scholarly journals A Highly Cost‐Efficient Large‐Scale Uniform Laminar Plasma Jet Array Enhanced by V – I Characteristic Modulation in a Non‐Self‐Sustained Atmospheric Discharge

2020 ◽  
Vol 7 (6) ◽  
pp. 1902616 ◽  
Author(s):  
Jing Li ◽  
Jing Wang ◽  
Bingying Lei ◽  
Tongyi Zhang ◽  
Jie Tang ◽  
...  
2021 ◽  
Vol 305 ◽  
pp. 130743
Author(s):  
Hui-Yu Zhang ◽  
Sen-Hui Liu ◽  
Chang-Jiu Li ◽  
Cheng-Xin Li

2020 ◽  
Vol 21 (11) ◽  
pp. 4127
Author(s):  
Xu Han ◽  
James Kapaldo ◽  
Yueying Liu ◽  
M. Sharon Stack ◽  
Elahe Alizadeh ◽  
...  

The effective clinical application of atmospheric pressure plasma jet (APPJ) treatments requires a well-founded methodology that can describe the interactions between the plasma jet and a treated sample and the temporal and spatial changes that result from the treatment. In this study, we developed a large-scale image analysis method to identify the cell-cycle stage and quantify damage to nuclear DNA in single cells. The method was then tested and used to examine spatio-temporal distributions of nuclear DNA damage in two cell lines from the same anatomic location, namely the oral cavity, after treatment with a nitrogen APPJ. One cell line was malignant, and the other, nonmalignant. The results showed that DNA damage in cancer cells was maximized at the plasma jet treatment region, where the APPJ directly contacted the sample, and declined radially outward. As incubation continued, DNA damage in cancer cells decreased slightly over the first 4 h before rapidly decreasing by approximately 60% at 8 h post-treatment. In nonmalignant cells, no damage was observed within 1 h after treatment, but damage was detected 2 h after treatment. Notably, the damage was 5-fold less than that detected in irradiated cancer cells. Moreover, examining damage with respect to the cell cycle showed that S phase cells were more susceptible to DNA damage than either G1 or G2 phase cells. The proposed methodology for large-scale image analysis is not limited to APPJ post-treatment applications and can be utilized to evaluate biological samples affected by any type of radiation, and, more so, the cell-cycle classification can be used on any cell type with any nuclear DNA staining.


2019 ◽  
Vol 489 (3) ◽  
pp. 3582-3590 ◽  
Author(s):  
Dmitry A Duev ◽  
Ashish Mahabal ◽  
Frank J Masci ◽  
Matthew J Graham ◽  
Ben Rusholme ◽  
...  

ABSTRACT Efficient automated detection of flux-transient, re-occurring flux-variable, and moving objects is increasingly important for large-scale astronomical surveys. We present braai, a convolutional-neural-network, deep-learning real/bogus classifier designed to separate genuine astrophysical events and objects from false positive, or bogus, detections in the data of the Zwicky Transient Facility (ZTF), a new robotic time-domain survey currently in operation at the Palomar Observatory in California, USA. Braai demonstrates a state-of-the-art performance as quantified by its low false negative and false positive rates. We describe the open-source software tools used internally at Caltech to archive and access ZTF’s alerts and light curves (kowalski ), and to label the data (zwickyverse). We also report the initial results of the classifier deployment on the Edge Tensor Processing Units that show comparable performance in terms of accuracy, but in a much more (cost-) efficient manner, which has significant implications for current and future surveys.


2016 ◽  
Vol 13 (5) ◽  
pp. 1387-1408 ◽  
Author(s):  
Zhen Zhang ◽  
Niklaus E. Zimmermann ◽  
Jed O. Kaplan ◽  
Benjamin Poulter

Abstract. Simulations of the spatiotemporal dynamics of wetlands are key to understanding the role of wetland biogeochemistry under past and future climate. Hydrologic inundation models, such as the TOPography-based hydrological model (TOPMODEL), are based on a fundamental parameter known as the compound topographic index (CTI) and offer a computationally cost-efficient approach to simulate wetland dynamics at global scales. However, there remains a large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl (Lund–Potsdam–Jena Wald Schnee und Landschaft version) Dynamic Global Vegetation Model (DGVM) and quantifies uncertainties by comparing three digital elevation model (DEM) products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. In addition, we found that calibrating TOPMODEL with a benchmark wetland data set can help to successfully delineate the seasonal and interannual variation of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows the best accuracy for capturing the spatiotemporal dynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is  ∼ 10.3 Mkm2 (106 km2), with a mean annual maximum of  ∼ 5.17 Mkm2 for 1980–2010. When integrated with wetland methane emission submodule, the uncertainty of global annual CH4 emissions from topography inputs is estimated to be 29.0 Tg yr−1. This study demonstrates the feasibility of TOPMODEL to capture spatial heterogeneity of inundation at a large scale and highlights the significance of correcting maximum wetland extent to improve modeling of interannual variations in wetland area. It additionally highlights the importance of an adequate investigation of topographic indices for simulating global wetlands and shows the opportunity to converge wetland estimates across LSMs by identifying the uncertainty associated with existing wetland products.


RNA ◽  
2016 ◽  
Vol 22 (9) ◽  
pp. 1454-1466 ◽  
Author(s):  
Anna-Lisa Fuchs ◽  
Ancilla Neu ◽  
Remco Sprangers

2012 ◽  
Vol 78 (13) ◽  
pp. 4740-4743 ◽  
Author(s):  
Siu F. Lee ◽  
Vanessa L. White ◽  
Andrew R. Weeks ◽  
Ary A. Hoffmann ◽  
Nancy M. Endersby

ABSTRACTWe have developed and validated two new fluorescence-based PCR assays to detect theWolbachia wMel strain inAedes aegyptiand thewRi andwAu strains inDrosophila simulans. The new assays are accurate, informative, and cost-efficient for large-scaleWolbachiascreening.


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