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Search for Diphoton Resonances in the 66 to 110 GeV Mass Range Using pp Collisions at (Formula Presented.) TeV with the ATLAS Detector
No full textA search is performed for light, spin-0 bosons decaying into two photons in the 66 to 110 GeV mass range, using 140 fb−1 of proton-proton collisions at s = 13 TeV produced by the Large Hadron Collider and collected by the ATLAS detector. Multivariate analysis techniques are used to define event categories that improve the sensitivity to new resonances beyond the Standard Model. A model-independent search for a generic spin-0 particle and a model-dependent search for an additional low-mass Higgs boson are performed in the diphoton invariant mass spectrum. No significant excess is observed in either search. Mass-dependent upper limits at the 95% confidence level are set in the model-independent scenario on the fiducial cross-section times branching ratio into two photons in the range of 8 fb to 53 fb. Similarly, in the model-dependent scenario upper limits are set on the total cross-section times branching ratio into two photons as a function of the Higgs boson mass in the range of 19 fb to 102 fb. © 2025 Elsevier B.V., All rights reserved
Measurement of Top-Quark Pair Production in Association With Charm Quarks in Proton-Proton Collisions at √s=13 Tev With the Atlas Detector
No full textMcKee, Shawn/0000-0002-4551-4502; /0000-0001-5765-1750; Soto, Orlando/0000-0002-8613-0310; Herrmann, Linda/0000-0002-1857-6310; Petersen, Troels/0000-0003-0221-3037; Zanzottera, Riccardo/0009-0006-5900-2539; Etzion, Erez/0000-0001-6871-7794; Zivkovic, Lidija/0000-0003-4236-8930; Haley, Joseph/0000-0002-6938-7405; Aad, Georges/0000-0002-6665-4934; Giuli, Francesco/0000-0002-8506-274X; Kretzschmar, Jan/0000-0002-8515-1355; Fiorini, Luca/0000-0002-5070-2735; Camplani, Alessandra/0000-0002-6386-9788; Carmignani, Joseph (Joe)/0000-0002-1705-1061; Abicht, Nils Julius/0000-0001-5763-2760; Teixeira-Dias, Pedro/0000-0001-9977-3836; Aboulhorma, Asmaa/0000-0002-9987-2292; Pintucci, Laura/0000-0001-9842-9830; D'Auria, Saverio/0000-0003-3393-6318; Gwilliam, Carl/0000-0002-9401-5304; Mlinarevic, Marin/0000-0003-3587-646X; Abdelhameed, Sara/0000-0002-0287-5869; Mitsou, Vasiliki A./0000-0002-1533-8886; Nasella, Laura/0000-0002-4871-784X; Abramowicz, Halina/0000-0001-5329-6640; Ragusa, Francesco/0000-0002-4064-0489; de la Torre Perez, Hector/0000-0002-4516-5269; Sala, Alessandro/0000-0003-0824-7326; Stanislaus, Beojan/0000-0001-9007-7658; Calafiura, Paolo/0000-0002-1692-1678; Konstantinidis, Nikolaos/0000-0002-4140-6360; Abbott, Braden/0000-0002-5888-2734; Gonnella, Francesco/0000-0003-0885-1654; Rompotis, Nikolaos/0000-0003-2577-1875; Carbone, Antonio/0000-0002-4117-3800; Williams, Scott/0000-0001-7860-8962; Butterworth, Jonathan/0000-0002-5905-5394; Mazzeo, Elena/0000-0002-8406-0195Inclusive cross-sections for top-quark pair production in association with charm quarks are measured with proton-proton collision data at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of 140 fb(-1), collected with the ATLAS experiment at the LHC between 2015 and 2018. The measurements are performed by requiring one or two charged leptons (electrons and muons), two b-tagged jets, and at least one additional jet in the final state. A custom flavor-tagging algorithm is employed for the simultaneous identification of b-jets and c-jets. In a fiducial phase space that replicates the acceptance of the ATLAS detector, the cross-sections for t (t) over bar >= 2c and t (t) over bar + 1c production are measured to be 1.28(- 0.24)(+0.27) pb and 6.4(-0.9)(+1.0) pb, respectively. The measurements are primarily limited by uncertainties in the modeling of inclusive t (t) over bar and t (t) over bar + b (b) over bar production, in the calibration of the flavor-tagging algorithm, and by data statistics. Cross-section predictions from various t (t) over bar simulations are largely consistent with the measured cross-section values, though all underpredict the observed values by 0.5 to 2.0 standard deviations. In a phase-space volume without requirements on the t (t) over bar decay products and the jet multiplicity, the cross-section ratios of t (t) over bar + >= 2c and t (t) over bar + 1c to total t (t) over bar + jets production are determined to be (1.23 +/- 0.25)% and (8.8 +/- 1.3)%.