bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is there a pollution haven in European Union global value chain participation?
Authors: Campos-Romero Hugo , Mourao Paulo Reis , Rodil-Marzábal Óscar 
Published: July 2023

AbstractThis paper aims to test the pollution haven hypothesis within the European Union (EU), especially among newcomer countries, through the participation in global value chains (GVCs). The study used a combination of multiregional input–output method and multilevel mixed econometric analysis to investigate the relationship between global value chain trade flows, foreign direct investment flows, energy consumption, and carbon emissions across countries, sectors, and time. The study tested both the “pollution haven” and “pollution halo” hypotheses and found a non-linear relationship between foreign capital flows and carbon emissions, which became less relevant after the economic integration process. The results suggest the existence of a pollution haven in Europe. Although Eastern economies still exhibit problematic issues in relation to pollution control, they have made significant progress in reducing their emissions intensity. The conclusions include some policy recommendations based on the main findings of the research.
Monitoring Framework for the Performance Evaluation of an IoT Platform with Elasticsearch and Apache Kafka
Authors: Calderon Gonzalo , del Campo Guillermo , Saavedra Edgar , Santamaría Asunción 
Published: July 2023

Abstract
IoT platforms are in charge of extracting and processing the data that come from IoT networks, generating additional value, and providing access to the user through usable interfaces. However, the ever growing number of devices, networks, services and applications within the IoT ecosystem, and the recently adopted edge/cloud architecture, increase the complexity. Therefore, IoT platforms should integrate monitoring and visualization tools to facilitate deployment, management and maintenance tasks. In this work, we present the implementation and performance evaluation of an IoT modular platform for distributed architectures that combines the use of Elastic Stack tools (Elasticsearch, Kibana and Beats) and Apache Kafka. We have developed a monitoring framework based on Beats agents that supervise the platform performance attending to different metrics; and adapted the Kibana visualization tools to provide friendly and accessible information to platform administrators and users. Finally, we have deployed and evaluated the IoT platform in four real use cases, identifying the factors that affect the performance of the different modules: Edge Node, Data Streaming, Cloud Server and Search Engine.
Observation of structural, optical, electrical and magnetic properties of ternary copper-doped CeO2/GO/SrTiO3 nanocomposites
Authors: Hossam F. , Elseman Ahmed Mourtada , Rasly M. , Mahani R. M. , Sayed S. A. , Rashad M. M. 
Published: July 2023

AbstractA ternary system involving copper-substituted ceria (Cu:CeO2)0.95−y(GO)y(SrTiO3)0.05nanocomposite where the GO concentration (y) is varied between 0.15 and 0.30. The innovation of this work lies in the purposeful assembly of the nanocomposite using a grinding method, which was optimized through the individual fabrication of Cu-doped CeO2with different CuO concentrations. In the first, Cu-doped CeO2with various CuO concentrations (x = 0.0, 0.05, 0.1, 0.2, and 0.3) was first individually fabricated based on a sol–gel auto-combustion strategy to optimize the best ratio. The XRD profiles confirm the successful fabrication of cubic cerium (IV) oxide CeO2using glycine as a fuel at an annealing temperature of 400 °C for 2 h. AC conductivity was investigated for both Cu-doped CeO2and the ternary nanocomposite over a wide frequency range (10–1to 107 Hz) at room temperature. The conductivity showed lower values for CeO2doped with 0.05, 0.2, and 0.3 wt% CuO, whereas it showed its maximum values upon doping with 0.1 wt% CuO. Interestingly, the conductivity of graphene oxide–doped CeO2was 103times higher than that of pure CeO2, i.e., it increased from 1.7 × 10–6to 2 × 10–3S/cm. The magnetic-field dependence of MS of the ternary Cu-doped CeO2/GO/SrTiO3nanocomposites showed a systematic increase in MS as the Cu2+ion content increased. This strengthens the ferromagnetism in our samples as Cu2+ion content increases.
On the limited consensus of mountain pine beetle impacts on wildfire
Authors: Romualdi D. C. , Wilkinson S. L. , James P. M. A. 
Published: July 2023

Abstract
Context
The mountain pine beetle (MPB; Dendroctonus ponderosae) is a native bark beetle whose outbreaks leads to widespread conifer forest mortality. Of particular concern to forest and wildfire managers is the influence of MPB outbreaks on wildfire via spatial legacies left in impacted forest stands. There is, however, limited consensus in the literature regarding how MPB outbreaks affect wildfire across western North America.

