bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social network and linguistic analysis of the #nutrition discourse on the social network platform X, formerly known as Twitter
Authors: Ellis Cassandra H. , Moore J. Bernadette , Ho Peter , Ahmed Wasim , Evans Charlotte E. L. 
Published: December 2024

Abstract
Social network analysis (SNA) of social media content allows information transfer to be visualised, identifies influential actors, and reveals public opinion. However, to date no research has investigated content related to nutrition on X. This study examined the #nutrition conversations on X (formerly Twitter) utilising SNA and linguistic methods. NodeXL Pro was used for network, semantic and sentiment analyses on English language posts including ‘#nutrition’ collected between 1 and 21 March 2023. The #nutrition network included 17,129 vertices (users) with 26,809 edges (relationships). NodeXL Pro was used to assess the structure of the network and the actors involved by calculating the network metrics. The results show a low density, dispersed network (graph density = 0.001) with most users communicating heavily with a small number of other users. These subgroup community cluster structures restrict information flow outside of the subgroups (modularity = 0.79). These network structures rely on influential users to share information (betweenness centrality range, 0 to 23,375,544). Notably, influential users were typically from both personal and not-for-profit accounts. Semantic analysis identified 97,000 word-pair edges with the most frequently discussed topics related to health, healthy lifestyle and diet, with a positive sentiment found across the network. By using SNA, semantic, and sentiment analyses, this study found a dispersed X network with a high proportion of unconnected users who did not have relationship with other users in the network. The findings reveal a publicly driven debate focused on healthy diets and lifestyle, with information primarily propagated through reposting.
Comparative analysis of laparoscopic, retro-muscular, and open mesh repair techniques for ventral and incisional hernias: a comprehensive review and meta-analysis
Authors: Elhadidi Amro , Shetiwy Mohamed , Al-Katary Mohammed 
Published: December 2024

AbstractVentral hernias are abnormalities in anterior abdominal wall occurring due to an incision or are congenital. This comprehensive review and meta-analysis aim to objectively compare laparoscopic to retro-muscular or any other mesh repair approach to manage ventral incisional hernia. To identify studies that managed ventral incisional hernia using laparoscopic, open, or retro-muscular mesh repair techniques, a comprehensive literature search was performed. Random effects model was used, and data were presented as log odds ratio (logOR) or as Hedge’s g with corresponding 95% confidence intervals (CI). Cochran’s Q test was implemented to measure heterogeneity among articles, and funnel plots were utilized to examine publication bias visually. Quality of all selected studies was assessed using Critical Appraisal Checklists for Studies developed by the Joanna Briggs Institute. 20 studies (16,247 patients) were included published from 2003 to 2023. Significantly reduced incisional hernias developed in laparoscopic group. The recurrence of hernia lowered with laparoscopic repair vs. open repair. In retro-muscular vs. laparoscopic, recurrence was lower, however, not statistically significant (p = 0.97). Open repair type resulted in a longer hospital stay than laparoscopic (p = 0.03). In laparoscopic repair, the postoperative complications reduced compared to the open repair (p = 0.02). Laparoscopic incisional and ventral hernia repair is a practical and successful alternative to open method. It is associated with shorter hospital stay and lower risk of postoperative complications. In few instances, retro-muscular mesh repair may be opted for.
Microstructure and tribological performance of ceramic-based self-lubricating sealing coating on a composite substrate
Authors: Wang Yi , Wang Xiaoli , Sun Linlin , Feng Tao , Hua Ke , Wang Haifeng 
Published: December 2024

AbstractThis work used high velocity oxygen fuel spraying technology to prepare three types of ceramic-based self-lubricating sealing coating on C/SiC substrates, with Yttria-stabilized zirconia as the matrix and different mass fractions of Mo and Ag as lubricating phases. The compositions are S1(50%YSZ40%CaF210%Mo), S2(50%YSZ40%CaF210%Ag) and S3 (40%YSZ30%CaF210%Mo10%Ag10%SiO2). The friction coefficient and wear rate of the coating were examined at room temperature (RT), 400°C and 800°C. The effects of different lubricating phases on the tribological properties of the coating were compared. The wear mechanism of the coating under different temperature environments will be revealed by clarifying the evolution law of the microstructure of the coating. The results show that the addition of Ag can improve the lubricating ability of the coating. Ag element forms a continuous and smooth tribo-layer on the sliding surface to reduce the friction coefficient of the coating. In addition, the lubricating effect of Ag element is more significant at medium and low temperatures. At 800°C, the S3 coating with both Ag and Mo exhibited excellent tribological properties. The wear mechanism of the coating is that it starts with adhesive wear and gradually transitions to abrasive wear as friction continues. This work provides theoretical support and experimental evidence for the construction of ceramic-based self-lubricating sealing coating with a wide temperature range.
Impact of climatic elements on the political and social development of Ilam city: a logistics perspective
Authors: Arzani Mosadegh , Borna Reza , Jafarpour Ghalehteimouri Kamran , Morshedi Jafar , Zohoorian Pordel Manijeh 
Published: December 2024

