bluuebunny/crossref_metadata_2025_split huggingface dataset:
Between artificial intelligence and customer experience: a literature review on the intersection
Authors: Peruchini Melise , da Silva Gustavo Modena , Teixeira Julio Monteiro 
Published: January 2024

AbstractThis paper is a literature review of the intersection field between Artificial Intelligence (AI) and Customer Experience (CX). We analyzed and synthesized the most recent and prominent literature on the subject, providing an overview of the state of the art, through articles found in the Scopus database. Among the main findings, it is noteworthy that this intersection appears as an interdisciplinary topic of interest in the fields of Computer Science, Business and Management, and Engineering. Additionally, studies often examine conversational agents such as chatbots and voicebots, as well as machine learning prediction models and recommendation systems as a way to improve the Customer Experience. The most common sectors in the review are tourism, banking and e-commerce. Other segments and technologies appear less and may be underrepresented, thus a scope for future research agenda. Despite the existing literature, it is observed that there is still substantial space for expansion and exploration, especially considering the emergence of new generative Artificial Intelligence models.
Propagating speedups during quiescence escalate to the 2020–2021 surge of Sít’ Kusá, southeast Alaska
Authors: Liu Jukes , Enderlin Ellyn M. , Bartholomaus Timothy C. , Terleth Yoram , Mikesell Thomas Dylan , Beaud Flavien 
Published: January 2024

Abstract
We use satellite image processing techniques to measure surface elevation and velocity changes on a temperate surging glacier, Sít’ Kusá, throughout its entire 2013–2021 surge cycle. We present detailed records of its dynamic changes during quiescence (2013–2019) and its surge progression (2020–2021). Throughout quiescence, we observe order-of-magnitude speedups that propagate down-glacier seasonally from the glacier's upper northern tributary, above a steep icefall, into the reservoir zone for the surging portion of the glacier. The speedups initiate in fall and gradually accelerate through winter until they peak in late spring, ~1 − 2 months after the onset of melt. Propagation distance of the speedups controls the distribution of mass accumulation in the reservoir zone prior to the surge. Furthermore, the intensity and propagation distance of each year's speedup is correlated with the positive degree day sum from the preceding melt season, suggesting that winter melt storage drives the seasonal speedups. We demonstrate that the speedups are kinematically similar to the 2020–2021 surge, differing mainly in that the surge propagates past the dynamic balance line at the lower limit of the reservoir zone, likely triggered by the exceedance of a tipping point in mass accumulation and basal enthalpy in the reservoir zone.
Revisiting the punitiveness of deportation
Authors: Spalding Amanda 
Published: January 2024

AbstractImmigration measures such as deportation are currently not regarded as punitive and there has been little exploration of this from a legal perspective. This paper will consider this issue in depth, covering little discussed case law from the European Court of Human Rights. It will also explore how this legal position on deportation does not reflect the findings of other disciplines such as criminology and sociology on how immigration measures are used and experienced as punitive. This paper will build on existing literature by demonstrating the significance of a recent development in UK law to this debate. Section 47 of the Nationality and Borders Act 2022 (NBA 2022) introduced a ‘stop the clock’ provision into the Early Removal Scheme for foreign national prisoners. This new provision may prompt the judiciary to revisit the question of whether deportation is punitive in some contexts.
The depletion of star-forming gas by AGN activity in radio sources
Authors: Curran S. J. 
Published: January 2024

