Upper Cretaceous Foreland Flysch Deposits From the Neotethyan Intra-Pontide Ocean: Geological and Palaeontological Evidence From the Elmadağ Olistostrome of Ankara, Central Türkiye

The Ankara region of Türkiye is located on the Sakarya Continent, bounded by two NeoTethyan oceans (Intra-Pontide to the north and Izmir-Ankara-Erzincan to the south). In this region, the oldest lithologies of the Sakarya Continent are the Middle Triassic Dikmen Greywacke. The lower part of the Dikmen Greywacke comprises low-grade metamorphics, while its upper part is primarily represented by non-metamorphic greywacke with rare carbonates/chert interlayers and a basic volcanic breccia at the top. The Dikmen Greywacke is overlain unconformably by the Coniacian Elmadağ Olistostrome, composed of blocks of varying sizes (pebble to mega-block of 2-3km width) within a calcareous clastic to clayey carbonate matrix. Based on the benthonic Foraminifera assemblages, while detrital limestone provides a Kungurian to Changhsingian (late Early to latest Permian) age, platform carbonates yield latest Capitanian-late Changhsingian (latest Middle to latest Permian) ages. Radiolarian assemblages reveal a Changhsingian (latest Permian) age from a radiolarian chert, middle Late Ladinian (Middle Triassic) from a spiculite/radiolarian chert, latest Bajocian-early Bathonian (Middle Jurassic) from a radiolarian chert, early Hauterivian (Early Cretaceous) from a pelagic limestone, and late Hauterivian (Early Cretaceous) from a radiolarian chert. Combined geological and palaeontological evidence suggest that the Elmadağ Olistostrome has been formed in a foreland basin in front of the southwardly advancing nappes originating from the Intra-Pontide domain. The determined ages imply that the Intra-Pontide basin was rifted after the Artinskian (Early Permian), possibly during late Early Permian to latest Permian. With the gradual deepening of this basin, the first pelagic rock unit occurred in late Changhsingian (latest Permian), where platform carbonates were also present at the rim of the basin in this time interval. Due to the continuous deepening in the basin, pelagic rock units were deposited from middle Late Ladinian (Middle Triassic) to late Hauterivian (Early Cretaceous). By correlation to the other olistostrome occurrence to the south of the Ankara region, it can be suggested that the Elmadağ Olistostrome formed in the Ankara region during Coniacian (Late Cretaceous) owing to the closure of the Intra-Pontide Ocean. © 2025 Author(s).Slovenska Akademija Znanosti in Umetnosti, SASA; Hacettepe Üniversitesi, (FHD-202220129); Hacettepe Üniversites

Combined Effects of Terrain Corrections and Deterministic Modifiers on the Stokes-Helmert Geoid Over Sophisticated Topography

This study focuses on analysing the impact of deterministic modifications of the Stokes kernel and terrain correction methods for precise geoid determination using the Stokes-Helmert method over a sophisticated topography. Three deterministic modification methods of Stokes's kernel (Wong-Gore, Van ; iacuteccaron;ek-Kleusberg, and Featherstone-Evans-Olliver) are tried to minimize the truncation error emanating from the non-availability of gravity data all over the Earth by utilizing two independent satellite only global geopotential models. In parallel to the modified Stokes kernel functions, two terrain correction techniques, i.e., spatial-spectral combined method with mass-prisms and spatial method with mass-cylinders, have also been examined to assess their combined effects on geoid heights over the Konya Closed Basin in T ; uuml;rkiye. The developed geoid models are validated with GNSS-levelling data and inter-compared pixel-wise. The numerical results show that although the overall statistical values depict consistent precision for various combinations of TCs, Stokes kernel modifiers, and GGMs, a holistic validation-comparison analysis reveals significant variations in view of the cm-precise geoid.This research is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) under grant number 120Y246. Ropesh Goyal is supported by the National Centre for Geodesy at IIT Kanpur established with the support of Dept. of Science ; Technology, Govt. of India for his travel to the Konya Technical University, Konya, Turkiye.Scientific and Technological Research Council of Turkey (TUBITAK) [120Y246]; National Centre for Geodesy at IIT Kanpu

Polyoxometalate-Doped Hole Transport Layer To Boost Performance of Mapbi3-Based Inverted-Type Perovskite Solar Cells

