bluuebunny/crossref_metadata_2025_split huggingface dataset:
Regularized methods via cubic model subspace minimization for nonconvex optimization
Authors: Bellavia Stefania , Palitta Davide , Porcelli Margherita , Simoncini Valeria 
Published: February 2025

Abstract
Adaptive cubic regularization methods for solving nonconvex problems need the efficient computation of the trial step, involving the minimization of a cubic model. We propose a new approach in which this model is minimized in a low dimensional subspace that, in contrast to classic approaches, is reused for a number of iterations. Whenever the trial step produced by the low-dimensional minimization process is unsatisfactory, we employ a regularized Newton step whose regularization parameter is a by-product of the model minimization over the low-dimensional subspace. We show that the worst-case complexity of classic cubic regularized methods is preserved, despite the possible regularized Newton steps. We focus on the large class of problems for which (sparse) direct linear system solvers are available and provide several experimental results showing the very large gains of our new approach when compared to standard implementations of adaptive cubic regularization methods based on direct linear solvers. Our first choice as projection space for the low-dimensional model minimization is the polynomial Krylov subspace; nonetheless, we also explore the use of rational Krylov subspaces in case where the polynomial ones lead to less competitive numerical results.
The impact of pan trap diameter on sampled bee communities and bycatch weight
Authors: Krahner André , Dietzsch Anke C. , Klaus Felix 
Published: February 2025

Abstract
Although pan traps are an established method for sampling bees across a wide range of habitats and geographical regions, uncertainty persists as to how pan-trap characteristics influence sampling results. We investigated the effect of pan-trap diameter (23 cm versus 12 cm), interacting with trap colour, on sampled bee communities and bycatch in wildflower strips within agricultural landscapes in Germany, using fluorescent blue, white and yellow pan traps. Based on 1147 collected bee individuals identified on a species level (69 species), we observed interacting effects of pan trap colour and size on the number of sampled bee individuals and species. Large pan traps collected significantly more bee individuals (white and yellow pan traps) and species (all colours) than small pan traps. Large pan traps also collected significantly more bycatch biomass than small pan traps, irrespectively of pan trap colour. The estimated number of sampled species based on the same number of sampled individuals (individual-based rarefaction) was higher for larger pan traps than for smaller pan traps at all sampling sites. Implications for insect conservation: using larger pan traps for sampling bees increases trap efficacy (absolute numbers of sampled individuals and species) and efficiency (sampled species per sampled individuals), but larger traps also capture more bycatch biomass. Particularly in long-term monitoring schemes, we encourage a limitation of this potential impact on the non-target insect fauna by employing methodological refinements. The option to use more small traps per site versus fewer large traps remains to be explored.
Berndt-type integrals: unveiling connections with Barnes zeta and Jacobi elliptic functions
Authors: Bradshaw Zachary P. , Vignat Christophe 
Published: February 2025

Abstract
We address a class of definite integrals known as Berndt-type integrals, highlighting their role as specialized instances within the integral representation framework of the Barnes-zeta function. Building upon the foundational insights of Xu and Zhao, who adeptly evaluate these integrals using rational linear combinations of Lambert-type series and derive closed-form expressions involving products of

$$\Gamma ^4(1/4)$$

Γ
4

(
1
/
4
)

and

$$\pi ^{-1}$$

π

-
1

, we uncover direct evaluations of the Barnes-zeta function. Moreover, our inquiry leads us to establish connections between Berndt-type integrals and Jacobi elliptic functions, as well as moment polynomials investigated by Lomont and Brillhart, a relationship elucidated through the seminal contributions of Kuznetsov. In this manner, we extend and integrate these diverse mathematical threads, unveiling deeper insights into the intrinsic connections and broader implications of Berndt-type integrals in special function and integration theory.
Unraveling the link between frailty and Alzheimer’s disease biomarkers in patients with mild cognitive impairment
Authors: Buscarnera Simona , Canevelli Marco , Bruno Giuseppe , Garibotto Valentina , Frisoni Giovanni Battista , Ribaldi Federica 
Published: February 2025

