Existence of an additional layer in equatorial ionosphere: other observations

Variability of an additional layer in the equatorial ionosphere over Fortaleza

Journal of Geophysical Research Atmospheres ◽

10.1029/1999ja000020 ◽

2000 ◽

Vol 105 (A5) ◽

pp. 10603-10613 ◽

Cited By ~ 39

Author(s):

N. Balan ◽

I. S. Batista ◽

M. A. Abdu ◽

G. J. Bailey ◽

S. Watanabe ◽

...

Keyword(s):

Equatorial Ionosphere ◽

Additional Layer

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Physical mechanism and statistics of occurrence of an additional layer in the equatorial ionosphere

Journal of Geophysical Research Atmospheres ◽

10.1029/98ja02823 ◽

1998 ◽

Vol 103 (A12) ◽

pp. 29169-29181 ◽

Cited By ~ 93

Author(s):

N. Balan ◽

I. S. Batista ◽

M. A. Abdu ◽

J. MacDougall ◽

G. J. Bailey

Keyword(s):

Physical Mechanism ◽

Equatorial Ionosphere ◽

Additional Layer

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Stratification of the Low-Latitude and Near-EquatorialF2Layer, Topside Ionization Ledge, andF3Layer: What We Know about This? A Review

International Journal of Geophysics ◽

10.1155/2012/938057 ◽

2012 ◽

Vol 2012 ◽

pp. 1-22 ◽

Cited By ~ 12

Author(s):

M. V. Klimenko ◽

B. Zhao ◽

A. T. Karpachev ◽

V. V. Klimenko

Keyword(s):

Electric Field ◽

Physical Mechanism ◽

Equatorial Ionosphere ◽

Layer Formation ◽

Low Latitude ◽

Meridional Component ◽

Ionospheric Physics ◽

Additional Layer ◽

Plasma Diffusion ◽

History Of

A large number of researches have been devoted to the formation of additional layers in theFregion of the equatorial ionosphere, first of which has been published in 1940s. Originally the occurrence of such layer was named “stratification of equatorialF2layer.” The additional layer was later named as theF3layer. The theoretical researches have shown that theF3layer is formed by zonal component of electric field with assistance of meridional component of thermospheric wind and field-aligned plasma diffusion. The physical mechanism of theF3layer formation is clearly formulated for the morning-noon period, although theF3layer is also observed at other hours. This paper presents a brief review into the history of the additional layer researches, describes the current progress of these researches, and identifies the most important problems in this field of the ionospheric physics.

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A novel box for aerosol and droplet guarding and evacuation in respiratory infection (BADGER) for COVID-19 and future outbreaks

Scientific Reports ◽

10.1038/s41598-021-82675-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hau D. Le ◽

Gordon A. Novak ◽

Kevin C. Janek ◽

Jesse Wang ◽

Khang N. Huynh ◽

...

Keyword(s):

Respiratory Infection ◽

Healthcare Providers ◽

Airborne Particles ◽

Risk Of Infection ◽

Indirect Contact ◽

Vacuum Suction ◽

Qualitative And Quantitative ◽

Additional Layer ◽

Increased Risk ◽

Design Construction

AbstractThe coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has infected millions and killed more than 1.7 million people worldwide as of December 2020. Healthcare providers are at increased risk of infection when caring for patients with COVID-19. The mechanism of transmission of SARS-CoV-2 is beginning to emerge as airborne spread in addition to direct droplet and indirect contact as main routes of transmission. Here, we report on the design, construction, and testing of the BADGER (Box for Aerosol and Droplet Guarding and Evacuation in Respiratory Infection), an affordable, scalable device that contains droplets and aerosol particles, thus minimizing the risk of infection to healthcare providers. A semi-sealed environment is created inside the BADGER, which is placed over the head of the patient and maintains at least 12-air changes per hour using in-wall vacuum suction. Multiple hand-ports enable healthcare providers to perform essential tasks on a patient’s airway and head. Overall, the BADGER has the potential to contain large droplets and small airborne particles as demonstrated by simulated qualitative and quantitative assessments to provide an additional layer of protection for healthcare providers treating COVID-19 and future respiratory contagions.

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A Continuously Active Antimicrobial Surface Coating Reduces Bioburden in a Healthcare Setting

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.1105 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s439-s439

Author(s):

Valerie Beck

Keyword(s):