AbstractCold, neutral interstellar gas, the reservoir for star formation, is traced through the absorption of the 21-cm continuum radiation by neutral hydrogen (Hi). Although detected in one hundred cases in the host galaxies of distant radio sources, only recently have column densities approaching the maximum value observed in Lyman-$\alpha$absorption systems ($N_{{\textrm{H}\,\scriptsize{\textrm{I}}}}\sim 10^{22}$$\textrm{cm}^{-2}$) been found. Here, we explore the implications these have for the hypothesis that the detection rate of Hiabsorption is dominated by photo-ionisation from the active galactic nucleus (AGN). We find, with the addition all of the current searches for Hiabsorption at$z\geq0.1$, a strong correlation between the Hiabsorption strength and the ionising photon rate, with the maximum value at which Hiis detected remaining close to the theoretical value in which all of the neutral gas would be ionised in a large spiral galaxy ($Q_{{\textrm{H}\,\scriptsize{\textrm{I}}}} = 2.9\times10^{56}$ionising photons s$^{-1}$). We also rule out other effects (excitation by the radio continuum and changing gas properties) as the dominant cause for the decrease in the detection rate with redshift. Furthermore, from the maximum theoretical column density, we find that the five high column density systems have spin temperatures close to those of the Milky Way ($T_{\textrm{spin}} \lesssim 300$K), whereas, from our model of a gaseous galactic disc, the Hidetection at$Q_{{\textrm{H}\,\scriptsize{\textrm{I}}}} =2.9\times10^{56}$ s$^{-1}$yields$T_{\textrm{spin}}\sim10\,000$K, consistent with the gas being highly ionised.
Le Bloc québécois et la souveraineté : une analyse des communiqués de presse de 2002 à 2021
Authors: Duval Dominic , Villeneuve-Siconnelly Katryne 
Published: January 2024

RésuméComme l'illustrent Bélanger et Nadeau (2009), l'axe identitaire traditionnel au Québec apparait de moins en moins prédominant sur la scène politique québécoise. Cette situation impose l'adoption d'une stratégie différente de la part des divers partis dits souverainistes. Comment se sont articulées ces tentatives de repositionnement au sein du Bloc québécois? Afin d'explorer cette question, nous avons amassé plus de 7500 communiqués de presse diffusés par le parti entre 2002 et 2021. À l'aide de méthodes d'analyse automatisées et une approche deLatent Semantic Scalingdéveloppée par Watanabe (2020), nous illustrons et discutons de la prédominance de l'enjeu souverainiste à travers cette période, ainsi que le ton du parti quant à cet enjeu. Les résultats indiquent que les élections et les résultats de celles-ci jouent un rôle crucial dans la stratégie communicationnelle du Bloc québécois à l’égard de la souveraineté. De façon plus générale, nous observons certaines fluctuations importantes de l'attention accordée à cet enjeu et des variations importantes quant au cadrage de cet enjeu autour des élections. Cette note de recherche apporte un éclairage méthodologique nouveau quant aux théories entourant le réalignement politique en cours au Québec et la saillance qu'occupe le clivage de la souveraineté.
Effects of natamycin, hexanoic acid and Lactobacillus plantarum on fermentation, aerobic stability and in vitro digestibility of an ensiled total mixed ration containing water bamboo sheath leaves
Authors: Li Xinbao , Liu Haopeng , Dai Tongtong , Dong Dong , Xu Guofeng , Jia Yushan , Shao Tao 
Published: January 2024

AbstractThe work aimed to evaluate the effect of lactic acid bacteria, natamycin and hexanoic acid on the fermentation quality, aerobic stability and in vitro digestibility of total mixed ration (TMR) silages containing water bamboo sheath leaves. The treatments were as follows: (1) no additives (control, C), (2) lactic acid bacteria (L), (3) natamycin (N), (4) hexanoic acid (H), (5) lactic acid bacteria + natamycin (LN), (6) lactic acid bacteria + hexanoic acid (LH). Silos were opened and silages were evaluated to assess fermentation quality, aerobic stability and in vitro digestibility. All TMR silages were well-preserved as indicated by dominant lactic acid content, low ammonia nitrogen/total nitrogen, trace propionic acid and negligible butyric acid contents. All additives improved the fermentation quality and in vitro digestibility, evidenced by higher lactic acid/acetic acid ratio, lactic acid, acetic acid, water-soluble carbohydrate contents and lactic acid bacteria count, and lower pH, aerobic bacteria and yeast counts. The LN had the highest lactic acid, acetic acid, lactic acid/acetic acid ratio, in vitro gas production and in vitro digestibility. During aerobic exposure, the LN silage had the highest lactic acid and acetic acid contents, and the lowest pH among all TMR silages. The LN and LH prolonged aerobic stability, reaching 85.5 and 81.5 h, respectively. The LN is recommended to improve the fermentation quality, aerobic stability and in vitro digestibility of TMR prepared with water bamboo sheath leaves.
Household Financial Decision-Making After Natural Disasters: Evidence from Hurricane Harvey
Authors: del Valle Alejandro , Scharlemann Therese , Shore Stephen 
Published: January 2024

