Emergency Response, and Community Impact After February 6, 2023 Kahramanmaraş Pazarcık and Elbistan Earthquakes: Reconnaissance Findings and Observations on Affected Region in Türkiye

Türkiye has a long history of devastating earthquakes, and on February 6, 2023, the region experienced two major earthquakes with magnitudes of 7.7 and 7.6, striking Pazarcık and Elbistan, Kahramanmaraş, respectively, on the East Anatolian Fault Zone. These earthquakes resulted in significant loss of life and property, impacting multiple cities across 11 cities, and leaving a lasting impact on the country. The 2023 Kahramanmaraş Earthquakes rank among the deadliest and most damaging earthquakes in Türkiye, alongside the historical significance of the 1939 Erzincan Earthquake and the 1999 Marmara Earthquake. Despite reforms following the 1999 Marmara Earthquake in disaster policy and preparedness, the scale of damage from the February 6 earthquakes has been shocking, necessitating further insights and lessons for future earthquake management. This paper presents the outcomes of immediate response efforts organized after the 2023 Kahramanmaraş earthquakes to elucidate emergency response activities and their impacts on communities, considering the substantial size and severity of the damages. The study focuses on evaluating the emergency response provided within the first 24 h, 3 days, and 2 weeks after the earthquakes, aiming to promptly identify the nature and effectiveness of these responses, as well as the conditions that hindered their efficacy. By shedding light on the specific experiences and challenges faced during these crucial timeframes, the research aims to offer valuable insights and lessons learned. These findings contribute to improved preparedness strategies and more efficient emergency response measures needed in responding to future disaster scenarios. Ultimately, this study provides a useful resource for all stakeholders involved in emergency response and disaster management, offering valuable guidance to enhance resilience and preparedness in the face of seismic hazards. © The Author(s) 2024.Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK; Doğal Afetler Odaklı Saha Çalışması Acil Destek Programı; Scientific and Technological Research Institution of Türkiy

A Novel Approach for Modeling Liner Interface Debonding in Solid Rocket Motors

In solid rocket motors, liner is applied into case/insulation and propellant interface to ensure the bonding of the propellant. Debonding occurring at the liner interface may lead to failure of the motor. The aim of this study is to develop a new approach for modeling liner interface debonding with cohesive zone model and to examine the usage of peel test for the fracture energy input of the model. To develop a cohesive zone model, peel tests and bond in tension tests are conducted. Liner's fracture energy is calculated via outputs of the peel tests and energy equations. Finite element analysis of the peel test is performed with the developed bilinear cohesive zone model. Agreement is achieved between the numerical and test results without any inverse analysis. Therefore, the developed approach can be utilized to build cohesive zone models for liners without a costly iterative procedure

Flower-Like Nanoscale Ni(OH)2/MnCo3 Electrocatalyst for Efficient Hydrogen Evolution Reaction in Wide Ph Range

Duran Durmus, Hatice/0000-0001-6203-3906It is indispensable to develop efficient and cost-effective electrocatalysts, especially those that can work in a wide pH range for the HER (hydrogen evolution reaction) and OER (oxygen evolution reaction). In this study, we have devised a hydrothermal one-pot method for the production of Ni(OH)2/MnCO3 composite nanosheets on nickel foam having close resemblance with flowers. The electrocatalyst exhibited appreciable performance for HER with a minimum overpotential of-60 m V and-120 mV in acidic and alkaline media respectively, to deliver 10 mA cm- 2 current density. Tafel slope of 38 mV dec-1 (in acidic) and 112 mV dec-1 (in alkaline) medium under a limited potential range of 0 to-0.1 V was observed. The significant performance of such a hybrid system can be attributed to thin sheet morphology, the mutual support of Ni(OH)2 and Mn(CO3)2, and possible generation of active sites at the interface and may contribute to the electrochemically active surface area i.e. 350 cm2 (acidic) 190 cm2 (alkaline). This study presents a novel approach to pave the way for advanced self-supported nanoscale materials to boost HER in both acidic and alkaline environments

Two Modified Forms of the SAIR Model With a Fuzzyfied Vaccination Effectiveness Parameter