This study delves into the examination of the efficiency, stability, and repeatability of perovskite solar cells (PSCs), a focal point in contemporary photovoltaic (PV) technologies. The aim is to address the challenges encountered in PSCs. To achieve this goal, Ge-doped polyoxometalate, a structure of significance in recent molecular electronics, was employed as a dopant in the hole transport layer (HTL). The study investigated alterations in the conductivity, improvements in efficiency, and changes in PV parameters. The utilization of PEDOT/PSS doped with a maximum of 2% GePOM resulted in an average efficiency increase of 27% in PSCs compared with the reference. Moreover, enhancements in stability and repeatability were also noted. Comparatively, the reference PSC operated at an efficiency of 11.18%, while PSCs incorporating 2% GePOM into PEDOT/PSS as the HTL exhibited a notable increase in the efficiency, reaching 14.22%. Furthermore, the champion device exhibited an observed fill factor value of 0.74, a short-circuit current density (J sc) value of 19.78 mA/cm2, and an open-circuit voltage (V oc) value of 0.98 V. Consequently, noteworthy enhancements have been noticed in the PV parameters of PSCs with the introduction of GePOM doping.We thank Scientific Research Project of Selcuk University (PN: 20111010) for the financial support.Sel?uk University Research Foundation [20111010]; Scientific Research Project of Selcuk Universit

Study of Wh Production Through Vector Boson Scattering and Extraction of the Relative Sign of the W and Z Couplings To the Higgs Boson in Proton-Proton Collisions at √s=13 Te

A search for the production of a W boson and a Higgs boson through vector boson scattering (VBS) is presented, using CMS data from proton-proton collisions at root s = 13 TeV collected from 2016 to 2018. The integrated luminosity of the data sample is 138 fb(-1). Selected events must be consistent with the presence of two jets originating from VBS, the leptonic decay of the W boson to an electron or muon, possibly also through an intermediate tau lepton, and a Higgs boson decaying into a pair of b quarks, reconstructed as either a single merged jet or two resolved jets. A measurement of the process as predicted by the standard model (SM) is performed alongside a study of beyond-the-SM (BSM) scenarios. The SM analysis sets an observed (expected) 95% confidence level upper limit of 14.3 (9.9) on the ratio of the measured VBS WH cross section to that expected by the SM. The BSM analysis, conducted within the so-called kappa framework, excludes all scenarios with lambda(WZ) 0 that are consistent with current measurements, where lambda(WZ) = kappa(W)/kappa(Z) and kappa W and kappa(Z) are the HWW and HZZ coupling modfiers, respectively. The significance of the exclusion is beyond 5 standard deviations, and it is consistent with the SM expectation of lambda(WZ) = 1.FWF; FNRS; FWO (Belgium) [30820817]; CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MOST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; DFG; HGF (Germany); NKFIH (Hungary); DAE; DST; IPM; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; NASU (Ukraine); NSF (USA); Marie-Curie program; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); Beijing Municipal Science ; Technology Commission [Z191100007219010]; Fundamental Research Funds for the Central Universities (China); Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Shota Rustaveli National Science Foundation; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 400140256 -GRK2497]; Hellenic Foundation for Research and Innovation (HFRI) [2288]; Hungarian Academy of Sciences [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64]; Council of Science and Industrial Research, India - NextGenerationEU program (Italy); Latvian Council of Science; Ministry of Education and Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552]; Fundacao para a Ciencia e a Tecnologia [CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund; ERDF "a way of making Europe [MDM-2017-0765]; National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation [B37G660013]; Kavli Foundation; Nvidia Corporation; Welch Foundation [C-1845]; Weston Havens Foundation (USA)We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MOST, and NSFC (China); Minciencias (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, Conahcyt, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MoSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; The Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science - OS'' -be.h project n. 30820817; the Beijing Municipal Science ; Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); The Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR22985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy - EXC 2121 "Quantum Universe''-390833306, and under project number 400140256 -GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program -UNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; ICSC - National Research Center for High Performance Computing, Big Data and Quantum Computing and FAIR - Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF "a way of making Europe'', and the Programa Estatal de Fomento de la Investigacion Cientfica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation, grant B37G660013 (Thailand); the Kavli Foundation; the Nvidia Corporation; the Super-Micro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA)

Performance Analysis of Cloud Computing Task Scheduling Using Metaheuristic Algorithms in DdoS and Normal Environments

