bluuebunny/crossref_metadata_2025_split huggingface dataset:
Very-early-onset Inflammatory Bowel Disease in an Infant with a Partial RIPK1 Deletion
Authors: Tuna Kırsaçlıoğlu Ceyda , Frohne Alexandra , Kuloğlu Zarife , Kristofersdottir Isidora , Demir Engin , Altuntaş Cansu , Haskoloğlu Zehra Şule , Çobanoğlu Fatma Nazan , Kendirli Tanıl , Özdemir Halil , Özçakar Zeynep Birsin , Savaş Berna , Doğu Figen , İkincioğulları Aydan , Boztug Kaan , Kansu Aydan 
Published: April 2024

AbstractThe monogenic causes of very-early-onset inflammatory bowel disease (VEO-IBD) have been defined by genetic studies, which were usually related to primary immunodeficiencies. Receptor-interacting serine/threonine-protein kinase-1 (RIPK1) protein is an important signalling molecule in inflammation and cell death pathways. Its deficiency may lead to various clinical features linked to immunodeficiency and/or inflammation, including IBD. Here, we discuss an infant with malnutrition, VEO-IBD, recurrent infections and polyathritis who has a homozygous partial deletion in RIPK1 gene.
Rethinking Regularization with Random Label Smoothing
Authors: dos Santos Claudio Filipi Gonçalves , Papa João Paulo 
Published: April 2024

AbstractRegularization helps to improve machine learning techniques by penalizing the models during training. Such approaches act in either the input, internal, or output layers. Regarding the latter, label smoothing is widely used to introduce noise in the label vector, making learning more challenging. This work proposes a new label regularization method, Random Label Smoothing, that attributes random values to the labels while preserving their semantics during training. The idea is to change the entire label into fixed arbitrary values. Results show improvements in image classification and super-resolution tasks, outperforming state-of-the-art techniques for such purposes.
The Politics of Personal Crisis: How Life Disruptions Shape Political Participation
Authors: Ojeda Christopher , Michener Jamila , Haselswerdt Jake 
Published: April 2024

AbstractEconomic risk and instability are urgent and central facts in the lives of increasing numbers of Americans. Though experienced as “personal,” the causes of life disruptions like unemployment, eviction, and loss of health insurance are also deeply political. In this paper, we build on existing “single crisis” studies to offer a comprehensive theoretical and empirical picture of how life disruptions shape political behavior. We use several large surveys to show that personal crises generally dampen turnout but sometimes spur other political acts. We also find that highly politicized crises (such as those related to COVID) boost all forms of participation. Our findings speak to the importance of considering life disruptions in the study of political behavior, particularly in an era when the lives of Americans are especially precarious.
Longitudinal effects of socioeconomic status on first and second language reading development: evidence from Chinese children learning English
Authors: Pan Jinger , McBride Catherine , Kwan Joyce Lok Yin , Shu Hua 
Published: April 2024

AbstractWhile it has been shown that socioeconomic status (SES) is important for children’s literacy development in their first language (L1), less is known about its association with reading in a second language (L2). The present study examined the different effects of SES on the acquisition of reading in Chinese as L1 and English as L2 from ages 7 to 11, among 291 Chinese children. The results showed that the contribution of SES to Chinese word reading was not significant. In contrast, SES significantly predicted English word reading. Mediation analyses revealed that SES had direct and indirect effects on English word reading, through phonological awareness and letter name knowledge, but only an indirect effect on Chinese word reading through phonological awareness and vocabulary knowledge. These findings highlight the importance of SES for reading acquisition in L2, and the influence of language-specific characteristics on the cognitive/linguistic skills required to master reading in a specific language.
Population growth of two limno-terrestrial Antarctic microinvertebrates in different aqueous soil media
Authors: McCarthy Jordan S. , Brown Kathryn E. , King Catherine K. , Nielsen Uffe N. , Plaisted Katie , Wallace Stephanie M. N. , Reichman Suzie M. 
Published: April 2024

AbstractTerrestrial microinvertebrates provide important carbon and nutrient cycling roles in soil environments, particularly in Antarctica where larger macroinvertebrates are absent. The environmental preferences and ecology of rotifers and tardigrades in terrestrial environments, including in Antarctica, are not as well understood as their temperate aquatic counterparts. Developing laboratory cultures is critical to provide adequate numbers of individuals for controlled laboratory experimentation. In this study, we explore aspects of optimising laboratory culturing for two terrestrially sourced Antarctic microinvertebrates, a rotifer (Habrotrocha sp.) and a tardigrade (Acutuncus antarcticus). We tested a soil elutriate and a balanced salt solution (BSS) to determine their suitability as culturing media. Substantial population growth of rotifers and tardigrades was observed in both media, with mean rotifer population size increasing from 5 to 448 ± 95 (soil elutriate) and 274 ± 78 (BSS) individuals over 60 days and mean tardigrade population size increasing from 5 to 187 ± 65 (soil elutriate) and 138 ± 37 (BSS) over 160 days. We also tested for optimal dilution of soil elutriate in rotifer cultures, with 20–80% dilutions producing the largest population growth with the least variation in the 40% dilution after 36 days. Culturing methods developed in this study are recommended for use with Antarctica microinvertebrates and may be suitable for similar limno-terrestrial microinvertebrates from other regions.
Soil organic carbon as an indicator of land use impacts in life cycle assessment
Authors: De Laurentiis Valeria , Maier Stephanie , Horn Rafael , Uusitalo Ville , Hiederer Roland , Chéron-Bessou Cécile , Morais Tiago , Grant Tim , Milà i Canals Llorenç , Sala Serenella 
Published: April 2024

