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Journal articles on the topic 'Term variability'

Author: Grafiati

Published: 4 June 2025

Last updated: 23 June 2025

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1

Pagano, Isabella. "Long-term stellar variability." Proceedings of the International Astronomical Union 5, S264 (2009): 136–45. http://dx.doi.org/10.1017/s1743921309992547.

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AbstractStars with significant subsurface convection zones develop magnetic loop structures that, arising from the surface upward to the external atmospheres, cause flux variability detectable throughout the whole electromagnetic spectrum. In fact, diagnostics of magnetic activity are in radio wavelengths, where gyrosincrotron radiation arises from the quiescent and flaring corona; in the optical region, where important signatures are the Balmer lines, the Ca ii IRT and H&K lines; in the UV and X ray domains, the latter mainly due to coronal thermal plasma. The zoo of different magnetic features observed for the Sun – spots, faculae, flares, CMEs – are characterized by different temporal evolution and energetics, both in quantity and quality. As a consequence, the time scale of variability, the amount of involved energy and the quality of the involved photons are used as fingerprints in interpreting the observed stellar variability in the framework of the solar-stellar analogy. Here I review main results from long-term multiwavelength observations of cool star atmospheres, with emphasis to similarities and differences with the solar case.

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Borbotko, Liudmila, and Ekaterina Vishnevskaya. "Terminological Variability in the Category of Educational Publications." ARPHA Proceedings 4 (May 31, 2021): 154–68. https://doi.org/10.3897/ap.e4.e0154.

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Nowadays is witnessing new challenges related to the current state of the digital era. The phenomenon of digital consciousness that is the result of digitalization calls for the new objectives and instruments in all spheres of human activity. The latter especially concerns education. Nevertheless, new technological perspectives rely on the expertise that comes in the form of verified and approved teaching and learning tools that are books coming in a variety of types. Variability in terms of naming those manuals is linguistically due to the common processes in terminology as well as methodologically explained by the differences in the set of objectives and goals to hit with the help of this or that manual. Moreover, the diversity of manual types which implies variability of terms used to name them is regulated by such principal factors as official recognition and compliance with the curriculum. Still, various manuals that are characterized by different titles, functional and teaching potential have a structure that is strictly determined and obligatory.

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3

Lewis, Kerry E., Thomas Watterson, and Ann Blanton. "Comparison of Short-Term and Long-Term Variability in Nasalance Scores." Cleft Palate-Craniofacial Journal 45, no. 5 (2008): 495–500. http://dx.doi.org/10.1597/07-150.1.

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Objective: To evaluate long-term nasalance score variability while accounting for short-term variation associated with subject performance and headgear change variability. Stimuli: Turtle and Mouse Passages. Design: Short-term immediate test-retest nasalance score variability was assessed with no headgear change (NCHG) and with change of headgear (CHG). Long-term variability was assessed with scores obtained in the morning and afternoon of the same day, 1 day apart, and 1 week apart. Scores from the long-term conditions necessarily reflect variability associated with headgear change plus variability, which may be attributed to time. Participants: Twenty-six adults (19 to 70 years of age) with normal speech and resonance. Main Outcome Measures: Forty-six nasalance scores per subject. Results: Mean nasalance difference scores across conditions were compared. Three contrasts were significantly different, each involving comparison of nasalance difference scores in the NCHG condition to difference scores from a CHG condition. Overall, long-term variability was slightly greater than short-term variability. For the Turtle Passage, in the short-term CHG condition, 92% of repeated scores were within five points. In the long-term conditions, 83% to 89% of scores were within five points. For the Mouse Passage, 88% of repeated scores in the CHG condition were within five points. In the long-term conditions, 81% to 83% of scores were within five points. Conclusions: Nasalance scores obtained over time showed slightly greater variability than scores obtained in immediate test-retest conditions; however, variability did not increase as the length of time between measures increased.

