bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mast Cells are Dependent on Glucose Transporter 1 (GLUT1) and GLUT3 for IgE-mediated Activation
Authors: Grujic Mirjana , Alim Md Abdul , Hellman Lars , Peterson Magnus , Pejler Gunnar 
Published: April 2024

AbstractMast cells (MCs) are known to have a pathological impact in a variety of settings, in particular in allergic conditions. There is also limited evidence implicating MCs in diabetes, raising the possibility that MC function may be influenced by alterations in glucose levels. However, it is not known whether MCs are directly affected by elevated glucose concentrations. Moreover, it is not known which glucose transporters that are expressed by MCs, and whether MCs are dependent on glucose transporters for activation. Here we addressed these issues. We show that MCs express high levels of both glucose transporter 1 (GLUT1/Slc2A1) and GLUT3 (Slc2A3). Further, we show that the inhibition of either GLUT1 or GLUT3 dampens both MC degranulation and cytokine induction in response to IgE receptor crosslinking, and that combined GLUT1 and GLUT3 inhibition causes an even more pronounced inhibition of these parameters. In contrast, the inhibition of GLUT1 or GLUT3, or combined GLUT1 and GLUT3 inhibition, had less impact on the ability of the MCs to respond to activation via compound 48/80. Elevated glucose concentrations did not affect MC viability, and had no stimulatory effect on MC responses to either IgE receptor crosslinking or compound 48/80. Altogether, these findings reveal that MCs are strongly dependent on glucose transport via GLUT1 and/or GLUT3 for optimal responses towards IgE-mediated activation, whereas MC functionality is minimally affected by elevated glucose levels. Based on these findings, antagonists of GLUT1 and GLUT3 may be considered for therapeutic intervention in allergic conditions.
Phase transformations in yttria-partly stabilized zirconia induced by dental polishing regimes
Authors: Wertz Markus , Berthold Christoph , Flicker Annette , Sander Stephan A. H. , Brinkmann Lisa , Fuchs Florian , Koenig Andreas 
Published: April 2024

AbstractThe study examined how three polishing methods, using equipment from NTI CeraGlaze (NTI), Komet Dental (Komet), and EVE Diacera (EVE) and employing either wet or dry grinding, affect the texture (roughness) and phase composition of Y-PSZ dental crowns. Dental crowns made from VITA’s 3Y-/4Y-/5Y-partly stabilized zirconia (Y-PSZ; YZ-HT/ST/XT), utilizing a standard CAD/CAM process, underwent both wet or dry grinding and polishing. The effects of distinct polishing treatments on Y-PSZ surface phase content were investigated using X-ray diffraction (XRD) and Rietveld refinement, the grain size was measured by field emission scanning electron microscopy (FE-SEM), and confocal scanning laser microscopy (CLSM) was used to determine the surface roughness as the arithmetical mean height (Sa). To analyse the different mode of action, the components of the polishers were analysed using XRD, along with micro X-ray computer tomography (µXCT), FE-SEM, and CLSM for microstructural examination. The Komet and NTI polishing regimes reduced roughness significantly better than the EVE regime for the 3Y and all wet specimens, but caused a rhombohedral phase fraction. A possible explanation for this result is the overall finer structure of the EVE coarse polisher (abrasive particle size and content, texture density), which probably results in a lower force on the Y-PSZ surface. Therefore, the rhombohedral phase boundary would not be reached. Due to rhombohedral phase having larger volume expansion and shear than the monoclinic phase, it may result in enhanced transformation toughening or detrimental low-temperature degradation effects.
Graphical abstract
Continuity with caveats in anesthesia: state and response entropy of the EEG
Authors: Ebensperger Max , Kreuzer Matthias , Kratzer Stephan , Schneider Gerhard , Schwerin Stefan 
Published: April 2024

