bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Impacts of Economic Policies, Policy Uncertainty, and Politics on Carbon Emissions
Authors: Chiou Wan-Jiun Paul , Fu Shan-Heng , Lin Jeng-Bau , Tsai Wei 
Published: January 2025

Abstract
Addressing climate change challenges through managing and mitigating CO2 emissions has taken center stage in shaping economic policies. This paper analyzes the intricate interplay among economic policies, their uncertainty, political dynamics, and CO2 emissions by utilizing the U.S. data from 1973 to 2024. Our empirical results derived from the autoregressive distributed lag (ARDL) model with dummy variables indicate that expansionary monetary policies and higher corporate tax rates may increase CO2 emissions. Political factors, including economic policy uncertainty and the political climate, yield long-term impacts on CO2 emissions. The dominant party in the legislative branch, but not the presidency, emerges as a key determinant in carbon dioxide emission control, underscoring the significance of consensus-building in democratic processes, yet with variation in effects across different chambers. The robustness of these key findings is reaffirmed through different models. The findings suggest that party affiliation does not always dictate environmental policy outcomes, emphasizing the complexity of policy formulation and its representation within legislative bodies, providing insight to decision-makers when economic policies are considered.
Promoting mathematical competence development through programming activities
Authors: Brandsæter Andreas , Berge Runar Lie 
Published: January 2025

Abstract
The reasons for teaching programming in school are indeed manifold. Programming can for example be utilized as a vehicle for understanding and learning particular mathematical subject matter, or as a tool for solving mathematical problems. In this paper, however, we propose to utilize programming as a vehicle for developing mathematical competencies such as problem-solving, exploration, modeling, reasoning, representation, generalization, and abstraction. We perform a design study utilizing a systematic, iterative development process for designing teaching sessions, focusing on one mathematical competence at a time. We apply the proposed methodology on a set of teaching sessions that are developed, implemented, and tested in a range of classroom settings. Based on this development process, we conclude that programming can be used to develop mathematical competencies. Furthermore, we identify a set of teacher practices that can be used to facilitate mathematical competence development in programming activities.
Trophy fish heads are a source of body size information for historical and contemporary ecology
Authors: O’Connell Matthew , Humphries Paul , Kopf R. Keller , Bond Jennifer , Spennemann Dirk H. R. , McCasker Nicole 
Published: January 2025

Abstract
This study investigated whether trophy taxidermy specimens of Australia’s largest freshwater fish, Murray cod (Maccullochella peelii), can provide accurate records of historical body size. Taxidermy mounts came mostly from informal collections in hotels from across the Murray–Darling Basin, south-eastern Australia, comprising 20% whole-body and 80% head forms. We compared the morphology of mounts to live Murray cod, collected from the mid–Murray River in 2018, and identified the head morphometrics that most accurately described length and weight of whole mounts and live fish. Eight morphological characters were analysed for 60 whole mounts, 172 head mounts and 51 live fish. We found that inter-orbital distance, inter-nare width and upper jaw length were relatively robust to taxidermy processes and were reliable features for predicting fish total length and total weight. Shrinkage in head morphometrics due to taxidermy was evident, however, and we recommend that this be considered when reconstructing length and weight measures. We discuss how estimated body length and weight from head morphometrics of trophy fish, coupled with analysis of the accompanying remaining tissue and hard parts, opens up opportunities to explore patterns in genetics, life history, movement and trophic ecology of historical fish populations and of past environments.
Hypomorphic RAG2 Deficiency Promotes Selection of Self-Reactive B Cells
Authors: Thouvenel Christopher D. , Tipton Christopher M. , Yamazaki Yasuhiro , Zhang Ting-ting , Rylaarsdam Stacey , Hom Jennifer R. , Snead Catherine , Zhu Chengsong , Li Quan-Zhen , Lee Yu Nee , Kawai Tomoki , Haque Neshatul , Zimmermann Michael T. , Ponnan Sivasankaran Munusamy , Jackson Shaun W. , James Rich G. , Sanz Ignacio , Notarangelo Luigi D. , Torgerson Troy R. , Ochs Hans D. , Rawlings David J. , Allenspach Eric J. 
Published: January 2025

