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Turkronicles: Diachronic Resources for the Fast Evolving Turkish Language
No full textOver the past century, the Turkish language has undergone substantial changes, mainly driven by governmental interventions. The relatively rapid linguistic evolution of the Turkish language complicates the processing of historical Turkish documents. In this work, we introduce Turkronicles, which is a diachronic corpus for Turkish derived from the Official Gazette of Türkiye and the records of the Grand National Assembly of Türkiye, spanning the period from 1920 to 2024. Turkronicles contains 46,328 documents and 1.1B tokens, making it an important resource for analyzing the linguistic evolution of Turkish and developing models to process historical Turkish documents. In addition, we develop a library to conduct linguistic analysis on diachronic corpora easily. Furthermore, we train a model to fix OCR errors within the documents. Moreover, we explore how the Turkish vocabulary and the writing conventions have changed since 1920 using our corpus. Our analysis reveals that the vocabulary has changed significantly and multiple spellings exist for several words. Specifically, we show that vocabulary divergence increases over time, as expected. Due to such significant vocabulary change in Turkish over time, similarity between the periods 1920–1929 and 2010–2019 is 57%. Despite the substantial vocabulary changes, we demonstrate that it is possible to identify old Turkish words that have the same meanings with newly coined ones using word embeddings. Regarding writing conventions, we found a noticeable decrease in the use of circumflex. In addition, words ending with the letters ‘-b’ and ‘-d’ have been largely replaced by their counterparts ending with ‘-p’ and ‘-t’, respectively, although the former are still in use. Lastly, we observe an increase in the usage of words that comply with vowel harmony rules as a result of the “purification” process of Turkish Language Reform. Overall, our study quantitatively highlights the dramatic changes in Turkish from various linguistic aspects. © 2025 Elsevier B.V., All rights reserved
A New Concept in Public Relations: A Systematic Review on "Corporate Social Advocacy"
No full textGörece yeni bir kavram olan kurumsal sosyal savunuculuk bireylerin markalara yönelik dönüşen beklentileriyle birlikte önemli bir araştırma ve tartışma alanı yaratmıştır. Toplumun ‘daha yaşanılabilir bir dünya’ için markalardan beklentileri, hem şirketlerin kurumsal sosyal savunuculuk eksenli dönüşümünde belirleyici bir rol üstlenmiş hem de alana yönelik akademik araştırmaları zorunlu hale getirmiştir. Buradan hareketle bu çalışma, bir yandan kurumsal sosyal savunuculuğa ilişkin kavramsal bir değerlendirme ortaya koymayı amaçlarken; diğer yandan akademik alana yönelik araştırmalar üzerine gerçekleştirilen sistematik analiz yoluyla hem akademisyenler hem de şirketlere konuya yönelik bir çerçeve sunmayı hedeflemektedir. Bu amaçla yapılan analiz sonucunda kurumsal sosyal savunuculuğun giderek hem kurumsal yapılar hem de akademik çalışmalar bağlamında önem kazandığı görülmekle beraber, akademik alanda konuya yönelik gerçekleştirilen araştırmalarda yöntemsel eksiklikler tespit edilmiştir. Çalışmanın bir diğer önemli bulgusu, araştırmaların büyük oranda ABD toplumu ve şirketleri üzerine gerçekleştirilmesi dolayısıyla alanın ABD’ye ilişkin literatürle sınırlı kalmış olmasıdı
Search for Higgs Boson Decays Into a Z Boson and a Light Hadronically Decaying Resonance in pp Collisions at S=13 TeV with the ATLAS Detector
