bluuebunny/crossref_metadata_2025_split huggingface dataset:
Learning Automata-based Misinformation Mitigation via Hawkes Processes
Authors: Abouzeid Ahmed , Granmo Ole-Christoffer , Webersik Christian , Goodwin Morten 
Published: February 2021

AbstractMitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint random walk over the state space. We use three Twitter datasets to evaluate our approach, one of them being a new COVID-19 dataset provided in this paper. Our approach shows fast convergence and increased valid information exposure. These results persisted independently of network structure, including networks with central nodes, where the latter could be the root of misinformation. Further, the LA obtained these results in a decentralized manner, facilitating distributed deployment in real-life scenarios.
Testing Buddha: Is Acute Desire Associated with Lower Momentary Happiness?
Authors: Murphy Stephen L. , Ozaki Yuka , Friese Malte , Hofmann Wilhelm 
Published: February 2021

AbstractA central Buddhist claim is that having desires causes suffering. While this tenet draws from the belief that an acute desire state is more momentarily aversive than a no-desire state, the efficacy of this belief has yet to be comprehensively examined. To empirically investigate this claim, we furnished data from two experience sampling studies across USA/Canadian (N = 101; 3224 observations) and Japanese cultures (N = 237; 8497 observations). We compared states of acute desire with states of no desire regarding momentary happiness. We then tested, in an additional step, whether acute desires at greater conflict with personal goals were associated with even lower levels of momentary happiness. Findings were consistent across studies, with participants experiencing greater momentary happiness when not experiencing a desire compared to experiencing acute desire. Also, the greater the desire conflicted with important goals the lower the momentary happiness. The present findings support a key basis of the Buddhist belief that having desires causes suffering, showing acute desire states on average to be more aversive than no desire states.
Autonomous long-range drone detection system for critical infrastructure safety
Authors: Zhang Xindi , Kusrini Kusrini 
Published: February 2021

AbstractThe development of unmanned aerial vehicles has been identified as a potential source of a weapon for causing operational disruptions against critical infrastructures. To mitigate and neutralise the threat posed by the misuse of drones against malicious and terrorist activity, this paper presents a holistic design of a long-range autonomous drone detection platform. The novelty of the proposed system lies in the confluence between the design of hardware and software components to effective and efficient localisation of the intruder objects. The research presented in the paper proposes the design and validation of a situation awareness component which is interfaced with the hardware component for controlling the focal length of the camera. The continuous stream of media data obtained from the region of vulnerability is processed using the object detection that is built on region based fully connected neural network. The novelty of the proposed system relies on the processing of multi-threaded dual-media input streams that are evaluated to mitigate the latency of the system. Upon the successful detection of malicious drones, the system logs the occurrence of intruders that consists of both event description and the associated media evidence for the deployment of the mitigation strategy. The analytics platform that controls the signalling of the low-cost sensing equipment contains the NVIDIA GeForce GTX 1080 for detecting drones. The experimental testbeds developed for the validation of the proposed system has been constructed to include environments and situations that are commonly faced by critical infrastructure operators such as the area of protection, drone flight path, tradeoff between the angle of coverage against the distance of coverage. The validation of the proposed system has resulted in yielding a range of intruder drone detection by 250m with an accuracy of 95.5%.
Client-driven animated GIF generation framework using an acoustic feature
Authors: Mujtaba Ghulam , Lee Sangsoon , Kim Jaehyoun , Ryu Eun-Seok 
Published: February 2021

