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The geomagnetic 'solar flare effect' (SFE) results from excess ionization in the Earth's ionosphere, famously first detected at the time of the Carrington flare in 1859. This indirect detection of a flare constituted one of the first cases of 'multimessenger astronomy', whereby solar ionizing radiation stimulates ionospheric currents. Well-observed SFEs have few-minute time-scales and perturbations of >10 nT, with the greatest events reaching above 100 nT. In previously reported cases, the SFE time profiles tend to resemble those of solar soft X-ray emission, which ionizes the D-region; there is also a less-well-studied contribution from Lyman α. We report here a specific case, from flare SOL2024-03-10 (M7.4), in which an impulsive SFE deviated from this pattern. This flare contained an 'early impulsive' component of exceptionally hard radiation, extending up to γ-ray energies above 1 MeV, distinctly before the bulk of the flare soft X-ray emission. We can characterize the spectral distribution of this early-impulsive component in detail, thanks to the modern extensive wavelength coverage. A more typical gradual SFE occurred during the flare's main phase. We suggest that events of this type warrant exploration of the solar physics in the 'impulse response' limit of very short time-scales. [ABSTRACT FROM AUTHOR]

Deficits in episodic memory have been reported in various psychiatric conditions, including Major Depressive Disorder (MDD). Many widely used episodic memory tests do not have the ability to distinguish between impaired memory of separate components of a real-life event (e.g., what happened, where it happened and when), and impaired binding of such real-life features. To address this issue, a naturalistic, real-world What-Where-When memory task was employed to assess the nature of episodic memory impairments in MDD. A validation study established that the task is sensitive to age-related episodic memory changes, and that intentional encoding does not invalidate the task. The main study then compared the performance of patients with depression and control participants on the intentionally encoded WWW task. Patients with MDD presented an overall episodic memory impairment arising from deficits in object memory and the ability to bind objects to temporal context. Taken together, our study confirms the episodic memory impairment in MDD, by providing evidence of deficient object memory and reduced ability to bind temporal context to objects in patients. Our naturalistic WWW task presents a promising approach for thorough identification of the nature of episodic memory impairments, under a real-world environment, in various conditions, including MDD. [ABSTRACT FROM AUTHOR]

Background: Abnormalities in dopamine and norepinephrine signaling are implicated in cognitive impairments in bipolar disorder (BD) and attention‐deficit hyperactivity disorder (ADHD). This systematic review by the ISBD Targeting Cognition Task Force therefore aimed to investigate the possible benefits on cognition and/or ADHD symptoms and safety of established and off‐label ADHD therapies in BD. Methods: We included studies of ADHD medications in BD patients, which involved cognitive and/or safety measures. We followed the procedures of the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis (PRISMA) 2020 statement. Searches were conducted on PubMed, Embase and PsycINFO from inception until June 2023. Two authors reviewed the studies independently using the Revised Cochrane Collaboration's Risk of Bias tool for Randomized trials. Results: Seventeen studies were identified (N = 2136), investigating armodafinil (k = 4, N = 1581), methylphenidate (k = 4, N = 84), bupropion (k = 4, n = 249), clonidine (k = 1, n = 70), lisdexamphetamine (k = 1, n = 25), mixed amphetamine salts (k = 1, n = 30), or modafinil (k = 2, n = 97). Three studies investigated cognition, four ADHD symptoms, and 10 the safety. Three studies found treatment‐related ADHD symptom reduction: two involved methylphenidate and one amphetamine salts. One study found a trend towards pro‐cognitive effects of modafinil on some cognitive domains. No increased risk of (hypo)mania was observed. Five studies had low risk of bias, eleven a moderate risk, and one a serious risk of bias. Conclusions: Methylphenidate or mixed amphetamine salts may improve ADHD symptoms in BD. However, there is limited evidence regarding the effectiveness on cognition. The medications produced no increased mania risk when used alongside mood stabilizers. Further robust studies are needed to assess cognition in BD patients receiving psychostimulant treatment alongside mood stabilizers. [ABSTRACT FROM AUTHOR]

