Research Profiles

JP

"T" Keywords - 46 Result(s)

T
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 T

[tumor-specific]

Production of Tumor-Specific Monoclonal Antibodies

 
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特徴・独自性
  • Podoplanin (PDPN/Aggrus/T1α), a platelet aggregation-inducing mucin-like sialoglycoprotein, is highly expressed in many cancers and normal tissues. A neutralizing monoclonal antibody (mAb; NZ-1) can block the association between podoplanin and C-type lectin-like receptor-2 (CLEC-2) and inhibit podoplanin-induced cancer metastasis, but NZ-1 reacts with podoplanin-expressing normal cells such as lymphatic endothelial cells. Recently, we established a platform to produce cancer-specific mAbs (CasMabs). The newly established LpMab-2 mAb reacted with podoplanin-expressing cancer cells but not with normal cells, as shown by flow cytometry and immunohistochemistry; therefore, LpMab-2 is an anti-podoplanin CasMab that is expected to be useful for molecular targeting therapy against podoplanin-expressing cancers.
実用化イメージ

We can produce cancer-specific mAbs (CasMabs) against all membranous proteins. CasMabs are expected to be useful for molecular targeting therapy without side effects.

Researchers

Graduate School of Medicine

Yukinari Kato

[tunnel magnetoresistance]

Development of High Sensitive Magnetic Sensor Operating at Room Temperature with Tunnel Magnetoresistance Devices

 
 
 
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特徴・独自性
  • Recently, many tunnel magnetoresistance devices with high magnetoresistance effect are reported. These are expected to be applied to high sensitive magnetic sensors. There are many magnetic sensors with variety of the mechanism, in order to meet the demand of the very wide range of sensing magnetic field. However, there is no magnetic sensor which has high sensitivity, easy to use, operation at room temperature and low cost. Only a magnetic sensor with tunnel magnetoresistance devices can satisfy all the demand in principle. As the device has very wide range of the sensing magnetic field, it can be designed for any demand to the sensors.
実用化イメージ

For example, this device can sense a bio-magnetic field easily at room temperature, so that it could be replaced SQUID device, which is popular now but is very expensive and not easy to use personally. Therefore, by using this device, we expect we can conduct effective collaborative research in medical field.

Researchers

Graduate School of Engineering

Yasuo Ando

[Turbulence]

Data science-based analysis for unsteady aerodynamic flows

 
 
 
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概要

Our group studies a range of unsteady flow phenomena leveraging data science, nonlinear machine learning, complex network theory, information theory, and computational fluid dynamics. Our ultimate goal is to build a data-oriented foundation for real-time analysis, modeling, and control of unsteady flows ubiquitously appearing in various situations around small air vehicles, airplanes, motor vehicles, and fluid-based industrial machines.

従来技術との比較

Equipped with nonlinear machine learning-based sparse sensor reconstruction and data compression supported through traditional numerical and experimental analysis, our approach enables high-resolution reconstruction, real-time prediction, and control of flow fields with limited availability of data.
These techniques are aimed at analyzing and controlling large-scale, complex nonlinear flow phenomena that have been challenging to tackle with conventional linear methods.

特徴・独自性
  • ・Real-time spatiotemporal flow field reconstruction from sparse sensors is enabled by turbulence super-resolution analysis with machine learning.
  • ・Understanding and modeling of unsteady fluid flows at low cost is made possible through low-dimensional manifold identification and compression.
  • ・Development of explainable machine-learning approaches for analyzing causal vortex interactions based on complex network theory and information theory.
  • ・Multi-modal data analysis through the fusion of numerical, experimental, and theoretical data.
実用化イメージ

Our group aims to develop technologies that accurately sense, predict, model, and control fluid flows —such as air and water— around objects including airplanes, automobiles, and wind turbines, even with sparse sensor information.

These technologies can contribute to society in various ways, including:
・Improving fuel efficiency and safety of aircraft
・Enhancing the aerodynamic performance of vehicles for energy savings
・Supporting disaster prevention through wind flow prediction during emergencies

We actively seek to co-create innovations through joint research with industrial companies interested in the following areas:

・Predicting and controlling fluid flows using AI and machine learning
・Understanding flow structures through information theory and network science
・Building highly accurate and reproducible models by integrating traditional fluid dynamics with modern data-driven methods

Equipped with physics-based nonlinear machine learning, we are working to develop groundbreaking fluid analysis technologies that benefit a wide range of industrial, environmental, and societal applications.

Researchers

Graduate School of Engineering

Kai Fukami

[Two-dimensional system]

Transport Control of Semiconductor Quantum Structures and Highly Sensitive NMR

 
 
 
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特徴・独自性
  • Highly-sensitive NMR technique has been developed by manipulation polarization of nuclear spins via control of transport characteristics in GaAs and InSb quantum structures. This highly-sensitive NMR can be applied to two-dimensional and nanostructures. Furthermore, ideal gate controllability has been demonstrated in InSb quantum structures with Al2 O3 dielectrics. More importantly, the concept of generalized coherence time was introduced, where noise characteristics felt by nuclear spins can be measured including their frequency dependence. This concept will bring about a change in all nuclear-spin related measurements.
実用化イメージ

Next generation InSb devices based on good gate controllability. Various nuclear-spin based measurements and NMR utilizing the concept of generalized coherence time. Highly-sensitive NMR is now important for fundamental physics studies. In the future, it will contribute to quantum information processing.

Researchers

Center for Science and Innovation in Spintronics

Yoshiro Hirayama

[Two-Directional Electric Field Drive System ]

[tyhoon]

Prediction and evaluation of future thermal and wind environments based on CFD, and planning of urban environments adaptable to future climate

 
 
 
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特徴・独自性
  • Numerical simulations of the physical environment of urban outdoor spaces are conducted to predict the physical environment, such as temperature, humidity, wind, and pollutant concentration, and field measurements are conducted to understand the actual physical environment. In addition, the future outdoor environments and heat stroke risks due to global warming are predicted and evaluated.
    Furthermore, the impacts of urban morphology (building shape and layout, street trees, etc.) on the adaptation to severe heat in summer and rare typhoons and floods are evaluated quantitatively.
実用化イメージ

Numerical analysis is used to quantitatively evaluate the "merits and demerits" of designing buildings, planning city blocks and urban areas, and introducing various heat control technologies on the wider thermal environment and the formation of wind ventilation paths, as well as the adverse effects of typhoons and other disasters. The materials for making decisions on whether or not to introduce these technologies are provided.

Researchers

Graduate School of Engineering

Yasuyuki Ishida

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