bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is A Star A Document? Catalogued Students and Learning Analytics
Authors: Gourlay Lesley 
Published: June 2024

AbstractThe media theorist Suzanne Briet proposed that through the recording of information about entities in the world, these entities are not only documented, but they themselves are rendered into documents. She asks us to consider the case of an antelope which is captured, brought to Europe, put in a zoo, and examined by experts and members of the public. She argues that the zoo is effectively a laboratory in which the antelope is analysed, displayed, and therefore itself becomes a document due to these material analytical assemblages around it. In this paper, I propose that Briet’s notion of the document can be applied to data visualisation used in learning analytics, and its effect on students. With reference to a philosophical discussion of the status of data visualisation in terms of Kant’s theory of the sublime versus Deleuze’s notion of the diagram, I argue that a learning analytics dashboard designed for individual student use not only renders the student into a document but also imbricates the student in a co-constitutive form of relationality with that document, which explicitly encourages and rewards a very particular form of action in the world in relation to the learning management system. I conclude that this has real-world effects not only in this inculcation, but in the reification of a particular neoliberal ideology of student engagement as a performance of observable, traceable, self-optimisation in a highly individualised educational worldview.
Influence of Microalgae Biomasses Retrieved from Phycoremediation of Wastewaters on Yield of Lettuce, Soil Health, and Nitrogen Environmental Fate
Authors: La Bella Emanuele , Baglieri Andrea , Fragalà Ferdinando , Saccone Rossella , Salvagno Erika , Terrazzino Sergio , Puglisi Ivana 
Published: June 2024

AbstractThe main purpose of this study was to investigate the effects of three microalgae strains, Chlorella vulgaris, Scenedesmus quadricauda, and Klebsormidium sp. K39, on the enhancement of lettuce yield and soil fertility and in mitigation of nitrogen losses in groundwater, focusing on some aspects of the complex soil-plant system. The experimental trials were carried in pots, and involved the application of microalgae cells at two different concentrations (50 and 500 mg kg− 1 of soil), alone or in combination with standard mineral fertilization. The yield, main morpho-biometric parameters, and protein content of lettuce seedlings, as well as the activities of key enzymes involved in the nitrogen pathway (nitrate reductase, glutamine synthase, and glutamate synthetase) at both root and shoot levels, were monitored and the results were compared to not-inoculated control plants. The nitrate leached due to over irrigation was also evaluated. Furthermore, even the effects of microalgae biostimulants on soil biochemical activity were analysed by monitoring fluorescein diacetate hydrolysis, dehydrogenase, acid and alkaline phosphomonoesterase, and urease activities. All treatments significantly improved lettuce growth, especially when combined with mineral fertilization, providing comparable levels to the control plants treated only with microalgae cells. Furthermore, microalgae treatments positively influenced soil biological activities, as evidenced by increased of the potential biochemical index of soil fertility (Mw). In conclusion, microalgae soil treatments may be considered as a viable strategy to assist growers in reducing the use of mineral fertilizers, with a view to improve plant growth as well as soil biological activity.
You are How You Eat: Foraging Behavior as a Potential Novel Marker of Rat Affective State
Authors: Neville Vikki , Finnegan Emily , Paul Elizabeth S. , Davidson Molly , Dayan Peter , Mendl Michael 
Published: June 2024

AbstractEffective and safe foraging requires animals to behave according to the expectations they have about the rewards, threats, and costs in their environment. Since these factors are thought to be reflected in the animals’ affective states, we can use foraging behavior as a window into those states. In this study, rats completed a foraging task in which they had repeatedly to decide whether to continue to harvest a food source despite increasing time costs, or to forgo food to switch to a different food source. Rats completed this task across two experiments using manipulations designed to induce both positive and negative, and shorter- and longer- term changes in affective state: removal and return of enrichment (Experiment 1), implementation and reversal of an unpredictable housing treatment (Experiment 1), and delivery of rewards (tickling or sucrose) and punishers (air-puff or back-handling) immediately prior to testing (Experiment 2). In Experiment 1, rats completed fewer trials and were more prone to switching between troughs when housed in standard, compared to enriched, housing conditions. In Experiment 2, rats completed more trials following pre-test tickling compared to pre-test sucrose delivery. However, we also found that they were prone to disengaging from the task, suggesting they were really choosing between three options: ‘harvest’, ‘switch’, or ‘not work’. This limits the straightforward interpretation of the results. At present, foraging behavior within the context of this task cannot reliably be used as an indicator of an affective state in animals.
Self-Provisioning Infrastructures for the Next Generation Serverless Computing
Authors: Nastic Stefan 
Published: June 2024

