bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Personal Story of ‘Coincidence’ in Becoming an Academic and Early Career Researcher: Being Creative to Push Boundaries
Authors: McKnight Anthony 
Published: December 2024

AbstractDr. Anthony McKnight’s chapter is infused with stories of lessons from Elders and family. Dr. McKnight explains that the chapter might be confusing for some readers, reflecting his own academic journey and mirroring the way Elders often indirectly guide community through convoluted stories. We see an example of Aunty pedagogy and the capacity to maintain connection through discourse. The chapter is a powerful insight into the intersecting tensions between not forgetting where you come from, latent community fear of losing their young people to Western education systems, and community expectations and the responsibility of being an Indigenous person doing doctoral work. Using that most ordinary, everyday item, the humble potato chip, Dr. McKnight seeks to distill his experiences and lessons learned into an instructive poem.
Dimension-8 SMEFT contact-terms for vector-pair production via on-shell Higgsing
Authors: Goldberg Jared M. , Liu Hongkai , Shadmi Yael 
Published: December 2024

Abstract
We derive the dimension-8 standard-model effective theory (SMEFT) contact terms relevant for vector-pair production at the LHC and lepton colliders. We first list the relevant dimension-8 massless SMEFT amplitudes, and then obtain the low-energy amplitudes using on-shell Higgsing. In all cases, the contributions we calculate are the leading-order contributions to 4-point contact-terms; the dimension-6 SMEFT merely corrects the three-point couplings entering the amplitudes. Since they are given in terms of physical quantities, namely momenta and polarizations, the results allow for a direct mapping of EFT effects to low-energy observables. The vector amplitudes are sensitive to both anomalous vector couplings and Higgs self-couplings. The left-handed fermion amplitudes feature SU(2) violating effects first generated at dimension-8. We also compare our results to HEFT predictions. Interestingly, the dimension-8 SMEFT populates almost all the novel structures generated by the dimension-8 HEFT.
Weak rates in strongly coupled cold quark matter
Authors: Hoyos Carlos , Olzi Andrea , Rodriguez-Fernandez David 
Published: December 2024

Abstract
The rates of flavor-changing weak processes are crucial in determining the conditions of beta equilibrium in neutron stars and mergers, influencing the damping of oscillations, the stability of rotating pulsars, and the emission of gravitational waves. We derive a formula for these rates at nonzero temperature, to leading order in the Fermi coupling and exact in the QCD coupling. Utilizing a simple phenomenological holographic model dual to QCD, we study massless unpaired quark matter at high densities. We numerically compute the rate for small deviations from beta equilibrium and derive an analytic approximation for small temperatures. Our findings reveal that, compared to the perturbative result, the rate is suppressed by logarithmic factors of the temperature.
The next-to-leading order Higgs impact factor at physical top mass: the real corrections
Authors: Celiberto Francesco Giovanni , Rose Luigi Delle , Fucilla Michael , Gatto Gabriele , Papa Alessandro 
Published: December 2024

Abstract
We compute the real corrections to the impact factor for the production of a forward Higgs boson, retaining full top-mass dependence. We demonstrate that the rapidity divergence is the one predicted by the BFKL factorization and perform the explicit subtraction in the BFKL scheme. We show that the IR-structure of the impact factor is the expected one and that, in the infinite-top-mass approximation, the previously known result is recovered. We also verify that the impact factor vanishes when the transverse momenta of the t-channel Reggeon goes to zero, in agreement with its gauge-invariant definition, exploiting the mt → ∞ expansion up to the next-to-next-to-leading order.
Clinical relevance of feto-maternal microchimerism in (hematopoietic stem cell) transplantation
Authors: Kruchen Anne , Fehse Boris , Müller Ingo 
Published: December 2024