AbstractThis paper proposes a novel, lightweight method to generate animated graphical interchange format images (GIFs) using the computational resources of a client device. The method analyzes an acoustic feature from the climax section of an audio file to estimate the timestamp corresponding to the maximum pitch. Further, it processes a small video segment to generate the GIF instead of processing the entire video. This makes the proposed method computationally efficient, unlike baseline approaches that use entire videos to create GIFs. The proposed method retrieves and uses the audio file and video segment so that communication and storage efficiencies are improved in the GIF generation process. Experiments on a set of 16 videos show that the proposed approach is 3.76 times more computationally efficient than a baseline method on an Nvidia Jetson TX2. Additionally, in a qualitative evaluation, the GIFs generated using the proposed method received higher overall ratings compared to those generated by the baseline method. To the best of our knowledge, this is the first technique that uses an acoustic feature in the GIF generation process.
Effect of Species Composition on Polycyclic Aromatic Hydrocarbon (PAH) Accumulation in Urban Forest Soils of Krakow
Authors: Lasota Jarosław , Łyszczarz Stanisław , Kempf Piotr , Kempf Marta , Błońska Ewa 
Published: February 2021

AbstractPolycyclic aromatic hydrocarbons (PAHs) are among the most hazardous organic pollutants due to their toxic, carcinogenic, mutagenic properties, wide distribution, recalcitrance and stability in the environment. The study objective is to determine the impact of the species composition of tree stands on PAH accumulation in urban forest soils of Krakow. The study compared the impact of deciduous and coniferous species on similar soils on PAH biodegradation. Basic physicochemical properties, activity of enzymes involved in the nutrient cycle and PAH content were measured in soil samples. Our study shows lower accumulation of PAHs in soils with deciduous tree stands, which are characterized by higher pH and higher biochemical activity expressed by enzymatic activity. There is statistically significant difference in the enzymatic activity in the soils of deciduous tree stands, which results in differences in PAH accumulation. Among the studied deciduous species, soils with Norway maple and locust were characterized by highest enzymatic activity. At the same time, soils under these species were characterized by the lowest PAH accumulation. Among the coniferous species, highest PAH accumulation was observed under pine and spruce, where low enzymatic activity was observed at the same time.
An enhancement of the current design concepts for the improved consideration of residual stresses in fatigue-loaded welds
Authors: Nitschke-Pagel Th. , Hensel J. 
Published: February 2021

AbstractThe consideration of residual stresses in fatigue-loaded welds is currently done only qualitatively without reliable knowledge about their real distribution, amount and prefix. Therefore, the tools which enable a more or less unsafe consideration in design concepts are mainly based on unsafe experiences and doubtful assumptions. Since the use of explicitly determined residual stresses outside the welding community is state of the art, the target of the presented paper is to show a practicable way for an enhanced consideration of residual stresses in the current design tools. This is not only limited on residual stresses induced by welding, but also on post-weld treatment processes like HFMI or shot peening. Results of extended experiments with longitudinal fillet welds and butt welds of low and high strength steels evidently show that an improved use of residual stresses in fatigue strength approximation enables a better evaluation of peening processes as well as of material adjusted welding procedures or post-weld stress relief treatments. The concept shows that it is generally possible to overcome the existing extremely conservative but although unsafe rules and regulations and may also enable the improved use of high strength steels.
Correlation effect of transformed or corrected data inversion
Authors: Balázs László 
Published: February 2021

AbstractBefore performing the inversion process, the original measured data set is often transformed (corrected, smoothed, Fourier-transformed, interpolated etc.). These preliminary transformations may make the original (statistically independent) noisy measurement data correlated. The noise correlation on transformed data must be taken into account in the parameter fitting procedure (inversion) by proper derivation of likelihood function. The covariance matrix of transformed data system is no longer diagonal, so the likelihood based metrics, which determines the fitting process is also changed as well as the results of inversion. In the practice, these changes are often neglected using the “customary” estimation procedure (simple least square method) resulting wrong uncertainty estimation and sometimes biased results. In this article the consequence of neglected correlation is studied and discussed by decomposing the inversion functional to “customary” and additional part which represents the effect of correlation. The ratio of two components demonstrates the importance and justification of the inversion method modification.
A capabilities approach to best interests assessments
Authors: Thomson Michael 
Published: February 2021

