2,020 research outputs found
Density and stratigraphy of firn at Lomonosovfonna derived from shallow cores in 1997-2015
No full textThe present dataset contains measurements of density and observations of stratigraphy in the subsurface snow/firn/ice done at Lomonosovfonna during 1997-2015. The variables are named according to the year, when the data was derived: "LF" for Lomonosovfonna and "NN" corresponds to the year, e.g. 97 - 1997, 07 - 2007. Most variables contain the following fields:rho* - density measurements: column 1 - depth of sample top, m; column 2 - depth of sample bottom, m; column 3 - density values, kg m^-3;rho*_reg - density measurements on a regular 1 cm spaced grid, gaps are filled by linear interpolation and extrapolated using "nearest neighbor" logic; column 1 - depth, m; column 2 - density values, kg m^-3;strat - stratigraphy: column 1 - depth of sample top, m; column 2 - depth of sample bottom, m; column 3 - stratigraphy coded as: 1 - snow, 2 - firn, 3 - ice lens;lat* - latitude, degrees to the North of equator;lon* - longitude, degrees to the East of the prime meridian;h* - elevation, m above the sea level.LF97: Six shallow cores were drilled in spring 1997 approximately along the centerline of Nordenskiöldbreen. A system of mass balance stakes at locations of the cores is maintained by Uppsala university. The density is approximated from visual stratigraphic description according to the classification suggested by Pohjola et al., 2002 (see Table 1 there). The density values are the result of averaging of density values ascribed to stratigraphic units identified in core pieces and weighted by their respective thicknesses.LF99: Three shallow cores were drilled in the end of April 1999 at the location where in 1997 a 120 m long ice core was drilled. The cores were drilled along a North-South oriented line with a spacing of 2.5 m between the neighboring cores. The fields in the LF99 variable are named accordingly: fields with the data from the southern location contain "S", northern - "N", central - "C". The field and laboratory work was done by Håkan Samuelsson. Methods and analysis are described in detail in the Master Thesis: "Distribution of melt layers on the ice field Lomonosovfonna, Spitsbergen", defended at Uppsala University in 2001.LF08: One shallow core was drilled by Sanja Forsström, Elisabeth Isaksson, Veijo Pohjola and Jim Hedfors within ca 100 from the location where in 1997 a 120 m long ice core was drilled. Density was measured using two different methods at the cold lab of the Norwegian Polar Institute in Tromso by Sanja Forsström and Tonu Martma. The structure field "rho" contains values calculated from measured geometrical dimensions of the core samples and weights. The fields "rhoDEPcorepieces", "rhoDEPionsamples" and "rhoDEPisotopesamples" contain density values measured using dielectric profiling in three sets of samples.LF12: The core was drilled by Veijo Pohjola and Rickard Pettersson on the 13 of April 2012. Field notes done by Sergey Marchenko. Cold lab operations were done by Sergey Marchenko and Elena Klimenko at the University Centre in Svalbard (UNIS) in Longyearbyen, Norway during 26 April - 3 May 2012. Density was measured in cylindrical and cuboid samples prepared using a band saw to ensure regular shape. The structure field "rho_c" contains density measurements done using cylindrical core pieces. The structure field "rho_rb" contains density measurements done using relatively long cuboid samples prepared from cylindrical core pieces using a band saw. The structure field "rho_rs" contains density measurements done using shorter cuboid samples prepared from the longer pieces using a band saw. The structure field "rho_reg" is based on the "rho_rs" structure field.LF13: The core was drilled by Christian Zdanowics, Dorothee Vallot and Veijo Pohjola in April 2013 and later analyzed by Carmen Vega in the cold lab of the Norwegian Polar Institute in Tromso, Norway.LF14: The core was drilled by Veijo Pohjola and Ward van Pelt in the end of March 2014. Field notes are done by Veijo Pohjola. Cold lab operations were done by Sergey Marchenko, William Kohler and Elisbeth Isaksson in the Norwegian Polar Institute facilities in Tromso, Norway, during 05-10 of