Level Of Solar Activity Research Articles

Cyclic myocardial infarctions follow solar variations: A pilot study in Mediterranean populations

To map time-structures is a burgeoning scientific field enriching the (P4) medicine models. Relevant local evidence in Mediterranean populations is poorly investigated. Myocardial infarctions (MI) incidence and fatality rate is high, whilst its statistics fail to cover full etiology risk factors. This pilot study extents our previous work on stroke mortality variations [1] to MIs and aims to evaluate historical data of MI mortality events a. from Aghios Pavlos General Hospital in Thessaloniki (1955–1962) b. in Tel-Aviv (1972–1988) – periods free of confounding factors like life-style, pollution, stress. Sunspot numbers (Rz) were derived from the archives of measurements published by Solar Geographical Data. 930 Death events of myocardial infarctions from the archives of Aghios Pavlos General Hospital archives were collected and been evaluated by Δstatistics, while, 5667 publicly available MI deaths from Tel-Aviv hospitals were evaluated by correlation coefficient (r). MI variations and solar activity levels. Common cyclic variations of 2 and 4 years of sunspot numbers (as established marker of solar activity) and MI incidence was observed. The Correlation coefficient of Rz and monthly MI for Thessaloniki was r a = 0.402 P < 0.001, whilst for Tel-Aviv it was calculated as high as r b = 0.44 P < 0.001. Time structure patterns may provide novel insight in MI epidemic and, thus, contribute to future sophisticated public health planning and chronotherapy evaluations.

Empirical relations between the intensities of Lyman lines of H and He+

Context.Empirical relations between major UV and extreme UV spectral lines are one of the inputs for models of chromospheric and coronal spectral radiances and irradiances. They are also needed for the interpretation of some of the observations of the Solar Orbiter mission.Aims.We aim to determine an empirical relation between the intensities of the H I121.6 nm and He II30.4 nm Ly-αlines.Methods.Images at 121.6 nm from the Chromospheric Lyman-Alpha Spectro Polarimeter (CLASP) and Multiple XUV Imager (MXUVI) sounding rockets were co-registered with simultaneous images at 30.4 nm from the EIT and AIA orbital telescopes in order to derive a spatially resolved relationship between the intensities.Results.We have obtained a relationship between the H I121.6 nm and He II30.4 nm intensities that is valid for a wide range of solar features, intensities, and activity levels. Additional SUMER data have allowed the derivation of another relation between the H I102.5 nm (Ly-β) and He II30.4 nm lines for quiet-Sun regions. We combined these two relationships to obtain a Ly-α/Ly-βintensity ratio that is comparable to the few previously published results.Conclusions.The relationship between the H I121.6 nm and He II30.4 nm lines is consistent with the one previously obtained using irradiance data. We have also observed that this relation is stable in time but that its accuracy depends on the spatial resolution of the observations. The derived Ly-α/Ly-βintensity ratio is also compatible with previous results.

Two Stage Prediction Model of Sunspots Monthly Value Based on CEEMDAN and Particle Swarm Optimization ELM

Sunspot number is the most basic parameter to describe the level of solar activity. The accurate prediction of sunspot number can reflect the electromagnetic disturbance level of the electromagnetic layer, ionosphere and the middle and high layers in the future in advance, so as to provide important reference information for navigation, positioning, communication and the prediction of orbital attenuation of LEO satellites. Aiming at the characteristics of sunspot time series such as non-stationary, chaotic and difficult to predict, this paper proposed a two-stage combined prediction model based on complete Ensemble Empirical mode decomposition with adaptive noise (CEEMDAN), particle swarm optimization (PSO) and extreme learning machine(ELM) network. In the first stage of prediction: firstly, the original sunspot monthly mean series is decomposed by CEEMDAN to reduce the non-linearity and non-stationary of the original series. Then, an ELM prediction model is established for the sub-sequences decomposed by CEEMDAN, and the input layer dimension, hidden layer dimension, input layer weight and hidden layer bias of ELM are optimized by PSO algorithm. Finally, the prediction results of the first stage are obtained by superimposing the prediction results of each sub-sequence. The second stage is the error self-correction stage. Firstly, the prediction error sequence of the first stage is obtained. Then, the CEEMDAN-PSO-ELM prediction model is used to self-correct the prediction error of the first stage. Finally, the prediction results of the first stage and the self-correction results of the second stage are superimposed to obtain the final prediction value of the monthly sunspot number.In this paper, CEEMDAN is used to reduce the non-linearity and non-stationary of the sunspot series, and PSO is used to determine the best parameters of ELM network, and the useful information in the prediction error is fully considered, which effectively improves the prediction accuracy of sunspot monthly mean series. The prediction experiment is carried out by using the measured sunspot monthly mean series, and the proposed model is compared with wavelet neural network (WNN), back propagation neural network (BPNN), ELM, CEEMDAN-ELM and CEEMDAN-PSO-ELM. The experimental results show that the prediction accuracy of the proposed two-stage prediction model has been significantly improved, and has better prediction stability.

