bluuebunny/crossref_metadata_2025_split huggingface dataset:
Biases in machine learning models and big data analytics: The international criminal and humanitarian law implications
Authors: Milaninia Nema 
Published: March 2021

AbstractAdvances in mobile phone technology and social media have created a world where the volume of information generated and shared is outpacing the ability of humans to review and use that data. Machine learning (ML) models and “big data” analytical tools have the power to ease that burden by making sense of this information and providing insights that might not otherwise exist. In the context of international criminal and human rights law, ML is being used for a variety of purposes, including to uncover mass graves in Mexico, find evidence of homes and schools destroyed in Darfur, detect fake videos and doctored evidence, predict the outcomes of judicial hearings at the European Court of Human Rights, and gather evidence of war crimes in Syria. ML models are also increasingly being incorporated by States into weapon systems in order to better enable targeting systems to distinguish between civilians, allied soldiers and enemy combatants or even inform decision-making for military attacks.The same technology, however, also comes with significant risks. ML models and big data analytics are highly susceptible to common human biases. As a result of these biases, ML models have the potential to reinforce and even accelerate existing racial, political or gender inequalities, and can also paint a misleading and distorted picture of the facts on the ground. This article discusses how common human biases can impact ML models and big data analytics, and examines what legal implications these biases can have under international criminal law and international humanitarian law.
Media and compassion after digital war: Why digital media haven't transformed responses to human suffering in contemporary conflict
Authors: Hoskins Andrew 
Published: March 2021

AbstractThere is a persistent belief in the power of media images to transform the events they depict. Yet despite the instant availability of billions of images of human suffering and death in the continuous and connective digital glare of social media, the catastrophes of contemporary wars, such as in Syria and Yemen, unfold relentlessly. There are repeated expressions of surprise by some in the West when the dissemination of images of suffering and wars, particularly in mainstream news media, does not translate into a de-escalation of conflict.In this article I consider today's loosening of the often presumed relationship between media representation, knowledge and response under the conditions of “digital war”. This is the digital disruption of the relationship between warfare and society in which all sides participate in the uploading and sharing of information on, and images and videos of, conflict.Is it the case that the capacity of images of human injury and death to bring about change, and the expectation that they would stir practical intervention in wars, is and has been exaggerated? Even if we are moved or shocked upon being confronted by such images, does this translate into some form of action, individual or otherwise? In this article I contend that the saturation of information and images of human suffering and death in contemporary warfare has not ushered in a new era of “compassion fatigue”. Rather, algorithmically charged outrage is a proxy for effects. It is easy to misconstrue the velocity of linking and liking and sharing as some kind of mass action or mass movement.Humanitarian catastrophes slowly unfold in an age of continuous and connective digital glare, and yet they are unseen. If the imploded battlefield of digital war affording the most proximate and persistent view of human suffering and death in history cannot ultimately mobilize radically effective forms of public response, it is difficult to imagine what will.
The Influence of Slow-Paced Breathing on Executive Function
Authors: Laborde S. , Allen M. S. , Borges U. , Hosang T. J. , Furley P. , Mosley E. , Dosseville F. 
Published: March 2021

Abstract. The aim of this experiment was to test the immediate effects of slow-paced breathing on executive function. Slow-paced breathing is suggested to increase cardiac vagal activity, and the neurovisceral integration model predicts that higher cardiac vagal activity leads to better executive functioning. In total, 78 participants (41 men, 37 women; Mage = 23.22 years) took part in two counterbalanced experimental conditions: a 3 × 5 min slow-paced breathing condition and a television viewing control condition. After each condition, heart rate variability was measured and participants performed three executive function tasks: the color-word match Stroop (inhibition), the automated operation span task (working memory), and the modified card sorting task (cognitive flexibility). Results showed that performance on executive function tasks was better after slow-paced breathing compared to control, with higher scores observed for Stroop interference accuracy, automated operation span score, and perseverative errors, but not Stroop interference reaction times. This difference in executive function between experimental conditions was not mediated by cardiac vagal activity. Therefore, findings only partially align with predictions of the neurovisceral integration model. Slow-paced breathing appears a promising technique to improve immediate executive function performance. Further studies are recommended that address possible alternative underlying mechanisms and long-term effects.
A New Model for Formation of Lacustrine Primary Dolomite by Subaqueous Hydrothermal Venting
Authors: Yang Zhe , Whitaker Fiona F. , Liu Runchao , Phillips Jeremy C. , Zhong Dakang 
Published: March 2021