October 2014. Density was measured in cylindrical or cuboid samples prepared using a band saw to ensure regular shape.LF15: the core was drilled by Veijo Pohjola and Ward van Pelt on the 15th of April 2015. Field notes are done by Veijo Pohjola. Cold lab operations were done by Sergey Marchenko, Glennda Villanflor and Elisbeth Isaksson in the Norwegian Polar Institute facilities in Tromso, Norway, during 02-05 of November 2015. Density was measured in cylindrical or cuboid samples prepared using a band saw to ensure regular shape. The data is used in the following publications:1) Marchenko, S., Cheng, G., Lötstedt, P., Pohjola, V., Pettersson, R., van Pelt, W., Reijmer, C., (2019). Thermal conductivity of firn at Lomonosovfonna, Svalbard, derived from subsurface temperature measurements, The Cryosphere Discussions, doi: 10.5194/tc-2018-294;2) Marchenko, S., van Pelt, W., Claremar, B., Pohjola, V., Pettersson, R., Machguth, H., Reijmer, C., (2017). Parameterizing Deep Water Percolation Improves Subsurface Temperature Simulations by a Multilayer Firn Model, Frontiers in Earth Science, doi: 10.3389/feart.2017.00016;3) Marchenko, S., Pohjola, V., Pettersson, R., van Pelt, W., Vega, C., Machguth, H., Bøggild C., Isaksson, E., (2017). A plot-scale study of firn stratigraphy at Lomonosovfonna, Svalbard, using ice cores, borehole video and GPR surveys in 2012-14, Journal of Glaciology, doi: 10.1017/jog.2016.118;4) Pohjola, V., Moore, J., Isaksson, E., Jauhiainen, T., van de Wal, R., Martma, T., Meijer, H., Vaikmäe, R., (2002). Effect of periodic melting on geochemical and isotopic signals in an ice core from Lomonosovfonna, Svalbard, Journal of Geophysical Research, doi:10.1029/2000JD000149;5) Isaksson, E., Pohjola, V., Jauhiainen, T., Moore, J., Pinglot, J., Vaikmäe, R., van De Wal, R., Hagen, J.O., Ivask, J., Karlöf, L., Martma, T., Meijer, H., Mulvaney, R., Thomassen M., van den Broeke, M., (2001). A new ice-core record from Lomonosovfonna, Svalbard: Viewing the 1920–97 data in relation to present climate and environmental conditions, Journal of Glaciology, doi:10.3189/172756501781832313;6) Pälli, A., Kohler, J., Isaksson, E., Moore, J., Pinglot, J., Pohjola, V., & Samuelsson, H., (2002). Spatial and temporal variability of snow accumulation using ground-penetrating radar and ice cores on a Svalbard glacier, Journal of Glaciology, doi:10.3189/172756502781831205;7) van Pelt, W, Pettersson, R., Pohjola, V., Marchenko, S., Claremar, B., and Oerlemans, J., (2014). Inverse estimation of snow accumulation along a radar transect on Nordenskiöldbreen, Svalbard, Journal of Geophysical Research, doi:10.1002/2013JF003040;8) Vega, C., Pohjola, V., Beaudon, E., Claremar, B., van Pelt, W., Pettersson, R., Isaksson, E., Martma, T., Schwikowski, M., Bøggild, C., (2016). A synthetic ice core approach to estimate ion relocation in an ice field site experiencing periodical melt: a case study on Lomonosovfonna, Svalbard, The Cryosphere, doi:10.5194/tc-10-961-2016;</div
Climatic drivers
No full textContributing authors : Carl Barrette, Diane Chaumont, Chris Derksen, James Hamilton, Stephen Howell, Thomas Ingeman-Nielsen, Thomas James, Diane Lavoie, Sergey Marchenko, Steffen M. Olsen, Christian B. Rodehacke, Martin Sharp, Sharon L. Smith, Martin Stendel, Rasmus T. Tonbo
Maritime activity in the high north – the range of unwanted incidents and risk patterns
No full textAuthor's accepted version (post-print).This is the accepted manuscript (post-print) of the article Marchenko, N., Borch, O. J., Markov, S. V. & Andreassen, N. (2015). Maritime activity in the high north – the range of unwanted incidents and risk patterns. Proceedings – International Conference on Port and Ocean Engineering under Arctic Conditions available at http://www.poac.com/PapersOnline.htm
Intermittent high-frequency percussive ventilation therapy in 3 patients with severe covid-19 pneumonia