No full textA search for decays of the Higgs boson into a Z boson and a light resonance, with a mass of 0.5–3.5 GeV, is performed using the full 140 fb−1 dataset of 13 TeV proton–proton collisions recorded by the ATLAS detector during LHC Run 2. Leptonic decays of the Z boson and hadronic decays of the light resonance are considered. The resonance can be interpreted as a J/ψ or ηc meson, an axion-like particle, or a light pseudoscalar predicted in two-Higgs-doublet models. Due to its low mass, this resonance is produced with a high Lorentz boost in the laboratory frame and therefore reconstructed as a single small-radius jet of hadrons. A neural network is used to correct the Monte Carlo simulation of the total expected background using data from sideband regions. Two additional neural networks are used to distinguish signal from background, enhancing the purity of the signal region. A binned profile-likelihood fit is performed on the final-state invariant mass distribution. No significant excess of events relative to the expected background is observed, and upper limits at 95% confidence level are set on the Higgs boson's branching fraction to a Z boson and a light resonance. The exclusion limit is ∼10% for the lower masses, and increases for higher masses. Upper limits on the effective coupling CZHeff/Λ of an axion-like particle to a Higgs boson and Z boson are also set at 95% confidence level, and range from 0.9 to 2 TeV−1. © 2025 CERN for the benefit of the ATLAS CollaborationMinisterio de Ciencia, Innovación y Universidades, MCIU; Agencia Nacional de Investigación y Desarrollo; BSF-NSF; BNL; Australian Research Council, ARC; Israel Academy of Sciences and Humanities; DRAC; La Caixa Banking Foundation; Centre National pour la Recherche Scientifique et Technique, CNRST; NAWA; Center for African Studies, CAS; Fundação para a Ciência e a Tecnologia, FCT; European Union, Future Artificial Intelligence Research; Göran Gustafssons Stiftelser; European Organization for Nuclear Research; Ministero dell'Università e della Ricerca, MUR; MINERVA , Israel; Polish National Science Centre; Georgia Health Initiative, HGF; Narodowe Centrum Nauki, NCN; Grantová Agentura České Republiky, GACR; National Science Foundation, NSF; Baden-Württemberg Stiftung; Science and Technology Facilities Council, STFC; Carl Tryggers Stiftelse för Vetenskaplig Forskning; H2020 Marie Skłodowska-Curie Actions, MSCM; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, FAPERJ; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO; Ministerio de Ciencia e Innovación, MCIN; Ministry of Science and Innovation; Istituto Nazionale di Fisica Nucleare; Ministry of Science and Higher Education; ICHEP; Leverhulme Trust; Baden-Württemberg Stiftung, BWS; Research Council of Norway; Japan Society for the Promotion of Science; Knut och Alice Wallenbergs Stiftelse; MVZI; PROMETEO; Spine Education and Research Institute, SERI; Neubauer Family Foundation, NFF; The Slovenian Research and Innovation Agency, ARIS; IDUB AGH; Foundation for Science and Technology; Generalitat de Catalunya; Neubauer Family Foundation; Bundesministerium für Wissenschaft, Forschung und Wirtschaft, BMWFW; Austrian Science Fund, FWF; BCKDF; Narodowa Agencja Wymiany Akademickiej, NAWA; GenT Programmes Generalitat Valenciana , Spain; Yerevan Physics Institute; Leverhulme Trust; ERDF; Agencia Nacional de Investigación y Desarrollo, ANID; Bundesministerium für Bildung und Forschung, BMBF; Slovenian Research Agency; Canada Foundation for Innovation, FCI; 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; Horizon 2020 Framework Programme; Göran Gustafssons Stiftelser; Deutsche Forschungsgemeinschaft, DFG; United States-Israel Binational Science Foundation, BSF; Generalitat de Catalunya; European Commission, EC; European Social Fund Plus, FSE; European Cooperation in Science and Technology, COST; EU-ESF; Horizon 2020 , ICSC-NextGenerationEU; COST; CRC; Generalitat Valenciana; International Council of Shopping Centers, ICSC; RGC; Duchenne Research Fund, DRF; Netherlands Organisation for Scientific Research; Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP; PRIMUS; Agencia Estatal de Investigación, AEI; ICSC; ANR; Institutul de Fizică Atomică, IFA; Natural Sciences and Engineering Research Council of Canada, NSERC; Chinese Ministry of Science and Technology; Swiss National Science Foundation; Marie Skłodowska-Curie Actions; National Science and Technology Council, NSTC; EU; FONDECYT; Irish Rugby Football Union, IRFU; Cantons of Bern and Geneva; Agence Nationale de la Recherche; Defence Science Institute, DSI; National Natural Science