bluuebunny/crossref_metadata_2025_split huggingface dataset:
A randomized trial of aerobic exercise for major depression: examining neural indicators of reward and cognitive control as predictors and treatment targets
Authors: Brush C. J. , Hajcak Greg , Bocchine Anthony J. , Ude Andrew A. , Muniz Kristina M. , Foti Dan , Alderman Brandon L. 
Published: August 2020

AbstractBackgroundAerobic exercise has demonstrated antidepressant efficacy among adults with major depression. There is a poor understanding of the neural mechanisms associated with these effects. Deficits in reward processing and cognitive control may be two candidate targets and predictors of treatment outcome to exercise in depression.MethodsSixty-six young adults aged 20.23 years (s.d. = 2.39) with major depression were randomized to 8 weeks of moderate-intensity aerobic exercise (n = 35) or light stretching (n = 31). Depressive symptoms were assessed across the intervention to track symptom reduction. Reward processing [reward positivity (RewP)] and cognitive control [error-related negativity (ERN)] were assessed before and after the intervention using event-related brain potentials.ResultsCompared to stretching, aerobic exercise resulted in greater symptom reduction (gs = 0.66). Aerobic exercise had no impact on the RewP (gav = 0.08) or ERN (gav = 0.21). In the aerobic exercise group, individuals with a larger pre-treatment RewP [odds ratio (OR) = 1.45] and increased baseline depressive symptom severity (OR = 1.18) were more likely to respond to an aerobic exercise program. Pre-treatment ERN did not predict response (OR = 0.74).ConclusionsAerobic exercise is effective in alleviating depressive symptoms in adults with major depression, particularly for those with increased depressive symptom severity and a larger RewP at baseline. Although aerobic exercise did not modify the RewP or ERN, there is preliminary support for the utility of the RewP in predicting who is most likely to respond to exercise as a treatment for depression.
Mild cognitive impairment with Lewy bodies: neuropsychiatric supportive symptoms and cognitive profile
Authors: Donaghy Paul C , Ciafone Joanna , Durcan Rory , Hamilton Calum A , Barker Sally , Lloyd Jim , Firbank Michael , Allan Louise M , O'Brien John T , Taylor John-Paul , Thomas Alan J 
Published: August 2020

AbstractBackgroundRecently published diagnostic criteria for mild cognitive impairment with Lewy bodies (MCI-LB) include five neuropsychiatric supportive features (non-visual hallucinations, systematised delusions, apathy, anxiety and depression). We have previously demonstrated that the presence of two or more of these symptoms differentiates MCI-LB from MCI due to Alzheimer's disease (MCI-AD) with a likelihood ratio >4. The aim of this study was to replicate the findings in an independent cohort.MethodsParticipants ⩾60 years old with MCI were recruited. Each participant had a detailed clinical, cognitive and imaging assessment including FP-CIT SPECT and cardiac MIBG. The presence of neuropsychiatric supportive symptoms was determined using the Neuropsychiatric Inventory (NPI). Participants were classified as MCI-AD, possible MCI-LB and probable MCI-LB based on current diagnostic criteria. Participants with possible MCI-LB were excluded from further analysis.ResultsProbable MCI-LB (n = 28) had higher NPI total and distress scores than MCI-AD (n = 30). In total, 59% of MCI-LB had two or more neuropsychiatric supportive symptoms compared with 9% of MCI-AD (likelihood ratio 6.5, p < 0.001). MCI-LB participants also had a significantly greater delayed recall and a lower Trails A:Trails B ratio than MCI-AD.ConclusionsMCI-LB is associated with significantly greater neuropsychiatric symptoms than MCI-AD. The presence of two or more neuropsychiatric supportive symptoms as defined by MCI-LB diagnostic criteria is highly specific and moderately sensitive for a diagnosis of MCI-LB. The cognitive profile of MCI-LB differs from MCI-AD, with greater executive and lesser memory impairment, but these differences are not sufficient to differentiate MCI-LB from MCI-AD.
A systematic review of treatments for alcohol-related cognitive impairment: lessons from the past and gaps for future interventions
Authors: Caballeria Elsa , Oliveras Clara , Nuño Laura , Balcells-Oliveró Mercedes , Gual Antoni , López-Pelayo Hugo 
Published: August 2020

