bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinicopathologic features and long-term prognosis of hepatitis B virus-associated glomerulonephritis: a retrospective cohort study
Authors: Lu Hailing , Li Yu , Lai Maxiu , Guan Tianjun , Yu Yinghao , Zheng Zhiyong , Zhuang Yongze 
Published: July 2023

Abstract
Background
Hepatitis B virus-associated glomerulonephritis is a common form of secondary glomerulonephritis in China. However, the clinicopathological features and long-term prognosis of Hepatitis B virus-associated Glomerulonephritis remain only partially known.

Methods
Biopsy-proven Hepatitis B virus-associated Glomerulonephritis patients were enrolled between November 1994 and December 2013 at our center. The composite endpoints were doubling serum creatinine, end-stage renal disease, or death from renal disease during follow-up. The clinicopathological features and predictors of the long-term prognosis of Hepatitis B virus-associated Glomerulonephritis patients were explored.

Results
The median age of the 259 Hepatitis B virus-associated Glomerulonephritis patients was 31.0 years (IQR 24.0–40.0), and 71.0% were males. Among the patients, 45.2% presented with nephrotic syndrome, and 45.9% presented with proteinuria combined with hematuria. The two most prevalent pathological patterns were IgA nephropathy (27.0%) and membranous nephropathy (27.0%). The mean follow-up period was 68.8 ± 46.9 months. The 3-, 5-, and 10-year clinical event-free survival rates were 93.4%, 85.2%, and 70.3%, respectively. Multivariable Cox regression analysis showed that hypertension (HR 2.580, 95% CI 1.351–4.927, P = 0.004), hyperuricemia (HR 2.101, 95% CI 1.116–3.954, P = 0.021), glomerulosclerosis (P = 0.001), and intrarenal arterial lesions (P = 0.041) were independent predictors of composite clinical event endpoint. Patients in the antiviral therapy group exhibited a significantly better prognosis compared to those who received no antiviral therapy (log-rank χ2 = 5.772, P = 0.016).

Conclusion
Hepatitis B virus-associated Glomerulonephritis has specific clinicopathologic features and should not be considered a benign disease in adults. Hypertension, hyperuricemia, glomerulosclerosis, and intrarenal arterial lesions were independent predictors of the long-term prognosis in Hepatitis B virus-associated Glomerulonephritis patients. Antiviral therapy could be effective in improving the long-term prognosis of Hepatitis B virus-associated Glomerulonephritis patients.

Graphic abstract
Complex dual hesitant fuzzy TODIM method and their application in Russia–Ukraine war’s impact on global economy
Authors: Liu Yi , Tariq Muhammad , Khan Saifullah , Abdullah Saleem 
Published: July 2023

AbstractThe primary objective of this research is to examine how the Russia–Ukraine war impacted the global economy. To achieve this goal, we propose operational laws, a score and accuracy function, and a divergence measure for complex dual hesitant fuzzy sets. Furthermore, we investigate the challenges associated with multi-criteria decision-making (MCR) using aggregation operators and the TODIM method with complex dual hesitant fuzzy (CDHF) information. Drawing inspiration from arithmetic aggregation operations, we introduce several aggregation operators for complex dual hesitant fuzzy information, including the complex dual hesitant fuzzy weighted average (CDHFWA) operator, complex dual hesitant fuzzy ordered weighted average (CDHFOWA) operator, and complex dual hesitant fuzzy hybrid average (CDHFHA) operator. We thoroughly analyze the unique characteristics of these proposed operators and use them in conjunction with the TODIM method to develop practical approaches for solving complex dual hesitant fuzzy multi-criteria decision-making problems. To validate our approach and demonstrate its applicability, we provide a practical example of how the Russia–Ukraine war affected the global economy. Our study confirms the effectiveness of our approach and highlights how it can be used to solve real-world problems.
Cyclic reduction densities for elliptic curves
Authors: Campagna Francesco , Stevenhagen Peter 
Published: July 2023

AbstractFor an elliptic curve E defined over a number field K, the heuristic density of the set of primes of K for which E has cyclic reduction is given by an inclusion–exclusion sum $$\delta _{E/K}$$

δ

E
/
K

involving the degrees of the m-division fields $$K_m$$

K
m

of E over K. This density can be proved to be correct under assumption of GRH. For E without complex multiplication (CM), we show that $$\delta _{E/K}$$