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Pielke, Roger A., and Xubin Zeng. "Long-Term Variability of Climate." Journal of the Atmospheric Sciences 51, no. 1 (1994): 155–59. http://dx.doi.org/10.1175/1520-0469(1994)051<0155:ltvoc>2.0.co;2.

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Damineli, Augusto, Mairan Teodoro, Michael F. Corcoran та Jose H. Groh. "η Carinae long-term variability". Proceedings of the International Astronomical Union 6, S272 (2010): 604–5. http://dx.doi.org/10.1017/s1743921311011513.

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AbstractWe present preliminary results of our analysis on the long-term variations observed in the optical spectrum of the LBV star η Carinae. Based on the hydrogen line profiles, we conclude that the physical parameters of the primary star did not change in the last 15 years.

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6

Palatini, Paolo. "Short-term blood pressure variability." Journal of Hypertension 36, no. 9 (2018): 1795–97. http://dx.doi.org/10.1097/hjh.0000000000001799.

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7

Bischoff, K., W. Kollatschny, and M. Dietrich. "Long-Term Variability of AGN." International Astronomical Union Colloquium 159 (1997): 171–72. http://dx.doi.org/10.1017/s0252921100039920.

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8

Pap, Judit M. "Long-term solar irradiance variability." Symposium - International Astronomical Union 181 (1997): 235–50. http://dx.doi.org/10.1017/s0074180900061180.

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Measurements of the solar energy throughout the solar spectrum and understanding its variability provide important information about the physical processes and structural changes in the solar interior and in the solar atmosphere. Solar irradiance measurements (both bolometric and at various wavelengths) over the last two decades have demonstrated that the solar radiative output changes with time as an effect of the waxing and waning solar activity. Although the overall pattern of the long-term variations is similar in the entire spectrum and at various wavelengths, being higher during high solar activity conditions, remarkable differences exist between the magnitude and shape of the observed changes. These differences arise from the different physical conditions in the solar atmosphere where the irradiances are emitted. The aim of this paper is to discuss the solar-cycle-related long-term changes in solar total and UV irradiances. The space-borne irradiance observations are compared to ground-based indices of solar magnetic activity, such as the Photometric Sunspot Index, full disk magnetic flux, and the Mt. Wilson Magnetic Plage Strength Index. Considerable part of the research described in this paper was stimulated by the discussions with the late Philippe Delache, who will always remain in the heart and memory of the author of this paper.

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9

Grandi, P., L. Maraschi, C. M. Urry, et al. "Long term variability of 3C279." Advances in Space Research 15, no. 5 (1995): 23–26. http://dx.doi.org/10.1016/0273-1177(94)00029-z.

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10

Abbott, Rosalyn D., Francis E. Borowsky, Carlo A. Alonzo, Adam Zieba, Irene Georgakoudi, and David L. Kaplan. "Variability in responses observed in human white adipose tissue models." Journal of Tissue Engineering and Regenerative Medicine 12, no. 3 (2017): 840–47. http://dx.doi.org/10.1002/term.2572.

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11

Steele, Bernard W., Edward Wang, Glenn Palomaki, George G. Klee, Ronald J. Elin, and David L. Witte. "Sources of Variability." Archives of Pathology & Laboratory Medicine 125, no. 2 (2001): 183–90. http://dx.doi.org/10.5858/2001-125-0183-sov.