AbstractAlcohol-related cognitive impairment (ARCI) is highly prevalent among patients with alcohol dependence. Although it negatively influences treatment outcome, this condition is underdiagnosed and undertreated. The aim of this systematic review is to investigate the existing evidence regarding both cognitive and pharmacological interventions for ARCI. We systematically reviewed PubMed, Scopus and Science direct databases up to May 2019 and followed the PRISMA guidelines. The quality of the studies was assessed using the Jadad Scale. Twenty-six studies were eligible for inclusion (14 referring to neuropsychological interventions and 12 to pharmacological treatments). Among neuropsychological interventions, computerised treatments, errorless learning and component method showed positive effects on working memory, memory measures and general cognitive function. On the other hand, thiamine, memantine and methylphenidate improved working memory, long-term memory and general cognitive function. Nevertheless, these studies have several limitations, such as small sample size, lack of replication of the results or low specificity of the interventions. Therefore, no gold-standard intervention can yet be recommended for clinical practice, and further research based on promising strategies (e.g. digital interventions, thiamine) is required.
‘It gives you a reason to be in this world’: the interdependency of communities, environments and social justice for quality of life in older people
Authors: Robertson Jane M. , Gibson Grant , Greasley-Adams Corinne , McCall Vikki , Gibson Joan , Mason-Duff Janice , Pengelly Ro 
Published: August 2020

AbstractResearch regarding quality of life among older people has predominantly focused on functional elements experienced at individual or dyadic level despite the complex interplay of factors that contribute to quality of life. Perspectives which explore interdependencies within communities and the intersecting environments in which older people exercise agency have seen less study. They do, however, play an important role in influencing quality of life as experienced by older people across community settings. Qualitative data from a co-produced study of dimensions influencing quality of life in older people was subjected to secondary analysis using a critical human ecological approach. Findings demonstrate the importance of community interdependencies in supporting individual quality of life, the expression of active agency to foster quality of life within and across communities, and the importance of state infrastructures and service provision within these interdependencies. This article argues for a movement beyond functional conceptualisations of quality of life towards the inclusion of perspectives regarding communal wellbeing, alongside the role differing types of community play in influencing quality of life. Through developing conceptions of quality of life in social relations and community cohesion, in particular how quality of life is influenced by perceptions of solidarity and social justice including across generations, assessing quality of life at community level will assist in driving cultural change in policy making and practice.
Sentinel surveillance strategies for early detection of coronavirus disease in fever clinics: experience from China
Authors: Lai Rongtao , Chen Erzhen , Gao Weiyi , Cheng Chengwei , Xie Qing 
Published: August 2020

Abstract
Sentinel surveillance system plays a key role in screening and monitoring emerging and acute infectious diseases in order to identify the suspected cases in time. During SARS period in 2003, fever clinics emerged in many cities in mainland China with the purpose to screen the suspected SARS patients and to transfer the confirmed cases to designated hospitals for professional management. Shanghai city has reserved the fever clinics and the designated hospitals since then. Hence, clinicians in the front line are able to respond quickly to the emerging COVID-19 outbreak with their accumulated knowledge and experiences from the past. One hundred seventeen fever clinics distributed in various district areas in Shanghai have played a vital ‘sentinel’ role to fight against the COVID-19 epidemic. Most of suspected patients were identified in fever clinics and thereafter among these suspected patients the COVID-19 cases were confirmed and were isolated quickly to avoid the spread. We would like to share the sentinel roadmap for screening and diagnosis of COVID-19 to medical healthcare workers around the world, especially countries who are facing great challenges to cope with COVID-19 and meanwhile with limited medical resources. These sentinel surveillance strategies will certainly provide insight into the early detection and timely isolation of suspected cases from the others.
A TWO-DIMENSIONAL LOGIC FOR TWO PARADOXES OF DEONTIC MODALITY
Authors: FUSCO MELISSA , KOCUREK ALEXANDER W. 
Published: August 2020

