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Despite routine detection of coseismic acoustic‐gravity waves (AGWs) in Global Navigation Satellite System (GNSS) total electron content (TEC) observations, models of the earthquake‐atmosphere‐ionosphere dynamics, essential for validating data‐driven studies, remain limited. We present the results of three‐dimensional numerical simulations encompassing the entire coupling from Earth's interior to the ionosphere during the Mw${M}_{w}$7.8 2016 Kaikoura earthquake. Incorporating the impact of data/model uncertainties in estimating the ionospheric state, the results show a good agreement between observed and simulated slant TEC (sTEC) signals, assessed through a set of metrics. The signals exhibit intricate waveforms, resulting from the integrated nature of TEC and phase cancellation effects, emphasizing the significance of direct signal comparisons along realistic line‐of‐sight paths. By comparing simulation results initialized with kinematic and dynamic source models, the study demonstrates the quantifiable sensitivity of sTEC to AGW source specifications, pointing to their utility in the analysis of coupled dynamics. Earthquakes launch acoustic‐gravity waves (AGWs) into the atmosphere, spanning periods from seconds to minutes, that can reach the ionosphere at ∼${\sim} $100–400 km altitude. The majority of AGW detections in the ionosphere are performed with the use of GNSS signals collected with ground‐based receivers that nowadays comprehensively cover seismically active regions. However, the modeling of earthquake‐atmosphere‐ionosphere processes together, essential for validating and supporting data‐driven studies, remains rare. We present the outcomes of three‐dimensional numerical modeling of interconnected processes, spanning from Earth's interior to the ionosphere. We conducted a case study focused on the 2016 Mw${M}_{w}$7.8 earthquake in New Zealand, renowned for its complexity and comprehensive observations of coseismic AGWs recorded with GNSS signals. Our results demonstrate a high level of accuracy of simulated GNSS signals, also revealing the high sensitivity to the chosen earthquake model and the complexity of resulting ionospheric signals, highlighting the necessity of attributing realistic geometries of GNSS TEC observations. The findings highlight the potential for using GNSS signals to investigate coseismic AGWs to infer characteristics of earthquakes. Acoustic‐gravity wave‐driven slant total electron content (sTEC) signals are analyzed in terms of amplitude, waveform, and onset timeIntricate sTEC signal waveforms result from ionospheric fluctuations measured along lines‐of‐sight between satellites and receiversHigh sensitivity of sTEC signals to acoustic‐gravity wave source specification provides additional basis for earthquake characterization Acoustic‐gravity wave‐driven slant total electron content (sTEC) signals are analyzed in terms of amplitude, waveform, and onset time Intricate sTEC signal waveforms result from ionospheric fluctuations measured along lines‐of‐sight between satellites and receivers High sensitivity of sTEC signals to acoustic‐gravity wave source specification provides additional basis for earthquake characterization