Objectives
This meta-analysis aims to (1) summarize available evidence regarding MPB-wildfire interactions, and (2) identify environmental and methodological indicators associated with various wildfire responses (i.e., amplified, neutral, or dampened) post-outbreak.

Methods
We include peer-reviewed publications focusing on MPB outbreaks and subsequent wildfire activity in forests across western Canada and the USA between 2000 and 2021. A classification scheme was used to examine attributes of each publication to assess which indicators contribute most to their associated wildfire response.

Results
We found that spatial scale, forest fuels, and weather are main drivers of variation in wildfire response post-outbreak. Metrics of forest fuels and inclusion of weather data on a stand-scale are related to amplified fire responses, whereas dampened responses correspond to landscape-scale analyses. Furthermore, red-stage stands are associated with amplified fire response, whereas other stages are associated with dampened response—supporting current conceptual models of the importance of outbreak stage on wildfire.

Conclusions
Advancing our understanding regarding drivers of wildfire responses post-MPB outbreak is key to developing accurate, and comparative research studies. These findings provide crucial information for wildfire, and forest management agencies, especially in forests newly exposed to this disturbance interaction under climate change.
Pathogenic Role of Fibrinogen in the Neuropathology of Multiple Sclerosis: A Tale of Sorrows and Fears
Authors: Alruwaili Mubarak , Al-kuraishy Hayder M. , Alexiou Athanasios , Papadakis Marios , ALRashdi Barakat M. , Elhussieny Omnya , Saad Hebatallah M. , Batiha Gaber El-Saber 
Published: July 2023

AbstractMultiple sclerosis (MS) is an autoimmune demyelinating neurodegenerative disease of the central nervous system (CNS) due to injury of the myelin sheath by immune cells. The clotting factor fibrinogen is involved in the pathogenesis of MS by triggering microglia and the progress of neuroinflammation. Fibrinogen level is correlated with MS severity; consequently, inhibition of the fibrinogen cascade may reduce MS neuropathology. Thus, this review aimed to clarify the potential role of fibrinogen in the pathogenesis of MS and how targeting of fibrinogen affects MS neuropathology. Accumulation of fibrinogen in the CNS may occur independently or due to disruption of blood–brain barrier (BBB) integrity in MS. Fibrinogen acts as transduction and increases microglia activation which induces the progression of inflammation, oxidative stress, and neuronal injury. Besides, brain fibrinogen impairs the remyelination process by inhibiting the differentiation of oligodendrocyte precursor cells. These findings proposed that fibrinogen is associated with MS neuropathology through interruption of BBB integrity, induction of neuroinflammation, and demyelination with inhibition of the remyelination process by suppressing oligodendrocytes. Therefore, targeting of fibrinogen and/or CD11b/CD18 receptors by metformin and statins might decrease MS neuropathology. In conclusion, inhibiting the expression of CD11b/CD18 receptors by metformin and statins may decrease the pro-inflammatory effect of fibrinogen on microglia which is involved in the progression of MS.
Mean Field Models of Flux Transport Dynamo and Meridional Circulation in the Sun and Stars
Authors: Hazra Gopal , Nandy Dibyendu , Kitchatinov Leonid , Choudhuri Arnab Rai 
Published: July 2023