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Abstract Objective.—To determine the magnitudes and sources of analytic variation in testing for therapeutic drugs. Specifically, among laboratories using the same analytic method, to compare the within-laboratory variation (including both short- and long-term variation) with the between-laboratory variation. Design.—Four identical challenges were prepared from a lyophilized pool of spiked sera and were sent in pairs 4 months apart to laboratories participating in a nationwide proficiency-testing program. For each of 25 drugs, the variability in reported results from laboratories using the same method was investigated using nested analysis of variance. Setting.—The first 2 mailings of the College of American Pathologists Therapeutic Drug Monitoring Survey, 1996, sets Z and ZM. Main Outcome Measures.—For each drug, total variance was partitioned into within- and between-laboratory components for common methods. The within-laboratory component was further partitioned into short- and long-term components. Participants.—The approximately 5000 laboratories enrolled in the survey. Results.—For the 25 drugs, the average percentages of the total variance due to short-term, within-laboratory variance; long-term, within-laboratory variance; between-laboratory variance; and total laboratory variance were 25.0% (range, 8.8–50.6%), 57.8% (35.3–73.7%), 17.3% (5.0–35.4%), and 82.7% (64.6–95.0%), respectively. Conclusion.—For all drugs tested, the within-laboratory component of variance was greater than the between-laboratory component of variance. Within laboratories, the magnitude of the long-term component was generally greater than the magnitude of the short-term component. This information will be helpful in determining the clinical utility of various drug assays and in evaluating the appropriateness of regulations involving therapeutic drug testing.

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Wium, Daniel J. W., and Oral Buyukozturk. "Variability in Long‐Term Concrete Deformations." Journal of Structural Engineering 111, no. 8 (1985): 1792–809. http://dx.doi.org/10.1061/(asce)0733-9445(1985)111:8(1792).

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13

Morris, M. R., S. D. Hornstein, A. M. Ghez, J. R. Lu, K. Matthews, and F. K. Baganoff. "Short-term variability of Sgr A*." Proceedings of the International Astronomical Union 2, S238 (2006): 195–200. http://dx.doi.org/10.1017/s1743921307004966.

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AbstractObservations of Sgr A* over the past 4 years with the Keck Telescope in the near-infrared, coupled with millimeter and submillimeter observations, show that the 3.7×106M⊙Galactic Black Hole, Sagittarius A*, displays continuous variability at all these wavelengths, with the variability power concentrated on characteristic time scales of a few hours, and with a variability fraction that increases with wavelength. We review the observations indicating that the few-hour time scale for variability is reproduced at all accessible wavelengths. Interpreted as a dynamical time, this time scale corresponds to a radial distance of 2 AU, or ∼25 Schwarzschild radii. Searches for quasi-periodicities in the near-infrared data from the Keck Telescope have so far been negative. One interpretation of the character of these variations is that they result from a recurring disk instability, rather than from variations in the mass accretion rate flowing through the outer boundary of the emission region. However, neither a variable accretion rate nor a mechanism associated with a jet can presently be ruled out.

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14

Nesselroade, John R. "Intraindividual Variability and Short-Term Change." Gerontology 50, no. 1 (2003): 44–47. http://dx.doi.org/10.1159/000074389.

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Griffin, E., and L. Balona. "Accessing Data for Long-Term Variability." Proceedings of the International Astronomical Union 14, S339 (2017): 269–73. http://dx.doi.org/10.1017/s1743921318002739.

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AbstractAstronomy’s heritage, comprised mainly of several million photographic plates (both images and spectra), extends backwards in time for many decades. It constitutes a unique and irreplaceable resource for research into long-term variations. Unfortunately, to date rather few of the plates can be accessed in digital formats and cannot therefore be used in modern research. That lack of use encourages the attitude that ‘old’ data have no value and might as well be destroyed. This Workshop discussed ways and means to avert such threats, and prioritised a list of actions that need to be taken as soon as possible.

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Tomson, Teolan, and Gunnar Tamm. "Short-term variability of solar radiation." Solar Energy 80, no. 5 (2006): 600–606. http://dx.doi.org/10.1016/j.solener.2005.03.009.

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Paul, A. K. "Short term variability of the ionosphere." Advances in Space Research 15, no. 2 (1995): 25–33. http://dx.doi.org/10.1016/s0273-1177(99)80020-9.