AbstractThe growing use of neuromonitoring in general anesthesia provides detailed insights into the effects of anesthetics on the brain. Our study focuses on the processed EEG indices State Entropy (SE), Response Entropy (RE), and Burst Suppression Ratio (BSR) of the GE EntropyTM Module, which serve as surrogate measures for estimating the level of anesthesia. While retrospectively analyzing SE and RE index values from patient records, we encountered a technical anomaly with a conspicuous distribution of index values. In this single-center, retrospective study, we analyzed processed intraoperative electroencephalographic (EEG) data from 15,608 patients who underwent general anesthesia. We employed various data visualization techniques, including histograms and heat maps, and fitted custom non-Gaussian curves. Individual patients’ anesthetic periods were evaluated in detail. To compare distributions, we utilized the Kolmogorov–Smirnov test and Kullback–Leibler divergence. The analysis also included the influence of the BSR on the distribution of SE and RE values. We identified distinct pillar indices for both SE and RE, i.e., index values with a higher probability of occurrence than others. These pillar index values were not age-dependent and followed a non-equidistant distribution pattern. This phenomenon occurs independently of the BSR distribution. SE and RE index values do not adhere to a continuous distribution, instead displaying prominent pillar indices with a consistent pattern of occurrence across all age groups. The specific features of the underlying algorithm responsible for this pattern remain elusive.
Causality Detection and Quantification by Ensembles of Time Delay Neural Networks for Application to Nuclear Fusion Reactors
Authors: Gelfusa Michela , Rossi Riccardo , Murari Andrea 
Published: April 2024

AbstractThe understanding and control of complex systems in general, and thermonuclear plasmas in particular, require analysis tools, which can detect not the simple correlations but can also provide information about the actual mutual influence between quantities. Indeed, time series, the typical signals collected in many systems, carry more information than can be extracted with simple correlation analysis. The objective of the present work consists of showing how the technology of Time Delay Neural Networks (TDNNs) can extract robust indications about the actual mutual influence between time indexed signals. A series of numerical tests with synthetic data prove the potential of TDNN ensembles to analyse complex nonlinear interactions, including feedback loops. The developed techniques can not only determine the direction of causality between time series but can also quantify the strength of their mutual influences. An important application to thermonuclear fusion, the determination of the additional heating deposition profile, illustrates the capability of the approach to address also spatially distributed problems.
Unmasking Risky Habits: Identifying and Predicting Problem Gamblers Through Machine Learning Techniques
Authors: Sándor Máté Cs. , Bakó Barna 
Published: April 2024

AbstractThe use of machine learning techniques to identify problem gamblers has been widely established. However, existing methods often rely on self-reported labeling, such as temporary self-exclusion or account closure. In this study, we propose a novel approach that combines two documented methods. First we create labels for problem gamblers in an unsupervised manner. Subsequently, we develop prediction models to identify these users in real-time. The methods presented in this study offer useful insights that can be leveraged to implement interventions aimed at guiding or discouraging players from engaging in disordered gambling behaviors. This has potential implications for promoting responsible gambling and fostering healthier player habits.
Image segmentation and classification for fission track analysis for nuclear forensics using U-net model
Authors: Elgad Noam , Babayew Rami , Last Mark , Weiss Aryeh , Gilad Erez , Levy Galit Katarivas , Halevy Itzhak 
Published: April 2024

AbstractThis study introduces a novel methodology for the detection and classification of fission track (FT) clusters in microscope images, employing state-of-the-art deep learning techniques for segmentation and classification (Elgad in nuclear forensics—fission track analysis—star segmentation and classification using deep learning, Ben-Gurion University, 2022). The U-Net model, a fully convolutional network, was used to carry out the segmentation of various star-like patterns in both single-class and multi-class scenarios.
Financing Climate-Smart Agriculture: a case study from the Indo-Gangetic Plains
Authors: Villalba Roberto , Joshi Garima , Daum Thomas , Venus Terese E. 
Published: April 2024