The connection between the critical frequency and the total electron content of the ionosphere at low and high solar activity period

Ionosonde-f0F2 measurements and corresponding GNSS TEC measurements have been analysed. Available f0F2 and TEC data respectively obtained from a pair of ionosonde and GNSS receiver stations of a mid-latitude station, named MO155, located in Moscow (55.8˚N, 37.2˚E), for 2010 and 2014 was used. Data for two years were respectively used in the study to represent years of low and high solar activity. A significant relation between the ionosonde-f0F2 measurements and the corresponding GNSS-VTEC measurements with correlation coefficients above 0.8 was observed for both periods. The f0F2/TEC ratios, for the MO155 station illustrated, are typically in the range of about 0.2 to 1.6 Mhz/TECU during the low solar activity period and 0.2 to 2.5 Mhz/TECU during the high solar activity period. The ratio is lower during the day-time, and higher during the nights and early mornings. The analysis of the four seasons for both periods (low solar activity and high solar activity) reveals a strong relationship between TEC and f0F2 in all the seasons. Significantly, summer season appear to have a different trend from all other seasons with a relatively low correlation. The relationship between TEC and f0F2 seem to be stronger during period of high solar activity than period of low solar activity. Results from the work indicate that the relationship between f0F2 and TEC is mostly dependent on the seasons, followed by the level of solar activity, and then the local time. It was shown that the relationship between f0F2 and TEC is not purely monotonic as suggested earlier; but that this relationship depends on factors like the season, level of solar activity, and local time. Considering the strong relationship between f0F2 and TEC, the study affirms the method of using TEC as a proxy for f0F2 estimation.

Solar Activity Level in 1611–1613: Sunspot Groups and Areas

Solar Activity Level in 1611–1613: Sunspot Groups and Areas

Improved Neutral Density Predictions Through Machine Learning Enabled Exospheric Temperature Model

AbstractThe community has leveraged satellite accelerometer data sets in previous years to estimate neutral mass density and exospheric temperatures. We utilize derived temperature data and optimize a nonlinear machine‐learned (ML) regression model to improve upon the performance of the linear EXospheric TEMPeratures on a PoLyhedrAl gRid (EXTEMPLAR) model. The newly developed EXTEMPLAR‐ML model allows for exospheric temperature predictions at any location with one model and provides performance improvements over its predecessor. We achieve reductions in mean absolute error of 2 K on an independent test set while providing similar error standard deviation values. Comparing the performance of both EXTEMPLAR models and the Naval Research Laboratory Mass Spectrometer and Incoherent Scatter radar Extended model (NRLMSISE‐00) across different solar and geomagnetic activity levels shows that EXTEMPLAR‐ML has the lowest mean absolute error across 80% of conditions tested. A study for spatial errors demonstrated that at all grid locations, EXTEMPLAR‐ML has the lowest mean absolute error for over 60% of the polyhedral grid cells on the test set. Like EXTEMPLAR, our model's outputs can be utilized by NRLMSISE‐00 (exclusively) to more closely match satellite accelerometer‐derived densities. We conducted 10 case studies where we compare the accelerometer‐derived temperature and density estimates from four satellites to NRLMSISE‐00, EXTEMPLAR, and EXTEMPALR‐ML during major storm periods. These comparisons show that EXTEMPLAR‐ML generally has the best performance of the three models during storms. We use principal component analysis on EXTEMPLAR‐ML outputs to verify the physical response of the model to its drivers.

