bluuebunny/crossref_metadata_2025_split huggingface dataset:
Where the past meets the present: connecting nitrogen from watersheds to streams through groundwater flowpaths
Authors: Moore Eric M , Barclay Janet R , Haynes Adam B , Jackson Kevin E , Bisson Alaina M , Briggs Martin A , Helton Ashley M 
Published: November 2023

Abstract
Groundwater discharge to streams is a nonpoint source of nitrogen (N) that confounds N mitigation efforts and represents a significant portion of the annual N loading to watersheds. However, we lack an understanding of where and how much groundwater N enters streams and watersheds. Nitrogen concentrations at the end of groundwater flowpaths are the culmination of biogeochemical and physical processes from the contributing land area where groundwater recharges, within the aquifer system, and in the near-stream riparian area where groundwater discharges to streams. Our research objectives were to quantify the spatial distribution of N concentrations at groundwater discharges throughout a mixed land-use watershed and to evaluate how relationships among contributing and riparian land cover, modeled aquifer characteristics, and groundwater discharge biogeochemistry explain the spatial variation in groundwater discharge N concentrations. We accomplished this by integrating high-resolution thermal infrared surveys to locate groundwater discharge, biogeochemical sampling of groundwater, and a particle tracking model that links groundwater discharge locations to their contributing area land cover. Groundwater N loading from groundwater discharges within the watershed varied substantially between and within streambank groundwater discharge features. Groundwater nitrate concentrations were spatially heterogeneous ranging from below 0.03–11.45 mg-N/L, varying up to 20-fold within meters. When combined with the particle tracking model results and land cover metrics, we found that groundwater discharge nitrate concentrations were best predicted by a linear mixed-effect model that explained over 60% of the variation in nitrate concentrations, including aquifer chemistry (dissolved oxygen, Cl−, SO4
2−), riparian area forested land cover, and modeled physical aquifer characteristics (discharge, Euclidean distance). Our work highlights the significant spatial variability in groundwater discharge nitrate concentrations within mixed land-use watersheds and the need to understand groundwater N processing across the many spatiotemporal scales within groundwater cycling.
A storyline analysis of Hurricane Irma’s precipitation under various levels of climate warming
Authors: Huprikar Annika S , Stansfield Alyssa M , Reed Kevin A 
Published: November 2023

Abstract
Understanding how extreme weather, such as tropical cyclones, will change with future climate warming is an interesting computational challenge. Here, the hindcast approach is used to create different storylines of a particular tropical cyclone, Hurricane Irma (2017). Using the community atmosphere model, we explore how Irma’s precipitation would change under various levels of climate warming. Analysis is focused on a 48 h period where the simulated hurricane tracks reasonably represent Irma’s observed track. Under future scenarios of 2 K, 3 K, and 4 K global average surface temperature increase above pre-industrial levels, the mean 3-hourly rainfall rates in the simulated storms increase by 3–7% K−1 compared to present. This change increases in magnitude for the 95th and 99th percentile 3-hourly rates, which intensify by 10–13% K−1 and 17–21% K−1, respectively. Over Florida, the simulated mean rainfall accumulations increase by 16–26% K−1, with local maxima increasing by 18–43% K−1. All percent changes increase monotonically with warming level.
Projections of central Arctic summer sea surface temperatures in CMIP6
Authors: Han Ju-Seok , Park Hyo-Seok , Chung Eui-Seok 
Published: November 2023

