bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maladaptation in an unequal world: an evolutionary model with heterogeneous agents
Authors: Antoci Angelo , Borghesi Simone , Galdi Giulio , Sodini Mauro , Ticci Elisa 
Published: March 2024

AbstractMaladaptation is steadily increasing its presence in agenda and debates about climate change and its impacts. The term denotes actions undertaken, at the individual or collective level, to defend against the adverse effects of climate change or environmental degradation, but that ultimately exacerbate the underlying risk factors. In this paper, we investigate the effects of maladaptation in terms of well-being and inequality in a two-population (North–South) evolutionary model. While agents in the South often face higher vulnerability to environmental degradation and limited defense mechanisms compared to their Northern counterparts, the latter stand to endure greater economic losses, in absolute terms. Our model demonstrates that the diffusion of maladaptive choices could result in a Pareto-dominated steady state, influencing inequality levels positively or negatively based on the scale of maladaptation impacts relative to the existing environmental degradation. These findings stress the imperative of integrating environmental risk studies with maladaptive effects and dynamics. Additionally, they advocate for international discourse not only on climate change mitigation but also on adaptive measures among countries.
An evolutive model of a boundedly rational consumer with changing preferences and reference group consumption
Authors: Bischi Gian Italo , Tramontana Fabio 
Published: March 2024

AbstractIn this paper, two dynamic models, recently proposed to describe the adaptive repeated choices of a boundedly rational consumer, are joined together. One considers a consumer adjusting the consumption level of a given good over time according to the observed discrepancy between expected and realized utility gain and modifies the utility function according to past consumption experience, also including saturation effects when past consumption is excessive. The other one considers the same adjustment mechanism with constant preferences but with a behavioral effect that introduces a tendency (or bias) to imitate a reference group of consumers. Merging these two models, a two-dimensional nonlinear dynamical system is obtained which describes consumers that decide their next period consumption of a given good by following two different (sometimes contrasting) criteria: their own utility maximization on the one side and imitation of a reference group of consumers on the other side. This leads to a greater uncertainty with respect to the model without the behavioral bias. Such uncertainty is studied through a numerical exploration of the long-run dynamics, guided by some global dynamical features of the nonlinear model, such as the folding action of the critical curves that characterize the behavior of the iterated noninvertible map and the singularities related to the presence of a vanishing denominator, namely focal points and prefocal curves. So, the aim of the paper is twofold: on the one side, it tries to contribute to the literature on the economic theory of boundedly rational consumers represented by evolutionary and behavioral approaches; On the other side, it tries to contribute to the recent literature about the global analysis of discrete dynamical systems characterized by contact bifurcations leading to the creation of complex topological structures of the attractors and their basins of attraction.
Framing to Make an Argument: The Case of the Genocide Hashtag in the Russia-Ukraine war
Authors: Musi Elena 
Published: March 2024

AbstractThis study tackles hashtags as framing devices which shape public arguments and controversies in computer-mediated communication environments. It focuses on the use of thegenocidehashtag on Twitter in the context of the Ukraine-Russia war. It proposes and showcases a methodology to surface how the semantic and discourse properties of the term genocide affect its framing properties as a hashtag which bears argumentative functions, directly or indirectly calling for action.
Effects of pockmark activity on iron cycling and mineral composition in continental shelf sediments (southern Baltic Sea)
Authors: Kurowski Stanisław , Łukawska-Matuszewska Katarzyna , Čović Anđela , Jozić Dražan , Brodecka-Goluch Aleksandra 
Published: March 2024

