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Search for heavy long-lived charged particles with large ionization energy loss in proton-proton collisions at = 13 TeV
No full textAbstract A search for heavy, long-lived, charged particles with large ionization energy loss within the silicon tracker of the CMS experiment is presented. A data set of proton-proton collisions at a center of mass energy at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msqrt> <mml:mi>s</mml:mi> </mml:msqrt> </mml:math> = 13 TeV, collected in 2017 and 2018 at the CERN LHC, corresponding to an integrated luminosity of 101 fb −1, is used in this analysis. Two different approaches for the search are taken. A new method exploits the independence of the silicon pixel and strips measurements, while the second method improves on previous techniques using ionization to determine a mass selection. No significant excess of events above the background expectation is observed. The results are interpreted in the context of the pair production of supersymmetric particles, namely gluinos, top squarks, and tau sleptons, and of the Drell-Yan pair production of fourth generation (τ′) leptons with an electric charge equal to or twice the absolute value of the electron charge (e). An interpretation of a Z’ boson decaying to two τ′ leptons with an electric charge equal to 2e is presented for the first time. The 95% confidence upper limits on the production cross section are extracted for each of these hypothetical particles.https://doi.org/10.1007/jhep04(2025)109https://dx.doi.org/10.3204/pubdb-2024-06826https://dx.doi.org/10.5445/ir/1000184038https://dx.doi.org/10.18154/rwth-2025-08457https://dx.doi.org/10.3204/pubdb-2025-02087https://dx.doi.org/10.18154/rwth-2025-08418https://dx.doi.org/10.5445/ir/1000184039https://dx.doi.org/10.48550/arxiv.2410.09164https://dx.doi.org/10.3929/ethz-b-000748859http://arxiv.org/abs/2410.09164http://hdl.handle.net/10261/403131https://doaj.org/article/a249c56597b94344b4e8905b95eea15dhttps://hdl.handle.net/11368/3108699https://doi.org/10.1007/JHEP04(2025)109https://hdl.handle.net/20.500.12831/27050http://dx.doi.org/10.13039/501100000781http://dx.doi.org/10.13039/501100000780http://dx.doi.org/10.13039/501100011033http://dx.doi.org/10.13039/100011941https://bib-pubdb1.desy.de/record/617495https://bib-pubdb1.desy.de/record/631972https://hdl.handle.net/10281/576382https://hal.science/hal-05061557v1https://doi.org/10.5445/IR/1000184038https://publikationen.bibliothek.kit.edu/1000184038https://publikationen.bibliothek.kit.edu/1000184038/164037310https://publikationen.bibliothek.kit.edu/1000184039https://publikationen.bibliothek.kit.edu/1000184039/164037623https://doi.org/10.5445/IR/1000184039https://hdl.handle.net/11589/288842https://hdl.handle.net/11384/154951https://hdl.handle.net/20.500.12713/7443https://www.webofscience.com/wos/woscc/full-record/WOS:001489180100001http://hdl.handle.net/20.500.11850/748859https://publications.rwth-aachen.de/record/1019536https://publications.rwth-aachen.de/record/101961
How does team reflexivity affect new generation employee cooperative behavior in China? A cross-level moderated mediation model
No full textIntroductionEmployee cooperative behavior is crucial for enterprises navigating uncertainty in the rapidly evolving digital era. Drawing on social information processing theory, this study examines the impact of team reflexivity on employee cooperative behavior, with a focus on the mediating role of organizational trust and the moderating role of employee involvement climate.MethodsA cross-level moderated mediation model was developed and tested using survey data from 412 employees across 84 project teams in China. Hierarchical linear modeling (HLM) was employed to analyze the proposed relationships.ResultsThe findings reveal that: (1) Team reflexivity significantly enhances employee cooperative behavior. (2) Organizational trust mediates the relationship between team reflexivity and employee cooperative behavior. (3) Employee involvement climate moderates the indirect effect, such that the mediation effect of organizational trust is stronger in teams with a higher level of employee involvement.DiscussionThese results contribute to the understanding of how team reflexivity fosters cooperation among employees, highlighting the critical role of trust and the influence of organizational climate. The study provides theoretical and practical implications for fostering teamwork and trust in dynamic work environments.https://doi.org/10.3389/fpsyg.2025.1365026https://pubmed.ncbi.nlm.nih.gov/40212305http://dx.doi.org/10.3389/fpsyg.2025.1365026https://doaj.org/article/31b9f10eb7354f1ba94ffa64071d950
The effect of the important variables for the design novel milli-channel cooling system on the evaporator performance by the Taguchi method
No full texthttps://doi.org/10.1007/s10973-024-13894-yhttps://avesis.yildiz.edu.tr/publication/details/1089102f-3368-490a-9651-ada6335731fc/oa
Enhanced sonophotocatalytic degradation of phthalate acid ester using copper-chromium layered double hydroxides on carbon nanotubes and biochar