AbstractServerless computing has ushered in a transformative paradigm, with a promise to alleviate developers from the intricacies of infrastructure management. However, current serverless platforms predominantly offer only serverless compute capabilities. As a consequence, the application developers are once again tasked to explicitly provision and manage the backend services (BaaS), such as object stores or API gateways, the infrastructure, and the configuration models. This violates the main promise of serverless computing and erases much of the practical benefits of the serverless paradigm. It also introduces the challenges of managing the application execution environment, which includes maintaining provisioning and deployment scripts, configuring and managing access permissions, and scaling the services during runtime. To address these challenges, in this paper we introduce a novel paradigm for the next generation of serverless computing, called self-provisioning infrastructure. The self-provisioning infrastructure is an infrastructure that is capable to automatically and autonomously (with zero-configuration and zero-touch) provision serverless functions, their infrastructure, and their supporting BaaS services. To achieve this vision, we introduce novel design principles, models, and mechanisms that are formalized vianovel programming, function, and system models. With this novel paradigm, we intend to fortify the core design principles of serverless computing but also extend themto the entire application execution environment. By doing so, we aim to enable the next-generation serverless computing in the Edge-Cloud continuum.
Sample size calculation in biomedical, clinical and biological sciences research
Authors: Sadiq Idris Zubairu , Usman Abubakar , Muhammad Aliyu , Ahmad Kabiru Haliru 
Published: June 2024

Abstract
Sample size determination is a critical aspect of biomedical research, as it dictates the number of samples needed for a successful experiment that can yield generalizable results to the broader population. This paper outlines the methodology for calculating sample sizes in various categories of biomedical and clinical research, encompassing cross-sectional surveys, comparative studies, case–control studies, cohort studies, and animal studies. Detailed examples are provided for each category. The determination of an appropriate sample size holds significant importance from scientific, ethical, and resource allocation perspectives. It is noteworthy that research outcomes are often directly influenced by the accuracy of sample size calculations. A robust sample size calculation serves as a cornerstone for researchers, enabling them to draw precise inferences with a high level of precision across a spectrum of biomedical and clinical investigations.
Effect of hypnosis versus mindfulness on self-defined treatment goals and sleep following acquired brain injury: a randomized actively controlled trial
Authors: Kvamme Timo L. , Lindeløv Jonas Kristoffer , Thomsen Kristine Rømer , Overgaard Rikke , Overgaard Morten 
Published: June 2024

Abstract
Introduction
Cognitive rehabilitation for brain injury using hypnosis has received little attention.

Methods
Here, we report on self-defined treatment goals and sleep-related outcomes from a randomized actively controlled trial of 49 patients with chronic cognitive sequelae following acquired brain injury. Patients were randomized to two groups, who initially received hypnotic suggestions either from a classical hypnosis tradition (“targeted”) or from a mindfulness tradition (“non-targeted”). Patients set self-defined goals for their everyday lives.

Results
After eight sessions, patients reported outcomes (PROs) indicated large improvements with “same” (13%), “better” (44%), “much better” (18%), or “not a problem anymore” (25%). The reported “not a problem anymore” was exclusively reported following hypnosis, not mindfulness. After a 7-week follow-up period both groups experienced a decrease in their need for sleep (~ 55 min/day). Exploratory factor analysis showed that only improvement on objective but not subjective measures (e.g. Working Memory Index, Trail Making Test, and the European Brain Injury Questionnaire scored by a relative) reflected a latent improvement factor. This indicates that subjective reports following hypnotic suggestions should be interpreted cautiously.

