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Neurosurgery with Heads-up Display
In the following video interviews Prof. Dr. Raphael Guzman, Vice Chairman of the Department of Neurosurgery at the University Hospital in Basel, Switzerland, talks about his experience in heads-up…
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Workflows and Instrumentation for Cryo-electron Microscopy
Cryo-electron microscopy is an increasingly popular modality to study the structures of macromolecular complexes and has enabled numerous new insights in cell biology. In recent years, cryo-electron…
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研究におけるモデル生物
モデル生物とは、特定の生物学的プロセスを研究するために研究者が使用する生物種です。 モデル生物は、人間と似た遺伝的特徴を持ち、遺伝子学、発生生物学、神経科学などの研究分野で一般的に使用されています。 通常、モデル生物は実験環境での維持や繁殖が容易であること、生殖サイクルが短いこと、または、特定の形質や病気を研究するために突然変異体を生成する能力を持つことで選ばれます。
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An Introduction to Computational Clearing
Many software packages include background subtraction algorithms to enhance the contrast of features in the image by reducing background noise. The most common methods used to remove background noise…
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Factors to Consider When Selecting a Research Microscope
An optical microscope is often one of the central devices in a life-science research lab. It can be used for various applications which shed light on many scientific questions. Thereby the…
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Challenges Faced When Manually Rating Non-Metallic Inclusions (NMIs) to Determine Steel Quality
Rapid, accurate, and reliable rating of non-metallic inclusions (NMIs) is instrumental for the determination of steel quality. This article describes the challenges that arise from manual NMI rating,…
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How Can Immunofluorescence Aid Virology Research?
Modern virology research has become as crucial now as ever before due to the global COVID-19 pandemic. There are many powerful technologies and assays that virologists can apply to their research into…
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Augmented Reality (AR) Fluorescence Image Gallery
Building on a decade of leadership in fluorescence imaging technology, GLOW800 AR fluorescence is the first of many modalities based on the proprietary GLOW AR platform.
The sophisticated imaging…
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LIGHTNINGによって試料から最大限の情報を引き出す
LIGHTNINGは、他の方法では簡単に可視化できない、微細な構造や形態を完全自動で明らかにする、適応能力に優れた情報抽出プロセスです。 LIGHTNINGは、画像全体を同一のパラメーターで演算する従来型の手法とは異なり、ボクセル（3次元画素）ごとに適切なパラメーターを算出することによって、最高の忠実度であらゆる微細形態を明らかにします。