AbstractToleration of a semi-allogeneic fetus in the mother’s uterus as well as tolerance after allogeneic hematopoietic stem cell transplantation (HSCT) appear to share some immunologic concepts. The existence of microchimeric cells, and the original idea of a bidirectional cell trafficking between mother and child during pregnancy have been known for decades. Today, origins and mechanisms of persistence of microchimeric cells are intensively being elucidated. Both, the translation of the phenomenon of feto-maternal immune tolerance to donor choice or prevention of graft-versus-host disease (GvHD) in HSCT, and the implications of microchimeric cells in and for HSCT are highly intriguing. Yet, differences in detection methods of microchimeric cells, as well as in transplantation protocols impede the comparison of larger cohorts, and limit potential clinical advice. Still, matching of non-inherited maternal antigens (NIMA), which are expressed on maternal microchimeric cells, demonstrated a strong association with decreased risk for the development of acute GvHD in the context of various transplantation strategies. Despite the fact that advances in graft manipulation and immunosuppression ameliorated the safety and outcome after HSCT, NIMA-matching retained a beneficial role in selection of sibling, child, or maternal donors, as well as for cord blood units. Recent findings indicate the existence of a microchimeric stem cell niche, in which only one dominant microchimeric cell population of only one semi-allogeneic origin persists at a time. This implies that studies regarding the impact of (maternal and fetal) microchimerism (MC) on clinical outcome of HSCT should combine analysis of NIMA and direct detection of microchimeric cells from donor and recipient on the verge of HSCT to be efficiently conclusive.
Changing the Inoculum Type From Preculture to Spore Suspension Markedly Alters the Production of Secondary Metabolites in Filamentous Microbial Coculture
Authors: Boruta Tomasz , Pawlikowska Weronika , Foryś Martyna , Englart Grzegorz , Ścigaczewska Anna 
Published: December 2024

AbstractThe shake flask cocultures of Aspergillus terreus and Streptomyces rimosus were investigated with regard to the production of mevinolinic acid (lovastatin), oxytetracycline, and other secondary metabolites (SMs). The aim of the study was to determine the effect of inoculum type (spore suspension or preculture) on the levels of SMs in the fermentation broth. Altogether, 17 SMs were detected, including 4 products with confirmed identities, 10 putatively annotated metabolites, and 3 unknown molecules. As observed over the course of qualitative and quantitative analyses, the selection of inoculum type markedly influenced the SM-related outcomes of cocultures. Depending on the coculture initiation procedure, replacing the preculture with spore inoculum positively affected the biosynthesis of oxytetracycline, butyrolactone I, (+)-geodin, as well as the molecules putatively identified as rimocidin, CE-108, and (+)-erdin. It was concluded that the comparative analyses of SM production in filamentous microbial cocultures and monocultures are dependent on the type of inoculum and thus the diversification of inocula is highly recommended in such studies. Furthermore, it was demonstrated that designing a coculture experiment that involves only a single type of inoculum may lead to the underestimation of biosynthetic repertoires of filamentous microorganisms.
Associations between dietary macronutrient composition and cardiometabolic health: data from NHANES 1999–2014
Authors: Koemel Nicholas A. , Senior Alistair M. , Laouali Nasser , Celermajer David S. , Grech Amanda , Parker Helen M. , Simpson Stephen J. , Raubenheimer David , Gill Timothy P. , Skilton Michael R. 
Published: December 2024

Abstract

Purpose
Dietary macronutrients significantly impact cardiometabolic health, yet research often focuses on individual macronutrient relationships. This study aimed to explore the associations between dietary macronutrient composition and cardiometabolic health.

Methods
This study included 33,681 US adults (49.7 ± 18.3 years; 52.5% female) from the National Health and Nutrition Examination Survey during 1999–2014. Dietary data was derived from 1 to 2 separate 24-hour recalls and cardiometabolic health included lipid profile, glycemic control, blood pressure, and adiposity collected in a mobile examination center. Associations between dietary macronutrient composition and cardiometabolic health were examined using generalized additive models adjusted for age, socio-demographics, lifestyle, and diet quality.