AbstractPockmarks are formed as a result of gas (methane) or/and groundwater outflow from the sea bottom. Methane, the second most important (after CO2) greenhouse gas, has a significant impact on biogeochemical processes in the bottom sediments by affecting the cycling of some elements, e.g. C, Fe, and S. Active pockmarks may also lead to changes in water column conditions by causing nutrients release from sediments. In the present study, we have focused on the impact of biogeochemical processes in pockmarks (methanogenesis, anaerobic methane oxidation, and groundwater seepage) on the transformation of iron (Fe) and the mineral composition of the sediment. In pore water, concentrations of hydrogen sulfide, phosphate, ammonia, sulfate, chloride, dissolved inorganic carbon, iron, and methane were analyzed. In the sediment, Fe speciation was performed using sequential extraction. The mineral composition was determined using powder X-Ray diffraction and scanning electron microscopy. The results from two pockmarks (with active gas seepage and groundwater infiltration) and two reference stations in the southern Baltic Sea show that geochemical conditions in pockmark sediments are significantly different from those in the typical muddy sea bottom. Pore water in pockmarks is characterized by lower sulfate and higher dissolved carbon concentrations as compared to areas of the seafloor where such structures are absent. This is due to the outflow of groundwater, which was confirmed by lower chloride concentration. In addition, sulfate is used to oxidize methane diffusing from deeper layers. Sediments in pockmarks are enriched in Fe(II) carbonates and depleted in Fe(III) (oxy)hydroxides, resulting from the anaerobic oxidation of methane with Fe(III) (Fe-AOM). Ferrous iron produced in large quantities during Fe-AOM is precipitated with carbonates.
A privacy-preserving federated learning framework for blockchain networks
Authors: Abuzied Youssif , Ghanem Mohamed , Dawoud Fadi , Gamal Habiba , Soliman Eslam , Sharara Hossam , ElBatt Tamer 
Published: March 2024

AbstractIn this paper we introduce a scalable, privacy-preserving, federated learning framework, coined FLoBC, based on the concept of distributed ledgers underlying blockchains. This is motivated by the rapid growth of data worldwide, especially decentralized data which calls for scalable, decenteralized machine learning models which is capable of preserving the privacy of the data of the participating users. Towards this objective, we first motivate and define the problem scope. We then introduce the proposed FLoBC system architecture hinging on a number of key pillars, namely parallelism, decentralization and node update synchronization. In particular, we examine a number of known node update synchronization policies and examine their performance merits and design trade-offs. Finally, we compare the proposed federated learning system to a centralized learning system baseline to demonstrate its performance merits. Our main finding in this paper is that our proposed decentralized learning framework was able to achieve comparable performance to a classic centralized learning system, while distributing the model training process across multiple nodes without sharing their actual data. This provides a scalable, privacy-preserving solution for training a variety of large machine learning models.
Graphical abstract
Effects of adaptive feedback through a
digital tool – a mixed-methods study on the course of self-regulated
learning
Authors: Mejeh Mathias , Sarbach Livia , Hascher Tina 
Published: March 2024

AbstractLifelong learning is emerging as a key priority for promoting equity and
sustainability in societies. Self-regulated learning (SRL) is a fundamental
requirement for achieving successful lifelong learning, and digitization is
increasingly influential in this regard. This mixed-methods study explores the
degree to which adaptive learning technology (ALT) can assist university students in
their SRL with timely and personalized support. Additionally, the study examines how
students perceive this feedback and incorporate it into their learning behavior.
Using hierarchical linear modeling, we investigated the development of SRL over a
9-week period. Semi-structured interviews were conducted with purposively selected
learners, based on stimulated recalls. The quantitative results demonstrate positive
development in certain components of SRL. Furthermore, the results indicate that
metacognitive activity can be partially predicted by motivational and emotional
states. The qualitative findings reveal that learners have varying perceptions of
feedback received from ALT and integrate it into their learning behaviors based on
their individual benefits. The results support the assumption that feedback provided
through educational technology must be precisely tailored to the needs of learners,
taking into account the dynamics of their individual learning processes. The study
contributes to the ongoing discussion on the design of educational
technology.
An effort to understand parents’ media mediation roles and early childhood children's digital game addiction tendency: A descriptive correlational survey study
Authors: Çalhan Ceren , Göksu İdris 
Published: March 2024