AbstractThe most widely accepted model of the solar cycle is the flux transport dynamo model. This model evolved out of the traditional$\alpha \Omega $αΩdynamo model which was first developed at a time when the existence of the Sun’s meridional circulation was not known. In these models the toroidal magnetic field (which gives rise to sunspots) is generated by the stretching of the poloidal field by solar differential rotation. The primary source of the poloidal field in the flux transport models is attributed to the Babcock–Leighton mechanism, in contrast to the mean-field$\alpha $α-effect used in earlier models. With the realization that the Sun has a meridional circulation, which is poleward at the surface and is expected to be equatorward at the bottom of the convection zone, its importance for transporting the magnetic fields in the dynamo process was recognized. Much of our understanding about the physics of both the meridional circulation and the flux transport dynamo has come from the mean field theory obtained by averaging the equations of MHD over turbulent fluctuations. The mean field theory of meridional circulation makes clear how it arises out of an interplay between the centrifugal and thermal wind terms. We provide a broad review of mean field theories for solar magnetic fields and flows, the flux transport dynamo modelling paradigm and highlight some of their applications to solar and stellar magnetic cycles. We also discuss how the dynamo-generated magnetic field acts on the meridional circulation of the Sun and how the fluctuations in the meridional circulation, in turn, affect the solar dynamo. We conclude with some remarks on how the synergy of mean field theories, flux transport dynamo models and direct numerical simulations can inspire the future of this field.
Evaluation of groundwater quality in the rural environment using geostatistical analysis and WebGIS methods in a Hungarian settlement, Báránd
Authors: Balla Dániel , Kiss Emőke , Zichar Marianna , Mester Tamás 
Published: July 2023

AbstractThe evaluation, visualization of environmental data from long-term monitoring, and making them accessible in a processed form in user-friendly interfaces on the Internet are important tasks of our time. The pollution of groundwater resources in settlements is a global phenomenon, the mitigation of which requires a number of environmental measures. In this study, water quality changes following the construction of a sewerage network were examined in the course of long-term monitoring between 2013 and 2022, during which 40 municipal groundwater wells were regularly sampled. Classifying the monitoring data into pollution categories based on water quality index (WQI) and degree of contamination index (Cd), a high degree of contamination was found in the period before the installation of the sewerage network (2014), as the majority of the wells were classified as contaminated and heavily contaminated. In the monitoring period following the installation of the sewerage network, a significant positive change was found in the case of most of the water chemical parameters tested (EC, NH4+, NO2−, NO3−, PO43−). Based on interpolated maps, it was found that an increasing part of the area shows satisfactory or good water quality. This was confirmed by the discriminant analysis as well, as it is possible to determine with an accuracy of 80.4% whether the given sample originates from the period before or after the installation of the sewerage network based on the given water chemical parameters. However, 8 years after setting up the sewerage network, the concentration of inorganic nitrogen forms and organic matter remains high, indicating that the accumulated pollutants in the area are still present. To understand the dynamics of purification processes, additional, long-term monitoring is necessary. Making these data available to members of the society can contribute to appropriate environmental measures and strategies.
Quantitatively mapping the research status and trends of vegetation responses to climate change with bibliometric analysis
Authors: Li Xinzhe , Wen Zhiqiang , Cui Lizhen , Chen Yang , Li Tong , Liu Hongdou , Xu Zhihong , Cui Xiaoyong , Song Xiufang 
Published: July 2023

Abstract
Purpose
Vegetation is a typical sensitive indicator of climate change, and therefore provides theoretical and valuable information for addressing issues arising from climate change including improving soil ecosystem services. Exploring how vegetation responses to climate change has become one of major hotspots of research. However, few scholars have performed bibliometric analyses of this field. This study investigated the current research activities and the trend developments of vegetation responses to climate change.

Materials and methods
We conducted a quantitative bibliometric analysis of 2,310 publications on vegetation responses to climate change from 1991 to 2021 retrieved in the Web of Science Core Collection. The analysis comprised significant journals, disciplines, and scholars, as well as partnerships between countries and institutions, keyword co-occurrence and burst analysis. The bibliometric analysis tools, Histcite, Vosviewer, CiteSpace software, and R (Bibliometrix package), were applied.

Results and discussion
The related publications on vegetation responses to climate change had been increasing exponentially in the past 30 years and its total global cited score reached its peak in 2010. The USA and China were the leading countries, with the Chinese Academy of Sciences having the highest number of publications and citations. The scholars who had the most citations were Allen CD, Bresears DD, and Running SW. Six research clusters were generated by keywords co-occurrence analysis, including impact, response, CO2, growth, climate change, and vegetation. These clusters represented the current research topics that highlighted the responses of vegetation to climate change, the manifestation of its impact, and coping strategies. In future research on vegetation, the emphasis is expected to be placed on “human activities” and “N2O emission”.