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We present a new technique for the upcoming tri‐static incoherent scatter radar system EISCAT 3D (E3D) to perform a volumetric reconstruction of the 3D ionospheric electric current density vector field, focusing on the feasibility of the E3D system. The input to our volumetric reconstruction technique are estimates of the 3D current density perpendicular to the main magnetic field, j⊥, and its covariance, to be obtained from E3D observations based on two main assumptions: (a) Ions fully magnetized above the Eregion, set to 200 km here. (b) Electrons fully magnetized above the base of our domain, set to 90 km. In this way, j⊥estimates are obtained without assumptions about the neutral wind field, allowing it to be subsequently determined. The volumetric reconstruction of the full 3D current density is implemented as vertically coupled horizontal layers represented by Spherical Elementary Current Systems with a built‐in current continuity constraint. We demonstrate that our technique is able to retrieve the three dimensional nature of the currents in our idealized setup, taken from a simulation of an active auroral ionosphere using the Geospace Environment Model of Ion‐Neutral Interactions (GEMINI). The vertical current is typically less constrained than the horizontal, but we outline strategies for improvement by utilizing additional data sources in the inversion. The ability to reconstruct the neutral wind field perpendicular to the magnetic field in the Eregion is demonstrated to mostly be within ±50 m/s in a limited region above the radar system in our setup. We introduce a novel method for the upcoming EISCAT 3D (E3D) radar system to reconstruct the 3D electric current density vector in Earth's ionosphere. Here we present the new technique and assess its feasibility for the E3D system. The input to the 3D reconstruction technique relies on estimates of the current density perpendicular to the Earth's magnetic field, obtained from the E3D observations. We include estimates of uncertainties originating from the observations of the 3D ion velocity vectors and electron density in our reconstruction. Comparisons with simulations of an active auroral ionosphere exemplify that our technique provides reasonably accurate estimates of current density, especially in the 90–150 km altitude range. Our results demonstrate success in retrieving the horizontal part of the electric current system in the Eregion, while the vertical part has more uncertainty. Our method offers insight into how electric currents flow in a specific region of the Earth's atmosphere. The results can be further improved with additional data sources; this flexibility is a significant advantage of our approach. Overall, our study facilitates the advanced knowledge of Earth's upper atmosphere using innovative radar observations in companion with advanced analysis techniques. A technique for volumetric reconstruction of 3D electric current density from tri‐static incoherent scatter radar observations is presentedConsidering the anticipated noise levels, the radar system is likely to produce good current density estimates in a limited regionThe reconstruction technique is particularly well suited for inclusion of additional data sources that improve overall performance A technique for volumetric reconstruction of 3D electric current density from tri‐static incoherent scatter radar observations is presented Considering the anticipated noise levels, the radar system is likely to produce good current density estimates in a limited region The reconstruction technique is particularly well suited for inclusion of additional data sources that improve overall performance

Data products relating to auroral arc systems are often sparse and distributed while ionospheric simulations generally require spatially continuous maps as boundary conditions at the topside ionosphere. Fortunately, all‐sky auroral imagery can provide information to fill in the gaps. This paper describes three methods for creating electrostatic plasma convection maps from multi‐spectral imagery combined with plasma flow data tracks from heterogeneous sources. These methods are tailored to discrete arc structures with coherent morphologies. The first method, “reconstruction,” builds the electric potential map (from which the flow field is derived) out of numerous arc‐like ridges that are then optimized against the plasma flow data. This method is designed for data from localized swarms of spacecraft distributed in both latitude and longitude. The second method, “replication,” uses a 1D across‐arc flow data track and replicates these data along a determined primary and secondary arc boundary while simultaneously scaling and rotating to keep the flow direction parallel to the arc and the flow shear localized at the arc boundaries. The third, “weighted replication,” performs a replication on two data tracks and calculates a weighted average between them, where the weighting is based on data track proximity. This paper shows the use of these boundary conditions in driving and assessing 3D auroral ionospheric, multi‐fluid simulations. The aurora, or northern and southern lights, are embedded within a complicated system of interacting electric fields, magnetic fields, and charged particles, the more energetic of which produce the lights themselves by exciting the neutral atmosphere. This brings about a 3D electric current system. These currents enter and exit the atmosphere along the Earth's magnetic field lines, and can only close their circuit between 80 and 150 km. This paper outlines the importance of simulating auroral arc systems in 3D and thus the need for generating continuous horizontal top‐boundary drivers for these simulations. This is difficult as the available data products are limited. This paper provides three methods for creating these boundary conditions using multi‐color, all‐sky auroral imagery in conjunction with approximately across‐arc plasma flow data tracks provided by spacecraft, sounding rockets, and/or radar measurements. We provide three methods for developing ionospheric convection flow maps from limited data tracks in conjunction with auroral imageryMethods for generating distributed plasma flow surrounding auroral arcs can benefit from auroral arc information provided by all‐sky imageryModeling realistic auroral current closure needs drivers that vary along‐arc, across‐arc, and in altitude via electron precipitation spectra We provide three methods for developing ionospheric convection flow maps from limited data tracks in conjunction with auroral imagery Methods for generating distributed plasma flow surrounding auroral arcs can benefit from auroral arc information provided by all‐sky imagery Modeling realistic auroral current closure needs drivers that vary along‐arc, across‐arc, and in altitude via electron precipitation spectra

