Novel x-ray analysis methods using a MicroStrip gas chamber

Author(s):  
Atsuhiko Ochi ◽  
Toru Tanimori ◽  
Yuji Nishi ◽  
Tsutomu Nagayoshi ◽  
Yasuro Nishi ◽  
...  
Keyword(s):  
X Ray ◽  
2016 ◽  
Vol 38 (2) ◽  
pp. 15-32
Author(s):  
E. Kalinichenko ◽  
A. Brik ◽  
A. Nikolaev ◽  
A. Kalinichenko ◽  
O. Frank-Kamenetskaya ◽  
...  
Keyword(s):  
X Ray ◽  

CrystEngComm ◽  
2014 ◽  
Vol 16 (44) ◽  
pp. 10262-10272 ◽  
Author(s):  
A. Ostasz ◽  
R. Łyszczek ◽  
L. Mazur ◽  
B. Tarasiuk

Novelp-xylylene-bis(thioacetic) acid (p-XBTA) and its co-crystals with 2-amino-4,6-dimethylpyrimidine (DMP) have been synthesized and characterized by single-crystal X-ray diffraction, infrared spectroscopy and thermal analysis methods (TG/DSC).


2017 ◽  
Vol 71 (11) ◽  
pp. 2538-2548 ◽  
Author(s):  
Qian Wang ◽  
Xiaomei Wu ◽  
Lingcong Chen ◽  
Zheng Yang ◽  
Zheng Fang

Currently, spectral analysis methods used in the classification of plastics have limitations that do not apply to opaque plastics or the stability of experimental results is not strong. In this paper, X-ray absorption spectroscopy (XAS) has been applied to classify plastics due to its strong penetrability and stability. Fifteen kinds of plastics are selected as specimens. X-ray, which is excited by a voltage of 60 kV, penetrated these specimens. The spectral data acquired by CdTe X-ray detector are processed by principal component analysis (PCA) and other data analysis methods. Then the back propagation neural networks (BPNN) algorithm is used to classify the processed data. The average recognition rate reached 96.95% and classification results of all types of plastic results were analyzed in detail. It indicates that XAS has the potential to classify plastics and that XAS can be used in some fields such as plastic waste sorting and recycling. At the same time, the technology of XAS, in the future, can also be used to classify more substances.


2018 ◽  
Vol 2 (1) ◽  
pp. 69-79 ◽  
Author(s):  
Martin A. Schroer ◽  
Dmitri I. Svergun

Small-angle X-ray scattering (SAXS) has become a streamline method to characterize biological macromolecules, from small peptides to supramolecular complexes, in near-native solutions. Modern SAXS requires limited amounts of purified material, without the need for labelling, crystallization, or freezing. Dedicated beamlines at modern synchrotron sources yield high-quality data within or below several milliseconds of exposure time and are highly automated, allowing for rapid structural screening under different solutions and ambient conditions but also for time-resolved studies of biological processes. The advanced data analysis methods allow one to meaningfully interpret the scattering data from monodisperse systems, from transient complexes as well as flexible and heterogeneous systems in terms of structural models. Especially powerful are hybrid approaches utilizing SAXS with high-resolution structural techniques, but also with biochemical, biophysical, and computational methods. Here, we review the recent developments in the experimental SAXS practice and in analysis methods with a specific focus on the joint use of SAXS with complementary methods.


2011 ◽  
Vol 6 ◽  
pp. 2402041-2402041 ◽  
Author(s):  
Morgan W. SHAFER ◽  
Devon J. BATTAGLIA ◽  
Ezekial A. UNTERBERG ◽  
John M. CANIK ◽  
Todd E. EVANS ◽  
...  
Keyword(s):  
X Ray ◽  

2020 ◽  
Vol 1 (3) ◽  
pp. 137-146
Author(s):  
Yun Chen ◽  
Gongfa Jiang ◽  
Yue Li ◽  
Yutao Tang ◽  
Yanfang Xu ◽  
...  

Abstract The coronavirus disease 2019 (COVID-19) has infected more than 9.3 million people and has caused over 0.47 million deaths worldwide as of June 24, 2020. Chest imaging techniques including computed tomography and X-ray scans are indispensable tools in COVID-19 diagnosis and its management. The strong infectiousness of this disease brings a huge burden for radiologists. In order to overcome the difficulty and improve accuracy of the diagnosis, artificial intelligence (AI)-based imaging analysis methods are explored. This survey focuses on the development of chest imaging analysis methods based on AI for COVID-19 in the past few months. Specially, we first recall imaging analysis methods of two typical viral pneumonias, which can provide a reference for studying the disease on chest images. We further describe the development of AI-assisted diagnosis and assessment for the disease, and find that AI techniques have great advantage in this application.


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