bluuebunny/crossref_metadata_2025_split huggingface dataset:
Heart Failure: a Punch from the Gut
Authors: Mahenthiran Ajay , Wilcox Jennifer , Tang W.H. Wilson 
Published: February 2024

Abstract
Purpose of Review
This article seeks to elucidate the mechanisms underlying the bidirectional relationship between the gut and the heart, focusing on the pathophysiology of heart failure. We have previously demonstrated that Heart failure (HF) has significant effects on splanchnic vasculature and leads to key alterations in the gut microbiome, portending greater comorbidity with HF.

Recent Findings
A growing field of research is focused on the effects of a “leaky gut” in the development of disease across organ systems. The leaky gut hypothesis centers on intestinal epithelial barrier dysfunction causing increased permeability of the gut and subsequent alterations to gut composition by endotoxins and microbial metabolites. Changes in the quantities of metabolites including short-chain fatty acids, trimethylamine N-oxide and other amino acid metabolites, and various bile acid species have been shown to result in gut dysbiosis and worsening HF.

Summary
The gut plays a highly significant role in HF prognosis and requires greater attention for future therapeutic interventions. Treatments targeting gut composition could have very beneficial effects on HF prognosis.
Civil Society Under Attack: The Consequences for Horizontal Accountability Institutions
Authors: Smidt Hannah , Johansson Jessica , Richter Thomas 
Published: February 2024

AbstractExisting research shows that the activity of independent civil society organizations (CSOs) is an important ingredient of democratization and democratic consolidation. Yet, what happens when governments impose restrictions on CSO activity? This manuscript investigates how restrictions on CSOs affect the quality of horizontal accountability institutions like parliaments and courts. CSOs monitor and mobilize against violations of democratic norms. Thus, if governments impose restrictions on CSO activity, they may face fewer barriers (i.e., less scrutiny and criticism) to dismantling horizontal checks and balances. In addition, when restrictions prevent CSOs from supporting horizontal accountability institutions (e.g., with monitoring and expertise), the latter’s ability to control and constrain governments likely declines. Our large-N cross-country analysis supports this argument, suggesting that the imposition of restrictions on CSOs diminishes the quality of horizontal accountability institutions. We examine alternative explanations (i.e., prior autocratization trends and the authoritarian nature of governments) and offer qualitative evidence from Kenya and Turkey to illustrate the expected causal pathways. Our results imply that a crackdown on CSOs serves as a warning sign of deteriorating horizontal oversight.
Human trafficking, sexual exploitation and digital technologies
Authors: L’Hoiry Xavier , Moretti Alessandro , Antonopoulos Georgios A. 
Published: February 2024

AbstractThis is the introduction to the special issue on ‘human trafficking, sexual exploitation and digital technologies’. This special issue contributes to the knowledge base by bringing together four articles that focus on the use of online platforms by human traffickers for the purposes of commercial sexual exploitation. In doing so, this special issue explores the affordances of online platforms to human traffickers, the challenges faced by law enforcement and other actors seeking to intervene in human trafficking in the digital age, and perhaps pathways towards overcoming these challenges in the future.
All laser direct writing process for temperature sensor based on graphene and silver
Authors: Li Qi , Bai Ruijie , Guo Lianbo , Gao Yang 
Published: February 2024

