Classification of electrohydrodynamic spraying modes of water in air at atmospheric pressure

The investigations of the spectrum of fluorine which had been made up to the year 1923 are summarised in Kayser’s ‘Handbuch der Spektroscopie’ (vol. 5, p. 444; vol. 7, p. 401). They include measurements of lines attributed to fluorine by various workers, but there is no attempt to classify the lines of the neutral atom, the singly ionised atom, etc. Gale and Monk, however, have since published further measures of fluorine lines, and have made the beginnings of a classification by distinguishing the lines produced in vacuum-tube discharges through fluorine gas from those obtained only from a spark discharge in the gas at atmospheric pressure: Their work has been followed up by Carragan, who has made a study of the Zeeman effects for some of the lines of the former group, and, from the rules of Landé, has deduced the existence of multiplets of the first order and suggested certain term combinations. The results here recorded are the first-fruits of an investigation of the fluorine spectrum under different conditions of excitation. Evidence of at least three successive spectra has been obtained as the exciting agency is gradually intensified. Under the gentlest stimulus the lines which appear form an isolated group in the red and infra-red region of the spectrum. They are in the main identical with the vacuum-tube lines of Gale and Monk, and have been produced simultaneously with strong bands of silicon tetrafluoride when a discharge has been passed through this gas. They have accordingly been assigned to the neutral atom of fluorine. The identification, measurement and classification of these lines form the substance of the present paper. Data concerning the spectra produced by more intense discharges will be published in due course.

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Classification of surface atmospheric pressure fields in the Laptev and East Siberian seas

Arctic and Antarctic Research ◽

10.30758/0555-2648-2021-67-4-394-405 ◽

2021 ◽

Vol 67 (4) ◽

pp. 394-405

Author(s):

V. S. Porubaev ◽

L. N. Dyment

Keyword(s):

Surface Pressure ◽

Atmospheric Pressure ◽

Ice Cover ◽

The Arctic ◽

Wind Fields ◽

Arctic Seas ◽

Pressure Fields ◽

Ice Drift ◽

Waves And Currents

The need for classifying surface atmospheric pressure fields over the Arctic seas arose as a method was being developed for predicting the characteristics of discontinuities (leads) in the sea ice cover. Wind, which is determined by the atmospheric pressure field, acts on the ice cover and causes it to drift. Leads are formed in the ice cover due to the irregularity of ice drift. Ice drift can be caused by several factors, such as skewed sea level, tidal waves and currents. However, the main cause of ice drift in the Arctic seas is wind. Each typical field of surface atmospheric pressure corresponds to a certain field of leads in the ice cover. This makes it possible to predict the characteristics of leads in the ice cover by selecting fields similar to predictive fields of atmospheric pressure based on archived data.The variety of atmospheric pressure fields makes it difficult to find an analogue to a given field by simply going through all the corresponding data available in the electronic archive. Classification of atmospheric pressure fields makes it possible to simplify the process of selecting an analogue.To develop the classification, we used daily surface pressure maps at 00 hours GMT for the cold seasons (from mid- October to the end of May) 2016–2021. The atmospheric pressure fields, which were similar in configuration, and hence the wind fields, belonged to the same type. In total, 27 types were identified, applicable both to the Laptev Sea and the East Siberian Sea. Within one type, a division into subtypes was made, depending on the speed of the geostrophic wind.The wind intensity was estimated by the number of isobars multiples of 5 mb on the surface atmospheric pressure map. All the surface pressure fields observed over the waters of the Laptev and East Siberian Seas over the past 5 years have been assigned to one of the types identified using cluster analysis. Each type of atmospheric pressure within the framework of the forecasting method being developed is supposed to correspond to a field of discontinuities in the ice cover.

