# User:Eugene M. Izhikevich/Proposed/Chronomics

Chronomics (from Gk chronos, time, and Gk nomos, rule), a computer-aided discipline, aligns and investigates the structures in time (chronomes) around us and in us, Figure 1. Cyclic and other components -- trends and chaos, Figure 1 -- in aligned time series describing organismic and environmental variables, are investigated, first each in its own right and next to uncover any (usually time-varying) associations (interactions) among the records. By detecting the signature in biology of both photic and more wobbly non-photic environmental cycles, Figure 1, chronomics led to the finding of intra , inter- and transdisciplinary congruence among the periods, τs, of spectral structures in and around us, where congruence is defined as overlying or overlapping CIs (95% confidence intervals) of the τs involved, defined in the abstract Figure 2 and illustrated by about 7-day (circaseptan), Figure 3; about 30-day (circatrigintan), Figure 4; near- and far-transannual, Figures 5 and 6 respectively; and decadal and didecadal τs, Figure 7, and transtridecadals, Figure 8. Acrophases, φ, Figure 9, and quindecadal and semimillennial regions of transdisciplinary spectra, Figures 10 and 11, follow. Fixing the time of day for long-term sampling is not necessarily helpful.

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Figure 2: Abstract definitions of congruence and similarity (top section) and example of actually congruent periods in the hormone/vitamin melatonin of circulating human blood (bottom section). Congruences and/or similarities can refer to the periods of various time series of the same variable, as inter-time series intra-variable phenomena. This case is shown in the bottom section for melatonin in six time series consisting of blood sampled at one or the other of six different clock-hours, covering the 24-h span at 4-h intervals and in time series of averages (MESORs) and circadian amplitudes derived from the individuals' data sets. There can also be inter-variable intradisciplinary congruence, such as that seen at several frequencies (not at all of them) between the solar wind's speed and geomagnetics, i.e., an inter-variable intradisciplinary physical (or biospheric among psychophysiological variables) congruence (not here illustrated). There was also transdisciplinary congruence in this study between the periods uncovered for different series of melatonin determinations on the one hand and the series consisting of the incidences of sudden cardiac death in various countries, Minnesota, Hungary and the Czech Republic, and furthermore in Tokyo and Austria. Congruences and similarities become most interesting when they are transdisciplinary, e.g., between the Schwabe, Hale or geomagnetic cycles on the one hand and biospheric variables on the other hand. The wobbly nature of some natural physical environmental and/or biospherical spectral components requires an inferential statistical approach in each case, e.g., according to Marquardt (20; cf. 19, 21). The congruence of anticipated components could be meaningfully assessed by a yet-to-be-developed test of H0: τ1 (e.g., melatonin MESOR τ) = τ2 (e.g., biological τ) [= ... = τk (e.g., sociological τ)], or the already available test at a fixed τ of H0: φ1 = φ2 [= ... = φk].© Halberg.
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Figure 3: Circaseptan synchronization of the acrophases of several urinary variables in a clinically healthy man, relatively closely synchronized as compared to a circadian chart (Figure 23 in Circadian Rhythms; Sothern et al. 1974). © Halberg.
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Figure 4: Start of a partial circasemiannual acrophase map. © Halberg.