Foundation of China; MSTDI; Horizon 2020 Framework Programme; MNE; Agencia Nacional de Promoción Científica y Tecnológica, ANPCyT; Royal Society; Minerva Foundation; Marcus och Amalia Wallenbergs minnesfond, MMW; Royal Society; CERN-CZ; National Research Foundation, NRF; Ministerstwo Edukacji i Nauki, MNiSW; FAPERJ; European Research Council; Generalitat Valenciana, GVA; CERN, CERN; Ministerstvo Školství, Mládeže a Tělovýchovy, MEYS; European Union; National Research Council Canada, CNRC; Vetenskapsrådet, VR; Alexander von Humboldt-Stiftung, AvH; Multiple Sclerosis Scientific Research Foundation, MSSRF; DFG; AvH Foundation; Horizon 2020; Istituto Nazionale di Fisica Nucleare, INFN; British Columbia Knowledge Development Fund, BCKDF; CANARIE; Ministry of Education, Culture, Sports, Science and Technology, MEXT; UK Research and Innovation, UKRI; Japan Society for the Promotion of Science, KAKENHI, (JP22KK0227, JP22H04944, JP23KK0245, JP22H01227); Japan Society for the Promotion of Science, KAKENHI; National Natural Science Foundation of China, NSFC, (12275265, 12175119, NSFC-12075060); National Natural Science Foundation of China, NSFC; Center for Advancing Research Impact in Society, ARIS, (J1-3010); Center for Advancing Research Impact in Society, ARIS; European Regional Development Fund, EFRR, (IDIFEDER/2018/048); European Regional Development Fund, EFRR; Norges Forskningsråd, (RCN-314472); Norges Forskningsråd; H2020 European Research Council, (ERC - 101002463); FEDER, (IDIFEDER/2018/048); NCN, (2021/42/E/ST2/00350, 2023/51/B/ST2/02507, 2022/47/B/ST2/03059, UMO-2023/51/B/ST2/00920, H2020 MSCA 945339, UMO-2021/40/C/ST2/00187, UMO-2022/47/O/ST2/00148, UMO-2023/49/B/ST2/04085, UMO-2020/37/B/ST2/01043, UMO-2019/34/E/ST2/00393); Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNSF, (PCEFP2_194658, RPG-2020-004, NIF-R1-231091); Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNSF; Ministry of Education Youth and Sports, (ERC-CZ-LL2327); FORTE, (CZ.02.01.01/00/22_008/0004632, PRIMUS/21/SCI/017); North Dakota Game and Fish Department, NDGF, (CC-IN2P3); North Dakota Game and Fish Department, NDGF; Swedish Research Council, (VR 2021-03651, VR 2018-00482, VR 2022-03845, VR 2023-03403, 2023-04654, VR 2022-04683); Polish National Agency for Academic Exchange, (PPN/PPO/2020/1/00002/U/00001); Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYT, (1240864, 1230987, 1230812); Fondo Nacional de Desarrollo Científico y Tecnológico, FONDECYT; 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; DNSRC, (IN2P3-CNRS); 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; FAIR-NextGenerationEU, (PE00000013); U.S. Department of Energy, ENERGYGOV, (ECA DE-AC02-76SF00515); U.S. Department of Energy, ENERGYGOV; NextGenerationEU, NGEU, (PE00000013); NextGenerationEU, NGEU; Ministero dell'Università e della Ricerca, (I53D23000820006 M4C2.1.1); European Research Council, ERC, (101089007, 948254); European Research Council, ERC; Czech Science Foundation, (GACR - 24-11373S); Deutsche Forschungsgemeinschaft, (DFG - CR 312/5-2, DFG - 469666862); Knut and Alice Wallenberg Foundation, (KAW 2018.0458, KAW 2019.0447, KAW 2022.0358); Carl Trygger Foundation, (CTS 22:2312); H2020 European Research Council, CER, (ERC - 101002463); H2020 European Research Council, CER; ERC, (101089007); MUCCA, (CHIST-ERA-19-XAI-00); MCIN, (RYC2020-030254-I, RYC2021-031273-I, PCI2022-135018-2, RYC2022-038164-I, PID2021-125273NB, RYC2019-028510-I); U.S. Department of Energy, (ECA DE-AC02-76SF00515
Düşük Işık Görüntü İyileştirme Tekniklerinin Karşılaştırılması İçin Kapsamlı Çok Düzeyli Düşük Işık Video Veri Seti