Results
In females, triglycerides (P < 0.01) and HDL cholesterol (P < 0.01) were the least optimal in diets containing lower fat (10%) and higher carbohydrate (75%). In males, HDL cholesterol was positively associated with fat (P < 0.01) and no association with triglycerides was detected. Total-C associations were male specific (P = 0.01) and highest in diets composed of 25% protein, 30% carbohydrate, and 45% fat. In both sexes, systolic blood pressure (P ≤ 0.02) was highest in diets containing lower fat (10%) coupled with moderate protein (25%). Diastolic blood pressure associations were female specific (P < 0.01) with higher values in those consuming the upper range of fat (55%). There were no associations of macronutrient composition with glycemic control or adiposity.

Conclusion
This study revealed sex-specific relationships between macronutrient composition and cardiometabolic health. Future research is needed to explore these relationships across age groups.
Laryngeal dystonia and vocal tremor response to botulinum toxin injection
Authors: Pinto João Viana , López Isabel García 
Published: December 2024

Abstract

Purpose
The main objective of this study was to compare laryngeal dystonia (LD) and vocal tremor’s (VT) response to botulinum toxin injection.

Methods
Retrospective study including every patient with LD or VT injected with botulinum toxin guided by electromyography, from January 1, 2010, to September 30, 2022, at a tertiary hospital centre. Improvement was assessed with the VHI-10, grade of dysphonia in a visual analogue scale (VAS; 0–10), GRBAS(I) scale (0–3) and maximum phonation time (MPT).

Results
A total of 77 patients were included, 44 patients with LD and 33 with VT. There were no differences between groups on pre-treatment VHI-10, grade of dysphonia in the VAS, MPT and G, R, B, A and I at diagnosis (p > 0.05). S was significantly higher in patients with LD (p < 0.001). After the first injection, both groups showed an increase in the grade of dysphonia on the VAS and a decrease in VHI-10, G, S and I (p < 0.05), with a higher variation in the VAS and S parameters in the LD group compared to VT (p < 0.05). In the 54 patients that performed two or more injections, G, S and I had a higher decrease in patients with LD when compared to patients with VT (p < 0.05).

Conclusion
BTX injection was successful in improving the VHI-10, grade of dysphonia on the VAS and G, S and I in the GRBAS-I scale for both DT and VT. LD seems to have a better response to BTX in comparison to VT.
A review of short-term weather impacts on honey production
Authors: Vincze Csilla , Leelőssy Ádám , Zajácz Edit , Mészáros Róbert 
Published: December 2024

Abstract
Beekeeping is an exceptionally weather-sensitive agricultural field. Honey production and pollination services depend on the complex interaction of plants and bees, both of which are impacted by short-term weather changes. In this review, classical and recent research is collected to provide an overview on short-term atmospheric factors influencing honey production, and the optimal and critical weather conditions for bee activity. Bee flight can be directly obstructed by precipitation, wind, extreme temperatures and also air pollution. Bees generally fly within a temperature range of 10–40 °C, with optimal foraging efficiency occurring between 20 and 30 °C. Wind speeds exceeding 1.6–6.7 m/s can reduce foraging efficiency. Additionally, bee activity is significantly correlated with temperature, relative humidity and solar radiation, factors which influence nectar production. Optimal conditions for nectar collection typically occur in the morning and early afternoon hours with mild and moist weather. The diurnal nectar collection habit of bees adjusts to the nectar production of individual plant species. Extreme weather occurring in the sensitive hours is noticeable both in the nectar production of plants and in the activity of bees, thus in the honey yield. Understanding the impact of weather on honey bees is crucial in the management and planning of honey production. This review highlights the importance of studying these interactions to better adapt beekeeping practices to changing environmental conditions.