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Figure 5: Near-transyears around (1–6) and in (7–10) organism(s)*. It is indispensable to specify the calendar span and thereby also the length of a time series upon which the resolution of a (set of) spectral component(s) (c) with period(s) (τ) rests. Thus, based on a series of ~4.5 years, one finds a component of systolic blood pressure (10a) with a τ of a year since its 95% confidence interval (CI) overlaps the exact 1-year period. In row 10b below, based on an about 6.5-year record, the resolution of a neartransyear (with a τ between 1.0 and 1.2 years and a CI overlapping neither of these lengths) becomes possible, perhaps as a function of age. In another case (RBS), examined over decades as a function of age (not shown), transyears become more prominent with age. A still longer record will have to confirm that during an even longer span at a still later age, as in FH, Fig. 3, there will be only transyears and no component with a CI of τ overlapping the calendar year length. As to mechanisms, it seems pertinent that the only endocrine record covering 15 years of observation of an adult's 17-ketosteroid excretion reveals globally no yearly component, only a near- and two fartransyears, the latter not shown. The finding of mutually reinforcing physical and biological near-transyears, defined by 1.00 year (y) < τ < 1.20 y, is the message of this graph, drawn with a curtain of uncertainty indicating the uncertainties of aeolians. These near-transyears in us, acquired by evolution, reinforce the reality of those around us from which they likely derive. We all stacked data in the past over a year and other τs such as a day; yet whenever possible, we should get an estimate of the period involved before stacking! This was a sine qua non well over 50 years ago for circadians and has become one for circannuals and in particular for aeolians, such as the near-transyear, here depicted as calendar-time-location- and series-length-dependent neartransyears. *As separate components and probably not as sidelobes of circannual variation (not stemming from amplitude and/or phase modulation by components with a lower frequency). Circles = period lengths (point estimations); horizontal lines crossing circles = 95% confidence intervals (Cls) of spectral components (when the zero-amplitude assumption was rejected nonlinearly. From www noaa.gov 1: Stanford data from May 1975 – Apr 2002 (27 y) /Diamond: longer record of 37 y with added Stanford data (up to 2004) and including other data from Crimea starting in 1968; when data were available from both sites, Stanford and Crimea, they were avaraged; total record length from 1968 to 2004; 6: 131 y (1868 – 1998), From OMNI2 (1963 – 2003) (ftp://nssdcftp.gsfc.nasa.gov/spacecraft _data/omni) 2–4: SW = Solar wind. Sigma = Standard deviation, 5: Bz = North – South component of Interplanetary Magnetic Field (IMF), From BIOCOS 7: Oxygen production (1980–1994), 8: Quarterly incidence, 10.5 y (1994–2004), 9: Daily excretion for 15 y of urinary steroidal metabolites (17 – ketosteroids, CH, Oct 1948 – Oct 1963), 10: Half-hourly records from a man (GSK). 70 y old at start of measurements from Mar 1998 to Feb 2003 (a): to Dec 2004 (b), and to Apr 2005 (c). An initially lacking near-transyear appears with lengthening of series and/or age. © Halberg.
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Figure 6: (a) Acrophase chart of presumably 1.0-year synchronized component of solar wind speed and human physiology. Relative clustering of 1.0-year acrophases of blood pressure and heart rate monitored longitudinally for 5 to 35 years by 4 subjects and of the velocity of the solar wind recorded by the IMP8 and Wind satellites. (b) Acrophase chart of ~1.3-year Richardson component on solar wind speed and human physiology. Relative clustering of acrophases of the about 1.3-year component of blood pressure and heart rate monitored longitudinally for 6 to 35 years by 4 subjects and of the velocity of the solar wind recorded by the IMP8 and Wind satellites. Acrophases computed at the average period of 1.301 year. © Halberg.
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Figure 7: Signatures in the biosphere of Schwabe’s ∼10.5-year and Hale’s ∼21-year non-photic solar activity cycles.© Halberg.
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Figure 8: Inter-individual transtridecadal congruence of different variables in the circulation of blood in the men. © Halberg.
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Figure 9: A gliding spectral window of a series of sunspots, extrapolated by Strestik and Mikulecky to cover half a millennium involved intervals of 42 years displaced in increments of 3 years through the time series. In the range of trial periods from one cycle in 42 years to one cycle in 7 years, computed in each interval, a plot of amplitudes shows, as expected, a (dark) band (larger amplitudes) at frequencies around one cycle in 11 years, except during the Maunder minimum, when the amplitude drops to much smaller values. © Halberg.
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Figure 10: {500-yr map} {?} m © Halberg.
