Coastal morphology: analysis, modelling and prediction

We are traditionally used Microscope in clinical laboratory for determination of white blood cells of human blood smear. Now, in this study we were used Foldscope with Smartphone in the place of Microscope and examine many samples of human blood smear which was collected from local diagnostic centers. We were very easily quantity & morphology analysis of all types of WBC cells such as Neutrophils, Lymphocytes, Monocytes, Eosionophils, Basophils in blood smear with the help of Foldscope & image taken by Smartphone. The main objective of this study is to use Foldscope for quantity & morphology analysis of human WBCs at field level especially poor resource area where healthcare services or centers is not available & where carry of microscope is not possible.

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Application of remote sensing technology to the relation of submarine pipelines and coastal morphology

Water Science & Technology ◽

10.2166/wst.1995.0077 ◽

1995 ◽

Vol 32 (2) ◽

pp. 77-83

Author(s):

Y. Yüksel ◽

D. Maktav ◽

S. Kapdasli

Keyword(s):

Remote Sensing ◽

Sediment Transport ◽

Surf Zone ◽

Hydrodynamic Forces ◽

Construction Site ◽

Coastal Morphology ◽

Remote Sensing Technology ◽

Sensing Technology ◽

Sea Bed

Submarine pipelines must be designed to resist wave and current induced hydrodynamic forces especially in and near the surf zone. They are buried as protection against forces in the surf zone, however this procedure is not always feasible particularly on a movable sea bed. For this reason the characteristics of the sediment transport on the construction site of beaches should be investigated. In this investigation, the application of the remote sensing method is introduced in order to determine and observe the coastal morphology, so that submarine pipelines may be protected against undesirable seabed movement.

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A fully automated pipeline for the dynamic at‐line morphology analysis of microscale Aspergillus cultivation

Fungal Biology and Biotechnology ◽

10.1186/s40694-021-00109-4 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Roman Jansen ◽

Kira Küsters ◽

Holger Morschett ◽

Wolfgang Wiechert ◽

Marco Oldiges

Keyword(s):

Filamentous Fungi ◽

High Throughput ◽

Automated Image Analysis ◽

Height Velocity ◽

Pellet Size ◽

Application Study ◽

Liquid Handling ◽

Morphology Analysis ◽

Development And Utilization ◽

Increasing Demand

Abstract Background Morphology, being one of the key factors influencing productivity of filamentous fungi, is of great interest during bioprocess development. With increasing demand of high-throughput phenotyping technologies for fungi due to the emergence of novel time-efficient genetic engineering technologies, workflows for automated liquid handling combined with high-throughput morphology analysis have to be developed. Results In this study, a protocol allowing for 48 parallel microbioreactor cultivations of Aspergillus carbonarius with non-invasive online signals of backscatter and dissolved oxygen was established. To handle the increased cultivation throughput, the utilized microbioreactor is integrated into a liquid handling platform. During cultivation of filamentous fungi, cell suspensions result in either viscous broths or form pellets with varying size throughout the process. Therefore, tailor-made liquid handling parameters such as aspiration/dispense height, velocity and mixing steps were optimized and validated. Development and utilization of a novel injection station enabled a workflow, where biomass samples are automatically transferred into a flow through chamber fixed under a light microscope. In combination with an automated image analysis concept, this enabled an automated morphology analysis pipeline. The workflow was tested in a first application study, where the projected biomass area was determined at two different cultivation temperatures and compared to the microbioreactor online signals. Conclusions A novel and robust workflow starting from microbioreactor cultivation, automated sample harvest and processing via liquid handling robots up to automated morphology analysis was developed. This protocol enables the determination of projected biomass areas for filamentous fungi in an automated and high-throughput manner. This measurement of morphology can be applied to describe overall pellet size distribution and heterogeneity.

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Phase and Morphology Analysis in Synthesis of CuFeSe2 Powder

Integrated Ferroelectrics ◽

10.1080/10584587.2021.1911299 ◽

2021 ◽

Vol 216 (1) ◽

pp. 322-328

Author(s):

Kegao Liu ◽

Mingxing Jing ◽

Yong Xu

Keyword(s):

Morphology Analysis

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Coastal Morphology Assessment and Coastal Protection

Journal of Marine Science and Engineering ◽

10.3390/jmse9070713 ◽

2021 ◽

Vol 9 (7) ◽

pp. 713

Author(s):

Yoshimichi Yamamoto

Keyword(s):

Coastal Protection ◽

Coastal Morphology

Sediment-collecting in rivers and seas to secure a large amount of aggregate reduces the supply of earth and sand to coasts [...]

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244An automated beat exclusion algorithm to improve beat-to-beat P-wave morphology analysis

EP Europace ◽

10.1093/europace/euaa162.165 ◽

2020 ◽

Vol 22 (Supplement_1) ◽

Author(s):

D Tachmatzidis ◽

D Filos ◽

I Chouvarda ◽

A Tsarouchas ◽

D Mouselimis ◽

...

Keyword(s):

P Wave ◽

Strongly Correlated ◽

Wave Analysis ◽

Morphology Analysis ◽

Wave Morphology ◽

History Of ◽

Ectopic Beats ◽

Rater Variability ◽

Operator Workload

Abstract Background A manually beat-to-beat P-wave analysis has previously revealed the existence of multiple P-wave morphologies in patients with paroxysmal Atrial Fibrillation (AF) while on sinus rhythm, distinguishing them from healthy, AF free patients. Purpose The aim of this study was to investigate the effectiveness of an Automated Beat Exclusion algorithm (ABE) that excludes noisy or ectopic beats, replacing manual beat evaluation during beat-to-beat P-wave analysis, by assessing its effect on inter-rater variability and reproducibility. Methods Beat-to-beat P-wave morphology analysis was performed on 34 ten-minute ECG recordings of patients with a history of AF. Each recording was analyzed independently by two clinical experts for a total of four analysis runs; once with ABE and once again with the manual exclusion of ineligible beats. The inter-rater variability and reproducibility of the analysis with and without ABE were assessed by comparing the agreement of analysis runs with respect to secondary morphology detection, primary morphology ECG template and the percentage of both, as these aspects have been previously used to discriminate PAF patients from controls. Results Comparing ABE to manual exclusion in detecting secondary P-wave morphologies displayed substantial (Cohen"s k = 0.69) to almost perfect (k = 0.82) agreement. Area difference among auto and manually calculated main morphology templates was in every case <5% (p < 0.01) and the correlation coefficient was >0.99 (p < 0.01). Finally, the percentages of beats classified to the primary or secondary morphology per recording by each analysis were strongly correlated, for both main and secondary P-wave morphologies, ranging from ρ=0.756 to ρ=0.940 (picture) Conclusion The use of the ABE algorithm does not diminish inter-rater variability and reproducibility of the analysis. The primary and secondary P-wave morphologies produced by all analyses were similar, both in terms of their template and their frequency. Based on the results of this study, the ABE algorithm incorporated in the beat-to-beat P-wave morphology analysis drastically reduces operator workload without influencing the quality of the analysis. Abstract Figure.

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