AbstractIn this paper, we axiomatize the deontic logic in Fusco (2015), which uses a Stalnaker-inspired account of diagonal acceptance and a two-dimensional account of disjunction to treat Ross’s Paradox and the Puzzle of Free Choice Permission. On this account, disjunction-involving validities are a priori rather than necessary. We show how to axiomatize two-dimensional disjunction so that the introduction/elimination rules for boolean disjunction can be viewed as one-dimensional projections of more general two-dimensional rules. These completeness results help make explicit the restrictions Fusco’s account must place on free-choice inferences. They are also of independent interest, as they raise difficult questions about how to “lift” a Kripke frame for a one-dimensional modal logic into two dimensions.
Vertical mobility and cotton tolerance to trifludimoxazin, a new protoporphyrinogen oxidase-inhibiting herbicide, in three West Texas soils
Authors: Asher B. Scott , Dotray Peter A. , Liebl Rex A. , Keeling J. Wayne , Ritchie Glen D. , Udeigwe Theophilus K. , Reed Jacob D. , Keller Kyle E. , Bowe Steve J. , Aldridge Ryan B. , Simon Anja 
Published: August 2020

AbstractTrifludimoxazin, a new protoporphyrinogen oxidase–inhibiting herbicide, is being evaluated for possible use as a soil-residual active herbicide treatment in cotton for control of small-seeded annual broadleaf weeds. Laboratory and greenhouse studies were conducted to compare vertical mobility and cotton tolerance of trifludimoxazin to flumioxazin and saflufenacil, which are two currently registered protoporphyrinogen oxidase–inhibiting herbicides for use in cotton, in three West Texas soils. Vertical soil mobility of trifludimoxazin was similar to flumioxazin in Acuff loam and Olton loam soils, but was more mobile than flumioxazin in the Amarillo loamy sand soil. The depth of trifludimoxazin movement after a 2.5-cm irrigation event ranged from 2.5 to 5.0 cm in all soils, which would not allow for crop selectivity based on herbicide placement, because ideal cotton seeding depth is from 0.6 to 2.54 cm deep. Greenhouse studies indicated that PRE treatments were more injurious than the 14 d preplant treatment when summarized across soils for the three herbicides (43% and 14% injury, respectively). No differences in visual cotton response or dry weight was observed after trifludimoxazin preplant as compared with the nontreated control within each of the three West Texas soils and was similar to the flumioxazin preplant across soils. On the basis of these results, a use pattern for trifludimoxazin in cotton may be established with the use of a more than 14-d preplant restriction before cotton planting.
Forecasting Global Fire Emissions on Subseasonal to Seasonal (S2S) Time Scales
Authors: Chen Yang , Randerson James T. , Coffield Shane R. , Foufoula‐Georgiou Efi , Smyth Padhraic , Graff Casey A. , Morton Douglas C. , Andela Niels , van der Werf Guido R. , Giglio Louis , Ott Lesley E. 
Published: August 2020

AbstractFire emissions of gases and aerosols alter atmospheric composition and have substantial impacts on climate, ecosystem function, and human health. Warming climate and human expansion in fire‐prone landscapes exacerbate fire impacts and call for more effective management tools. Here we developed a global fire forecasting system that predicts monthly emissions using past fire data and climate variables for lead times of 1 to 6 months. Using monthly fire emissions from the Global Fire Emissions Database (GFED) as the prediction target, we fit a statistical time series model, the Autoregressive Integrated Moving Average model with eXogenous variables (ARIMAX), in over 1,300 different fire regions. Optimized parameters were then used to forecast future emissions. The forecast system took into account information about region‐specific seasonality, long‐term trends, recent fire observations, and climate drivers representing both large‐scale climate variability and local fire weather. We cross‐validated the forecast skill of the system with different combinations of predictors and forecast lead times. The reference model, which combined endogenous and exogenous predictors with a 1 month forecast lead time, explained 52% of the variability in the global fire emissions anomaly, considerably exceeding the performance of a reference model that assumed persistent emissions during the forecast period. The system also successfully resolved detailed spatial patterns of fire emissions anomalies in regions with significant fire activity. This study bridges the gap between the efforts of near‐real‐time fire forecasts and seasonal fire outlooks and represents a step toward establishing an operational global fire, smoke, and carbon cycle forecasting system.
Challenges in Specifying and Predicting Space Weather
Authors: Schunk R. W. , Scherliess L. , Eccles V. , Gardner L. C. , Sojka J. J. , Zhu L. , Pi X. , Mannucci A. J. , Komjathy A. , Wang C. , Rosen G. 
Published: August 2020