Seasonal and Solar Cycle Dependence of Energy Transfer Rates in the Auroral E‐Region

AbstractWe report one of the first comprehensive ground‐based investigations of energy transfer rates in the E‐region ionosphere compared relative to geomagnetic activity, seasonal effects, and solar activity level using nearly continuously sampled data collected with the Poker Flat Incoherent Scatter Radar (PFISR) between 2010 and 2019. We quantified the integrated electromagnetic (EM) energy transfer rate and the integrated Joule heating rate in the E‐region between 90 and 130 km, which includes the contribution from the neutral winds. We find that (a) the median Joule heating rate and EM energy transfer rate in the evening sector are larger in the winter versus the summer and have similar magnitudes in the spring and fall for the same solar activity and geomagnetic conditions. (b) The seasonal dependence of the energy transfer rates is closely associated with the seasonal variations of the electric fields. Our analysis shows that the larger EM energy transfer and Joule heating rates in disturbed conditions in the winter versus the summer are associated with the combined effects of both the electric field and Pedersen conductance with the electric field playing a dominant role. Given that the Pedersen conductance in the evening sector is closely related to the particle precipitation and field aligned currents in the auroral region, this study provides complementary ionospheric evidence of the winter‐summer asymmetry of the intensity and density of field‐aligned currents (e.g., Ohtani et al., 2009, https://doi.org/10.1029/2009ja014115). (c) The geomagnetic activity level has the most significant impact on the magnitude of the energy transfer rates, followed by seasonal variations, and last the solar activity level.

Reconstruction of solar activity based on 14C and other isotope profiles in lunar regolith

The Moon might be considered as an integral detector of Galactic Cosmic Rays (GCR) as it contains on its surface cosmogenic isotopes produced by nuclear reactions. Since the retrieval of lunar regolith cores by Apollo missions, there were numerous attempts to measure concentrations and depth profiles of those isotopes and reconstruct the level of cosmic radiation at 1AU at various time scales, ranging from thousands to millions of years. The data also contains encoded levels of solar activity, as the Sun affects the differential flux of GCRs in a well-known manner. All those attempts showed that our nuclear interaction codes, GEANT4 for example, need corrections to describe the lunar data, be it tweaking of cross-sections or any other methods. There are also such archives on Earth: ice cores and trees. Based on terrestrial modulation potential reconstruction we try to calibrate GEANT4 code in a transparent manner, and also present our estimates on the solar activity on time scales of 0.02 and 3 Myrs. The estimates made using our calibration procedure show values consistent with modern understanding of history of solar modulation potential, and demonstrate the necessity to establish an agreed correction method for the analysis of lunar data. We also compare our results and method with another estimation of solar modulation potential during the last 1 Myr.

Climatology of Spread F over Tucumán from Massive Statistical Analysis of Autoscaled Data

Automatic ionogram interpretation methods developed for real-time ionospheric monitoring can be applied in retrospective studies to analyze large quantities of data. The Autoscala software, implemented for such a purpose, includes a routine for automatic detection of diffused echoes known as spread F, which appear in ionograms due to the presence of ionospheric irregularities along the radio signal path. The main objective of this routine is to reject bad quality ionograms. This new capability was used in a climatological study including a large number of ionograms recorded at the low-latitude ionospheric station of Tucumán (26.9° S, 294.6° E, magnetic latitude 15.5° S, Argentina). The study took into account different levels of geomagnetic and solar activity from 2012 to 2020. The results demonstrate the capability of Autoscala to capture the main signature characteristics of spread F and the temporal evolution of the ionosphere peak heigh hmF2, capturing the post-sunset plasma surge that precedes development of spread F. Maximum occurrence of spread F is observed in local summer, with a tendency to shift before midnight with increasing solar activity. Other new climatological details that emerged from the study are illustrated and briefly discussed, dealing with connection with geomagnetic activity, and morning hmF2 behavior after extremely marked nighttime spread F occurrence.