Electron density irregularities in the ionosphere can give rise to scintillations, affecting radio wave phase and amplitude. While scintillations in the cusp and polar cap regions are commonly associated with mesoscale density inhomogeneities and/or shearing, the auroral regions exhibit a strong correlation between scintillation and density structures generated by electron precipitation (arcs). We aim to examine the impact of electron precipitation on the formation of scintillation‐producing density structures using a high‐resolution physics‐based plasma model, the “Geospace Environment Model of Ion‐Neutral Interactions,” coupled with a radio propagation model, the “Satellite‐beacon Ionospheric‐scintillation Global Model of the upper Atmosphere.” Specifically, we explore the effects of varying spatial and temporal characteristics of the precipitation, including electron total energy flux and their characteristic energies, obtained from the all‐sky‐imagers and Poker Flat Incoherent Scatter Radar observations, on auroral scintillation. To capture small‐scale structures, we incorporate a power‐law turbulence spectrum that induces short wavelength features sensitive to scintillation. Finally, we compare our simulated scintillation results with satellite‐observed scintillations, along with spectral comparisons. A physics‐based plasma model and a radio propagation model are used to examine the effects of precipitation on auroral scintillationPrecipitation fluxes with higher energy, a turbulent noise spectrum, and a faster‐moving arc intensify scintillationThe presence of small‐scale precipitation amplifies both phase and amplitude scintillations A physics‐based plasma model and a radio propagation model are used to examine the effects of precipitation on auroral scintillation Precipitation fluxes with higher energy, a turbulent noise spectrum, and a faster‐moving arc intensify scintillation The presence of small‐scale precipitation amplifies both phase and amplitude scintillations

Cardiovascular and metabolic disorders rarely occur alone in old age but often cluster together in the so-called metabolic syndrome (MetS). While individual components of MetS, such as obesity, hypertension, and diabetes, have been linked to dementia and brain atrophy, their combined impact on cognitive and brain aging remains poorly explored. Our current study aims to investigate the relationship between MetS and markers of neurodegenerative and cerebrovascular pathologies while also considering potential differences between sexes.

Space‐based observations of the signatures associated with STEVE show how this phenomenon might be closely related to an extreme version of a SAID channel. Measurements show high velocities (>4 km/s), high temperatures (>4,000 K), and very large current density drivers (up to 1μA/m2). This phenomena happens in a small range of latitudes, less than a degree, but with a large longitudinal span. In this study, we utilize the GEMINI model to simulate an extreme SAID/STEVE. We assume a FAC density coming from the magnetosphere as the main driver, allowing all other parameters to adjust accordingly. We have two main objectives with this work: show how an extreme SAID can have velocity values comparable or larger than the ones measured under STEVE, and to display the limitations and missing physics that arise due to the extreme values of temperature and velocity. Changes had to be made to GEMINI due to the extreme conditions, particularly some neutral‐collision frequencies. The importance of the temperature threshold at which some collision frequencies go outside their respective bounds, as well as significance of the energies that would cause inelastic collisions and impact ionization are displayed and discussed. We illustrate complex structures and behaviors, emphasizing the importance of 3D simulations in capturing these phenomena. Longitudinal structure is emphasized, as the channel develops differently depending on MLT. However, these simulations should be viewed as approximations due to the limited observations available to constrain the model inputs and the assumptions made to achieve sensible results. We present a full 4D (3D + time) simulation of an extreme SAIDWe utilize the GEMINI model for the simulation due to the practicality and easiness to set arbitrary input files. Though challenges remainWe highlight the importance of inelastic collisions and impact ionization on damping the channel velocity, physics not included in GEMINI We present a full 4D (3D + time) simulation of an extreme SAID We utilize the GEMINI model for the simulation due to the practicality and easiness to set arbitrary input files. Though challenges remain We highlight the importance of inelastic collisions and impact ionization on damping the channel velocity, physics not included in GEMINI