Abstract
Alzheimer’s disease (AD) can be identified through biomarkers of amyloid (A) and tau (T) pathology. Frailty, a measure of biological aging, could impact the association between AD neuropathology and its clinical manifestation. We aimed to investigate the relationship between frailty and AD biomarkers among people with mild cognitive impairment (MCI) attending a university memory clinic. Data were collected from a cohort of patients with MCI at the Memory Center of Geneva University Hospital (Switzerland). Frailty was assessed using a 35-item Frailty Index (FI). A and T positivity were determined through amyloid and tau PET or CSF analysis. Participants were divided into two subgroups: (i) A + T + (both amyloid and tau positive) and (ii) E/N (either A + or T + , neither A + nor T +), including all other combinations of A/T status. We first explored the correlation between FI, age, and education. Demographics, FI scores, and neuropsychological test results were then compared between these two groups. Logistic regression models, adjusted for age, sex, and education were used to examine the association between FI and AT positivity. One hundred twenty patients were included. FI was positively correlated with age and inversely with education. A + T + patients exhibited lower FI scores compared to E/N participants (0.13 ± 0.10 vs. 0.15 ± 0.08, p = 0.01). Logistic regressions found a negative association between FI and A + T + (OR 0.6, 95% CI 0.32–0.90; p = 0.02). Frailty is associated with a lower likelihood of AD biomarker positivity in patients with MCI. Frailty might reflect alternative pathophysiological mechanisms contributing to cognitive impairment.
Reactivity to confidence ratings: evidence of impaired rule-learning
Authors: Double Kit S. , Goldwater Micah B. , Birney Damian P. 
Published: February 2025

Abstract
Recent evidence has shown that eliciting confidence ratings can affect cognitive performance– a so-called reactivity effect. Several mechanisms have been proposed to account for reactivity, but currently there is only indirect evidence about why confidence ratings are reactive. Here, we explore the strategic changes in cognitive processes that occur in response to confidence ratings. Using a category learning paradigm that distinguishes between memorization and rule learning, in a large-sample (N = 710) pre-registered study, we show that eliciting confidence ratings caused a reduction in rule-based learning, even when compared to participants who made judgments of learning that asked them to reflect on their learning during the task as a whole. We argue that confidence ratings promote changes in the strategies participants adopt, driven by a more conservative approach that prioritizes performance over mastery and ultimately hinders rule-based learning and knowledge transfer.
Towards Highly Dense Yb-Silicate Microstructures Deposited by Air Plasma Spray for Environmental Barrier Coating Applications II: Plasma Gas Composition, Feedstock, and Anode Orifice Comparisons
Authors: Gildersleeve Edward J. , Bakan Emine , Vaßen Robert 
Published: February 2025

Abstract
In all air plasma sprayed (APS) environmental barrier coating (EBC) applications, the predominant goal is to achieve maximum coating density, gas tightness, and/or hermeticity prior to subjecting it to harsh environments (i.e., high-temperature impingement of high-velocity water vapor). The microstructures of APS coatings are historically understood to be influenced by the input processing parameters. Beyond the local deposition rate (surface speed, feeding rate) explored in Part I, there are further extrinsic processing parameters such as plasma gas composition, feedstock choice, and anode orifice dimensions which can be tuned, but have not been fully explored in the context of EBCs. Screening these ancillary extrinsic inputs in a rigorous and systematic way presents challenges in determining which control variable(s) to select to gain meaningful insights. A constant particle temperature distribution (not average particle temperature) in the spray stream was held as a constraint, and the aforementioned extrinsic parameters were varied. As in Part I, a qualitative microstructural approach toward examining the presence (or absence) of advantageous vertical thin microcracks in the as-deposited coating was taken. For certain conditions, a Dense Vertically Macrocracked structure was achieved. Concurrent synthesis of these results offers further insights into process selection and parameter design can be gained.
AI Ethics beyond Principles: Strengthening the Life-world Perspective
Authors: Heuser Stefan , Steil Jochen , Salloch Sabine 
Published: February 2025

