Showing 99,561 - 99,580 results of 100,872 for search '(( 12 nn decrease ) OR ( 5 ((((non decrease) OR (point decrease))) OR (a decrease)) ))', query time: 1.62s Refine Results
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    Data_Sheet_2_Machine learning approach to classifying declines of physical function and muscle strength associated with cognitive function in older women: gait characteristics base... by Bohyun Kim (4768821)

    Published 2024
    “…Background<p>The aging process is associated with a cognitive and physical declines that affects neuromotor control, memory, executive functions, and motor abilities. …”
  3. 99563

    Table_3_Effects of different manganese sources on nutrient digestibility, fecal bacterial community, and mineral excretion of weaning dairy calves.pdf by Huimin Ji (8641476)

    Published 2023
    “…The aim of this study was to clarify the effects of different manganese (Mn) sources in basal diets on nutrient apparent digestibility, fecal microbes, and mineral elements excretion before and after weaning.</p>Methods<p>A total of 15 Holstein heifer calves (6-week-old, 82.71 ± 1.35, mean ± standard error) were randomly designed into three groups (five each): no extra Mn supplemented (CON), 20 mg Mn/kg (dry matter basis) in the form of chelates of lysine and glutamic acid in a mixture of 1:1 (LGM), and 20 mg Mn/kg (dry matter basis) in the form of MnSO<sub>4</sub>. …”
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    DataSheet_1_Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models.docx by Geng Bai (17748969)

    Published 2024
    “…Midwest has not been found. This study presents a two-year field experiment carried out in Eastern Nebraska, USA, to estimate AGB of five different cover crop species [canola (Brassica napus L.), rye (Secale cereale L.), triticale (Triticale × Triticosecale L.), vetch (Vicia sativa L.), and wheat (Triticum aestivum L.)] using high-throughput phenotyping and Machine Learning (ML) models. …”
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