Geomagnetically induced currents (GIC) driven by geoelectric fields pose a hazard to ground-based infrastructure, such as power grids and pipelines. Here, a new method is presented for modelling geoelectric fields in near real time, to provide valuable information to help mitigate the impact of GIC. The method uses magnetic field measurements from the Magnetometer Network of Ireland (MagIE; https://www.magie.ie), interpolates the geomagnetic field variations between magnetometers using spherical elementary current systems (SECS), and estimates the local electric field using a high-density (

Objectives: Cognitive impairment is a core feature of bipolar disorder (BD) and major depressive disorder (MDD). Deficits in processing speed (PS) and sustained attention (SA) may be particularly impaired and may underpin a broader profile of deficits, however current knowledge of the nature of these impairments is limited by heterogeneous results in the literature. Few reviews to date have attempted to disentangle sources of heterogeneity to assess the presence and magnitude of impairments in PS and SA in BD and MDD. Methods: One hundred and three studies were reviewed to examine performance in tests of PS and SA in BD (n = 3452) and MDD (n = 5461) compared to healthy controls (n = 8016). Neuropsychological methodology used in the literature was summarised. Data were meta-analysed to assess impairments in PS and SA for each neuropsychological test separately. Subgroup analysis was performed across mood states to investigate sources of heterogeneity. Results: Impairments were found across most neuropsychological tests, with small to large effect sizes for BD (range: d = 0.19-0.96) and MDD (range: d = 0.29-0.86). Impairments were present in symptomatic states and euthymia in most cases. Some outcome measures were not impaired in euthymia. Heterogeneity was observed for most neuropsychological tests and remained after separating by mood state. There inadequate data to meta-analyse some outcome measures, particularly for symptomatic groups. Conclusion: Impairments in PS and SA in BD and MDD can be observed across most neuropsychological tests. Future research should further investigate the nature of these impairments across mood states, controlling for clinical confounds. [ABSTRACT FROM AUTHOR]

Introduction: Emotion processing is an essential part of interpersonal relationships and social interactions. Changes in emotion processing have been found in both mood disorders and in aging, however, the interaction between such factors has yet to be examined in detail. This is of interest due to the contrary nature of the changes observed in existing research - a negativity bias in mood disorders versus a positivity effect with aging. It is also unclear how changes in non-emotional cognitive function with aging and in mood disorders, interact with these biases. Methods and results: In individuals with mood disorders and in healthy control participants, we examined emotional processing and its relationship to age in detail. Data sets from two studies examining facial expression recognition were pooled. In one study, 98 currently depressed individuals (either unipolar or bipolar) were compared with 61 healthy control participants, and in the other, 100 people with bipolar disorder (in various mood states) were tested on the same facial expression recognition task. Repeated measures analysis of variance was used to examine the effects of age and mood disorder diagnosis alongside interactions between individual emotion, age, and mood disorder diagnosis. A positivity effect was associated with increasing age which was evident irrespective of the presence of mood disorder or current mood episode. Discussion: Results suggest a positivity effect occurring at a relatively early age but with no evidence of a bias toward negative emotions in mood disorder or specifically, in depressed episodes. The positivity effect in emotional processing in aging appears to occur even within people with mood disorders. Further research is needed to understand how this fits with negative biases seen in previous studies in mood disorders. [ABSTRACT FROM AUTHOR]