AbstractA highly sensitive temperature sensing array is prepared by all laser direct writing (LDW) method, using laser induced silver (LIS) as electrodes and laser induced graphene (LIG) as temperature sensing layer. A finite element analysis (FEA) photothermal model incorporating a phase transition mechanism is developed to investigate the relationship between laser parameters and LIG properties, providing guidance for laser processing parameters selection with laser power of 1–5 W and laser scanning speed (greater than 50 mm/s). The deviation of simulation and experimental data for widths and thickness of LIG are less than 5% and 9%, respectively. The electrical properties and temperature responsiveness of LIG are also studied. By changing the laser process parameters, the thickness of the LIG ablation grooves can be in the range of 30–120 μm and the resistivity of LIG can be regulated within the range of 0.031–67.2 Ω·m. The percentage temperature coefficient of resistance (TCR) is calculated as − 0.58%/°C. Furthermore, the FEA photothermal model is studied through experiments and simulations data regarding LIS, and the average deviation between experiment and simulation is less than 5%. The LIS sensing samples have a thickness of about 14 μm, an electrical resistivity of 0.0001–100 Ω·m is insensitive to temperature and pressure stimuli. Moreover, for a LIS-LIG based temperature sensing array, a correction factor is introduced to compensate for the LIG temperature sensing being disturbed by pressure stimuli, the temperature measurement difference is decreased from 11.2 to 2.6 °C, indicating good accuracy for temperature measurement.
Graphical Abstract
Clinical heterogeneity and five phenotypes identified in pediatric Behçet’s syndrome: a cohort study from Shanghai Behçet’s syndrome database
Authors: Hu Dan , She Chun-Hui , Bao Hua-Fang , Zou Jun , Cai Jian-Fei , Ye Jing‑Fen , Shen Yan , Ma Hai‑Fen , Luo Dan , Guan Jian-Long 
Published: February 2024

Abstract
Objectives
Behçet’s syndrome (BS) is a rare disease of unknown etiology, with limited reports especially in pediatric BS. The clinical characteristics and phenotypes of pediatric BS as a highly heterogeneous variable vessel vasculitis were investigated in this study.

Methods
A cross-sectional study was conducted to compare clinical variables and descriptive characteristics of BS by age of onset and gender. Cluster analysis was then performed to identify the phenotypes of pediatric BS.

Results
A total of 2082 BS patients were included in this study, 1834 adults and 248 children. Compared with adult-onset BS, pediatric BS had a higher incidence of folliculitis [relative risks (RR) and 95% confidence interval (CI) 1.3 (1.0–1.5)], uveitis of the left eye [RR and 95% CI 2.3 (1.0–5.0)], intestinal ulcer complications [RR and 95% CI 2.1 (1.1–4.2)], pericarditis [RR and 95% CI 2.5 (1.0–6.2)], and psychiatric disorders [RR and 95% CI 2.8(1.0–7.9)], while the incidence of thrombocytopenia was lower [RR 0.2 (0.1–1.0)]. Among pediatric BS, females had more genital ulcers, while males were more likely to have skin lesions, panuveitis, vascular involvement, venous lesions, cardiac involvement, and aortic aneurysms. Cluster analysis classified pediatric BS into five clusters (C1–C5): C1 (n = 61, 24.6%) showed gastrointestinal (GI) involvement; C2 (n = 44, 17.7%) was the central nervous system (CNS) type where 23 cases overlapped joint involvement; in C3 (n = 35, 14.1%), all patients presented with arthritis or arthralgia; all patients in C4 (n = 29, 11.7%) manifested ocular involvement, with a few patients overlapping with GI involvement or joint damage; C5 (n = 79, 31.9%) was the mucocutaneous type, presenting both oral ulcers, genital ulcers, and skin lesions.

Conclusions
The clinical features of pediatric and adult BS differ significantly. Male and female pediatric BS also have a distinct demography. Five phenotypes including GI, CNS, joint, ocular, and mucocutaneous types were identified for pediatric BS.