AbstractIt is an accepted principle of domestic and international law and policy that the welfare or best interests of the child must be the primary or paramount consideration in any decision made with regard to that child's upbringing. While this ‘best interests standard’ has become a core principle of welfare law, what might constitute a child or young person's best interests is given very little formal shape or content. This has provoked sustained criticism from practitioners, academics and the judiciary. In response, this paper argues that the capabilities approach can give best interests assessments much needed normative content, thereby addressing many of the criticisms directed towards the standard. The approach provides a theoretically nuanced framework for theorising about basic social justice and for evaluation, deliberation, and policy development across social welfare sectors. In arguing for a capabilities approach to best interests assessments, the paper sets out an agenda for change. It addresses the conceptual and methodological justifications for this change, and explores the empirical work that would be required. It identifies the steps and underlying principles necessary for a best interests process aligned with the capabilities approach, providing the necessary foundations for a radical reconceptualisation of best interests processes.
The vowesses, the anchoresses and the aldermen's wives: Lady Margaret Beaufort and the devout society of late medieval Stamford
Authors: Delman Rachel M. 
Published: February 2021

AbstractThis article investigates a devout society centring on the household of Margaret Beaufort (d. 1509) at Collyweston in Northamptonshire and St Katherine's guild in the neighbouring market town of Stamford in Lincolnshire. The discussion unveils Margaret Beaufort's place at the heart of a vibrant devotional community, whose members, among them a core group of lay and religious townswomen, were united by their geography and shared devotional interests. Ultimately, this article sheds new light on the overlapping spiritual networks of an important market town and the household of a highly influential noblewoman, whilst also demonstrating how Margaret's sponsorship of the society informed her self-fashioning as a pious matriarch of the house of Tudor.
Alcohol, coffee and tea intake and the risk of cognitive deficits: a dose–response meta-analysis
Authors: Ran L. S. , Liu W. H. , Fang Y. Y. , Xu S. B. , Li J. , Luo X. , Pan D. J. , Wang M. H. , Wang W. 
Published: February 2021

Abstract

Aims
Lifestyle interventions are an important and viable approach for preventing cognitive deficits. However, the results of studies on alcohol, coffee and tea consumption in relation to cognitive decline have been divergent, likely due to confounds from dose–response effects. This meta-analysis aimed to find the dose–response relationship between alcohol, coffee or tea consumption and cognitive deficits.

Methods
Prospective cohort studies or nested case-control studies in a cohort investigating the risk factors of cognitive deficits were searched in PubMed, Embase, the Cochrane and Web of Science up to 4th June 2020. Two authors searched the databases and extracted the data independently. We also assessed the quality of the studies with the Newcastle-Ottawa scale. Stata 15.0 software was used to perform model estimation and plot the linear or nonlinear dose–response relationship graphs.

Results
The search identified 29 prospective studies from America, Japan, China and some European countries. The dose–response relationships showed that compared to non-drinkers, low consumption (<11 g/day) of alcohol could reduce the risk of cognitive deficits or only dementias, but there was no significant effect of heavier drinking (>11 g/day). Low consumption of coffee reduced the risk of any cognitive deficit (<2.8 cups/day) or dementia (<2.3 cups/day). Green tea consumption was a significant protective factor for cognitive health (relative risk, 0.94; 95% confidence intervals, 0.92–0.97), with one cup of tea per day brings a 6% reduction in risk of cognitive deficits.

Conclusions
Light consumption of alcohol (<11 g/day) and coffee (<2.8 cups/day) was associated with reduced risk of cognitive deficits. Cognitive benefits of green tea consumption increased with the daily consumption.
Early Warning of the Pacific Decadal Oscillation Phase Transition Using Complex Network Analysis
Authors: Lu Zhenghui , Yuan Naiming , Yang Qing , Ma Zhuguo , Kurths Jürgen 
Published: February 2021