Geoelectric fields are generated at the Earth's surface and can lead to the induction of hazardous geomagnetically induced currents (GIC) in infrastructure like power grids, railways and pipelines during geomagnetic storms. Magnitude and orientation of the geoelectric fields, in relation to the infrastructure, are key features needed to determine the intensity of GIC. Here, we developed the first geoelectric hazard map for the island of Ireland, with the aim of providing detailed information that can help stakeholders mitigate the impact of GICs. The hazard map was developed by modeling and mapping the geoelectric field across Ireland for 28 years (1991–2018) using magnetic field data with magnetotelluric transfer functions. The approach for developing the hazard map calculates the probability of exceeding a hazardous geoelectric field threshold (500 mV/km) during large geomagnetic storms, taking directionality and amplitude into account. We found hazardous geoelectric fields to be mostly localized in areas in the west, south‐west and northern coast. We observed that the geoelectric field have a stronger dominant orientation than the orientation of the geomagnetic field, often constraining the hazardous geoelectric field in particular directions only. We demonstrate a seasonal/diurnal effect is present in the geoelectric field time series. The impact of galvanic distortion was also assessed, and we demonstrate that there is a significant difference in terms of amplitude and direction between both models. Plain Language Summary: Variations in the Earth's magnetic field, during geomagnetic storms, can lead to the creation of electric fields at the surface of the Earth called geoelectric fields. Geoelectric fields can drive electrical currents known as geomagnetically induced currents (GIC) in infrastructure like power grids, railways, and pipelines. In this study, we created the first geoelectric field hazard map for Ireland. The purpose of this map is to provide a product that can help those people involved in infrastructure planning and management to reduce the impact of GIC. The results of the study indicate that areas along the northern coast, as well as the west and southwest of Ireland are more susceptible to large geoelectric fields. We found that the electric fields have a strong directional component, suggesting that the hazardous effects may occur only if the infrastructure, such as power networks are aligned in the same direction. Key Points: Geoelectric field hazard maps were generated across Ireland to evaluate the potential hazard of space weather to ground‐based infrastructureAmplitude and direction of the geoelectric field are affected by galvanic distortion, with a correction applied to examine its effectPeak geoelectric fields of 3 and 9 V/km are expected respectively for galvanic corrected and galvanic non‐corrected models [ABSTRACT FROM AUTHOR]

Episodic memory enables the detailed and vivid recall of past events, including target and wider contextual information. In this paper, we investigated whether/how encoding intentionality affects the retention of target and contextual episodic information from a novel experience. Healthy adults performed (1) a "What-Where-When" ("WWW") episodic memory task involving the hiding and delayed recall of a number of items ("what") in different locations ("where") in temporally distinct sessions (when) and (2) unexpected tests probing memory for wider contextual information from the "WWW" task. Critically, some participants were informed that memory for "WWW" information would be subsequently probed (intentional group), while this came as a surprise for others (incidental group). The probing of contextual information came as a surprise for "all" participants. Participants also performed several measures of episodic and nonepisodic cognition from which common episodic and nonepisodic factors were extracted. Memory for target ("WWW") and contextual information was superior in the intentional group compared with the incidental group. Memory for target and contextual information was "unrelated" to factors of nonepisodic cognition, irrespective of encoding intentionality. In addition, memory for target information was "unrelated" to factors of episodic cognition. However, memory for wider contextual information was "related" to some factors of episodic cognition, and these relationships differed between the intentional and incidental groups. Our results lead us to propose the hypothesis that intentional encoding of episodic information increases the coherence of the representation of the context in which the episode took place. This hypothesis remains to be tested.

Models of particle acceleration in solar eruptive events suggest that roughly equal energy may go into accelerating electrons and ions. However, while previous solar X-ray spectroscopic imagers have transformed our understanding of electron acceleration, only one resolved image of γ-ray emission from solar accelerated ions has ever been produced. This paper outlines a new satellite instrument concept—the large imaging spectrometer for solar accelerated nuclei (LISSAN)—with the capability not only to observe hundreds of events over its lifetime, but also to capture multiple images per event, thereby imaging the dynamics of solar accelerated ions for the first time. LISSAN provides spectroscopic imaging at photon energies of 40 keV–100 MeV on timescales of ≲10 s with greater sensitivity and imaging capability than its predecessors. This is achieved by deploying high-resolution scintillator detectors and indirect Fourier imaging techniques. LISSAN is suitable for inclusion in a multi-instrument platform such as an ESA M-class mission or as a smaller standalone mission. Without the observations that LISSAN can provide, our understanding of solar particle acceleration, and hence the space weather events with which it is often associated, cannot be complete. [ABSTRACT FROM AUTHOR]

Unit human capital resources (HCRs) are positively associated with unit performance and developing them is vital to sustaining unit performance. Yet, extant research has focused primarily on formal human resource methods of developing individual and group capacities (e.g., training) and given lesser attention to on-the-job mechanisms and processes impacting unit HCRs. We advance a theoretical framework featuring unit deployments, which reflect the formal or informal configuration of existing unit members' assignments to unit-relevant tasks at a point in time, as a powerful tool for unit HCR development. We first articulate how deployments can enhance unit HCR by increasing members' HCRs, cultivating members' social capital resources, and influencing unit emergence enabling states. We then introduce four types of unit HCR portfolios that differ in resource and coordination flexibility and highlight how units can use distinct deployment strategies to cultivate each type of portfolio. We conclude by detailing when each unit HCR portfolio will likely generate the greatest return for units under varying task dynamism and complexity conditions. [ABSTRACT FROM AUTHOR]