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Bjorkman, K. S., A. S. Miroshnichenko, D. A. McDavid та T. M. Pogrosheva. "Long–term Variability of π Aqr". International Astronomical Union Colloquium 175 (2000): 535–38. http://dx.doi.org/10.1017/s025292110005644x.

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AbstractWe present our recent photometric and spectroscopic observations of the bright classical Be star π Aquarii and analyse those available in literature. This star currently shows only weak signs of circumstellar emission and a low optical brightness. Physical parameters of the underlying star are determined from data obtained during quiescence, while those of its circumstellar disk are estimated during the active period.

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19

Yang, Jiang-he, Jun-hui Fan, Yi Liu, Yong-xiang Wang, and Ru-shu Yang. "Long-term Variability Properties of Mkn501." Chinese Astronomy and Astrophysics 32, no. 2 (2008): 129–39. http://dx.doi.org/10.1016/j.chinastron.2008.04.011.

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20

Hensberge, Herman. "Long Term Variability in CP Stars." International Astronomical Union Colloquium 138 (1993): 547–60. http://dx.doi.org/10.1017/s0252921100021023.

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AbstractA search for CP2 stars with long photometric periods during more than one decade has led to the detection of the long period variables HD 94660 and HD 116458. Furthermore, in the case of ϒ Equ, the CP star with the longest magnetic period, a monotonic change of the light output has been measured. Light curves are presented for the known long period variables HD 187474 and HD 188041. The results on the other stars in the programme are shortly discussed.

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21

Etoka, S., and A. M. Le Squeren. "Long-term OH variability of Miras." Astronomy and Astrophysics Supplement Series 146, no. 2 (2000): 179–215. http://dx.doi.org/10.1051/aas:2000268.

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22

Lee, Raymond L., and Javier Hernández-Andrés. "Short-term variability of overcast brightness." Applied Optics 44, no. 27 (2005): 5704. http://dx.doi.org/10.1364/ao.44.005704.

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Kontor, N. N. "Long term variability of solar activity." Advances in Space Research 13, no. 9 (1993): 417–27. http://dx.doi.org/10.1016/0273-1177(93)90514-c.

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24

Butkovskaya, V., S. Plachinda, G. Valyavin, D. Baklanova, and B. C. Lee. "The long-term variability of Vega." Astronomische Nachrichten 332, no. 9-10 (2011): 956–60. http://dx.doi.org/10.1002/asna.201111587.

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25

Kuehni, Rolf. "Focal Color Variability and Unique Hue Stimulus Variability." Journal of Cognition and Culture 5, no. 3-4 (2005): 409–26. http://dx.doi.org/10.1163/156853705774648554.

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AbstractThe degree to which physiology and culture have affected the formation of primitive color categories continues to be a matter of discussion. In this paper the degree of agreement between the ranges of individual color term foci for the four hue-based color categories yellow, green, blue, and red and individual choices of Munsell samples representing for the observers Hering's four unique hues is investigated. The color term focus range data are extracted from the survey results of the 110 unwritten languages of the World Color Survey, also in terms of the Munsell color order system. Agreement of approximately 90% between the two has been found, indicating the likelihood of a strong color vision system related physiological component in the formation of these four primitive hue categories.

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Garg, Uttam C., Zhi-Jie Zheng, Aaron R. Folsom, et al. "Short-term and long-term variability of plasma homocysteine measurement." Clinical Chemistry 43, no. 1 (1997): 141–45. http://dx.doi.org/10.1093/clinchem/43.1.141.

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Abstract Within-person and methodological variability of a given analyte are important elements in determining whether an individual has altered concentrations of that analyte. We report the short-term (1 month) within-person, between-person, and methodological variability of plasma homocysteine in 20 healthy participants from whom samples were drawn weekly for 4 weeks. The short-term between-person variance was high, whereas within-person and methodological variances were relatively very low, giving a high reliability coefficient (R) for homocysteine (R = 0.94). The long-term (30 months) reliability coefficient was 0.65, but was greatly influenced by an outlier (R = 0.82 with the outlier excluded). The data suggest that an individual’s plasma homocysteine concentration is relatively constant over at least 1 month, and a single measurement characterizes the average concentration reasonably well.

