bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lactate dehydrogenase contribution to symptom persistence in long COVID: A pooled analysis
Authors: Udeh Raphael , Utrero‐Rico Alberto , Dolja‐Gore Xenia , Rahmati Masoud , McEVoy Mark , Kenna Tony 
Published: September 2023

AbstractThere's critical need for risk predictors in long COVID. This meta‐analysis evaluates the evidence for an association between plasma lactate dehydrogenase (LDH) and long COVID and explores the contribution of LDH to symptoms persistent across the distinct post‐acute sequelae of COVID‐19 (PASC) domains. PubMed, EMBASE, Web of Science, and Google Scholar were searched for articles published up to 20 March 2023 for studies that reported data on LDH levels in COVID‐19 survivors with and without PASC. Random‐effect meta‐analysis was employed to estimate the standardized mean difference (SMD) with corresponding 95% confidence interval of each outcome. There were a total of 8289 study participants (3338 PASC vs. 4951 controls) from 46 studies. Our meta‐analysis compared to the controls showed a significant association between LDH elevation and Resp‐PASC [SMD = 1.07, 95%CI = 0.72, 1.41, p = 0.01] but not Cardio‐PASC [SMD = 1.79, 95%CI = −0.02, 3.61, p = 0.05], Neuro‐PASC [SMD = 0.19, 95%CI = −0.24, 0.61, p = 0.40], and Gastrointestinal‐PASC [SMD = 0.45, 95%CI = −1.08, 1.98, p = 0.56]. This meta‐analysis suggests elevated LDH can be used for predicting Resp‐PASC, but not Cardio‐PASC, Neuro‐PASC or gastrointestinal‐PASC. Thus, elevated plasma LDH following COVID infection may be considered as a disease biomarker.
Aligning global health policy and research with sustainable development: A strategic market approach
Authors: Haenssgen Marco J. 
Published: September 2023

AbstractAttaining Sustainable Development Goal 3 (SDG 3: Health and Well‐Being) faces a dual challenge of diminishing returns of established intervention designs, and a threat to future gains from complex inter‐connected global health challenges like antimicrobial resistance and global biodiversity loss. The growing movement of context‐sensitive approaches could help realise yet untapped potential for intervention designs, but contemporary global health policy and research still remain dominated by a model of individual market style choices. This paper therefore aims to support the development of global health planning processes that are more grounded and integrative across the SDGs. Reiterating calls for disruptive policy change is unlikely to impact the modus operandi of global health policy and research. This paper therefore builds on a logic that already finds widespread and intuitive application in their underlying planning processes: ‘the market’. However, it challenges the dominant supply‐and‐demand approach to healthcare markets and redefines them from a strategic marketing perspective. Translated to the interface of populations and health systems, the strategic market is a site for solving problems that are defined by people with multidimensional health needs. This framework offers four guiding questions to define the strategic market and six premises as a simple intellectual starting point and checklist for more grounded and inter‐sectorial action across the SDGs. The analysis of data from one of the largest behavioural survey data sets, covering 6683 villagers across China, India, Lao PDR and Thailand, demonstrates the relevance of the premises empirically.
Bayesian predictive model averaging approach to joint longitudinal‐survival modeling: Application to an immuno‐oncology clinical trial
Authors: Yao Zixuan , Morita Satoshi , Nishida Sumiyuki , Sugiyama Haruo 
Published: September 2023