Conclusion
Based on our findings and converging evidence, we conclude that hypnosis is a promising method in cognitive neurorehabilitation following acquired brain injury, although further high-quality randomized controlled trials are required.
Applying Weighted Salinity Stratification to Rapid Intensification Prediction of Tropical Cyclone With Machine Learning
Authors: Yang Wen , Huang Xiaogang , Fei Jianfang , Ding Juli , Cheng Xiaoping 
Published: June 2024

AbstractTropical cyclone (TC) intensification is influenced by environmental conditions, inner‐core dynamics, and interactions with upper‐ocean layers. Rapid intensification (RI) is a significant threat that is difficult to predict, prompting multiple institutions to collaborate. However, the accuracy still needs further improvements. It is well‐known that a warm upper ocean is conducive to RI, but the role of salinity stratification in this process is not well understood, particularly under different TC translation speeds. This study reveals that rapidly intensifying TCs are related to large salinity stratification, especially when TC moves slowly. To develop a predictive model, several machine learning (ML) algorithms are used, with the most appropriate parameters and weights for each algorithm being determined. Our final ML model, which incorporates salinity stratification as a predictor and TC translation speed as a weight parameter, demonstrates superior performance across various predictive metrics, including the probability of detection (POD), false alarm ratio (FAR), and Peirce Skill Score (PSS) over the Western North Pacific during 2004–2022 compared to the model without these two factors. The most significant enhancement is observed for intense RI episodes. The improvements are up to 14% for both in POD; 7% and 13% in FAR; and 19% and 16% in PSS for 12.75 and 15.3 m s−1 RI thresholds, respectively. These results highlight the importance of including salinity stratification as a new predictor and TC translation speed as a weighted parameter using ML techniques in RI prediction models.
Role of Surface Energy Fluxes in Urban Overheating Under Buoyancy‐Driven Atmospheric Conditions
Authors: Back Yannick , Bach Peter M. , Santamouris Mattheos , Rauch Wolfgang , Kleidorfer Manfred 
Published: June 2024

AbstractUrbanization alters land surface properties in absorbing, reflecting and emitting radiation as well as infiltrating, evaporating and storing water. This consequently modifies surface energy and water fluxes and, thus, urban climates. Weak synoptic flow, clear sky conditions and higher surface temperatures in cities compared to their rural surroundings create a buoyancy‐driven atmospheric circulation, in which surface energy fluxes become the main determinants of urban daytime overheating. Here, we demonstrate the role of surface energy fluxes for warming and cooling processes in the urban canopy layer under buoyancy‐driven atmospheric conditions. We improve and apply an integrated CFD‐GIS modeling approach to provide a detailed analysis of fine‐scale land‐atmosphere interactions and assess the surfaces' profound implications on energy and water exchange. We show that variations in the ratios of the surface energy fluxes to the net radiation can be separated from meteorological conditions (wind speed, air temperature and incoming solar radiation) and emissivity values, varying explicitly with changes in land surface type and water availability for vegetated areas. Based on the energy flux ratios, we introduce an approach to assess the surface‐induced warming and cooling effect and its contribution to urban overheating in the urban canopy layer, under buoyancy‐driven atmospheric conditions, directly applicable to strategic urban planning for climate change adaptation. Independent of meteorological conditions, this approach can be used to evaluate different surface materials (both natural and artificial) and climate adaptation measures, such as urban nature‐based solutions and blue‐green infrastructures, and to monitor changes in the energy and water balance.
Catchment Properties Shape Seasonal Variation in Groundwater‐Surface Water Interaction—Geogenic Silica as a Proxy for Hydrological Turnover Induced Mixing
Authors: Bäthke Lars , Schuetz Tobias 
Published: June 2024

