26 research outputs found
Taskification β Gamification of Tasks
Leading a busy lifestyle can have a negative impact on the productivity levels of individuals. Lack of motivation is also another factor that can influence the output of any task or activity conducted by a user. This also applies to students within an academic context, where the distractions and lack of motivation can have a negative impact on their learning and results. In this paper, we propose βTaskificationβ, a task management mobile application, which incorporates core gamification features. The objective of this application is to increase student engagement and motivation during tasks such as coursework or exam preparation
The influence of environmental forcing on biodiversity and extinction in a resource competition model
In this paper, we study a model of many species that compete, directly or indirectly, for a pool of common resources under the influence of periodic, stochastic, and/or chaotic environmental forcing. Using numerical simulations, we find the number and sequence of species going extinct when the community is initially packed with a large number of species of random initial densities. Thereby, any species with a density below a given threshold is regarded to be extinct
Π¦ΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ²ΡΠΉ ΠΏΡΠΎΡΠΈΠ»Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΊΠ°ΡΠ΄ΠΈΠΎ- ΠΈ ΠΎΡΡΠ°Π»ΡΠΌΠΎΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠ΅ΠΉ
Π‘ΠΎΡΠ΅ΡΠ°Π½Π½Π°Ρ ΠΊΠ°ΡΠ΄ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΈ ΠΎΡΡΠ°Π»ΡΠΌΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡ ΠΈΠΌΠ΅Π΅Ρ Π²ΡΡΠΎΠΊΡΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½ΡΠ½Π½ΠΎΡΡΡ Π² ΡΡΠ°ΡΡΠΈΡ
Π²ΠΎΠ·ΡΠ°ΡΡΠ½ΡΡ
Π³ΡΡΠΏΠΏΠ°Ρ
Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈ ΠΎΠ±ΡΠΈΠ΅ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΡ, ΠΊ ΡΠΈΡΠ»Ρ ΠΊΠΎΡΠΎΡΡΡ
, Π±Π΅Π·ΡΡΠ»ΠΎΠ²Π½ΠΎ, ΠΎΡΠ½ΠΎΡΠΈΡΡΡ Π½Π°ΡΡΡΠ΅Π½ΠΈΠ΅ ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ²ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠΈΠ»Ρ. ΠΠ΄Π½Π°ΠΊΠΎ ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ²ΡΠΉ ΠΏΡΠΎΡΠΈΠ»Ρ ΠΊΡΠΎΠ²ΠΈ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ Π½Π΅ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π»ΡΡ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² ΠΏΠΎΠΆΠΈΠ»ΠΎΠ³ΠΎ Π²ΠΎΠ·ΡΠ°ΡΡΠ° Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ° Ρ Π³Π»Π°ΡΠΊΠΎΠΌΠΎΠΉ. Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ β ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ²ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠΈΠ»Ρ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΊΠ°ΡΠ΄ΠΈΠΎ- ΠΈ ΠΎΡΡΠ°Π»ΡΠΌΠΎΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠ΅ΠΉ. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΎ Π² Π’Π°ΠΌΠ±ΠΎΠ²ΡΠΊΠΎΠΌ ΡΠΈΠ»ΠΈΠ°Π»Π΅ ΠΠΠ’Π Β«ΠΠΈΠΊΡΠΎΡ
ΠΈΡΡΡΠ³ΠΈΡ Π³Π»Π°Π·Π° ΠΈΠΌΠ΅Π½ΠΈ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΠΊΠ° Π‘.Π. Π€Π΅Π΄ΠΎΡΠΎΠ²Π°Β» Π² Π΄Π²ΡΡ
Π³ΡΡΠΏΠΏΠ°Ρ
: ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ° Ρ Π³Π»Π°ΡΠΊΠΎΠΌΠΎΠΉ (n=58 ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ) ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ° (n=49 ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ), ΠΈΠΌΠ΅ΡΡΠΈΡ
Π² ΠΎΠ±ΠΎΠΈΡ
ΡΠ»ΡΡΠ°ΡΡ