Abstract
One of the most dramatic climate responses to future global warming is the near-disappearance of the perennial sea ice cover in the central Arctic Ocean, a phenomenon known as the ice-free summer Arctic. The immediate consequence of an ice-free Arctic would be the surface warming of the central Arctic Ocean, where sea surface temperatures (SSTs) used to be at freezing levels. Through an analysis of climate models participating in the climate model intercomparison project phase-6, this study demonstrates a wide range of responses in the central Arctic SSTs in August–September as a result of the projected ice-free summer Arctic. These responses vary from 0.7 to 8 °C in the shared socioeconomic pathway 2 (SSP2-4.5), referred to as the ‘middle of the road’ scenario, in which socioeconomic and technological trends do not significantly deviate from historical patterns. The extent of the central Arctic sea surface warming in August–September is found to have a loose correlation with the September sea ice extent (SIE), but a stronger connection to the SIE during spring to early summer (May–July), when incoming shortwave radiation is most intense. In certain climate models, the perennial sea ice cover disappears completely in September, causing central Arctic SSTs to rise by 5 °C–8 °C by the end of the 21st century. This leads to a bimodal distribution of annual SSTs. Further analysis reveals a close relationship between mid-summer SSTs in the central Arctic Ocean and preceding winter sea ice thickness (SIT). This underscores the significance of winter SIT in predicting future Arctic surface warming and marine heatwaves.
Material and component developments for the DEMO divertor using fibre reinforcement and additive manufacturing
Authors: Neu R , Coenen J W , Curzadd B , Gietl H , Greuner H , Höschen T , Hunger K , Lürbke R , Müller Av , Riesch J , Schlick G , Siefken U , Visca E , You JH 
Published: November 2023

Abstract
Within the research along the European Fusion Roadmap, water-cooled divertor PFCs are foreseen in the design of a first fusion demonstration power plant (DEMO) in order to provide reliable heat removal capability. In the frame of this concerted attempt, the Max Planck Institute for Plasma Physics is concentrating on the development and testing of composite materials based on tungsten (W, preferred armour material) and copper (Cu, preferred heat sink material). W fibres (Wf) as monofilaments and yarns as reinforcement play a central role in these investigations due to their extraordinary properties concerning ductility already at room temperature and high tensile strength. Recent investigations on the impact of radiation damage suggest that the fibres retain their ductility upon irradiation. W reinforced with W fibres (Wf/W) allows to overcome the intrinsic brittleness of W. Quantitative mechanical fracture tests of Wf /W confirm the basic mechanisms of fibre reinforcement and the increased resistance to mechanical fatigue. The good wettability of W with liquid Cu and the absence of any metallurgical solubility make up an ideal material pairing for composite production. W fibre-reinforced Cu (Wf/Cu) cooling tubes provide a rather high thermal conductivity (> 250 W mK−1) and at least twice the strength of CuCrZr in hoop direction in the temperature range up to at least 500 °C. Very recent neutron irradiation experiments confirm the sustainment of ductility of the Wf/Cu composite. Numerical simulations suggest that thermal stresses in W-Cu PFCs could be strongly reduced by tailoring the local W and Cu volume fraction. This ‘freely’ distributed material composition can be achieved by means of additively manufactured W skeletons consecutively infiltrated by Cu. Investigations with W preforms produced by Laser Beam Powder Bed Fusion and infiltrated by Cu demonstrate the feasibility of this approach while testing of specifically prepared specimen is ongoing.
Influence of the position relationship between the cathode and magnetic separatrix on the discharge process of a Hall thruster
Authors: CAO 曹 Xifeng 希峰 , MA 麻 Hongning 洪宁 , XIA 夏 Guojun 国俊 , LIU 刘 Hui 辉 , ZHAO 赵 Fangzhou 方舟 , WANG 王 Yuhang 宇航 , CHEN 陈 Juhui 巨辉 
Published: November 2023