No full textIsik UniversityImages taken indoor and/or outdoor can suffer from adverse effects when there is inadequate lighting in the environment. The overall efficacy of computer vision systems may be compromised due to the resultant low dynamic range and elevated noise levels in the images. To overcome this problem, many traditional and deep learning-based enhancement methods have been employed. In terms of deep learning models, to achieve better results, the deep models need to be trained with good quality and rich datasets. Although there are many low-light static image datasets in the literature, there is a lack of multi-level low light image/video dataset. For a live video captured in a low-light environment, the level of the light naturally can change with respect to time. Therefore, the model should also adopt to those different level of low-light conditions. In this study, a new multi-level low-light video dataset is presented. This dataset includes 3 different scenes captured with a color camera under different levels of light. By using this dataset, in this study several state-of-the-art low-light image enhancement methods are tested and compared. © 2025 Elsevier B.V., All rights reserved
Ultrastructural Changes in the Striatum of the Slitrk5-/-Mouse Model of Obsessive-Compulsive Disorder Using Volume Electron Microscopy
No full textStudies in obsessive-compulsive disorder have suggested rare, damaging coding variants in the SLIT and NTRKlike family member 5 (Slitrk5) gene as possible contributors to the disorder. Here we identify previously unrecognized pathological changes in the dorsomedial striatum of a Slitrk5 knockout mouse model using serial block-face scanning electron microscopy. Following a combination of manual annotation and automatic segmentation, detailed 2D and 3D analyses of myelin, axons, and mitochondria revealed ultrastructural abnormalities in the myelinated axons resembling Wallerian degeneration challenging the current understanding of Slitrk5 ' s role, extending its importance beyond neurite outgrowth to maintaining axonal integrity. Additionally, we observed a marked reduction in the g-ratio, reduced node of Ranvier volume, as well as activated microglial phagocytosis of myelin debris indicating potential neuroinflammatory processes. These results suggest that the absence of Slitrk5 heightens the vulnerability of myelinated axons to degenerative processes, providing new insights into the molecular underpinnings of obsessive-compulsive disorder. Our findings emphasize the need to reconsider Slitrk5 ' s neuroprotective function and lay the foundation for further research on its role in other brain regions and its broader implications for neurodegenerative diseases.Sino-Danish Centre for Research and Education; Jascha Fonden, and Torben og Alice Frimodt FondenThis work was supported by Sino-Danish Centre for Research and Education, A.P. M ; oslash;ller Fonden, Jascha Fonden, and Torben og Alice Frimodt Fonden. The funders had no involvement in the study design, data collection, analysis, manuscript preparation, or decision to publish
A LoRa Based Method for Efficient Model Parameter Reduction
No full textThis paper presents an efficient model parameter reduction technique that is applicable across a wide range of neural network architectures, including convolutional neural networks (CNNs) and transformer-based models. Motivated by the LoRA (low-rank adaptation) method originally proposed for efficiently fine-tuning transformer architectures, the presented technique aims to enhance model parameter efficiency by leveraging a generalized approach that can be seamlessly integrated into virtually any network architecture. Extensive experiments with state-of-the-art CNN and transformer models demonstrate the robustness and versatility of the proposed technique in improving model parameter efficiency by achieving the same level of accuracy while using almost half as many parameters. The results highlight potential of this method as a universal optimization strategy for modern deep learning frameworks, offering a valuable tool for practitioners and researchers seeking to lower computation load and memory usage of deep models during inference. © 2025 Elsevier B.V., All rights reserved
Ethical Dilemma in Psychiatry: Real Cases Scenario