AbstractPhysics‐based Data Assimilation (DA) has been shown to be a powerful technique for specifying and predicting space weather. However, it is also known that different data assimilation models simulating the same geophysical event can display different space weather features even if the same data are assimilated. In this study, we used our Multimodel Ensemble Prediction System (MEPS) of DA models to elucidate the similarities and differences in the individual DA model reconstructions of the mid‐low latitude ionosphere when the same data are assimilated. Ensemble model averages were also obtained. For this ensemble modeling study, we selected the quiet/storm period of 16 and 17 March 2013 (equinox, solar medium). Five data assimilation models and one physics‐based model were used to produce an ensemble mean output for Total Electron Content (TEC), ionospheric peak density (NmF2), and ionospheric peak height (hmF2) for latitudes less than 60° and all longitudes. The data assimilated included ground‐based Global Positioning Satellite TEC and topside plasma densities near 800 km altitude derived from the COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites. Both a simple average and a weighted average of the models were used in the ensemble averaging in order to determine if there was an improvement of the ensemble averages over the individual models.
Long‐Term Shifts in U.S. Nitrogen Sources and Sinks Revealed by the New TREND‐Nitrogen Data Set (1930–2017)
Authors: Byrnes D. K. , Van Meter K. J. , Basu N. B. 
Published: August 2020

AbstractReactive nitrogen (N) fluxes have increased tenfold over the last century, driven by increases in population, shifting diets, and increased use of commercial N fertilizers. Runoff of excess N from intensively managed landscapes threatens drinking water quality and disrupts aquatic ecosystems. Excess N is also a major source of greenhouse gas emissions from agricultural soils. While N emissions from agricultural landscapes are known to originate from not only current‐year N input but also legacy N accumulation in soils and groundwater, there has been limited access to fine‐scale, long‐term data regarding N inputs and outputs over decades of intensive agricultural land use. In the present work, we synthesize population, agricultural, and atmospheric deposition data to develop a comprehensive, 88‐year (1930–2017) data set of county‐scale components of the N mass balance across the contiguous United States (Trajectories Nutrient Dataset for nitrogen [TREND‐nitrogen]). Using a machine‐learning algorithm, we also develop spatially explicit typologies for components of the N mass balance. Our results indicate a large range of N trajectory behaviors across the United States due to differences in land use and management and particularly due to the very different drivers of N dynamics in densely populated urban areas compared with intensively managed agricultural zones. Our analysis of N trajectories also demonstrates a widespread functional homogenization of agricultural landscapes. This newly developed typology of N trajectories improves our understanding of long‐term N dynamics, and the underlying data set provides a powerful tool for modeling the impacts of legacy N on past, present, and future water quality.
Topside Ionosphere of NeQuick2 and IRI‐2016 Validated by Using Onboard GPS Observations From Multiple LEO Satellites
Authors: Ren Xiaodong , Chen Jun , Zhang Xiaohong , Yang Pengxin 
Published: August 2020