AbstractThe cumulative and bidirectional groundwater‐surface water (GW‐SW) interaction along a stream is defined as hydrological turnover (HT) influencing solute transport and source water composition. However, HT proves to be highly variable, producing spatial exchange patterns influenced by local groundwater, geology, and topography. Hence, identifying factors controlling HT poses a challenge. We studied spatiotemporal HT variability at two reaches of a third order tributary of the river Mosel, Germany. Additionally, we sampled for silica concentrations in the stream and in the near‐stream groundwater. Thus, creating snapshots of the boundary layer between ground‐ and surface water where HT occurs, driven by mixing processes in the hyporheic zone. We utilize an enhanced hydrograph separation method, unveiling reach differences in storage drainage based on aquifer dimension and connectivity. The data shows a site‐specific negative correlation of HT with discharge, while hydraulic gradients correlate with HT only at the reach with faster catchment drainage behavior. Examining silica concentrations between stream and wells shows that silica variation increases significantly with the decrease of HT under low flow conditions at the slower draining reach. At the fast draining reach this relationship is seasonal. In Summary, our results show that stream discharge shapes the influence of HT on solute transport. Yet, reach drainage behavior shapes seasonal states of groundwater storages and can be an additional control of HT. Hence, concentration change of pollutants could be masked by HT. Thus, our findings contribute to the understanding of HT variability along streams and its ability of influencing physico‐chemical stream water composition.
Thermochemical Structure of the Superior Craton and Environs: Implications for the Evolution and Preservation of Cratonic Lithosphere
Authors: Dave Riddhi , Darbyshire Fiona , Afonso Juan Carlos , Fomin I. 
Published: June 2024

AbstractThe Archean Superior craton was formed by the assemblage of continental and oceanic terranes at ∼2.6 Ga. The craton is surrounded by multiple Proterozoic mobile belts, including the Paleoproterozoic Trans‐Hudson Orogen which brought together the Superior and Rae/Hearne cratons at ∼1.9–1.8 Ga. Despite numerous studies on Precambrian lithospheric formation and evolution, the deep thermochemical structure of the Superior craton and its surroundings remains poorly understood. Here we investigate the upper mantle beneath the region from the surface to 400 km depth by jointly inverting Rayleigh wave phase velocity dispersion data, elevation, geoid height and surface heat flow, using a probabilistic inversion to obtain a (pseudo‐)3D model of composition, density and temperature. The lithospheric structure is dominated by thick cratonic roots (>300 km) beneath the eastern and western arms of the Superior craton, with a chemically depleted signature (Mg# > 92.5), consistent with independent results from mantle xenoliths. Beneath the surrounding Proterozoic and Phanerozoic orogens, the Mid‐continent Rift and Hudson Strait, we observe a relatively thinner lithosphere and more fertile composition, indicating that these regions have undergone lithospheric modification and erosion. Our model supports the hypothesis that the core of the Superior craton is well‐preserved and has evaded lithospheric destruction and refertilization. We propose three factors playing a critical role in the craton's stability: (a) the presence of a mid‐lithospheric discontinuity, (b) the correct isopycnic conditions to sustain a strength contrast between the craton and the surrounding mantle, and (c) the presence of weaker mobile belts around the craton.
Repacking in Compacting Mushes at Intermediate Melt Fractions: Constraints From Numerical Modeling and Phase Separation Experiments on Granular Media
Authors: Florez Darien , Huber Christian , Hoyos Susana , Pec Matej , Parmentier E. M. , Connolly James A. D. , Hirth Greg 
Published: June 2024