Abstract
Purpose
Anthropogenic activities are a major driver of soil and land degradation. Due to the spatial heterogeneity of soil properties and the global nature of most value chains, the modelling of the impacts of land use on soil quality for application in life cycle assessment (LCA) requires a regionalised assessment with global coverage. This paper proposes an approach to quantify the impacts of land use on soil quality, using changes in soil organic carbon (SOC) stocks as a proxy, following the latest recommendation of the Life Cycle Initiative.

Methods
An operational set of SOC-based characterisation factors for land occupation and land transformation were derived using spatial datasets (1 km resolution) and aggregated at the national and global levels. The developed characterisation factors were tested by means of a case study analysis, investigating the impact on soil quality caused by land use activities necessary to provide three alternative energy supply systems for passenger car transport (biomethane, ethanol, and solar electricity). Results obtained by applying characterisation factors at local, regional, and national levels were compared, to investigate the role of the level of regionalisation on the resulting impacts.

Results and discussion
Global maps of characterisation factors are presented for the 56 land use types commonly used in LCA databases, together with national and global values. Urban and industrial land uses present the highest impacts on SOC stocks, followed by severely degraded pastures and intensively managed arable lands. Instead, values obtained for extensive pastures, flooded crops, and urban green areas often report an increase in SOC stocks. Results show that the ranking of impacts of the three energy systems considered in the case study analysis is not affected by the level of regionalisation of the analysis. In the case of biomethane energy supply, impacts assessed using national characterisation factors are more than double those obtained with local characterisation factors, with less significant differences in the other two cases.

Conclusions
The integration of soil quality aspects in life cycle impact assessment methods is a crucial challenge due to the key role of soil conservation in ensuring food security and environmental protection. This approach allows the quantification of land use impacts on SOC stocks, taken as a proxy of soil quality. Further research needs to improve the assessment of land use impacts in LCA are identified, such as the ability to reflect the effects of agricultural and forestry management practices.
Dissipation-based life cycle impact assessment of mineral resource use—a review, case study, and implications for the product environmental footprint
Authors: Berger Markus 
Published: April 2024

Abstract
Purpose
Impacts of mineral resource use on the availability of resources can be assessed using a broad range of methods. Until recently, life cycle inventory (LCI) and life cycle impact assessment (LCIA) models have been based on resource extraction. As extracted resources are not necessarily “lost” for future use, recent methodological developments have shifted the focus from resource extraction to resource dissipation. This paper aims at reviewing dissipation-based LCIA methods, testing them in a case study, analyzing potential implications for the product environmental footprint (PEF), and providing recommendations for future method development.

Method
Five recently developed LCIA methods have been reviewed and compared based on 22 criteria, such as the forms and time horizons of dissipation considered, scientific publication, and number of characterization factors (CFs). Additionally, the abiotic depletion potential (ADP) method has been included to serve as a non-dissipation-based reference. All methods are tested in a case study on a theoretical product, designed solely for demonstration purposes, and consisting of 1 kg of the metals aluminum, cobalt, copper, molybdenum, nickel, and zinc. In addition to the absolute LCIA results, the contributions of metal production stages and individual resource extractions/emissions have been investigated. Finally, normalization and weighting have been carried out to analyze consequences of replacing ADP with the new dissipation-based methods in the context of PEF.

Results and discussion
Most recently developed LCIA methods take a long-term perspective, cover emissions of resources to the environment (and partly technosphere), and vary in the number of CFs and resources covered. The case study results obtained by ADP are dominated by the molybdenum dataset; the results of the dissipation-based LCIA methods are strongly influenced by the cobalt dataset. All results are strongly sensitive to the LCI database used (ecoinvent or GaBi). Normalization and weighting revealed that the mineral resource use impact result dominates the aggregated PEF score (57%), when using the currently recommended ADP model. Shifting from the resource extraction-based ADP to dissipation-based models can reduce the contribution to 23% or < 1% depending on the method.

