bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reconsidering inequalities in COVID-19 vaccine uptake in Germany: a spatiotemporal analysis combining individual educational level and area-level socioeconomic deprivation
Authors: Reis Marvin , Michalski Niels , Bartig Susanne , Wulkotte Elisa , Poethko-Müller Christina , Graeber Daniel , Rosario Angelika Schaffrath , Hövener Claudia , Hoebel Jens 
Published: October 2024

AbstractCombining the frameworks of fundamental causes theory and diffusion of innovation, scholars had anticipated a delayed COVID-19 vaccination uptake for people in lower socioeconomic position depending on the socioeconomic context. We qualify these propositions and analyze educational differences in COVID-19 vaccination status over the first ten months of Germany’s vaccination campaign in 2021. Data from the study “Corona Monitoring Nationwide” (RKI-SOEP-2), collected between November 2021 and February 2022, is linked with district-level data of the German Index of Socioeconomic Deprivation (GISD). We estimated the proportion of people with at least one vaccination dose stratified by educational groups and within different settings of regional socioeconomic deprivation at three time points. Logistic multilevel regression models were applied to adjust for multiple covariates and to test cross-level-interactions between educational levels and levels of area-level socioeconomic deprivation. Vaccination rates were lower among respondents with lower education. With increasing area-level socioeconomic deprivation, educational differences were larger due to particularly low vaccination rates in groups with low education levels. The analysis of vaccination timing reveals that educational gaps and gaps by area-level socioeconomic deprivation had appeared early in the vaccination campaign and did not close completely before the 4th wave of COVID-19 infections
Exploring the unfolding pathways of protein families using Elastic Network Model
Authors: Kumar Ranjan , Dutta Sandipan 
Published: October 2024

AbstractWe explore how a protein’s native structure determines its unfolding process. We examine how the local structural features, like shear, and the global structural properties, like the number of soft modes, change during unfolding. Simulations are performed using a Gaussian Network Model (GNM) with bond breaking for both thermal and force-induced unfolding scenarios. We find that unfolding starts in areas of high shear in the native structure and progressively spreads to the low shear regions. Interestingly, analysis of single domain protein families (Chymotrypsin inhibitor and Barnase) reveal that proteins with distinct unfolding pathways exhibit divergent behavior of the number of soft modes during unfolding. This suggests that the number of soft modes might be a valuable tool for understanding thermal unfolding pathways. Additionally, we found a strong link between a protein’s overall structural similarity (TM-score) and its unfolding pathways, highlighting the importance of the native structure in determining how a protein unfolds.
Chiral active systems near a substrate: Emergent damping length controlled by fluid friction
Authors: Mecke Joscha , Gao Yongxiang , Gompper Gerhard , Ripoll Marisol 
Published: October 2024

AbstractChiral active fluids show the emergence of a turbulent behaviour characterised by multiple dynamic vortices whose maximum size varies for each experimental system, depending on conditions not yet identified. We propose and develop an approach to model the effect of friction close to a surface in a particle based hydrodynamic simulation method in two dimensions, in which the friction coefficient can be related to the system parameters and to the emergence of a damping length. This length is system dependent, limits the size of the emergent vortices, and influences other relevant system properties such as the actuated velocity, rotational diffusion, or the cutoff of the energy spectra. Comparison of simulation and experimental results of a large ensemble of rotating colloids sedimented on a surface shows a good agreement, which demonstrates the predictive capabilities of the approach, which can be applied to a wider class of quasi-two-dimensional systems with friction.
ACT‐GAN: Radio map construction based on generative adversarial networks with ACT blocks
Authors: Chen Qi , Yang Jingjing , Huang Ming , Zhou Qiang 
Published: October 2024