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. [98]. We gratefully acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerba.an; 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; ISF and Benoziyo Center, 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, United States of America. 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, ICSCNextGenerationEU 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 wish to acknowledge support from Armenia: Yerevan Physics Institute (FAPERJ); CERN: European Organization for Nuclear Research (CERN PJAS); Chile: Agencia Nacional de Investigacion y Desarrollo (FONDECYT 1230812, FONDECYT 1230987, FONDECYT 1240864); China: Chinese Ministry of Science and Technology (MOST-2023YFA1605700), National Natural Science Foundation of China (NSFC -12175119, NSFC 12275265, NSFC-12075060); Czech Republic: Czech Science Foundation (GACR -24-11373S), Ministry of Education Youth and Sports (FORTE CZ.02.01.01/00/22_008/0004632), PRIMUS Research Programme (PRIMUS/21/SCI/017); EU: H2020 European Research Council (ERC -101002463); European Union: European Research Council (ERC -948254, ERC 101089007), European Union, Future Artificial Intelligence Research (FAIR-NextGenerationEU PE00000013), Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC, NextGenerationEU); France: Agence Nationale de la Recherche (ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-21-CE31-0022, ANR-22-EDIR-0002); Germany: Baden-Wurttemberg Stiftung (BW Stiftung-Postdoc Eliteprogramme), Deutsche Forschungsgemeinschaft (DFG -469666862, DFG -CR 312/5-2); Italy: Istituto Nazionale di Fisica Nucleare (ICSC, NextGenerationEU), Ministero dell'Universita e della Ricerca (PRIN -20223N7F8K -PNRR M4.C2.1.1); Japan: Japan Society for the Promotion of Science (JSPS KAKENHI JP22H01227, JSPS KAKENHI JP22H04944, JSPS KAKENHI JP22KK0227, JSPS KAKENHI JP23KK0245); Netherlands: Netherlands Organisation for Scientific Research (NWO Veni 2020 -VI.Veni.202.179); Norway: Research Council of Norway (RCN-314472); Poland: Ministry of Science and Higher Education (IDUB AGH, POB8, D4 no 9722), Polish National Agency for Academic Exchange (PPN/PPO/2020/1/00002/U/00001), Polish National Science Centre (NCN 2021/42/E/ST2/00350, NCN OPUS 2023/51/B/ST2/02507, NCN OPUS nr 2022/47/B/ST2/03059, NCN UMO-2019/34/E/ST2/00393, NCN ; H2020 MSCA 945339, UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187, UMO-2022/47/O/ST2/00148, UMO-2023/49/B/ST2/04085, UMO-2023/51/B/ST2/00920); Slovenia: Slovenian Research Agency (ARIS grant J1-3010); Spain: Generalitat Valenciana (Artemisa, FEDER, ID-IFEDER/2018/048), Ministry of Science and Innovation (MCIN ; NextGenEU PCI2022-135018-2, MICIN ; FEDER PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273I, RYC2022-038164-I); Sweden: Carl Trygger Foundation (Carl Trygger Foundation CTS 22:2312), Swedish Research Council (Swedish Research Council 2023-04654, VR 2018-00482, VR 2022-03845, VR 2022-04683, VR 2023-03403, VR grant 2021-03651), Knut and Alice Wallenberg Foundation (KAW 2018.0458, KAW 2019.0447, KAW 2022.0358); Switzerland: Swiss National Science Foundation (SNSF-PCEFP2_194658); United Kingdom: Leverhulme Trust (Leverhulme Trust RPG-2020-004), Royal Society (NIF-R1-231091); United States of America: U.S. Department of Energy (ECA DE-AC02-76SF00515), Neubauer Family Foundation.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; ISF; Benoziyo Center, Israel; INFN, Italy; MEXT; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW, Poland; FCT, Portugal; MNE/IFA, Romania; MSSR, Slovakia; SRC; Wallenberg Foundation, Sweden; SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; STFC/UKRI, United Kingdom; DOE; NSF, United States of America; 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; 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) [1230812]; FONDECYT [1240864]; China: Chinese Ministry of Science and Technology [MOST-2023YFA1605700]; National Natural Science Foundation of China [NSFC -12175119, NSFC 12275265, NSFC-12075060]; Czech Republic: Czech Science Foundation; Ministry of Education Youth and Sports [FORTE CZ.02.01.01/00/22_008/0004632]; PRIMUS Research Programme [PRIMUS/21/SCI/017]; EU [ERC -101002463]; European Union: European Research Council [ERC -948254, 101089007]; European Union [FAIR-NextGenerationEU PE00000013]; France: Agence