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Bao, Nisha, Alex Lechner, Andrew Fletcher, Peter Erskine, David Mulligan, and Zhongke Bai. "SPOTing long-term changes in vegetation over short-term variability." International Journal of Mining, Reclamation and Environment 28, no. 1 (2012): 2–24. http://dx.doi.org/10.1080/17480930.2012.710505.

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Janssen, Ben J. A., Peter J. A. Leenders, and Jos F. M. Smits. "Short-term and long-term blood pressure and heart rate variability in the mouse." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 278, no. 1 (2000): R215—R225. http://dx.doi.org/10.1152/ajpregu.2000.278.1.r215.

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Knowledge on murine blood pressure and heart rate control mechanisms is limited. With the use of a tethering system, mean arterial pressure (MAP) and pulse interval (PI) were continuously recorded for periods up to 3 wk in Swiss mice. The day-to-day variation of MAP and PI was stable from 5 days after surgery. Within each mouse ( n = 9), MAP and PI varied by 21 ± 6 mmHg and 17 ± 4 ms around their respective 24-h averages (97 ± 3 mmHg and 89 ± 3 ms). Over 24-h periods, MAP and PI were bimodally distributed and clustered around two preferential states. Short-term variability of MAP and PI was compared between the resting (control) and active states using spectral analysis. In resting conditions, variability of MAP was mainly confined to frequencies <1 Hz, whereas variability of PI was predominantly linked to the respiration cycle (3–6 Hz). In the active state, MAP power increased in the 0.08- to 3-Hz range, whereas PI power fell in the 0.08- to 0.4-Hz range. In both conditions, coherence between MAP and PI was high at 0.4 Hz with MAP leading the PI fluctuations by 0.3–0.4 s, suggesting that reflex coupling between MAP and PI occurred at the same frequency range as in rats. Short-term variability of MAP and PI was studied after intravenous injection of autonomic blockers. Compared with the resting control state, MAP fell and PI increased after ganglionic blockade with hexamethonium. Comparable responses of MAP were obtained with the α-blocker prazosin, whereas the β-blocker metoprolol increased PI similarly. Muscarinic blockade with atropine did not significantly alter steady-state levels of MAP and PI. Both hexamethonium and prazosin decreased MAP variability in the 0.08- to 1-Hz range. In contrast, after hexamethonium and metoprolol, PI variability increased in the 0.4- to 3-Hz range. Atropine had no effect on MAP fluctuations but decreased those of PI in the 0.08- to 1-Hz range. These data indicate that, in mice, blood pressure and its variability are predominantly under sympathetic control, whereas both vagal and sympathetic nerves control PI variability. Blockade of endogenous nitric oxide formation by N G-nitro-l-arginine methyl ester increased MAP variability specifically in the 0.08- to 0.4-Hz range, suggesting a role of nitric oxide in buffering blood pressure fluctuations.

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Czeglédi, I., and Tibor Ers. "Characterizing the long-term taxonomic and functional variability of a stream fish assemblage." Fundamental and Applied Limnology 183, no. 2 (2013): 153–62. http://dx.doi.org/10.1127/1863-9135/2013/0495.

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Zherebtsov, Geliy, Konstantin Ratovsky, and Irina Medvedeva. "Long-term variations in peak electron density and temperature of mesopause region: Dependence on solar, geomagnetic, and atmospheric activities, long-term trends." Solar-Terrestrial Physics 10, no. 4 (2024): 3–13. https://doi.org/10.12737/stp-104202401.