AbstractWe study household credit responses to Hurricane Harvey using new, geographically granular data on credit cards, mortgages, and flooding. Estimates from a differences-in-differences design that exploits the flooding gradient show that affected households only borrow at low-interest rates, often using promotional (zero interest) cards and that they quickly pay down balances. We also document that take-up of forbearance (borrowing by missing mortgage payments without penalty) increases with flooding. These results are attenuated in floodplains, particularly in structures subject by code to physical hardening. Our results indicate that credit acts as a substitute for the lack of physical hardening.
Comparative advantage, specialized viticulture, and the economic development of Gallia Narbonensis
Authors: Rice Candace M. 
Published: January 2024

AbstractThis paper explores the processes of specialized viticulture in the province of Gallia Narbonensis over the first three centuries CE and brings this evidence to bear on broader economic questions, particularly as they relate to the effects of connectivity and globalization on Roman economic development. Evidence from small farms to sprawling villas suggests that specialized production stretched across multiple strata of society in Narbonensis, from so-called peasants to the wealthiest elites. The existence of specialized agricultural production at the scale documented in Narbonensis required significant demand, well-connected and integrated markets, sustained trade, and an awareness of these economic factors by the residents of the province. The evidence presented here demonstrates that the residents of Narbonensis recognized that they were part of an economic environment in which high levels of connectivity and integrated markets allowed them to pursue more profitable production strategies and that they pursued these opportunities.
RT-SCNNs: real-time spiking convolutional neural networks for a novel hand gesture recognition using time-domain mm-wave radar data
Authors: Shaaban Ahmed , Strobel Maximilian , Furtner Wolfgang , Weigel Robert , Lurz Fabian 
Published: January 2024

AbstractThis study introduces a novel approach to radar-based hand gesture recognition (HGR), addressing the challenges of energy efficiency and reliability by employing real-time gesture recognition at the frame level. Our solution bypasses the computationally expensive preprocessing steps, such as 2D fast Fourier transforms (FFTs), traditionally employed for range-Doppler information generation. Instead, we capitalize on time-domain radar data and harness the energy-efficient capabilities of spiking neural networks (SNNs) models, recognized for their sparsity and spikes-based communication, thus optimizing the overall energy efficiency of our proposed solution. Experimental results affirm the effectiveness of our approach, showcasing significant classification accuracy on the test dataset, with peak performance achieving a mean accuracy of 99.75%. To further validate the reliability of our solution, individuals who have not participated in the dataset collection conduct real-time live testing, demonstrating the consistency of our theoretical findings. Real-time inference reveals a substantial degree of spikes sparsity, ranging from 75% to 97%, depending on the presence or absence of a performed gesture. By eliminating the computational burden of preprocessing steps and leveraging the power of (SNNs), our solution presents a promising alternative that enhances the performance and usability of radar-based (HGR) systems.
Seaweed as a Resilient Food Solution After a Nuclear War
Authors: Jehn Florian Ulrich , Dingal Farrah Jasmine , Mill Aron , Harrison Cheryl , Ilin Ekaterina , Roleda Michael Y. , James Scott C. , Denkenberger David 
Published: January 2024

AbstractAbrupt sunlight reduction scenarios such as a nuclear winter caused by the burning of cities in a nuclear war, an asteroid/comet impact or an eruption of a large volcano inject large amounts of particles in the atmosphere, which limit sunlight. This could decimate agriculture as it is practiced today. We therefore need resilient food sources for such an event. One promising candidate is seaweed, as it can grow quickly in a wide range of environmental conditions. To explore the feasibility of seaweed after nuclear war, we simulate the growth of seaweed on a global scale using an empirical model based on Gracilaria tikvahiae forced by nuclear winter climate simulations. We assess how quickly global seaweed production could be scaled to provide a significant fraction of global food demand. We find seaweed can be grown in tropical oceans, even after nuclear war. The simulated growth is high enough to allow a scale up to an equivalent of 45% of the global human food demand (spread among food, animal feed, and biofuels) in around 9–14 months, while only using a small fraction of the global ocean area. The main limiting factor being the speed at which new seaweed farms can be built. The results also show that the growth of seaweed increases with the severity of the nuclear war, as more nutrients become available due to increased vertical mixing. This means that seaweed has the potential to be a viable resilient food source for abrupt sunlight reduction scenarios.
Probabilistic Assessment of Global Drought Recovery and Its Response to Precipitation Changes
Authors: Zhang Limin , Yuan Fei , He Xiaogang 
Published: January 2024