ΠΎΠ΄ΠΈΠ½Π°ΠΊΠΎΠ²ΡΠΉ Π²ΠΎΠ·ΡΠ°ΡΡ 60-74 Π»Π΅Ρ. ΠΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ° Π³Π»Π°ΡΠΊΠΎΠΌΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π° Π² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΠΊΡΠΈΡΠ΅ΡΠΈΡΠΌΠΈ Β«ΠΠ°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²Π° ΠΏΠΎ Π³Π»Π°ΡΠΊΠΎΠΌΠ΅Β». ΠΠ»Ρ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΠΈ ΡΠ΅ΡΠ΄ΡΠ° Π²ΡΠΏΠΎΠ»Π½ΡΠ»ΠΈΡΡ ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅, ΡΡ
ΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅, ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅, ΡΠ½Π·ΠΈΠΌΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ² Π² ΠΏΠ»Π°Π·ΠΌΠ΅ ΠΊΡΠΎΠ²ΠΈ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ Π½Π° Π°ΠΏΠΏΠ°ΡΠ°ΡΠ΅ Β«Beckton Dickinson FACS Canto 2 (USA)Β» Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π½Π°Π±ΠΎΡΠ° CBA (BD Biosciences, USA). Π‘ΡΠ΅Π΄ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² ΡΡΠ°Π²Π½ΠΈΠ²Π°Π΅ΠΌΡΡ
Π³ΡΡΠΏΠΏ ΠΎΠ΄ΠΈΠ½Π°ΠΊΠΎΠ²ΠΎΠ³ΠΎ Π²ΠΎΠ·ΡΠ°ΡΡΠ° Π²ΡΡΠ²Π»Π΅Π½Ρ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡ ΠΏΠΎ Π±ΠΎΠ»ΡΡΠΈΠ½ΡΡΠ²Ρ ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ², Π° ΠΈΠΌΠ΅Π½Π½ΠΎ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΠ΅ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΊΠ°ΡΠ΄ΠΈΠΎ- ΠΈ ΠΎΡΡΠ°Π»ΡΠΌΠΎΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠ΅ΠΉ ΠΎΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΠΎ Π³ΡΡΠΏΠΏΡ Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ°. ΠΠΎΠ²ΡΡΠΈΠ»ΠΎΡΡ Π² ΠΏΠ»Π°Π·ΠΌΠ΅ ΠΊΡΠΎΠ²ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ°, ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ Ρ Π³Π»Π°ΡΠΊΠΎΠΌΠΎΠΉ, ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ IL-5, IL-12, IFN-Ξ³, TNF-Ξ± c Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΡΠΌ ΡΠ°Π·Π»ΠΈΡΠΈΠ΅ΠΌ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌΠΈ Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ°. ΠΠ΄Π½Π°ΠΊΠΎ Π½Π°ΠΈΠ²ΡΡΡΠ΅Π΅ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ ΡΡΠ΅Π΄ΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΡΡ
ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ² Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ½ΠΎ Π΄Π»Ρ IL-6 ΠΈ IL-17, ΡΠΎΡΡΠ°Π²ΠΈΠ²ΡΠ΅Π΅ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΊΠ°ΡΠ΄ΠΈΠΎ- ΠΈ ΠΎΡΡΠ°Π»ΡΠΌΠΎΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠ΅ΠΉ 23,8Β±1,1 ΠΏΠ³/ΠΌΠ» ΠΈ 20,2Β±1,7 ΠΏΠ³/ΠΌΠ» ΠΏΡΠΎΡΠΈΠ² 6,3Β±0,3 ΠΏΠ³/ΠΌΠ» ΠΈ 7,9Β±0,5 ΠΏΠ³/ΠΌΠ» ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ°. ΠΠΌΠ΅ΡΡΠ΅ Ρ ΡΠ΅ΠΌ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ ΡΠ½ΠΈΠ·ΠΈΠ»ΡΡ ΡΡΠΎΠ²Π΅Π½Ρ IL-4 ΠΈ IL-10 Π΄ΠΎ 2,2Β±0,2 ΠΏΠ³/ΠΌΠ» ΠΈ 6,4Β±0,4 ΠΏΠ³/ΠΌΠ» ΠΏΡΠΎΡΠΈΠ² 4,8Β±0,3 ΠΏΠ³/ΠΌΠ» ΠΈ 11,9Β±0,6 ΠΏΠ³/ΠΌΠ». ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π»ΠΎΠ³ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ Π²Π΅Π»ΠΈΡΠΈΠ½Ρ ΠΎΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΈΡΠΊΠ° ΠΈΠ·ΡΡΠ΅Π½Π½ΡΡ
ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ² ΠΊΡΠΎΠ²ΠΈ ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°ΡΡ Π½Π΅ΡΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΈ ΡΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΡΠΎΠ³Π»Π°ΡΠ½ΠΎ ΠΊΠΎΡΠΎΡΡΠΌ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ΅ΡΠ½Π°Ρ Π°ΡΡΠΎΡΠΈΠ°ΡΠΈΡ Ρ ΡΠΈΡΠΊΠΎΠΌ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΠΈ ΡΠ΅ΡΠ΄ΡΠ° Ρ Π³Π»Π°ΡΠΊΠΎΠΌΠΎΠΉ ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½Π° Π΄Π»Ρ IL-6 ΠΈ IL-17, Ρ Π²Π΅Π»ΠΈΡΠΈΠ½Π°ΠΌΠΈ ΠΎΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΈΡΠΊΠ° Π² Π½Π΅ΡΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ 2,87 ΠΈ 2,71 ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ (p<0,001). ΠΠ΄Π½Π°ΠΊΠΎ Π² ΡΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π°ΡΡΠΎΡΠΈΠ°ΡΠΈΡ IL-6 Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ° Ρ Π³Π»Π°ΡΠΊΠΎΠΌΠΎΠΉ ΠΏΠΎΠ²ΡΡΠΈΠ»Π°ΡΡ Π΄ΠΎ 2,92 (ΠΠ 2,80-3,27, Ρ=0,004), Π° IL-17 ΡΠΌΠ΅Π½ΡΡΠΈΠ»ΠΎΡΡ Π΄ΠΎ 2,64 (ΠΠ 2,51-2,85, Ρ=0,003). Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½Π° ΡΠ°ΠΊΠΆΠ΅ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½Π°Ρ Π°ΡΡΠΎΡΠΈΠ°ΡΠΈΡ IL-4, IL-5, IL-12, IFN-Ξ³ ΠΈ TNF-Ξ± Ρ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ° Ρ Π³Π»Π°ΡΠΊΠΎΠΌΠΎΠΉ. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΎΠ΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°Π»ΠΎ Π½ΠΎΠ²ΡΠ΅ Π°ΡΡΠΎΡΠΈΠ°ΡΠΈΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΡΡ
ΡΠΈΡΠΎΠΊΠΈΠ½ΠΎΠ² Ρ ΡΠΈΡΠΊΠΎΠΌ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΎΡΠ΅ΡΠ°Π½Π½ΠΎΠΉ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ° Ρ Π³Π»Π°ΡΠΊΠΎΠΌΠΎΠΉ
A mathematical model for positive permafrost carbon-climate feedback
The permafrost methane emission problem is the focus of attention on different climate models. Here,
we present a mathematical model for permafrost lake methane emission and its influence on the climate
system. We model this process using the theory of non-linear phase transitions. Further, we find that a
climate catastrophe possibility depends on a value of feedback connecting the methane concentration in
the atmosphere and temperature, and on the tundra permafrost methane pool.We note that the permafrost
lake model that we developed for the methane emission positive feedback loop problem is a conceptual
climate model
Time Series Analysis of Atmospheric Precipitation Characteristics in Western Siberia for 1979–2018 across Different Datasets
A comparative statistical analysis of the spatiotemporal variability of atmospheric precipitation characteristics (mean and extreme values) in Western Siberia was performed based on data acquired from meteorological stations, global precipitation datasets such as the project of Asian Precipitation—Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) and from Global Precipitation Climatology Centre (GPCC), and reanalysis archives, including from National Centers of Environmental Prediction (NCEP-DOE) and the European Center for Medium Range Weather Forecasts (ERA5) for the period 1979–2018. The best agreement of the values from the observational data was observed with the values from GPCC. This archive also represented the periodicities in the time series of observational data from meteorological stations, especially in the short-period part of the spectrum. Underestimated values were revealed for the APHRODITE archive, while overestimated ones were found for the NCEP reanalysis data. In comparison with GPCC, the ERA5 dataset reproduced the general variability but with a smaller amplitude (the correlation coefficient was up to 0.9). In general, the median estimates of the precipitation amount derived from the meteorological stations’ data, as well from the reanalysis data, were in better agreement with each other rather than their extreme values. However, their temporal variability can be effectively described by other datasets