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  1. 81

    Kinematic links between elements of the caterpillar drive of the tracked military vehicle by S. V. Baglaychuk, V. A. Nekhaev, V. А. Nikolaev

    Published 2017-08-01
    “…On the analysis’ basis of the dynamic processes (continuous (vibratory) and pulsed (striking)) occurring in caterpillar drive and stringing system of the tracked military vehicle, when moving on rough terrain with different carrying capacity and a road bed’s profile, there are determined the equations of kinematic links of the driving wheel with a frame of the tracked machine; aligning wheel with a mechanism of the track’s tension; fastening balancing levers, torsions’ links with the tracked machine’s body.…”
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  2. 82

    Impact of environmental pollution on human health: Investigating the role of Polycyclic Aromatic Hydrocarbons in pediatric osteosarcoma by Mingxian Xu, Yu Xu, Yaping Huang, Jixiang Shi, Lifeng Yin, Jian Tu, Junqiang Yin, Changye Zou

    Published 2025-09-01
    “…Among these, ACTB, EGFR, and JUN were identified as key prognostic genes through survival analysis and machine learning models. These genes were enriched in oncogenic pathways, including the PI3K-Akt signaling pathway. …”
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  3. 83

    Numerical model of cutting tool blade wear by Panchuk V., Onysko O., Kotwica K., Barz C., Borushchak L.

    Published 2021-12-01
    “…The efficiency of drill string largely depends on the pipe-end connector’s accuracy named tapered thread tool joint. …”
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  4. 84
  5. 85

    SMILES all around: structure to SMILES conversion for transition metal complexes by Maria H. Rasmussen, Magnus Strandgaard, Julius Seumer, Laura K. Hemmingsen, Angelo Frei, David Balcells, Jan H. Jensen

    Published 2025-04-01
    “…Scientific contribution We present a method that can create RDKit-parsable SMILES strings of transition metal complexes (TMCs) from Cartesian coordinates and use it to create a dataset of 227k TMC SMILES strings. …”
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  6. 86

    Highly stable two-level current fluctuation in complex oxide heterostructures by Doyeop Kim, Jung-Woo Lee, Jihyun Lim, Sungjun Choi, Khimananda Acharya, Seobin Oh, Jaewhan Oh, Tula R. Paudel, Yongsoo Yang, Kitae Eom, Sunwoo Lee, Hyungwoo Lee

    Published 2025-07-01
    “…We utilize the stable two-level fluctuations to generate random bit-strings and confirm their applicability in practical stochastic machine learning algorithms for image super-resolution. …”
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  7. 87

    Prediction of the classification, labelling and packaging regulation H-statements with confidence using conformal prediction with N-grams and molecular fingerprints by Ulf Norinder, Ziye Zheng, Ian Cotgreave

    Published 2025-01-01
    “…Utilization of the N-grams allows handling of all symbols in SMILES strings including those related to metals and salts that may be important for the compounds to exhibit their experimental determined toxicities. …”
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  8. 88

    Decoding words during sentence production with ECoG reveals syntactic role encoding and structure-dependent temporal dynamics by Adam M. Morgan, Orrin Devinsky, Werner K. Doyle, Patricia Dugan, Daniel Friedman, Adeen Flinker

    Published 2025-06-01
    “…Abstract Sentence production is the uniquely human ability to transform complex thoughts into strings of words. Despite the importance of this process, language production research has primarily focused on single words. …”
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  9. 89

    xBitterT5: an explainable transformer-based framework with multimodal inputs for identifying bitter-taste peptides by Nguyen Doan Hieu Nguyen, Nhat Truong Pham, Duong Thanh Tran, Leyi Wei, Adeel Malik, Balachandran Manavalan

    Published 2025-08-01
    “…Specifically, incorporating both peptide sequences and their molecular strings, xBitterT5 demonstrates superior performance compared to previous methods on the same benchmark datasets. …”
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  10. 90

    Data: to share or not to share? A Semi-Systematic Literature Review in (rational) data sharing in inter-organizational systems by Rogier Harmelink, Reinoud Joosten, Engin Topan, Arjen Adriaanse, Jos van Hillegersberg

    Published 2024-12-01
    “…Therefore, data sharing is essential to extract maximum benefits from technologies like Machine Learning and the Internet of Things in an Industry 4.0 context. …”
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  11. 91

    Estimation of Stresses in a Plate with a Concentrator through Ultrasonic Measurements of Acoustic Anisotropy by D. A. Tretyakov, D. S. Osovik

    Published 2024-12-01
    “…The literature describes in detail the application of this approach in the case of a biaxial strength of extended structures: main pipelines, rail strings, steam generators, and others. They assume the presence of a uniform field with zero or weak gradients of stresses and deformations. …”
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  12. 92

    LiSENCE: A Hybrid Ligand and Sequence Encoder Network for Predicting CYP450 Inhibitors in Safe Multidrug Administration by Abena Achiaa Atwereboannah, Wei-Ping Wu, Sophyani B. Yussif, Muhammed Amin Abdullah, Edwin K. Tenagyei, Chiagoziem C. Ukuoma, Yeong Hyeon Gu, Mugahed A. Al-antari

    Published 2025-04-01
    “…The LEN and SEN, as deep learning pipelines, extract high-level features from drug ligand strings and CYP protein target sequences, respectively. …”
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  13. 93

    Psychotic relapse prediction via biomarker monitoring: a systematic review by Alexandros Smyrnis, Christos Theleritis, Christos Theleritis, Panagiotis Ferentinos, Nikolaos Smyrnis, Nikolaos Smyrnis

    Published 2024-12-01
    “…In the wearables group, machine learning models were trained based on features such as heart rate, acceleration, and geolocation, which were measured continuously. …”
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  14. 94

    Methods of elimination of rails increased damage in the area of weld joints by E. A. Shur, V. M. Fedin, A. I. Borts, Yu. V. Ronzhina, A. I. Fimkin

    Published 2019-11-01
    “…Currently, these weak points are the defects connected with lack of penetration in the welding area, burns at the points of poor contact of the rail foot with the current-carrying contact tips, or with defects of the weld joint machining after welding, as well as the local hardness reduction in areas affected by heat after welding, and local heat treatment after welding. …”
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