bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bioaerosol-induced in vitro activation of toll-like receptors and inflammatory biomarker expression in waste workers
Authors: Eriksen Elke , Afanou Anani Komlavi , Straumfors Anne , Graff Pål 
Published: May 2023

Abstract
Purpose
Occupational exposure to bioaerosols during waste handling remains a health concern for exposed workers. However, exposure-related health effects and underlying immunological mechanisms are still poorly described.

Methods
The present study assessed the inflammatory potential of work-air samples (n = 56) in vitro and investigated biomarker expression in exposed workers (n = 69) compared to unexposed controls (n = 25). These quantitative results were compared to self-reported health conditions.

Results
Personal air samples provoked an activation of TLR2 and TLR4 HEK reporter cells in one-third of all samples, indicating that the work environment contained ligands capable of inducing an immune response in vitro. Monocyte levels, as well as plasma biomarker levels, such as IL-1Ra, IL-18 and TNFα were significantly higher in exposed workers, compared to the control group when confounding factors such as BMI, sex, age and smoking habits were accounted for. Furthermore, a significant exposure-related increase in midweek IL-8 levels was measured among exposed workers. Tendencies of increased prevalence of health effects of the respiratory tract were identified in exposed workers.

Conclusion
Inhalable dust provoked TLR activation in vitro, indicating that an exposure-related immune response may be expected in susceptible workers. However, despite significant differences in inflammatory plasma biomarker levels between exposed and unexposed workers, prevalence of self-reported health effects did not differ between the groups. This may be due to the healthy worker effect, or other factors such as adequate use of personal protective respiratory devices or adaptation to the work environment with reduced activation of the immune system.
Size-Dependent Behaviour of Hard Rock Under Triaxial Loading
Authors: González-Fernández Manuel A. , Estévez-Ventosa Xian , Alejano Leandro R. , Masoumi Hossein 
Published: May 2023

AbstractUnderstanding size effects is important to rigorously analyse the behaviour of rocks and rock masses at different scales and for different applications. A number of empirical and numerical studies have included size effects on the uniaxial compressive strength of different rocks, but only few have focussed on the triaxial compressive strength. In this study, several triaxial tests were conducted on granite samples at different confinements (from 0.2 to 15 MPa) and sizes (from 30 to 84 mm in diameter). The most relevant strength parameters were recovered including peak and residual strengths, orientation and frictional response of shear bands. Size effects were observed to be less dominant at high confining pressures for both peak and residual strengths. The resulting data were analysed in the context of size-dependent rock strength theories. For peak strength analyses, the unified size effect law (USEL) and the improved unified size law (IUSEL) were used, in which the double trends, ascending descending behaviours were observed. Size-dependent Hoek–Brown modified failure criteria based on USEL and IUSEL were fit to peak strengths exhibiting a good agreement between the models and the laboratory data. The brittle-ductile transition and the frictional behaviour of shear band under triaxial loading were also analysed. A clear brittle behaviour was particularly observed in samples with large-diameters tested at low confinements. Finally, in regards to frictional behaviour, the shear band angle found to be affected by both confinement and sample size.
Spatio-temporal variation in avian taxonomic, functional, and phylogenetic diversity and its relevance for conservation in a wetland ecosystem in Myanmar
Authors: Htay Thazin , Røskaft Eivin , Ringsby Thor Harald , Ranke Peter Sjolte 
Published: May 2023

