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相关概念视频

MALDI-TOF Mass Spectrometry01:19

MALDI-TOF Mass Spectrometry

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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...
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Mass Analyzers: Overview01:13

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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...
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Comparison of Carmustine-, Lomustine-, and Nitrosourea-free Conditioning Regimens for Autologous Hematopoietic Cell Transplantation in Lymphoma (auto-HTC): Results from the Hematopoietic Cell Transplantation Brazilian Registry (HCTBR).

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Haploidentical versus HLA-Matched Unrelated Donors for Hematopoietic Cell Transplantation in Acute Leukemia: A Multicenter Observational Study in a Developing Country Facilitated by Collaboration between the CIBMTR and the Brazilian Society of Cellular Therapy and Bone Marrow Transplantation (SBTMO).

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Functional validation of a modified platelet desialylation test for immune and hereditary thrombocytopenias.

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Soluble E-Cadherin as a New Prognostic Biomarker Able to Predict Survival in Newly Diagnosed Diffuse Large B-Cell Lymphoma.

Biomolecules·2026
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SowPostureDS: A Multi-Class Image Dataset for YOLO-Based Detection of Sow Postures in diverse Farrowing Systems.

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相关实验视频

Updated: Jan 7, 2026

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
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MH-1M:一个有134万个样本的多功能Android恶意软件数据集与丰富的元数据.

Hendrio Bragança1, Diego Kreutz2, Vanderson Rocha3

  • 1Federal University of Amazonas (UFAM), Institute of Computing, Manaus-AM, 69.077-000, Brazil. hendrio.luis@icomp.ufam.edu.br.

Scientific data
|December 31, 2025
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概括
此摘要是机器生成的。

本研究介绍了MH-1M,这是一个大型的Android恶意软件数据集,用于高级研究. 它有助于通过全面的数据和分析来了解不断发展的恶意软件威胁.

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科学领域:

  • 计算机科学 计算机科学
  • 网络安全 网络安全
  • 数据科学数据科学数据科学

背景情况:

  • 安卓恶意软件对移动安全构成重大和不断发展的威胁.
  • 现有的数据集可能缺乏高级恶意软件分析所需的规模或细节.

研究的目的:

  • 介绍MH-1M,一个全面的数据集,用于Android恶意软件研究.
  • 通过开放数据访问,促进对Android恶意软件的高级分析.

主要方法:

  • 编制了一个 1,340,515 个 Android 应用程序的数据集.
  • 利用VirusTotal API与多个检测引擎进行恶意软件分类.
  • 提取了每个应用程序的功能和收集了广泛的元数据.

主要成果:

  • MH-1M数据集包含超过 130 万个 Android 应用程序.
  • 数据集包括全面的元数据和VirusTotal分析结果.
  • 在Figshare,Harvard Dataverse和GitHub仓库中提供超过400GB的数据.

结论:

  • MH-1M数据集是研究当前Android恶意软件风景的宝贵资源.
  • 对这种大规模数据集的开放访问将推进Android恶意软件研究和防御策略.