Nationale de la Recherche [ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-21-CE31-0022]; Germany: Baden-Wurttemberg Stiftung; Deutsche Forschungsgemeinschaft [DFG -469666862, DFG -CR 312/5-2]; Ministero dell'Universita e della Ricerca; Japan Society for the Promotion of Science (JSPS KAKENHI) [JP22H01227, JP22H04944, JP22KK0227, JP23KK0245, RCN-314472]; Polish National Agency for Academic Exchange [PPN/PPO/2020/1/00002/U/00001]; Polish National Science Centre (NCN) [2021/42/E/ST2/00350]; NCN OPUS [2022/47/B/ST2/03059, UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187, UMO-2022/47/O/ST2/00148, UMO-2023/49/B/ST2/04085, UMO-2023/51/B/ST2/00920]; Slovenian Research Agency [J1-3010]; Spain: Generalitat Valenciana; FEDER [ID-IFEDER/2018/048, NextGenEU PCI2022-135018-2]; MICIN FEDER [PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273I]; Carl Trygger Foundation; Swedish Research Council (Swedish Research Council) [2023-04654, VR 2018-00482, VR 2022-03845, VR 2022-04683, VR 2023-03403, 2021-03651]; Knut and Alice Wallenberg Foundation [KAW 2018.0458, KAW 2019.0447, SNSF-PCEFP2_194658]; Leverhulme Trust (Leverhulme Trust) [RPG-2020-004]; United States of America; Neubauer Family Foundatio
Design and Empirical Validation of a Low-Cost Outdoor Mmwave Altimetry Test Bench for Uas
No full textDalveren, Yaser/0000-0002-9459-0042The increasing adoption of unmanned aerial systems (UAS) in diverse urban applications necessitates reliable and precise altimetry solutions for situational awareness and landing safety. Despite significant advancements in the realm of waveform design and signal processing, empirical validation of millimeter wave (mmWave) Frequency Modulated Continuous Wave (FMCW) waveforms for altimetry use case remains a critical gap in literature. This study argues the necessity of empirical validation of candidate FMCW waveforms by proposing an inexpensive and practical outdoor test bench. The multipath propagation model for the said test bench is presented along with a simplified testing methodology suitable for implementation on contemporary mmWave automotive radars. The specifics of the test bench are deliberated where a flat concrete wall with a sufficiently large surface area is employed as a static target. The underpinnings established by this body of work shall serve dynamic testing on a drone platform against various terrain types in the next phase of research. The experimental results demonstrate the potential of practical use of mmWave altimetry on UAS in urban deployment
Two Birds, One Stone: Minimum Wage and Child Labor
No full textPurpose: This paper investigates the impact of quasi-exogenous and substantial increases in the minimum wage on child labor outcomes in Türkiye. The study aims to provide empirical evidence on how minimum wage policies affect child labor outcomes in a developing country context, with a focus on gender and age differences. It seeks to understand whether minimum wage increases lead to a reduction in child labor and whether the impact is different for various demographic groups. Design/methodology/approach: The research employs a difference-in-differences methodology using data from the 2012 and 2019 Child Labor Force Survey in Türkiye. The treatment group consists of children from households with minimum wage earners, while the control group comprises children from other households. Various labor market outcomes are analyzed, and robustness checks are performed. Findings: Our findings indicate that while the overall effect of minimum wage increases on child labor is statistically insignificant, there are notable heterogeneous impacts across different demographic groups and employment sectors. Specifically, we observe a significant reduction in the employment probability of girls under the age of 15 and unpaid family workers. Additionally, the likelihood of younger children being wage earners decreases, and the minimum wage increase reduces employment in the agriculture and services sectors for certain subgroups. The impact is also more limited for children in single-adult-worker households. Social implications: These results underscore the varying effects of minimum wage policies on child labor and highlight the importance of considering demographic and sectoral differences in policy formulation. Policymakers should complement such policies