In 2019, the emergence of COVID-19 underscored the critical role of mathematical modeling in understanding and forecasting global health crises. The rapid and often unnoticed spread of infectious diseases by asymptomatic carriers poses a significant challenge to public health efforts worldwide. Understanding and accurately modeling this transmission is crucial for developing effective vaccination strategies and controlling outbreaks. We address this critical issue by enhancing the SAIR model, a Susceptible-Asymptomatic-Infected-Recovered compartmental model, to better capture the dynamics of asymptomatic spread and vaccination effectiveness. This study focuses on the SAIR models to investigate the dynamics of COVID-19 transmission, with a particular emphasis on asymptomatic individuals, who can unknowingly transmit the disease. In this paper, we present two modifications to the SAIR model. The first modification assumes that individuals gain lifelong immunity after recovering from the infection. The second modification, known as the SAIRS model, considers the possibility of reinfection, meaning recovered individuals can become susceptible again. By applying these enhanced models to real-world data on daily reported COVID-19 cases in T ; uuml;rkiye, we aim to gain a deeper understanding of the pandemic's behavior and progression in the country. The novelty of this work lies in the integration of a vaccine effectiveness parameter into the SAIR model, uniquely considering the delayed immunity of vaccinated individuals and the distinct transmission dynamics of both symptomatic and asymptomatic cases. Analyzing this parameter within a fuzzy environment enhances the accuracy of predictions, providing more dependable estimations of future disease scenarios. This approach offers a new dimension to epidemic modeling, contributing valuable insights to public health strategies and vaccination policies

The Analysis Description Language Ecosystem: Latest Developments and Physics Applications

We present latest developments in Analysis Description Language (ADL), a declarative domain-specific language describing the physics algorithm of a HEP data analysis decoupled from software frameworks. Analyses written in ADL can be integrated into any framework for various tasks. ADL is a multipurpose construct with uses ranging from analysis design to preservation, reinterpretation, queries, visualisation, combination, etc. The most advanced infrastructure to execute ADL on events is the CutLang runtime interpreter. Recent technical developments include an automated interface with different data types, generation of the abstract syntax tree, a visualization tool that that auto-converts analysis flows to graphs, incorporation of trained machine learning models and a Jupyter-based plotting tool. We also report physics implications including a large scale LHC analysis implementation and validation effort for beyond the standard model reinterpretation purposes and studies with ATLAS and CMS open data. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).National Research Foundation of Korea, NRF; Ministry of Education, MOE, (NRF-2021R1I1A3048138, NRF-2018R1A6A1A06024970, NRF-2008-00460); Ministry of Education, MO

Measurement of Photonuclear Jet Production in Ultraperipheral (Formula Presented) Collisions at (Formula Presented) With the Atlas Detector