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The paper overviews the main results of the study of long-term variations in characteristics of the upper neutral atmosphere and ionosphere, obtained during the implementation of Russian Science Foundation Project No. 22-17-00146 “Experimental and theoretical study of the coupling neutral and ionized components of Earth’s atmosphere”. We study and compare long-term variations in the peak electron density and temperature of the mesopause region. Their dependences on solar, geomagnetic, and atmospheric activity, as well as long-term trends, are analyzed. The analysis is based on data from long-term measurements with the ISTP SB RAS complex of instruments. The peak electron density (NmF2) data was acquired with the Irkutsk analog automatic ionospheric station for 1955–1996 and the Irkutsk digital ionosonde DPS-4 for 2003–2021. The atmospheric temperatures at mesopause altitudes (Tm) were obtained from spectrometric observations of the hydroxyl molecule emission (OH (6-2) band, 834.0 nm, emission maximum height ~87 km) for 2008–2020. The analysis uses solar (F10.7) and geomagnetic (Ap) activity indices, as well as data on variations in the Southern Oscillation Index (SOI). The study employs simple and multiple linear regression methods. Annual average NmF2 values are found to be predominantly controlled by changes in solar flux. Analysis of regression residuals shows that the largest deviations from regression (for both simple and multiple regression) are observed in years near the maxima of solar cycles 19 (1956–1959) and 22 (1989–1991). Annual average temperature variability in the mesopause region correlates with changes in the SOI index: day-to-day variability exhibits a positive correlation with SOI; and intra-diurnal variability, a negative correlation with SOI. No significant relationship was found between year-to-year variations in the NmF2 and Tm variability.

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Mallamaci, Francesca, Giovanni Tripepi, Graziella D’Arrigo, et al. "Blood Pressure Variability, Mortality, and Cardiovascular Outcomes in CKD Patients." Clinical Journal of the American Society of Nephrology 14, no. 2 (2019): 233–40. http://dx.doi.org/10.2215/cjn.04030318.

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Background and objectivesShort-term BP variability (derived from 24-hour ambulatory BP monitoring) and long-term BP variability (from clinic visit to clinic visit) are directly related to risk for cardiovascular events, but these relationships have been scarcely investigated in patients with CKD, and their prognostic value in this population is unknown.Design, setting, participants, & measurementsIn a cohort of 402 patients with CKD, we assessed associations of short- and long-term systolic BP variability with a composite end point of death or cardiovascular event. Variability was defined as the standard deviation of observed BP measurements. We further tested the prognostic value of these parameters for risk discrimination and reclassification.ResultsMean ± SD short-term systolic BP variability was 12.6±3.3 mm Hg, and mean ± SD long-term systolic BP variability was 12.7±5.1 mm Hg. For short-term BP variability, 125 participants experienced the composite end point over a median follow-up of 4.8 years (interquartile range, 2.3–8.6 years). For long-term BP variability, 110 participants experienced the composite end point over a median follow-up of 3.2 years (interquartile range, 1.0–7.5 years). In adjusted analyses, long-term BP variability was significantly associated with the composite end point (hazard ratio, 1.24; 95% confidence interval, 1.01 to 1.51 per 5-mm Hg higher SD of office systolic BP), but short-term systolic BP variability was not (hazard ratio, 0.92; 95% confidence interval, 0.68 to 1.25 per 5-mm Hg higher SD of 24-hour ambulatory systolic BP). Neither estimate of BP variability improved risk discrimination or reclassification compared with a simple risk prediction model.ConclusionsIn patients with CKD, long-term but not short-term systolic BP variability is related to the risk of death and cardiovascular events. However, BP variability has a limited role for prediction in CKD.

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Hawkins, M. R. S. "Quasar Variability From Microlensing." Symposium - International Astronomical Union 173 (1996): 291–92. http://dx.doi.org/10.1017/s0074180900231604.

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Quasars are known to vary in brightness over a wide range of time scales. Short term intrinsic variability has been well documented, and a strong case can be made that long term variation is due to microlensing. In this paper the effect of time dilation as a means for distinguishing between intrinsic variation and gravitational lensing is discussed.