AbstractThe Indo-Gangetic Plains represents one of South Asia’s most productive agricultural regions, yet it is highly vulnerable to climate change and requires the widespread adoption of Climate-Smart Agriculture. Although farmers understand the benefits of such technologies, financial constraints often undermine adoption. Using a case study from Haryana, we assess the opportunities and challenges aligned with the different pathways available for farmers to adopt and finance two capital-intensive technologies: laser land levelers and happy seeders. Our analysis uses unique data from Karnal, where stakeholders have partnered in Climate-Smart-Villages, and combines a household survey from 120 farmers, interviews, and focus group discussions with banks and cooperatives. Our results indicate adoption rates of 77% for laser land levelers and 52% for happy seeders, with only 7% and 21% of farmers owning the technologies, respectively. Hiring is highly preferred over purchase, mainly due to the flourishing of Custom-Hiring Centers, which are vital in driving large-scale implementation. We find that farmers prefer funding from family, savings, and moneylenders (indirect pathways) rather than from commercial banks (direct pathways) to get immediate access to credit and avoid bureaucratic procedures. Our study offers broader insights into the state of agricultural finance in India and adaptation to climate change and reveals that institutional innovations can enhance the financing of CSA technologies for smallholder farmers. Our findings have important implications for decision-makers seeking to streamline credit access for CSA machinery rental. Future research should focus on the efficacy of different finance channels and their causal impact on pathways for technology adoption.
Cumulative histogram as a feature selection technique for anomaly detection
Authors: Nassar Mostafa , Salama Rania A. , Saleeb Adel A. , El-bahnasawy Nirmeen A. , Ahmed Hossam Eldin H. , Abd El-Samie Fathi E. 
Published: April 2024

AbstractThe enhancement of Intrusion Detection Systems (IDS) is required to ensure protection of network resources and services. This is a hot research topic, especially in the presence of advanced intrusions and attacks. This paper provides a comparison between Distributed Cumulative Histogram (DCH) as a Feature Selection (FS) technique, Information Gain Ratio (IGR) FS and wrapper-based FS in terms of accuracy and Root Mean Square Error (RMSE). The utilization of DCH of the traffic instances in normal and attack cases allows us to compare the traffic charts. We can observe the difference between effective features and less effective ones. We verify the feasibility of using DCH as an FS technique in the field of anomaly detection with just six selected features giving more accurate results with most classifiers compared to the IGR and wrapper-based FS. We applied our experiments on the modern UNSW dataset with the WEKA simulation platform that contains a group of classification, feature reduction and selection techniques.
Alternate realities in interactive digital narratives – understanding and improving design and prosocial effects through empirical methods
Authors: Koenitz Hartmut , Roth Christian , Mekler Elisa 
Published: April 2024

AbstractInteractive digital narratives (IDNs) create alternate realities using both fictional and non-fiction material. The interactive aspect of IDN turns audiences into participants and enables the exploration of alternative perspectives and actions within a single artifact. Such multifaceted representations make IDN a vehicle for representing complex issues, a crucial capability at a time when the limits of traditional narrative media to adequately represent complex issues such as climate change become apparent. Conversely, properly evaluated, generalized knowledge about how exactly IDNs engage and influence us and what this means for the design of such works is still scant and thus this topic needs scholarly attention. In this overview paper, we discuss the potential of IDN, but also the difficulties of realizing this potential in terms of design and of verifying the effectiveness through empirical research methods. The potential of IDN as dynamic, participatory, and encyclopedic artifacts can be clearly expressed, yet the same cannot be said when it comes to the design and especially the evaluation of intended prosocial effects, the topic this paper is focused on. We start by identifying the problem of IDN design resulting from a combination of the lack of generalized knowledge and formal professional training. Then, we discuss the challenge of measuring the effectiveness of IDN design for prosocial effects and report on several case studies. In this context, we discuss methodological issues and advocate for best practices. Finally, we consider future steps in addressing the continuing challenge of evaluating IDNs.
Intraoperative magnetic resonance imaging in glioma surgery: a single-center experience
Authors: Mirzayeva Leyla , Uçar Murat , Kaymaz Ahmet Memduh , Temel Esra 
Published: April 2024

Abstract
Purpose
To investigate the effect of intraoperative magnetic resonance imaging (Io MRI) on overall and progression-free survival (OS and PFS), on the extent of resection (EOR) in patients with glioma, and impact of the radiological diagnosis on the decision to continue the surgery when a residual mass was detected on Io MRI.