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Plasma Polymerization at Atmospheric Pressure with a New Type of DBD Reactor for Combinatorial Studies: Classification of Precursor Concentration Dependencies

Plasma Processes and Polymers ◽

10.1002/ppap.201500136 ◽

2015 ◽

Vol 13 (5) ◽

pp. 509-520 ◽

Cited By ~ 8

Author(s):

Jens Philipp ◽

Andreas K. Czerny ◽

Claus-Peter Klages

Keyword(s):

Atmospheric Pressure ◽

Plasma Polymerization ◽

Precursor Concentration ◽

New Type ◽

Dbd Reactor

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The role of lipids in the classification of astrocytoma and glioblastoma using MS tumor profiling

Biomeditsinskaya Khimiya ◽

10.18097/pbmc20206604317 ◽

2020 ◽

Vol 66 (4) ◽

pp. 317-325

Author(s):

V.A. Eliferov ◽

E.S. Zhvansky ◽

A.A. Sorokin ◽

V.A. Shurkhay ◽

D.S. Bormotov ◽

...

Keyword(s):

Atmospheric Pressure ◽

Tumor Tissue ◽

Biological Tissues ◽

Mass Spectrometric ◽

Postoperative Rehabilitation ◽

Machine Learning Methods ◽

Modern Machine

Express MS identification of biological tissues has become a much more accessible research method due to the application of direct specimen ionization at atmospheric pressure. In contrast to traditional methods of analysis employing GC-MS methods for determining the molecular composition of the analyzed objects it eliminates the influence of mutual ion suppression. Despite significant progress in the field of direct MS of biological tissues, the question of mass spectrometric profile attribution to a certain type of tissue still remains open. The use of modern machine learning methods and protocols (e.g., “random forests”) enables us to trace possible relationships between the components of the sample MS profile and the result of brain tumor tissue classification (astrocytoma or glioblastoma). It has been shown that the most pronounced differences in the mass spectrometric profiles of these tumors are due to their lipid composition. Detection of statistically significant differences in lipid profiles of astrocytoma and glioblastoma may be used to perform an express test during surgery and inform the neurosurgeon what type of malignant tissue he is working with. The ability to accurately determine the boundaries of the neoplastic growth significantly improves the quality of both surgical intervention and postoperative rehabilitation, as well as the duration and quality of life of patients.

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Rapid Liquid AP-MALDI MS Profiling of Lipids and Proteins from Goat and Sheep Milk for Speciation and Colostrum Analysis

Proteomes ◽

10.3390/proteomes8030020 ◽

2020 ◽

Vol 8 (3) ◽

pp. 20 ◽

Cited By ~ 1

Author(s):

Cristian Piras ◽

Carlotta Ceniti ◽

Evita Hartmane ◽

Nicola Costanzo ◽

Valeria Maria Morittu ◽

...

Keyword(s):

Atmospheric Pressure ◽

Goat Milk ◽

Speciation Analysis ◽

Maldi Ms ◽

Late Time ◽

Food Fraud ◽

Milk Samples ◽

Sheep Milk ◽

Specific Species

Rapid profiling of the biomolecular components of milk can be useful for food quality assessment and for food fraud detection. Differences in commercial value and availability of milk from specific species are often the reasons for the illicit and fraudulent sale of milk whose species origin is wrongly declared. In this study, a fast, MS-based speciation method is presented to distinguish sheep from goat milk and sheep colostrum at different phases. Using liquid atmospheric pressure (AP)-matrix-assisted laser desorption/ionisation (MALDI) MS, it was possible to classify samples of goat and sheep milk with 100% accuracy in one minute of data acquisition per sample. Moreover, an accuracy of 98% was achieved in classifying pure sheep milk samples and sheep milk samples containing 10% goat milk. Evaluating colostrum quality and postnatal stages represents another possible application of this technology. Classification of sheep colostrum samples that were collected within 6 hours after parturition and 48 hours later was achieved with an accuracy of 84.4%. Our data show that substantial changes in the lipid profile can account for the accurate classification of colostrum collected at the early and late time points. This method applied to the analysis of protein orthologs of different species can, as in this case, allow unequivocal speciation analysis.