δ

E
/
K

is the product of an explicit non-negative rational number reflecting the finite entanglement of the division fields of E and a universal infinite Artin-type product. For E admitting CM over K by a quadratic order $$\mathcal {O}$$
O
, we show that $$\delta _{E/K}$$

δ

E
/
K

admits a similar ‘factorization’ in which the Artin type product also depends on $$\mathcal {O}$$
O
. For E admitting CM over $$\overline{K}$$

K
¯

by an order $$\mathcal {O}\not \subset K$$

O
⊄
K

, which occurs for $$K=\textbf{Q}$$

K
=
Q

, the entanglement of division fields over K is non-finite. In this case we write $$\delta _{E/K}$$

δ

E
/
K

as the sum of two contributions coming from the primes of K that are split and inert in $$\mathcal {O}$$
O
. The split contribution can be dealt with by the previous methods, the inert contribution is of a different nature. We determine the ways in which the density can vanish, and provide numerical examples of the different kinds of densities.
Development of an ejector for passive hydrogen recirculation in PEM fuel cell systems by applying 2D CFD simulation
Authors: Singer Gerald , Köll Rebekka , Pertl Patrick , Trattner Alexander 
Published: July 2023

AbstractThe anode subsystem is a major energy consumer of polymer-electrolyte-membrane (PEM) fuel cell systems. A passive hydrogen recirculation system, like an ejector, is an excellent solution to maximize hydrogen utilization while maintaining low parasitic losses. However, high development efforts are necessary to maximize the performance of the ejector for the entire operating range. This research paper provides part of a toolchain for ejector development, consisting in particular of a multi-parameter simulation based on rotational symmetric 2D CFD. The 2D CFD greatly helps optimize the design of the ejector, reducing development effort, and increasing accuracy. In addition, the main correlations between thermodynamic states and geometry on the entrainment ratio are evaluated. Subsequently, an ejector is designed for a PEM fuel cell application using 2D CFD and the results show in which operating range a single ejector can be applied. This toolchain enables rapid design and optimization of ejector geometry, saving development time and cost while increasing accuracy and extending the operating range.
Analysis of urban expansion and its impact on temperature utilising remote sensing and GIS techniques in the Accra Metropolis in Ghana (1986–2022)
Authors: Frimpong Bernard Fosu , Koranteng Addo , Opoku Fosu Senior 
Published: July 2023

AbstractThe Accra Metropolis of Ghana has experienced rapid urban expansion over the past decades. Agricultural and forestlands have been transformed into urban/built-up areas. This study analysed urban expansion and its relationship with the temperature of Accra from 1986 to 2022. Multi-source datasets such as remote sensing (RS) and other ancillary data were utilised. Land use land cover (LULC) maps were produced employing the random forests classifier. Land surface temperature (LST) and selected d(RS) Indices were extracted. Regression techniques assessed the interplay between LST and remote sensing indices. The LULC maps revealed increasing trends in the urban/built-up areas at the expense of the other LULC types. The analysis from the LST and the RS indices revealed a direct relationship between temperature and urban/built-up areas and an inverse relationship between temperature and vegetation. Thus, spatial urban expansion has modified the urban temperature of Accra. The integrated utilisation of RS and GIS demonstrated to be an efficient approach for analysing and monitoring urban expansion and its relationship with temperature.
Developing Thick Cardiac Tissue with a Multilayer Fiber Sheet for Treating Myocardial Infarction
Authors: Li Junjun , Qu Xiang , Liu Li , Li Lingjun , Hua Ying , Zhang Jingbo , Ishida Masako , Yoshida Noriko , Tabata Akiko , Sougawa Nagako , Ito Emiko , Mochizuki-Oda Noriko , Harada Akima , Kawamura Takuji , Matsuura Ryohei , Wang Yingzhe , Morishima Keisuke , Miyagawa Shigeru , Sawa Yoshiki 
Published: July 2023