Abstract
Previous studies have shown that there is an obvious coupling relationship between the installation location of the external cathode and the magnetic separatrix in the plume region of a Hall thruster. In this paper, the particle-in-cell simulation method is used to compare the thruster discharge process under the conditions of different position relationships between the cathode and the magnetic separatrix. By comparing the distribution of electron conduction, potential, plasma density and other microscopic parameters, we try to explain the formation mechanism of the discharge difference. The simulation results show that the cathode inside and outside the magnetic separatrix has a significant effect on the distribution of potential and plasma density. When the cathode is located on the outer side of the magnetic separatrix, the potential above the plume region is relatively low, and there is a strong potential gradient above the plume region. This potential gradient is more conducive to the radial diffusion of ions above the plume, which is the main reason for the strong divergence of the plume. The distribution of ion density is also consistent with the distribution of potential. When the cathode is located on the outer side of the magnetic separatrix, the radial diffusion of ions in the plume region is enhanced. Meanwhile, by comparing the results of electron conduction, it is found that the trajectories of electrons emitted from the cathode are significantly different between the inner and outer sides of the magnetic separatrix. This is mainly because the electrons are affected by the magnetic mirror effect of the magnetic tip, which makes it difficult for the electrons to move across the magnetic separatrix. This is the main reason for the difference in potential distribution. In this paper, the simulation results of macroscopic parameters under several conditions are also compared, and they are consistent with the experimental results. The cathode is located on the inner side of the magnetic separatrix, which can effectively reduce the plume divergence angle and improve the thrust. In this paper, the cathode moves from R = 50 mm to R = 35 mm along the radial direction, the thrust increases by 3.6 mN and the plume divergence angle decreases by 23.77%. Combined with the comparison of the ionization region and the peak ion density, it is found that the main reason for the change in thrust is the change in the radial diffusion of ions in the plume region.
Weavable thermoelectrics: advances, controversies, and future developments
Authors: Shi Xiao-Lei , Sun Shuai , Wu Ting , Tu Jian , Zhou Zhiming , Liu Qingfeng , Chen Zhi-Gang 
Published: November 2023

Abstract
Owing to the capability of the conversion between thermal energy and electrical energy and their advantages of light weight, compactness, noise-free operation, and precision reliability, wearable thermoelectrics show great potential for diverse applications. Among them, weavable thermoelectrics, a subclass with inherent flexibility, wearability, and operability, find utility in harnessing waste heat from irregular heat sources. Given the rapid advancements in this field, a timely review is essential to consolidate the progress and challenge. Here, we provide an overview of the state of weavable thermoelectric materials and devices in wearable smart textiles, encompassing mechanisms, materials, fabrications, device structures, and applications from recent advancements, challenges, and prospects. This review can serve as a valuable reference for researchers in the field of flexible wearable thermoelectric materials and devices and their applications.
Sexual attraction with pollination during feeding behaviour: implications for transitions between specialized strategies
Authors: Phillips Ryan D , Bohman Björn , Peakall Rod , Reiter Noushka 
Published: November 2023

Abstract

Background and Aims
Understanding the origin of pollination by sexual deception has proven challenging, as sexually deceptive flowers are often highly modified, making it hard to resolve how any intermediate forms between sexual deception and an ancestral strategy might have functioned. Here, we report the discovery in Caladenia (Orchidaceae) of sexual attraction with pollination during feeding behaviour, which may offer important clues for understanding shifts in pollination strategy.

Methods
For Caladenia robinsonii, we observed the behaviour of its male wasp pollinator, Phymatothynnus aff. nitidus (Thynnidae), determined the site of release of the sexual attractant, and experimentally evaluated if the position of the attractant influences rates of attempted copulation and feeding behaviour. We applied GC-MS to test for surface sugar on the labellum. To establish if this pollination strategy is widespread in Caladenia, we conducted similar observations and experiments for four other Caladenia species.

Key Results
In C. robinsonii, long-range sexual attraction of the pollinator is via semiochemicals emitted from the glandular sepal tips. Of the wasps landing on the flower, 57 % attempted copulation with the sepal tips, while 27 % attempted to feed from the base of the labellum, the behaviour associated with pollen transfer. A similar proportion of wasps exhibited feeding behaviour when the site of odour release was manipulated. A comparable pollination strategy occurs in another phylogenetically distinct clade of Caladenia.