This study examines cumulative effects of a series of poleward moving auroral forms on ion upflow and downflow. These effects are investigated using an ionospheric model with inputs derived from the Rocket Experiment for Neutral Upwelling 2 (RENU2) sounding rocket campaign. Auroral precipitation inputs are constrained by all‐sky imager brightness values resulting in significant latitudinal structuring in simulated ionospheric upflows due to transient forcing. For contrast, a case with steady forcing generates almost double the O+upflow transport through 1,000 km when compared to poleward moving auroral form‐like structures. At high altitudes, model results show a spread in upflow response time dependent on ion mass, with molecular ions responding slower than atomic ions by several minutes. While the modeled auroral precipitation is not strong enough to accelerate ions to escape velocities, source populations available for higher‐altitude energization processes are greatly impacted by variable forcing exhibited by the RENU2 event. Imager data provide realistic transient forcing constraints for model inputs to simulate observations from a high‐latitude rocket flightTransient forcing deposits energy over a wider latitudinal region but less energy in any specific locationModeling a sequence of poleward moving auroral forms with realistic spatiotemporal variability generates significant latitudinal structuring

Electromagnetic signals including Global Navigation Satellite Systems (GNSS) signals often experience fluctuations due to ionospheric density structures termed as scintillation. Physical processes contributing to these structures in polar cap regions likely include gradient‐drift instability. GNSS scintillations are frequently observed at high latitudes and are potentially useful diagnostics of how energy from the transient forcing in the cusp or polar cap region cascades, via instabilities, to small scales. This work interfaces a physics‐based plasma model (Geospace Environment Model of Ion‐Neutral Interactions) to a radio wave propagation model (Satellite‐beacon Ionospheric‐scintillation Global Model of the upper Atmosphere) to explore this cascade. In this work, Geospace Environment Model of Ion‐Neutral Interactions‐Satellite‐beacon Ionospheric‐scintillation Global Model of the upper Atmosphere is used to simulate signal propagation through gradient‐drift instability over Resolute Bay for comparison with GNSS observations during a geomagnetic storm presented earlier in this series of papers. Our spectral and multiscale analyses show close agreement for simulated and observed data, suggesting the use of our physics‐based platform for understanding and predicting the effects of ionospheric instabilities on navigation and communication. Radio signals such as those from Global Positioning System experience fluctuations due to plasma structures or instabilities in the Earth's upper atmosphere (ionosphere) that cause the signal to bend and scatter, called scintillation. Navigation and communication on the ground can be severely affected during geomagnetically active conditions. It is difficult to understand the ionospheric turbulence and how it is generated by simply looking at the Global Positioning System measurements. For the first time, a physics‐based ionosphere model and 3‐D Electromagnetic (EM) wave propagation model are combined to extract quantitative details about the irregularities. We present our results of comparing observations during a geomagnetic storm to a simulation from a combination of two models Geospace Environment Model of Ion‐Neutral Interactions and Satellite‐beacon Ionospheric‐scintillation Global Model of the upper Atmosphere. Our simulation results provide basic agreement with observations in terms of the scale sizes and strength of the ionospheric structures, thus providing a promising avenue for a further study of causes of scintillation. Such a state‐of‐the‐art tool provides a way to potentially characterize scintillation coming from different types of instabilities and evolving in time under different types of forcing mechanisms in the ionosphere. We have interfaced a high‐latitude plasma instability model with a model of scintillationWe can simulate GNSS scintillation observed on the edges of polar cap patches generated by gradient‐drift instabilitiesSpectral and multiscale analysis results show that the simulated phase has periods and scales similar to the observations