Graphical Abstract
A real-time platform for Spanish Sign Language interpretation
Authors: Morillas-Espejo Francisco , Martinez-Martin Ester 
Published: December 2024

Abstract
More than 13% of the Spanish population suffers from hearing impairment. Despite the existence of several hearing aids and implants making sounds clearer and louder, there are some people unable to use them and, consequently, their only means of communication is Sign Language. However, this language is not widely known in the society. Consequently, those who are deaf or hard of hearing may be socially excluded and experience frustration as a result of the lack of communication. In this context, Sign Language Recognition and interpretation would help to break down the existing communication barriers and facilitate the creation of inclusive environments. With that aim, this paper presents a real-time platform to recognize and interpret finger-spelt words in Spanish Sign Language (Lengua de Signos Española). As finger spelling implies the recognition of each signed letter, a comparative analysis of different deep learning techniques to properly recognize the Spanish Sign Language alphabet has been carried out. For that, due to the lack of Spanish Sign Language datasets, the first step was to capture and build an image dataset representing its 30 letters. As there are static and in-motion letters, spatial and temporal analysis has been conducted by considering different kind of neural networks (Convolutional Neural Networks, Recurrent Neural Networks, and Vision Transformers). The experimental results highlight the good performance of the studied architectures, obtaining a maximum accuracy of 79.96% on previously unseen data. Finally, a real-time platform for the recognition and interpretation of finger-spelt words in Spanish Sign Language has been implemented making the communication possible.
Optimization of workflow processes for sustainable paternal involvement: case study of an academic “daddy surgeon” in Japan
Authors: Kanaya Nobuhiko , Kuroda Shinji , Kondo Yoshitaka , Takehara Yuko , Kakiuchi Yoshihiko , Minagi Hitoshi , Sakamoto Masaki , Kagawa Shunsuke , Kataoka Hitomi , Fujiwara Toshiyoshi 
Published: December 2024

AbstractWork–life balance is often discussed in Japan. Yet surgeons find it challenging to take paternity leave because of their demanding surgical duties and a strong sense of responsibility. One Japanese male surgeon had his first paternity experience as a research fellow in the US. When he returned to Japan, he resumed his surgical training and started a research project to become an academic surgeon. When he and his wife were expecting their second child, they discussed his paternity participation before the delivery and decided on a sustainable paternity participation plan. By coordinating his responsibilities with his co-workers, he limited his attendance at work to daytime hours only for 1 month to manage paternity duties. This adjustment did not affect the number of main and assistant operations conducted that month and effective optimization of workflow processes decreased the extra workload for other team members. His experience suggests that the optimization of workflow processes can enhance personal life, including paternity participation. (150/150).
On the use of feed-forward neural networks in the context of surrogate aeroelastic simulations
Authors: Roccia Bruno A. , Ruiz Marcelo , Gebhardt Cristian G. 
Published: December 2024

AbstractFor a few decades now, the proliferation of digital computers has driven the development of increasingly complex models to study the physical phenomena that are part of our reality. Particularly, in the field of aeronautics and renewable energy (wind), correct aeroelastic modeling is crucial for many reasons: structural and aerodynamic optimization, determining operational envelopes, and avoiding destructive aeroelastic phenomena such as divergence or flutter, among others. Furthermore, the study of systems involving multiple fields of physics (aerodynamics, structural dynamics, control, etc.) is characterized by exhibiting highly nonlinear phenomena (limit cycle oscillations, bifurcations, chaos, etc.), which are very challenging to capture with linear approximations or simplified models. In this work, we present a comprehensive statistical analysis of the performance of shallow feed-forward neural networks (FNNs) to capture supercritical Hopf bifurcations when dealing with aeroelastic flutter. The FNNs are trained by considering data sets generated by using two different aeroelastic models of increasing complexity. For the structural model, we consider a two-degree-of-freedom model consisting of an airfoil oscillating in pitch and plunge. The aerodynamic forces are accounted for by using two different flow solvers: (1) a non-compressible two-dimensional linear (but ergodic) model based on Wagner’s theory (referred as Fung’s model), which results in analytical expressions for the lift and aerodynamic moment, and (2) a two-dimensional version of the well-known unsteady vortex-lattice method (UVLM). The assessment of the resulting FNN-based models is carried out through a Monte Carlo experiment over R replicates. As a measure of performance, we use the mean-squared error test associated with the estimators, here the system’s response and its consistent aerodynamic coefficients. We also discuss, in detail, the behavior of FNN-based surrogate aeroelastic frameworks when they are trained with data coming from Fung-based or UVLM-based aeroelastic simulations. Furthermore, we highlight a number of challenges faced by shallow FNNs, as well as some difficulties when integrated into surrogate aeroelastic environments. Finally, we provide explanations to questions raised throughout the article and conjecture some others without a definitive answer.
Novel affibody molecules targeting the AXL extracellular structural domain for molecular imaging and targeted therapy of gastric cancer
Authors: Zhang HuiHui , Zheng Maolin , Cai YiQi , Kamara Saidu , Chen Jun , Zhu Shanli , Zhang Lifang 
Published: December 2024