Abstract
Reduced function or hypomorphic variants in recombination-activating genes (RAG) 1 or 2 result in a broad clinical phenotype including common variable immunodeficiency (CVID) and even adult-onset disease. Milder RAG variants are less characterized. Here we describe the longitudinal course of a milder combined RAG deficiency in 3 of 7 siblings sharing the same RAG2 mutations over a 50-year study. Whole-genome and repertoire sequencing, bacteriophage immunizations, and deep immunophenotyping were used to compare affected and unaffected family members. The clinical phenotype of three affected siblings with hypomorphic RAG deficiency ranged from combined immunodeficiency and early mortality to a late-onset CID with hyper-IgM phenotype. T cells were remarkably similar across affected siblings, yet CDR3 skewing and regulatory T cell defects were not observed. B cell analysis showed elevated unswitched CD27+ and CD21low cells as well as features of an autoreactive antibody repertoire and presence of secreted autoantibodies, yet no clinical autoimmunity was present. Most striking was an expanded polyclonal marginal zone-like B cell population (IgM+IgD+CD27+) utilizing the self-reactive unmutated VH4-34 receptor demonstrating that hypomorphic RAG deficiency can promote expansion of self-reactive B cells. This process, however, was not sufficient to trigger clinical autoimmunity. Utilizing multiple approaches, we functionally measured the specific RAG2 variant effects and assessed how selection and secondary triggers altered the BCR repertoire and immunophenotype overtime. Overall, we demonstrate a broad disease spectrum in siblings with identical hypomorphic RAG deficiency, highlighting that phenotypic divergence can result from expansion of IgM + memory B cells.
Forecasting Mortality Associated Emergency Department Crowding with LightGBM and Time Series Data
Authors: Nevanlinna Jalmari , Eidstø Anna , Ylä-Mattila Jari , Koivistoinen Teemu , Oksala Niku , Kanniainen Juho , Palomäki Ari , Roine Antti 
Published: January 2025

Abstract
Emergency department (ED) crowding is a global public health issue that has been repeatedly associated with increased mortality. Predicting future service demand would enable preventative measures aiming to eliminate crowding along with its detrimental effects. Recent findings in our ED indicate that occupancy ratios exceeding 90% are associated with increased 10-day mortality. In this paper, we aim to predict these crisis periods using retrospective time series data such as weather, availability of hospital beds, calendar variables and occupancy statistics from a large Nordic ED with a LightGBM model. We predict mortality associated crowding for the whole ED and individually for its different operational sections. We demonstrate that afternoon crowding can be predicted at 11 a.m. with an AUC of 0.82 (95% CI 0.78-0.86) and at 8 a.m. with an AUC up to 0.79 (95% CI 0.75-0.83). Consequently we show that forecasting mortality-associated crowding using time series data is feasible.
Ammonia and beyond – biomarkers of hepatic encephalopathy
Authors: Gallego Juan-José , Ballester María-Pilar , Fiorillo Alessandra , Casanova-Ferrer Franc , López-Gramaje Adrià , Urios Amparo , Arenas Yaiza María , Ríos María-Pilar , Durbán Lucía , Megías Javier , San-Miguel Teresa , Benlloch Salvador , Lluch Paloma , Jalan Rajiv , Montoliu Carmina 
Published: January 2025

Abstract
Ammonia is a product of amino acid metabolism that accumulates in the blood of patients with liver cirrhosis, leading to neurotoxic effects and hepatic encephalopathy (HE). HE manifestations can range from mild, subclinical disturbances in cognition, or minimal HE (mHE) to gross disorientation and coma, a condition referred to as overt HE. Many blood-based biomarkers reflecting these neurotoxic effects of ammonia and liver disease can be measured in the blood allowing the development of new biomarkers to diagnose cirrhosis patients at risk of developing HE. The effect of ammonia on the brain is modulated by severity of systemic inflammation, and both hyperammonemia and inflammation can induce oxidative stress, which may mediate the neurological alterations associated to HE. This review aims to provide the latest evidence on biomarkers of HE beyond ammonia. We present different approaches to predict overt HE based on the combination of blood ammonia with some analytical and clinical parameters. Magnetic resonance analysis of brain images could also provide sensitive diagnostic biomarkers based on neuroimaging parameters. Some reports suggest that markers of systemic inflammation, oxidative stress, and central nervous system-derived components, may serve as additional biomarkers of HE. The involvement of extracellular vesicles and microbiota in the pathophysiology of mHE and HE has recently acquired importance and it would be interesting to explore their usefulness as early biomarkers of the disease. It is important to have a biomarker or a combination of them for early diagnosis of mHE to improve its treatment and prevent progression to overt HE.
Strategic Communication and Evaluation to Improve the Capacities of Local Administration for Climate Change Adaptation: A Case Study on Dresden, Germany
Authors: Olfert Alfred , Hutter Gérard 
Published: January 2025