AbstractThe radio map serves as a vital tool in assessing wireless communication networks and monitoring radio coverage, providing a visual representation of electromagnetic spatial characteristics. To address the limitation of low accuracy in current radio map construction method, this article presents a novel method based on Generative Adversarial Network (GAN), called ACT‐GAN. This method incorporates the aggregated contextual‐transformation block, the convolutional block attention module, and the transposed convolutional block into the generator, significantly enhancing the construction accuracy of radio map. The performance of ACT‐GAN is validated in three distinct scenarios. The results indicate that, in scenario 1, where the transmitter locations are known, the average reduction in Root Mean Square Error (RMSE) is 14.6%. In scenario 2, where the transmitter locations are known and supplemented with sparse measurement maps, the average reduction in RMSE is 13.3%. Finally, in scenario 3, where the transmitter locations are unknown, the average reduction in RMSE is 7.1%. Moreover, the proposed model exhibits clearer predictive results and can accurately capture multi‐scale shadow fading.
Maximizing wind farm production through pitch control using graph neural networks and hybrid learning methods
Authors: Huo Yuchong , Xu Chang , Li Qun , Li Qiang , Yin Minghui 
Published: October 2024

AbstractThis article presents a novel methodology to maximize wind farm power generation by integrating graph neural networks (GNN), supervised learning, and reinforcement learning techniques. First, the article introduces a graph‐based representation of the wind farm, capturing wind turbines as vertices and the inter‐turbine wake interactions as edges. The construction of this graph representation integrates the Jensen wake model, which includes insights derived from prior knowledge of wind farm aerodynamics. Subsequently, a detailed description of the GNN model's architecture, incorporating a message passing mechanism, is outlined. This GNN model is trained initially with supervised learning using a dataset of optimal pitch angles generated from the analytical results derived from Jensen wake model. Moreover, to improve the GNN model's accuracy and adaptability, reinforcement learning techniques are employed. The GNN model interacts with a high‐fidelity wind farm simulation environment, receiving feedback in the form of rewards derived from the wind farm's actual power output. Through a policy gradient approach, the GNN parameters undergo iterative updates, enabling the model to learn and adapt to dynamic wind conditions and intricate turbine interactions. The effectiveness and advantages of the proposed methodology are demonstrated through comprehensive case studies across various wind farm layouts.
Dynamic of mode transition in air surface micro-discharge plasma: reactive species in confined space
Authors: ZHANG 张 Jingyun 敬芸 , ZHU 朱 Min 珉 , ZHANG 张 Chaohai 潮海 
Published: October 2024

Abstract
Flexible surface micro-discharge plasma is a non-thermal plasma technique used for treating wounds in a painless way, with significant efficacy for chronic or hard-to-heal wounds. In this study, a confined space was designed to simulate wound conditions, with gelatin used to simulate wound tissue. The distinction between open and confined spaces was explored, and the effects of temperature, humidity, discharge power and the gap size within the confined space on the plasma characteristics were analyzed. It was found that temperature, humidity and discharge power are important factors that affect the concentration distribution of active components and the mode transition between ozone and nitrogen oxides. Compared to open space, the concentration of ozone in confined space was relatively lower, which facilitated the formation of nitrogen oxides. In open space, the discharge was dominated by ozone initially. As the temperature, humidity and discharge power increased, nitrogen oxides in the gas-phase products were gradually detected. In confined space, nitrogen oxides can be detected at an early stage and at much higher concentrations than ozone concentration. Furthermore, as the gap of the confined space decreased, the concentration of ozone was observed to decrease while that of nitrate increased, and the rate of this concentration change was further accelerated at higher temperature and higher power. It was shown that ozone concentration decreased from 0.11 to 0.03 μmol and the nitrate concentration increased from 20.5 to 24.5 μmol when the spacing in the confined space was reduced from 5 to 1 mm, the temperature of the external discharge was controlled at 40 °C, and the discharge power was 12 W. In summary, this study reveals the formation and transformation mechanisms of active substances in air surface micro-discharge plasma within confined space, providing foundational data for its medical applications.
Reducing readmissions with pharmacist-integrated care in Medicare value-based programs
Authors: Partosh Dor , Ricabal Lazara Cabrera , Beltran Diana C , Simmons Sade , Sherbeny Fatimah , Lazaridis Dovena 
Published: October 2024

Abstract

Purpose
Pharmacy transitions of care (ToC) programs have been shown to decrease 30-day hospital readmissions and improve patient outcomes, but there is limited published data on the impact of pharmacist-integrated ToC services beyond 30 days. The objective of this study was to evaluate the impact of pharmacist-integrated ToC and population health services on 30-, 60-, and 90-day all-cause readmissions in a Medicare value-based program (MV-BP) population and to compare mean times to first readmission with and without pharmacist care.

