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Jennifer Gamble,Manuel O. Lagravère,Paul W. Major,Giseon Heo 대한영상의학회 2012 Korean Journal of Radiology Vol.13 No.2
Objective: To describe a statistical method of three-dimensional landmark configuration data and apply it to an orthodontic data set comparing two types of rapid maxillary expansion (RME) treatments. Materials and Methods: Landmark configurations obtained from cone beam CT scans were used to represent patients in two types (please describe what were two types) of RME groups and a control group over four time points. A method using tools from persistent homology and dimensionality reduction is presented and used to identify variability between the subjects. Results: The analysis was in agreement with previous results using conventional methods, which found significant differences between treatment groups and the control, but no distinction between the types of treatment. Additionally, it was found that second molar eruption varied considerably between the subjects, and this has not been evaluated in previous analyses. Conclusion: This method of analysis allows entire configurations to be considered as a whole, and does not require specific inter-landmark distances or angles to be selected. Sources of variability present themselves, without having to be individually sought after. This method is suggested as an additional tool for the analysis of landmark configuration data. Objective: To describe a statistical method of three-dimensional landmark configuration data and apply it to an orthodontic data set comparing two types of rapid maxillary expansion (RME) treatments. Materials and Methods: Landmark configurations obtained from cone beam CT scans were used to represent patients in two types (please describe what were two types) of RME groups and a control group over four time points. A method using tools from persistent homology and dimensionality reduction is presented and used to identify variability between the subjects. Results: The analysis was in agreement with previous results using conventional methods, which found significant differences between treatment groups and the control, but no distinction between the types of treatment. Additionally, it was found that second molar eruption varied considerably between the subjects, and this has not been evaluated in previous analyses. Conclusion: This method of analysis allows entire configurations to be considered as a whole, and does not require specific inter-landmark distances or angles to be selected. Sources of variability present themselves, without having to be individually sought after. This method is suggested as an additional tool for the analysis of landmark configuration data.
윤승철,신태성,Gerald W. Heitschmidt,Kurt C. Lawrence,박보순,Gary Gamble 한국농업기계학회 2019 바이오시스템공학 Vol.44 No.3
Purpose Hyperspectral imaging often requires a special camera system to obtain spectral images. The cost for acquisition and process of hyperspectral images is usually much higher than color images. On the contrary, typical consumer-grade digital color cameras are much cheaper to obtain and process spatially high-resolution images than hyperspectral cameras. This paper is concerned with the development of a hyperspectral image recovery technique that can reconstruct hyperspectral images only from color images obtained by a digital color camera. Methods A sparse representation and least squares regression-based classification of foodborne pathogens on agar plates are presented. The target pathogen bacteria were the six representative non-O157 Shiga toxin-producing Escherichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145). The wavelength range for the spectral recovery was from 400 to 1000 nm. Unlike many other studies using color charts with known and noise-free spectra for training their spectral recovery models, we directly used the hyperspectral and color images of real scenes for training the spectral recovery models. Both hyperspectral and color images were calibrated to percent reflectance values and then spatially registered. Two spectral recovery models including polynomial multivariate linear regression (MLR) and partial least squares regression (PLSR) were evaluated and compared by cross-validation and independent test. Results The spectral recovery results showed that the PLSR was more effective than the MLR. The classification accuracy measured with recovered spectra in an independent test set was about 5–10% less than the case of using the true hyperspectral images although the difference in maximum classification accuracy was only about 2%. Conclusion The results suggested the potential of a cost-effective color imaging system using hyperspectral image classification algorithms for differentiating pathogens in agar plates.
Microwave-driven coherent operation of a semiconductor quantum dot charge qubit.
Kim, Dohun,Ward, D R,Simmons, C B,Gamble, John King,Blume-Kohout, Robin,Nielsen, Erik,Savage, D E,Lagally, M G,Friesen, Mark,Coppersmith, S N,Eriksson, M A Nature Pub. Group 2015 Nature nanotechnology Vol.10 No.3
<P>An intuitive realization of a qubit is an electron charge at two well-defined positions of a double quantum dot. This qubit is simple and has the potential for high-speed operation because of its strong coupling to electric fields. However, charge noise also couples strongly to this qubit, resulting in rapid dephasing at all but one special operating point called the 'sweet spot'. In previous studies d.c. voltage pulses have been used to manipulate semiconductor charge qubits but did not achieve high-fidelity control, because d.c. gating requires excursions away from the sweet spot. Here, by using resonant a.c. microwave driving we achieve fast (greater than gigahertz) and universal single qubit rotations of a semiconductor charge qubit. The Z-axis rotations of the qubit are well protected at the sweet spot, and we demonstrate the same protection for rotations about arbitrary axes in the X-Y plane of the qubit Bloch sphere. We characterize the qubit operation using two tomographic approaches: standard process tomography and gate set tomography. Both methods consistently yield process fidelities greater than 86% with respect to a universal set of unitary single-qubit operations.</P>
Bioresorbable silicon electronic sensors for the brain
Kang, Seung-Kyun,Murphy, Rory K. J.,Hwang, Suk-Won,Lee, Seung Min,Harburg, Daniel V.,Krueger, Neil A.,Shin, Jiho,Gamble, Paul,Cheng, Huanyu,Yu, Sooyoun,Liu, Zhuangjian,McCall, Jordan G.,Stephen, Manu Nature Publishing Group, a division of Macmillan P 2016 Nature Vol.530 No.7588
<P>Many procedures in modern clinical medicine rely on the use of electronic implants in treating conditions that range from acute coronary events to traumatic injury(1,2). However, standard permanent electronic hardware acts as a nidus for infection: bacteria form biofilms along percutaneous wires, or seed haematogenously, with the potential to migrate within the body and to provoke immune-mediated pathological tissue reactions(3,4). The associated surgical retrieval procedures, meanwhile, subject patients to the distress associated with re-operation and expose them to additional complications(5-8). Here, we report materials, device architectures, integration strategies, and in vivo demonstrations in rats of implantable, multifunctional silicon sensors for the brain, for which all of the constituent materials naturally resorb via hydrolysis and/or metabolic action(9-12), eliminating the need for extraction. Continuous monitoring of intracranial pressure and temperature illustrates functionality essential to the treatment of traumatic brain injury(2,13); the measurement performance of our resorbable devices compares favourably with that of non-resorbable clinical standards. In our experiments, insulated percutaneous wires connect to an externally mounted, miniaturized wireless potentiostat for data transmission. In a separate set-up, we connect a sensor to an implanted (but only partially resorbable) data-communication system, proving the principle that there is no need for any percutaneous wiring. The devices can be adapted to sense fluid flow, motion, pH or thermal characteristics, in formats that are compatible with the body's abdomen and extremities, as well as the deep brain, suggesting that the sensors might meet many needs in clinical medicine.</P>