Conclusion
This study has performed a comprehensive and systematic and quantitative analysis of the publications on the responses of vegetation to climate change. The results reveal the characteristics, development patterns, and research trends of studies on vegetation activity in response to climate change, which sheds new insights into understanding the relationship between soil and climate.
A clustering heuristic to improve a derivative-free algorithm for nonsmooth optimization
Authors: Gaudioso Manlio , Liuzzi Giampaolo , Lucidi Stefano 
Published: July 2023

AbstractIn this paper we propose an heuristic to improve the performances of the recently proposed derivative-free method for nonsmooth optimization CS-DFN. The heuristic is based on a clustering-type technique to compute an estimate of Clarke’s generalized gradient of the objective function, obtained via calculation of the (approximate) directional derivative along a certain set of directions. A search direction is then calculated by applying a nonsmooth Newton-type approach. As such, this direction (as it is shown by the numerical experiments) is a good descent direction for the objective function. We report some numerical results and comparison with the original CS-DFN method to show the utility of the proposed improvement on a set of well-known test problems.
Data Sharing During Pandemics: Reciprocity, Solidarity, and Limits to Obligations
Authors: Silva Diego S. , Smith Maxwell J. 
Published: July 2023

AbstractSouth Africa shared with the world the warning of a new strain of SARS-CoV2, Omicron, in November 2021. As a result, many high-income countries (HICs) instituted complete travel bans on persons leaving South Africa and other neighbouring countries. These bans were unnecessary from a scientific standpoint, and they ran counter to the International Health Regulations. In short, South Africa was penalized for sharing data. Data sharing during pandemics is commonly justified by appeals to solidarity. In this paper, we argue that solidarity is, at best, an aspirational ideal to work toward but that it cannot ground an obligation to share data. Instead, low-and-middle income countries (LIMCs) should be guided by the principle of reciprocity, which states that we ought to return good for good received. Reciprocity is necessarily a conditional principle. LMICs, we argue, should only share data during future pandemics on the condition that HICs provide enforceable assurances that the benefits of data sharing will be equitably distributed and that LMICs won’t be penalized for sharing information.
The Effect of Substrate Stiffness on Elastic Force Transmission in the Epithelial Monolayers over Short Timescales
Authors: Tervonen Aapo , Korpela Sanna , Nymark Soile , Hyttinen Jari , Ihalainen Teemu O. 
Published: July 2023

Abstract
Purpose
The importance of mechanical forces and microenvironment in guiding cellular behavior has been widely accepted. Together with the extracellular matrix (ECM), epithelial cells form a highly connected mechanical system subjected to various mechanical cues from their environment, such as ECM stiffness, and tensile and compressive forces. ECM stiffness has been linked to many pathologies, including tumor formation. However, our understanding of the effect of ECM stiffness and its heterogeneities on rapid force transduction in multicellular systems has not been fully addressed.

Methods
We used experimental and computational methods. Epithelial cells were cultured on elastic hydrogels with fluorescent nanoparticles. Single cells were moved by a micromanipulator, and epithelium and substrate deformation were recorded. We developed a computational model to replicate our experiments and quantify the force distribution in the epithelium. Our model further enabled simulations with local stiffness gradients.

Results
We found that substrate stiffness affects the force transduction and the cellular deformation following an external force. Also, our results indicate that the heterogeneities, e.g., gradients, in the stiffness can substantially influence the strain redistribution in the cell monolayers. Furthermore, we found that the cells’ apico-basal elasticity provides a level of mechanical isolation between the apical cell–cell junctions and the basal focal adhesions.

Conclusions
Our simulation results show that increased ECM stiffness, e.g., due to a tumor, can mechanically isolate cells and modulate rapid mechanical signaling between cells over distances. Furthermore, the developed model has the potential to facilitate future studies on the interactions between epithelial monolayers and elastic substrates.
Ventral Hippocampal CA1 Pyramidal Neurons Encode Nociceptive Information
Authors: Wang Yue , Liu Naizheng , Ma Longyu , Yue Lupeng , Cui Shuang , Liu Feng-Yu , Yi Ming , Wan You 
Published: July 2023

