Showing 281 - 300 results of 558 for search '(( i e decrease ) OR ( 100 (((((per OR peter) decrease) OR (a decrease))) OR (mean decrease)) ))', query time: 0.19s Refine Results
  1. 281

    Ziziphus nummularia attenuates the malignant phenotype of human pancreatic cancer cells: Role of ros by Mesmar, J.

    Published 2021
    “…In addition, ZNE significantly decreased the migratory and invasive capacity of Capan-2 with a concomitant downregulation of integrin α2 and increased cell–cell aggregation. …”
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    Changes in Copepod Community Structure in Response to Land-Based Activities along Alexandria Coastline, Mediterranean Sea by El Din, Nehad M. Nour [نهاد مصطفى نور الدين]

    Published 2000
    “…Industrial discharge exerted the highest impact on the copepod population by decreasing its density to less than 500 ind./m3. Despite the decrease m copepod abundance during high flow of sewage, the impacted area sustained the maximum copepod density low discharge i.e. 11,222 ind.…”
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    Daily-seasonal operation in net-zero energy building powered by hybrid renewable energies and hydrogen storage systems by Mehrjerdi, H.

    Published 2019
    “…These issues are investigated at net-zero energy building supported by renewable resources (i.e., solar energy, hydro energy, and fuelcell) and energy storage systems (i.e., hydrogen storage system). …”
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    Co-doped zigzag graphene nanoribbon based gas sensor for sensitive detection of H2S: DFT study by Salih, Ehab

    Published 2021
    “…The adsorption energy (Eads) of H2S/Zn-ZGNR and H2S/Cu-ZGNR systems were found to be −2.237 and −1.129 eV, respectively. For the case of H2S/Cu/Zn-ZGNR, the adsorption energy (Eads) and charge transfer (Δq) reflected an outstanding increase to −7.043 eV and −0.311 e, respectively, when compared with both pristine and doped systems: ZGNR, Zn-ZGNR, and Cu-ZGNR. …”
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  14. 294

    An intelligent data uploading selection mechanism for offloading uplink traffic of cellular networks by Wang, Qian

    Published 2020
    “…In IDUSM, our proposed probability prediction model precisely predicts a participant’s mobility from spatial and temporal aspects, and we decrease data redundancy produced in the Wi-Fi offloading process to reduce waste of participants’ limited resources (e.g., storage, battery). …”
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