Some existing auroral data products are insufficient for ionospheric simulation input on subkilometer spatial scales and high (second) time resolution near the boundaries of arc structures. Ideally, two‐dimensional data maps of the relevant parameters over these small scales would provide models with constraining inputs. Available in situ data have the time and spatial resolution for small‐scale features but only provide a 1‐D cut through the structure. Ground‐based data can provide 2‐D maps but have lower resolution in time and space than is required to accurately interpret the small‐scale structure near an arc. This paper provides a method to construct two‐dimensional maps of auroral parameters from the combination of one‐dimensional in situ data cuts with two‐dimensional ground‐based (and time dependent) camera imagery. Arc boundaries for each image are defined, and the available 1‐D ionospheric flow data are replicated into many 1‐D cuts at different points along the arc, yielding an irregularly sampled 2‐D flow map. These mapped data are fitted to a regular grid via a divergence minimization routine to generate a regularly sampled flow field that is enforced as divergence free. Comparison of the generated 2‐D data maps to available information from camera inversions and other data products is shown, as are assumptions made through the replication process and alternative strategies. Reconstructed flow maps are shown to maintain the small‐scale features near arc boundaries while increasing the dimensionality to 2‐D and to follow the time evolution of the arc structure by comparisons to imagery. The average electric field magnitudes per unit area of the reconstructed and divergence‐minimized flow fields are also calculated and compared between different data sources. We provide a new procedure for mapping ionospheric flow data using ground camera imageryWe evaluate mapped ionospheric plasma flow data in context of existing measurementsWe compare model outputs with existing measurements and auroral assumptions

Atrial fibrillation (AF) is a known risk factor for stroke and heart failure (HF). In addition, individuals with HF have an increased risk for AF. An increasing body of evidence have also linked AF to dementia, while less is known regarding the relation between HF and dementia. We aim to investigate if higher genetic risk, measured with polygenic risk scores (PRSs), for AF and HF increases dementia and stroke risk in the general population.

Genome-wide association studies (GWASs) have shown that several genes, beside the “high-effect” APOE gene, are involved in modulating the risk of dementia and longevity, and some of these genes overlap between the traits. Considering longevity, there are also associations with genes related to other age-related disorders, such as diabetes and cancer. Previous studies have shown associations between genetics of dementia and longevity and measures reflecting brain age, but the vast majority of these studies were performed in age heterogeneous samples. The aim of our study is to investigate how polygenic scores for dementia, general cognitive function, and longevity, associate with predicted biological brain age in 70-year-olds from the general population.

Distinct patterns of brain atrophy exists in common neurodegenerative disorders. However, whether these patterns are present also in non-clinical populations remains elusive, yet crucial to detect people at-risk of dementia. This cross-sectional study aimed to identify specific patterns of grey matter atrophy and their determinants among cognitively intact older individuals.

Exposure to dementia risk factors throughout life can lead to brain atrophy and older- appearing brains on neuroimaging. Resilience mechanisms can help sustain the brain structure (brain maintenance, BM) and/or compensate for the neuropathological damage (cognitive reserve, CR), preserving cognition. Traditional proxy-based approaches (e.g., education) face challenges in measuring these mechanisms as they cannot capture the core biological dimension. However, with deep learning is possible to develop algorithms predicting the biological age of the brain from raw brain images. This study investigated whether differences between predicted brain age and chronological age (PBA-CA) can be used as a marker of BM and/or CR following the NIH-funded Collaboratory on Reserve and Resilience framework.

A higher adherence to a Mediterranean diet (MeDi) has been associated with more brain integrity, and slower cognitive decline. In 2019, the EAT-Lancet commission presented a new, mainly plant-based healthy reference diet, aimed to be environmentally sustainable. However, health benefits of the diet have been questioned, and the impact on cognition and brain health has not been established. This cross-sectional study aims to compare the EAT-Lancet diet vs. the MeDi in relation to cognitive function and neuroimaging markers of neurodegenerative and cerebrovascular alterations among older adults.

Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to aging. Yet, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool quantifying normative neurodevelopmental trajectories.