AbstractAlmost 230 years after it was first described, formation of the mineral dolomite remains enigmatic. Dolomitic rocks are abundant throughout the geological record, and most are thought to form by replacement of limestone. Recent work has identified substantial volumes of high‐temperature primary dolomite deposited in Cretaceous lacustrine rift basins in Northern China. Here we provide the missing conceptual understanding of the fundamental processes that may have formed such dolomitic sediments by combining an analysis of the physics and chemistry of sub‐lacustrine hydrothermal systems with new data on the mineralogy and geochemistry of the dolomites. This novel mechanism accounts for systematic changes in the characteristics of the dolomite sequence that intimately link with the evolution of convection within the fault damage zone and venting of brine‐rich mixtures to the lake basin, and provides a new model to be tested against dolomitic sediments in high‐enthalpy settings such as rifting basins.
Seafloor Geodetic Pressure Measurements to Detect Shallow Slow Slip Events: Methods to Remove Contributions From Ocean Water
Authors: Watts D. Randolph , Wei Meng , Tracey Karen L. , Donohue Kathleen A. , He Bing 
Published: March 2021

AbstractShallow slow slip events (SSEs) provide a mechanism for strain release in the shallow part of subduction zones, with fundamental implications for fault mechanics and tsunami hazards. Despite their importance, SSEs are challenging to monitor. They occur under the ocean far from land‐based GPS stations, and while seafloor pressure sensors can detect SSE vertical seafloor movements, the measured bottom pressure includes “ocean noise” signals from pressure variations within the water column. Seeking to improve techniques to remove ocean noise, a pilot study offshore Oregon collected seafloor pressure and near‐bottom current measurements at four sites from April to November 2017. Three methods were applied to reduce ocean noise: 1) subtract a reference pressure, 2) apply complex empirical orthogonal function analysis to pressure measurements, and 3) combine pressure and current measurements with optimal interpolation (OI). All three methods are established techniques from either geodesy or oceanography. Each method produced residual standard deviation, σ < 1 hPa. No SSE was detected during this study. For illustration purposes synthetic SSEs of 2 cm amplitude and 7‐days duration were added and detected, one at a time at different spots. Because currents are unaffected by a SSE, the combination of currents and pressures with the dynamical constraint of geostrophy in OI reduced the false interpretation of the synthetic SSEs as oceanic. OI produced the most reliable detection. Future seafloor geodesy field projects should consider adding current sensors and using OI methods to reduce ocean noise and to reveal tectonic signals.
Focal Mechanisms of Intraslab Earthquakes: Insights From Pseudotachylytes in Mantle Units
Authors: Hosseinzadehsabeti E. , Ferré E. C. , Andersen T. B. , Geissman J. W. , Bilardello D. , Di Toro G. 
Published: March 2021