The dependence of solar plasma parameters on the hemispheric solar activity level during the period 1967–2017

The dependence of solar plasma parameters on the hemispheric solar activity level during the period 1967–2017

Studying the winter anomaly with altimeter-derived TEC data

• This work presents of a new approach for using altimeter TEC data to study the ionospheric WA. • The outcomes agree with historical results on the locations of WA active regions. • A phenomenon leading to WA events during high solar activity was possibly identified. The ionospheric Winter Anomaly (WA) is a phenomenon discovered almost 100 years ago. It can be defined as the situations in which over a given location the winter ionization level is larger than the summer ionization level, for approximately the same solar activity conditions. Along the decades, a lot of studies have been carried out and relevant theories have been formulated to explain this phenomenon, but some aspects of the nature and physical principles of the WA are still a matter of discussion. The first objective of this work was to introduce a new technique for studying the WA, at any given location over the Oceans, based on the 27-year series of altimeter (TOPEX, Jason1, Jason 2 and Jason3 satellites)-derived Total Electron Content (TEC) data. The second objective of this work was to validate the new technique by presenting a comparative analysis between the results obtained with the new technique and those already published. This goal has been accomplished by studying the WA events over the 50°N and 50°S geographic parallels using the 27-year long altimeter data series. The results have indicated clear and systematic WA occurrences over the Northern Hemisphere and a more complex situation over the Southern Hemisphere, with two regions having different behaviors. These results are in full agreement with the findings published in relevant previous works. The last objective of this work was to present some original findings related to WA events. Taking advantage of the new technique, it has been shown that the WA might be interpreted as a high solar activity period consequence of a yearly periodic phenomenon. This phenomenon is always present, also during low solar activity years, even when WA effects are not visible. During winters over the Southern Hemisphere, it systematically produces (at any solar activity level) low maximum TEC values in the (180°E–360°E) longitudinal region and high maximum TEC values in the (0°E–180°E) longitudinal sector. Precisely, this last sector matches with the well-known region over which WA events are observed for high solar activity.

The young Sun's XUV-activity as a constraint for lower CO2-limits in the Earth's Archean atmosphere

Despite their importance for determining the evolution of the Earth's atmosphere and surface conditions, the evolutionary histories of the Earth's atmospheric CO2 abundance during the Archean eon and the Sun's activity are poorly constrained. In this study, we apply a state-of-the-art physical model for the upper atmosphere of the Archean Earth to study the effects of different atmospheric CO2/N2 mixing ratios and solar activity levels on the escape of the atmosphere to space. We find that unless CO2 was a major constituent of the atmosphere during the Archean eon, enhanced heating of the thermosphere by the Sun's strong X-ray and ultraviolet radiation would have caused rapid escape to space. We derive lower limits on the atmospheric CO2 abundance of approximately 40% at 3.8 billion years ago, which is likely enough to counteract the faint young Sun and keep the Earth from being completely frozen. Furthermore, our results indicate that the Sun was most likely born as a slow to moderate rotating young G-star to prevent rapid escape, putting essential constraints on the Sun's activity evolution throughout the solar system's history. In case that there were yet unknown cooling mechanisms present in the Archean atmosphere, this could reduce our CO2 stability limits, and it would allow a more active Sun.

Reactive oxygen species, DNA damage and Solar-Earth communications

Reactive oxygen species play a significant role in regulating the main functions of the cell both in the normal conditions and when exposing the cell to exogenous and endogenous factors under electromagnetic and radiation emission at various levels of solar activity. The research studied the impact of low-intensity alternating magnetic field; the intensity level is comparable to the geomagnetic field, in the frequency range from 3 to 60 Hz and γ-radiation on the generation of the most stable ROS which are hydrogen peroxide, in vitro. A degree of oxidative DNA damage in the blood serum of health donors, after being exposed to the alternating magnetic field, was investigated by determining the content of 8- hydroxy-2-deoxyguanosine (8-OHdG) in the blood serum and DNA single breaks in the lymphocytes. An increase of the content of 8-OHdG in DNA by a factor of 1.5 – 2 in comparison with non-emitted samples, and non-linear change in the level of lipid peroxide in the blood serum with maxima at MF frequencies of 8 and 50 Hz. In lymphocytes are observed. When exposed to gamma radiation, the number of single-strand breaks (SSB) of DNA increased with increasing exposure time from 44.3 ± 0.4% (irradiation for 30 minutes) to 68.3 ± 0.8% (irradiation for 90 minutes) compared to the control samples. It is concluded that the obtained effects can be associated with the generation of reactive oxygen species in the aquatic environment with variations in solar activity and affect the adaptive capabilities of the human body as a whole.