Electron-transfer and -capture dissociations of doubly protonated peptides gave dramatically different product ions for a series of histidine-containing pentapeptides of both non-tryptic (AAHAL, AHAAL, AHADL, AHDAL) and tryptic (AAAHK, AAHAK, AHAAK, HAAAK, AAAHR, AAHAR, AHAAR, HAAAR) type. Electron transfer from gaseous Cs atoms and fluoranthene anions triggered backbone dissociations of all four N−Cαbonds in the peptide ions in addition to loss of H and NH3. Substantial fractions of charge-reduced cation-radicals did not dissociate on an experimental time scale ranging from 10−6to 10−1s. Multistage tandem mass spectrometric (MSn) experiments indicated that the non-dissociating cation-radicals had undergone rearrangements. These were explained as being due to proton migrations from N-terminal ammonium and COOH groups to the C-2′ position of the reduced His ring, resulting in substantial radical stabilization. Ab initio calculations revealed that the charge-reduced cation-radicals can exist as low-energy zwitterionic amide π* states which were local energy minima. These states underwent facile exothermic proton migrations to form aminoketyl radical intermediates, whereas direct N−Cαbond cleavage in zwitterions was disfavored. RRKM analysis indicated that backbone N−Cαbond cleavages did not occur competitively from a single charge-reduced precursor. Rather, these bond cleavages proceeded from distinct intermediates which originated from different electronic states accessed by electron transfer. In stark contrast to electron transfer, capture of a free electron by the peptide ions mainly induced radical dissociations of the charge-carrying side chains and loss of a hydrogen atom followed by standard backbone dissociations of even-electron ions. The differences in dissociation are explained by different electronic states being accessed upon electron transfer and capture.

Plasma escape from the high‐latitude ionosphere (ion outflow) serves as a significant source of heavy plasma to the magnetospheric plasma sheet and ring current regions. Outflows alter mass density and reconnection rates, hence global responses of the magnetosphere. A new fully kinetic and semi‐kinetic model, KAOS (Kinetic model of Auroral ion OutflowS), is constructed from first principles which traces large numbers of individual O+ion macro‐particles along curved magnetic field lines, using a guiding‐center approximation, in order to facilitate calculation of ion distribution functions and moments. Particle forces include mirror and parallel electric field forces, a self‐consistent ambipolar electric field, and a parameterized source of ion cyclotron resonance wave heating, thought to be central to the transverse energization of ions. The model is initiated with a steady‐state ion density altitude profile and Maxwellian velocity distribution and particle trajectories are advanced via a direct simulation Monte Carlo scheme. This outlines the implementation of the kinetic outflow model, demonstrates the model's ability to achieve near‐hydrostatic equilibrium necessary for simulation spin‐up, and investigates L‐shell dependent wave heating and pressure cookers scenarios. This paper illustrates the model initialization process and numerical investigations of L‐shell dependent outflows and pressure cooker environments and serves to advance our understanding of the drivers and particle dynamics in the auroral ionosphere. A new model, KAOS (Kinetic model of Auroral ion OutflowS), is introduced for studying ionospheric outflows from first principlesWe quantify dependence of upflowing/outflowing ion distributions on parameters pertaining to the characterization of pressure cookersMagnetospheric potential structures may transport highly transversely energized ion distributions to ionospheric altitudes A new model, KAOS (Kinetic model of Auroral ion OutflowS), is introduced for studying ionospheric outflows from first principles We quantify dependence of upflowing/outflowing ion distributions on parameters pertaining to the characterization of pressure cookers Magnetospheric potential structures may transport highly transversely energized ion distributions to ionospheric altitudes