AbstractDevastating seismic events occur mainly in subduction zones, and a significant percentage of them are intraslab earthquakes. The geologic record of these events holds valuable information that needs to be investigated for a comprehensive seismic risk assessment. Here we investigate pseudotachylytes formed in oceanic peridotites and that are interpreted to result from intraslab seismic rupture. Each vein has recorded the seismic slip direction and slip sense of a single coseismic shear‐heating event. The well‐preserved exposures, showing individual veins up to 7 m in length and about 3 cm in width, of Cima di Gratera, in the Schistes Lustrés ophiolitic units of Corsica, offer unparalleled opportunities to investigate intraslab rupture kinematics in mantle rocks. The principal ferromagnetic phase in these rocks is a Ti‐poor magnetite. We use the anisotropy of magnetic susceptibility (AMS) recorded in pseudotachylyte generation veins (bulk susceptibilities range from 600 to 20,000 × 10−6 [SI] volume, with P′ ranging from 1.05 to 2.5) to reconstruct the co‐seismic deformation parameters, that is, fault plane attitude, direction and sense of slip. These new results, internally consistent at the vein level, span across oblate and prolate symmetries and reveal that seismic deformation recorded in these veins was kinematically diverse and included mostly normal mechanisms acting along the same subduction zone. In addition, our investigations show that the magnetic fabric of peridotite‐hosted pseudotachylytes provides key information bearing on the complex dynamics of frictional melts at a unprecedently high spatial resolution.
Mitigating Injection‐Induced Seismicity Along Basement Faults by Extraction: Application to 2016–2018 Pohang Earthquakes
Authors: Chang K. W. , Yoon H. 
Published: March 2021

AbstractThe risk of induced earthquake is considered as the major obstacle for sustainable subsurface energy activities. As a mitigation approach, mechanistic risk assessment can be essential to minimize the potential of seismic hazard. Coupled hydro‐mechanical modeling approach is integrated with geomechanical analysis to better assess the occurrence of seismicity induced by injection and/or extraction, which will provide a basis to update operational conditions (e.g., number and location of mitigating wells, rate and duration of operations) for mitigating earthquake nucleation. The Coulomb stability analysis and seismicity rate estimates from this generic study indicate that simultaneous extraction can relieve injection‐induced pore‐pressure buildup, but also transfer and accumulate elastic energy along the faults. Field‐scale simulation with variation in well design for the Pohang EGS site, South Korea, show that multiple wells aligned across a preexisting fault form gradients of pressure and stress fields normal to the fault, which can enhance the direct impact of diffusion process and poroelastic stressing on the fault stability perturbation. Our mechanistic study suggests multiphysics‐oriented mitigation strategies that consider (1) possible mechanical deformation, caused by hydro‐mechanical coupling effects, and (2) proper configuration of well operations based on site‐specific geological characteristics.
Annual Mixed Layer Carbon Budget for the West Antarctic Peninsula Continental Shelf: Insights From Year‐Round Mooring Measurements
Authors: Yang Bo , Shadwick Elizabeth H. , Schultz Cristina , Doney Scott C. 
Published: March 2021

AbstractFor the first time the annual carbon budget on the West Antarctic Peninsula shelf was studied with continuously measured CO2 system parameters (pH and pCO2) from a subsurface mooring. The temporal evolution of the mixed layer dissolved inorganic carbon (DIC) is investigated via a mass balance. The annual mixed layer DIC inventory change was 1.1 ± 0.4 mol m−2 yr−1, which was mainly regulated by biological drawdown (−2.8 ± 2.4 mol m−2 yr−1), diapycnal eddy diffusion (2.6 ± 1.3 mol m−2 yr−1), entrainment/detrainment (0.9 ± 0.4 mol m−2 yr−1), and air‐water gas exchange (0.4 ± 2.1 mol m−2 yr−1). Significant carbon drawdown was observed in the spring and summer, which was replenished by the physical processes mentioned above. These observations suggest this area is an annual atmosphere CO2 sink with a mixed layer net community production of 2.8 ± 2.4 mol m−2 yr−1. These results highlight the significant seasonality in the DIC mass balance and the necessity of year‐round continuous observations for robust assessments of biogeochemical cycling in this region.
A New Probabilistic Wave Breaking Model for Dominant Wind‐Sea Waves Based on the Gaussian Field Theory
Authors: Stringari C. E. , Prevosto M. , Filipot J.‐F. , Leckler F. , Guimarães P. V. 
Published: March 2021