Methods
A retrospective observational chart review was conducted to identify eligible hospital discharge encounters (DEs). Patients 18 years of age or older enrolled in an MV-BP were assigned to 4 study groups (a control group or one of 3 intervention arms) based on the pharmacy ToC services they received from either an inpatient ToC pharmacist or a dedicated population health pharmacist (PHP).

Results
Among 1,065 eligible DEs, 90-day follow-up was completed in 1,039 cases. The control group (n = 213) had a 90-day readmission rate of 34.74%. Intervention arm 1 (n = 201) had no significant reduction in 90-day readmissions, with a rate of 29.85% (odds ratio [OR], 0.94; 95% CI, 0.61-1.47; P = 0.80), while intervention arms 2 (n = 209), and 3 (n = 416) had significantly lower rates of readmission: 9.57% (OR, 0.26; 95% CI, 0.15-0.46; P &lt; 0.01), and 17.07% (OR, 0.41; 95% CI, 0.27-0.61; P &lt; 0.01), respectively.

Conclusion
A combination of ToC and PHP services reduced 30-, 60-, and 90-day readmission rates in an MV-BP population. These results support the expansion of pharmacy-based ToC to minimize readmissions within 90 days for this Medicare population.
Device placement using Laplacian PCA and graph attention networks
Authors: Han Meng , Zeng Yan , Shu Hao , Yue Lupeng , Zhang Jilin , Wan Jian , Ren Yongjian 
Published: October 2024

Abstract
The exponential growth in data and parameters in modern neural networks has created the need to distribute these models across multiple devices for efficient training, resulting in the device placement problem. Existing graph encoding approaches for device placement suffer from low efficiency when searching for optimal parallel strategies, primarily due to suboptimal positional information retrieval. To address these challenges, we propose the Laplacian Principal Component Analysis-graph attention networks (LPCA-GAT) model. Firstly, we employ GAT to capture complex relationships between nodes and generate node encodings. Secondly, we leverage LPCA on the graph Laplacian matrix to extract crucial low-dimensional positional information. Finally, by integrating these two components, we obtain the final node encodings. This enhances the representation capability of nodes within the graph, enabling efficient device placement. The experimental results demonstrate that LPCA-GAT achieves superior device placement results, specifically accelerating execution and computation time by 13.24% and 96.38%, respectively, leading to significant improvements in both operational efficiency and performance.
Convergence of an adaptive C0-interior penalty Galerkin method for the biharmonic problem
Authors: Dominicus Alexander , Gaspoz Fernando D , Kreuzer Christian 
Published: October 2024

Abstract
We develop a basic convergence analysis for an adaptive ${C}^{0}\mathsf{IPG}$ method for the biharmonic problem that provides convergence without rates for all practically relevant marking strategies and all penalty parameters assuring coercivity of the method. The analysis hinges on embedding properties of (broken) Sobolev and BV spaces, and the construction of a suitable limit space. In contrast to the previous convergence result of adaptive discontinuous Galerkin methods for elliptic PDEs, here we have to deal with the fact that the Lagrange finite element spaces may possibly contain no proper $C^{1}$-conforming subspace. This prevents from a straight forward generalization and requires the development of some new key technical tools.
Large language model uncertainty proxies: discrimination and calibration for medical diagnosis and treatment
Authors: Savage Thomas , Wang John , Gallo Robert , Boukil Abdessalem , Patel Vishwesh , Safavi-Naini Seyed Amir Ahmad , Soroush Ali , Chen Jonathan H 
Published: October 2024

Abstract

Introduction
The inability of large language models (LLMs) to communicate uncertainty is a significant barrier to their use in medicine. Before LLMs can be integrated into patient care, the field must assess methods to estimate uncertainty in ways that are useful to physician-users.

Objective
Evaluate the ability for uncertainty proxies to quantify LLM confidence when performing diagnosis and treatment selection tasks by assessing the properties of discrimination and calibration.