Conclusion
The development of methods addressing mineral resource use in LCIA has shifted from resource extraction to dissipation. The analyzed methods are applicable and lead to different findings than the extraction-based ADP. Using the newly developed methods in the context of PEF would significantly change the relevance of the mineral resource use impact category in comparison to other environmental impacts.
Modelling the Impact of NETosis During the Initial Stage of Systemic Lupus Erythematosus
Authors: Suvandjieva Vladimira , Tsacheva Ivanka , Santos Marlene , Kararigas Georgios , Rashkov Peter 
Published: April 2024

AbstractThe development of autoimmune diseases often takes years before clinical symptoms become detectable. We propose a mathematical model for the immune response during the initial stage of Systemic Lupus Erythematosus which models the process of aberrant apoptosis and activation of macrophages and neutrophils. NETosis is a type of cell death characterised by the release of neutrophil extracellular traps, or NETs, containing material from the neutrophil’s nucleus, in response to a pathogenic stimulus. This process is hypothesised to contribute to the development of autoimmunogenicity in SLE. The aim of this work is to study how NETosis contributes to the establishment of persistent autoantigen production by analysing the steady states and the asymptotic dynamics of the model by numerical experiment.
Maxillofacial fractures among non-indigenous ethnic groups in the Irish national maxillofacial unit: a review
Authors: Costello Liam , Ogunbowale Akinsola , Ekanayake Kumara 
Published: April 2024

Abstract
Background
This study investigates maxillofacial fractures in non-indigenous ethnic groups who were reviewed in the national maxillofacial unit in Ireland. The aim of this study was to highlight any potential trends in presentation of facial fractures in non-indigenous groups in comparison to previous reports which have included all ethnicities. This unique study is based on the fact that Ireland has only recently transformed into a diverse, multi-cultural country. This is unlike countries such as the UK and USA which have a long history of multicultural integration.

Materials and methods
This retrospective study evaluated the trauma database of 4761 patients with 5038 fractures who attended the national maxillofacial unit over a 5-year period from 2015 to 2019. Parameters included age, gender, mechanism of injury, fracture sustained, time of the day, day of the week, month of injury, and the referral source were obtained from patient records.

Results
The study identified 456 patients who did not identify as being born in Ireland, with 384 males and 72 females. The most common fracture seen was of the zygomatic bone, and the most common mechanism of injury was alleged assault for this cohort. Most injuries occurred in late afternoon with Friday being the most common day of the week.

Conclusion
This study shows how maxillofacial units need to adapt to the changing trends in Irish demographics with increased demand for resources such as translation services. A further study could evaluate the rapidly changing demographic with mass migration of people currently seeking refuge in Western Europe.
Integrals of groups. II
Authors: Araújo João , Cameron Peter J. , Casolo Carlo , Matucci Francesco , Quadrelli Claudio 
Published: April 2024

AbstractAn integral of a group G is a group H whose derived group (commutator subgroup) is isomorphic to G. This paper continues the investigation on integrals of groups started in the work [1]. We study:

A sufficient condition for a bound on the order of an integral for a finite integrable group (Theorem 2.1) and a necessary condition for a group to be integrable (Theorem 3.2).

The existence of integrals that are p-groups for abelian p-groups, and of nilpotent integrals for all abelian groups (Theorem 4.1).

Integrals of (finite or infinite) abelian groups, including nilpotent integrals, groups with finite index in some integral, periodic groups, torsion-free groups and finitely generated groups (Section 5).

The variety of integrals of groups from a given variety, varieties of integrable groups and classes of groups whose integrals (when they exist) still belong to such a class (Sections 6 and 7).

Integrals of profinite groups and a characterization for integrability for finitely generated profinite centreless groups (Section 8.1).

Integrals of Cartesian products, which are then used to construct examples of integrable profinite groups without a profinite integral (Section 8.2).

We end the paper with a number of open problems.
Primary Care and Surgical Collaborations in Addressing Breast Cancer: A Comprehensive Review
Authors: Oyetoran Anuoluwa , Sircar Samantha , Oladeru Oluwadamilola , Johnson Kim Barbel 
Published: April 2024

Abstract
Purpose of Review
This review explores the collaboration between primary care physicians (PCPs) and surgical specialists in breast cancer management. It outlines their evolving roles focusing on early detection, treatment decisions, and patient-centered care. It also addresses challenges, emphasizes interdisciplinary communication, and discusses opportunities for improved breast cancer care.

Recent Findings
Recent research highlights the expanded role of PCPs in comprehensive breast cancer care, from diagnosis, treatment, survivorship, and prevention. Surgeons play a crucial role in decision-making and personalized treatment planning. Collaborative approaches, including multidisciplinary teams, show improved diagnoses and outcomes. Advances in breast cancer research, such as targeted treatments and immunotherapy, offer promising avenues for enhanced care.