In ultrarelativistic heavy ion collisions at the LHC, each nucleus acts a sources of high-energy real photons that can scatter off the opposing nucleus in ultraperipheral photonuclear ((Formula presented)) collisions. Hard scattering processes initiated by the photons in such collisions provide a novel method for probing nuclear parton distributions in a kinematic region not easily accessible to other measurements. ATLAS has measured production of dijet and multijet final states in ultraperipheral (Formula presented) collisions at (Formula presented) using a dataset recorded in 2018 with an integrated luminosity of (Formula presented). Photonuclear final states are selected by requiring a rapidity gap in the photon direction; this selects events where one of the outgoing nuclei remains intact. Jets are reconstructed using the anti-(Formula presented) algorithm with radius parameter, (Formula presented). Triple-differential cross sections, unfolded for detector response, are measured and presented using two sets of kinematic variables. The first set consists of the total transverse momentum ((Formula presented)), rapidity, and mass of the jet system. The second set uses (Formula presented) and particle-level nuclear and photon parton momentum fractions, (Formula presented) and (Formula presented), respectively. The results are compared with leading-order perturbative QCD calculations of photonuclear jet production cross sections, where all leading order predictions using existing fits fall below the data in the shadowing region. More detailed theoretical comparisons will allow these results to strongly constrain nuclear parton distributions, and these data provide results from the LHC directly comparable to early physics results at the planned Electron-Ion Collider. © 2025 CERN, for the ATLAS Collaboration.Ministerio de Ciencia, Innovación y Universidades, MCIU; BSF-NSF; Australian Research Council, ARC; DRAC; La Caixa Banking Foundation; BMWFW; Centre National pour la Recherche Scientifique et Technique, CNRST; Fundação para a Ciência e a Tecnologia, FCT; European Union, Future Artificial Intelligence Research; Cooperative Research Centres, Australian Government Department of Industry, CRCs; Center for Advancing Research Impact in Society, ARIS; National Science Foundation, NSF; CEA-DRF; Science and Technology Facilities Council, STFC; Horizon 2020, ICSC-NextGenerationEU; H2020 Marie Skłodowska-Curie Actions, MSCA; INFN-CNAF; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, FAPERJ; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO; Ministry of Science and Technology, Taiwan, MOST; Israel Science Foundation, ISF; Wallenberg Foundation; Leverhulme Trust; Baden-Württemberg Stiftung, BWS; MVZI; PROMETEO; Neubauer Family Foundation, NFF; Staatssekretariat für Bildung, Forschung und Innovation, SBFI; IDUB AGH; Generalitat de Catalunya; Instituto Nazionale di Fisica Nucleare, INFN; Austrian Science Fund, FWF; Yerevan Physics Institute; Agencia Nacional de Investigación y Desarrollo, ANID; Bundesministerium für Bildung und Forschung, BMBF; Helmholtz-Gemeinschaft, HGF; Danmarks Grundforskningsfond, DNRF; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Forskningsrådet för hälsa, arbetsliv och välfärd, FORTE; Karlsruhe Institute of Technology, KIT; Canarie; GridKA; Göran Gustafssons Stiftelser; European Commission, EC; European Cooperation in Science and Technology, COST; EU-ESF; International Council of Shopping Centers, ICSC; RGC; Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP; PRIMUS; Institutul de Fizică Atomică, IFA; Natural Sciences and Engineering Research Council of Canada, NSERC; Nella and Leon Benoziyo Center for Neurological Diseases, Weizmann Institute of Science; GenT Programmes Generalitat Valenciana, Spain; National Science and Technology Council, NSTC; Irish Rugby Football Union, IRFU; Cantons of Bern and Geneva; Chinese Academy of Sciences, CAS; Defence Science Institute, DSI; MSTDI; MNE; Agencia