Cloud computing has emerged as a fundamental pillar of modern technology, enabling large-scale data management, computational efficiency, and operational flexibility. However, critical challenges persist, particularly concerning security and performance. DDoS attacks severely impact cloud infrastructure by degrading system performance and causing service disruptions. These persistent threats raise concerns about cloud system reliability and underscore the necessity for advanced security measures. This study investigates the cloud computing task scheduling problem, recognized as NP-hard, and explores the impact of adversarial conditions such as DDoS attacks on system performance. To address this challenge, metaheuristic algorithms are employed. The research evaluates the effectiveness of traditional approaches, including genetic algorithms (GAs), particle swarm optimization (PSO), and artificial bee colony (ABC), while also introducing a GA–PSO algorithm designed to enhance task scheduling efficiency. The proposed method aims to minimize makespan by optimizing task allocation across virtual machines (VMs) within cloud environments. A comparative analysis of scheduling performance under both normal and DDoS-affected conditions reveals that metaheuristic techniques contribute significantly to system resilience. Furthermore, the GA–PSO algorithm demonstrates notable improvements at specific iteration levels. The findings underscore the potential of advanced scheduling methods to enhance cloud computing sustainability while offering practical solutions to mitigate real-world security threats. © 2025 by the authors

Enhancing Mechanical Performance of Glass Fiber Reinforced Gypsum Composites With Carbon Black and Magnetite: an Integrated Optimization Approach

Toktas, Abdurrahim/0000-0002-7687-9061This study presents a comprehensive optimization methodology that integrates Taguchi Design of Experiments (Taguchi DoE), data augmentation, and the Cuckoo Search Algorithm (CSA) to improve the mechanical and electromagnetic characteristics of gypsum-based composites reinforced with carbon black, magnetite, and glass fiber. The effects of these additives on compressive and flexural strengths were evaluated using an L-16 orthogonal array, and optimal mixes were determined. The hybrid model attained a compressive strength of 32.23 MPa and a flexural strength of 1.41 MPa, demonstrating remarkable prediction accuracy (R-2 > 0.95). The integrated approach also allows cost-effective creation of multifunctional gypsum composites with improved mechanical and electromagnetic properties, in line with advanced construction material development.The authors gratefully acknowledge the Scientific and Technological Research Council of Turkey (TUBITAK) for support with grant number 221M271, and KMU BILTEM staff for their assistance and support.Scientific and Technological Research Council of Turkey (TUBITAK) [221M271

Search for Charged-Lepton Flavor Violation in the Production and Decay of Top Quarks Using Trilepton Final States in Proton-Proton Collisions at √s=13 Tev