SummaryIn immuno‐oncology clinical trials, multiple immunological biomarkers are usually examined over time to comprehensively and appropriately evaluate the efficacy of treatments. Because predicting patients' future survival statuses on the basis of such recorded longitudinal information might be of great interest, joint modeling of longitudinal and time‐to‐event data has been intensively discussed as a toolkit to implement such a prediction. To achieve a desirable predictive performance, averaging over multiple candidate predictive models to account for the model uncertainty might be a more suitable statistical approach than selecting the single best model. Although Bayesian model averaging can be one of the approaches, several problems related to model weights with marginal likelihoods have been discussed. To address these problems, we here propose a Bayesian predictive model averaging (BPMA) method that uses Bayesian leave‐one‐out cross‐validation predictive densities to account for the subject‐specific and time‐dependent nature of the prediction. We examine the operating characteristics of the proposed BPMA method in terms of the predictive accuracy (ie, the calibration and discrimination abilities) in extensive simulation studies. In addition, we discuss the strengths and limitations of the proposed method by applying it to an immuno‐oncology clinical trial in patients with advanced ovarian cancer.
Strong, Lightweight, and Shape‐Memory Bamboo‐Derived All‐Cellulose Aerogels for Versatile Scaffolds of Sustainable Multifunctional Materials
Authors: Dong Hongping , Li Xiazhen , Cai Zhiyong , Wei Song , Fan Shutong , Ge Yanglin , Li Xianjun , Wu Yiqiang 
Published: September 2023

AbstractStrong, lightweight, and shape‐memory cellulose aerogels have great potential in multifunctional applications. However, achieving the integration of these features into a cellulose aerogel without harsh chemical modifications and the addition of mechanical enhancers remains challenging. In this study, a strong, lightweight, and water‐stimulated shape‐memory all‐cellulose aerogel (ACA) is created using a combination strategy of partial dissolution and unidirectional freezing from bamboo. Benefiting from the firm architecture of cellulose microfibers bridging cellulose nanofibers /regenerated cellulose aggregated layers and the bonding of different cellulose crystal components (cellulose Iβ and cellulose II), the ACA, with low density (60.74 mg cm−3), possesses high compressive modulus (radial section: 1.2 MPa, axial section: 0.96 MPa). Additionally, when stimulated with water, the ACA exhibits excellent shape‐memory features, including highly reversible compression‐resilience and instantaneous fold‐expansion behaviors. As a versatile scaffold, ACA can be integrated with hydroxyapatite, carboxyl carbon nanotubes, and LiCl, respectively, via a simple impregnation method to yield functionalized cellulose composites for applications in thermal insulation, electromagnetic interference shielding, and piezoresistive sensors. This study provides inspiration and a reliable strategy for the elaborately structural design of functional cellulose aerogels endows application prospects in various multifunction opportunities.
Searching High‐Potential Dihydroxynaphthalene Cathode for Rocking‐Chair All‐Organic Aqueous Proton Batteries
Authors: Zhao Guoqing , Yan Xiaorong , Dai Yujie , Xiong Jiakui , Zhao Qian , Wang Xinyu , Yu Haiping , Gao Jiefeng , Zhang Naibo , Hu Mingjun , Yang Jun 
Published: September 2023

AbstractThe lack of acid‐proof high‐potential cathode largely limits the development and competitiveness of proton batteries. Herein, the authors systematically investigated six dihydroxynaphthalenes (DHNs) and found that 2,6‐DHN delivered the best cathode performance in proton battery with the highest redox potential (0.84 V, vs SHE) and a specific capacity of 91.6 mAh g−1 at 1 A g−1. In situ solid‐state electropolymerization of DHNs is responsible for the voltage and capacity fading of DHNs, and 2,6‐DHN's excellent electrochemical performance is derived from its high polymerization energy barrier. By compounding with rGO, the 2,6‐DHN/rGO electrode can maintain a specific capacity of 89 mAh g−1 even after 12 000 cycles at 5 A g−1. When it is paired with the 2,6‐dihydroxyanthraquinone (DHAQ) anode, the assembled rocking‐chair all‐organic proton battery exhibited a high cell voltage of 0.85 V, and excellent energy/power densities (70.8 Wh kg−1/850 W kg−1). This study showcases a new‐type high‐potential proton‐containing organic cathode and paves the way for constructing a high‐voltage rocking‐chair proton battery. Also, in situ solid‐state electropolymerization will inspire the further study of phenol‐based small‐molecule electrodes.
MetaHate: AI‐based hate speech detection for secured online gaming in metaverse using blockchain
Authors: Sanghvi Harshil , Bhavsar Rushir , Hundlani Vini , Gohil Lata , Vyas Tarjni , Nair Anuja , Desai Shivani , Jadav Nilesh Kumar , Tanwar Sudeep , Sharma Ravi , Yamsani Nagendar 
Published: September 2023