Prophet-Based Research on the Medium and Long-Term Forecast Method of the F10.7 Flux of the Sun

The F10.7 flux of the sun is an important parameter that characterizes the level of solar activity. However, due to the long-term periodicity and short-term randomness of solar activity, it is difficult to obtain accurate prediction results for F10.7 using statistical methods. The Prophet algorithm is based on time series decomposition and machine learning fitting. It can deal with the situation where there are some outliers in the time series, and it can also deal with the problem of partial missing values. F10.7 is a typical time series data, composed of two parts: time and observations, and has a history of nearly one hundred years of observation. It is inevitable that there will be some outliers and missing values in the observation process. Prophet’s data processing characteristics make it suitable for the requirements of the solar F10.7 observation data. Through reasonable selection of change points, it can realize the forecast of the future and the forecast of the seasonal trend, and finally realize the model fitting. The experimental results show that using the Prophet model to predict the consistency of F10.7 data and real data can reach more than 90%.

Characteristics of Energetic Oxygen Ions Escaping From Mars: MAVEN Observations

AbstractWe used nearly 4 years of data from the Mars Atmosphere and Volatile EvolutioN orbiter to map the distribution and motion of energetic O+ ions (2.3–30 keV) in the Martian environment. Our analysis reveals two typical features: a strong plume of energetic O+ ions in the +E hemisphere at dayside, driven by the convective electric field, and a less strong tailward gathering flow of energetic O+ ions in the –E hemisphere at nightside. Based on previous studies, this study reveals more details on energetic O+ ion escape: (a) velocities for energetic O+ ions between bow shock and induced magnetic boundary have much larger Y‐axis component, indicating that energetic O+ ions may not only escape along +Z‐axis but also slip away on the Y‐axis in MSE coordinates; (b) energetic O+ ions at low altitude in the –E hemisphere have little component along Y‐axis, and energetic O+ ions at nightside in the –E hemisphere “gather” along the tail and finally escape from the planet, driven by the convective electric field and the Martian current system. Comparing the fluxes and escape rates of energetic O+ at different distances away from the Sun and under different solar activities, we found that the heliocentric radial distance of Mars plays a more important role in ion escape than the solar activity level.

Multi-channel coronal hole detection with convolutional neural networks

Context.A precise detection of the coronal hole boundary is of primary interest for a better understanding of the physics of coronal holes, their role in the solar cycle evolution, and space weather forecasting.Aims.We develop a reliable, fully automatic method for the detection of coronal holes that provides consistent full-disk segmentation maps over the full solar cycle and can perform in real-time.Methods.We use a convolutional neural network to identify the boundaries of coronal holes from the seven extreme ultraviolet (EUV) channels of the Atmospheric Imaging Assembly (AIA) and from the line-of-sight magnetograms provided by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). For our primary model (Coronal Hole RecOgnition Neural Network Over multi-Spectral-data; CHRONNOS) we use a progressively growing network approach that allows for efficient training, provides detailed segmentation maps, and takes into account relations across the full solar disk.Results.We provide a thorough evaluation for performance, reliability, and consistency by comparing the model results to an independent manually curated test set. Our model shows good agreement to the manual labels with an intersection-over-union (IoU) of 0.63. From the total of 261 coronal holes with an area &gt; 1.5 × 1010km2identified during the time-period from November 2010 to December 2016, 98.1% were correctly detected by our model. The evaluation over almost the full solar cycle no. 24 shows that our model provides reliable coronal hole detections independent of the level of solar activity. From a direct comparison over short timescales of days to weeks, we find that our model exceeds human performance in terms of consistency and reliability. In addition, we train our model to identify coronal holes from each channel separately and show that the neural network provides the best performance with the combined channel information, but that coronal hole segmentation maps can also be obtained from line-of-sight magnetograms alone.Conclusions.The proposed neural network provides a reliable data set for the study of solar-cycle dependencies and coronal-hole parameters. Given the fast and robust coronal hole segmentation, the algorithm is also highly suitable for real-time space weather applications.