Abstract
Gastric cancer (GC) has a poor prognosis and high mortality because it is often diagnosed at an advanced stage. Targeted therapeutics are considered an important class for advanced GC treatment. However, the fewer effective therapeutic targets and the poor coverage of the GC population limit the use of GC targeted therapies. Recent research suggests that the AXL receptor tyrosine kinase (AXL) plays an vital role in the survival and proliferation of GC cells, and blocking AXL pathway may be an effective strategy for targeted therapies. On the other hand, the affibody molecule, with its small size and faster penetration of tissue, has great potential in tumor imaging and targeted therapy. In this study, we report the novel AXL-binding affibody molecules (ZAXL:239) screened by a phage-displayed peptide library. The ZAXL:239 could specifically bind and interact with AXL proteins in vitro and in vivo, as demonstrated by surface plasmon resonance, co-immunoprecipitation, immuno-fluorescence co-localization, and near infrared fluorescent imaging. In addition, ZAXL:239 affibody molecules could significantly inhibit the proliferative activity and induce apoptosis of AXL-positive GC cells by decreasing the phosphorylation levels of the PI3K/AKT1 and MEK/ERK pathway, leading to the suppression of the downstream nuclear protein c-myc. Moreover, ZAXL:239 was found to have significant anti-tumor effects in AXL-positive GC transplantation tumor nude mouse models. In brief, we provide strong evidence that the novel ZAXL:239 affibody molecules have great potential as a potent tumor-specific molecular imaging and targeted therapeutic agents for GC.
Conceptual modelling of temporality and subjectivity as cross-cutting concerns
Authors: Gonzalez-Perez Cesar 
Published: December 2024

AbstractConceptual models represent the world, but the world changes over time, and is different, to some extent, depending on who you ask. To cater for these aspects, conceptual models must address the representation of temporality and subjectivity. Although some work has been done to incorporate these aspects into conceptual modelling languages, no mainstream language incorporates explicit support for temporality and subjectivity in relation to the existence and predication on the represented entities. In this article, I propose an approach to conceptualising and implementing temporality and subjectivity into conceptual modelling languages as cross-cutting aspects that provide built-in language primitives to the modeller while not imposing any particular manner to represent time or subjects. The approach has been adopted by ConML, a conceptual modelling language geared towards the humanities and social sciences, implemented in the Bundt software tool, and applied to a number of research projects.
Deep mining the textual gold in relation extraction
Authors: Sharma Tanvi , Emmert-Streib Frank 
Published: December 2024

AbstractRelation extraction (RE) is a fundamental task in natural language processing (NLP) that seeks to identify and categorize relationships among entities referenced in the text. Traditionally, RE has relied on rule-based systems. Still, recently, a variety of deep learning approaches have been employed, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), and bidirectional encoder representations from transformers (BERT). This review aims to provide a comprehensive overview of relation extraction, focusing on deep learning models. Given the complexity of the RE problem, we will present it from a multi-dimensional perspective, covering model steps, relation types, method types, benchmark datasets, and applications. We will also highlight both historical and current research in the field, identifying promising research areas for further development and emerging directions. Specifically, we will focus on potential enhancements for relation extraction from poorly labeled data and provide a detailed assessment of current shortcomings in handling complex real-world situations.