No full textPsychiatry is a field that differs from other fields of medical practice in terms of its ethical problems and ethical dilemmas it encounters. The physicians who specialize in the field of psychiatry or health professionals who work in mental health services should be equipped to recognize these ethical problems, to deal with them in the right ethical frameworks and to offer practical and appropriate solutions in their clinical practice. The work compiles extensive experiences from Medical Faculty of Ankara University, Turkey. The book aims to give a comprehensive understanding about the particular ethical problems and dilemmas in psychiatry and provide tools and methods to approach them in an ethically appropriate way. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Search for Pair-Production of Vector-Like Quarks in Lepton Plus Jets Final States Containing at Least One B-Tagged Jet Using the Run 2 Data From the Atlas Experiment
No full textA search is presented for the pair-production of heavy vector-like quarks in the lepton+jets final state using 140 fb-1 of proton-proton collisions at root s = 13 TeV collected with the ATLAS detector. The search is optimised for vector-like top-quarks (T) that decay into a W boson and a b-quark, with one W boson decaying leptonically and the other hadronically. Other vector-like quark flavours and decay modes are also considered. Events are selected with one high transverse-momentum electron or muon, large missing transverse momentum, a large-radius jet identified as a W boson, and multiple small-radius jets, at least one of which is b-tagged. Vector-like b-quarks with 100% branching ratio to W b are excluded at 95% CL for masses below 1700 GeV. These limits are also applied to vector-like Y-quarks, which decay exclusively into a W boson and a b-quark. Isospin singlets with B(T -> W b : Ht : Zt) = 1/2 : 1/4 : 1/4 are excluded for masses below 1360 GeV
Localization in Massive Mimo Networks: From Far-Field To Near-Field
No full textSource localization is the process of estimating the location of signal sources based on the signals received at different antennas of an antenna array. It has diverse applications, ranging from radar systems and underwater acoustics to wireless communication networks. Subspace-based approaches are among the most effective techniques for source localization due to their high accuracy, with Multiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT) being two prominent methods in this category. These techniques leverage the fact that the space spanned by the eigenvectors of the covariance matrix of the received signals can be divided into signal and noise subspaces, which are mutually orthogonal. Originally designed for far-field source localization, these methods have undergone several modifications to accommodate near-field scenarios as well. This chapter aims to present the foundations of MUSIC and ESPRIT algorithms and introduce some of their variations for both far-field and near-field localization by a single array of antennas. We further provide numerical examples to demonstrate the performance of the presented methods. © 2025 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved
Temporal Lobe Epilepsy Focus Detection Based on the Correlation Between Brain Mr Images and Eeg Recordings With a Decision Tree
No full textKocak, Onur/0000-0002-8240-4046; Ficici, Cansel/0000-0002-3698-6137Background/Objectives: In this study, a medical decision support system is presented to assist physicians in epileptic focus detection by correlating MRI and EEG data of temporal lobe epilepsy patients. Methods: By exploiting the asymmetry in the hippocampus in MRI images and using voxel-based morphometry analysis, gray matter reduction in the temporal and limbic lobes is detected, and epileptic focus prediction is realized. In addition, an epileptic focus is also determined by calculating the asymmetry score from EEG channels. Finally, epileptic focus detection was performed by associating MRI and EEG data with a decision tree. Results: The results obtained from the proposed algorithm provide 100% overlap with the physician's finding on the EEG data. Conclusions: MRI and EEG correlation in epileptic focus detection was improved compared with physicians. The proposed algorithm can be used as a medical decision support system for epilepsy diagnosis, treatment, and surgery planning