No full textObjective: Background: Cases Reports: Conclusions: Unusual clinical course High-frequency percussive ventilation (HFPV) is a method that combines mechanical ventilation with high-fre-quency oscillatory ventilation. This report describes 3 cases of patients with severe COVID-19 pneumonia who received intermittent adjunctive treatment with HFPV at a single center without requiring admission to the Intensive Care Unit (ICU). Case 1 was a 60-year-old woman admitted to the hospital 14 days after the onset of SARS-CoV-2 infection symptoms, and cases 2 and 3 were men aged 65 and 72 years who were admitted to the hospital 10 days after the onset of SARS-CoV-2 infection symptoms. All 3 patients presented with clinical deterioration accom-panied by worsening lung lesions on computed tomography (CT) scans after 21 days from the onset of symp-toms. SARS-CoV-2 infection was confirmed in all patients by real-time reverse transcription-polymerase chain reaction (RT-PCR) assay from nasal swabs. All 3 patients had impending respiratory failure when non-invasive intermittent HFPV therapy was initiated. After therapy, the patients had significant clinical improvement and visibly decreased lung lesions on followup CT scans performed 4-6 days later. The 3 cases described in this report showed that the use of intermittent adjunctive treatment with HFPV in patients with severe pneumonia due to infection with SARS-CoV-2 improved lung function and may have prevent-ed clinical deterioration. However, recommendations on the use of intermittent HFPV as an adjunctive treatment in COVID-19 pneumonia requires large-scale controlled clinical studies. In the pandemic context, with a shortage of ICU beds, avoiding ICU admission by using adjunctive therapies on the ward is a useful option
High-Order Block Toeplitz Inner-Bordering method for solving the Gelfand-Levitan-Marchenko equation
No full textWe propose a high precision algorithm for solving the
Gelfand-Levitan-Marchenko equation. The algorithm is based on the block version
of the Toeplitz Inner-Bordering algorithm of Levinson's type. To approximate
integrals, we use the high-precision one-sided and two-sided Gregory quadrature
formulas. Also we use the Woodbury formula to construct a computational
algorithm. This makes it possible to use the almost Toeplitz structure of the
matrices for the fast calculations
SERGEY YURIEVICH PREOBRAZHENSKY, SCHOLAR AND AUTHOR OF VERSES
No full textThe article is written in memoria of Sergey Yurievich Preobrahzhensky, linguist and poet. It tackles upon the scientific interests of the scholar, deals with his principal concepts in prosody and other spheres of poetics. Besides, It also contains a brief characteristics and examples of his own poetic work
Sergey Witte and his Foreign Investment Policy in the studies by English-speaking scholars
No full text. The article discusses the development of the interest of English-speaking historians in the foreign investment policy of Sergey Witte. The paper also examines the role of the Secret Memorandum of Sergey Wittein the understanding of the foreign investment in the Russian economy. The author shows that Russian and English-speaking historians, despite the political upheavals of the 20th century, were engaged in a scholarly conversation in their discussion of the subject
Subsurface temperature at Lomonosovfonna, Svalbard, April 2012-2016
No full textThe dataset contains subsurface temperature measurements done at Lomonosovfonna, Svalbard, during April 2012 - 2016.
All measurements are done at the site with coordinates: 78.8235 N, 17.432 E.
The data is contained in four cells of a matlab structure containing data from installations deployed in April 2012 - cell 1, April 2013 - cell 2, April 2014 - cell 3 and April 2015 - cell 4. In 2012-2014 nine thermistor strings were installed in each year. The nine T-strings were arranged in a 3*3 square grid with a 3 m spacing between neighboring strings. In 2015 one t-string was installed.
Hardware: Campbell Scientific CR10X data loggers in combination with several relay multiplexers (AM416 of AM16/32B) were used for temperature measurements. For that a reference temperature stable resistor (Rr Ohm) was connected is series with thermistors. Known excitation voltage (Ue) was supplied to the circuit and the voltage was measured (Um) at the leads of the reference resistor.
The resistance of a thermistor (Rt) was then calculated as:
Rt = Ue * Rr / Um - Rr.
The resistance was then converted to temperature values provided by the manufacturer of thermistors.
Technical information is contained in the variables: LF{N}.T.system.
