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Showing 1,401 - 1,420 results of 1,810 for search '((( resource OR resources) detection function ) OR ( source detection function ))', query time: 0.35s Refine Results
  1. 1401

    Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach by Zhengyuan Su, Huadong Jiang, Ying Yang, Xiangqing Hou, Yanli Su, Li Yang

    Published 2025-04-01
    “…Basic acoustic features (eg, Mel Frequency Cepstral Coefficients, formant frequencies, jitter, shimmer) and high-level statistical function (HSF) features (using OpenSMILE [Open-Source Speech and Music Interpretation by Large-Space Extraction] with the ComParE 2016 configuration) were extracted. …”
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  2. 1402

    Estimating the mass of tephra accumulated on roads to best manage the impact of volcanic eruptions: the example of Mt Etna, Italy by L. Mereu, L. Mereu, M. Stocchi, M. Stocchi, A. Garcia, M. Prestifilippo, L. Sandri, C. Bonadonna, S. Scollo

    Published 2025-06-01
    “…First, we analysed a sequence of 39 short-lasting and intense lava fountains detected by the X-band weather radar, applying a volcanic ash radar retrieval approach that permits us to compute the main eruption source parameters (ESPs), such MER, <span class="inline-formula"><i>H</i><sub>TP</sub></span>, and GSD. …”
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  3. 1403

    MergeBot: A platform of semi-structured merge conflict resolution for C/C++ code by Hua He, Xiaofan Liu, Lei Xu, Guanghui Mei, Jifeng Xuan

    Published 2025-05-01
    “…In software version control systems, like Git, merge conflicts typically arise when multiple developers edit the same segment of a source file from different branches. Detecting merge conflicts can be automated; however, resolving merge conflicts is tedious and demanding. …”
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  4. 1404

    Intratumoural aldosterone and CYP11B2 expression levels among different genotypes of aldosterone producing tumours by Tobias Åkerström, Branislav Klimàcek, Matilda Annebäck, Olov Norlén, Peter Stålberg

    Published 2025-06-01
    “…Primary aldosteronism is the most common endocrine cause of hypertension, affecting 5–10% of hypertensive patients. Determining the source of aldosteronism is necessary for correct diagnosis and further molecular analysis. …”
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  5. 1405

    Antioxidant Profiling of Botryocladia leptopoda Based on In Silico and In Vitro Studies by Fenny Crista Anastasia Panjaitan, Huey-Jine Chai

    Published 2025-05-01
    “…Thus, B. leptopoda can be considered a promising source of antioxidative products in the functional food and pharmaceutical industries.…”
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  6. 1406

    Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

    Published 2025-06-01
    “…Point-of-care ultrasound and portable diagnostic devices have expanded real-time imaging and functional assessment capabilities across diverse clinical settings. …”
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  7. 1407

    Immunoexpression of tumor suppressor genes p53, p21WAF1/CIP1 and p27KIP1 in humam astrocystic tumors Imuno-expressão dos genes supressores tumorais p53, p21WAF1/CIP1 e p27KIP1 em t... by Mário Henrique Girão Faria, Régia Maria do Socorro Vidal do Patrocínio, Manoel Odorico de Moraes Filho, Silvia Helena Barem Rabenhorst

    Published 2007-12-01
    “…These results indicated the p53 mutation as an initial, relevant and potentially predictor of tumor progression event in astrocytomas, with the detection of p21 protein as an important resource for the deduction of functional situation of this gene. …”
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  8. 1408

    Direct-fed microbials optimize ruminal fermentation, microbial ecosystem and milk quality to enhance the lactation performance of Sanhe dairy cows by Aoyu Jiang, Zixin Liu, Ziyan Yang, Shizhe Zhang, Jian Wu, Chuanshe Zhou, Zhiliang Tan

    Published 2025-07-01
    “…Dairy cows are the most important source of milk production, with billions of microorganisms present in the rumen. …”
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  9. 1409

