Fabrication of 3D Micro Patterns on Concave Substrate and Its Application for the Fabrication of Cylindrical Polymer Stamps

2012 ◽  
Vol 132 (9) ◽  
pp. 303-308
Author(s):  
Jongho Park ◽  
Nobuyuki Takama ◽  
Hiroyuki Fujita ◽  
Beomjoon Kim
Keyword(s):  
Micro Patterns

A facile and combined methodology to fabricate sputtered thin film micro-patterns for heater/sensor applications utilizing CO2 laser-cut masks

2021 ◽  
pp. 1-10
Author(s):  
Mohammed Adnan Hasan ◽  
K. Prajwal ◽  
Dwarika Nath Sahu ◽  
Arpana Prasad ◽  
Arjun Dey ◽  
...  
Keyword(s):  
Thin Film ◽  
Co2 Laser ◽  
Sensor Applications ◽  
Micro Patterns

scholarly journals Controlling T cells spreading, mechanics and activation by micropatterning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anaïs Sadoun ◽  
Martine Biarnes-Pelicot ◽  
Laura Ghesquiere-Dierickx ◽  
Ambroise Wu ◽  
Olivier Théodoly ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Activation ◽  
Cell Activation ◽  
Young Modulus ◽  
Careful Examination ◽  
Adhesion Receptor ◽  
Force Microscopy ◽  
Atomic Force ◽  
Micro Patterns

AbstractWe designed a strategy, based on a careful examination of the activation capabilities of proteins and antibodies used as substrates for adhering T cells, coupled to protein microstamping to control at the same time the position, shape, spreading, mechanics and activation state of T cells. Once adhered on patterns, we examined the capacities of T cells to be activated with soluble anti CD3, in comparison to T cells adhered to a continuously decorated substrate with the same density of ligands. We show that, in our hand, adhering onto an anti CD45 antibody decorated surface was not affecting T cell calcium fluxes, even adhered on variable size micro-patterns. Aside, we analyzed the T cell mechanics, when spread on pattern or not, using Atomic Force Microscopy indentation. By expressing MEGF10 as a non immune adhesion receptor in T cells we measured the very same spreading area on PLL substrates and Young modulus than non modified cells, immobilized on anti CD45 antibodies, while retaining similar activation capabilities using soluble anti CD3 antibodies or through model APC contacts. We propose that our system is a way to test activation or anergy of T cells with defined adhesion and mechanical characteristics, and may allow to dissect fine details of these mechanisms since it allows to observe homogenized populations in standardized T cell activation assays.

Chip-scale alignment of long DNA nanofibers on a patterned self-assembled monolayer

Lab on a Chip ◽  
2017 ◽  
Vol 17 (19) ◽  
pp. 3234-3239 ◽  
Author(s):  
J. Xia ◽  
M. Su
Keyword(s):  
Surface Tension ◽  
Genomic Dna ◽  
Electrostatic Force ◽  
Self Assembled Monolayer ◽  
Self Assembled ◽  
Micro Patterns

Centimeter-long genomic DNA nanofibers produced by the interplay between surface tension and electrostatic force of micro-patterns.

Printing High-resolution Micro-patterns by Solution Processes

2021 ◽  
Vol 37 (5) ◽  
pp. 1008-1018
Author(s):  
Kejie Zhang ◽  
Min Zhang ◽  
Huan Liu
Keyword(s):  
High Resolution ◽  
Solution Processes ◽  
Micro Patterns

scholarly journals Patterns in Natural Halophytic Grasslands at the Border of Forest-Steppe and Steppe Zones of South Ural

2020 ◽  
Vol 20 (4) ◽  
pp. 465-476
Author(s):  
Nazar N. Nazarenko ◽  
◽  
Aleksandr V. Malaev ◽  
Alla V. Pirozhenkova ◽  
Natalya A. Bayda ◽  
...  
Keyword(s):  
Random Distribution ◽  
Forest Steppe ◽  
Steppe Species ◽  
Soil Aeration ◽  
Natural Complex ◽  
Continuum Concept ◽  
Concept Theory ◽  
Micro Patterns

The patterns (mosaicity) in natural halophytic grasslands at the border of Forest-steppe and Steppe zones of South Ural were characterized by the hierarchical continuum concept theory for the Troitskiy state natural complex preserve example. It was established, that the grass canopy is fragmented by salinization impact, the individual’s random distribution is typical of halophytes and salttolerant steppe species form patterns. Only the micro-patterns (0,8 m) level is statistically significant, parcels (8 m) and coenotics (12 m) are fuzzy and fragmentation of mosaicity is observed. There are two coenotics series defined for parcels – halophytic and steppe, relating to the distribution of halophytes and steppe grasses respectively. There is clear coenosis. Separation is observed by phytodiversity and biotopes descriptions. The intracoenotic interactions between species, soil moistening variability, soil aeration and acidity (alkalinity) and soil mineralization increase (decrease) are significant for parcels and coenosis forming.

Biomolecular linear motors confined to move upon micro-patterns on glass

2006 ◽  
Vol 16 (8) ◽  
pp. 1550-1554 ◽  
Author(s):  
Yumi Yoshida ◽  
Ryuji Yokokawa ◽  
Hiroaki Suzuki ◽  
Kyoko Atsuta ◽  
Hiroyuki Fujita ◽  
...  
Keyword(s):  
Linear Motors ◽  
Micro Patterns

Drop-on-Demand Electrohydrodynamic Printing of High Resolution Conductive Micro Patterns for MEMS Repairing

2018 ◽  
Vol 19 (6) ◽  
pp. 811-819 ◽  
Author(s):  
Young Jin Yang ◽  
Hyung Chan Kim ◽  
Memoon Sajid ◽  
Soo wan Kim ◽  
Shahid Aziz ◽  
...  
Keyword(s):  
High Resolution ◽  
On Demand ◽  
Drop On Demand ◽  
Electrohydrodynamic Printing ◽  
Micro Patterns

Role of Artificial Intelligence in Modeling Psychometrics to Detect Neurodevelopmental Disorders

2020 ◽  
pp. 213-227
Author(s):  
Navjot Singh ◽  
Amarjot Kaur
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neurodevelopmental Disorders ◽  
Machine Learning Techniques ◽  
Diagnosis And Prognosis ◽  
Processing Power ◽  
Learning Techniques ◽  
Numerous Data ◽  
Applications Of Machine Learning ◽  
Micro Patterns

The objective of the present chapter is to highlight applications of machine learning and artificial intelligence (AI) in clinical diagnosis of neurodevelopmental disorders. The proposed approach aims at recognizing behavioral traits and other cognitive aspects. The availability of numerous data and high processing power, such as graphic processing units (GPUs) or cloud computing, enabled the study of micro-patterns hundreds of times faster compared to manual analysis. AI, being a new technological breakthrough, enables study of human behavior patterns, which are hidden in millions of micro-patterns originating from human actions, reactions, and gestures. The chapter will also focus on the challenges in existing machine learning techniques and the best possible solution addressing those problems. In the future, more AI-based expert systems can enhance the accuracy of the diagnosis and prognosis process.

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