with income-generating programs and targeted education initiatives to address child labor issues more comprehensively and sustainably. Originality/value: This study fills a critical gap in the limited international literature on the causal effects of minimum wage policies on child labor incidence. One notable exception, Menon and van der Meulen Rodgers (2018) have explored the impact of minimum wage on child labor in India using regional variation, our study uniquely analyzes the effects at the household level in Türkiye. This approach provides valuable insights into how minimum wage changes affect child labor outcomes in a developing economy context with a high prevalence of minimum wage earners. It also contributes to the broader economic understanding of child labor and household income dynamics. © 2024, Emerald Publishing Limited.TOBB-ETU; Economic Research Forum, ER
A New Rank Estimator for Least Squares Estimation of Weibull Modulus
No full textThe Weibull distribution is widely used in reliability analysis to evaluate the failure behavior and lifetime characteristics of various systems and components. One of the most commonly used methods for estimating the parameters of the Weibull distribution is the ordinary least squares (OLS) technique, which is based on fitting a linear regression model to the transformed data. This paper proposes a new rank estimator for ordinary least squares estimation of Weibull modulus, a key parameter used as a measure of variability in the data. The new rank estimator is a quadratic function of the ranks of order statistics, with three parameters that are optimized by Monte Carlo simulations. Using relative efficiency as a criterion, the performance of the new rank estimator is compared with three commonly used rank estimators, mean, median and Hazen rank estimators, which are linear functions of the ranks of order statistics. The results show that the new rank estimator has a significant advantage over the other rank estimators for any sample size between 3 and 150. The findings also imply that other nonlinear functions, such as cubic polynomials, could be applied to further improve the efficiency of the parameter estimators of the ordinary least squares method
Identifying Risk Factors for Open Reduction in Pediatric Supracondylar Humerus Fractures
No full textBrainit: A Generic IT Core Mechanism for Continuous Growth-Flow in Dynamic Chaotic Context
No full textAmerican Council on Science and EducationBrain CAPEX (Capital Expenses) is for free to the human being but the OPEX (Operational Expenses) is not. Since, the fluctuations on critical nutrition for brain makes it complicated to grow via optimal path as continues progress due to the chaotic OPEX changes. Fortunately, intelligent systems are able to adapt the change dynamically up to varying chaotic context, by keeping trustworthiness of the whole system via available distributed resources and algorithms. However, increasing number of nodes in the system inflates complexity of swarm behavior due to computation and memory limitations. Drastic progress saved in the emerging edge devices, can enable to produce innovative trusted AI/ML algorithms at run-time, which can help to make massive analytics at the edge nodes in (near) real time. In spite of this, keeping the system resilient require real-time updates in different system layers. As another critical milestone, increased scalability and faster in memory processing speed can be accomplished via big data technologies and ledger base chained structures in some manner. In order to keep high performance of the total system, mission/safety/operation critical applications require to be verified by critical check-points. Thereby, end-to-end trust mechanism and swarm controller methods can improve trusted scalability of the intelligent systems analytical functions and resources. So that, the dynamic holistic views can ensure trustworthiness in chaotic context with the brainIT generic IT core mechanism for continuous growth in massive-chaos, which ensures to keep local/global legal constraints-based risk minimization via 5G connected hybrid-cloud systems within the observed socio-dynamic parameters with minimized optimal OPEX costs. © 2025 Elsevier B.V., All rights reserved
Artificial Intelligence Based Social Protest Effectiveness Analysis