Methods
We examined confidence elicitation (CE), token-level probability (TLP), and sample consistency (SC) proxies across GPT3.5, GPT4, Llama2, and Llama3. Uncertainty proxies were evaluated against 3 datasets of open-ended patient scenarios.

Results
SC discrimination outperformed TLP and CE methods. SC by sentence embedding achieved the highest discriminative performance (ROC AUC 0.68-0.79), yet with poor calibration. SC by GPT annotation achieved the second-best discrimination (ROC AUC 0.66-0.74) with accurate calibration. Verbalized confidence (CE) was found to consistently overestimate model confidence.

Discussion and Conclusions
SC is the most effective method for estimating LLM uncertainty of the proxies evaluated. SC by sentence embedding can effectively estimate uncertainty if the user has a set of reference cases with which to re-calibrate their results, while SC by GPT annotation is the more effective method if the user does not have reference cases and requires accurate raw calibration. Our results confirm LLMs are consistently over-confident when verbalizing their confidence (CE).
Enhancing photosynthetic phosphorus use efficiency through coordination of leaf phosphorus fractions, allocation, and anatomy during soybean domestication
Authors: Chen Geng , Ran Qiu-Xia , Wang Cai , Pang Jiayin , Ren Ming-Jian , Wang Zheng-Yu , He Jin , Lambers Hans 
Published: October 2024

Abstract
Soybean domestication has significantly changed key agronomic traits, yet its impact on leaf photosynthetic phosphorus use efficiency (PPUE) and its underlying traits remains poorly known. Further information on this would be important to increase soybean P use efficiency. To address this gap, 48 soybean accessions (16 wild relatives, 16 landraces, and 16 cultivars) were used to compare leaf anatomical traits, foliar chemical P fractions, P allocation, and PPUE under two P levels. The results showed that the cultivars had higher area-based and mass-based photosynthesis rates, PPUE, metabolite P concentration, and its percentage of leaf total P, as well as a greater percentage of lipid P, nucleic acid P, and residual P. Conversely, wild relatives tended to have higher leaf P concentration, palisade:spongy thickness ratio, and concentrations of inorganic P, nucleic acid P, lipid P, and residual P. PPUE was negatively correlated with leaf inorganic P concentration and its percentage relative to leaf total P, while it was positively correlated with the concentration and percentage of metabolite P. We concluded that soybean domestication increased PPUE, as a result of both increased photosynthesis rate and decreased leaf P concentration; domestication reduced the palisade:spongy thickness ratio coupled with increased allocation of P to P-containing metabolites, thereby contributing to faster photosynthesis and higher PPUE. This study sheds light on the significance of leaf P allocation and anatomical traits affecting PPUE during soybean domestication, offering a mechanistic understanding to further enhance soybean P use efficiency.
Trade literature provides a path from research to practice
Authors: Dobre Silvia , Herbert Rachel , Hicks Diana 
Published: October 2024

Abstract
The work of professionals practicing in the community provides a pathway for knowledge advances to reach practice. Yet outside of medicine, little attention has been paid to this phenomenon. Similarly, professions are defined by bodies of knowledge yet studies of professions do not attend to the dynamic relationship between professionals and the ever advancing frontiers of knowledge. In this paper, we delineate the pathway from research to practice as evidenced in trade literature. Our analysis is based on bibliometric and survey data. We find evidence that trade literature is informed by research in references to research papers found in trade periodicals, and trade press articles authored by researchers. Professionals feed back their advances in practice to the community by writing articles for trade publications, and sometimes these are articles are cited by scholarly journal articles, thus the exchange of knowledge is bi-directional to a certain extent. Our survey established that many professionals read trade literature because the contents are relevant to their practice. They trust, with caveats, the material they read but trust more in material with an obvious connection to public sector research. Professionals can often point to ways their practice has improved due to something they read in a trade periodical. Thus the trade literature has institutionalized a mechanism of indirect linkage between research and practice. Indexing trade periodicals could provide a valuable resource for those wishing to make visible the connection between research and practice.
Assessment of radiological contamination due to gold mining in soil and food crops of Babban Tsauni, Gwagwalada, Nigeria
Authors: Odelami Kafayat Abdulrasheed , Oladipo Mark Omotola Afolayan , Onoja Michael Akor , Musa Yahaya , Aremu Saudat Olabisi 
Published: October 2024