Nacional de Promoción Científica y Tecnológica, ANPCyT; Royal Society; Minerva Foundation; CERN-CZ; National Research Foundation, NRF; Ministerstwo Edukacji i Nauki, MNiSW; Generalitat Valenciana, GVA; CERN; National Research Council Canada, NRC; Brookhaven National Laboratory, BNL; Alexander von Humboldt-Stiftung, AvH; Multiple Sclerosis Scientific Research Foundation, MSSRF; Caring Futures Institute, Flinders University, CFI; British Columbia Knowledge Development Fund, BCKDF; Ministry of Education, Culture, Sports, Science and Technology, MEXT; UK Research and Innovation, UKRI; Australian Education International, Australian Government, AEI; Ministero dell’Istruzione, dell’Università e della Ricerca, MIUR, (20223N7F8K—PNRR M4.C2.1.1); Ministero dell’Istruzione, dell’Università e della Ricerca, MIUR; The Slovenian Research and Innovation Agency, ARRS, (J1-3010); The Slovenian Research and Innovation Agency, ARRS; Deutsche Forschungsgemeinschaft, DFG, (DFG—CR 312/5-2, DFG—469666862); Deutsche Forschungsgemeinschaft, DFG; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF, (RPG-2020-004, NIF-R1-231091, SNSF—PCEFP2_194658); Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF; European Regional Development Fund, ERDF, (IDIFEDER/2018/048); European Regional Development Fund, ERDF; Carl Tryggers Stiftelse för Vetenskaplig Forskning, (CTS-22:2312); Carl Tryggers Stiftelse för Vetenskaplig Forskning; Narodowe Centrum Nauki, NCN, (UMO-2021/40/C/ST2/00187, NCN-2021/42/E/ST2/00350, UMO-2023/49/B/ST2/04085, NCN-UMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, NCN-OPUS-2022/47/B/ST2/03059, UMO-2023/51/B/ST2/00920, UMO-2022/47/O/ST2/00148, H2020 MSCA 945339); Narodowe Centrum Nauki, NCN; Narodowa Agencja Wymiany Akademickiej, NAWA, (PPN/PPO/2020/1/00002/U/00001); Narodowa Agencja Wymiany Akademickiej, NAWA; Ministerio de Ciencia e Innovación, MCIN, (PID2021-125273NB, RYC2021-031273-I, RYC2022-038164-I, PCI2022-135018-2, RYC2020-030254-I, RYC2019-028510-I); Ministerio de Ciencia e Innovación, MCIN; Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT, (FORTE CZ.02.01.01/00/22_008/0004632, PRIMUS/21/SCI/017); Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT; Grantová Agentura České Republiky, GAČR, (GACR—24-11373S); Grantová Agentura České Republiky, GAČR; Norges Forskningsråd, (RCN-314472); Norges Forskningsråd; H2020 European Research Council, ERC, (ERC-101002463); H2020 European Research Council, ERC; DNSRC, (IN2P3-CNRS); Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYT, (1240864, 1230987, 1230812); Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYT; Investissements d’Avenir Labex, (ANR-11-LABX-0012); National Natural Science Foundation of China, NSFC, (NSFC-12275265, NSFC-12175119, NSFC-12075060); National Natural Science Foundation of China, NSFC; Japan Society for the Promotion of Science, JSPS, (JP22KK0227, JP22H04944, JP23KK0245, JP22H01227); Japan Society for the Promotion of Science, JSPS; Horizon 2020 Framework Programme, H2020, (CHIST-ERA-19-XAI-00); Horizon 2020 Framework Programme, H2020; Vetenskapsrådet, VR, (VR 2022-03845, VR 2023-04654, VR 2022-04683, VR 2021-03651, VR 2018-00482, VR 2023-03403); Vetenskapsrådet, VR; FAIR-NextGenerationEU, (PE00000013); Agence Nationale de la Recherche, ANR, (ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-22-EDIR-0002, ANR-21-CE31-0022); Agence Nationale de la Recherche, ANR; U.S. Department of Energy, USDOE, (ECA DE-AC02-76SF00515); U.S. Department of Energy, USDOE; Ministry of Science and Technology of the People's Republic of China, MOST, (MOST-2023YFA1609300, MOST-2023YFA1605700); Ministry of Science and Technology of the People's Republic of China, MOST; North Dakota Game and Fish Department, (CC-IN2P3); North Dakota Game and Fish Department; European Research Council, ERC, (ERC-101089007, ERC-948254); European Research Council, ERC; Knut och Alice Wallenbergs Stiftelse, (KAW 2018.0458, KAW 2019.0447, KAW 2022.0358); Knut och Alice Wallenbergs Stiftels