    Frontotemporal lobar degeneration changes neuronal beta-frequency dynamics during the mismatch negativity response by Alistair Perry, Laura E. Hughes, Natalie E. Adams, Michelle Naessens, Niels A. Kloosterman, Matthew A. Rouse, Alexander G. Murley, Duncan Street, P. Simon Jones, James B. Rowe

    Published 2024-01-01
    “…Across bvFTD and PSP groups, the beta response to deviant stimuli (relative to standard stimuli) correlated with clinical severity, but not with atrophy of the prefrontal source region. These findings confirm the proposed importance of higher-order cortical regions, and their beta-power generators, in sensory change detection and context-updating during oddball paradigms. …”
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  10. 1410
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  12. 1412

    De novo transcriptome assembly of the Mediterranean sea-rock pool mosquitoes Aedes mariae and Aedes zammitii by Valentina Mastrantonio, Daniele Porretta, Franco Liberati, Roberta Bisconti, Tiziana Castrignanò, Daniele Canestrelli

    Published 2025-01-01
    “…Validation by BUSCO confirmed the high quality of our resources. Homology alignments of predicted ORFs showed that 21,842 sequences from Ae. mariae and 21,944 sequences from Ae. zammitii mapped to the Nr, SwissProt, and TrEMBL databases, while 19,208 and 19,393 predicted ORFs, respectively, were functionally annotated using the COG and KEGG databases. …”
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  13. 1413

    Influence of Organic Nitrogen Derived from Recycled Wine Lees and Inorganic Nitrogen on the Chemical Composition of Cabernet Sauvignon Wines Fermented in the Presence of Non-Saccha... by Claudia López-Lira, Pedro Valencia, Alejandra Urtubia, Esteban Landaeta, Ricardo A. Tapia, Wendy Franco

    Published 2024-12-01
    “…In this study, the influences of inorganic nitrogen source (INS) and organic nitrogen source (ONS) supplementation during the wine fermentation process using three non-Saccharomyces yeasts (<i>Candida zemplinina</i>, <i>Candida oleophila</i>, and <i>Candida boidinii</i>) were analyzed. …”
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  14. 1414

    Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

    Published 2025-12-01
    “…Moreover, integrating machine learning into risk management enhances decision-making by providing precise, data-driven predictions, allowing for more effective strategies and efficient resource allocation.Future research could incorporate additional data, such as historical records, economic indicators, and internal process information, to further improve prediction accuracy. …”
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  15. 1415

    Preliminary Study on Natural Infection of Shellfish with Movement Disorder Nodavirus (MDNV) by Ping LI, Jitao XIA, Changming BAI, Ruidong XU, Tingting XU, Shuang LIU, Liang YAO, Xingtong YU, Qingli ZHANG

    Published 2025-08-01
    “…Shellfish is an important source of high-quality protein for human beings and simultaneously plays an important ecological service function in the marine ecosystem. …”
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  16. 1416
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  18. 1418

    There is no transfer of mitochondria from donor hematopoietic cells to recipient mesenchymal stromal cells after allogeneic hematopoietic stem cells transplantation in humans by Natalya Sats, Vadim Surin, Tatiana Abramova, Aleksandra Sadovskaya, Nataliya Petinati, Nikolay Kapranov, Ksenia Nikiforova, Nina Drize, Luisa Karaseva, Olga Pokrovskaya, Larisa Kuzmina, Elena Parovichnikova

    Published 2025-07-01
    “…Mitochondria, which can be transferred between cells via nanotubes or extracellular vesicles, play a key role in the functions of mesenchymal stromal cells. In a murine model, donor hematopoietic stem and progenitor cells transfer functional mitochondria to bone marrow mesenchymal stromal cells of the recipient. …”
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  19. 1419

    Modeling the effects of land use change on agricultural carrying capacity and food security by R. Harini, R. Rijanta, E.H. Pangaribowo, R.F. Putri, I. Sukri

    Published 2025-04-01
    “…Food problems are related to the availability of food sources. The availability of agricultural land as the primary source of food production is decreasing due to the increase in population. …”
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  20. 1420