Dieulafoy lesions (DL) are an uncommon cause of gastrointestinal bleeding which is often difficult to diagnose due to the rarity of the condition and varying clinical presentations. This case describes an unusual presentation of upper gastrointestinal bleeding in an 85-year-old female with findings on two separate gastroscopies of both a gastric ulcer and duodenal DL. The pathophysiology of DL remains poorly understood and despite shared risk factors, these two pathologies are rarely reported concurrently. The presence of a concomitant gastric ulcer further complicated the diagnosis and treatment of the duodenal DL in this case. This highlights the importance of clinician awareness of this pathology and its presentation and the need for early repeat endoscopy. [ABSTRACT FROM AUTHOR]

The European Union funded the FLARECAST project, that ran from January 2015 until February 2018. FLARECAST had a research-to-operations (R2O) focus, and accordingly introduced several innovations into the discipline of solar flare forecasting. FLARECAST innovations were: first, the treatment of hundreds of physical properties viewed as promising flare predictors on equal footing, extending multiple previous works; second, the use of fourteen (14) different machine learning techniques, also on equal footing, to optimize the immense Big Data parameter space created by these many predictors; third, the establishment of a robust, three-pronged communication effort oriented toward policy makers, space-weather stakeholders and the wider public. FLARECAST pledged to make all its data, codes and infrastructure openly available worldwide. The combined use of 170+ properties (a total of 209 predictors are now available) in multiple machine-learning algorithms, some of which were designed exclusively for the project, gave rise to changing sets of best-performing predictors for the forecasting of different flaring levels, at least for major flares. At the same time, FLARECAST reaffirmed the importance of rigorous training and testing practices to avoid overly optimistic pre-operational prediction performance. In addition, the project has (a) tested new and revisited physically intuitive flare predictors and (b) provided meaningful clues toward the transition from flares to eruptive flares, namely, events associated with coronal mass ejections (CMEs). These leads, along with the FLARECAST data, algorithms and infrastructure, could help facilitate integrated space-weather forecasting efforts that take steps to avoid effort duplication. In spite of being one of the most intensive and systematic flare forecasting efforts to-date, FLARECAST has not managed to convincingly lift the barrier of stochasticity in solar flare occurrence and forecasting: solar flare prediction thus remains inherently probabilistic.

The low frequency array (LOFAR) is a phased array interferometer currently consisting of 13 international stations across Europe and 38 stations surrounding a central hub in the Netherlands. The instrument operates in the frequency range of ~10–240 MHz and is used for a variety of astrophysical science cases. While it is not heliophysics or space weather dedicated, a new project entitled “LOFAR for Space Weather” (LOFAR4SW) aims at designing a system upgrade to allow the entire array to observe the Sun, heliosphere, Earth’s ionosphere, and Jupiter throughout its observing window. This will allow the instrument to operate as a space weather observing platform, facilitating both space weather science and operations. Part of this design study aims to survey the existing space weather infrastructure operating at radio frequencies and show how LOFAR4SW can advance the current state-of-the-art in this field. In this paper, we survey radio instrumentation and facilities that currently operate in space weather science and/or operations, including instruments involved in solar, heliospheric, and ionospheric studies. We furthermore include an overview of the major space weather service providers in operation today and the current state-of-the-art in the radio data they use and provide routinely. The aim is to compare LOFAR4SW to the existing radio research infrastructure in space weather and show how it may advance both space weather science and operations in the radio domain in the near future.

One essential component of operational space weather forecasting is the prediction of solar flares. With a multitude of flare forecasting methods now available online it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Space weather researchers are increasingly looking towards methods used by the terrestrial weather community to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASAP, ASSA, MAG4, MOSWOC, NOAA, and MCSTAT). Forecasts from each method are weighted by a factor that accounts for the method’s ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. It is found that most ensembles achieve a better skill metric (between 5% and 15%) than any of the members alone. Moreover, over 90% of ensembles perform better (as measured by forecast attributes) than a simple equal-weights average. Finally, ensemble uncertainties are highly dependent on the internal metric being optimized and they are estimated to be less than 20% for probabilities greater than 0.2. This simple multi-model, linear ensemble technique can provide operational space weather centres with the basis for constructing a versatile ensemble forecasting system – an improved starting point to their forecasts that can be tailored to different end-user needs.