Abstract
This work assessed the activity concentrations of 238U(226Ra), 232Th, and 40K and their associated radiological risks due to exposure to soil and consumption of food crops in Babban Tsauni artisanal gold mine, Gwagwalada, Nigeria, using the gamma spectrometry technique. The mean activity concentrations of 226Ra, 232Th, and 40K in the mine soil were 60.2 ± 9.9, 161.4 ± 16.2, and 664.6 ± 138.2, while they were 46.4 ± 4.9, 79.9 ± 39.3, 266.4 ± 185.4 for tubers and 46.9 ± 15.7, 100.5 ± 35.8, 311.4 ± 132.7 (Bq/kg) for grains, respectively. The results reveal that the activity concentrations of radionuclides in all samples exceeded the recommended values set by United Nations Scientific Committee on the Effects of Atomic Radiation (33, 45, and 420 Bq/kg) except 40K, which fell within the acceptable limit in all food crop sample types. Estimated results for radiological hazard parameters, radium equivalent, annual effective dose due to ingestion, and excess life cancer risk were within safe limits, while the annual effective dose due to external gamma radiation in soil and annual gonadal equivalent dose were significantly high in all investigated samples; these call for constant radiological monitoring.
“The Damage is Permanent”: Law, Women’s “Honor,” and the Psychiatrization of Sexual Violence in Post-reform Turkey
Authors: Ellialtı-Köse Tuğçe 
Published: October 2024

Abstract
Existing literature is deeply divided on the effectiveness of rape law reforms. Intervening in this literature, this article examines the workings and consequences of ostensibly gender-neutral and victim-friendly reforms in Turkey. Through court observations, document analysis, and interviews with legal actors, I show how complex—and gendered—notions of victimization, harm, and trauma are embedded in sexual assault laws. I argue that the law defines sexual violence as inherently and invariably traumatizing, causing symptoms that can be identified and evidenced through the examination of the mental states of survivors, thus psychiatrizing it. This psychiatrization rests on the idea that rape primarily, and unequivocally, damages women’s “honor.” Consequently, the category of “legitimate victimhood” does not disappear; rather, it is reinvented by medico-legal logics that invoke gendered norms of honor and morality, which infuse and shape deliberations of justice in cases of sexual violence.
PRC2 facilitates the transition from heterotrophy to photoautotrophy during seedling emergence
Authors: Samo Naseem , Trejo-Arellano María Guadalupe , Gahurová Lenka , Erban Alexander , Ebert Alina , Rivière Quentin , Kubásek Jiří , Aflaki Fatemeh , Hönig Mondeková Helena , Schlereth Armin , Dubois Annick , Zhou Mingxi , Novák Ondřej , Šantrůček Jiří , Bouyer Daniel , Roudier Franҫois , Kopka Joachim , Mozgová Iva 
Published: October 2024

AbstractSeed-to-seedling transition represents a key developmental and metabolic switch in plants. Catabolism of seed storage reserves fuels germination and early seedling emergence until photosynthesis is established. The developmental transition is controlled by Polycomb repressive complex 2 (PRC2). However, the coordination of PRC2 activity and its contribution to transcriptional reprogramming during seedling establishment is unknown. By analysing the re-distribution of H3K27me3 and changes in gene transcription in shoot and root tissues of heterotrophic and photoautotrophic seedlings, we reveal two phases of PRC2-mediated gene repression. The first phase is independent of light and photosynthesis and results in irreversible repression of the embryo maturation programme, marked by heterotrophy and biosynthesis of reserve storage molecules. The second phase is associated with the repression of metabolic pathways related to germination and early seedling emergence, and H3K27me3 deposition in this phase is sensitive to photosynthesis inhibition. We show that preventing transcription of the PRC2-repressed glyoxylate cycle geneISOCITRATE LYASEis sufficient to drive the vegetative phase transition in PRC2-depleted plants. This underscores a key role of PRC2 repression in the coordinated metabolic and developmental switches during seedling emergence and emphasizes the close connection between metabolic and developmental identities.