AbstractThe emergence of Web 3.0, blockchain technology (BC), and artificial intelligence (AI) are transforming multiplayer online gaming in the metaverse. This development has its concerns about safety and inclusivity. Hate speech, in particular, poses a significant threat to the harmony of these online communities. Traditional moderation methods struggle to cope with the immense volume of user‐generated content, necessitating innovative solutions. This article proposes a novel framework,MetaHate, that employs AI and BC to detect and combat hate speech in online gaming environments within the metaverse. Various machine learning (ML) models are applied to analyze Hindi–English code mixed datasets, with gradient boosting proving the most effective, achieving 86.01% accuracy. AI algorithms are instrumental in identifying harmful language patterns, while BC technology ensures transparency and user accountability. Moreover, a BC‐based smart contract is proposed to support the moderation of hate speech in the game chat. Integrating AI and BC can significantly enhance the safety and inclusivity of the metaverse, underscoring the importance of these technologies in the ongoing battle against hate speech and in bolstering user engagement. This research emphasizes the potential of AI and BC synergy in creating a safer metaverse, highlighting the need for continuous refinement and deployment of these technologies.
Co‐occurrence of periodontal lesions and dental wear in incisor and masticatory teeth in two sheep flocks in Brazil
Authors: Agostinho Sabrina Donatoni , Borsanelli Ana Carolina , Campello Paula Letícia , Saraiva Júlia Rebecca , Silva Tamires Ataides , Schweitzer Christiane Marie , Gaetti‐Jardim Elerson , Dutra Iveraldo dos Santos 
Published: September 2023

AbstractBackgroundPeriodontitis and tooth wear are multifactorial diseases with distinct etiopathogenesis that affect the health, feed efficiency and welfare of sheep.MethodsThis study evaluated the co‐occurrence of tooth wear and periodontal lesions in 129 ewes from two Brazilian flocks, clinically classified the lesions and presence of dental calculus, and identified potential pathogens in the dental biofilm of 63 ewes by polymerase chain reaction.ResultsOf the 129 ewes included in the study, 75 presented periodontal lesions, while all animals presented tooth wear and dental calculus. Of the animals with periodontal lesions, 16.2% had lesions in incisor teeth and 52.7% in masticatory teeth. Regarding excessive tooth wear, 38.6% had severe wear on the incisor teeth and 89.1% on the masticatory teeth. Ewes older than 36 months had a higher frequency of periodontal lesions in incisor teeth (p < 0.001) and a greater amount of dental calculus (p < 0.001), but there was no association between tooth wear and animal age. Fusobacterium nucleatum, Tannerella forsythia and Fusobacterium necrophorum predominated in periodontal lesions.LimitationThis study is limited by the small sample size and lack of diagnostic imaging to assess periodontal disease.ConclusionThe co‐occurrence of periodontal lesions and excessive dental wear involving both the incisor and masticatory teeth suggests that although the two diseases have different aetiologies, they likely have common risk factors.
Exploring the potential of long‐term agreements for achieving landscape‐scale environmental recovery
Authors: Barkley Lucy V. , Short Christopher J. , Chivers Charlotte‐Anne 
Published: September 2023