AbstractAccurate assessment of drought recovery probability is crucial for proactive strategies in cost‐effective water resource allocation, resilient agriculture management, and sustainable energy planning. However, there has been a notable gap in assessing drought recovery from a probabilistic and multi‐variate perspective. Here, we develop a Vine Copula‐based framework to quantify global drought recovery probability and explore its elasticity to precipitation changes. Compared to the historical period (1951–1983), 51% of global land has become increasingly difficult to recover from extreme droughts over 1984–2016 within 8–14 days during growing seasons. Furthermore, the response of global drought recovery to precipitation changes depends on the background climate and varies asymmetrically between wet and dry conditions. Under an extremely wet climate, a 1% historical precipitation increase yields a mere 0.5% increase in global median drought recovery probability during June‐July‐August, but can lead to a pronounced 6.6% increase if climate gets extremely drier.
Integration of a Deep‐Learning‐Based Fire Model Into a Global Land Surface Model
Authors: Son Rackhun , Stacke Tobias , Gayler Veronika , Nabel Julia E. M. S. , Schnur Reiner , Alonso Lazaro , Requena‐Mesa Christian , Winkler Alexander J. , Hantson Stijn , Zaehle Sönke , Weber Ulrich , Carvalhais Nuno 
Published: January 2024

AbstractFire is a crucial factor in terrestrial ecosystems playing a role in disturbance for vegetation dynamics. Process‐based fire models quantify fire disturbance effects in stand‐alone dynamic global vegetation models (DGVMs) and their advances have incorporated both descriptions of natural processes and anthropogenic drivers. Nevertheless, these models show limited skill in modeling fire events at the global scale, due to stochastic characteristics of fire occurrence and behavior as well as the limits in empirical parameterizations in process‐based models. As an alternative, machine learning has shown the capability of providing robust diagnostics of fire regimes. Here, we develop a deep‐learning‐based fire model (DL‐fire) to estimate daily burnt area fraction at the global scale and couple it within JSBACH4, the land surface model used in the ICON‐ESM. The stand‐alone DL‐fire model forced with meteorological, terrestrial and socio‐economic variables is able to simulate global total burnt area, showing 0.8 of monthly correlation (rm) with GFED4 during the evaluation period (2011–2015). The performance remains similar with the hybrid modeling approach JSB4‐DL‐fire (rm = 0.79) outperforming the currently used uncalibrated standard fire model in JSBACH4 (rm = −0.07). We further quantify the importance of each predictor by applying layer‐wise relevance propagation (LRP). Overall, land properties, such as fuel amount and water content in soil layers, stand out as the major factors determining burnt fraction in DL‐fire, paralleled by meteorological conditions over tropical and high latitude regions. Our study demonstrates the potential of hybrid modeling in advancing fire prediction in ESMs by integrating deep learning approaches in physics‐based dynamical models.
Causes of Reduced Climate Sensitivity in E3SM From Version 1 to Version 2
Authors: Qin Yi , Zheng Xue , Klein Stephen A. , Zelinka Mark D. , Ma Po‐Lun , Golaz Jean‐Christophe , Xie Shaocheng 
Published: January 2024