A Bifunctional Electrocatalyst for Energy-Efficient Hydrogen Production and Ethanol Upgrading into Acetate via Hybrid Seawater Splitting

The sluggish kinetics of the oxygen evolution reaction (OER) and the competing chlorine evolution reaction (CER) significantly limit the efficiency of seawater electrolysis for hydrogen production. Replacing OER/CER with thermodynamically more favorable anodic reactions presents a promising strategy for reducing energy consumption and overcoming chlorine-based toxic products. This study reports a hybrid seawater electrolysis system that couples the ethanol oxidation reaction (EOR) with the hydrogen evolution reaction (HER), enabling the co-production of green hydrogen and value-added potassium acetate in alkaline seawater. Utilizing bimetallic NiCu hierarchical nanostructures supported on nickel foam (NiCu–HNS@NF) as a bifunctional electrocatalyst, this promising system required 220 mV less potential for EOR compared to OER to achieve a current density of 20 mA cm−2. Meanwhile, the HER required a low overpotential of only 97 mV to attain the same current density, with a faradaic efficiency (FE) of 97.6%. The COinf>2/inf>-free selective conversion of ethanol into acetate, along with the high faradaic efficiency (FE) for Hinf>2/inf>, may be attributed to the bubbles-templated interconnected hierarchical nanostructures and the bimetallic synergistic effect. This study highlights the potential of ethanol-assisted seawater electrolysis as an energy-efficient and economically viable platform for sustainable hydrogen production and biomass valorization. © 2025 Elsevier B.V., All rights reserved

Polythiophene Block Copolymer-Perylene Diimide-Based Electron Donor-Acceptor Double-Cable Polymer and Its Potential as an All-Organic Photocatalyst for Artificial Photosynthesis of H2O2

Enhancing the light energy harvesting and conversion capabilities of all-organic photoactive materials is of significant scientific interest. Herein, we report the synthesis of a photoactive double-cable polymer (DCP) consisting of a polythiophene (PTh) block copolymer electron donor (D) conjugated to a perylene diimide (PDI) electron acceptor (A). GRIM polymerization and postsynthetic modifications are employed to synthesize the block copolymer [P3HT-b-poly(3-HT-co-PTh/PDI)] consisting of a poly-3-hexylthiophene (P3HT) block and a block comprising of randomly distributed repeat units bearing hexyl and PDI groups. Besides H-1 NMR, ATR-FTIR, UV/visible, and fluorescence spectroscopic characterizations, AFM and XRD analyses are performed to reveal self-assembly and crystallinity behaviors. Compared to P3HT, PDI, and their physical hybrid (P3HT-PDI-PH), the P3HT-b-poly(3-HT-co-PTh/PDI) shows superior D-A electronic communication, higher (photo)electrochemical current, faster electrochemical kinetics, and lower charge transfer resistance. The photocatalytic performance of all photocatalysts in the artificial photosynthesis of H2O2 is demonstrated over 10 photocatalytic cycles. Comparing the results from the highest H2O2 producing cycles, the photocatalytic performance of P3HT-b-poly(3HT-co-Th/PDI) is similar to 2.1, similar to 3.2, and similar to 1.9 times superior compared to that of P3HT, PDI, and P3HT-PDI-PH, respectively. In summary, this work contributes to the development of organic semiconducting polymer-based photoactive materials for application in light energy harvesting and conversion technologies.Lahore University of Management Sciences [20-15989]; Higher Education Commission (HEC) of Pakistan; Faculty Initiative Fund (FIF); LUMS [RGY0074/2016]; HFSP [20-1740/RD/10/3368, 1799/RD/10-5302, 5922, TDF-033]; HEC for NRPUThis work was financially supported by the Higher Education Commission (HEC) of Pakistan (NRPU Project No.20-15989) and the Faculty Initiative Fund (FIF), LUMS. B.Y. acknowledges support from HFSP (RGY0074/2016), HEC for NRPU (Project Nos. 20-1740/R;D/10/3368, 20-1799/R;D/10-5302, and 5922), and TDF-033 grants, and LUMS for start-up fund. Support from Prof. Raja Shahid (GCU) for the steady-state fluorescence spectroscopy is highly appreciated

