bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the potential of the ketogenic diet in autism spectrum disorder: metabolic, genetic, and therapeutic insights
Authors: Schrickel Alexa , Groeneweg Jop , Dekeyster Eline 
Published: January 2025

Abstract
Current treatment approaches for Autism spectrum disorder (ASD) primarily focus on symptom management rather than addressing underlying dysfunctions. The ketogenic diet (KD), a high-fat, low-carbohydrate diet inducing nutritional ketosis, has shown promise in treating epilepsy and may offer therapeutic benefits for ASD by modulating metabolic and neuroprotective pathways. This review examined the potential impact of KD on underlying mechanisms in ASD. While evidence from human studies on underlying mechanisms is limited, animal research has shown a large overlap of mechanisms modulated by KD and dysfunctions in ASD. As such, targeting multiple disrupted pathways at once, KD presents a potential multifaceted treatment approach for ASD. However, more evidence from human studies is needed on the effectiveness of KD in the modulation of underlying dysfunctions in ASD. Additionally, precision medicine approaches could help identify individuals who would benefit most from the intervention, potentially extending its use to other psychiatric conditions with similar metabolic patterns. Consequently, KD interventions might show the potential to induce a drastic paradigm shift in understanding and treating ASD.
Proportionality in the Aggregate
Authors: Uzan Elad 
Published: January 2025

Abstract
Much of revisionist just war theory is individualistic in nature: morality in war is just an extension of morality in interpersonal circumstances, so that killing in war is subject to the same moral principles that govern personal self-defense and defense of others. Recent work in the ethics of self-defense suggests that this individualism leads to a puzzle, which I call the puzzle of aggregation, when many threateners contribute to a single threatened harm. In this paper, I investigate the moral problems posed by the puzzle of aggregation and develop a novel account recently proposed by Jeff McMahan, which he calls “proportionality in the aggregate”. I argue that accepting proportionality in the aggregate as a moral constraint on the use of force has significant implications for the ethics of war and self-defense.
Exploring the potential of seed inoculation with microbial consortia to mitigate drought stress in maize plants under greenhouse conditions
Authors: Yim Bunlong , Heider Marie Amelie , Bloem Elke , Vetterlein Doris , Behr Jan Helge , Babin Doreen , Smalla Kornelia 
Published: January 2025

Abstract
Background and aims
Plant-beneficial microbes may attenuate climate change-induced stresses on plants such as drought. We investigated the potential of beneficial microbial consortia (BMc) on plant growth and rhizosphere bacterial/archaeal community under drought.

Methods
Seeds of Zea mays B73 were inoculated with six plant-beneficial bacterial isolates either alone or combined in two three-member consortia (BMc1, BMc2) before sowing in loamy or sandy substrates in the greenhouse. A known effective consortium (BMc3) was included as positive control. Drought treatment was established with the BMc treatments by omitting watering in the last of the five weeks growth period. The maize growth in single and BMc treatments was determined. Colony-forming units (CFUs) of inoculants were evaluated by selective plating, and effects of BMc treatments on the native rhizosphere bacterial/archaeal community were assessed using 16S rRNA gene amplicon sequencing of basal root and root tip rhizosphere of plants grown in loam.

Results
In both substrates and water conditions, CFUs of single and BMc inoculations were higher at rhizosphere basal roots than root tips. Under well-watered conditions, seed inoculation with a single bacterial isolate had no effect on maize growth in both substrates. BMc treatment resulted in higher shoot (but not root) growth compared to non-inoculated controls in both water conditions in loam. The root zone was the most important driver for bacterial/archaeal beta-diversity, followed by water conditions, while BMc treatments showed no effect.

Conclusion
Our study suggests that BMc seed inoculation has the potential to attenuate drought stress during maize growth.
An analysis of country-by-country data for EU banks: an investigation of bank performance and risk
Authors: Cordina Renzo , Kourtzidis Stavros , Power David M. , Tzeremes Nickolaos G. 
Published: January 2025

AbstractOne of the biggest changes to financial reporting within the European Union over the last decade has been the growth of country-by-country (CbC) reporting. European legislation has required companies in certain sectors such as banking to publish information either about their performance or their payments to governments for each country where they operate. Our research explores the relevance of disclosures that have been mandated by the Capital Requirement Directive IV for the banking industry. We construct a composite performance indicator using a Benefit-of-the-Doubt model to explore how this information can be employed by stakeholders to evaluate the operational performance of European banks. Data for 39 of the 50 largest European banks over the period 2015–2019 are included in the study, with four major findings. Firstly, the results suggest that the risk of underperformance can be sizeable; there are a large number of low performing and a small number of high performing bank establishments. Secondly, both the bank-level gap (BLG) and the jurisdiction-level gap (JLG) are important sources of low performance. Thirdly, the path for improvement varies for different banks; while some need to enhance performance within specific jurisdictions compared to the other jurisdictions of the same bank, others must improve their performance relative to other banks. Finally, there is heterogeneity in the results at a country level, and the best performing establishments are often located in countries considered as tax-havens under certain taxonomies.
Exploring Effective Diffusion Coefficients in Water-Saturated Reservoir Rocks via the Pressure Decay Technique: Implications for Underground Hydrogen Storage
Authors: Khajooie Saeed , Gaus Garri , Seemann Timo , Ahrens Benedikt , Hua Tian , Littke Ralf 
Published: January 2025