Abstract
Climate change increasingly affects human health, prosperity and the quality of life and increases the probability of disasters, thus calling for consistent answers by local administrations. The paper presents a case study on Capacity Building through professional training in Dresden, a local frontrunner in Germany. A minimum-standard design to output-to-outcome evaluation of the trainings is applied. Results show a highly differentiated effect on motivation factors and that the influence on the intention to act can remain weak even if other factors are enhanced. Hence, a strategic and comprehensive approach to Capacity Building is essential for disaster risk reduction.
Parametric insurance for climate adaptation in fisheries and aquaculture
Authors: Hobday Alistair J. , Little L. Richard , Watson James R. , Spillman Claire M. 
Published: January 2025

Abstract
Ensuring resilience and adaptability of the seafood sector in the face of accelerating climate change involves risk management and risk reduction. In a world where climate patterns are rapidly evolving, innovative financial instruments have a role to play in managing environmental risks and reducing exposure to these risks through climate adaptation. Here, we consider the application of parametric insurance—when a predetermined amount is paid out based on parameters chosen based on expected losses associated with extreme events. We offer insights into its utility, implementation, and limitations. We emphasise the role of ocean forecasting in developing and pricing parametric insurance products to help mitigate and adapt to climate-related risks in aquaculture and fisheries. Forecasting is essential for anticipating changing environmental conditions at a range of spatial and temporal scales and thus informing decision-making regarding resource allocation and adaptation strategies. Through both climate-aware insurance policy design and the provision of education, capacity-building programs, and financial support for industry transition, parametric insurance has the potential to help seafood producers navigate the challenges posed by climate change. Use of parametric insurance can facilitate a managed retreat from vulnerable or non-viable areas to more sustainable alternatives or livelihoods by reducing climate risk in a measured environment. This approach can also contribute to the long-term resilience of seafood industries and coastal communities while protecting the health of marine ecosystems.
Effect of administration of nanoparticles of human chorionic gonadotropin on testicular hemodynamics, testicular volume, testicular echotexture, and circulating testosterone and nitric oxide in pubescent goat bucks under heat stress conditions
Authors: Essam Mayada , ElSayed Mohamed A. I. , Youssef Fady Sayed , Samir Haney 
Published: January 2025

Abstract
The current study investigated the effect of a single administration of human chorionic gonadotropin hormone (hCG) and its nanoparticles (NPs) on testicular hemodynamics using Doppler ultrasonography, testicular volume, testicular echotexture (PIX), and circulating testosterone and nitric oxide (NO) in pubescent goat bucks during summer months. Fifteen Baladi goats were divided into three groups (5 in each) and subjected to a single intramuscular administration of one ml of physiological saline ( control group), one ml containing 500 IU of hCG (hCG group) or one ml containing 125 IU of hCG NPs (hCG NPs group). Testicular hemodynamics assessment was done just before administration (0 h), and at 2, 4, 6, 24, and daily till 7 days after administration. Testicular volume and PIX were measured and analyzed by B-mode ultrasonography and computer analysis software. Testosterone and NO concentrations were measured using commercial kits. Results revealed significant decreases (P ˂0.05) in Doppler indices values (resistance index and pulsatility index) especially at 24 h in the hCG group (0.314 ± 0.01, 0.382 ± 0.01, respectively) compared with the hCG NPs group (0.428 ± 0.01, 0.567 ± 0.02, respectively), and the control group (0.464 ± 0.006, 0.64 ± 0.01, respectively). There were significant increases (P < 0.001) in testicular volume, PIX, testosterone, and NO concentrations in hCG NPs and hCG groups compared to the control group. There were no significant differences between the hCG NPs and hCG groups (P ˃ 0.05) in testicular volume and PIX, while testosterone significantly increased in the hCG group compared to the hCG NPs group and NO was significantly increased in the hCG NPs group compared to the hCG group. In conclusion, a single administration of hCG or its NPs improved testicular vascularization, testicular volume, and circulating testosterone and NO in pubescent goat bucks. So, hCG NPs could be recommended for improving the reproductive performance of goat bucks under heat-stress conditions.
Unsupervised Semantic Segmentation of Urban Scenes via Cross-Modal Distillation
Authors: Vobecky Antonin , Hurych David , Siméoni Oriane , Gidaris Spyros , Bursuc Andrei , Pérez Patrick , Sivic Josef 
Published: January 2025