AbstractBefore large volumes of crystal poor rhyolites are mobilized as melt, they are extracted through the reduction of pore space within their corresponding crystal matrix (compaction). Petrological and mechanical models suggest that a significant fraction of this process occurs at intermediate melt fractions (ca. 0.3–0.6). The timescales associated with such extraction processes have important ramifications for volcanic hazards. However, it remains unclear how melt is redistributed at the grain‐scale and whether using continuum scale models for compaction is suitable to estimate extraction timescales at these melt fractions. To explore these issues, we develop and apply a two‐phase continuum model of compaction to two suites of analog phase separation experiments—one conducted at low and the other at high temperatures, T, and pressures, P. We characterize the ability of the crystal matrix to resist porosity change using parameterizations of granular phenomena and find that repacking explains both data sets well. A transition between compaction by repacking to melt‐enhanced grain boundary diffusion‐controlled creep near the maximum packing fraction of the mush may explain the difference in compaction rates inferred from high T + P experiments and measured in previous deformation experiments. When upscaling results to magmatic systems at intermediate melt fractions, repacking may provide an efficient mechanism to redistribute melt. Finally, outside nearly instantaneous force chain disruption events occasionally recorded in the low T + P experiments, melt loss is continuous, and two‐phase dynamics can be solved at the continuum scale with an effective matrix viscosity.
Enrichment of Phosphates, Lead, and Mixed Soil‐Organic Particles in INPs at the Southern Great Plains Site
Authors: Cornwell Gavin C. , Steinke Isabelle , Lata Nurun Nahar , Zelenyuk Alla , Kulkarni Gourihar , Pekour Mikhail , Perkins Russell , Levin Ezra J. T. , China Swarup , DeMott Paul J. , Burrows Susannah M. 
Published: June 2024

AbstractIce nucleating particles (INPs) are rare particles that initiate primary ice formation, a critical step required for subsequent important cloud microphysical processes that ultimately govern cloud phase and cloud radiative properties. Laboratory studies have found that organic‐rich dusts, such as those found in soils, are more efficient INPs compared to mineral dust. However, the atmospheric relevance of these organic‐rich dusts are not well understood, particularly in regions with significant agricultural activity. The Agricultural Ice nuclei at the Southern Great Plains field campaign (AGINSGP) was conducted in rural Oklahoma to investigate how soil dusts contribute to INP populations in the Great Plains. We present chemical characterization of ambient and ice crystal residual particles from a single day of sampling, using single particle mass spectrometry (SPMS) and scanning microscopy. Ambient particles were primarily carbonaceous or secondary aerosol, while the fraction of dust particles was higher in the residual particles. We also observed an unusual particle type consisting of a carbonaceous core mixed with dust fragments on the surface, which was found in higher proportion in residuals. Dust particles measured during residual sampling contained greater proportions of phosphate (63 and 79) and lead (206Pb+). Strong sulfate signals were not seen in the residual dust particles measured by the SPMS, while nitrate was slightly depleted relative to ambient dust. This study shows that organic‐rich soils may be important contributors to the ambient INP population in agricultural regions.
Lithological Impact on Radon Levels: A Study of Indoor and Soil Gas Radon in the Centre Region of Cameroon
Authors: Ndjana Nkoulou J. E. , Saïdou  , Hamadou Yerima A. , Oumar Bobbo M. , Nugraha E. D. , Ipan A. S. , Najam L. A. , Suárez‐Navarro J. A. , Yoho B. , Kwato Njock M. G. 
Published: June 2024

AbstractThe objectives of the current study are to carry out soil gas radon (Rn) measurements, to evaluate the total inhalation effective dose, to determine risk levels over the lithological formations of the study area. The behavior investigation of Rn activity concentration distributions in dwellings and soils, and soil Rn mapping were also conducted. Soil gas Rn measurements were made at 102 sampling points by Markus 10 instrument. This data was combined with previously reported results from 140 indoor Rn RADTRAK dosimeters to determine the total inhalation effective dose and to conduct a statistical analysis. Overall, the Rn activity concentrations in soil and dwellings range from 4 to 66 kBq m−3 and from 15 to 140 Bq m−3, with averages of 31 ± 15 kBq m−3 and 41 ± 24 Bq m−3 respectively. The corresponding total inhalation effective dose ranges from 0.35 to 3.53 mSv y−1, with a mean value of 1.37 ± 0.58 mSv y−1. For soil gas Rn, the chlorite schist lithology showed the highest average concentration level. Which could be justified by the possible presence, within chlorite minerals, highly emitting zones of alpha particles, leading to the formation of radioactive halos. Normal and high‐risk level of Rn were found for about 82% and 11% of the total area surveyed respectively. These findings highlight the need for preventive measure against Rn exposure in homes within the investigated areas. This study contributes valuable insights into Rn distribution patterns and risk assessment, offering a basis for targeted interventions in the region.