Abstract
The assessment of gas diffusion in water-saturated rocks is essential for quantifying gas loss and determining the amount of gas that could trigger abiotic and biotic processes, potentially altering fluid and rock properties. Additionally, estimating diffusion coefficients is critical for evaluating the balance between hydrogen generation and dissipation in radioactive waste repositories. This investigation involved experimental determination of diffusion coefficients for various gases both in water and in water-saturated Bentheim, Oberkirchner, Grey Weser, and Red Weser sandstones. Experimental conditions included pressures ranging from 0.2 to 1.0 MPa, consistently maintained at a temperature of 35 °C. The diffusion coefficients of hydrogen, helium, and methane in water were determined to be 6.7·10–9, 9.6·10–9, and 2.8·10–9 m2/s, respectively, consistent with literature values obtained through gas concentration measurements without pressure gradients. However, the diffusivity of carbon dioxide and argon in water was measured at 10.9·10–9 and 44.6·10–9 m2/s, significantly exceeding their corresponding literature values by an order of magnitude. This discrepancy is attributed to the significant solubility of these gases in water, resulting in density-driven convection as the primary transport mechanism. Furthermore, the effective diffusion coefficients for hydrogen within the analyzed rock specimens varied from 0.8·10–9 to 2.9·10–9 m2/s, which are higher than those for methane and carbon dioxide, both ranging from 0.3·10–9 to 0.9·10–9 m2/s. This yielded diffusive tortuosity values ranging from 2.6 to 8.2. The observed effective diffusivity values were positively correlated with porosity, permeability, and mean pore size, while exhibiting a negative correlation with tortuosity. Given that the gas–liquid mass transfer coefficient is directly proportional to the effective gas diffusivity in water, the determined values for H2 are essential for studying the impact of pore characteristics on microbial activity.
Specific staining and precise killing of cancer cells through fusion of pharmaceutical chemistry and π-bridge effect design philosophy
Authors: Liu Qiong , Deng Qiyun , Zhu Changxu , Chen Kongqi , Chen Lidan , Sun Zhaohui , Tang Ben Zhong , Wang Zhiming 
Published: January 2025

Abstract
The development of an advanced phototheranostic platform that combines imaging and therapy in a single agent is an appealing yet challenging task. In this study, we successfully constructed three novel fluorescent probes by leveraging pharmaceutical chemistry and the design philosophy of the π-bridge effect. Through a systematic comparative analysis of their fluorescence properties, water solubility, molecular conformation, and electrostatic potential, we revealed the fundamental principles governing the optical behavior and biological selectivity of these probes. Notably, the probe TPhIQ-CNTh demonstrated extended fluorescence in the near-infrared region, a significant aggregation-induced emission (AIE) effect, and the ability to distinguish tumor cells from normal cells. Moreover, it efficiently generated reactive oxygen species (ROS) and specifically labeled lipid droplets, enabling the precise staining and killing of cancer cells. This study presents a practical strategy for designing precise tumor treatments that integrate efficient imaging-guided photodynamic therapy (PDT) by harnessing the unique properties of AIE materials.
Comparison of active learning algorithms in classifying head computed tomography reports using bidirectional encoder representations from transformers
Authors: Wataya Tomohiro , Miura Azusa , Sakisuka Takahisa , Fujiwara Masahiro , Tanaka Hisashi , Hiraoka Yu , Sato Junya , Tomiyama Miyuki , Nishigaki Daiki , Kita Kosuke , Suzuki Yuki , Kido Shoji , Tomiyama Noriyuki 
Published: January 2025

Abstract
Purpose
Systems equipped with natural language (NLP) processing can reduce missed radiological findings by physicians, but the annotation costs are burden in the development. This study aimed to compare the effects of active learning (AL) algorithms in NLP for estimating the significance of head computed tomography (CT) reports using bidirectional encoder representations from transformers (BERT).

Methods
A total of 3728 head CT reports annotated with five categories of importance were used and UTH-BERT was adopted as the pre-trained BERT model. We assumed that 64% (2385 reports) of the data were initially in the unlabeled data pool (UDP), while the labeled data set (LD) used to train the model was empty. Twenty-five reports were repeatedly selected from the UDP and added to the LD, based on seven metrices: random sampling (RS: control), four uncertainty sampling (US) methods (least confidence (LC), margin sampling (MS), ratio of confidence (RC), and entropy sampling (ES)), and two distance-based sampling (DS) methods (cosine distance (CD) and Euclidian distance (ED)). The transition of accuracy of the model was evaluated using the test dataset.