AbstractWetland ecosystems host an extensive number of avian species and play therefore a key role in biodiversity conservation. However, avifauna in wetlands is severely impacted by the anthropogenic transformation of natural habitats into other land uses. Understanding how habitat changes influence avian community dynamics is crucial for effective management and conservation of bird habitats. Here, we assessed spatio-temporal variation in taxonomic, functional, and phylogenetic diversity, and assembly structures of the bird community in the Indawgyi Wetland Ecosystem in Myanmar. Bird surveys were seasonally conducted at 120 sample plots, which were equally distributed among four habitat types subject to different level of human influences (natural lake habitat, seasonally flooded grasslands, riparian forest, and agricultural land). Across habitat types, functional and phylogenetic diversity were the highest in the lake habitat, especially during the migration season, and the lowest in the cultivated habitat. Our results indicated over-dispersed functional and phylogenetic structures in the lake habitat, with clustered structures in the remaining habitats. Diversity of species important for conservation was also higher in the lake habitat and in areas far away from human disturbances. Spatial variation of bird community diversity suggests that conservation efforts in this ecosystem should concentrate more on the lake habitat and associated grassland habitats. Moreover, our results suggest the need for habitat restoration in riparian forests and increased sustainable agricultural practices in order to improve the contribution of these habitats to the diversity in the avifauna community. Our study highlighted the importance of integrating functional and phylogenetic dimensions into biodiversity analyses providing broader ecological insights for conservation.
A School Story, Not a Student Story: The Dyslexic Diagnosis Paradigm in Children’s and Young Adult Literature
Authors: Leung Elizabeth 
Published: May 2023

AbstractRepresentations of dyslexia have a history of educational and literary scholarship primarily concerned with how dynamic characters with learning disabilities are and if they are positively portrayed. This article uses narrative theory to analyze how diagnosis operates on a structural level to create what I call the dyslexic diagnosis paradigm. Examining school stories featuring characters with dyslexia published between 2007 and 2020, I demonstrate how this paradigm functions through a structural closure of struggle, diagnosis and accommodations, and a psychological closure consisting of shame, declaration, and acceptance within these novels. Variations or polytypes of this narrative are also common within this corpus which maintain the psychological closure of shame, declaration, and acceptance present within the prototypical narrative. While some disability counternarratives or dyslexic persistence narratives nuance the school story, the dyslexic diagnosis paradigm ultimately remains prevalent and upholds the medical model of disability within the educational system, promoting the flawed status quo of disability rather than asking readers to question the validity of the systems which enforce them.
The social cost of methane
Authors: Azar Christian , Martín Jorge García , Johansson Daniel JA. , Sterner Thomas 
Published: May 2023

AbstractA rapid and sustained reduction of methane emissions has been proposed recently as a key strategy to meet the climate targets of the Paris Agreement. The social cost of methane (SCM), which expresses the climate damage cost associated with an additional metric ton of methane emitted, is a metric that can be used to design policies to reduce the emissions of this gas. Here, we extend the DICE-2016R2 model so that it includes an improved carbon cycle and energy balance model as well as methane emissions, methane abatement cost, and an atmospheric methane cycle explicitly to be able to provide consistent estimations of the SCM. We estimate the SCM to lie in the range 880–8100 USD/tCH4in 2020, with a base case estimate of 4000 USD/tCH4. We find our base case estimate to be larger than the average SCM presented in other studies mainly due to the revised damage function we use. We also estimate the social cost of carbon (SCC) and find that SCM estimates are less sensitive to variations in the social discount rate than the SCC due to the relatively short lifetime of methane. Changes in the parameterization of the damage function have similar relative impacts on both SCM and SCC. Furthermore, we evaluate the ratio of SCM to SCC as an alternative metric to GWP-100 of CH4to facilitate tradeoffs between these two gases. We find this ratio to lie in the range 7–33 in 2020, with a base case estimate of 21, based on an extensive sensitivity analysis with respect to the discount rate, damage cost, and underlying emission scenarios. We also show that the global warming potential (GWP) and the SCM to SCC ratio are almost the same if the inverse of the effective discounting (in the social cost calculations) is equal to the time horizon used to evaluate the GWP. For comparison, the most widely used GWP, i.e., with a time horizon of 100 years, equals 27, hence in the upper range of the ratio we find using the SCM to SCC ratio.
Was humpty dumpty right?: Towards a functional definition of e-learning
Authors: O’Neill Aidan 
Published: May 2023

AbstractThis paper discusses the importance of definitions in the context of academic discussion, highlights the inconsistent terminology used to describe e-learning, and examines a range of different definitions of e-learning used by academic authors since 2011. Following an outline of the methodology, the paper identifies 15 unique definitions of e-learning in peer-reviewed papers published between January 2011 and December 2022. The 15 definitions are analysed for significant properties, and these properties are reviewed to assess whether they are essential components of e-learning. The paper then proposes a functional definition of e-learning, including all essential elements of e-learning and eliminating elements that may be present in some, but not all, instances of e-learning.
Young Japanese Children’s Subjectification and Objectification Through the Lens of Joint Labor in a Mathematical Activity at a Preschool: A Case Study
Authors: Nakawa Nagisa , Uegatani Yusuke , Otani Hiroki , Fukuda Hiroto 
Published: May 2023