Charged-Hadron and Identified-Hadron (Ks0, Λ, Ξ-) Yield Measurements in Photonuclear Pb Plus Pb and P Plus Pb Collisions at √snn=5.02 Tev with ATLAS

Tishelman-Charny, Abraham/0000-0002-7332-5098; Angerami, Aaron/0000-0001-7834-8750; Kirk, Julie/0000-0001-8096-7577; Mete, Alaettin Serhan/0000-0002-5508-530X; Valero, Alberto/0000-0002-9776-5880; Schultz-Coulon, Hans-Christian/0000-0002-0860-7240; Morii, Masahiro/0000-0001-9324-057X; Merlassino, Claudia/0000-0002-5445-5938; Beretta, Matteo Mario/0000-0002-7026-8171; Petersen, Troels/0000-0003-0221-3037; Castro, Nuno/0000-0001-8491-4376; D'Uffizi, Matteo/0000-0003-2499-1649; Warburton, Andreas/0000-0002-2298-7315; White, Martin/0000-0001-5474-4580; Simsek, Sinem/0000-0002-9650-3846; Gaudio, Gabriella/0000-0002-6833-0933; Chan, Jay/0000-0001-7069-0295; Terzo, Stefano/0000-0003-3388-3906; Escobar Ibanez, Carlos/0000-0003-4442-4537; Dinu, Ioan-Mihail/0000-0002-2683-7349; Meloni, Federico/0000-0001-7075-2214; Volkotrub, Yuriy/0000-0002-3114-3798; Rompotis, Nikolaos/0000-0003-2577-1875; Grinstein, Sebastian/0000-0002-6460-8694; Koffas, Thomas/0000-0001-9612-4988; Bruschi, Marco/0000-0002-4319-4023; Pleier, Marc-Andre/0000-0002-9461-3494; Mclean, Christine/0000-0002-7450-4805; Iuppa, Roberto/0000-0001-5038-2762; Kretzschmar, Jan/0000-0002-8515-1355; Chwastowski, Janusz/0000-0002-6190-8376; Bouhova-Thacker, Evelina/0000-0002-5103-1558; De La Torre Perez, Hector/0000-0002-4516-5269; Moser, Brian/0000-0001-6750-5060; Onyisi, Peter/0000-0003-4201-7997; Novak, Tadej/0000-0002-3053-0913; Doglioni, Caterina/0000-0002-1509-0390; Konstantinidis, Nikolaos/0000-0002-4140-6360; Camarda, Stefano/0000-0003-0479-7689; Das, Sruthy Jyothi/0000-0003-2693-3389; Price, Darren/0000-0003-2750-9977; Schmitt, Stefan/0000-0001-8387-1853; Vincter, Manuella/0000-0002-5338-8972; Panizzo, Giancarlo/0000-0002-0352-4833; Mondal, Santu/0000-0002-6965-7380; Haley, Joseph/0000-0002-6938-7405; Munoz Sanchez, Francisca/0000-0002-6374-458X; Azuelos, Georges/0000-0003-4241-022X; Chu, Ming-Chung/0000-0002-1971-0403; Mlinarevic, Marin/0000-0003-3587-646X; Martoiu, Sorin/0000-0002-4963-9441; Butterworth, Jonathan/0000-0002-5905-5394; Vigl, Matthias/0000-0003-2281-3822; Montella, Alessandro/0000-0002-5578-6333; Di Luca, Andrea/0000-0002-9074-2133; Sciandra, Andrea/0000-0001-7163-501X; Quinn, Ryan/0000-0002-0879-6045; Kowalewski, Robert/0000-0002-7314-0990; Barakat, Marawan/0000-0001-5740-1866; Stark, Giordon/0000-0001-6616-3433; Aad, Georges/0000-0002-6665-4934; Martin Dit Latour, Bertrand/0000-0003-3420-2105; Keeler, Richard/0000-0002-0510-4189; Jia, Jiangyong/0000-0002-5725-3397; Cunha Sargedas Sousa, Mario Jose/0000-0001-7991-593X; Ghosh, Aishik/0000-0003-0819-1553; Beck, Hans Peter/0000-0001-7212-1096; Alimonti, Gianluca/0000-0002-7128-9046; Winter, Benedict Tobias/0000-0001-9606-7688; Lacasta, Carlos/0000-0002-2623-6252; Santra, Arka/0000-0003-4644-2579; Rousseau, David/0000-0001-7613-8063; Cheu, Elliott/0000-0002-2562-9724; Carmignani, Joseph (Joe)/0000-0002-1705-1061; Bella, Gideon/0000-0002-4009-0990; Worm, Steven/0000-0002-3865-4996; Sahinsoy, Merve/0000-0002-7400-7286; Dong, Qichen/0000-0002-0117-7831; Ernani Martins Neto, Daniel/0000-0003-2793-5335; Hoppesch, Matthew/0000-0002-7773-3654; Umaka, Ejiro/0000-0001-7725-8227; Klein, Lucas/0000-0002-0145-4747; Onofre, Antonio/0000-0003-3471-2703; Varvell, Kevin/0000-0003-1017-1295; Vecchio, Valentina/0000-0002-1351-6757; Berta, Peter/0000-0003-0780-0345; Mcpherson, Robert/0000-0001-9211-7019; Bhatta, Somadutta/0000-0002-9045-3278; Stanislaus, Beojan/0000-0001-9007-7658; Kumar, Mukesh/0000-0003-3681-1588; Martinez-Agullo, Pablo/0000-0001-8925-9518; Smirnova, Oxana/0000-0003-2517-531X; Citron, Zvi/0000-0003-1831-6452; Yabsley, Bruce/0000-0002-2680-0474; Su, Dong/0000-0001-6980-0215; Affolder, Anthony/0000-0002-9058-7217; Elsing, Markus/0000-0002-1213-0545; Kaji, Toshiaki/0000-0002-6532-7501; Cheong, Sanha/0000-0002-2797-6383; Beau, Tristan/0000-0002-2022-2140; Jackson, Paul/0000-0002-0847-402X; Cranmer, Kyle/0000-0002-5769-7094; Hance, Michael/0000-0001-8392-0934; Lloyd, Stephen/0000-0002-5073-2264; Bahmani, Marzieh/0000-0003-4173-0926; Islam, Wasikul/0000-0002-5624-5934; Fox, Harald/0000-0003-3089-6090; Held, Alexander/0000-0002-8924-5885; Mitsou, Vasiliki A./0000-0002-1533-8886; Bona, Marcella/0000-0002-9660-580X; Gwilliam, Carl/0000-0002-9401-5304; Mckee, Shawn/0000-0002-4551-4502; Ahmadov, Faig/0000-0003-3644-540X; Cristoforetti, Marco/0000-0002-0127-1342; Kontaxakis, Pantelis/0000-0002-4860-5979; Sampsonidou, Despoina/0000-0003-0384-7672; Sadrozinski, Hartmut/0000-0003-0019-5410; Koch, Simon