Graphical Abstract
Inter-organisational Sustainability Cooperation Among European Regions and the Role of Smart Specialisation
Authors: Kruse Mirko 
Published: February 2024

Abstract
Innovation represents one of the most crucial levers for regional prosperity and sectoral renewal. Additionally, it is applied to address challenges such as a sustainable transition and the battle against climate change. Since innovation is the result of cooperation between different actors with different backgrounds, the topic is increasingly studied from a systemic perspective. Here, not only internal cooperation but also cross-border connections between regions become important. While smart specialisation, a European policy for innovation and cohesion, highlights the role of interregional cooperation, practical manifestations and research on this aspect have remained limited so far. This article addresses this gap by discussing the relevance of interregional cooperation for knowledge creation and presents empirical evidence on cooperation between organisations in different European regions in the field of environmental sustainability. The underlying dataset was constructed from Horizon 2020 (H2020) research projects with Northern Germany as an exemplary set of regions chosen as the core of a social network analysis (SNA). The findings reveal that involvement in interregional projects is concentrated particularly in urban regions and correlates with GDP and population density. On the other hand, also organisations in regions with different structural characteristics are involved in interregional cooperation, and H2020 managed to introduce new cooperation patterns. Finally, the empirical data do not adequately match the regional smart specialisation strategies (S3) which raises questions on updating smart specialisation as a policy.
Can Social Media Be a Key Driver to Becoming an Entrepreneur?
Authors: Blanco-González-Tejero Cristina , Ulrich Klaus , Ribeiro-Navarrete Samuel 
Published: February 2024

Abstract
Social media have in recent years been considered crucial to entrepreneurial activity. There are, however, different ways of using them. Social media can be used from a professional or personal perspective to interact or influence by generating networks of contacts. Users freely share their opinions, desires, and concerns on the networks, thus contacting and interacting with influential people or with their own interest groups. Digitalization has given social media particular significance, but it is not clear that they are key motivating factors for entrepreneurial drive. Hence, through a survey conducted in organizations in the Community of Madrid, we have analyzed various factors such as the context and the intention to use social media and their influence on the decision to be an entrepreneur or engage in entrepreneurial activities. We used the fuzzy set qualitative comparative analysis (fsQCA) methodology, which allows us to provide reliability in the results without large samples. The findings suggest that social networks are dynamic and highly relevant tools today, with the ability to facilitate meaningful connections. Thus, while social media are influential and worthy of consideration, they are not the primary catalyst for entrepreneurial initiatives. Consequently, much of the information and knowledge generated in this area over the years is assumed to be normal and not particularly relevant to being an entrepreneur.
Science and values: a two-way direction
Authors: Ratti Emanuele , Russo Federica 
Published: February 2024

AbstractIn the science and values literature, scholars have shown how science is influenced and shaped by values, often in opposition to the ‘value free’ ideal of science. In this paper, we aim to contribute to the science and values literature by showing that the relation between science and values flows not only from values into scientific practice, but also from (allegedly neutral) science to values themselves. The extant literature in the ‘science and values’ field focuses by and large on reconstructing, post hoc, how values have influenced science; our reconstruction of the case studies, instead, aims to show that scientific concepts and methodstoo, because of specific identifiable characteristics,can promote some values rather than (or at the expense of) others. We explain this bidirectional relation in analogy to debates on the normativity of technical artifacts and on feminist approaches in science, and we illustrate our claims with cases from the health sciences and machine learning. While our arguments in this paper also draw on post hoc reconstructions, we intend to show where, in the science in the making, we should engage not only with the question whether a practice is value-laden, but also how specific conceptual and methodological choices can influence values down the road. All in all, these considerations expand the ways in which philosophers can contribute to more value-aware scientific practices.
Managing Provenance Data in Knowledge Graph Management Platforms
Authors: Kleinsteuber Erik , Al Mustafa Tarek , Zander Franziska , König-Ries Birgitta , Babalou Samira 
Published: February 2024