AbstractClimate factors in different climate change scenarios can influence social and political development in an area. This study explores the role of climatic factors in shaping the political and social landscape of Ilam, a city experiencing rapid urbanization due to population growth, increased demand for housing and commercial space, and the need for urban services. Through a descriptive-analytical approach and field data collection, the research surveyed 58 urban managers, researchers, and specialists in Ilam, using the SWOT technique to analyze the city's climatic strengths, weaknesses, opportunities, and threats in the context of political and social development. The results indicate that climate parameters play a significant role in Ilam's development, with the city's ability to align urban land development with soil temperature as a key strength. However, challenges exist in the technical sector, while opportunities lie in human resources and the integration of clean technologies. Environmental concerns, such as the degradation of agricultural land due to urban expansion, pose a threat to Ilam's development. The study confirms the impact of temperature and precipitation on Ilam's political and social development, emphasizing the interconnectedness between climate factors and the city's political and social dynamics. This research provides valuable insights into the complexities of urban development in Ilam, highlighting the importance of addressing the relationship between climate and political and social factors in this context.
Sources on the visual history of African wildlife, 1940s to 1980s: images that changed the animal world
Authors: Beinart William , McKeown Katie 
Published: December 2024

AbstractWe have recently completed the draft of a book on the changing representation of East African wildlife from the 1940s to the 1980s. We have used many published texts as well as visual representations such as photographs, films, and television. The output of material in these years was huge. We suggest that these media representations were a significant, and neglected, element in the emergence of a global animal-centric conservationist ethos. This article discusses some of the people involved and the papers, many of them in private hands, that we used. We believe that this is valuable material and should, where possible, be acquired by archives. The material is scattered, especially in Kenya, the UK, and USA. In the UK, the University of Bristol library now houses the Wildscreen film archives and also some private papers that could form the foundation for a larger collection.
‘Memory making’: commemoration of the fiftieth anniversary of the International Conference on Manding Studies (London, 1972)
Authors: Tiede Marcia 
Published: December 2024

AbstractParticipants in the International Conference on Manding Studies, held at the School of Oriental and African Studies (SOAS) in summer 1972, were contacted to share memories of the event in recognition of its fiftieth anniversary and while such recollections could still be gathered. An event in honour of fifty years of kora music at SOAS was also documented, bringing the project into the present. The result was a lengthy special feature in MANSA Kibaru, the newsletter of the Mande Studies Association (MANSA), in early 2023. Given the strong positive response from the MANSA community, which has historically looked back to the 1972 conference as a predecessor, it was decided to revise the newsletter’s special feature as a separate publication. This is an account of the process of bringing the commemoration together, the key contributors, and the timing and connections that shaped the outcome. It provides details that do not appear in the published commemoration. Some questions at the beginning of the project were cleared up by the evidence and accounts gathered. The Manding Conference’s ‘filiation’ or influence is touched upon, including the founding of MANSA. The selective and incomplete nature of this ‘memory making’ initiative is acknowledged.
Moderate deviations of many-server queues via idempotent processes
Authors: Puhalskii Anatolii 
Published: December 2024

Abstract
This paper obtains logarithmic asymptotics of moderate deviations of the stochastic process of the number of customers in a many-server queue with generally distributed inter-arrival and service times under a heavy-traffic scaling akin to the Halfin–Whitt regime. The deviation function is expressed in terms of the solution to a Fredholm equation of the second kind. A key element of the proof is the large-deviation principle in the scaling of moderate deviations for the sequential empirical process. The techniques of large-deviation convergence and idempotent processes are used extensively.
Expanding perspectives and understanding relational potential: Are mutually beneficial human-animal relationships compatible with current animal agricultural practices?
Authors: Ryan Erin B , Weary Daniel M , Zobel Gosia M , Webster Jim , Higgins E Tory , Franks Becca 
Published: December 2024