Abstract Human-induced pluripotent stem cell (hiPSC)-derived cardiac patches have been extensively used for treating myocardial infarction and have shown potential for clinical application. However, the limited patch thickness can hamper its therapeutic effect. We previously developed a fibrous scaffold that allowed the formation of well-organized cardiac tissue constructs. In the present study, based on the above technology, we developed a three-dimensional multilayer fibrous scaffold with dynamic perfusion, on which approximately 20 million hiPSC-derived cardiomyocytes (CMs) could be seeded in a single step and organized into 1 mm thick and viable tissue. The multilayer cardiac tissue demonstrated enhanced contractile properties and upregulated cytokine secretion compared with the control group. Notably, when used on the myocardial infarction model, the multilayer group showed improved functional recovery and less fibrosis. These results indicated that the appropriate hiPSC-CM dose requires careful evaluation in developing clinical therapy. The multilayer cardiac tissue group demonstrated significant improvement than the control group, indicating that higher doses of transplanted cells may have improved therapeutic effects in treating myocardial infarction.
Challenging AI for Sustainability: what ought it mean?
Authors: Falk Sophia , van Wynsberghe Aimee 
Published: July 2023

Abstract
This paper argues that the terms ‘Sustainable artificial intelligence (AI)’ in general and ‘Sustainability of AI’ in particular are overused to the extent that they have lost their meaning. The AI for (social) good movement is a manifestation of this trend in which almost any application used in the context of healthcare or agriculture can be classified as AI for good regardless of whether such applications have been evaluated from a broader perspective. In this paper, we aim to create a common understanding of what the ‘AI for Sustainability’ movement ought to mean. We distinguish between two possible AI for Sustainability applications, namely those that fulfill the necessary conditions and those that fulfill the sufficient conditions. The former are purely predictive systems that serve as information providers. The latter are directly involved in an activity that contributes to a sustainability goal. We argue that taking action is a key element in distinguishing between these two application groups, as inaction is the key bottleneck in effectively tackling climate change. Furthermore, we question how effective the use of AI applications can be for sustainability when the systems themselves are inherently unsustainable. Hence, AI for Sustainability should include both an action that contributes to a sustainable end goal as well as an investigation of the sustainability issues of the AI system itself. Following that, Sustainable AI research can be on a gradient: AI in an application domain, AI towards sustainability, and AI for Sustainability.
Team Dynamics and Nontechnical Skills Perception During the Disaster Response in Mozambique in 2019: A Survey Study Among the Italian Emergency Medical Team
Authors: Sacchetto Daniela , Raviolo Mario , Hubloue Ives , Valente Martina , Ragazzoni Luca 
Published: July 2023

AbstractObjective:Team dynamics and nontechnical skills in general are crucial for emergency medical teams (EMT). No study has ever examined these important issues during a real mission in the field. This study aimed to better investigate team dynamics and nontechnical skills for EMTs; it tried to understand if a real mission, when the people are obliged to work together for the first time, without a prior specific training focused on teamwork, is enough or not to work as an effective team in the field.Methods:The study is designed as a pre-test/post-test survey study, and it collected data from 51 people deployed to Mozambique in 2019. Three indexes (the self-efficacy (SE), the teamwork (TW), and the overall team’s performance (TW12)) were calculated as the average value of the rating given by all the participants. Open text feedback was also collected.Results:A positive trend was observed comparing the “post” data to the “pre” data, but results did not show a statistical significance, with the only exception of stratified analyses showing aP-value less than 0.05 for SE and TW12for some categories.Conclusions:According to the study findings, humanitarian workers feel good but not at their best; training programs focused on team dynamics can be really useful to improve self-confidence of people leaving for a mission.
Leveraging spatiotemporal information in meteorological image sequences: From feature engineering to neural networks
Authors: Bansal Akansha S. , Lee Yoonjin , Hilburn Kyle , Ebert-Uphoff Imme 
Published: July 2023