AbstractThis study aims to determine whether parents' media mediation roles are related to their early childhood children's digital game addiction tendencies. In addition, it examines whether these variables are related to the child's and parent's digital device usage habits and whether they differ according to various sociodemographic variables and digital device usage habits. In this context, we collected data from 433 parents (mother = 336, father = 97) with children aged 3–6. We analyzed the data using correlation analysis, one-way ANOVA, and t-test. Active-supportive, restrictive-supportive, active-limiting, restrictive-limiting, and active-interpreter roles of parents were negatively related to children's digital game addiction tendencies. In addition, parents' and children's digital device screen time was negatively associated with parents' media mediation roles and positively with children's digital game addiction tendencies. Mothers found their children more likely to have digital game addiction than fathers. Children of parents who play digital games have higher digital game addiction than those of parents who do not play, male children than female, children who have their own digital devices than those who do not, and children who only watch YouTube videos than those who only watch television channels for kids. Finally, we observed that mothers are more active in media mediation roles than fathers and that parents behave more restrictive toward their daughters.
The global challenge of reducing mercury contamination from artisanal and small-scale gold mining (ASGM): evaluating solutions using generic theories of change
Authors: Aldous Allison R. , Tear Tim , Fernandez Luis E. 
Published: March 2024

AbstractMercury contamination from artisanal and small-scale gold mining (ASGM) currently accounts for 37% of the global total, often affecting tropical regions where regulations, if they exist, are often poorly enforced. Ingestion by people and other animals damages the nervous, reproductive, and cognitive systems. Despite the efforts of many organizations and governments to curb mercury releases from ASGM, it is increasing globally. There are many possible interventions, all with significant complexity and cost. Therefore, we recommend taking an established systematic approach to articulate the current situation and construct theories of change (ToC) for different possible interventions for any government or organization trying to solve this problem. Here we present a high-level situation analysis and generic ToC to support a more coordinated approach that explicitly builds upon previous experience to identify organization- and situation-appropriate engagement on this issue. We then illustrate the use of these generic models to construct a specific ToC with a policy-focused entry point. This includes interventions through (1) engagement with the global Minamata Convention on Mercury; (2) support for existing national laws and policies connected to ASGM and mercury contamination; and (3) engagement of indigenous people and local communities with governments to meet the governments’ legal obligations. By methodically articulating assumptions about interventions, connections among actions, and desired outcomes, it is possible to create a more effective approach that will encourage more coordination and cooperation among governments and other practitioners to maximize their investments and support broad environmental and socio-political outcomes necessary to address this pernicious problem.
Eye movements in the development of geometric shape recognition: from sensory-motor processes to theoretical perception
Authors: Chumachenko Dmitry , Shvarts Anna , Dreneva Anna , Krichevets Anatoly 
Published: March 2024

AbstractEfficient recognition of geometric shapes is an important aspect of proficiency in geometry. Building theoretically on the cultural-historical approach enriched by the physiology of activity, we investigate theoretical perception in geometry—the ability to recognize conceptual geometric aspects of visual figures. Aiming to understand the development of theoretical perception, we investigate how sensory-motor processes of eye movements differ between adults and children when perceiving geometric figures. In an empirical study, we explored the variety of perceptual strategies used by first-grade students and compared them with the adults’ perception. The results reveal the contraction of eye movements: with growing expertise, foveal analysis—namely, an inspection of the figures by directing the gaze to their parts—is substituted by extrafoveal analysis—namely, perceiving without looking directly. The variety of the observed children’s perceptual strategies demonstrates that theoretical perception of different figures is heterogeneous. From the suggested theoretical perspective, the direct foveal inspection of particular figures is critical for the development of general anticipatory images of geometric shapes. Our theoretical analysis and empirical findings lead to distinguishing several functions of sensory-motor processes in theoretical perception in geometry. Those functions include positioning the retina in the best way for the comparison of sensory feedback with the geometric shape’s anticipatory image, advancing an anticipatory image based on visual experience, and regulating covert attention. All of these functions need to be taken into account when interpreting the results of eye-tracking studies in mathematics education research. Notably, our research highlights the limitations of the eye-mind hypothesis: direct fixations on a figure are not always needed for its theoretical perception and, the other way around, a fixation position may indicate the comparison of a broad extrafoveal region with an anticipatory image.
Comparison of individual and ensemble machine learning models for prediction of sulphate levels in untreated and treated Acid Mine Drainage
Authors: Hasrod Taskeen , Nuapia Yannick B. , Tutu Hlanganani 
Published: March 2024