No full textLayered double hydroxides (LDHs) are lamellar and stable nanocatalysts driven by visible light. They have received much attention in the context of advanced oxidation processes. Their catalytic performance is remarkably restricted owing to undesired aggregation and the possibility of electron-hole recombination. To address these issues, we engineered carbon-nanotube (CNT)-and biochar (BC)-based CuCr LDH nanocomposites via a facile hydrothermal method. The synthesized nanocomposites were physically and chemically characterized using various methods. The performances of the BC-CuCr LDH and CNT-CuCr LDH nanocomposites were compared during the sonophotocatalytic degradation of dimethyl phthalate. With 1.5 g L-1 of BC-CuCr LDH, complete degradation of dimethyl phthalate was achieved within 25 min under 50 W light intensity and 150 W ultrasound irradiation with a synergy factor of 14. The critical roles of the hydroxyl and superoxide radicals were confirmed by the addition of several inhibitors. Ultimately, six possible intermediates generated during the sonophotocatalytic process were identified using gas chromatography-mass spectrometry (GCMS).https://doi.org/10.1016/j.ultsonch.2025.107351https://pubmed.ncbi.nlm.nih.gov/40258311http://dx.doi.org/10.1016/j.ultsonch.2025.107351https://doaj.org/article/5866ce883b0948e389d40cecb49c8cb4https://avesis.kocaeli.edu.tr/publication/details/025f9eb9-7e1e-4e27-a573-c84a61da00ec/oa
Hate Speech Detection in the Kazakh Language Utilizing an Attention-Based BERT Model
No full texthttps://doi.org/10.1109/ubmk67458.2025.1120686
Neural network based frequency adaptive digital predistortion of RF power amplifiers
No full texthttps://doi.org/10.1007/s10470-025-02466-
Characterizations of Generalized Z-Flat Spacetimes and F(R,G)-Gravity
No full texthttps://doi.org/10.2139/ssrn.524788
Catalytic oxidation potential of graphene encapsulated iron-based nanocatalysts synthesized via chemical vapor deposition
No full textAbstract In recent years, conventional treatment methods have been reported as insufficient for effectively removing organic substances from water, emphasizing the potential of advanced oxidation processes as a promising solution. Therefore, the aim of this research was to evaluate the catalytic oxidation potential of graphene-encapsulated iron-based nanocatalysts synthesized from iron-containing salts using chemical vapor deposition combined with persulfate/UV-C for the degradation of total organic carbon in surface water. The microstructural and magnetic properties of the synthesized nanocatalysts were determined prior to their use as catalysts for advanced oxidation processes. The analysis results showed a significant total organic carbon removal ability, resulting in a reduction of up to 1.76 mg/L from an initial concentration of 4.55 mg/L under the conditions of pHo = 8.0, T = 25 °C, PS = 0.5 mM, and t = 60 min. Moreover, a decrease in UV254 during all experiments indicated that the organic matter present in the raw water, especially those with aromatic structures, underwent significant transformations during the catalytic processes.https://doi.org/10.1007/s13762-025-06344-1https://hdl.handle.net/20.500.12831/2461
From carotene-rich waste-to-food: Extraction, food applications, challenges and opportunities
No full textBackground: Food waste products of industrial processing pose environmental and economic problems. Although there are existing studies in the current literature regarding the evaluation of carotene-rich waste, there is a need for innovative and up-to-date information on the valorization of these wastes. Scope and approach: This article aims to provide an extensive approach to food waste valorization, extraction of carotenoids from waste including potential sources of functional food ingredients, food applications, and life cycle assessment in terms of carotene-rich wastes. Key findings and conclusions: Recovery of carotene from food waste is an important strategic aim in terms of a sustainable agriculture system and the development of functional foods and natural food colorants. In this sense, various green extraction techniques are used for high yields and the best quality carotenoids. Combining green extraction methods including pulsed electric field (PEF) and ultrasound-assisted extraction (UAE) or pressurized liquid extraction (PLE) and supercritical fluid extraction (SFE) may be an efficient approach. However, research on the extended applications of these carotenoid-rich extracts is scarce, so future studies should focus on their potential use in various food materials. Therefore, further studies are required to cover the current gaps relating to the upcoming valorization of carotenes.https://doi.org/10.1016/j.tifs.2024.104756https://hdl.handle.net/20.500.12831/24841https://avesis.uludag.edu.tr/publication/details/b1373c5d-e181-4b3a-95aa-e1a301d909ce/oaihttps://aperta.ulakbim.gov.tr/record/27997
Integration of Contrastive Predictive Coding and Spiking Neural Networks
No full textThis study examines the integration of Contrastive Predictive Coding (CPC) with Spiking Neural Networks (SNN). While CPC learns the predictive structure of data to generate meaningful representations, SNN mimics the computational processes of biological neural systems over time. In this study, the goal is to develop a predictive coding model with greater biological plausibility by processing inputs and outputs in a spike-based system. The proposed model was tested on the MNIST dataset and achieved a high classification rate in distinguishing positive sequential samples from non-sequential negative samples. The study demonstrates that CPC can be effectively combined with SNN, showing that an SNN trained for classification tasks can also function as an encoding mechanism. Project codes and detailed results can be accessed on our GitHub page: https://github.com/vnd-ogrenme/ongorusel-kodlama/tree/main/CPC_SNN4 pages, 5 figures, 1 table. Accepted at the 2025 33rd Signal Processing and Communications Applications Conference (SIU)https://doi.org/10.1109/siu66497.2025.11112390https://dx.doi.org/10.48550/arxiv.2506.09194http://arxiv.org/abs/2506.09194https://doi.org/10.48550/arXiv.2506.0919