No full textIsik UniversityCollective action has been employed across various historical contexts to influence societal change. Examples such as the suffragist and civil rights movements in the United States and recent farmers' protests in Europe demonstrate its potential impact. However, predicting protest outcomes remains difficult due to the interaction of multiple factors. In this study, the factors associated with protest success are examined, and a machine learning approach is proposed to estimate their effectiveness. After data rebalancing, outlier removal, and hyperparameter tuning, the Random Forest model achieved 75% accuracy and a 59% F1 score on the Global Protest Tracker dataset. The proposed method is intended to support computational assessments of protest dynamics and to encourage collaboration between social and computational sciences. © 2025 Elsevier B.V., All rights reserved
Effect of Fracture Level on Optimal Kirschner Wire Configuration in Pediatric Supracondylar Humerus Fractures: A Finite Element Analysis
No full textObjectives: This study aims to evaluate the biomechanical stability of three pin configurations for transverse supracondylar humerus fractures at various levels using finite element analysis (FEA). Materials and methods: Computed tomography data from a six-year-old child were used to generate a humerus bone model. Four different fracture levels (low, transolecranon, high, and ultrahigh) and three pin fixation techniques (one lateral and one medial cross-pin [1-1M], two lateral capitellar pins [1-1C], and three lateral capitellar pins [2-1C]) were designed for the study. Translational stiffness and rotational stiffness in all directions were analyzed in the mesh models. Convergence data and stiffness data were obtained in the FEA. Results: The translational and rotational stiffness values varied across fracture levels and pin configurations. Under valgus loading, the 1-1M configuration provided the highest stability in ultrahigh fractures (3289 N/mm), while the 2-1C configuration showed superior valgus and varus stability in low and transolecranon fractures. During extension and flexion loading, the 1-1M configuration yielded the highest stiffness values for transolecranon and high fractures, while the 2-1C configuration demonstrated increased stability in low and ultrahigh fractures. For rotational loading, 1-1M produced the highest inward and outward stiffness values in low-level fractures (9175 and 11035 N·mm/degree, respectively), whereas 2-1C displayed greater rotational stiffness in ultrahigh fractures. Conclusion: This preliminary study suggests that no single pin configuration is ideal for all fracture types, and the choice should be based on the specific fracture case
Isotropy-Conditioned Density Mapping for Lattice Design Using Topology Optimization
No full textHomogenization-based topology optimization methods used for designing graded lattice structures require multiple scaling laws because of the anisotropic elastic properties of cubic lattice cells. In this study, an isotropy-conditioned density mapping (ICDM) approach is presented to define lattice cells with isotropic elastic properties across the full range of relative densities, enabling the use of a single scaling law in density-based topology optimization. Strut radii for different groups within a cubic lattice cell are determined to satisfy an isotropy condition by evaluating homogenized elastic properties over the entire relative density range required for topology optimization. The resulting isotropy-conditioned lattice cells are used for density mapping in topology optimization based on the solid isotropic material with penalization (SIMP) method. The proposed approach is computationally efficient because it enables macroscopic optimization using the standard SIMP method while ensuring that spatially varying mesoscale lattice configurations satisfy isotropy using a single scaling law. The method is demonstrated through two three-dimensional numerical examples to show its efficacy. The improved structural performance of the optimized designs with the isotropy-conditioned lattice cells is shown by comparing their results with the existing designs.Scientific and Technological Research Council of Turkiye (TUBITAK)Open access funding provided by the Scientific and Technological Research Council of Turkiye (TUBITAK)