A numerical study of the effects of seismically generated acoustic waves in the ionosphere is conducted using a three‐dimensional (3‐D) ionospheric model driven by an axisymmetric neutral atmospheric model. A source consistent with the 2011 Tohoku earthquake initial ocean surface uplifting is applied to simulate the subsequent responses. Perturbations in electron density, ion drift, total electron content (TEC), and ground‐level magnetic fields are examined. Results reveal strong latitude and longitude dependence of ionospheric TEC, and of ground‐level magnetic field perturbations associated with acoustic wave‐driven ionospheric dynamo currents. Results also demonstrate that prior two‐dimensional models can capture dominant meridional responses of TEC over latitude, even though dynamics at other longitudes are not resolved. Conclusions support that TEC and magnetic signatures can arise from nonlinear acoustic waves generated by strong earthquakes; simulations elucidate the comprehensive physics of their 3‐D ionospheric responses. This paper reports new numerical model results on how the ionosphere—the ionized, conducting region of the upper‐atmosphere—responds to strong acoustic waves launched by earthquakes. The effects of these waves in the ionosphere can be observed from ground: They are measured as variations in Global Positioning System satellite signals received at the ground, which translate to variations in integrated electron content of the ionosphere. They can be detected also via small fluctuations in magnetic field, which are driven by ionospheric currents. The model results suggest that both measurement techniques can provide insight into the waves and their sources; new guidance for interpreting these measurements is provided. Further, results demonstrate a new capability for simulating these processes in three dimensions, which can be applied to more‐realistic case studies. Earthquake‐driven TEC and magnetic perturbations are studied with a 3‐D modelMagnetic fluctuations driven by infrasonic acoustic waves are detectableLocal geomagnetic field geometry affects directionality of TEC responses

This study examines how thermospheric motions due to gravity waves (GWs) drive ion upflow in the Fregion, modulating the topside ionosphere in a way that can contribute to ion outflow. We present incoherent scatter radar data from Sondrestrom, from 31 May 2003 which showed upflow/downflow motions, having a downward phase progression, in the field‐aligned velocity, indicating forcing by a thermospheric GW. The GW‐upflow coupling dynamics are investigated through the use of a coupled atmosphere‐ionosphere model to examine potential impacts on topside ionospheric upflow. Specifically, a sequence of simulations with varying wave amplitude is conducted to determine responses to a range of transient forcing reminiscent of the incoherent scatter radar data. Nonlinear wave effects, resulting from increases in amplitude of the modeled GW, are shown to critically impact the ionospheric response. GW breaking deposits energy into smaller scale wave modes, drives periods of large field‐aligned ion velocities, while also modulating ion densities. Complementary momentum transfer increases the mean flow and, through ion‐neutral drag, can increase ion densities above 300 km. Ionospheric collision frequency (cooling) and photoionization effects (heating), both dependent on ionospheric density, modify the electron temperature; these changes conduct quickly up geomagnetic field lines driving ion upflow at altitudes well above initial disturbances. This flow alters ion populations available for high‐altitude acceleration processes that may lead to outflow into the magnetosphere. We have included a representative source of transverse wave heating which, when supplemented by our GWs, illustrates strengthened upward fluxes in the topside ionosphere. High‐latitude ionospheric upflow can be modulated by thermospheric gravity wavesFregion density perturbations due to gravity wave modulations, through heating and cooling processes, modulate the electron temperatureIncreases in electron temperature quickly conduct up the magnetic field lines and drive upflow at altitudes above the initial heating region

It is a well-established fact that unfavourable social and economic conditions have a negative impact on health and longevity. Recent findings suggest that this is also true of age-related dementias. Yet most common indicators of socioeconomic status (SES) say very little about the actual mechanisms at play in disease development. The present paper explores five work exposure characteristics, all of which have a clear social gradient, that could potentially shed further light on the relationship between SES and dementia. Specifically, it investigates whether these exposures could moderate the impact of a well-known genetic risk factor: the APOEɛ4 allele. The empirical analyses are based on data from a Swedish population study (n = 1019). Main occupation was linked to The Job Exposure Matrix to estimate the individuals’ exposure to the following work environment factors: work control, support, psychological demands, physical demandsand job hazards.All analyses were conducted using binary logistic regression and focused specifically on gene-work exposure interactions. A significant main effect of work controlon dementia risk was detected for males (OR = 0.68; p< 0.05), but not for females. However, control was found to significantly moderate the effect of APOEɛ4 in both genders, albeit in different ways. These findings do not only underscore the importance of considering interactions between social and genetic risk factors to better understanding multifactorial diseases such as dementia. They also propose that gender- and class-based inequities interact, and hence must be considered simultaneously, also in relation to this particular disease.

