Investigating sediment re-mobilisation due to wave action by means of ADCP echo intensity data

2003 ◽  
Vol 58 (3) ◽  
pp. 467-474 ◽  
Author(s):  
Holger Klein
2014 ◽  
Vol 51 (7) ◽  
pp. 072801
Author(s):  
苍桂华 Cang Guihua ◽  
李明峰 Li Mingfeng ◽  
岳建平 Yue Jianping

Author(s):  
Douglas L. Dorset

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.


Author(s):  
J. van de Graaff ◽  
R. C. Steijn
Keyword(s):  

2020 ◽  
Vol 648 ◽  
pp. 19-38
Author(s):  
AI Azovsky ◽  
YA Mazei ◽  
MA Saburova ◽  
PV Sapozhnikov

Diversity and composition of benthic diatom algae and ciliates were studied at several beaches along the White and Barents seas: from highly exposed, reflective beaches with coarse-grained sands to sheltered, dissipative silty-sandy flats. For diatoms, the epipelic to epipsammic species abundance ratio was significantly correlated with the beach index and mean particle size, while neither α-diversity measures nor mean cell length were related to beach properties. In contrast, most of the characteristics of ciliate assemblages (diversity, total abundance and biomass, mean individual weight and percentage of karyorelictids) demonstrated a strong correlation to beach properties, remaining low at exposed beaches but increasing sharply in more sheltered conditions. β-diversity did not correlate with beach properties for either diatoms or ciliates. We suggest that wave action and sediment properties are the main drivers controlling the diversity and composition of the intertidal microbenthos. Diatoms and ciliates, however, demonstrated divergent response to these factors. Epipelic and epipsammic diatoms exhibited 2 different strategies to adapt to their environments and therefore were complementarily distributed along the environmental gradient and compensated for each other in diversity. Most ciliates demonstrated a similar mode of habitat selection but differed in their degree of tolerance. Euryporal (including mesoporal) species were relatively tolerant to wave action and therefore occurred under a wide range of beach conditions, though their abundance and diversity were highest in fine, relatively stable sediments on sheltered beaches, whereas the specific interstitial (i.e. genuine microporal) species were mostly restricted to only these habitats.


2021 ◽  
Vol 13 (9) ◽  
pp. 1779
Author(s):  
Xiaoyan Yin ◽  
Zhiqun Hu ◽  
Jiafeng Zheng ◽  
Boyong Li ◽  
Yuanyuan Zuo

Radar beam blockage is an important error source that affects the quality of weather radar data. An echo-filling network (EFnet) is proposed based on a deep learning algorithm to correct the echo intensity under the occlusion area in the Nanjing S-band new-generation weather radar (CINRAD/SA). The training dataset is constructed by the labels, which are the echo intensity at the 0.5° elevation in the unblocked area, and by the input features, which are the intensity in the cube including multiple elevations and gates corresponding to the location of bottom labels. Two loss functions are applied to compile the network: one is the common mean square error (MSE), and the other is a self-defined loss function that increases the weight of strong echoes. Considering that the radar beam broadens with distance and height, the 0.5° elevation scan is divided into six range bands every 25 km to train different models. The models are evaluated by three indicators: explained variance (EVar), mean absolute error (MAE), and correlation coefficient (CC). Two cases are demonstrated to compare the effect of the echo-filling model by different loss functions. The results suggest that EFnet can effectively correct the echo reflectivity and improve the data quality in the occlusion area, and there are better results for strong echoes when the self-defined loss function is used.


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