AbstractThis study presents a novel method for obtaining the probability of wave breaking (Pb) of deep water, dominant wind‐sea waves (i.e., waves made of the energy within ±30% of the peak wave frequency) derived from Gaussian wave field theory. For a given input wave spectrum, we demonstrate how it is possible to derive a joint probability density function between wave phase speed (c) and horizontal orbital velocity at the wave crest (u) from which a model for Pb can be obtained. A nonlinear kinematic wave breaking criterion consistent with the Gaussian framework is further proposed. Our model would allow, therefore, the application of the classical wave breaking criterion (i.e., wave breaking occurs if u/c > 1) in spectral wave models which, to the authors' knowledge, has not been done to date. Our results show that the proposed theoretical model has errors in the same order of magnitude as six other historical models when assessed using three field data sets. With optimization of the proposed model's single free parameter, it can become the best performing model for specific data sets. Although our results are promising, additional, more complete wave breaking data sets collected in the field are needed to comprehensively assess the present model, especially in regards to the dependence on phenomena such as direct wind forcing, long wave modulation, and wave directionality.
Hypoxic Effects on the Radiocarbon in DIC of the ECS Subsurface Water
Authors: Wang Shing‐Lin , Fan Daidu , Huang Wei‐Jen , Wu Yijing , Su Jianfeng 
Published: March 2021

AbstractDissolved inorganic carbon (DIC) in the East China Sea (ECS) is physically and chemically affected by the northward intrusion of the Kuroshio Branch Current (KBC) and the Changjiang River (CR) outflow. We trace these processes using dual DIC isotopic compositions (Δ14C and δ13C) along transects that begin in the CR and estuary, and extend out into middle shelf waters of the ECS. We especially focus on frequently occurred nearshore hypoxia, as they appeared in the summer of 2017. The Δ14C values (28.8‰–35.3‰) from the ECS mid‐shelf water were comparable to the reported value from the Kuroshio Current (KC) at the continental slope (34.4‰ ± 7.4‰), but Δ14C values in the CR (−173.6‰ & −162.3‰) were substantially lower than observations made in 2014. We also found that the Δ14C of DIC in the bottom waters along the inner shelf, including hypoxic area, decreased from 25.0‰ to 18.5‰, from south to north. Water masses mixing between the CR and the ECS mid‐shelf waters with and without organic carbon degradation can be identified in plots of Δ14C versus DIC‐1. With simple mixing calculations, we show that the northward decreasing Δ14C of inner shelf bottom water is caused by downward transport of DIC with low Δ14C value mediated by biological process from the surface, as opposed to simple physical mixing.
Modeling Extreme Warm‐Air Advection in the Arctic During Summer: The Effect of Mid‐Latitude Pollution Inflow on Cloud Properties
Authors: Bossioli Elissavet , Sotiropoulou Georgia , Methymaki Georgia , Tombrou Maria 
Published: March 2021

AbstractUsually the Arctic is relatively free of anthropogenic influence in summer, which means that particles from natural sources can be the most significant nuclei for cloud droplets. However, this is not the case during anomalously warm‐air intrusions when the air origin comes from lower latitudes. In this modeling study, we investigate the effect of mid‐latitude pollution inflow (anthropogenic and biomass burning [BB]) on the aerosol‐cloud‐radiation interactions during an episode of extreme warm‐air advection. This particular episode resulted in anomalously high air temperatures over the East Siberian Sea and has accelerated sea‐ice melting. The impact of different emission sources on aerosol vertical distribution, chemical composition, cloud formation, and radiation budget is examined using the Weather Research and Forecasting model, fully coupled with chemistry. Elevated turbulent clouds that occurred at the beginning of the episode are found to be more sensitive to aerosol variations and their negative feedback on supersaturation, compared to stably stratified fog layers that were dominant during the core period. Omission of either anthropogenic or BB source results in decreased cloud liquid water and cloud droplet concentrations; however, these changes are not substantially large to significantly modify the net surface radiation budget. Significant reduction of the net surface radiation is only observed if both anthropogenic and BB transported pollution reaches the area of interest.
Evaluation of the Effect of Low Soil Temperature Stress on the Land Surface Energy Fluxes Simulation in the Site and Global Offline Experiments
Authors: Zhu Siguang , Chen Haishan , Dai Yongjiu , Lu Xingjie , Shangguan Wei , Yuan Hua , Wei Nan 
Published: March 2021