AbstractKnowledge Graphs (KGs) present factual information about domains of interest. They are used in a wide variety of applications and in different domains, serving as powerful backbones for organizing and extracting knowledge from complex data. In both industry and academia, a variety of platforms have been proposed for managing Knowledge Graphs. To use the full potential of KGs within these platforms, it is essential to have proper provenance management to understand where certain information in a KG stems from. This plays an important role in increasing trust and supporting open science principles. It enables reproducibility and updatability of KGs. In this paper, we propose a framework for provenance management of KG generation within a web portal. We present how our framework captures, stores, and retrieves provenance information. Our provenance representation is aligned with the standardized W3C Provenance Ontology. Through our framework, we can rerun the KG generation process over the same or different source data. With this, we support four applications: reproducibility, altered rerun, undo operation, and provenance retrieval. In summary, our framework aligns with the core principles of open science. By promoting transparency and reproducibility, it enhances the reliability and trustworthiness of research outcomes.
Capped flexosomes for prominent anti-inflammatory activity: development, optimization, and ex vivo and in vivo assessments
Authors: Ahmed Sadek , Aziz Diana E. , Sadek Mohamed A. , Tawfik Mai Ahmed 
Published: February 2024

AbstractThis study aimed to formulate diacerein (DCN)-loaded flexosomes for enhanced efficacy against osteoarthritis. A 23 D-optimal design was employed, investigating the impact of surfactant type (A), surfactant concentration (%w/v) (B), and oleylamine amount (mg) (C). Flexosomes were formulated using a rotary evaporator, and Design-Expert® software was utilized to statistically analyze entrapment efficiency (EE%), zeta potential (ZP), poly-dispersity index (PDI), and particle size (PS) to determine the optimum formula. The selection criteria prioritized increased ZP (as absolute value) and EE%, coupled with decreased PDI and PS. Rigorous physicochemical, in vivo, and ex vivo tests were conducted to validate the safety, stability, and activity of the optimal formula. Physicochemical assessments encompassed pH measurement, transmission electron microscopy, differential scanning calorimetry, release profiles, storage effects, and Fourier transform infrared spectroscopy. In vivo tests included permeation studies, histopathology, anti-inflammatory activity, and skin irritancy, while ex vivo tests focused on permeation parameters and skin deposition. The optimum formula demonstrated high desirability (0.931), along with favorable EE% (90.93%), ZP (− 40.4 mV), particle size (188.55 nm), and sustained behavior. Notably, improved in vivo permeation (132 µm), skin deposition (193.43 µg/cm2), and antinociceptive activity (66%) compared to DCN suspension (48 µm, 66.31 µg/cm2, and 26%, respectively) were observed. The optimal formula also exhibited excellent safety and storage characteristics. In conclusion, DCN-loaded flexosomes exhibit significant potential for effectively managing osteoarthritis.
Graphical Abstract
Experimental Investigation of the Mechanical Properties of Polypropylene Fiber-Reinforced Clay Soil and Development of Predictive Models: Effects of Fiber Length and Fiber Content
Authors: Yazici Mehmet Fatih , Keskin Siddika Nilay 
Published: February 2024

AbstractThis study investigated the mechanical properties of a low-plasticity clay soil reinforced with polypropylene (PP) fiber in various contents (0.05%, 0.10%, 0.15%, and 0.20%) and lengths (6, 12, and 19 mm). The reinforced specimens were subjected to unconsolidated-undrained (UU) triaxial compression tests under three different confining pressures (50, 100, and 200 kPa). The optimum fiber contents in specimens reinforced with 6-, 12-, and 19-mm PP fiber were determined as 0.15%, 0.15%, and 0.20%, respectively. As a result, the highest values regarding deviator stress at failure (σdev), energy absorption capacity (EAC), and shear strength parameters occurred in specimens containing 0.20% PP (19 mm). As a result of the reinforcement process, the most remarkable improvements in the σdev, cohesion, internal friction angle, and EAC values of the natural soil are 59.95%, 21.80%, 63%, and 34.70%, respectively. Linear and nonlinear relationships between σdev and fiber length, fiber content, and confining pressure were investigated by multiple linear regression and artificial neural network methods. Equations were generated to predict σdev of a low-plasticity clay soil reinforced with PP fiber and were made available to geotechnical researchers.
Auf Sand gebaut? Über den Versuch, die Basisdimensionen der Unterrichtsqualität in erziehungswissenschaftlicher „Theorie“ zu verankern
Authors: Rothland Martin 
Published: February 2024