Conclusions
We document a previously overlooked type of sexual deception for orchids involving long-distance sexual attraction, but with pollination occurring during feeding behaviour at the labellum. We show this type of sexual deception operates in other Caladenia species and predict that it is widespread across the genus. Our findings may offer clues about how an intermediate transitional strategy from a food-rewarding or food-deceptive ancestor operated during the evolution of sexual deception.
Fraud on the tribunal in investor–State arbitration
Authors: Sharma Gunjan 
Published: November 2023

Abstract
Fraud on investor–State arbitration tribunals is somewhat uncommon but hardly rare. This article summarises 17 publicly known investor–State arbitration awards addressing fraud on the tribunal, to contribute to this underdeveloped field of law. The article notes that investor–State tribunals have confronted this wrongdoing in various ways, ranging from avoiding findings of fraud to imposing arbitral sanctions. It notes, however, the apparent dearth of referral to criminal processes arising out of proven fraud. It concludes with a summary of the potential remedies available to the tribunal when confronted with fraud.
ReGeNNe: genetic pathway-based deep neural network using canonical correlation regularizer for disease prediction
Authors: Sharma Divya , Xu Wei 
Published: November 2023

AbstractMotivationCommon human diseases result from the interplay of genes and their biologically associated pathways. Genetic pathway analyses provide more biological insight as compared to conventional gene-based analysis. In this article, we propose a framework combining genetic data into pathway structure and using an ensemble of convolutional neural networks (CNNs) along with a Canonical Correlation Regularizer layer for comprehensive prediction of disease risk. The novelty of our approach lies in our two-step framework: (i) utilizing the CNN’s effectiveness to extract the complex gene associations within individual genetic pathways and (ii) fusing features from ensemble of CNNs through Canonical Correlation Regularization layer to incorporate the interactions between pathways which share common genes. During prediction, we also address the important issues of interpretability of neural network models, and identifying the pathways and genes playing an important role in prediction.ResultsImplementation of our methodology into three real cancer genetic datasets for different prediction tasks validates our model’s generalizability and robustness. Comparing with conventional models, our methodology provides consistently better performance with AUC improvement of 11% on predicting early/late-stage kidney cancer, 10% on predicting kidney versus liver cancer type and 7% on predicting survival status in ovarian cancer as compared to the next best conventional machine learning model. The robust performance of our deep learning algorithm indicates that disease prediction using neural networks in multiple functionally related genes across different pathways improves genetic data-based prediction and understanding molecular mechanisms of diseases.Availability and implementationhttps://github.com/divya031090/ReGeNNe.
Temporary Agency Workers in the Personal Social Services—Doing Core Tasks in the Periphery
Authors: Shanks Emelie 
Published: November 2023

Abstract
Despite concerns about negative consequences for clients and permanent staff, temporary agency workers (TAWs) are frequently employed to manage staff shortages in personal social services (PSS) in Sweden and elsewhere. Drawing on qualitative interviews with thirty-four TAWs, managers and permanent social workers, this article aims to enhance our understanding of how TAWs are utilised in the PSS and the impact this has on (i) the preconditions for TAWs and (ii) the work environment for permanent employees. The findings suggest that TAWs are mainly contracted for core tasks, and often for heavy-duty work. In order to meet demands for expedient case administration, the supportive aspects of social work are sometimes deprioritised. Permanent staff report that positive effects of the use of TAWs include relief of workload and an influx of new knowledge, whereas negative effects include stagnated work development, deteriorating group dynamics and additional work. Moreover, it is shown that TAWs often reside in the periphery of the organisation and that they typically are contracted on an ad-hoc basis and during times of crisis. It is suggested that the organisational conditions that TAWs are contracted to help remedy paradoxically are unlikely to create the best preconditions for a successful use.
Multiple reproductive barriers maintain species boundaries in stone plants of the genus Argyroderma
Authors: Boucher Florian C , Verboom G Anthony , Gallien Laure , Ellis Allan G 
Published: November 2023