AbstractThe root water uptake (RWU) rate of plants is influenced by various environmental factors. Low soil temperature stress can reduce RWU rate by inhibiting the growth of plant roots and increasing the hydraulic resistance of water transport among the soil‐plant‐atmosphere continuum. Given that low soil temperature stress is not accounted for in current land surface models (LSMs); in this study, we introduce three functions to represent low soil temperature stress, and modify the RWU scheme of the Common Land Model to quantify the role of low soil temperature stress on water and energy exchange between land and atmosphere. The simulated water and energy fluxes are evaluated using both in situ and global observational data sets. The results from in situ simulations show that ignoring effects of low soil temperature stress, latent, and sensible heat fluxes in spring are overestimated and underestimated, respectively, with the root mean square error up to 40 W/m2. By incorporating the low soil temperature stress functions into the RWU scheme, nearly 40% of the simulated errors are reduced. The global simulated results also highlight the importance of accounting for low soil temperature stress on increasing the accuracy of the modeled latent heat flux over high latitude areas. While uncertainties from related physical processes and parameters warrant further investigations, our results indicate that consideration of low soil temperature stress significantly affects water and energy transport from land to atmosphere by restricting RWU rate, emphasizing the need to integrate it in LSMs to increase the model reliability, especially over cold regions.
Difference in the Sporadic E Layer Occurrence Ratio Between the Southern and Northern Low Magnetic Latitude Regions as Observed by COSMIC Radio Occultation Data
Authors: Niu J. 
Published: March 2021

AbstractIn this study, the difference in the sporadic E layer occurrence ratio between two low‐magnetic‐latitude (±5° to ±15°) regions is analyzed by using COSMIC scintillation observations covering the period from 2007.001 to 2017.365. Obvious longitudinal, seasonal, and LT dependencies of this phenomenon are found. Most features of the differences between two hemispheres could be explained by the difference in zonal vertical wind shear between the two hemispheres induced by the difference between the magnetic and geographic latitudes of the studied regions. This result also indicates that the wind shear mechanism still dominates sporadic E layer formation in low‐magnetic‐latitude regions.
Long Short‐Term Memory Neural Network for Ionospheric Total Electron Content Forecasting Over China
Authors: Xiong Pan , Zhai Dulin , Long Cheng , Zhou Huiyu , Zhang Xuemin , Shen Xuhui 
Published: March 2021

AbstractAn increasing number of terrestrial‐ and space‐based radio‐communication systems are influenced by the ionospheric space weather, making the ionospheric state increasingly important to forecast. In this study, a novel extended encoder‐decoder long short‐term memory extended (ED‐LSTME) neural network, which can predict ionospheric total electron content (TEC) is proposed. Useful inherent features were automatically extracted from the historical TEC by LSTM layers, and the performance of the proposed model was enhanced by considering solar flux and geomagnetic activity data. The proposed ED‐LSTME model was validated using 15‐min TEC values from GPS measurements over one solar cycle (from January 2006 to July 2018) collected at 15 GPS stations in China. Different assessment experiments were conducted in different geographical locations and seasons as well as under varying geomagnetic activities, to comprehensively evaluate the model's performance. These comparative experiments were conducted using an ED‐LSTM, a traditional LSTM, a deep neural network, autoregressive integrated moving average, and the 2016 International Reference Ionosphere models. The results indicated that the ED‐LSTME model is superior to the other statistical models, with R2 and root mean square error values of 0.89 and 12.09 TECU, respectively. In addition, TEC was adequately predicted under different ionospheric conditions, and satisfactory results were obtained even under geomagnetically disturbed conditions. These results suggest that the prediction performance could be significantly improved by utilizing auxiliary data. These observations confirm that the proposed model outperforms several state‐of‐the‐art models in making predictions at different times and under diverse conditions.