Results
The accuracy of the models with US was significantly higher than RS when reports in LD were < 1800, whereas DS methods were significantly lower than RS. Among the US methods, MS and RC were even better than the others. With the US methods, the required labeled data decreased by 15.4–40.5%, and most efficient in RC. In addition, in the US methods, data for minor categories tended to be added to LD earlier than RS and DS.

Conclusions
In the classification task for the importance of head CT reports, US methods, especially RC and MS can lead to the effective fine-tuning of BERT models and reduce the imbalance of categories. AL can contribute to other studies on larger datasets by providing effective annotation.
The Democratic Deficit of the Global Dominance of Producer-Driven Society
Authors: Buckley Peter 
Published: January 2025

Abstract
The argument of this paper is sequential. Democracy is associated with openness in trade, investment, and entrepreneurship. This is because of its support of property rights, contract enforcement, open governance, and civil society operational freedoms. However, these institutions are potentially open to capture by producer-driven interests. Institutions and political processes are not fixed but change over time and are the products of political contestation including the global projection of national producer interests. It is essential to see the world economy as a complex system that evolves under pressures of political, economic, technological, and societal changes. Democratic control of powerful producer-driven interests is not a given. Addressing the potential democratic deficit is one of global society’s “Grand Challenges”.
Rapid automatic detection of collapsed buildings with single period LiDAR data after an earthquake
Authors: Canözü Ömer , Acar Hayrettin 
Published: January 2025

AbstractEarthquakes are natural disasters that cannot be determined precisely where and when they will occur. In cases where precautions are insufficient, large losses of life and property can occur. Minimizing the loss of life after an earthquake depends on the rapid identification of collapsed structures and the urgent delivery of rescue teams to heavily damaged structures. Within the scope of the study, damaged and destroyed buildings were automatically detected in a very short time after the earthquake by using the LiDAR point cloud data obtained with a single period flight and the cadastral map of the region. With the algorithm produced, the robust, damaged and destroyed building classes were detected with 98.98% and 98.56% accuracy rates by considering 3D geometric changes in two different study areas. After obtaining LiDAR data, the detection of damaged and collapsed buildings can be performed within two hours. These findings demonstrate the potential of the proposed approach to effectively detect damaged and destroyed buildings after a disaster. The map of damaged and collapsed buildings after the earthquake is produced without being dependent on radiometric changes. This process is carried out in a very short time with a high accuracy rate, which reveals the superiority of the study compared to the literature. The studies conducted with satellite images without 3D analysis capabilities, it is not possible to detect collapsed buildings with undamaged roofs. In contrast, the proposed LiDAR-based method can detect such damaged structures with high accuracy. The method accelerates the planning and implementation of post-earthquake rescue and relief operations. In addition, the fact that it can prevent loss of life due to late interventions increases the importance of the proposed study.
Utilization of the Total Error Allowance Rule to Determine the Clinical Acceptability of Complete Blood Counts in the Blood Samples Collected via Peripherally Inserted Central Catheters in Cancer Patients
Authors: Xue Xiaojing , Tang Jie , Yang Yuwei , Yang Lijuan , Zhang Siqi , Du Xiaobo , Feng Gang , Guo Chao , Chen Rong , Yang Yalan 
Published: January 2025

AbstractPeripherally inserted central catheters (PICCs) are widely used in oncology patients for drug infusion and nutritional support; however, their usefulness for blood sample collection has not been clarified. This study aimed to evaluate the clinical acceptability of complete blood count (CBC) measurements in blood samples drawn from PICC lines in oncology patients. Blood samples were drawn twice successively from the PICC lines (PICC0 and PICC1 samples, respectively), and a peripheral blood collected from the contralateral limb was used as reference sample. Significant differences and sources of bias in the CBC measurements in two PICC samples were analyzed. Clinical acceptability was determined based on the total error allowance (TEa) rules. Except for hemoglobin and erythrocyte, no significant differences were observed in the other parameters between PICC1 and reference samples (all P > 0.05), including leukocyte, hematocrit, platelet, erythrocyte parameters and leukocyte differential counts. Deviations of erythrocyte and hemoglobin in PICC1 samples was only attributed to random error, whereas proportional bias were also observed in PICC0 samples. According to the given TEa, erythrocyte, leukocyte, hemoglobin, and platelet of the PICC1 samples met the 1/2 TEa criteria and had favorable clinical acceptability. However, the hematocrit and the three erythrocyte parameters failed to meet the 1/2 TEa criteria. Adherence to the TEa criteria may provide higher clinical acceptability for CBC results. Satisfactory results in oncology patients may be involve discarding the first 2 mL of blood samples during sample collection using PICC lines.
Academic course planning recommendation and students’ performance prediction multi-modal based on educational data mining techniques
Authors: Kord Ahmed , Aboelfetouh Ahmed , Shohieb Samaa M. 
Published: January 2025

