Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Mass Analyzers: Overview01:13

Mass Analyzers: Overview

The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
Column Efficiency: Plate Theory01:10

Column Efficiency: Plate Theory

Band broadening in a chromatography column is measured by its efficiency. This is determined by the number of theoretical plates (N). Theoretical plate theory states that a separation column consists of a continuous series of imaginary plates where solute equilibration occurs between stationary and mobile phases.
A higher number of theoretical plates signifies better column efficiency and improved separation capabilities. Plate height affects bandwidth and separation quality; it is inversely...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Use of a trauma registry to drive improvement in the regional trauma network systems in Hawassa, Ethiopia.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie·2022
Same author

Systematic review of complications associated with treatment by traditional bone setters for musculoskeletal injury.

Tropical doctor·2022
Same author

Coronavirus infection in hip fractures (CHIP) study.

The bone & joint journal·2021
Same author

Critiquing operative fracture fixation: the development of an assessment tool.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie·2017
Same author

External fixation in HIV-positive patients with open fractures.

Malawi medical journal : the journal of Medical Association of Malawi·2016
Same author

How safe is internal fixation in the immune compromised patient?

Malawi medical journal : the journal of Medical Association of Malawi·2016

関連する実験動画

Updated: Jul 11, 2026

Sediment Core Extrusion Method at Millimeter Resolution Using a Calibrated, Threaded-rod
06:06

Sediment Core Extrusion Method at Millimeter Resolution Using a Calibrated, Threaded-rod

Published on: August 17, 2016

スーパーコンピュータによる堆積層の分析

C M Bethke, S P Altaner, W J Harrison

    Science (New York, N.Y.)
    |January 15, 1988
    PubMed
    まとめ

    スーパーコンピュータは,堆積盆地の地質学的プロセスを分析し,地下状態と資源形成を制御する要因を明らかにします. この数値的なアプローチは,鉱石の起源と地質時間における炭化水素貯蔵庫の質を理解するのに役立ちます.

    科学分野:

    • 地質学 地質学 地質学
    • 地質化学 地質化学
    • 計算科学 計算科学とは

    背景:

    • 沈殿盆地には,重要なエネルギーと鉱物資源があります.
    • 流体輸送と化学反応は,これらの盆地内の重要な地質学的プロセスです.

    研究 の 目的:

    • 数学的実験を用いて堆積盆地における地質学的プロセスを分析する.
    • 地下状態と資源形成を制御する要因についての洞察を得るために.

    主な方法:

    • 数学的実験のためにスーパーコンピュータを活用した.
    • 統合された層図,海平面,プレート構造の歴史.

    主要な成果:

    • 地下の圧力,温度,化学反応を制御する要因を特定した.
    • ミネラル鉱石の起源に関する洞察を提供した.
    • 炭化水素貯蔵庫の分布と質を特徴づけた.

    結論:

    • 数学的分析は,堆積層の進化を研究するための強力なツールです.
    • 地質学的歴史と数学的方法を組み合わせることで,包括的な洞察が得られます.

    さらに関連する動画

    Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
    07:59

    Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors

    Published on: December 6, 2018

    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
    08:56

    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

    Published on: January 13, 2023

    関連する実験動画

    Last Updated: Jul 11, 2026

    Sediment Core Extrusion Method at Millimeter Resolution Using a Calibrated, Threaded-rod
    06:06

    Sediment Core Extrusion Method at Millimeter Resolution Using a Calibrated, Threaded-rod

    Published on: August 17, 2016

    Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
    07:59

    Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors

    Published on: December 6, 2018

    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
    08:56

    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

    Published on: January 13, 2023