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Climate Classification of Pakistan

International Journal of Economic and Environmental Geology ◽

10.46660/ijeeg.vol10.iss2.2019.264 ◽

2019 ◽

Vol 10 (2) ◽

pp. 60-71

Author(s):

Saifullah Khan ◽

Mahmood -Ul- Hasan

Keyword(s):

Atmospheric Pressure ◽

Monsoon Rainfall ◽

Monsoon Season ◽

Atmospheric Condition ◽

Cold Season ◽

Weather Data ◽

Winter Period ◽

Climate Variables ◽

Summer Period

The research covenants amid the evaluation and analysis of the weather data in regards to mean monthlytemperature, precipitation, rainy days, relative humidity, wind direction, atmospheric pressure, evaporation, solarradiation and with the literature cited. The components getting fluctuation in the atmospheric condition comprise ofglobal location, vicinity to ocean, geomorphic reliefs and continental extent, maritime affects, forests and landuse.Based on the daily and monthly temperature, the study area has divided into five localities consisting of hot, warm,mild, cool, and cold. Besides, the five precipitation zones namely arid, semi-arid, sub-humid, humid andundifferentiated highlands have been distinguished during course of work. Generally, eastern longitudes of the countryget substantial downpours amid summers (monsoon season). Though the western areas in winters excluding GilgitBaltistan, where it is from local thunderstorms. Pakistan encounters four precipitation seasons namely winter, premonsoon, monsoon, and post monsoon rainfall. Because of sub-tropical vicinity, the country has experienced twofundamental seasons explicitly winter and summer. Generally, the summer period goes on for five months in mountainsand seven months in plains, whilst the winter period differs for seven months in mountains and five months in plains.The stated two essential rainy periods are auxiliary sub-isolated into four sub-spells to be precisely hot, warm, monsoonand cold season. Based on appropriation and fluctuation of climate variables, Pakistan is classified in five macro areasthat auxiliary sub-curved up into 18 meso and 46 micro scale climate regions.

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Climate Classification of Pakistan

International Journal of Economic and Environmental Geology ◽

10.46660/ojs.v10i2.264 ◽

2019 ◽

Vol 10 (2) ◽

pp. 60-71

Author(s):

Saifullah Khan ◽

Mahmood -Ul- Hasan

Keyword(s):

Atmospheric Pressure ◽

Monsoon Rainfall ◽

Monsoon Season ◽

Atmospheric Condition ◽

Cold Season ◽

Weather Data ◽

Winter Period ◽

Climate Variables ◽

Summer Period

The research covenants amid the evaluation and analysis of the weather data in regards to mean monthlytemperature, precipitation, rainy days, relative humidity, wind direction, atmospheric pressure, evaporation, solarradiation and with the literature cited. The components getting fluctuation in the atmospheric condition comprise ofglobal location, vicinity to ocean, geomorphic reliefs and continental extent, maritime affects, forests and landuse.Based on the daily and monthly temperature, the study area has divided into five localities consisting of hot, warm,mild, cool, and cold. Besides, the five precipitation zones namely arid, semi-arid, sub-humid, humid andundifferentiated highlands have been distinguished during course of work. Generally, eastern longitudes of the countryget substantial downpours amid summers (monsoon season). Though the western areas in winters excluding GilgitBaltistan, where it is from local thunderstorms. Pakistan encounters four precipitation seasons namely winter, premonsoon, monsoon, and post monsoon rainfall. Because of sub-tropical vicinity, the country has experienced twofundamental seasons explicitly winter and summer. Generally, the summer period goes on for five months in mountainsand seven months in plains, whilst the winter period differs for seven months in mountains and five months in plains.The stated two essential rainy periods are auxiliary sub-isolated into four sub-spells to be precisely hot, warm, monsoonand cold season. Based on appropriation and fluctuation of climate variables, Pakistan is classified in five macro areasthat auxiliary sub-curved up into 18 meso and 46 micro scale climate regions.

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