AbstractObtaining an efficient prediction of the Pacific Decadal Oscillation (PDO) phase transition is a worldwide challenge. Here, we employed the climate network analysis to uncover early warning signals prior to a PDO phase transition. This way an examination of cooperative behavior in the PDO region revealed an enhanced signal that propagated from the western Pacific to the northwest coast of North America. The detection of this signal corresponds very well to the time when the upper ocean heat content in the off‐equatorial northwestern tropical Pacific reaches a threshold, in which case a PDO phase transition may be expected with the arising of the next El Ni o/La Ni a event. The objectively detected early warning signal successfully forewarned all the six PDO phase transitions from the 1890–2000, and also underpinned the possible PDO phase transition around 2015, which may be triggered by the strong El Nio event in 2015–2016.
The Application of a Deep Convolutional Generative Adversarial Network on Completing Global TEC Maps
Authors: Chen Jie , Fang Hanxian , Liu Zhendi 
Published: February 2021

AbstractTotal electron content (TEC) map is one of the important ionospheric parameters. The International Global Navigation Satellite System Service (Ionosphere Working Group) provides the combined vertical TEC maps. However, the postprocessing of the IGS TEC maps may cost quite a long time, and it's not easy for the organization to collect the complete data. It is necessary for researchers to figure out a method to complete the global TEC maps efficiently with regard to the problems of lack of data or not available to the standard IGS TEC. With the rapid development of the deep learning methods, the Deep Convolutional Generative Adversarial Network exhibits the great potential in computer vision. In this paper, we propose a new method called Global and Local GAN (GLGAN) based on the DCGAN and apply it on completing the global TEC maps. Different from the traditional GAN, the GLGAN consists of a generator (or called completion network) and two discriminators. The completion network is powerful enough to Extract features of IGS TEC maps to complete the TEC maps. The design of two discriminators enhances the ability of judging the quality of output images, and improves the accuracy of the completion network. After analyzing the results, we find the GLGAN have a better performance in complicate structures during geomagnetic storm time. The success of the GLGAN in completing the TEC maps suggests that the deep learning methods are able to solve many problems regarding to data and images in ionospheric parameters' reconstruction or forecasting.
Bayesian Filtering in Incoherent Scatter Plasma Parameter Fits
Authors: Virtanen Ilkka I. , Tesfaw Habtamu W. , Roininen Lassi , Lasanen Sari , Aikio Anita 
Published: February 2021

AbstractIncoherent scatter (IS) radars are invaluable instruments for ionospheric physics, since they observe altitude profiles of electron density (Ne), electron temperature (Te), ion temperature (Ti) and line‐of‐sight plasma velocity (Vi) from ground. However, the temperatures can be fitted to the observed IS spectra only when the ion composition is known, and resolutions of the fitted plasma parameters are often insufficient for auroral electron precipitation, which requires high resolutions in both range and time. The problem of unknown ion composition has been addressed by means of the full‐profile analysis, which assumes that the plasma parameter profiles are smooth in altitude, or follow some predefined shape. In a similar manner, one could assume smooth time variations, but this option has not been used in IS analysis. We propose a plasma parameter fit technique based on Bayesian filtering, which we have implemented as an additional Bayesian Filtering Module (BAFIM) in the Grand Unified Incoherent Scatter Design and Analysis Package (GUISDAP). BAFIM allows us to control gradients in both time and range directions for each plasma parameter separately. With BAFIM we can fit F1 region ion composition together with Ne, Te, Ti and Vi, and we have reached 4 s/900 m time/range steps in four‐parameter fits of Ne, Te, Ti and Vi in E region observations of auroral electron precipitation.
Airborne Geophysical Imaging of Weak Zones on Iliamna Volcano, Alaska: Implications for Slope Stability
Authors: Peterson Dana E. , Finn Carol A. , Bedrosian Paul A. 
Published: February 2021