AbstractEducational Data Mining (EDM) has recently received significant attention, leading to the development of various Data Mining (DM) methodologies for extracting hidden knowledge within educational data. This knowledge is crucial for enhancing teaching methods and improving student learning experiences, ultimately contributing to better student performance and overall educational outcomes. Students confront difficulties in selecting appropriate courses and suitable departments, which is regarded as the most important factor in avoiding career failure. Predicting students’ academic performance is vital for evaluating the success of educational institutions. In this study, eleven Machine Learning (ML) algorithms and three Deep Learning (DL) algorithms namely Support Vector Classification (SVC), K-Nearest Neighbor (KNN), Logistic regression (LR), Decision tree (DT), Linear discriminant analysis (LDA), Quadratic Discriminant Analysis (QDA), Random Forest (RF), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (Light GBM), Extra Trees, Deep Artificial Neural Network (DANN), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM), were evaluated using real dataset from the Faculty of Computers and Information Sciences (FCIS) at Mansoura University (MU). A prediction model was developed to predict students’ academic grades in upcoming courses based on their past performance, alongside a recommendation model for guiding students towards suitable courses and departments. The results demonstrate that the Support Vector Classification (SVC) model outperformed others, achieving a 78.04% multi-classification accuracy and a 75.37% F1-Score. This study underscores the potential of individual ML and DL models to predict students’ academic performance based on real dataset features.
Factors Regulating the Potential for Freshwater Mineral Soil Wetlands to Function as Natural Climate Solutions
Authors: Ma Shizhou , Mistry Purbasha , Badiou Pascal , Bansal Sheel , Creed Irena F. 
Published: January 2025

Abstract
There are increasing global efforts and initiatives aiming to tackle climate change and mitigate its impacts via natural climate solutions (NCS). Wetlands have been considered effective NCS given their capacity to sequester and retain atmospheric carbon dioxide (CO2) while also providing a myriad of other ecosystem functions that can assist in mitigating the impacts of climate change. However, wetlands have a dual impact on climate, influencing the atmospheric concentrations of both CO2 and methane (CH4). The cooling effect associated with wetland CO2 sequestration can be counterbalanced by the warming effect caused by CH4 emissions from wetlands. The relative ability of wetlands to sequester CO2 versus emit CH4 is dependent on a suite of interacting physical, chemical, and biological factors, making it difficult to determine if/which wetlands are considered important NCS. The fact that wetlands are embedded in landscapes with surface and subsurface hydrological connections to other wetlands (i.e., wetlandscapes) that flow over and through geochemically active soils and sediments adds a new layer of complexity and poses further challenges to understanding wetland carbon sequestration and greenhouse gas fluxes at large spatial scales. Our review demonstrates how additional scientific advances are required to understand the driving mechanisms associated with wetland carbon cycling under different environmental conditions. It is vital to understand wetland functionality at both wetland and wetlandscape scales to effectively implement wetlands as NCS to maximize ecological, social, and economic benefits.
Recycling of lithium-ion batteries: cobalt recovery with supercritical fluids
Authors: Morales Ibarra Rodolfo , Goto Motonobu , García Montes Saida Mayela , López Cuellar Enrique Manuel , Martínez de la Cruz Azael 
Published: January 2025

AbstractA long-term recycling strategy integrated into the circular economy of materials will be the only feasible option going forward on the use of lithium-ion batteries; the development of such a technology is critical to achieving a sustainable state of energy and waste management. Supercritical fluids are great technological candidates for recycling lithium-ion batteries and recovering cobalt which can be then integrated into a circular economy through the industrialization of an efficient recycling process. Cobalt recovery is feasible using supercritical CO2, supercritical and subcritical water with organic acids with up to 99% efficiency.
Adam Smith’s Pluralism and the Limits of Science
Authors: Sturn Richard 
Published: January 2025

Abstract
In recent decades, scholarly work on Adam Smith clarified important aspects of his multi-faceted account of human agency. However, the relevance of his view of knowledge and agency for political economy as science of the legislator has not been clarified sufficiently. It is contended here that Smith’s view of human agency in socio-economic contexts is linked to a kind of pragmatic pluralism, emphasizing the role of the knowledge made available by scientific “systems”, but also their limitations and incompleteness. Smith’s Theory of Moral Sentiments, his discussions of the mercantile system and honesty in commerce are considered as examples of pragmatic pluralism reflecting such limitations, while opening up horizons of reasonable disagreement and problem-responsive reform avoiding technocratic fallacies and reckless experimentation.