Abstract
Semantic image segmentation models typically require extensive pixel-wise annotations, which are costly to obtain and prone to biases. Our work investigates learning semantic segmentation in urban scenes without any manual annotation. We propose a novel method for learning pixel-wise semantic segmentation using raw, uncurated data from vehicle-mounted cameras and LiDAR sensors, thus eliminating the need for manual labeling. Our contributions are as follows. First, we develop a novel approach for cross-modal unsupervised learning of semantic segmentation by leveraging synchronized LiDAR and image data. A crucial element of our method is the integration of an object proposal module that examines the LiDAR point cloud to generate proposals for spatially consistent objects. Second, we demonstrate that these 3D object proposals can be aligned with corresponding images and effectively grouped into semantically meaningful pseudo-classes. Third, we introduce a cross-modal distillation technique that utilizes image data partially annotated with the learnt pseudo-classes to train a transformer-based model for semantic image segmentation. Fourth, we demonstrate further significant improvements of our approach by extending the proposed model using a teacher-student distillation with an exponential moving average and incorporating soft targets from the teacher. We show the generalization capabilities of our method by testing on four different testing datasets (Cityscapes, Dark Zurich, Nighttime Driving, and ACDC) without any fine-tuning. We present an in-depth experimental analysis of the proposed model including results when using another pre-training dataset, per-class and pixel accuracy results, confusion matrices, PCA visualization, k-NN evaluation, ablations of the number of clusters and LiDAR’s density, supervised finetuning as well as additional qualitative results and their analysis.
Deep Radiogenomics Sequencing for Breast Tumor Gene-Phenotype Decoding Using Dynamic Contrast Magnetic Resonance Imaging
Authors: Shiri Isaac , Salimi Yazdan , Mohammadi Kazaj Pooya , Bagherieh Sara , Amini Mehdi , Saberi Manesh Abdollah , Zaidi Habib 
Published: January 2025

Abstract

Purpose
We aim to perform radiogenomic profiling of breast cancer tumors using dynamic contrast magnetic resonance imaging (MRI) for the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) genes.

Methods
The dataset used in the current study consists of imaging data of 922 biopsy-confirmed invasive breast cancer patients with ER, PR, and HER2 gene mutation status. Breast MR images, including a T1-weighted pre-contrast sequence and three post-contrast sequences, were enrolled for analysis. All images were corrected using N4 bias correction algorithms. Based on all images and tumor masks, a bounding box of 128 × 128 × 68 was chosen to include all tumor regions. All networks were implemented in 3D fashion with input sizes of 128 × 128 × 68, and four images were input to each network for multi-channel analysis. Data were randomly split into train/validation (80%) and test set (20%) with stratification in class (patient-wise), and all metrics were reported in 20% of the untouched test dataset.

Results
For ER prediction, SEResNet50 achieved an AUC mean of 0.695 (CI95%: 0.610–0.775), a sensitivity of 0.564, and a specificity of 0.787. For PR prediction, ResNet34 achieved an AUC mean of 0.658 (95% CI: 0.573–0.741), a sensitivity of 0.593, and a specificity of 0.734. For HER2 prediction, SEResNext101 achieved an AUC mean of 0.698 (95% CI: 0.560–0.822), a sensitivity of 0.750, and a specificity of 0.625.