Abstract
The search for ethical guidance in the development of artificial intelligence (AI) systems, especially in healthcare and decision support, remains a crucial effort. So far, principles usually serve as the main reference points to achieve ethically correct implementations. Based on reviewing classical criticism of principle-based ethics and taking into account the severity and potentially life-changing relevance of decisions assisted by AI-driven systems, we argue for strengthening a complementary perspective that focuses on the life-world as ensembles of practices which shape people’s lives. This perspective focuses on the notion of ethical judgment sensitive to life forms, arguing that principles alone do not guarantee ethicality in a moral world that is rather a joint construction of reality than a matter of mere control. We conclude that it is essential to support and supplement the implementation of moral principles in the development of AI systems for decision-making in healthcare by recognizing the normative relevance of life forms and practices in ethical judgment.
Numerical simulation on fracturing fluid flowback from post-fracturing shale gas wells and influencing factors
Authors: Tang Dengji , Wu Jianfa , Zhao Jinzhou , Zeng Bo , Song Yi , Shen Cheng , Ren Lan , Wang Yiting , Wang Zhenhua 
Published: February 2025

Abstract
Fracture network fracturing is a key technology to achieve economic and effective development of shale gas. The flowback data after hydraulic fracturing is crucial to the characterization of hydraulic fracture networks and reservoir evaluation. Based on the flowback characteristics of shale gas fracturing fluid, combined with the crossflow equation and the flow material balance equation, a tree-shaped fractal fracture network two-phase flowback model is established in this paper suitable for inverting the effective fracture network volume of shale gas, which is used to calculate the effective fracture network volume and conduct sensitivity analysis of the main flowback parameters. The reliability of the model is verified by the actual flowback data of field fracturing wells. The research shows that the larger the initial fracture width of the tree-shaped fractal fracture network, the larger the peak value of the water, the larger the double peak value of the gas production curve, and the higher the flowback rate; the larger the ratio of fracture order to fracture length, the lower the flowback rate; the larger the ratio of fracture width to fracture height, the higher the flowback rate. By optimizing the fracture network structure, the flowback rate and test production of shale gas wells with fracture network fracturing can be improved. The flowback law of shale gas can be studied effectively by the tree-shaped fractal fracture network two-phase flowback model. And it has important value for the optimization design of shale gas fracturing.
Pediatric Emergency Medicine Fellowship Training: An Exploration of Challenges, Solutions, and Future Directions
Authors: Alsabri Mohamed , Oboli Victor N. , Onyejesi Chibuike Daniel , Aziz Mayam Mohamed , Okaruefe Cynthia Oghenekome , Ram Muskaan Doulat , Abdelbar Sohaila Mohamed , Waseem Muhammad 
Published: February 2025

Abstract

Background
Pediatric Emergency Medicine (PEM) fellowship programs are crucial for training physicians to handle the unique challenges of pediatric emergencies. Despite their importance, these programs face significant obstacles that can hinder the training process and the preparedness of fellows for independent practice.

Purpose of review
To identify the barriers faced by PEM fellows during their training and to propose potential solutions that can enhance their educational experience and clinical competence.

Methods
A comprehensive narrative review of existing literature was conducted to explore the challenges in PEM fellowship training. The literature search included articles from PubMed, Google Scholar, and official organizational websites such as the American Board of Pediatrics (ABP) and the Accreditation Council for Graduate Medical Education (ACGME). Key areas of focus included disparities in procedural exposure, administrative burdens, limited high-acuity case encounters, overreliance on consultations, medicolegal concerns, burnout, and the impact of the COVID-19 pandemic. Proposed solutions were derived from evidence-based practices and successful interventions implemented in various institutions.

Recent findings
The narrative review revealed several critical challenges, including insufficient exposure to high-acuity cases, disparities in procedural training, the impact of administrative demands, and the repercussions of the COVID-19 pandemic. Recent advancements such as simulation-based training, competency-driven curricula, and wellness initiatives have shown promise in mitigating these barriers.