Abstract
Atmospheric processes involve both space and time. Thus, humans looking at atmospheric imagery can often spot important signals in an animated loop of an image sequence not apparent in an individual (static) image. Utilizing such signals with automated algorithms requires the ability to identify complex spatiotemporal patterns in image sequences. That is a very challenging task due to the endless possibilities of patterns in both space and time. Here, we review different concepts and techniques that are useful to extract spatiotemporal signals from meteorological image sequences to expand the effectiveness of AI algorithms for classification and prediction tasks. We first present two applications that motivate the need for these approaches in meteorology, namely the detection of convection from satellite imagery and solar forecasting. Then we provide an overview of concepts and techniques that are helpful for the interpretation of meteorological image sequences, such as (a) feature engineering methods using (i) meteorological knowledge, (ii) classic image processing, (iii) harmonic analysis, and (iv) topological data analysis; (b) ways to use convolutional neural networks for this purpose with emphasis on discussing different convolution filters (2D/3D/LSTM-convolution); and (c) a brief survey of several other concepts, including the concept of “attention” in neural networks and its utility for the interpretation of image sequences and strategies from self-supervised and transfer learning to reduce the need for large labeled datasets. We hope that presenting an overview of these tools—many of which are not new but underutilized in this context—will accelerate progress in this area.
Science Journalism and Epistemic Virtues in Science Communication: A Defense of Sincerity, Transparency, and Honesty
Authors: Figdor Carrie 
Published: July 2023

Abstract
In recent works, Stephen John (2018, Social Epistemology32(2), 75–87; 2019, Studies in History and Philosophy of Science Part A78, 64–72) has deepened the social epistemological perspective on expert testimony by arguing that science communication often operates at the institutional level, and that at that level sincerity, transparency, and honesty are not necessarily epistemic virtues. In this paper I consider his arguments in the context of science journalism, a key constituent of the science communication ecosystem. I argue that this context reveals both the weakness of his arguments and a need for further analysis of how non-experts learn from experts.
“Make All the Laws You Want”: The Catholic Left against Legal Liberalism, circa 1968
Authors: Mayeux Sara 
Published: July 2023

AbstractHow has American Catholicism interacted with American legal culture? Legal scholars have often examined this question in the context of contraception and abortion debates. This article focuses instead on the so-called Catholic left that emerged in protest against the Vietnam War in the late 1960s, and thereby seeks to bring the rich history of Catholic radicalism and peace activism into closer conversation with legal history. Drawing on both primary sources and a rich body of secondary literature in religious and social history that legal scholarship has not fully incorporated, the author examines ideas about law within the writings of Catholic left figures, including writer-monk Thomas Merton, sociologist-priest Paul Hanly Furfey, and activist-priest Berrigan brothers. Building on work by religious historians who have interpreted the Catholic radical tradition as a distinctive response to the limitations of political liberalism, this author emphasizes that the Catholic left also expressed a profound alienation from legal liberalism, with its veneration of lawyers and its faith in courts as sites of social progress. Revisiting the Catholic left through the lens of legal history raises questions for future research about the possible connections between leftist antiliberalism and the more familiar Catholic tradition of conservative illiberalism.
Phase transition for the generalized two-community stochastic block model
Authors: Lee Sunmin , Lee Ji Oon 
Published: July 2023

AbstractWe study the problem of detecting the community structure from the generalized stochastic block model with two communities (G2-SBM). Based on analysis of the Stieljtes transform of the empirical spectral distribution, we prove a Baik–Ben Arous–Péché (BBP)-type transition for the largest eigenvalue of the G2-SBM. For specific models, such as a hidden community model and an unbalanced stochastic block model, we provide precise formulas for the two largest eigenvalues, establishing the gap in the BBP-type transition.
Association of dietary inflammatory index with risk of gestational diabetes mellitus and preeclampsia: a systematic review and meta-analysis
Authors: Hong Li , Zhu Liyuan , Zhang Jinru , Fu Yueqi , Qi Xiaoyan , Zhao Mei 
Published: July 2023

AbstractFindings from observational studies have suggested a possible association between dietary inflammatory index (DII) and risk of gestational diabetes mellitus (GDM) and preeclampsia (PE). However, the results of these studies were inconclusive. A systematic review and meta-analysis was carried out to illuminate this association. Systematic literature search was conducted in PubMed, Web of Science, Cochrane Library, EMBASE, Scopus and other databases from inception until January 2023. The qualities of included studies were assessed using the Newcastle–Ottawa scale. Nine studies (seven cohort, two case–control) were included in the meta-analysis, including 11 423 participants from five different countries. The meta-analysis indicated that a 1-unit increase in the DII score, representing pro-inflammatory diet, was associated with 13 % higher risk of GDM (OR = 1·13; 95 % CI 1·02, 1·25, I2 = 68·4 %, P = 0·004) and 24 % higher risk of PE (OR = 1·24; 95 % CI 1·14, 1·35, I2 = 52·0 %, P = 0·125). Subgroup analysis found that this association was evident among studies with Chinese populations (OR = 1·16; 95 % CI 1·06, 1·28) and studies with mid pregnancy (OR = 1·20; 95 % CI 1·07, 1·34). The findings indicate that pro-inflammatory diet can increase the risk of GDM and PE. Considering some limitations in this study, more studies are needed to verify this association.
Environmental education in the classroom: pilot study in Cabo Verde suggests differing impacts on local knowledge and environmental attitudes
Authors: Rice Romy , Hejmadi Momna , Silva Herval , Kelsh Robert N. , Agues Janete , Engel Noémie , Székely Tamás 
Published: July 2023