Kreczko, Luke/0000-0003-2341-8330; Bhowmik, Sandeep/0000-0003-1260-973X; Ivanov, Andrew/0000-0002-9270-5643; Csanad, Mate/0000-0002-3154-6925; Heath, Helen/0000-0001-6576-9740; Cussans, David/0000-0001-8192-0826; Garcia, Francisco/0000-0002-4023-7964; Brooke, James/0000-0003-2529-0684; Stylianou, Nicolas/0000-0002-0113-6829; Smith, Nicholas/0000-0002-0324-3054A search is performed for charged-lepton flavor violating processes in top quark (t) production and decay. The data were collected by the CMS experiment from proton-proton collisions at a center-of-mass energy of 13 TeV and correspond to an integrated luminosity of 138 fb(-1). The selected events are required to contain one opposite-sign electron-muon pair, a third charged lepton (electron or muon), and at least one jet of which no more than one is associated with a bottom quark. Boosted decision trees are used to distinguish signal from background, exploiting differences in the kinematics of the final states particles. The data are consistent with the standard model expectation. Upper limits at 95% confidence level are placed in the context of effective field theory on the Wilson coefficients, which range between 0.024-0.424 TeV-2 depending on the flavor of the associated light quark and the Lorentz structure of the interaction. These limits are converted to upper limits on branching fractions involving up (charm) quarks, t -> e mu u (t -> e mu c), of 0.032(0.498) x 10(-6), 0.022(0.369) x 10(-6), and 0.012(0.216) x 10(-6) for tensorlike, vectorlike, and scalarlike interactions, respectively.We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); MoER, ERC PUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, Contract No. 675440, 724704, 752730, 758316, 765710, 824093, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, Project No. 22rl-037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWTBelgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science-EOS"-be.h Project No. 30820817; the Beijing Municipal Science ; Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, Grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy-EXC 2121 "Quantum Universe"-390833306, and under project number 400140256-GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program-UNKP, the NKFIH research Grants No. K 124845, No. K 124850, No. K 128713, No. K 128786, No. K 129058, No. K 131991, No. K 133046, No. K 138136, No. K 143460, No. K 143477, No. 2020-2.2.1-ED-2021-00181, and No. TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; ICSC-National Research Center for High Performance Computing, Big Data and Quantum Computing, funded by the EU NexGeneration program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, Contracts No. Opus 2021/41/B/ST2/01369 and No. 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant No. CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF "a way of making Europe," and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, Grant No. MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation, Grant No. B37G660013 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, Contract C-1845; and the Weston Havens Foundation (USA).SC (Armenia); FWF (Austria); FNRS (Belgium); FWO (Belgium); CNPq (Brazil); CAPES (Brazil); FAPERJ (Brazil); FAPERGS (Brazil); FAPESP (Brazil); BNSF (Bulgaria); MoST (China); NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); MoER (Estonia); ERDF (Estonia); Academy of Finland (Finland); MEC (Finland); CEA (France); CNRS/IN2P3 (France); BMBF (Germany); DFG (Germany); HGF (Germany); NKFIH (Hungary); DAE (India); DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE (Malaysia); UM (Malaysia); BUAP (Mexico); CONACYT (Mexico); UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); NSTDA (Thailand); TUBITAK (Turkey); NASU (Ukraine); NSF (USA); Marie-Curie program (European Union); European Research Council (European Union); Horizon 2020 Grant (European Union) [675440, 724704, 752730, 758316, 765710, 824093, 884104]; COST Action (European Union) [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); FWO (Belgium) under the "Excellence of Science - EOS - be.h project [30820817]; Beijing Municipal Science ; Technology Commission [Z191100007219010]; Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Hellenic Foundation for Research and Innovation (HFRI) (Greece) [2288]; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 390833306, 400140256 - GRK2497]; Hungarian Academy of Sciences (Hungary); Council of Science and Industrial Research, India; Latvian Council of Science; National Science Center (Poland) [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552]; National Priorities Research Program by Qatar National Research Fund; MCIN/AEI, ERDF "a way of making Europe"; Programa Severo Ochoa del Principado de Asturias (Spain); Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation (Thailand) [B05F650021]; Kavli Foundation; Nvidia Corporation; SuperMicro Corporation; Welch Foundation [C-1845]; Weston Havens Foundation (USA); BMBWF (Austria); MES (Bulgaria); CERN; CAS (China); MINCIENCIAS (Colombia); MSES (Croatia); ERC PUT (Estonia); HIP (Finland); GSRI (Greece); MSIP (Republic of Korea); LAS (Lithuania); CINVESTAV (Mexico); LNS (Mexico); SEP (Mexico); MOS (Montenegro); MES (Poland); NSC (Poland); MCIN/AEI (Spain); MST (Taipei); MHESI (Thailand); TENMAK (Turkey); STFC (United Kingdom); DOE (USA); F.R.S.-FNRS (Belgium); New National Excellence Program - UNKP (Hungary); NKFIH (Hungary) [K 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64]; Ministry of Education and Science [2022/WK/14]; Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu (Spain) [MDM-2017-0765

Cleaning of Fine-Grained Lignite by Two-Stage Hydrophobic Flocculation Using Different Waste Oils

In this study, the conditions for obtaining clean coal from fine-grained lignite suspensions by two-stage hydrophobic flocculation using different waste oils were investigated. Waste vegetable oil, waste hydraulic oil and waste engine oil were chosen as bridging liquids for hydrophobic flocculation tests. During the studies, sodium silicate was used as the dispersant. Acetone was used at each stage to clean the floc obtained from the agglomeration process. The ash content (%) and combustible recoveries (CR, %) of the floc obtained at the end of each experiment were determined. In addition, contact angle (θ) and calorific values (kcal/kg) were measured and the results were evaluated in detail. At the end of the cleaning stages, low ash clean coal was obtained with a very high combustible recovery. In addition, it was observed that the calorific values increased considerably from 5128 to 5772,5558 to 6304 and 5447 to 5732 using waste vegetable oil, waste hydraulic oil and waste engine oil, respectively. © 2024 Taylor ; Francis Group, LLC