Summary
The review identified several challenges that negatively impact PEM fellowship training. Fellows often experience insufficient procedural opportunities, excessive administrative tasks, and limited autonomy in clinical decision-making. These factors contribute to decreased confidence, skill gaps, and increased burnout. Proposed solutions include enhanced simulation training, curriculum reform, administrative support, promotion of fellow autonomy, legal education, wellness programs, integration of technology and innovation, and adaptation to external challenges such as pandemics.

Conclusion
Addressing the challenges in PEM fellowship training requires a comprehensive approach that incorporates educational, administrative, technological, and wellness strategies. Implementing these solutions can improve the training experience, ensure procedural competence, and promote the overall well-being of fellows, ultimately leading to better patient care outcomes.
Lasiodiplodia theobromae disease symptom development in young avocado (Persea americana L.) plants depends on the inoculation method
Authors: Rodríguez-Gálvez Edgar , Haro-Diaz Cesar , Maza-Aguirre Samir , Canahuire-Castillo Fátima , Sullón-Saucedo Julio , Deising Holger B. 
Published: February 2025

Abstract

Lasiodiplodia theobromae is a pathogenic fungus of more than 500 plant species, including avocado (Persea americana Mill.). The global production volume of avocado exceeded 911,000 metric tons in 2023. Although detailed quantitative surveys of yield losses caused by L. theobromae are not available for most avocado-producing regions, estimates indicate that this pathogen is associated with stem-end rot disease in 30-35% of plots located in the Department of Antioquia in Colombia (Ramírez-Gil et al. Heliyon 7: e05905, 2021), suggesting an enormous economic impact. As yield losses strongly depend on the virulence of isolates, a reliable method for determining their aggressiveness is indispensable for initiating disease control measures. In this study, we compared progression of external and internal necrosis caused by the aggressive L. theobromae isolate LA-VLCA3 inoculated into wounded middle parts of the stem and onto excised apices. Irrespective of the inoculation method, internal progression of necrosis preceded that of external necrosis. Spreading of external and internal necrosis was significantly more severe in plants inoculated at the apex than in mid-stem inoculated plants. We conclude that apex inoculation causes stronger symptoms and is therefore better suited to compare virulence of isolates than mid-stem inoculation.
Italian firms’ trading behavior in the European carbon market
Authors: Nardone Claudia , Pittiglio Rosanna , Reganati Filippo 
Published: February 2025

Abstract
This paper investigates the trading behavior of firms regulated by the European Union Emission Trading System (EU ETS). Focusing on the first three periods of the EU ETS (2005–2021), our study specifically analyses the factors influencing ETS firms’ decisions to participate in the emission allowances market and the intensity of their trading activities. To conduct this research, we employ a panel double-hurdle model and leverage data from the Italian section of the European Transaction Log, in conjunction with ORBIS Bureau Van Dijk data. Our findings indicate that transaction costs, such as information and search costs, and net position are the primary determinants shaping the trading behavior of Italian firms throughout all phases of the EU ETS. These results hold true even when considering buyers and sellers separately, as well as interfirm and intrafirm trades. In contrast, the ability to reduce emissions decreases the probability of market participation and trade intensity only for purchasing ETS firms, and it reduces both the probability and intensity of trade only for internal exchanges. Energy-producing firms engage more in buying allowances, while carbon leakage sectors firms are more likely to sell excess allowances. Furthermore, belonging to these sectors appears to have no significant effect on intrafirm trade. These findings suggest that policy interventions such as reducing information and search costs, enhancing market transparency, and introducing price management mechanisms could improve market efficiency and the overall effectiveness of the EU ETS.
A State-Level Examination into Structural Racism and Racialized Disparities in Sexually Transmitted Infections
Authors: Evans Megan , Newmyer Lauren 
Published: February 2025