AbstractThe objective of this case study was to identify the role of finger gestures in learning mathematics informally during play, especially in sociocultural settings. A mathematical activity involving addition was qualitatively analyzed at a Japanese preschool. We explored how the process of subjectification and objectification contributed to a mathematical activity at a Japanese preschool and how the role of preschoolers’ finger gestures changed during the process of learning mathematics. We utilized Radford’s theoretical construct of joint labor and analyzed Japanese preschool children’s mathematical behaviors from a sociocultural perspective. The subjects were 15 Japanese preschool children and their teacher. We relied on both Radford’s methodology and a microgenetic approach for the analysis. We found that subjectification and objectification proceeded in the scene of the conversations regarding addition; observing joint labor in a classroom activity offered valuable insights into these processes. In the activity, the children actively extended their practice of posing and answering quizzes, and learned how to resolve a conflict with the support of the teacher. Secondly, although the role of finger gestures was originally used to obtain correct answers to quizzes, it was reconstructed to solve the conflict between the children through the teacher’s mediation. This showed that, even in an environment where children implicitly learn mathematics, they learn from one another, including the teacher, and that gestures in mathematical communications function well for developing mathematical thinking and skills.
Salinity as a tool for strain selection in recirculating land-based production of Ulva spp. from germlings to adults
Authors: Cardoso Isabel , Meiβner Anneke , Sawicki Anja , Bartsch Inka , Valentin Klaus-Ulrich , Steinhagen Sophie , Buck Bela H. , Hofmann Laurie C. 
Published: May 2023

AbstractThe genus Ulva is globally distributed and has been thoroughly studied because of its functional biochemical composition, rapid growth rates and opportunistic features, and interest in Ulva cultivation is growing worldwide. In Europe, mostly near- and on-shore flow-through cultivation systems are used and land-based recirculating aquaculture systems (RAS) using fresh water or artificial seawater have not been developed for Ulva. While RAS provides quality control and can be located inland, maintenance costs are high. Using selected strains adapted to low-salinity could reduce seawater production costs and improve the economic feasibility. Therefore, our study assessed how salinity can be used as a tool for strain selection and optimization of functional traits. Growth rates and antioxidant activity of three species (four strains) of tubular and foliose Ulva from the NE-Atlantic and Mediterranean (foliose: Ulva lacinulata – two geographical strains, tubular: Ulva linza and Ulva flexuosa) were followed for three weeks at salinities ranging from 10 to 30 PSU. The tubular strains achieved optimal growth at a lower salinity than U. lacinulata. However, growth rates of both foliose strains were higher than of tubular strains, even at sub-optimal salinity. Therefore, U. lacinulata is a good candidate for RAS with artificial seawater, and the cost of salt can be reduced by up to 33.3% (20 PSU) without significantly reducing the growth rate of U. lacinulata. Higher antioxidant activity was achieved by reducing the salinity to 10 PSU for 10 days, suggesting that the functional traits of cultivated Ulva lacinulata can be optimized prior to harvest.
Melt Processible Biodegradable Blends of Polyethylene Glycol Plasticized Cellulose Diacetate with Polylactic Acid and Polybutylene Adipate-Co-Terephthalate
Authors: Tselana Bethuel M. , Muniyasamy Sudhakar , Ojijo Vincent O. , Mhike Washington 
Published: May 2023