AbstractThis systematic review examines existing literature on environmental long‐term agreements (LTAs), such as conservation covenants, to identify the enablers and barriers to adoption and thus their potential for use in new contexts such as across land boundaries. To achieve environmental and societal targets, there is a clear and urgent need for more ambitious, longer‐term agri‐environment funding mechanisms which operate at a large scale. This is, in part, due to the recognition by national governments that shifts in policy for long‐term sustainability are needed since many existing agri‐environment schemes have not had the desired outcomes. The recent inclusion of conservation covenants in the UK's Environment Act demonstrates one such attempt to address this issue. Through critically analyzing the use of LTAs across the world using a systematic rapid evidence assessment approach, this article assesses the potential of these agreements to deliver landscape‐scale environmental benefits and public goods that are increasingly being sought by national governments as they strive for transformative policies to prevent and mitigate environmental and climate catastrophes. Exploring the enablers and barriers to adoption, alongside examples of successful LTAs, we provide an overview from which interested parties—policymakers, land managers, and private enterprises, among others—can begin to understand the opportunities and barriers which surround these agreements. Overall, this literature review identifies several factors likely to affect the uptake of LTAs, including concerns around land managers' and stakeholders' real/perceived capacity to engage, a need for flexibility, finance structures, and how monitoring and evaluation are managed.This article is categorized under:
Climate and Environment > Circular Economy
Climate and Environment > Ecosystem Services
Climate and Environment > Net Zero Planning and Decarbonization
Policy and Economics > Regional and International Strategies
Estimation of Temporal Variations in the Earth’s Gravity Field Using Novel Optical Clocks Onboard of Low Earth Orbiters
Authors: Shabanloui Akbar , Wu Hu , Müller Jürgen 
Published: September 2023

AbstractThe current generation of optical atomic clocks has reached a fractional frequency uncertainty of 1
$$\times $$

×
10
$$^{-18}$$

−18

(and beyond) which corresponds to a geopotential difference of 0.1 m
$$^{2}$$

2

/s
$$^{2}$$

2

. Those gravitational potential differences can be observed as gravitational redshift when comparing the frequencies of optical clocks. Even temporal potential variations might be determined with precise novel optical atomic clocks onboard of low-orbiting satellites such as SLR-like (e.g. LAGEOS-1/2) and GRACE-like missions.In this simulation study, the potential of precise space-borne optical clocks for the determination of temporal variations of low-degree Earth’s gravity field coefficients are investigated. Different configurations of satellite orbits, i.e. at different altitudes (between 400 and 6000 km) and inclinations, are selected as well as certain assumptions on the clock performance are made. A particular focus is put on how well degree-2 coefficients can be estimated from those optical clock measurements and how it compares to results from SLR.
Plagiarism Detection and Intertextuality Software
Authors: Anson Chris M. , Kruse Otto 
Published: September 2023

AbstractSoftware for plagiarism detection was developed in the early 2000s when powerful search engines offered writers opportunities for unattributed copy-and-pasting from other sources. Many algorithms were developed to reveal overlaps between original and source text. Although the software was imperfect, its use has spread across higher education, precipitating intense debates about its application to the teaching of writing. Because of instructors’ fear of false accusation and the effects on students’ anxiety, many educators have eschewed plagiarism detection systems. Others, however, have adopted plagiarism detection for formative and developmental reasons, such as helping students to understand intertextuality and making referencing a manageable skill. This chapter will briefly historicize the effects of the internet on the practice of plagiarism; describe the technology behind digital programs for plagiarism detection and its functional specifications; summarize some of the research on plagiarism detection programs; describe a few of the more popular programs; and conclude with implications.
Automated Text Generation and Summarization for Academic Writing
Authors: Benites Fernando , Delorme Benites Alice , Anson Chris M. 
Published: September 2023

AbstractIn this chapter, we discuss the implications of automatic text generation for academic writing. We first review the current state of the technology and how it is being used. We then discuss the implications of using automatic text generators for academic writing, including the need for users to be aware of the limitations of the technology and how to use it effectively. We also discuss how the use of automatic text generation can change the traditional stages of writing, and how the content generated by these systems is not justified by semantic or extra-linguistic criteria. We finally argue that notions that have been useful for explaining, analyzing, and teaching academic writing will need to be re-examined in the light of human–machine-interaction. (This abstract has been automatically generated using OpenAI and slightly post-edited; see this article’s Appendix for an explanation.)
Automated Scoring of Writing
Authors: Link Stephanie , Koltovskaia Svetlana 
Published: September 2023