Most solar flares originate in sunspot groups, where magnetic field changes lead to energy build-up and release. However, few flare-forecasting methods use information of sunspot-group evolution, instead focusing on static point-in-time observations. Here, a new forecast method is presented based upon the 24-h evolution in McIntosh classification of sunspot groups. Evolution-dependent ≥C1.0 and ≥M1.0 flaring rates are found from NOAA-numbered sunspot groups over December 1988–June 1996 (Solar Cycle 22; SC22) before converting to probabilities assuming Poisson statistics. These flaring probabilities are used to generate operational forecasts for sunspot groups over July 1996–December 2008 (SC23), with performance studied by verification metrics. Major findings are: (i) considering Brier skill score (BSS) for ≥C1.0 flares, the evolution-dependent McIntosh-Poisson method (BSSevolution = 0.09) performs better than the static McIntosh-Poisson method (BSSstatic = − 0.09); (ii) low BSS values arise partly from both methods over-forecasting SC23 flares from the SC22 rates, symptomatic of ≥C1.0 rates in SC23 being on average ≈80% of those in SC22 (with ≥M1.0 being ≈50%); (iii) applying a bias-correction factor to reduce the SC22 rates used in forecasting SC23 flares yields modest improvement in skill relative to climatology for both methods ( BSSstaticcorr = 0.09 BSSstaticcorr=0.09 and BSSevolutioncorr = 0.0.20 BSSevolutioncorr=0.20 ) and improved forecast reliability diagrams.

Coronal holes (CH) are regions of open magnetic fields that appear as dark areas in the solar corona due to their low density and temperature compared to the surrounding quiet corona. To date, accurate identification and segmentation of CHs has been a difficult task due to their comparable intensity to local quiet Sun regions. Current segmentation methods typically rely on the use of single Extreme Ultra-Violet passband and magnetogram images to extract CH information. Here, the coronal hole identification via multi-thermal emission recognition algorithm (CHIMERA) is described, which analyses multi-thermal images from the atmospheric image assembly (AIA) onboard the solar dynamics observatory (SDO) to segment coronal hole boundaries by their intensity ratio across three passbands (171 Å, 193 Å, and 211 Å). The algorithm allows accurate extraction of CH boundaries and many of their properties, such as area, position, latitudinal and longitudinal width, and magnetic polarity of segmented CHs. From these properties, a clear linear relationship was identified between the duration of geomagnetic storms and coronal hole areas. CHIMERA can therefore form the basis of more accurate forecasting of the start and duration of geomagnetic storms.

Background: The relationship between major depressive disorder (MDD) and personality disorders is complex, with implications for diagnosis and treatment. We sought to explore the relationship between these disorders quantitatively in an inpatient setting. Methods: We conducted a structured observational study exploring symptoms of depression and selected neurocognitive functions over the span of an inpatient admission in those with depression and personality disorders. Sixty inpatients presenting with symptoms of depression completed ratings of mood and neurocognitive function. Diagnosis was confirmed by structured clinical interview (SCID-5-RV) at discharge and used to allocate patients to one of the two groups for analysis: those with MDD-only and those with a personality disorder (with or without MDD). Results: On admission, observer-based ratings of depression were significantly higher in the MDD-only group while subjective ratings were higher in the personality disorder group. Depression rating scores lessened in both groups during the admission, but at discharge, the personality disorder group continued to report higher subjective ratings. The personality disorder group also rated themselves as more cognitively impaired than the MDD-only group and unlike the MDD-only group, they did not report subjective improvements in cognitive function over the course of admission. Objective assessment of cognitive function demonstrated improvements in both groups. Conclusions: In this study, the presence of a personality disorder was associated with greater subjective severity of depressive symptomatology and selected neurocognitive functioning, despite similar or lower objective severity in comparison with those with MDD. This finding has implications for understanding the patient journey through health care settings. [ABSTRACT FROM AUTHOR]