AbstractAn accurate description of the topside ionosphere is of great importance for space weather applications. Currently, there are two commonly used empirical ionosphere models, that is, NeQuick2 and IRI‐2016, that can be used to describe the topside ionosphere. In this study, topside total electron content (TEC) values derived from low Earth orbit (LEO) satellites are selected to validate the topside ionosphere predictions of the NeQuick2 and IRI‐2016 models from 2008 to 2018. The results show that these two models both underestimate the topside ionosphere. Compared with the global topside ionosphere model estimated by LEO‐based global positioning system (GPS) observations with orbital altitudes of 500 and 800 km, NeQuick2 and IRI‐2016 have similar performances over different latitudes and longitudes. The daily mean root mean square (RMS) values are approximately 4.10 and 2.10 TEC units (TECU) for the region above 500 and 800 km, respectively. The results assessed by the GPS‐TEC technique indicate that the performance of the NeQuick2 model is slightly better than that of the IRI‐2016 model. The daily mean bias mainly ranges from −1.5 to 1.5 and −3.0 to −1.0 TECU for the regions above 500 and 800 km, respectively. The RMS values for the corresponding parts are 3.50 and 2.74 TECU. Finally, the validation results of the dSTEC method show that the mean bias is −0.43 and −0.20 TECU above 500 and 800 km, respectively. The mean RMS values are 2.04 and 0.72 TECU for the corresponding regions.
Formation and Topology of Foreshock Bubbles
Authors: Omidi N. , Lee S. H. , Sibeck D. G. , Turner D. L. , Liu T. Z. , Angelopoulos V. 
Published: August 2020

AbstractWe use global and local hybrid (kinetic ions and fluid electrons) simulations to investigate the conditions under which foreshock bubbles (FBs) form and how their topology changes with solar wind conditions. FBs form as a result of the interaction between solar wind discontinuities and backstreaming ion beams in the foreshock. They consist of an outer shock and its associated sheath plasma and a low density high temperature core with low magnetic field strength. The structure of FBs is determined by the angle between the interplanetary magnetic field and the normal to the solar wind discontinuity. We show that interaction of rotational discontinuities with the foreshock during small angles between the interplanetary magnetic field and discontinuity normal results in the formation of a nearly spherical bubble with a radius that scales with the width of the foreshock. As this angle increases, FBs become more elongated and eventually become nearly planar structures with dimensions that scale with the length of the foreshock. Despite this transformation, the signatures of FBs in spacecraft time series data remain the same in agreement with the observations. Global simulation results show that FBs form when the solar wind flow speed corresponds to high or intermediate Alfvén Mach numbers (approximately >7 MA). In general, this is tied to the relative speed between the solar wind and ion beams and drop in density of the backstreaming ions.
Importance of Regional‐Scale Auroral Precipitation and Electrical Field Variability to the Storm‐Time Thermospheric Temperature Enhancement and Inversion Layer (TTEIL) in the Antarctic E Region
Authors: Wu Haonan , Lu Xian , Lu Gang , Chu Xinzhao , Wang Wenbin , Yu Zhibin , Kilcommons Liam M. , Knipp Delores J. , Wang Boyi , Nishimura Yukitoshi 
Published: August 2020

AbstractA dramatic thermospheric temperature enhancement and inversion layer (TTEIL) was observed by the Fe Boltzmann lidar at McMurdo, Antarctica during a geomagnetic storm (Chu et al. 2011, https://doi.org/10.1029/2011GL050016). The Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIEGCM) driven by empirical auroral precipitation and background electric fields cannot adequately reproduce the TTEIL. We incorporate the Defense Meteorological Satellite Program (DMSP)/Special Sensor Ultraviolet Spectrographic Imager (SSUSI) auroral precipitation maps, which capture the regional‐scale features into TIEGCM and add subgrid electric field variability in the regions with strong auroral activity. These modifications enable the simulation of neutral temperatures closer to lidar observations and neutral densities closer to GRACE satellite observations (~475 km). The regional scale auroral precipitation and electric field variabilities are both needed to generate strong Joule heating that peaks around 120 km. The resulting temperature increase leads to the change of pressure gradients, thus inducing a horizontal divergence of air flow and large upward winds that increase with altitude. Associated with the upwelling wind is the adiabatic cooling gradually increasing with altitude and peaking at ~200 km. The intense Joule heating around 120 km and strong cooling above result in differential heating that produces a sharp TTEIL. However, vertical heat advection broadens the TTEIL and raises the temperature peak from ~120 to ~150 km, causing simulations deviating from observations. Strong local Joule heating also excites traveling atmospheric disturbances that carry the TTEIL signatures to other regions. Our study suggests the importance of including fine‐structure auroral precipitation and subgrid electric field variability in the modeling of storm‐time ionosphere‐thermosphere responses.