy beneath the region. Splitting analysis of SKS waveforms provides two mainparameters, i.e., fast polarization direction and split delay time, which serve as proxies for thetrend and strength of seismic anisotropy beneath the stations. Our observation revealed acomplex pattern of splitting parameters with variations in the trend and strength of anisotropyacross the tectonic boundaries. We also verified the presence of multiple layers of anisotropy inconjunction with the lithosphere deformation and mantle flow field. Our observation andmodeling imply that a combined system of lithosphere deformation and asthenospheric flow islikely responsible for the observed pattern of anisotropy across the Iranian Plateau and Zagros.The rotational pattern of the fast polarization directions observed locally in Central Zagros mayindicate the diversion of mantle flow around a continental keel beneath the Zagros. Thecorrelation between the variation in lithosphere thickness and the trend of anisotropy in the studyarea implies that the topography of the base of lithosphere is also a determining factor for thepattern of mantle flow inferred from the observations.
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| 4. |
- Naqvi, Salman Raza, et al.
(author)
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Agro-industrial residue gasification feasibility in captive power plants : A South-Asian case study
- 2021
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In: Energy. - : Elsevier. - 0360-5442 .- 1873-6785. ; 214
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Journal article (peer-reviewed)abstract
- The objective of this study is to build knowledge on the potential of agro-industrial residue gasification (AIRG) for use in captive power generation through a comprehensive case study. In order to evaluate the economic viability, key performance indicators, such as net present value (NPV), levelized cost of electricity (LCOE), and operating costs etc. are studied. The major textile industry located in the Raiwind area of Punjab province of Pakistan has been selected. The effect and variations of the capacity factor has also been studied coupled with the levelized cost of electricity. The agricultural residue as feedstock to the gasifier is rice husk that is the abundantly available in South Asia. Furthermore, the impact of government subsidies on natural gas is also under the scope of the study. The agro-industrial residue gasification system is found to be a potential alternative to furnace oil (FO) or gas-based captive power plants (CPPs). The results of residue-based gasification system imply a large potential when comparing the cost of electricity with national grid electricity during the peak hours. Therefore, the proposed gasification system offers economic incentives when the textile industry potentially utilizes gasification-based electricity during peak hours and national grid electricity during off-peak hours. (C) 2020 Elsevier Ltd. All rights reserved.
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| 5. |
- Rabani, Syed Tanzeel, et al.
(author)
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Detecting suicidality on social media : Machine learning at rescue
- 2023
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In: Egyptian Informatics Journal. - : Elsevier. - 1110-8665 .- 2090-4754. ; 24:2, s. 291-302
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Journal article (peer-reviewed)abstract
- The rise in technological advancements and Social Networking Sites (SNS) made people more engaged in their virtual lives. Research has revealed that people feel more comfortable posting their feelings, including suicidal thoughts, on SNS than discussing them through face-to-face settings due to the social stigma associated with mental health. This research study aims to develop a multi-class machine learning classifier for identifying suicidal risk levels in social media posts. The proposed Enhanced Feature Engineering Approach for Suicidal Risk Identification (EFASRI) is used to extract features from a novel dataset collected from Twitter and Reddit platforms. Three machine learning algorithms, i.e. Support Vector Machine (SVM), Random Forest (RF) and Extreme Gradient Boosting (XGB) were employed for classification. The study demonstrates significant improvements in the precision, recall, and overall accuracy compared to previous research that used classical feature extraction mechanisms. The best-performing algorithm, Extreme Gradient Boosting (XGB), achieved an overall accuracy of 96.33%. The findings imply that different features contain different levels of information, and the right combination of the features supplied to the machine learning algorithms may improve the prediction results.
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| 6. |
- Aad, G, et al.
(author)
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- 2015
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swepub:Mat__t
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