AbstractEnhancing the melt processability of cellulose is key to broadening its applications. This is done via derivatization of cellulose, and subsequent plasticization and/or blending with other biopolymers, such as polylactic acid (PLA) and polybutylene adipate terephthalate (PBAT). However, derivatization of cellulose tends to reduce its biodegradability. Moreover, traditional plasticizers are non-biodegradable. In this study, we report the influence of polyethylene glycol (PEG) plasticizer on the melt processibility and biodegradability of cellulose diacetate (CD) and its blends with PLA and PBAT. CD was first plasticized with PEG (PEG-200) at 35 wt%, and then blended with PLA and PBAT using a twin-screw extruder. Blends of the PEG plasticized CD with PLA at 40 wt% and with PBAT at 60 wt% were studied in detail. Dynamic mechanical analysis (DMA) showed that PEG reduced the glass transition of the CD from ca. 220 °C to less than 100 °C, indicating effective plasticization. Scanning electron microscopy revealed that the CD/PEG-PBAT blend had a smoother morphology implying some miscibility. The CD/PEG-PBAT blend at 60 wt% PBAT had an elongation-to-break of 734%, whereas the CD/PEG-PLA blend had a tensile strength of 20.6 MPa, comparable to that of the PEG plasticized CD. After a 108-day incubation period under simulated aerobic composting, the CD/PEG-PBAT blend at 60 wt% PBAT exhibited a biodegradation of 41%, whereas that of the CD/PEG-PLA at 40 wt% PLA was 107%. This study showed that melt processible, biodegradable CD blends can be synthesized through plasticization with PEG and blending with PBAT or PLA.
Hydrothermal performance of a turbulent nanofluid with different nanoparticle shapes in a duct fitted with various configurations of coiled-wire inserts
Authors: Al-Tohamy Amro H. , Fadodun Olatomide G. , Kaood Amr 
Published: May 2023

AbstractThis paper examines the turbulent hydrothermal performance of boehmite/water–ethylene glycol$$(\upgamma -\mathrm{AlO}(\mathrm{OH})/{\mathrm{H}}_{2}\mathrm{O}-\mathrm{EG})$$(γ-AlO(OH)/H2O-EG)nanofluid flowing through a square duct fitted with various coiled-wire inserts (CWIs) using the finite volume method. The turbulent flow of$$\upgamma -\mathrm{AlO}(\mathrm{OH})/{\mathrm{H}}_{2}\mathrm{O}-\mathrm{EG}$$γ-AlO(OH)/H2O-EGnanofluid is modeled using single-phase and$$k-\varepsilon$$k-εmodel. A parametric study is carried out on the effect of Reynolds number ($$5.0\times {10}^{3}\le \mathrm{Re}\le 4.0\times {10}^{4}$$5.0×103≤Re≤4.0×104), the geometry of wire (circular, triangular, square, square-diamond, hexagon, octagon, and decagon), nanoparticle volume ratio ($$0\le \varphi \le 4\%$$0≤φ≤4%), and nanoparticle shapes (blade, brick, cylinder, platelet, and oblate-spheroid) on hydrodynamic and convective heat transfer performance (CHTP). The results showed that the combination between CWI and nanofluid enhances hydrothermal performance. For instance, among the geometries of CWI considered at$$\mathrm{Re}=5.0\times {10}^{3}$$Re=5.0×103, the square CWI has the highest normalized$${\mathrm{Nu}}^{\mathrm{G}}$$NuG(referencing empty channel) of 2.58, while the decagon has the lowest value of 1.78. Furthermore, regarding the nanoparticle shapes, the platelet shape has a maximum normalized$${\mathrm{Nu}}^{\mathrm{N}}$$NuN(referencing base fluid) of 1.53, while the oblate-spheroid has a minimum value of 0.93. Lastly, in terms of application, square and octagon wire-fitted channels are better than empty channel at low$$\mathrm{Re}$$Re, as the values of their hydrothermal performance evaluation criteria are greater than unity.
Exosomes derived from bone marrow mesenchymal stem cells alleviate biliary ischemia reperfusion injury in fatty liver transplantation by inhibiting ferroptosis
Authors: Tian Xuan , Wu Longlong , Li Xiang , Zheng Weiping , Zuo Huaiwen , Song Hongli 
Published: May 2023