Conclusion
The current study demonstrated the feasibility of imaging gene-phenotype decoding in breast tumors using MR images and deep learning algorithms with moderate performance.
First Detection of Arsenophonus in Potato Crop in Switzerland: A Threat for the Processing Industry?
Authors: Mahillon Mathieu , Bussereau Floriane , Dubuis Nathalie , Brodard Justine , Debonneville Christophe , Schumpp Olivier 
Published: January 2025

Abstract
The phloem-restricted phytopathogenic bacterium Candidatus Arsenophonus phytopathogenicus (Ap) causes the “syndrome basses richesses” (SBR), which has recently emerged as a major burden for sugar beets in several countries of Western Europe. Here, we report the first identification of Ap and its planthopper vector Pentastiridius leporinus in potato fields in Switzerland in 2023. The bacterium was detected in potato plants and tubers exhibiting phytoplasma-like symptoms and collected from cantons currently experiencing SBR outbreaks. Although our analyses indicate the absence of the Stolbur phytoplasma, the pathogenicity of Ap in potato remains unclear, a fortiori in the context of the poor phytosanitary status of crops in Switzerland in 2023. In infected tubers, we show that Ap can be detected after dormancy from the stem end to the emerging sprouts with decreasing titers. Importantly, Ap might induce threadlike sprouts and the browning of the flesh upon frying, raising strong concerns for varieties marketed for chips production. Altogether, our results align with recent studies performed in Germany, highlighting the host shift of Ap and its vector from sugar beet to potato crops. Our data should raise awareness in other European countries where the presence of the bacterium has been recently described.
Supporting innovating employees: how managerial coaching affects four dimensions of innovative work behavior
Authors: Pajuoja Maria , Viitala Riitta , Henttonen Kaisa 
Published: January 2025

Abstract
SMEs rely on innovation, and individual employees come up with and implement ideas to act as the microfoundations of organizational innovation. Managers play a critical role in encouraging employees’ innovative work behavior. However, thus far, this relationship has been studied utilizing a one-dimensional construct, and little is known about whether a determinant affects all phases of the innovation process equally. We investigate the effect of managerial coaching– managers coaching their employees to improve performance– on four dimensions of innovative work behavior. We show that managerial coaching positively influences innovative behavior in organizations, but is least important when employees explore ideas and most important when they implement ideas. We also find that employees tend to be more comfortable exploring and generating ideas than championing and implementing them, indicating innovation potential at the employee level which can be unlocked if managers know how to coach employees at the right time.
Twenty Years of Neuroinformatics: A Bibliometric Analysis
Authors: Guillén-Pujadas Miguel , Alaminos David , Vizuete-Luciano Emilio , Merigó José M. , Van Horn John D. 
Published: January 2025

Abstract
This study presents a thorough bibliometric analysis of Neuroinformatics over the past 20 years, offering insights into the journal’s evolution at the intersection of neuroscience and computational science. Using advanced tools such as VOS viewer and methodologies like co-citation analysis, bibliographic coupling, and keyword co-occurrence, we examine trends in publication, citation patterns, and the journal’s influence. Our analysis reveals enduring research themes like neuroimaging, data sharing, machine learning, and functional connectivity, which form the core of Neuroinformatics. These themes highlight the journal’s role in addressing key challenges in neuroscience through computational methods. Emerging topics like deep learning, neuron reconstruction, and reproducibility further showcase the journal’s responsiveness to technological advances. We also track the journal’s rising impact, marked by a substantial growth in publications and citations, especially over the last decade. This growth underscores the relevance of computational approaches in neuroscience and the high-quality research the journal attracts. Key bibliometric indicators, such as publication counts, citation analysis, and the h-index, spotlight contributions from leading authors, papers, and institutions worldwide, particularly from the USA, China, and Europe. These metrics provide a clear view of the scientific landscape and collaboration patterns driving progress. This analysis not only celebrates Neuroinformatics’s rich history but also offers strategic insights for future research, ensuring the journal remains a leader in innovation and advances both neuroscience and computational science.
Bulbophyllum halmaherae (Orchidaceae), an unusual species of section Polymeres from Halmahera, Maluku, Indonesia
Authors: Mustaqim Wendy A. , Yudistira Yuda R. , Jacop Sandy , Schuiteman André 
Published: January 2025

Summary

Bulbophyllum halmaherae Mustaqim, Yudistira, Jacop & Schuit. (Orchidaceae), a distinctive new species of sect. Polymeres, is described and illustrated. A detailed description, morphological comparisons, habitat information, a preliminary conservation assessment and a brief discussion are provided.