AbstractFor decades, automated essay scoring (AES) has operated behind the scenes of major standardized writing assessments to provide summative scores of students’ writing proficiency (Dikli in J Technol Learn Assess 5(1), 2006). Today, AES systems are increasingly used in low-stakes assessment contexts and as a component of instructional tools in writing classrooms. Despite substantial debate regarding their use, including concerns about writing construct representation (Condon in Assess Writ 18:100–108, 2013; Deane in Assess Writ 18:7–24, 2013), AES has attracted the attention of school administrators, educators, testing companies, and researchers and is now commonly used in an attempt to reduce human efforts and improve consistency issues in assessing writing (Ramesh and Sanampudi in Artif Intell Rev 55:2495–2527, 2021). This chapter introduces the affordances and constraints of AES for writing assessment, surveys research on AES effectiveness in classroom practice, and emphasizes implications for writing theory and practice.
Hypertext, Hyperlinks, and the World Wide Web
Authors: Lang Susan , Baehr Craig 
Published: September 2023

AbstractHypertext, defined at the most essential level as “linked text,” and the hyperlink (shortened to simply “link”) serves as the foundation of much writing in digitally native spaces, impacting print-based writing. The World Wide Web has stood for nearly three decades as the primary implementation space for hypertextual writing. The characteristics of hyperlinking, intertextuality, multi-pathed organization, hypermedia, content forms, and collaborative authoring practices have come to replace print-based writing conventions as the dominant features of electronic-based ones. Research has been conducted on hypertext and the World Wide Web since their inception by computer scientists and writing specialists, among others, to better understand technological needs, writing pedagogies and practices, as writers work from an increasingly diverse input base—from computers to tablets to mobile devices.
Digital Note-Taking for Writing
Authors: Pitura Joanna 
Published: September 2023

AbstractNote-taking is prevalent in academia—it is the basis of scholarly work, i.e. searching for information, collecting and reading literature, writing and collaborating, referred to as a “primitive” that assists these information activities (e.g., Palmer, C. L., Teffeau, L. C., & Pirmann, C. M. (2009). Scholarly information practices in the online environment: Themes from the literature and implications for library service development. OCLC Research. https://accesson.kisti.re.kr/upload2/i_report/1239602399570.pdf). Researchers and higher education students take notes throughout the inquiry cycle, i.e. while designing research, collecting data, analysing data, and writing the report. In addition, with written assignments being a considerable part of student academic work, notes are taken in the writing process, from generating ideas for writing tasks, through text planning and drafting to its editing. As this process may be challenging, digital note-taking has the potential to facilitate writing in academic contexts (Matysek, A., & Tomaszczyk, J. (2020). Digital wisdom in research work. Zagadnienia Informacji Naukowej—Studia Informacyjne, 58(2A(116A)), 98–113. https://doi.org/10.36702/zin.705). Yet, despite the availability of literature concerning formal requirements of writing, such as style, structure, referencing, etc., relatively little literature deals with the note-taking activity that assists academic writing, and even less with digital note-taking. In order to bridge this gap, this chapter focuses on the note-taking activity and shows how digital tools can support note takers in the academic writing context.
Targeting Completeness: Using Closed Forms for Size Bounds of Integer Programs
Authors: Lommen Nils , Giesl Jürgen 
Published: September 2023

AbstractWe present a new procedure to infer size bounds for integer programs automatically. Size bounds are important for the deduction of bounds on the runtime complexity or in general, for the resource analysis of programs. We show that our technique is complete (i.e., it always computes finite size bounds) for a subclass of loops, possibly with non-linear arithmetic. Moreover, we present a novel approach to combine and integrate this complete technique into an incomplete approach to infer size and runtime bounds of general integer programs. We prove completeness of our integration for an important subclass of integer programs. We implemented our new algorithm in the automated complexity analysis tool to evaluate its power, in particular on programs with non-linear arithmetic.
Weighted Path Orders Are Semantic Path Orders
Authors: Saito Teppei , Hirokawa Nao 
Published: September 2023

AbstractWe explore the relationship between weighted path orders and (monotonic) semantic path orders. Our findings reveal that weighted path orders can be considered instances of a variant of semantic path orders that comprise order pairs. This observation leads to a generalization of weighted path orders that does not impose simplicity on their underlying algebras. As a result, the generalized version is capable of proving termination of term rewrite systems beyond the realm of simple termination. In order to assess practicality we provide experimental data comparing generalized weighted path orders with the original ones as well as other well-known classes of reduction orders.