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Gleissner, T., J. Wilms, G. G. Pooley, et al. "Long term variability of Cygnus X-1." Astronomy & Astrophysics 425, no. 3 (2004): 1061–68. http://dx.doi.org/10.1051/0004-6361:20040280.

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Grinberg, V., N. Hell, K. Pottschmidt, et al. "Long term variability of Cygnus X-1." Astronomy & Astrophysics 554 (June 2013): A88. http://dx.doi.org/10.1051/0004-6361/201321128.

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Grinberg, V., K. Pottschmidt, M. Böck, et al. "Long term variability of Cygnus X-1." Astronomy & Astrophysics 565 (April 18, 2014): A1. http://dx.doi.org/10.1051/0004-6361/201322969.

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Palate, M., and G. Rauw. "Short-term spectroscopic variability of Plaskett’s star." Astronomy & Astrophysics 572 (November 19, 2014): A16. http://dx.doi.org/10.1051/0004-6361/201423608.

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37

Walsh, John E., and William L. Chapman. "Short-Term Climatic Variability of the Arctic." Journal of Climate 3, no. 2 (1990): 237–50. http://dx.doi.org/10.1175/1520-0442(1990)003<0237:stcvot>2.0.co;2.

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38

Weis, Edward W. "Long term variability in dwarf M stars." Astronomical Journal 107 (March 1994): 1135. http://dx.doi.org/10.1086/116925.

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Wilms, J., M. A. Nowak, K. Pottschmidt, G. G. Pooley, and S. Fritz. "Long term variability of Cygnus X-1." Astronomy & Astrophysics 447, no. 1 (2006): 245–61. http://dx.doi.org/10.1051/0004-6361:20053938.

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Lohmann, Gerald M., Adam H. Monahan, and Detlev Heinemann. "Local short-term variability in solar irradiance." Atmospheric Chemistry and Physics 16, no. 10 (2016): 6365–79. http://dx.doi.org/10.5194/acp-16-6365-2016.

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Abstract. Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1 Hz data recorded by as many as 99 pyranometers during the HD(CP)2 Observational Prototype Experiment (HOPE), we analyze field variability of clear-sky index k* (i.e., irradiance normalized to clear-sky conditions) and sub-minute k* increments (i.e., changes over specified intervals of time) for distances between tens of meters and about 10 km. By means of a simple classification scheme based on k* statistics, we identify overcast, clear, and mixed sky conditions, and demonstrate that the last of these is the most potentially problematic in terms of short-term PV power fluctuations. Under mixed conditions, the probability of relatively strong k* increments of ±0.5 is approximately twice as high compared to increment statistics computed without conditioning by sky type. Additionally, spatial autocorrelation structures of k* increment fields differ considerably between sky types. While the profiles for overcast and clear skies mostly resemble the predictions of a simple model published by Hoff and Perez (2012), this is not the case for mixed conditions. As a proxy for the smoothing effects of distributed PV, we finally show that spatial averaging mitigates variability in k* less effectively than variability in k* increments, for a spatial sensor density of 2 km−2.

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van den Meiracker, Anton H., Arie J. Man in ’t Veld, Henk J. Ritsema van Eck, Gert J. Wenting, and Maarten A. D. H. Schalekamp. "Determinants of Short-term Blood Pressure Variability." American Journal of Hypertension 1, no. 1 (1988): 22–26. http://dx.doi.org/10.1093/ajh/1.1.22.

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Rajput, Bhoomika, C. S. Stalin та Suvendu Rakshit. "Long term γ-ray variability of blazars". Astronomy & Astrophysics 634 (лютий 2020): A80. http://dx.doi.org/10.1051/0004-6361/201936769.