AbstractFatty liver grafts are susceptible to ischemia reperfusion injury (IRI), increasing the risk of biliary complications after liver transplantation (LT). Ferroptosis, a newly recognized programmed cell death, is expected to be a novel therapeutic target for IRI. We investigated whether exosomes derived from heme oxygenase 1-modified bone marrow mesenchymal stem cells (HExos) relieve ferroptosis and protect biliary tracts from IRI in a rat fatty liver transplantation model. Rats were fed with a methionine choline deficient (MCD) diet for 2 weeks to induce severe hepatic steatosis. Steatotic grafts were implanted and HExos were administered after liver transplantation. A series of functional assays and pathological analysis were performed to assess ferroptosis and biliary IRI. The HExos attenuated IRI following liver transplantation, as demonstrated by less ferroptosis, improved liver function, less Kupffer and T cell activation, and less long-term biliary fibrosis. MicroRNA (miR)-204-5p delivered by HExos negatively regulated ferroptosis by targeting a key pro-ferroptosis enzyme, ACSL4. Ferroptosis contributes to biliary IRI in fatty liver transplantation. HExos protect steatotic grafts by inhibiting ferroptosis, and may become a promising strategy to prevent biliary IRI and expand the donor pool.
A lava flow simulation experience oriented to disaster risk reduction, early warning systems and response during the 2021 volcanic eruption in Cumbre Vieja, La Palma
Authors: Martín-Raya Nerea , Díaz-Pacheco Jaime , López-Díez Abel , Dorta Antequera Pedro , Cabrera Amílcar 
Published: May 2023

AbstractLava flows are one of the hazards involved in a volcanic eruption, and although they rarely cause the loss of human life, they are highly destructive in terms of damage to property and economic activity. Therefore, the management of volcanic disasters requires fast and accurate information on the behaviour and evolution of the flows, mainly related to their extension, displacement, and trajectory. This was the case during the disaster linked to the volcanic event that occurred on the island of La Palma in the Cumbre Vieja area at the end of 2021, which lasted eighty-five days. This paper describes part of the work performed by many different groups to provide predictive information aimed at feeding the early warning system set up during the disaster. This case shows the experience in the use of a probabilistic simulation algorithm implemented in the Q-LavHA plugin for the QGIS software, which is both easily accessible and applicable, to analyze its features in detail, as well as its predictive capacity. The results show that the model can efficiently and quickly satisfy the demand for this type of information, and its high similarity value is also validated by the Kappa index.
Estimating fuzzy measures of deprivation at local level in Tuscany
Authors: Crescenzi Federico , Neri Laura 
Published: May 2023

AbstractIn this paper we estimate monetary and non-monetary poverty measures at two sub-regional levels in the region of Tuscany (Italy) using data from the ad-hoc Survey on Vulnerability and Poverty held by Regional Institute from Economic Planning of Tuscany (IRPET). We estimate the percentage of households living in poverty conditions and three supplementary fuzzy measures of poverty regarding deprivation in basic needs and lifestyle, children deprivation, and financial insecurity. The key feature of the survey is that it was carried out after the COVID-19 pandemic, therefore, some of the items collected focus on the subjective perception of poverty eighteen months after the beginning of the pandemic. We assess the quality of these estimates either with initial direct estimates along with their sampling variance, and with a secondary small area estimation when the formers are not sufficiently accurate.
Estimating the innovation benefits of first-mover and second-mover strategies when micro-businesses adopt artificial intelligence and machine learning
Authors: Nafizah Ully Y. , Roper Stephen , Mole Kevin 
Published: May 2023

Abstract

Digital technologies have the potential to transform all aspects of firms’ operations. The emergence of advanced digital technologies such as Artificial Intelligence and Machine Learning raises questions about whether and when micro-businesses should adopt these technologies. In this paper we focus on how firms’ adoption decisions on Artificial Intelligence and Machine Learning influence their innovation capabilities. Using survey data for over 6,000 micro-businesses in the UK, we identify two groups of adopters based on the timing of their adoption of Artificial Intelligence and Machine Learning. ‘first movers’ – early adopters of the new technologies - and ‘second movers’- later adopters of the new technology. Probit models are used to investigate the innovation benefits of first and second mover adoption strategies. Our results suggest strong and positive impacts of adopting Artificial Intelligence and Machine Learning on micro-businesses’ innovation outcomes and innovation processes. We highlight the differential benefits of first mover and second mover strategies and highlight the role of technology characteristics as the differentiating factor. Our results emphasize both the innovation enabling role of digital technologies and the importance of an appropriate strategic approach to adopting advanced digital technologies.