Summary
This article advocates for a transformative landscape in breast cancer care, with PCPs and surgeons leading collaborative efforts. Future research lies in the exploration of targeted treatments and the commitment to a holistic, patient-centered approach.
A new workflow for warning and controlling the water invasion
Authors: Zhang Peijun , Fan Hairun , Wen Guangyao , Mu Lingyu , Cheng Weiheng , Wang Xiaochen , Gao Chengwu , Gong Xinglin , Zhao Xurong 
Published: April 2024

AbstractWarning and controlling the water invasion in water-driving reservoirs is significant because water invasion will seriously hamper well productivity and gas recovery. Unfortunately, there are few comprehensive methods to control water invasion. First, we establish and verify a water invasion model of reservoir scale. Then, a new workflow for warning and controlling the water invasion is proposed using the numerical simulation method. The workflow first judges the water invasion characteristics, determines the water invasion index based on the production data, and then controls the water invasion by finding and closing the perforation layer of serious water production. Finally, the optimal water control scheme is obtained by comparing water and gas production. The results show that the accuracy of the geological reserves of the established water invasion model is 99% and has a good pressure fitting result. The early warning chart for the gas reservoir in the west of Amu Darya B area is drawn, including the early warning pressure and the level 1, level 2, and level 3 early warning water–gas ratio, which is convenient for field application. For the water-driving wells west of area B, the early warning value of the water–gas ratio increases with the increase of gas production rate during fixed production and decreases with the increase of bottom hole pressure during constant pressure production. Closing the harmful perforation from the water-finding study will significantly reduce the water while retaining the gas production. After water control technology, water production decreased by 90.9%, while gas production decreased by only 9.7%.
Exploring Machine Learning Techniques for Accurate Prediction of Methane Hydrate Formation Temperature in Brine: A Comparative Study
Authors: Aleem Waqas , Ahmad Sheraz , Qamar Sabih , Hussain Maham , Ali Omer , Rauf Abdul 
Published: April 2024

AbstractAccurate estimation of formation conditions plays a pivotal role in effectively managing various processes related to hydrates, including flow assurance, deep-water drilling, and hydrate-based technology development. The formation temperature of methane hydrates in the presence of brine greatly affects the efficacy and accuracy of these processes. This work presents a comprehensive and novel comparative analysis of nine distinct machine learning models for accurate prediction of formation temperatures of methane hydrate. This study investigated the application of major machine learning (ML) algorithms including multiple linear regression (MLR), long short-term memory (LSTM), radial basis function (RBF), support vector machine (SVM), artificial neural network (ANN), gradient boosting regression (GBR), gradient process regression (GPR), random forest (RF), and K-nearest neighbor (KNN). The model accuracy was validated against a large dataset comprising of over 1000 data points with diverse range of salt concentrations. In this regard, model accuracies were compared using several metrics including R2, ARD, and AARD. The experimental results exhibited KNN algorithm to be fast-converging, accurate, and consistent over the entire range of data points with an R2 score of 0.975 and AARD of 0.385%. The results enable efficient and accurate temperature estimation with ML algorithms for multiple hydrate-related processes.
Spatial-attention ConvMixer architecture for classification and detection of gastrointestinal diseases using the Kvasir dataset
Authors: Demirbaş Ayşe Ayyüce , Üzen Hüseyin , Fırat Hüseyin 
Published: April 2024

AbstractGastrointestinal (GI) disorders, encompassing conditions like cancer and Crohn’s disease, pose a significant threat to public health. Endoscopic examinations have become crucial for diagnosing and treating these disorders efficiently. However, the subjective nature of manual evaluations by gastroenterologists can lead to potential errors in disease classification. In addition, the difficulty of diagnosing diseased tissues in GI and the high similarity between classes made the subject a difficult area. Automated classification systems that use artificial intelligence to solve these problems have gained traction. Automatic detection of diseases in medical images greatly benefits in the diagnosis of diseases and reduces the time of disease detection. In this study, we suggested a new architecture to enable research on computer-assisted diagnosis and automated disease detection in GI diseases. This architecture, called Spatial-Attention ConvMixer (SAC), further developed the patch extraction technique used as the basis of the ConvMixer architecture with a spatial attention mechanism (SAM). The SAM enables the network to concentrate selectively on the most informative areas, assigning importance to each spatial location within the feature maps. We employ the Kvasir dataset to assess the accuracy of classifying GI illnesses using the SAC architecture. We compare our architecture’s results with Vanilla ViT, Swin Transformer, ConvMixer, MLPMixer, ResNet50, and SqueezeNet models. Our SAC method gets 93.37% accuracy, while the other architectures get respectively 79.52%, 74.52%, 92.48%, 63.04%, 87.44%, and 85.59%. The proposed spatial attention block improves the accuracy of the ConvMixer architecture on the Kvasir, outperforming the state-of-the-art methods with an accuracy rate of 93.37%.