Abstract
Measuring the strength of different reproductive barriers across species pairs is key to reveal the mechanisms that have led to evolutionary radiations. Here we study a genus of miniature plants, Argyroderma, which comprises 11 species restricted to a single plain of the Southern African desert. We measure different reproductive barriers to understand how species boundaries are maintained in this genus. Our results show that reproductive isolation is almost complete between all species pairs and relies on three pre-mating barriers: geographic isolation operating at spatial scales of c. 10 km, phenological isolation in flowering time, and habitat isolation operating at spatial scales of just a few metres, which is thought to be due to contrasting edaphic preferences between species. In comparison, post-mating isolation arising before seed formation is weak and does not restrict gene flow much between species. Interestingly, the high levels of both geographic and habitat isolation that we have measured between Argyroderma species might be due to their miniature size, which leads to restricted gene flow across space and to adaptation to spatially restricted micro-habitats.
Viral Suppression Trajectories Destabilized After Coronavirus Disease 2019 Among US People With Human Immunodeficiency Virus: An Interrupted Time Series Analysis
Authors: Spinelli Matthew A , Christopoulos Katerina A , Moreira Carlos V , Jain Jennifer P , Lisha Nadra , Glidden David V , Burkholder Greer A , Crane Heidi M , Shapiro Adrienne E , Jacobson Jeffrey M , Cachay Edward R , Mayer Kenneth H , Napravnik Sonia , Moore Richard D , Gandhi Monica , Johnson Mallory O 
Published: November 2023

Abstract
We examined changes in the proportion of people with human immunodeficiency virus (PWH) with virologic suppression (VS) in a multisite US cohort before and since the coronavirus disease 2019 (COVID-19) pandemic. Overall, prior gains in VS slowed during COVID-19, with disproportionate impacts on Black PWH and PWH who inject drugs.
Population data–based federated machine learning improves automated echocardiographic quantification of cardiac structure and function: the Automatisierte Vermessung der Echokardiographie project
Authors: Morbach Caroline , Gelbrich Götz , Schreckenberg Marcus , Hedemann Maike , Pelin Dora , Scholz Nina , Miljukov Olga , Wagner Achim , Theisen Fabian , Hitschrich Niklas , Wiebel Hendrik , Stapf Daniel , Karch Oliver , Frantz Stefan , Heuschmann Peter U , Störk Stefan 
Published: November 2023

Abstract

Aims
Machine-learning (ML)-based automated measurement of echocardiography images emerges as an option to reduce observer variability. The objective of the study is to improve the accuracy of a pre-existing automated reading tool (‘original detector’) by federated ML-based re-training.

Methods and results
Automatisierte Vermessung der Echokardiographie was based on the echocardiography images of n = 4965 participants of the population-based Characteristics and Course of Heart Failure Stages A–B and Determinants of Progression Cohort Study. We implemented federated ML: echocardiography images were read by the Academic Core Lab Ultrasound-based Cardiovascular Imaging at the University Hospital Würzburg (UKW). A random algorithm selected 3226 participants for re-training of the original detector. According to data protection rules, the generation of ground truth and ML training cycles took place within the UKW network. Only non-personal training weights were exchanged with the external cooperation partner for the refinement of ML algorithms. Both the original detectors as the re-trained detector were then applied to the echocardiograms of n = 563 participants not used for training. With regard to the human referent, the re-trained detector revealed (i) superior accuracy when contrasted with the original detector’s performance as it arrived at significantly smaller mean differences in all but one parameter, and a (ii) smaller absolute difference between measurements when compared with a group of different human observers.

Conclusion
Population data–based ML in a federated ML set-up was feasible. The re-trained detector exhibited a much lower measurement variability than human readers. This gain in accuracy and precision strengthens the confidence in automated echocardiographic readings, which carries large potential for applications in various settings.