AbstractAs a main structure of the limbic system, the hippocampus plays a critical role in pain perception and chronicity. The ventral hippocampal CA1 (vCA1) is closely associated with negative emotions such as anxiety, stress, and fear, yet how vCA1 neurons encode nociceptive information remains unclear. Using in vivo electrophysiological recording, we characterized vCA1 pyramidal neuron subpopulations that exhibited inhibitory or excitatory responses to plantar stimuli and were implicated in encoding stimuli modalities in naïve rats. Functional heterogeneity of the vCA1 pyramidal neurons was further identified in neuropathic pain conditions: the proportion and magnitude of the inhibitory response neurons paralleled mechanical allodynia and contributed to the confounded encoding of innocuous and noxious stimuli, whereas the excitatory response neurons were still instrumental in the discrimination of stimulus properties. Increased theta power and theta-spike coupling in vCA1 correlated with nociceptive behaviors. Optogenetic inhibition of vCA1 pyramidal neurons induced mechanical allodynia in naïve rats, whereas chemogenetic reversal of the overall suppressed vCA1 activity had analgesic effects in rats with neuropathic pain. These results provide direct evidence for the representations of nociceptive information in vCA1.
Emerging roles of noncoding RNAs in human cancers
Authors: Wu Shijie , Wu Yiwen , Deng Sijun , Lei Xiaoyong , Yang Xiaoyan 
Published: July 2023

AbstractStudies have found that RNA encoding proteins only account for a small part of the total number, most RNA is non-coding RNA, and non-coding RNA may affect the occurrence and development of human cancers by affecting gene expression, therefore play an important role in human pathology. At present, ncRNAs studied include miRNA, circRNA, lncRNA, piRNA, and snoRNA, etc. After decades of research, the basic role of these ncRNAs in many cancers has been clear. As far as we know, the role of miRNAs in cancer is one of the hottest research directions, however, it is also found that the imbalance of ncRNAs will affect the occurrence of gastric cancer, breast cancer, lung cancer, meanwhile, it may also affect the prognosis of these cancers. Therefore, the study of ncRNAs in cancers may help to find new cancer diagnostic and treatment methods. Here, we reviewed the biosynthesis and characteristics of miRNA, cricRNA, and lncRNA etc., their roles in human cancers, as well as the mechanism through which these ncRNAs affect human cancers.
Bringing Children’s and Teachers’ Agency Together to Create Meaningful Learning That Matters in a Diverse Preschool
Authors: Sisson J. H. 
Published: July 2023

AbstractThis article addresses children living and learning under difficult circumstances by problematising taken-for-granted views of what counts as learning and school readiness that perpetuate deficit views of children who have been impacted by forced migration. Drawing from a larger study focused on exploring how early childhood teachers re-design their pedagogy in culturally responsive ways, this article presents the findings of one team who shifted their views about a group of children impacted by forced migration who resisted planned learning experiences. The analysis focuses on how an assemblage of knowledge, actors, expressions and experiences came together to constitute children’s play and digital worlds as matter(ing) in teachers’ planning and pedagogy and teachers’ planning and pedagogy as matter(ing) in children’s play, demonstrating how children and their mediators of learning re-imagined their repertoires, identities and agencies to co-construct meaningful learning.
Electro-facies classification based on core and well-log data
Authors: Al Hasan Reda , Saberi Mohammad Hossein , Riahi Mohammad Ali , Manshad Abbas Khaksar 
Published: July 2023

AbstractFacies studies represent a key element of reservoir characterization. In practice, this can be done by making use of core and petrophysical data. The high cost and difficulties of drilling and coring operations coupled with the time-intensive nature of core studies have led researchers toward using well-log data as an alternative. In the Teapot Dome Oilfield, where core data are limited to those from only a single well, we used well-log data for reservoir electro-facies (EF) studies via two unsupervised clustering methods, namely multi-resolution graph-based clustering (MRGC) and self-organizing map (SOM). Satisfactory results were obtained with both methods, distinguishing seven electro-facies from one another, where MRGC had the highest discriminatory accuracy. The best reservoir quality was exhibited by electro-facies 1, as per both methods. Our findings can be used to avoid some time-intensive steps of conventional reservoir characterization approaches and are useful for prospect modeling and well location proposal.