Showing 114,081 - 114,100 results of 115,446 for search '(( 5 ((ppm decrease) OR (a decrease)) ) OR ( a ((non decrease) OR (nn decrease)) ))', query time: 1.63s Refine Results
  1. 114081
  2. 114082
  3. 114083

    Image_1_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>. …”
  4. 114084
  5. 114085

    Image_2_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>. …”
  6. 114086

    Table_2_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>. …”
  7. 114087

    Data_Sheet_1_Radiomics Analysis of Magnetic Resonance Imaging Facilitates the Identification of Preclinical Alzheimer’s Disease: An Exploratory Study.docx by Tao-Ran Li (6598853)

    Published 2020
    “…<p>Diagnosing Alzheimer’s disease (AD) in the preclinical stage offers opportunities for early intervention; however, there is currently a lack of convenient biomarkers to facilitate the diagnosis. …”
  8. 114088

    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. …”
  9. 114089

    datasheet1_Phenotypical Changes of Hematopoietic Stem and Progenitor Cells in Sepsis Patients: Correlation With Immune Status?.docx by Ping Wang (42415)

    Published 2021
    “…Our results may provide a novel diagnostic indicator and a new therapeutic approach.…”
  10. 114090

    Image_2_Osmoregulation in the Plotosidae Catfish: Role of the Salt Secreting Dendritic Organ.pdf by Salman Malakpour Kolbadinezhad (5476901)

    Published 2018
    “…Cl<sup>-</sup> levels were better regulated and the resulting strong ion ratio in BW suggests a metabolic acidosis. Elevated DO heat shock protein 70 levels in HSW fish indicate a cellular stress. …”
  11. 114091
  12. 114092

    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. …”
  13. 114093

    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>. …”
  14. 114094
  15. 114095
  16. 114096

    image1_Phenotypical Changes of Hematopoietic Stem and Progenitor Cells in Sepsis Patients: Correlation With Immune Status?.jpg by Ping Wang (42415)

    Published 2021
    “…Our results may provide a novel diagnostic indicator and a new therapeutic approach.…”
  17. 114097
  18. 114098
  19. 114099

    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. …”
  20. 114100