Methods
The study comprised 153 glioma patients who received surgical treatment between 2013 and 2023. One-hundred twenty-five of them had Io MRI guidance during surgery. The remainder 28 patients constituted the control group who did not undergo Io MRI. All patients' age at surgery, gender, initial radiological diagnosis, primary tumor localization, EOR, last histopathological diagnosis, and the follow-up periods were recorded.

Results
The rate of tumor recurrence in Io MRI cases was significantly lower compared to the cases in the control group (p < .0001). It was decided to continue the operation in 45 Io MRI applied cases. This raised the gross total resection (GTR) rate from 33.6% to 49.6% in the Io MRI group. The frequency of GTR was significantly higher in patients with an initial radiological diagnosis of low grade glioma than those with high grade glioma. The shortest OS was seen in occipital gliomas.

Conclusion
In this study, the convenience provided by the high-field MRI device was explored and proven both in reducing the tumor burden, increasing the PFS, and providing the surgeon with a maximal resection in the first operation.
“Wrong” skewness and endogenous regressors in stochastic frontier models: an instrument-free copula approach with an application to estimate firm efficiency in Vietnam
Authors: Haschka Rouven E. 
Published: April 2024

AbstractStochastic frontier models commonly assume positively skewed inefficiency. However, if the data speak against this assumption, sample-failure problems are often cited, but less attention is paid to economic reasons. We consider this phenomenon as a signal of distinctive population characteristics stemming from the inefficiency component, emphasizing its potential impact on evaluating market conditions. Specifically, we argue more generally that “wrong” skewness could indicate a lack of competition in the market. Moreover, endogeneity of model regressors presents another challenge, hindering the identification of causal relationships. To tackle these issues, this paper proposes an instrument-free estimation method based on Gaussian copulas to model the dependence between endogenous regressors and composite errors, while accommodating positively or negatively skewed inefficiency through simultaneous identification. Monte Carlo simulation experiments demonstrate the suitability of our estimator, comparing it with alternative methods. The contributions of this study are twofold. On the one hand, we contribute to the literature on stochastic frontier models by providing a comprehensive method for dealing with “wrong” skewness and endogenous regressors simultaneously. On the other hand, our contribution to an economic understanding of “wrong” skewness expands the comprehension of market behaviors and competition levels. Empirical findings on Vietnamese firm efficiency indicate that endogeneity hinders the detection of “wrong” skewness and suggests a lack of competitive market conditions. The latter underscores the importance of policy interventions to incentivize firms in non-competitive markets.
Does identity change matter? Everyday agency, moral authority and generational cascades in the transformation of groupness after conflict
Authors: Todd Jennifer 
Published: April 2024