Florian/0000-0002-2676-2842;This paper presents the measurement of charged-hadron and identified-hadron (K-S(0), Lambda, Xi(-)) yields in photonuclear collisions using 1.7 nb(-1) of root s(NN) = 5.02 TeV Pb + Pb data collected in 2018 with the ATLAS detector at the Large Hadron Collider. Candidate photonuclear events are selected using a combination of tracking and calorimeter information, including the zero-degree calorimeter. The yields as a function of transverse momentum and rapidity are measured in these photonuclear collisions as a function of charged-particle multiplicity. These photonuclear results are compared with 0.1nb(-1) of root s(NN) = 5.02 TeV p + Pb data collected in 2016 by ATLAS using similar charged-particle multiplicity selections. These photonuclear measurements shed light on potential quark-gluon plasma formation in photonuclear collisions via observables sensitive to radial flow, enhanced baryon-to-meson ratios, and strangeness enhancement. The results are also compared with the Monte Carlo DPMJET-III generator and hydrodynamic calculations to test whether such photonuclear collisions may produce small droplets of quark-gluon plasma that flow collectively.CERN; NDGF (Denmark, Norway, Sweden); KIT/GridKA (Germany); INFN-CNAF (Italy); NL-T1 (Netherlands), PIC (Spain); BNL (USA); ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW; FWF, Austria; ANAS; CNPq; FAPESP, Brazil; NSERC; CFI, Canada; NSFC, China; MEYS CR, Czech Republic; DNRF; DNSRC, Denmark; IN2P3-CNRS; CEA-DRF/IRFU, France; BMBF; MPG, Germany; RGC and Hong Kong SAR, China; ICHEP; Academy of Sciences and Humanities, Israel; INFN, Italy; MEXT; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW, Poland; FCT, Portugal; MNE/IFA, Romania; MSSR, Slovakia; Wallenberg Foundation, Sweden; SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; STFC/UKRI, United Kingdom; DOE; NSF; BCKDF; CANARIE; CRC; DRAC, Canada; FORTE; PRIMUS, Czech Republic; ERC; ERDF; Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex; ANR, France; DFG; AvH Foundation, Germany - EU-ESF; Greek NSRF, Greece; BSF-NSF; NCN [UMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, UMO-2022/47/O/ST2/00148, UMO-2023/49/B/ST2/04085, UMO-2023/51/B/ST2/00920, UMO-2024/53/N/ST2/00869]; La Caixa Banking Foundation; CERCA Programme Generalitat de Catalunya; PROMETEO; Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; Royal Society [NIF-R1-231091]; Leverhulme Trust, United Kingdom; Armenia: Yerevan Physics Institute (FAPERJ); CERN: European Organization for Nuclear Research; Chile: Agencia Nacional de Investigacion y Desarrollo; FONDECYT [1240864]; China: Chinese Ministry of Science and Technology [MOST-2023YFA1605700, MOST-2023YFA1609300]; National Natural Science Foundation of China; NSFC [12275265]; Czech Republic: Czech Science Foundation; GACR [24-11373S]; Ministry of Education Youth and Sports [ERC-CZ-LL2327, FORTE CZ.02.01.01/00/22_008/0004632]; PRIMUS Research Programme [PRIMUS/21/SCI/017]; EU: H2020 European Research Council; European Union: European Research Council; BARD [101116429]; European Regional Development Fund [SMASH COFUND 101081355]; (SLO ERDF); Horizon 2020 Framework Programme [MUCCA-CHIST-ERA-19XAI-00]; European Union [FAIR-NextGenerationEU PE00000013, EuroHPC-EHPC-DEV-2024D11-051]; Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC); France: Agence Nationale de la Recherche [ANR-21-CE31-0013, ANR-21-CE31-0022]; Germany: Baden-Wurttemberg Stiftung [BW Stiftung-Postdoc Eliteprogramme]; Deutsche Forschungsgemeinschaft [DFG-469666862, DFG-CR 312/5-2]; China: Research Grants Council (GRF); Istituto Nazionale di Fisica Nucleare (ICSC); Ministero dell'Universita e della Ricerca [PRIN20223N7F8K M4C2.1.1]; Japan Society for the Promotion of Science; JSPS KAKENHI [JP23KK0245]; Norway: Research Council of Norway [RCN-314472]; Ministry of Science and Higher Education [9722]; Polish National Science Centre; NCN OPUS [2022/47/B/ST2/03059]; Portugal: Foundation for Science and Technology (FCT); Spain: Generalitat Valenciana (Artemisa, FEDER) [IDIFEDER/2018/048]; Ministry of Science and Innovation (MCIN ; NextGenEU Grant) [PCI2022-135018-2]; MICIN FEDER [PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273-I]; Carl Trygger Foundation (Carl Trygger Foundation CTS) [22:2312]; Swedish Research Council (Swedish Research Council) [2023-04654, VR 2021-03651, VR 2022-03845]; VR [2022-04683, VR 2023-03403, VR 2024-05451]; Knut and Alice Wallenberg Foundation [KAW 2018.0458, KAW 2022.0358]; Swiss National Science Foundation; SNSF [PCEFP2_194658]; United Kingdom: Leverhulme Trust (Leverhulme Trust) [RPG-2020-004]; United States of America; U.S. Department of Energy; ECA [DE-AC02-76SF00515]; Neubauer Family FoundationWe thank CERN for the very successful operation of the LHC and its injectors, as well as the support staff at CERN and at our institutions worldwide without whom ATLAS could not be operated efficiently. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF/SFU (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide, and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [55]. We gratefully acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ICHEP and Academy of Sciences and Humanities, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW, Poland; FCT, Portugal; MNE/IFA, Romania; MSTDI, Serbia; MSSR, Slovakia; ARIS and MVZI, Slovenia; DSI/NRF, South Africa; MICIU/AEI, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; TENMAK, Turkiye; STFC/UKRI, United Kingdom; DOE and NSF, USA. Individual groups and members have received support from BCKDF, CANARIE, CRC and DRAC, Canada; CERN-CZ, FORTE and PRIMUS, Czech Republic; COST, ERC, ERDF, Horizon 2020, ICSC-NextGenerationEU and Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. In addition, individual members acknowledge support from Armenia: Yerevan Physics Institute (FAPERJ); CERN: European Organization for Nuclear Research (CERN DOCT); Chile: Agencia Nacional de Investigacion y Desarrollo (Grants No. FONDECYT 1230812, No. FONDECYT 1230987, and No. FONDECYT 1240864); China: Chinese Ministry of Science and Technology (Grants No. MOST-2023YFA1605700 and No. MOST-2023YFA1609300), National Natural Science Foundation of China (Grants No. NSFC 12175119 and No. NSFC 12275265); Czech Republic: Czech Science Foundation (Grant No. GACR 24-11373S), Ministry of Education Youth and Sports (ERC-CZ-LL2327, FORTE CZ.02.01.01/00/22_008/0004632), PRIMUS Research Programme (PRIMUS/21/SCI/017); EU: H2020 European Research Council (Grant No. ERC 101002463); European Union: European Research Council (Grants No. ERC 948254, No. ERC 101089007, and No. ERC, BARD, 101116429), European Regional Development Fund (SMASH COFUND 101081355, SLO ERDF), Horizon 2020 Framework Programme (MUCCA-CHIST-ERA-19XAI-00), European Union, Future Artificial Intelligence Research (FAIR-NextGenerationEU PE00000013), Horizon 2020 (EuroHPC-EHPC-DEV-2024D11-051), Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC, NextGenerationEU); France: Agence Nationale de la Recherche (Grants No. ANR-21-CE31-0013, No. ANR-21-CE31-0022, and No. ANR-22-EDIR-0002); Germany: Baden-Wurttemberg Stiftung (BW Stiftung-Postdoc Eliteprogramme), Deutsche Forschungsgemeinschaft (Grants No. DFG-469666862 and No. DFG-CR 312/5-2); China: Research Grants Council (GRF); Italy: Istituto Nazionale di Fisica Nucleare (ICSC, NextGenerationEU), Ministero dell'Universita e della Ricerca (NextGenEU PRIN20223N7F8K M4C2.1.1); Japan: Japan Society for the Promotion of Science (Grants No. JSPS KAKENHI JP22H01227, No. JSPS KAKENHI JP22H04944, No. JSPS KAKENHI JP22KK0227, and No. JSPS KAKENHI JP23KK0245); Norway: Research Council of Norway (Grant No. RCN-314472); Poland: Ministry of Science and Higher Education (IDUB AGH, POB8, D4 No. 9722), Polish National Science Centre (Grants No. NCN 2021/42/E/ST2/00350, No. NCN OPUS 2023/51/B/ST2/02507, No. NCN OPUS nr 2022/47/B/ST2/03059, No. NCN UMO-2019/34/E/ST2/00393, No. UMO-2020/37/B/ST2/01043, No. UMO-2022/47/O/ST2/00148, No. UMO-2023/49/B/ST2/04085, No. UMO-2023/51/B/ST2/00920, and No. UMO-2024/53/N/ST2/00869); Portugal: Foundation for Science and Technology (FCT); Spain: Generalitat Valenciana (Artemisa, FEDER, Grant No. IDIFEDER/2018/048), Ministry of Science and Innovation (MCIN ; NextGenEU Grant No. PCI2022-135018-2, MICIN ; FEDER Grants No. PID2021-125273NB, No. RYC2019-028510-I, No. RYC2020-030254-I, No. RYC2021-031273-I, and No. RYC2022-038164-I); Sweden: Carl Trygger Foundation (Carl Trygger Foundation CTS Grant No. 22:2312), Swedish Research Council (Swedish Research Council Grants No. 2023-04654, No. VR 2021-03651, No. VR 2022-03845, No. VR 2022-04683, No. VR 2023-03403, No. VR 2024-05451), Knut and Alice Wallenberg Foundation (Grants No. KAW 2018.0458, No. KAW 2022.0358, and No. KAW 2023.0366); Switzerland: Swiss National Science Foundation (Grant No. SNSF PCEFP2_194658); United Kingdom: Leverhulme Trust (Leverhulme Trust Grant No. RPG-2020-004), Royal Society (Grant No. NIF-R1-231091); United States of America: U.S. Department of Energy (Grant No. ECA DE-AC02-76SF00515), Neubauer Family Foundation