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We used the data from the Fermi Gamma-ray Space Telescope to characterise the γ-ray flux variability of blazars on month-like time scales. Our sample consists of 1120 blazars of which 481 are flat spectrum radio quasars (FSRQs) and 639 are BL Lac objects (BL Lacs). We generated monthly binned light curves of our sample for a period of approximately nine years from 2008 August to 2017 December and quantified variability by using excess variance (Fvar). On month-like time scales, 371/481 FSRQs are variable (80%), while only about 50% (304/639) of BL Lacs are variable. This suggests that FSRQs are more variable than BL Lac objects. We find a mean Fvar of 0.55 ± 0.33 and 0.47 ± 0.29 for FSRQs and BL Lacs respectively. Large Fvar in FSRQs is also confirmed from the analysis of the ensemble structure function. By Dividing our sample of blazars based on the position of the synchrotron peak in their broad-band spectral energy distribution, we find that the low synchrotron peaked (LSP) sources have the largest mean Fvar value of 0.54 ± 0.32 while the intermediate synchrotron peaked (ISP) and high synchrotron peaked sources have mean Fvar values of 0.45 ± 0.25 and 0.47 ± 0.33 respectively. On month-like time scales, we find FSRQs to show a high duty cycle (DC) of variability of 66% relative to BL Lacs that show a DC of 36%. We find that both the Fvar and time scale of variability (τ) do not correlate with MBH. We note that Fvar is found to be weakly correlated with Doppler factor (δ) and τ is also weakly correlated with δ. Most of the sources in our sample have τ of the order of days, which might be related to processes in the jet. We find marginal difference in the distribution of τ between FSRQs and BL Lacs.

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Kotze, M. M., and P. A. Charles. "Characterizing X-ray binary long-term variability." Monthly Notices of the Royal Astronomical Society 420, no. 2 (2011): 1575–89. http://dx.doi.org/10.1111/j.1365-2966.2011.20146.x.

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Grinberg, V., M. A. Leutenegger, N. Hell, et al. "Long term variability of Cygnus X-1." Astronomy & Astrophysics 576 (April 2015): A117. http://dx.doi.org/10.1051/0004-6361/201425418.

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G. M. Schmidt, A. G. Smajstrla, and F. S. Zazueta. "LONG-TERM VARIABILITY OF MONTHLY TOTAL PRECIPITATION." Transactions of the ASAE 40, no. 4 (1997): 1029–39. http://dx.doi.org/10.13031/2013.21355.

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NICOLIS, C. "Long-term climatic variability and chaotic dynamics." Tellus A 39A, no. 1 (1987): 1–9. http://dx.doi.org/10.1111/j.1600-0870.1987.tb00283.x.

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Telting, J. H. "Long-term Variability in Be-Star disks." International Astronomical Union Colloquium 175 (2000): 422–34. http://dx.doi.org/10.1017/s0252921100056219.

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AbstractBe stars can switch between non-disk, gradual disk growth, disk-loss events, and shell-line phases. Many aspects of this Be phenomenon are still not understood. In this paper I review recent work on variability in Be-star disks, divided in four different topics: disk growth (Section 1), long-term V/R variations and global disk oscillations (Section 2), spectacular variations (Section 3), and, concisely, the disk variability in Be/X-ray binaries (Section 4).

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Lee, Khee-Gan, Edo Berger та Gillian R. Knapp. "SHORT-TERM Hα VARIABILITY IN M DWARFS". Astrophysical Journal 708, № 2 (2009): 1482–91. http://dx.doi.org/10.1088/0004-637x/708/2/1482.

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Mancia, Giuseppe. "Short- and Long-Term Blood Pressure Variability." Hypertension 60, no. 2 (2012): 512–17. http://dx.doi.org/10.1161/hypertensionaha.112.194340.

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Oken, B. S., and K. H. Chiappa. "Short-term variability in EEG frequency analysis." Electroencephalography and Clinical Neurophysiology 69, no. 3 (1988): 191–98. http://dx.doi.org/10.1016/0013-4694(88)90128-9.

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