Abstract
Animal agriculture employs approximately one-eighth of world’s human population and results in the slaughter of over 160 billion animals annually, representing perhaps the most extensive intertwining of human and animal lives on the planet. In principle, close, intersubjective relationships (involving shared attention and mental states) between humans and the animals in agriculture are possible, though these are infrequently studied and are unlikely to be achieved in farming, given systemic constraints (e.g. housing and management). Much scientific research on human-animal relationships within agriculture has focused upon a fairly restricted range of states (e.g. reducing aversive human-animal interactions within standard systems, toward improving productivity and reducing injuries to workers). Considering human-animal relations along a continuum, we review scholarship supporting the rationale for expanding the range of relationships under consideration in animal welfare research, given the impacts these relationships can have on both animals and stockpersons, increasing consumer demand for humane food products, and the goal of providing animals under our care with good lives. Looking toward traditions that encourage taking the perspective of, and learning from non-humans, we provide entry points to approaches that can enable animal welfare research to expand to investigate a broader range of human-animal relationship states. By showing the potential for close mutually beneficial human-animal relationships, this line of research highlights pathways for understanding and improving the welfare of animals used in agriculture.
VigIA: prioritizing public procurement oversight with machine learning models and risk indices
Authors: Salazar Andrés , Pérez Juan F. , Gallego Jorge 
Published: December 2024

Abstract
Public procurement is a fundamental aspect of public administration. Its vast size makes its oversight and control very challenging, especially in countries where resources for these activities are limited. To support decisions and operations at public procurement oversight agencies, we developed and delivered VigIA, a data-based tool with two main components: (i) machine learning models to detect inefficiencies measured as cost overruns and delivery delays, and (ii) risk indices to detect irregularities in the procurement process. These two components cover complementary aspects of the procurement process, considering both active and passive waste, and help the oversight agencies to prioritize investigations and allocate resources. We show how the models developed shed light on specific features of the contracts to be considered and how their values signal red flags. We also highlight how these values change when the analysis focuses on specific contract types or on information available for early detection. Moreover, the models and indices developed only make use of open data and target variables generated by the procurement processes themselves, making them ideal to support continuous decisions at overseeing agencies.
Physics-constrained convolutional neural networks for inverse problems in spatiotemporal partial differential equations
Authors: Kelshaw Daniel , Magri Luca 
Published: December 2024

Abstract
We propose a physics-constrained convolutional neural network (PC-CNN) to solve two types of inverse problems in partial differential equations (PDEs), which are nonlinear and vary both in space and time. In the first inverse problem, we are given data that is offset by spatially varying systematic error (i.e., the bias, also known as the epistemic uncertainty). The task is to uncover the true state, which is the solution of the PDE, from the biased data. In the second inverse problem, we are given sparse information on the solution of a PDE. The task is to reconstruct the solution in space with high resolution. First, we present the PC-CNN, which constrains the PDE with a time-windowing scheme to handle sequential data. Second, we analyze the performance of the PC-CNN to uncover solutions from biased data. We analyze both linear and nonlinear convection-diffusion equations, and the Navier–Stokes equations, which govern the spatiotemporally chaotic dynamics of turbulent flows. We find that the PC-CNN correctly recovers the true solution for a variety of biases, which are parameterized as non-convex functions. Third, we analyze the performance of the PC-CNN for reconstructing solutions from sparse information for the turbulent flow. We reconstruct the spatiotemporal chaotic solution on a high-resolution grid from only 1% of the information contained in it. For both tasks, we further analyze the Navier–Stokes solutions. We find that the inferred solutions have a physical spectral energy content, whereas traditional methods, such as interpolation, do not. This work opens opportunities for solving inverse problems with partial differential equations.
Graph-based information management for retrofitting long-living assets
Authors: Laukotka Fabian N. , Moenck Keno , Schüppstuhl Thorsten , Krause Dieter 
Published: December 2024

Abstract
Many documents are produced over the years of managing assets, particularly those with long lifespans. However, during this time, the assets may deviate from their original as-designed or as-built state. This presents a significant challenge for tasks that occur in later life phases but require precise knowledge of the asset, such as retrofit, where the assets are equipped with new components. For a third party who is neither the original manufacturer nor the operator, obtaining a comprehensive understanding of the asset can be a tedious process, as this requires going through all available but often fragmented information and documents. While common knowledge regarding the domain or general type of asset can be helpful, it is often based on the experiences of engineers and is, therefore, only implicitly available. This article presents a graph-based information management system that complements traditional PLM systems and helps connect fragments by utilizing generic information about assets. To achieve this, techniques from systems engineering and data science are used. The overarching management platform also includes geometric analyses and operations that can be performed with geometric and product information extracted from STEP files. While the management itself is first described generically, it is also later applied to cabin retrofit in aviation. A mock-up of an Airbus A320 is utilized as the case study to demonstrate further how the platform can provide benefits for retrofitting such long-living assets.
Applying systems theory to global mental health
Authors: Jordans Mark J. D. 
Published: December 2024