The raw temperature measurements along with the time stamps and depths are contained in the variables LF{N}.T.system.T_raw, LF{N}.T.system.t_raw and LF{N}.T.system.z_raw.
After unpacking the data was subjected to the following post-processing steps:
- delete data from sensors that were left above the snow surface
- for the sensors installed in April 2013: delete data after 2013 July 12
- reset temperature values outsides of the range [-40 +10] degC to NaN
- for the sensors installed in April 2015: correct values from one of the sensors by linear interpolation in time between the following time points: 2015 November 15 02:00 and 2015 November 15 14:00, 2015 December 18 15:00 and 2015 December 19 21:00
- introduce corrections to depths of sensors to match temperature distributions measured at different T-strings during the periods dominated by conductive heat exchange in the firn pack
corrections are contained in the variable LF{N}.T.system.z_off and are given in meters.
- delete data from sensors that are deemed erroneous.
For the sensors installed in April 2012 that is: sensor 1 in T-string 9.
For the sensors installed in April 2013 that is: sensors 1 and 2 in T-string 2, sensors 1-6 in T-string 3, sensors 1-6 in T-string 4, sensors 1-5 in T-string 5, sensors 1-7 in T-string 6.
For the sensors installed in April 2014 that is: sensors 1 in T-string 1, sensor 1 in T-string 7, sensor 1 in T-string 9.
- apply offsets for individual sensors defined as the mode during the time period, when the temperature is expected to be at 0 degC. For the sensors installed in April 2012 and 2015 that is the entire measurement period. For the sensors installed in April 2014 the periods are defined based on subjective data analysis and are different for individual sensors. For the sensors installed in April 2013 and some sensors installed in April 2014 the offsets are set to 0 degC. The applied temperature offsets are contained in the variables: LF{N}.T.system.off. The relation between the number of temperature values equal to the offset and the total number of values during the calibration time is saved in the variable LF{N}.T.system.f.
After the above described post-processing steps the data was saved in the variable LF{N}.T.T (temperature values), LF{N}.T.z (depths of sensors) and LF{N}.T.t (time stamps).
Data interpolated on a regular grid is contained in the variables: LF{N}.T.T_i (temperature values) and LF{N}.T.z_i (depth vectors).
Data laterally averaged across all T-strings is contained in the variables: LF{N}.T.T_a (temperature values) and LF{N}.T.z_a (depth vectors).
The standard deviation in interpolated temperature values belonging to the same depth but coming from different T-strings are contained in the variables LF{N}.T.T_sd
Spectral, Scattering and Dynamics: Gelfand–Levitan–Marchenko–Krein Equations
No full textIn this paper, we consider the Gelfand–Levitan–Marchenko–Krein approach. It is used for solving a variety of inverse problems, like inverse scattering or inverse problems for wave-type equations in both spectral and dynamic formulations. The approach is based on a reduction of the problem to the set of integral equations. While it is used in a wide range of applications, one of the most famous parts of the approach is given via the inverse scattering method, which utilizes solving the inverse problem for integrating the nonlinear Schrodinger equation. In this work, we present a short historical review that reflects the development of the approach, provide the variations of the method for 1D and 2D problems and consider some aspects of numerical solutions of the corresponding integral equations
An Overview of Economics
No full textI assume that your objective of ’Economics 101’ is to try to understand how the economy works instead of going through an economic curriculum. If so you are guaranteed to have fun. I personally undertook a similar journey ten years back. I would say that it is better to understand the principles of economics and then try to understand the economy/economic situation of any given country. My recommendations (for BSc students and everyone who is interested in economics101) are based on my own readings: Sloman’s ”Essentials of economics;” Gwartney et al. ”Economics: Private Public Choice;” Jesus Huerta de Soto’s ”The Austrian School: Market Order and Entrepreneurial Creativity;” Rodrik’s ”Economics Rules;” Foley’s ”Adam’s fallacy: a guide to economic theology;” De Soto’s ”The mystery of capital: Why capitalism triumphs in the West and fails everywhere else;” Harford’s ”The Undercover Economist;” Levitt and Dubner’s ”Freakonomics.”This Paper should not be reported as representing the views of Central Bank of Armenia. The views in this paper are those of the author and should not be interpreted as those of Central Bank of Armenia
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