ZusammenfassungIn der Diskussion der drei Basisdimensionen der Unterrichtsqualität wird neben der sparsamen Systematik, empirischen Fundierung und dem generischen Anspruch die solide theoretische Begründung des Modells hervorgehoben und als erziehungswissenschaftliche Theoriebasis das Studienbuch „Theorie der Schule“ (Diederich & Tenorth, 1997) verwendet. Welche Ausführungen und Aspekte daraus zur theoretischen Fundierung des Modells wie in Anspruch genommen werden und ob sie eine erziehungswissenschaftliche Begründung bieten, wird in diesem Beitrag gefragt und diskutiert.
Phase Composition and Phase Transformation of Additively Manufactured Nickel Alloy 718 AM Bench Artifacts
Authors: Zhang Fan , Johnston-Peck Aaron C. , Levine Lyle E. , Katz Michael B. , Moon Kil-Won , Williams Maureen E. , Young Sandra W. , Allen Andrew J. , Borkiewicz Olaf , Ilavsky Jan 
Published: February 2024

AbstractAdditive manufacturing (AM) technologies offer unprecedented design flexibility but are limited by a lack of understanding of the material microstructure formed under their extreme and transient processing conditions and its subsequent transformation during post-build processing. As part of the 2022 AM Bench Challenge, sponsored by the National Institute of Standards and Technology, this study focuses on the phase composition and phase evolution of AM nickel alloy 718, a nickel-based superalloy, to provide benchmark data essential for the validation of computational models for microstructural predictions. We employed high-energy synchrotron X-ray diffraction, in situ synchrotron X-ray scattering, as well as high-resolution transmission electron microscopy for our analyses. The study uncovers critical aspects of the microstructure in its as-built state, its transformation during homogenization, and its phase evolution during subsequent aging heat treatment. Specifically, we identified secondary phases, monitored the dissolution and coarsening of microstructural elements, and observed the formation and stability ofγ’ andγ” phases. The results provide the rigorous benchmark data required to understand the atomic and microstructural transformations of AM nickel alloy 718, thereby enhancing the reliability and applicability of AM models for predicting phase evolution and mechanical properties.
Copyright Law and the Lifecycle of Machine Learning Models
Authors: Kretschmer Martin , Margoni Thomas , Oruç Pinar 
Published: February 2024

AbstractMachine learning, a subfield of artificial intelligence (AI), relies on large corpora of data as input for learning algorithms, resulting in trained models that can perform a variety of tasks. While data or information are not subject matter within copyright law, almost all materials used to construct corpora for machine learning are protected by copyright law: texts, images, videos, and so on. There are global policy moves to address the copyright implications of machine learning, in particular in the context of so-called “foundation models” that underpin generative AI. This paper takes a step back, exploring empirically three technological settings through detailed case studies. We set out the established industry methodology of a lifecycle of AI (collecting data, organising data, model training, model operation) to arrive at descriptions suitable for legal analysis. This will allow an assessment of the challenges for a harmonisation of rights, exceptions and disclosure under EU copyright law. The three case studies are:Machine learning for scientific purposes, in the context of a study of regional short-term letting markets;Natural Language Processing (NLP), in the context of large language models;Computer vision, in the context of content moderation of images.We find that the nature and quality of data corpora at the input stage is central to the lifecycle of machine learning. Because of the uncertain legal status of data collection and processing, combined with the competitive advantage gained by firms not disclosing technological advances, the inputs of the models deployed are often unknown. Moreover, the “lawful access” requirement of the EU exception for text and data mining may turn the exception into a decision by rightholders to allow machine learning in the context of their decision to allow access. We assess policy interventions at EU level, seeking to clarify the legal status of input data via copyright exceptions, opt-outs or the forced disclosure of copyright materials. We find that the likely result is a fully copyright-licensed environment of machine learning that may have problematic effects for the structure of industry, innovation and scientific research.