Abstract
In recent years the evidence base for psychological interventions in low- and -middle-income countries (LMIC) has rapidly accrued, demonstrating that task-shifting models result in desired outcomes. Next, it is important to look at how this evidence translates into practice. In doing so, this paper argues that the field of global mental health might benefit from applying a system theory or system science perspective. Systems thinking aims to understand how different components are connected and interdependent within a larger emergent entity. At present much of the research efforts into psychological interventions in LMIC are focusing on single interventions, with little focus on how these interventions sit in, or influence, a larger system. Adopting systems theory and system dynamics tools can help in; (i) better analyzing and understanding the key drivers of mental health problems and services, (ii) optimizing mental health services; and (iii) understanding the organization of people, institutions and resources required for rolling out and scaling-up mental health services. This paper reflects on some of these merits of a systems perspective, as well as provides some examples.
Accelerated group sequential sampling
Authors: Hu Jun , Zhuang Yan 
Published: December 2024

Abstract
We propose a novel and unified sampling scheme, called the accelerated group sequential sampling scheme, which incorporates four different types of sampling scheme: (i) the classic Anscombe–Chow–Robbins purely sequential sampling scheme; (ii) the accelerated sequential sampling scheme; (iii) the relatively new k-at-a-time group sequential sampling scheme; and (iv) the new k-at-a-time accelerated group sequential sampling scheme. The first-order and second-order properties of this unified sequential sampling scheme are fully investigated with two illustrations on minimum risk point estimation for the mean of a normal distribution and on bounded variance point estimation for the location parameter of a negative exponential distribution. We also provide extensive Monte Carlo simulation studies and real data analyses for each illustration.
Building from the Brain: Advancing the Study of Threat Perception in International Relations
Authors: Landau-Wells Marika 
Published: December 2024

Abstract“Threat perception” is frequently invoked as a causal variable in theories of international relations and foreign policy decision making. Yet haphazard conceptualization and untested psychological assumptions leave its effects poorly understood. In this article, I propose a unified solution to these two related problems: taking the brain into account. I first show that this approach solves the conceptualization problem by generating two distinct concepts that generalize across existing theories, align with plain language, and are associated with specific brain-level processes: threat-as-danger perception (subjectively apprehending danger from any source) and threat-as-signal perception (detecting a statement of the intention to harm). Because both types of perception occur in the brain, large-scale neuroimaging data capturing these processes offer a way to empirically test some of the psychological assumptions embedded in IR theories. I conduct two such tests using assumptions from the literatures on conflict decision making (“harms are costs”) and on coercion (“intentions are inscrutable”). Based on an original analysis of fifteen coordinate-based meta-analyses comprising 500+ studies and 11,000+ subjects, I conclude that these assumptions are inconsistent with the cumulative evidence about how the brain responds to threats of either kind. Further, I show that brain-level data illuminate aspects of threat perception's impact on behavior that have not yet been integrated into IR theory. Advancing the study of threat perception thus requires a microfoundational approach that builds from what we know about the brain.
Helminth diversity of nutria (Myocastor coypus) across the Morava basin in the Czech Republic
Authors: Benovics Michal , Nosková Eva , Klimešová Anna , Škorpíková Lucie , Jaššová Ema , Drimaj Jakub , Slováček Jan , Mikulka Ondřej 
Published: December 2024

Abstract
The nutria was introduced to Europe from South America and kept for the fur industry. This semiaquatic rodent became a well-established species in the Czech Republic; however, it still poses a significant threat to the native fauna, not only as a natural competitor but also as a vector of non-indigenous parasites. Our research aimed to investigate the diversity of endoparasitic helminths in nutria, with a particular focus on assessing the risk posed by helminth species with zoonotic potential. A total of 46 nutria cadavers were collected at 8 locations in the Morava River basin and examined using standard parasitological post-mortem procedures. Additionally, coprological and molecular methods were used to identify the parasites. The presence of 6 helminth species was revealed. The highest prevalence was observed for Strongyloides myopotami (78.3%) and Trichuris myocastoris (37.0%), both of which are host-specific nematodes of nutria. Only 2 trematode taxa were recorded (Echinostoma sp. and a representative of the family Psilostomidae). The presence of alveolar hydatid cysts of Echinococcus multilocularis in the livers of 5 nutria specimens was also recorded. Herein, we provide novel molecular data for each parasite species collected, which is valuable for future phylogenetic analyses. Our findings also demonstrate that nutria in the Czech Republic serve as a carrier of helminths with zoonotic potential, particularly E. multilocularis and S. myopotami. Although the nutria is a relatively new species in local fauna, its synanthropic behaviour raises concerns about potential threats to human health, underscoring the importance of exercising caution when handling these animals.