AbstractEveryday identity change is common after conflict, as people attempt to move away from oppositional group relations and closed group boundaries. This article asks how it scales up and out to impact these group relations and boundaries, and what stops this? Theoretically, the article focusses on complex oppositional configurations of groupness, where relationality and feedback mechanisms (rather than more easily measured variables) are crucial to change and continuity, and in which moral authority is a key node of reproduction. It uses the normatively weighted concept of transformation to augment existing research on boundary and identity change, while elaborating it to recognise the role of everyday agency in furthering change and moral inertia in impeding it. Substantively, the article compares the processes of everyday transformation of groupness in three cases that are very similar in historical depth, social embeddedness, symbolic opposition and everyday change, but very different in time-scale and with contrasting outcomes: successful transformation of reformation religious groupness; partial transformation of national groupness; and failed transformation of complexly-configured ethnic groupness in Northern Ireland. This allows tracing of the patterns and mechanisms at work. To anticipate, the article argues that everyday identity change can erode the moral authority of groupness. Its impact is generational and dependent on institutional linkages. The article highlights the importance of moral mechanisms as drivers of and obstacles to change; and it suggests ways that the obstacles could be overcome by radical policy interventions.
What does the 7th cooperative principle (concern for community) really mean?
Authors: Osten Flávio Luiz Von Der , Martins Tomas Sparano , Dong Hao , Bailey Adrian R. 
Published: April 2024

AbstractCooperatives are an important organizational form that operate under seven principles (Voluntary and Open Membership; Democratic Member Control; Member Economic Participation; Autonomy and Independence; Education, Training, and Information; Cooperation among Cooperatives; Concern for Community). Concern for Community was the last formally stated cooperative principle in 1995, after decades of discussion within the International Cooperative Alliance (ICA). The statement of this “new” principle has provoked questions for cooperatives and the cooperative movement more generally, regarding their definition, scope, and implementation. This article employs a systematic literature review to examine the academic understanding of Concern for Community that has emerged over the past 30 years. The review analyzes 32 academic journal articles from an initial dataset of 438 articles generated by a two-string search (“concern for community” and “cooperative principles”). Five themes are identified: cooperative principles, defining Concern for Community, adoption of Concern for Community, antecedents of Concern for Community, and outcomes. Comparing these themes with the normative instructions proposed by the ICA, the article develops a framework for future research. The review also finds that there is not an established clear difference between Concern for Community and corporate social responsibility in the extant literature, which carries the implication that constructs from the latter can be integrated into the analysis and development of the 7th principle.
AA Amyloidosis: A Contemporary View
Authors: Mirioglu Safak , Uludag Omer , Hurdogan Ozge , Kumru Gizem , Berke Ilay , Doumas Stavros A. , Frangou Eleni , Gul Ahmet 
Published: April 2024

Abstract
Purpose of Review
Amyloid A (AA) amyloidosis is an organ- or life-threatening complication of chronic inflammatory disorders. Here, we review the epidemiology, causes, pathogenesis, clinical features, and diagnostic and therapeutic strategies of AA amyloidosis.

Recent Findings
The incidence of AA amyloidosis has declined due to better treatment of the underlying diseases. Histopathological examination is the gold standard of diagnosis, but magnetic resonance imaging can be used to detect cardiac involvement. There is yet no treatment option for the clearance of amyloid fibril deposits; therefore, the management strategy primarily aims to reduce serum amyloid A protein. Anti-inflammatory biologic agents have drastically expanded our therapeutic armamentarium. Kidney transplantation is preferred in patients with kidney failure, and the recurrence of amyloidosis in the allograft has become rare as transplant recipients have started to benefit from the new agents.

Summary
The management of AA amyloidosis has been considerably changed over the recent years due to the novel therapeutic options aiming to control inflammatory activity. New agents capable of clearing amyloid deposits from the tissues are still needed.
What Makes Us Move, What Makes Us Stay: The Role of Language and Culture in Intra-EU Mobility
Authors: Sprenger Ekaterina 
Published: April 2024

AbstractThis article analyses the determinants of international migration flows within the European Union and specifically focuses on the role of cultural and linguistic differences in explaining the size of these flows. For that purpose, a set of indicators of cultural distance is controlled for along with economic, demographic, geographical, political and network variables using data from 28 member states of the EU over the period 1998–2018. Economic factors play an important role in examining migration flows, but economic differentials alone may be insufficient to explain the uneven real-life migration pattern in the EU. The results suggest strong evidence of the importance of linguistic distance in explaining the direction of migration flows across the EU.