AbstractThe effective climate sensitivity in the Department of Energy's Energy Exascale Earth System Model (E3SM) has decreased from 5.3 K in version 1 to 4.0 K in version 2. This reduction is mainly due to a weaker positive cloud feedback that leads to a stronger negative radiative feedback. Present‐day atmosphere‐only experiments with uniform 4 K sea surface temperature warming are used to separate the contributions of individual model modifications to the reduced cloud feedback. We find that the reduced cloud feedback is mostly driven by changes over the tropical marine low cloud regime, mainly related to a new trigger function for the deep convection scheme and modifications in the cloud microphysics scheme. The new trigger function helps weaken the low cloud reduction by increasing the cloud water detrainment at low levels from deep convection under warming. Changes to the formula of autoconversion rate from liquid to rain and an introduced minimum cloud droplet number concentration threshold in cloud microphysical calculations help sustain clouds against dissipation by suppressing precipitation generation with warming. In the midlatitudes, the increased Wegener‐Bergeron‐Findeisen (WBF) efficiency strongly reduces present‐day liquid water and leads to a stronger negative cloud optical depth feedback. The reduced trade cumulus cloud feedback in v2 is closer to estimates from recent observational and large‐eddy modeling studies but might not be due to the right physical reasons. The reduced mid‐latitude cloud feedback may be more plausible because more realistic present‐day mixed‐phase clouds are produced through the change in the WBF efficiency.
Investigation of Ionospheric Small‐Scale Plasma Structures Associated With Particle Precipitation
Authors: Enengl F. , Spogli L. , Kotova D. , Jin Y. , Oksavik K. , Partamies N. , Miloch W. J. 
Published: January 2024

AbstractWe investigate the role of auroral particle precipitation in small‐scale (below hundreds of meters) plasma structuring in the auroral ionosphere over the Arctic. In this scope, we analyze together data recorded by an Ionospheric Scintillation Monitor Receiver (ISMR) of Global Navigation Satellite System (GNSS) signals and by an All‐Sky Imager located in Longyearbyen, Svalbard (Norway). We leverage on the raw GNSS samples provided at 50 Hz by the ISMR to evaluate amplitude and phase scintillation indices at 1 s time resolution and the Ionosphere‐Free Linear Combination at 20 ms time resolution. The simultaneous use of the 1 s GNSS‐based scintillation indices allows identifying the scale size of the irregularities involved in plasma structuring in the range of small (up to few hundreds of meters) and medium‐scale size ranges (up to few kilometers) for GNSS frequencies and observational geometry. Additionally, they allow identifying the diffractive and refractive nature of fluctuations on the recorded GNSS signals. Six strong auroral events and their effects on plasma structuring are studied. Plasma structuring down to scales of hundreds of meters is seen when strong gradients in auroral emissions at 557.7 nm cross the line of sight between the GNSS satellite and receiver. Local magnetic field measurements confirm small‐scale structuring processes coinciding with intensification of ionospheric currents. Since 557.7 nm emissions primarily originate from the ionospheric E‐region, plasma instabilities from particle precipitation at E‐region altitudes are considered to be responsible for the signatures of small‐scale plasma structuring highlighted in the GNSS scintillation data.
Deep Learning‐Based Regional Ionospheric Total Electron Content Prediction—Long Short‐Term Memory (LSTM) and Convolutional LSTM Approach
Authors: Jeong Se‐Heon , Lee Woo Kyoung , Kil Hyosub , Jang Soojeong , Kim Jeong‐Heon , Kwak Young‐Sil 
Published: January 2024

AbstractThis study evaluates the performance of deep learning approach in the prediction of the ionospheric total electron content (TEC) during magnetically quiet periods. Two deep learning techniques, long short‐term memory (LSTM) and convolutional LSTM (ConvLSTM), are employed to predict TEC values 24 hr ahead in the vicinity of the Korean Peninsula (26.5°–40°N, 121°–134.5°E). The LSTM method predicts TEC at a single point based on time series of data at that point, whereas the ConvLSTM method simultaneously predicts TEC values at multiple points using spatiotemporal distribution of TEC. Both the LSTM and ConvLSTM models are trained using the complete regional TEC maps reconstructed by applying the Deep Convolutional Generative Adversarial Network–Poisson Blending (DCGAN‐PB) method to observed TEC data. The training period spans from 2002 to 2018, and the model performance is evaluated using 2019 data. Our results show that the ConvLSTM method outperforms the LSTM method, generating more reliable TEC maps with smaller root mean square errors when compared to the ground truth (DCGAN‐PB TEC maps). This outcome indicates that deep learning models can improve the prediction accuracy of TEC at a specific point by taking into account spatial information of TEC. We conclude that ConvLSTM is a reliable and efficient approach for the prompt ionospheric prediction.