AbstractMachine learning was used to provide data for further evaluation of potential extraction of octathiocane (S8), a commercially useful by-product, from Acid Mine Drainage (AMD) by predicting sulphate levels in an AMD water quality dataset. Individual ML regressor models, namely: Linear Regression (LR), Least Absolute Shrinkage and Selection Operator (LASSO), Ridge (RD), Elastic Net (EN), K-Nearest Neighbours (KNN), Support Vector Regression (SVR), Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Multi-Layer Perceptron Artificial Neural Network (MLP) and Stacking Ensemble (SE-ML) combinations of these models were successfully used to predict sulphate levels. A SE-ML regressor trained on untreated AMD which stacked seven of the best-performing individual models and fed them to a LR meta-learner model was found to be the best-performing model with a Mean Squared Error (MSE) of 0.000011, Mean Absolute Error (MAE) of 0.002617 and R2 of 0.9997. Temperature (°C), Total Dissolved Solids (mg/L) and, importantly, iron (mg/L) were highly correlated to sulphate (mg/L) with iron showing a strong positive linear correlation that indicated dissolved products from pyrite oxidation. Ensemble learning (bagging, boosting and stacking) outperformed individual methods due to their combined predictive accuracies. Surprisingly, when comparing SE-ML that combined all models with SE-ML that combined only the best-performing models, there was only a slight difference in model accuracies which indicated that including bad-performing models in the stack had no adverse effect on its predictive performance.
Shifting the terrain, enriching the academy: Indigenous PhD scholars’ experiences of and impact on higher education
Authors: Andrews Shawana , Gallant David , Mazel Odette 
Published: March 2024

AbstractIn Australia, much like other colonized locations such as Canada, New Zealand, and the USA, the colonial legacies embedded within higher education institutions, including the history of exclusion and the privileging of Western epistemologies, continue to make universities challenging places for Indigenous PhD scholars. Despite this, and while the numbers of Indigenous PhD scholars remain well below population parity, they are carving a space within the academy that is shifting the academic terrain and enriching the research process. Drawing on in-depth interviews with Indigenous PhD scholars working in the field of health and a qualitative survey of doctoral Supervisors and Advisory Committee Chairs, this paper explores the doctoral experience of Indigenous scholars. What becomes apparent, through this research, is that despite ongoing experiences of racism and alienation, these scholars are finding ways to circumvent inadequate supervisory processes, systems support, and research paradigms, to carve a path that centers Indigenous ways of knowing, being, and doing.
A New Strategy for Targeting UCP2 to Modulate Glycolytic Reprogramming as a Treatment for Sepsis A New Strategy for Targeting UCP2
Authors: Li Na , Deng Jiali , Zhang Junli , Yu Fei , Ye Fanghang , Hao Liyuan , Li Shenghao , Hu Xiaoyu 
Published: March 2024

