Micropost sensor array for cell traction forces studies

Abstract only availableA rapid fusion of MEMS (Microelectromechanical-Systems) and biology provides many diverse spheres and methods in cell studies. Micropost can be an important role in many different biological analyses because forces from cells can be obtained by calibrating micropost sensor array. Therefore, making better microposts will be useful for getting accurate force analysis. One way to make microposts is to pour poly-dimethylsiloxane (PDMS) onto wafer that has cylindrical holes array and peeled off from it after PDMS cured at room temperature for 24 hours. Before cultivating cells on microposts, deflection force relationship of micropost is expected be acquired in order to obtain forces that exerted by cells on its top. When cells were placed to Micropost Force Sensor Array (MFSA), they stuck and grew on MFSA's top surface which causes deflection of microposts, and this deflection can be transferred to the force. The relationship between laterally exerted point force at the top of microposts and micropost deflection force was observed by AFM (Atomic Force Microscope). Calibration shows that the relationship between deflection of microposts and force applied was non-linear. From the process of using MFSA technology, the result was that human skin fibroblasts (HSFs) made bigger traction forces than human patellar tendon fibroblasts (HPTFs). Therefore, MFSA is more accurate and a better technology that can help in useful knowledge such as the molecular and cellular system of tissue injury curing. In conclusion, we have used the MFSA technique with a non-linear micropost displacement/deflection-force relationship for measurement of the cell traction forces. New image analysis methods for measurement of displacement of microposts are implemented and high density micropost array were accomplished. This technique will be a very useful technology for many biological applications used in researching the reaction of cell shape and cytokines on CTFs and measuring CTF to find bad cells.College of Engineering Undergraduate Research Optio

Single-photon quantum nonlocality: Violation of the Clauser-Horne-Shimony-Holt inequality using feasible measurement setups

We investigate quantum nonlocality of a single-photon entangled state under feasible measurement techniques consisting of on-off and homodyne detections along with unitary operations of displacement and squeezing. We test for a potential violation of the Clauser-Horne-Shimony-Holt (CHSH) inequality, in which each of the bipartite party has a freedom to choose between 2 measurement settings, each measurement yielding a binary outcome. We find that single-photon quantum nonlocality can be detected when two or less of the 4 total measurements are carried out by homodyne detection. The largest violation of the CHSH inequality is obtained when all four measurements are squeezed-and-displaced on-off detections. We test robustness of violations against imperfections in on-off detectors and single-photon sources, finding that the squeezed-and-displaced measurement schemes perform better than the displacement-only measurement schemes.Comment: 7+ pages, 7 figures, 1 table, close to published versio

Effects of individuality, education, and image on visual attention: Analyzing eye-tracking data using machine learning

Machine learning, particularly classification algorithms, constructs mathematical models from labeled data that can predict labels for new data. Using its capability to identify distinguishing patterns among multi-dimensional data, we investigated the impact of three factors on the observation of architectural scenes: Individuality, education, and image stimuli. An analysis of the eye-tracking data revealed that (1) a velocity histogram was unique to individuals, (2) students of architecture and other disciplines could be distinguished via endogenous parameters, but (3) they were more distinct in terms of seeking structural versus symbolic elements. Because of the reverse nature of the classification algorithms that automatically learn from data, we could identify relevant parameters and distinguishing eye-tracking patterns that have not been reported in previous studies

An Unsupervised Algorithm for Change Detection in Hyperspectral Remote Sensing Data Using Synthetically Fused Images and Derivative Spectral Profiles

Multitemporal hyperspectral remote sensing data have the potential to detect altered areas on the earth’s surface. However, dissimilar radiometric and geometric properties between the multitemporal data due to the acquisition time or position of the sensors should be resolved to enable hyperspectral imagery for detecting changes in natural and human-impacted areas. In addition, data noise in the hyperspectral imagery spectrum decreases the change-detection accuracy when general change-detection algorithms are applied to hyperspectral images. To address these problems, we present an unsupervised change-detection algorithm based on statistical analyses of spectral profiles; the profiles are generated from a synthetic image fusion method for multitemporal hyperspectral images. This method aims to minimize the noise between the spectra corresponding to the locations of identical positions by increasing the change-detection rate and decreasing the false-alarm rate without reducing the dimensionality of the original hyperspectral data. Using a quantitative comparison of an actual dataset acquired by airborne hyperspectral sensors, we demonstrate that the proposed method provides superb change-detection results relative to the state-of-the-art unsupervised change-detection algorithms

Fundamental limits on concentrating and preserving tensorized quantum resources

Quantum technology offers great advantages in many applications by exploiting quantum resources like nonclassicality, coherence, and entanglement. In practice, an environmental noise unavoidably affects a quantum system and it is thus an important issue to protect quantum resources from noise. In this work, we investigate the manipulation of quantum resources possessing the so-called tensorization property and identify the fundamental limitations on concentrating and preserving those quantum resources. We show that if a resource measure satisfies the tensorization property as well as the monotonicity, it is impossible to concentrate multiple noisy copies into a single better resource by free operations. Furthermore, we show that quantum resources cannot be better protected from channel noises by employing correlated input states on joint channels if the channel output resource exhibits the tensorization property. We address several practical resource measures where our theorems apply and manifest their physical meanings in quantum resource manipulation.Comment: 12 pages, 3 figure