Mimari Tasarım Sürecinde Yaratıcılığı Geliştirmeye Yönelik Bir Model Önerisi

In architectural education, which is based on interaction and communication, there is a dialog provided by using the tools of representation. In the past, there was a more monopolistic educational structure shaped by the influence of schools and movements, while in the process, individualization was seen in the educational structure with the increasing number of universities with formal education. Over time, the diversification of representation tools with digitalization and the inability to use these tools in a qualified manner have led to a weakening in the quality of education. One of the most important factors of this situation is that the new generation born into the digital world cannot use technology in a qualified way and cannot spend the architectural design process efficiently as a result of the decrease in focus periods. The fact that students skip the creative thinking stages of the architectural design process and turn directly to the final product has led to a decline in creativity in architectural design education. In this context, considering the 21st century competencies, architectural design education needs to be reconsidered. Architectural design education is based on learning by doing and is focused on developing creativity. The use of architectural representation tools at the right stage of the design process is an important factor in the development of creativity. This study proposes a model in which traditional and digital tools are used together to support the production of creative thinking in architectural design education. This model, limited to architectural design studios, aims to improve the production of creative thinking by redefining architectural education in the digital age. The study, which aims to improve the creativity level of the designer-student in the architectural design education process with the appropriate and correct use of representation tools, follows a mixed methodology in which qualitative and quantitative research methods are used together. The effect of the proposed training model on the production of creative thinking was analyzed and tested on two separate field studies. As a result of the quantitative and qualitative analyses, the model was validated and defined as an educational method that can be applied in architectural design studios. As a result of the field study, it was determined that creativity is a phenomenon that can be developed by learning intellectual, architectural and technical skills. The findings of the field study are as follows; The pre-test results show that the perception and creativity levels of the architecture students participating in the tests need to be improved in the context of architecture education. The use of traditional or digital representation tools by the architecture students participating in the tests is not at a qualified level. As defined in the design stages of the education model, the increase in the level of creativity is higher with the representation tools used on-site. The increase in the creativity level of the students who use the representation tool qualitatively in the design stages of the education model is higher than those who do not. The education model applied in the workshop format increased the ability to produce creative thinking more than the compulsory studio course. It was determined that the creativity levels of the first-year architecture students who participated in the tests -despite having less architectural knowledge- were higher than the second-year architecture students who participated in the tests. As a result of the study, it was determined that creativity in architectural design education is a phenomenon that can be developed by learning the intellectual, architectural and technical skills of architecture. For this purpose, it was concluded that contemporary and conventional representation tools should be used appropriately, accurately and qualitatively. In order for architectural design education to catch up with the requirements of the age and to keep up to date, while including digital representation tools in education, it should not cause the existing tools to lose their meaning. In the design process, representation tools should be considered as tools that support the process, including the generation of the design idea and the visualization of the final product. Applying an educational model that will support the production