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Figure 12: Between the years 1001 and 1500 a Brückner-Egeson-Lockyer cycle, briefly BEL, was clearly demonstrated in yearly data on northern lights (reproduced from a catalogue by Krivsky and Pejml, 1988). © Halberg.
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Figure 13: Population chronomics with focus upon a cis-half-year, i.e., ~5-month (~0.42-year) cycles in the incidence pattern of solar flares (2nd and bottom rows) and of sudden human cardiac deaths on different continents (rows 5-7). The incidence of solar flares over ~40 years (top row) and of an ~0.42-year component (second row) and of two para-annuals (third and fourth rows) differed in patterns of intermittent significance (5). Note further the different behavior in different geographic regions of putative signatures of the 0.42-year component in sudden human cardiac death (rows 5-7 and footnotes). © Halberg.
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Figure 15: Odds ratios of associations between certain human mental functions and solar and terrestrial activity.© Halberg.
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Figure 16: Time courses of the frequency structures of the speed of the solar wind (SWS) (top) and of an elderly man's (FH) systolic and diastolic blood pressure and heart rate, SBP, DBP and HR (rows 2-4, respectively), examined by gliding spectral windows. Human systolic (S) blood pressure (BP) selectively resonates with solar wind speed (SWS) (top 2 sections). No obvious resonance, only minor coincidence with diastolic BP (DBP) or heart rate (HR) (bottom 2 sections). Aeolian Rhythms* in gliding spectra of SWS and SBP change in frequency (smoothly [A] or abruptly [B,C,D], bifurcating [D,F] and rejoining [G], they also change in amplitude (B) (up to disappearing [C,E] and reappearing). During a nearly 16- year span there are no consistent components with a period averaging precisely 1 year in the 3 physiologic variables, probably an effect of advancing age. While post hoc ergo propter hoc reasoning can never be ruled out, an abrupt change on top in SWS is followed in the second row in SBP by the disappearance of some components, suggesting that as a first demonstration, some of FH's cis- and transyear components were driven by the SW [since they disappeared with a lag of about a transyear following the disappearance (subtraction) of the same components from the SWS spectrum]. The persistence of other spectral features in turn suggests endogenicity, i.e., an evolutionary acquisition of solar transyear oscillations that may reflect solar dynamics for the past billions of years. Blood pressure and heart rate data are from a man 70 years of age at start of around-the-clock monitoring, mostly at 30-min intervals, with interruptions for nearly 16 years. *FH, man, 70 years (y) of age at start of automatic half-hourly around the clock measurements for ~ 16 y (N=2418 daily averages, total ~ 55000). Gliding spectra computed with interval = 8 y, resolution low in time but high in frequency, increment = 1 month, trial periods from 2.5 to 0.4 y, with harmonic increment = 0.05. Darker shading corresponds to larger amplitude. When several of these broad bands disappear in the SWS, at E, parts of the bands in SBP also disappear, with a lag (delay) at E’, while other parts persist. These components are presumably built into organisms over billions of years, as persistence without corresponding components in SWS shows, but can be driven in part by the solar wind, as their disappearence after loss of corresponding components in SWS suggests. "Aeolian", derived from Aeolus, Greek God of winds, who packed the winds up and then let them loose and had them change. © Halberg.
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Figure 17: An ~7-day spectral component in the HR of five men is less prominent when the solar wind loses its counterpart of corresponding length. Implied, but not shown, is the persistence in the biosphere of an ~7-day component that can be amplified (driven) by a reciprocal component in solar activity. © Halberg.
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Figure 18: The Phoenix Group of volunteering electrical and electronic engineers from the Twin Cities chapter of the Institute of Electrical and Electronics Engineers (http://www.phoenix.tcieee. org) is planning on developing an inexpensive, cuffless automatic monitor of blood pressure and on implementing the concept of a website (www.sphygmochron.org) for collection and analysis of data collected with these instruments. © Halberg.