AbstractSepsis is a severe and life-threatening disease caused by infection, characterized by a dysregulated immune response. Unfortunately, effective treatment strategies for sepsis are still lacking. The intricate interplay between metabolism and the immune system limits the treatment options for sepsis. During sepsis, there is a profound shift in cellular energy metabolism, which triggers a metabolic reprogramming of immune cells. This metabolic alteration impairs immune responses, giving rise to excessive inflammation and immune suppression. Recent research has demonstrated that UCP2 not only serves as a critical target in sepsis but also functions as a key metabolic switch involved in immune cell-mediated inflammatory responses. However, the regulatory mechanisms underlying this modulation are complex. This article focuses on UCP2 as a target and discusses metabolic reprogramming during sepsis and the complex regulatory mechanisms between different stages of inflammation. Our research indicates that overexpression of UCP2 reduces the Warburg effect, restores mitochondrial function, and improves the prognosis of sepsis. This discovery aims to provide a promising approach to address the significant challenges associated with metabolic dysfunction and immune paralysis.
Maternal Trauma and Psychopathology Symptoms Affect Refugee Children’s Mental Health But Not Their Emotion Processing
Authors: Michalek Julia E. , Qtaishat Lina , von Stumm Sophie , El Kharouf Amal , Dajani Rana , Hadfield Kristin , Mareschal Isabelle 
Published: March 2024

AbstractRefugee children’s development may be affected by their parents’ war-related trauma exposure and psychopathology symptoms across a range of cognitive and affective domains, but the processes involved in this transmission are poorly understood. Here, we investigated the impact of refugee mothers’ trauma exposure and mental health on their children’s mental health and attention biases to emotional expressions. In our sample of 324 Syrian refugee mother-child dyads living in Jordan (children’s Mage=6.32, SD = 1.18; 50% female), mothers reported on their symptoms of anxiety and depression, and on their children’s internalising, externalising, and attention problems. A subset of mothers reported their trauma exposure (n = 133) and PTSD symptoms (n = 124). We examined emotion processing in the dyads using a standard dot-probe task measuring their attention allocation to facial expressions of anger and sadness. Maternal trauma and PTSD symptoms were linked to child internalising and attention problems, while maternal anxiety and depression symptoms were associated with child internalising, externalising, and attention problems. Mothers and children were hypervigilant towards expressions of anger, but surprisingly, mother and child biases were not correlated with each other. The attentional biases to emotional faces were also not linked to psychopathology risk in the dyads. Our findings highlight the importance of refugee mothers’ trauma exposure and psychopathology on their children’s wellbeing. The results also suggest a dissociation between the mechanisms underlying mental health and those involved in attention to emotional faces, and that intergenerational transmission of mental health problems might involve mechanisms other than attentional processes relating to emotional expressions.
On the optimisation of phase fractions in harmonic structure materials
Authors: Shokry Abdallah , Ståhle Per , Orlov Dmytro 
Published: March 2024

AbstractMaterials with heterogeneous microstructures architected across several scales are becoming increasingly popular in structural applications due to unique strength–ductility balance. One of the most popular 3D-architected structure designs is harmonic structure (HS) where soft coarse-grain (CG) islands are embedded in a hard continuous 3D skeleton of ultrafine grains (UFGs). In this work, a series of HS with varying phase fractions and rheologies are studied based on several models. Model A focuses on a good fit with experimental data in the elastic–plastic transition region, model B focuses on a good fit at large-scale yielding, while in five intermediate models, phase rheology parameters are varied on a linear scale between the values for A and B. For each of the seven selected HS material models, structures with 19 different volumetric fractions of UFG were examined. It is found that the increase of UFG fraction leads to the monotonic increase of strength characteristics in HS material, while higher strain hardening rates in the phases lead to the enhancement of this effect. By contrast, the dependence of ductility characteristics on UFG fraction is non-monotonic having a local minimum at 30% UFG and a maximum at 60% UFG, while also significantly dependent on strain hardening in the phases. Namely, HS material with phases having significant strain hardening reveals the highest uniform elongation exceeding that in 100% CG material already at 40% UFG fraction. The fractions of UFG in a range of 58–62% form HS material with the highest possible uniform elongation.