Abstract
The population health literature recognizes structural racism as a fundamental determinant of racialized health disparities. However, the role of structural racism in the continued persistence of racialized disparities in sexually transmitted infections (STIs) has not been investigated despite Black Americans’ disproportionate experience of STIs in comparison to White Americans. Past research has largely investigated individual racial/ethnic identity as an individual-level factor predictive of STIs, failing to engage with the multitude of racially structured contexts which likely shape STI rates. This study combines multiple datasets, including data from the Centers for Disease Control and Prevention, the American Community Survey, and the Current Population Survey, to conduct a state-level analysis investigating the role of structural racism in contributing to Black–White racialized disparities in STIs between 2010 and 2020. Random effects spatial autoregressive models suggest that structural racism contributes to Black–White racialized disparities in STIs. This research contributes to literatures on structural racism and population health by better understanding how racialized state-level institutions shape the contraction of infections. The results have important implications for understanding states as institutional actors relevant for patterns of population health and the geography of racism.
The Poisoning of the Rule of Law
Authors: Coyle Sean 
Published: February 2025

Abstract
Discussions of Nazi law tend to centre upon Fuller’s desiderata of the rule of law. Whilst not disputing this connection, this essay argues that tyranny and oppression are marked by the (ab)use of law to invade the domain proper to individual moral thinking, and to transform citizens into models of conformity to whatever values the tyrant cherishes. Its main consideration is how a community can recover from periods of tyranny, and how the law can recover its dignity having shown itself capable of evil uses. So, it is focused more on ‘substantive’ rather than ‘procedural’ morality.
Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation
Authors: Malé Quentin , Lapeyre Corentin J. , Noiray Nicolas 
Published: February 2025

Abstract
This article establishes a data-driven modeling framework for lean hydrogen (

$ {\mathrm{H}}_2 $

)-air reaction rates for the Large Eddy Simulation (LES) of turbulent reactive flows. This is particularly challenging since

$ {\mathrm{H}}_2 $

molecules diffuse much faster than heat, leading to large variations in burning rates, thermodiffusive instabilities at the subfilter scale, and complex turbulence-chemistry interactions. Our data-driven approach leverages a Convolutional Neural Network (CNN), trained to approximate filtered burning rates from emulated LES data. First, five different lean premixed turbulent

$ {\mathrm{H}}_2 $

-air flame Direct Numerical Simulations (DNSs) are computed each with a unique global equivalence ratio. Second, DNS snapshots are filtered and downsampled to emulate LES data. Third, a CNN is trained to approximate the filtered burning rates as a function of LES scalar quantities: progress variable, local equivalence ratio, and flame thickening due to filtering. Finally, the performances of the CNN model are assessed on test solutions never seen during training. The model retrieves burning rates with very high accuracy. It is also tested on two filter and downsampling parameters and two global equivalence ratios between those used during training. For these interpolation cases, the model approximates burning rates with low error even though the cases were not included in the training dataset. This a priori study shows that the proposed data-driven machine learning framework is able to address the challenge of modeling lean premixed

$ {\mathrm{H}}_2 $

-air burning rates. It paves the way for a new modeling paradigm for the simulation of carbon-free hydrogen combustion systems.
Building occupancy type classification and uncertainty estimation using machine learning and open data
Authors: Narock Tom , Johnson J. Michael , Singh-Mohudpur Justin , Modaresi Rad Arash 
Published: February 2025

Abstract
Federal and local agencies have identified a need to create building databases to help ensure that critical infrastructure and residential buildings are accounted for in disaster preparedness and to aid the decision-making processes in subsequent recovery efforts. To respond effectively, we need to understand the built environment—where people live, work, and the critical infrastructure they rely on. Yet, a major discrepancy exists in the way data about buildings are collected across the United SStates There is no harmonization in what data are recorded by city, county, or state governments, let alone at the national scale. We demonstrate how existing open-source datasets can be spatially integrated and subsequently used as training for machine learning (ML) models to predict building occupancy type, a major component needed for disaster preparedness and decision -making. Multiple ML algorithms are compared. We address strategies to handle significant class imbalance and introduce Bayesian neural networks to handle prediction uncertainty. The 100-year flood in North Carolina is provided as a practical application in disaster preparedness.