Surface Coating ◽

Geometric Mean ◽

Healthcare Setting ◽

Aerobic Bacteria ◽

Healthcare Settings ◽

Additional Layer ◽

Clostridioides Difficile ◽

Sustained Reduction ◽

Before And After ◽

Healthcare Associated

Background: It is well known that contaminated surfaces contribute to the transmission of pathogens in healthcare settings, necessitating the need for antimicrobial strategies beyond routine cleaning with momentary disinfectants. A recent publication demonstrated that application of a novel, continuously active antimicrobial surface coating in ICUs resulted in the reduction of healthcare-associated infections. Objective: We determined the general microbial bioburden and incidence of relevant pathogens present in patient rooms at 2 metropolitan hospitals before and after application of a continuously active antimicrobial surface coating. Methods: A continuously active antimicrobial surface coating was applied to patient rooms in intensive care units (ICUs) twice over an 18-month period and in non-ICUs twice over a 6-month study period. The environmental bioburden was assessed 8–16 weeks after each treatment. A 100-cm2 area was swabbed from frequently touched areas in patient rooms: patient chair arm rest, bed rail, TV remote, and backsplash behind the sink. The total aerobic bacteria count was determined for each location by enumeration on tryptic soy agar (TSA); the geometric mean was used to compare bioburden before and after treatment. Each sample was also plated on selective agar for carbapenem-resistant Enterobacteriaceae (CRE), vancomycin-resistant enterococci (VRE), methicillin-resistant Staphylococcus aureus (MRSA), and Clostridioides difficile to determine whether pathogens were present. Pathogen incidence was calculated as the percentage of total sites positive for at least 1 of the 4 target organisms. Results: Before application of the antimicrobial coating, total aerobic bacteria counts in ICUs were >1,500 CFU/100 cm2, and at least 30% of the sites were positive for a target pathogen (ie, CRE, VRE, MRSA or C. difficile). In non-ICUs, the bioburden before treatment was at least 500 CFU/100 cm2, with >50% of sites being contaminated with a pathogen. After successive applications of the surface coating, total aerobic bacteria were reduced by >80% in the ICUs and >40% in the non-ICUs. Similarly, the incidence of pathogen-positive sites was reduced by at least 50% in both ICUs and non-ICUs. Conclusions: The use of a continuously active antimicrobial surface coating provides a significant (P < .01) and sustained reduction in aerobic bacteria while also reducing the occurrence of epidemiologically important pathogens on frequently touched surfaces in patient rooms. These findings support the use of novel antimicrobial technologies as an additional layer of protection against the transmission of potentially harmful bacteria from contaminated surfaces to patients.Funding: Allied BioScience provided Funding: for this study.Disclosures: Valerie Beck reports salary from Allied BioScience.

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ATLAS IBL: integration of new HW/SW readout features for the additional layer of Pixel Detector

Journal of Instrumentation ◽

10.1088/1748-0221/6/01/c01018 ◽

2011 ◽

Vol 6 (01) ◽

pp. C01018-C01018

Author(s):

G Bruni ◽

M Bruschi ◽

I D'Antone ◽

J Dopke ◽

D Falchieri ◽

...

Keyword(s):

Pixel Detector ◽

Additional Layer

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Improving the photodetection and stability of a visible-light QDs/ZnO phototransistor via an Al2O3 additional layer

Journal of Materials Chemistry C ◽

10.1039/d0tc05626j ◽

2021 ◽

Author(s):

Sungho Park ◽

Byung Jun Kim ◽

Tae Yeon Kim ◽

Eui Young Jung ◽

Kyu-Myung Lee ◽

...

Keyword(s):

Zinc Oxide ◽

Atomic Layer Deposition ◽

Quantum Dot ◽

Aluminum Oxide ◽

Thin Layer ◽

Visible Light ◽

Atomic Layer ◽

Zno Films ◽

Additional Layer ◽

Layer Deposition

We have developed a visible-light phototransistor with excellent photodetection characteristics and stability via atomic layer deposition (ALD) to add a thin layer of aluminum oxide (Al2O3) to quantum dot (QD)/zinc oxide (ZnO) films.

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Leveraging Multiple Layers of Data To Predict Drosophila Complex Traits

G3 Genes|Genome|Genetics ◽

10.1534/g3.120.401847 ◽

2020 ◽

Vol 10 (12) ◽

pp. 4599-4613

Author(s):

Fabio Morgante ◽

Wen Huang ◽

Peter Sørensen ◽

Christian Maltecca ◽

Trudy F. C. Mackay

Keyword(s):

Precision Agriculture ◽

Complex Traits ◽

Prediction Accuracy ◽

Cellular Response ◽

Complex Trait ◽

Sources Of Information ◽

Starvation Resistance ◽

Expression Levels ◽

Chill Coma ◽

Additional Layer

The ability to accurately predict complex trait phenotypes from genetic and genomic data are critical for the implementation of personalized medicine and precision agriculture; however, prediction accuracy for most complex traits is currently low. Here, we used data on whole genome sequences, deep RNA sequencing, and high quality phenotypes for three quantitative traits in the ∼200 inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) to compare the prediction accuracies of gene expression and genotypes for three complex traits. We found that expression levels (r = 0.28 and 0.38, for females and males, respectively) provided higher prediction accuracy than genotypes (r = 0.07 and 0.15, for females and males, respectively) for starvation resistance, similar prediction accuracy for chill coma recovery (null for both models and sexes), and lower prediction accuracy for startle response (r = 0.15 and 0.14 for female and male genotypes, respectively; and r = 0.12 and 0.11, for females and male transcripts, respectively). Models including both genotype and expression levels did not outperform the best single component model. However, accuracy increased considerably for all the three traits when we included gene ontology (GO) category as an additional layer of information for both genomic variants and transcripts. We found strongly predictive GO terms for each of the three traits, some of which had a clear plausible biological interpretation. For example, for starvation resistance in females, GO:0033500 (r = 0.39 for transcripts) and GO:0032870 (r = 0.40 for transcripts), have been implicated in carbohydrate homeostasis and cellular response to hormone stimulus (including the insulin receptor signaling pathway), respectively. In summary, this study shows that integrating different sources of information improved prediction accuracy and helped elucidate the genetic architecture of three Drosophila complex phenotypes.

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