of creative thinking to architecture students at an early stage will produce more successful results.Temelinde etkileşim ve iletişimin olduğu mimarlık eğitiminde, temsil araçları kullanılarak sağlanan bir diyalog vardır. Geçmişte ekol ve akımların etkisi ile şekillenen, daha tekel ilerleyen bir eğitim yapısı mevcutken, süreçte formel eğitimle birlikte artan üniversite sayısı ile eğitim yapısında bireyselleşmeler görülmüştür. Zaman içerisinde dijitalleşme ile birlikte temsil araçlarının çeşitlenmesi ve bu araçların nitelikli kullanılamaması ise eğitimin niteliğinde zayıflamaya yol açmıştır. Bu durumun en önemli faktörlerinden biri dijitalin içine doğan yeni neslin, teknolojiyi nitelikli kullanamaması ve odak sürelerinin azalması sonucu mimari tasarım sürecinin verimli geçirememeleridir. Öğrencilerin mimari tasarım sürecinin yaratıcı düşünce üretme aşamalarının atlanarak, direk sonuç ürüne yönelmesi mimari tasarım eğitiminde yaratıcılığın gerilemesine neden olmuştur. Bu bağlamda, 21.yy yeterlilikleri göz önüne alındığında mimari tasarım eğitiminin yeniden ele alınması gerekmektedir. Mimari tasarım eğitimi, yaparak öğrenme üzerine kurguludur ve yaratıcılığı geliştirme odaklıdır. Tasarım sürecinde mimari temsil araçlarının tasarımın doğru aşamasında ve nitelikli kullanılması yaratıcılığın geliştirilmesinde önemli bir etkendir. Bu çalışma, mimari tasarım eğitiminde yaratıcı düşünce üretimini destekleyecek, geleneksel ve dijital araçlarının bir arada kullanıldığı bir model önerir. Mimari tasarım stüdyoları ile sınırlandırılan bu model, dijital çağda mimarlık eğitimini yeniden tanımlayarak yaratıcı düşünce üretimini iyileştirmeyi hedefler. Mimari tasarım eğitimi sürecinde, tasarımcı-öğrencinin yaratıcılık düzeyini, temsil araçlarının yerinde ve doğru kullanımı ile geliştirmeyi hedefleyen çalışmada, nitel ve nicel araştırma yöntemlerinin bir arada kullanıldığı karma bir metodoloji izlenmiştir. Önerilen eğitim modelinin yaratıcı düşünce üretimine etkisi iki ayrı alan çalışması üzerinde incelenerek test edilmiştir. Yapılan nicel ve nitel analizler sonucunda modelin geçerliliği sağlanarak, mimari tasarım stüdyolarında uygulanabilecek bir eğitim metodu olarak tanımlanmıştır. Alan çalışması sonucunda, yaratıcılığın düşünsel, mimari ve teknik becerilerin öğrenilmesi ile geliştirilebilen bir olgu olduğu tespit edilmiştir. Alan çalışması bulguları şu şekildedir; Ön test sonuçları, testlere katılan mimarlık öğrencilerinin algı ve yaratıcılık düzeylerinin mimarlık eğitimi bağlamında geliştirilmesi gerekmektedir. Testlere katılan mimarlık öğrencilerinin geleneksel ya da dijital temsil aracı kullanımı nitelikli seviyede değildir. Eğitim modelinin tasarım aşamalarında tanımlandığı şekliyle yerinde kullanılan temsil araçları ile yaratıcılık düzeyinde yaşanan artış daha fazladır. Eğitim modelinin tasarım aşamalarında temsil aracını nitelikli kullanan öğrencilerin yaratıcılık düzeylerindeki artış, kullanmayanlara oranla daha fazladır. Atölye formatında uygulanan eğitim modeli, zorunlu stüdyo dersine göre yaratıcı düşünce üretme yetisini daha fazla arttırmıştır. Testlere katılan birinci sınıf mimarlık öğrencilerinin -daha az mimari bilgiye sahip olmalarına rağmen- yaratıcılık düzeylerinin testlere katılan ikinci sınıf mimarlık öğrencilerinden daha yüksek olduğu tespit edilmiştir. Çalışma sonucunda, mimari tasarım eğitiminde yaratıcılığın, mimarlığın düşünsel, mimari ve teknik becerilerinin öğrenilmesi ile geliştirilebilen bir olgu olduğu tespit edilmiştir. Bunun için çağdaş ve konvansiyonel temsil araçlarının yerinde, doğru ve nitelikli kullanılması gerektiği sonucuna ulaşılmıştır. Mimari tasarım eğitiminin çağın gerekliliklerini yakalaması ve güncelliğini koruması için dijital temsil araçlarını eğitime dâhil ederken, mevcut araçların anlamını yitirmesine sebep olmamalıdır. Tasarım sürecinde temsil araçları, tasarım fikrinin üretilmesinde ve sonuç ürünün görselleştirilmesinde olmak üzere, süreci destekleyen araçlar olarak ele alınmalıdır. Yaratıcı düşünce üretimini destekleyecek eğitim modelinin mimarlık öğrencilerine erken dönemde uygulanması daha başarılı sonuçlar ortaya çıkaracaktır

Facile Synthesis of Zeolitic-Imidazole Framework-67 (zif-67) for the Adsorption of Indigo Carmine Dye

the authors reviewed and edited the content as needed and took full responsibility for the content of the publication.The authors sincerely acknowledge Horizon 2020 Waste2fresh project (958491) for providing materials and analysis. During the preparation of this wor