Identification of Fractal Properties in Geomagnetic Data of Southeast Asian Region during Various Solar Activity Levels

The fractal properties of geomagnetic northward component data (H-component) in the equatorial region during various phases of solar activity over Southeast Asia were investigated and then quantified using the parameter of the Hurst exponent (H). This study began with the identification of existence of spectral peaks and scaling properties in international quiet day H-component data which were measured during three levels of solar activity: low, intermediate, and high. Then, various cases of quiet and disturbed days during different solar activity levels were analyzed using the method that performed the best in the preceding part. In all the years analyzed, multifractal scaling and spectral peaks exist, signifying that the data have fractal properties and that there are external factors driving the fluctuations of geomagnetic activity other than solar activity. The analysis of various cases of quiet and disturbed days generally showed that quiet days had anti-persistence tendencies (H &lt; 0.5) while disturbed days had persistence tendencies (H &gt; 0.5)—generally a higher level of Hurst exponent compared to quiet days. As for long-term quiet day H-component data, it had a Hurst exponent value that was near H ≃ 0.50, while the long-term disturbed day H-component data showed higher values than that of the quiet day.

Comparative analysis of variations in the critical frequency of the ionospheric F2 layer under different heliogeophysical conditions at the Moscow station

Results of the statistical analysis of variations of critical frequency of a layer of F2 of an ionosphere at various levels of solar and geomagnetic activity are presented by data from the station Moscow from 1957 to 2019. Optimum intervals of division into levels of geomagnetic activity are experimentally found. The need to divide solar activity into low and high in ionospheric research has been proved. The effect of solar and geomagnetic activity on the occurrence of periodic positive and negative deviations of the critical frequency of the ionosphere F2 layer from the median, calculated for 27 previous days in various seasons, is shown. It has been shown that the daily course of deviations at a high level of geomagnetic activity for negative deviations ceases to be pronounced, unlike positive deviations.

Solar activity modulates the El Niño‐Southern Oscillation‐induced precipitation anomalies over southern China in early spring

AbstractThe present study identifies an evident solar cycle modulation upon the spatial pattern of the El Niño‐Southern Oscillation (ENSO) impact on the southern China precipitation in early spring (February–March). During high/low solar activity (HS/LS) years, the significant positive correlation between the wintertime Niño 3.4 index and the precipitation in the following early spring mainly locates at the southeastern China/Yangtze River Valley (SEC/YRV). Our analysis also suggests that the precipitation anomalies show asymmetries between ENSO warm and cold events under both solar phases. In HS years, the ENSO warm events‐related rainfall anomalies over the southern China are weak, but during the ENSO cold events significant dry anomalies appear at the SEC region. In LS years, significant wet anomalies over the YRV region are found during the ENSO warm events, whilst the rainfall anomalies are insignificant for the ENSO cold events. These modulations on precipitation are mediated by the changes in the ENSO‐associated anomalous western North Pacific anticyclone/cyclone, which may be attributed to the solar modulations on the ENSO‐associated sea surface temperature anomalies. Our results highlight that the level of solar activity should be taken into account when ENSO is used as a predictor for the precipitation over East Asia. [Correction added on 18 June 2021, after first online publication: The text for the abstract and graphical abstract were interchanged in the original‐published article. This updated version rectifies the error.]

Geopsychology of instrumental aggression: daily concurrence of global terrorism and solar-geomagnetic activity (1970-2018)

Formal scientific study of the geopsychology of human aggression dates back at least a century and has consistently demonstrated a positive association between solar-geomagnetic activity and aggressive behaviour. Advances in the theories, methodologies, and practical applications of geopsychology could therefore contribute to collective efforts to comprehend, to forecast, and to develop interventions for aggressive behaviours such as those seen in terrorism. This requires a rigorous and precise estimate of the magnitude of association between solar-geomagnetic activity and aggression using a representative, contemporary sample of strictly-operationalized behaviour. Here we show that days in recent history (1970-2018) with the lowest levels of instrumental human aggression (number of casualty-associated terrorism incidents) also had the lowest levels of solar and geomagnetic activity, and that stepwise increases in human aggression were mirrored by progressive increases in solar activity. We used Bayesian methods robust to outliers and heterogeneity of variance to analyze the most comprehensive and contemporary global database of terrorism incidents available, which included more than 106,000 unique instances of instrumental aggression spanning 48 years. We conclude that there is a small, nonzero promotional effect of solar-geomagnetic activity on terrorism-related aggression. This may reflect the fact that solar-geomagnetic activity serves as a zeitgeber that coordinates the expression of instrumental aggression across an aggregation of susceptible individuals. We propose that many behaviours – even instrumental acts such as terrorism which are presumed to involve a degree of planning and intention – may be subject to subtle geopsychological induction or suppression.