AbstractTo execute environmental education effectively, the success and impacts of educational activities must be assessed. In areas of high biodiversity there is generally a lack of evaluation of the impact of environmental education. In this study we investigate the effect of a one-time classroom activity on student knowledge of local environmental issues, environmental attitudes and aspirations. The project was conducted on the island of Maio, Cabo Verde, a small, highly biodiverse island, as part of a classroom visit programme with the local environmental organization, Maio Biodiversity Foundation. We visited every fourth-grade class (i.e. students with an age range of 9–10 years) on the island (a total of 142 students) and delivered a half-day classroom activity. The results show that this activity did not influence environmental attitudes; however, it did significantly improve student knowledge and awareness of local environmental issues. This study shows that environmental education should not be assumed to improve attitudes and knowledge but requires individual evaluation for each type of activity. For environmental education to reach its full potential, activities should be planned in response to evaluation results.
God and being at an impasse: The case of John Duns Scotus and Jean-Luc Marion
Authors: Spinks Casey 
Published: July 2023

AbstractThis essay examines the relationship between Jean-Luc Marion's argument of ‘conceptual idolatry’ and John Duns Scotus’ doctrine of the univocity of being. I argue that Scotus does fall under Marion's criticisms, which radically undermine the use of ‘being’ in theology, but that univocity, in its barest Scotist form, also seems impossible to avoid. After arguing that attempts to move past this ontological conundrum fail, I conclude the relationship stands at an impasse. While this conclusion is critical, I make it for the sake of a constructive argument: post-metaphysical theology should reckon with the inevitability of being, appreciating this impasse between the apparent hegemony of being and the priority of God's self-revelation. Making the impasse clear at least points the way towards a renewed theological consideration of being.
Game semantics of Martin-Löf type theory
Authors: Yamada Norihiro 
Published: July 2023

AbstractThis work presents game semantics of Martin-Löf type theory (MLTT) equipped with the One, the Zero, the N, Pi, Sigma and Id types. Game semantics interprets a wide range of logic and computation, even the polymorphic
$\lambda$
-calculus; however, it has remained a well-known challenge in the past 25 years to achieve game semantics of dependent type theories such as MLTT, and past attempts lack directness or generality. For instance, the approach taken by Abramsky et al. interprets Sigma types indirectly by formal lists, not by games, making an interpretation of universes hopeless, and it is limited to a very specific class of dependent types. The difficulty of this challenge comes from a conflict between the extensionality of dependent types and the intensionality of game semantics. We overcome the challenge by inventing a novel variant of games, while we keep strategies unchanged, in such a way that this variant inherits the strong points of conventional game semantics. Also, our method enables an interpretation of subtyping on dependent types for the first time as game semantics. We finally give a new, game-semantic proof of the independence of Markov’s principle from MLTT. This proof illustrates an advantage of our intensional model over extensional ones such as Hyland’s effective topos.
Limiting empirical spectral distribution for the non-backtracking matrix of an Erdős-Rényi random graph
Authors: Wang Ke , Wood Philip Matchett 
Published: July 2023

AbstractIn this note, we give a precise description of the limiting empirical spectral distribution for the non-backtracking matrices for an Erdős-Rényi graph
$G(n,p)$
assuming
$np/\log n$
tends to infinity. We show that derandomizing part of the non-backtracking random matrix simplifies the spectrum considerably, and then, we use Tao and Vu’s replacement principle and the Bauer-Fike theorem to show that the partly derandomized spectrum is, in fact, very close to the original spectrum.