Depression and dementia in the elderly have been suggested to share similar risk factors and pathogenetic background, and recently the authors reported that the APOEɛ4 allele is a risk factor for both disorders in the general population. The aim of the present study was to examine the influence of the well-known polymorphisms rs1799752 in the angiotensin-converting enzyme (ACE) and rs5186 in the angiotensin receptor II type 1 (AGTR1) on late-life depression and dementia in a population-based Swedish cohort of older individuals followed over 12 years.

Numerical models of ionospheric coupling with the neutral atmosphere are used to investigate perturbations of plasma density, vertically integrated total electron content (TEC), neutral velocity, and neutral temperature associated with large‐amplitude acoustic waves generated by the initial ocean surface displacements from strong undersea earthquakes. A simplified source model for the 2011 Tohoku earthquake is constructed from estimates of initial ocean surface responses to approximate the vertical motions over realistic spatial and temporal scales. Resulting TEC perturbations from modeling case studies appear consistent with observational data, reproducing pronounced TEC depletions which are shown to be a consequence of the impacts of nonlinear, dissipating acoustic waves. Thermospheric acoustic compressional velocities are ∼±250–300 m/s, superposed with downward flows of similar amplitudes, and temperature perturbations are ∼300 K, while the dominant wave periodicity in the thermosphere is ∼3–4 min. Results capture acoustic wave processes including reflection, onset of resonance, and nonlinear steepening and dissipation—ultimately leading to the formation of ionospheric TEC depletions “holes”—that are consistent with reported observations. Three additional simulations illustrate the dependence of atmospheric acoustic wave and subsequent ionospheric responses on the surface displacement amplitude, which is varied from the Tohoku case study by factors of 1/100, 1/10, and 2. Collectively, results suggest that TEC depletions may only accompany very‐large amplitude thermospheric acoustic waves necessary to induce a nonlinear response, here with saturated compressional velocities ∼200–250 m/s generated by sea surface displacements exceeding ∼1 m occurring over a 3 min time period. Large undersea earthquakes generate large‐amplitude acoustic waves with compressional velocities exceeding 200 m/sModeled ionospheric responses to the 2011 Tohoku earthquake, including TEC depletions, are consistent with the dataTEC depletions are shown to be a result of an initial acoustic shock followed by nonlinear, dissipating acoustic waves in the thermosphere.

A new anisotropic fluid model is developed to describe ionospheric upflow responses to magnetospheric forcing by electric fields and broadband ELF waves at altitudes of 90–2500 km. This model is based on a bi‐Maxwellian ion distribution and solves time‐dependent, nonlinear equations of conservation of mass, momentum, parallel energy, and perpendicular energy for six ion species important to E, F, and topside ionospheric regions. It includes chemical and collisional interactions with the neutral atmosphere, photoionization, and electron impact ionization. This model is used to examine differences between isotropic and anisotropic descriptions of ionospheric upflow driven by DC electric fields, possible effects of low‐altitude (<500 km) wave heating, and impacts of neutral winds on ion upflow. Results indicate that isotropic models may overestimate field‐aligned ion velocity responses by as much as ∼48%. Simulations also show significant ionospheric responses at low altitudes to wave heating for very large power spectral densities, but ion temperature anisotropies below the Fregion peak are dominated by frictional heating from DC electric fields. Neutral winds are shown to play an important role regulating ion upflow. Thermospheric winds can enhance or suppress upward fluxes driven by DC and BBELF fields by 10–20% for the cases examined. The time history of the neutral winds also affects the amount of ionization transported to higher altitudes by DC electric fields. A new anisotropic fluid model is developed and describes ionospheric responses to energy sources causing anisotropyDC electric fields dominate temperature anisotropies at lower altitudes, while wave heating dominates at higher altitudesHigh‐latitude thermospheric winds can aid or hinder upflow depending on the wind direction