AbstractWater‐saturated, hydrothermally altered rocks reduce the strength of volcanic edifices and increase the potential for sector collapses and far‐traveled mass flows of unconsolidated debris. Iliamna Volcano is an andesitic stratovolcano located on the western side of the Cook Inlet, ∼225 km southwest of Anchorage and is a source of repeated avalanches. The widespread snow and ice cover on Iliamna Volcano make surface alteration difficult to identify. However, intense hydrothermal alteration significantly reduces both the electrical resistivity and magnetization of volcanic rock and can therefore be identified with airborne geophysical measurements. We use airborne electromagnetic and magnetic data to map snow and ice thickness and identify underlying alteration zones at Iliamna Volcano, Alaska. Resistivities were calculated to an average depth of >300 m, and a 3‐D susceptibility model extends from the surface to the base of the volcano, about 3,000 m below the summit. Geophysical models image low resistivity (<30 ohm‐m) and low susceptibilities near the summit of Iliamna and below its older vent complex, with the low susceptibilities indicating alteration up to ∼800 m in thickness. Thin conductors (∼50–100 m thick) on the edifice slopes coincide with recorded locations of repeated debris avalanches over the past ∼60 years and are attributed to saturated zones at high elevation. Three‐dimensional slope stability models based upon the geophysically constrained alteration distribution suggest the edifice of Iliamna is unstable and could lead to collapse scars ∼400 m deep near the current and former vent complexes.
Density of Fe‐Ni‐C Liquids at High Pressures and Implications for Liquid Cores of Earth and the Moon
Authors: Zhu Feng , Lai Xiaojing , Wang Jianwei , Amulele George , Kono Yoshio , Shen Guoyin , Jing Zhicheng , Manghnani Murli H. , Williams Quentin , Chen Bin 
Published: February 2021

AbstractThe presence of light elements in the metallic cores of the Earth, the Moon, and other rocky planetary bodies has been widely proposed. Carbon is among the top candidates in light of its high cosmic abundance, siderophile nature, and ubiquity in iron meteorites. It is, however, still controversial whether carbon‐rich core compositional models can account for the seismic velocity observations within the Earth and lunar cores. Here, we report the density and elasticity of Fe90Ni10‐3 wt.% C and Fe90Ni10‐5 wt.% C liquid alloys using synchrotron‐based X‐ray absorption experiments and first‐principles molecular dynamics simulations. Our results show that alloying of 3 wt.% and 5 wt.% C lowers the density of Fe90Ni10 liquid by ∼2.9–3.1% at 2 GPa, and ∼3.4–3.6% at 9 GPa. More intriguingly, our experiments and simulations both demonstrate that the bulk moduli of the Fe‐Ni‐C liquids are similar to or slightly higher than those of Fe‐Ni liquids. Thus, the calculated compressional velocities (vp) of Fe‐Ni‐C liquids are higher than that of pure Fe‐Ni alloy, promoting carbon as a possible candidate to explain the elevated vp in the Earth's outer core. However, the values and slopes of both density and vp of the studied two Fe‐Ni‐C liquids do not match the outer core seismic models, suggesting that carbon may not be the sole principal light element in Earth's outer core. The high vp of Fe‐Ni‐C liquids does not match the presumptive vp of the lunar outer core well, indicating that carbon is less likely to be its dominant light element.
Retrieval of Ocean Wave Heights From Spaceborne SAR in the Arctic Ocean With a Neural Network
Authors: Wu Ke , Li Xiao‐Ming , Huang Bingqing 
Published: February 2021

AbstractThe twin Sentinel‐1 (S1) satellites have been extensively acquiring synthetic aperture radar (SAR) data in the Arctic, providing the unique opportunity to obtain ocean dynamic parameters with both high spatial resolution and wide swath coverage in the Arctic Ocean. In this study, we proposed a method for retrieving the ocean significant wave height (SWH) from S1 SAR data in horizontal‐horizontal (HH) polarization based on a backpropagation neural network (BPNN). A total of 4,273 scenes from S1 extra‐wide swath mode data acquired in the Arctic were collocated with data from four radar altimeters (RA), yielding 126,128 collocated data pairs. These data were separated into training and testing data sets to develop the BPNN model for retrieving SWH. Comparing the S1 retrieved SWH using the testing data set with the RA SWH yielded a bias of 0.17 m, a root‐mean‐square error of 0.71 m and a scatter index (SI) of 23.05% for SWH less than 10 m. The S1 retrieved SWH was further compared with the CFOSAT/SWIM data acquired in the Arctic between August 2019 and May 2020, which suggests that the SWIM has different performances on wave measurements at different beams.