bluuebunny/crossref_metadata_2025_split huggingface dataset:
NFC: a deep and hybrid item-based model for item cold-start recommendation
Authors: Bernardis Cesare , Cremonesi Paolo 
Published: October 2021

AbstractNew items, also called cold-start items, are introduced every day in the catalogs of numerous online systems. Due to the absence of previous preferences, recommending these items is difficult but important task for a recommender system. For this reason, the item cold-start recommendation problem still represents an interesting research topic for the community. In this work, we propose Neural Feature Combiner (NFC), a novel deep learning, item-based approach for cold-start item recommendation. The model learns to map the content features of the items into a low-dimensional hybrid embedding space. The features that compose the embeddings are then combined in order to reproduce collaborative item similarity values. We compare NFC with three variants of the same model that learn from user feedback, showing the advantages of learning from similarities in terms of accuracy and convergence time. With an extensive set of experiments on four datasets, we show that NFC outperforms several cutting edge approaches in the top-n recommendation task of cold-start items. Results in extremely cold (i.e., with a very low amount of interactions for training) and cold-warm hybrid scenarios prove that NFC effectively exploits collaborative information, leading to state-of-the-art accuracy. We finally conduct a qualitative analysis of the embeddings generated by different models, and we provide an analysis of the importance that different models assign to the input features, empirically demonstrating the robustness of the hybrid representations produced by our new model.
19F MRI Imaging Strategies to Reduce Isoflurane Artifacts in In Vivo Images
Authors: Staal Alexander H. J. , Veltien Andor , Srinivas Mangala , Scheenen Tom W. J. 
Published: October 2021

Abstract
Purpose

Isoflurane (ISO) is the most commonly used preclinical inhalation anesthetic. This is a problem in 19F MRI of fluorine contrast agents, as ISO signals cause artifacts that interfere with unambiguous image interpretation and quantification; the two most attractive properties of heteronuclear MRI. We aimed to avoid these artifacts using MRI strategies that can be applied by any pre-clinical researcher.

Procedures
Three strategies to avoid ISO chemical shift displacement artifacts (CSDA) in 19F MRI are described and demonstrated with measurements of 19F-containing agents in phantoms and in vivo (n = 3 for all strategies). The success of these strategies is compared to a standard Rapid Acquisition with Relaxation Enhancement (RARE) sequence, with phantom and in vivo validation. ISO artifacts can successfully be avoided by (1) shifting them outside the region of interest using a narrow signal acquisition bandwidth, (2) suppression of ISO by planning a frequency-selective suppression pulse before signal acquisition or by (3) preventing ISO excitation with a 3D sequence with a narrow excitation bandwidth.

Results
All three strategies result in complete ISO signal avoidance (p < 0.0001 for all methods). Using a narrow acquisition bandwidth can result in loss of signal to noise ratio and distortion of the image, and a frequency-selective suppression pulse can be incomplete when B1-inhomogeneities are present. Preventing ISO excitation with a narrow excitation pulse in a 3D sequence yields the most robust results (relative SNR 151 ± 28% compared to 2D multislice methods, p = 0.006).

Conclusion
We optimized three easily implementable methods to avoid ISO signal artifacts and validated their performance in phantoms and in vivo. We make recommendation on the parameters that pre-clinical studies should report in their method section to make the used approach insightful.
Geochemical baseline establishment, contamination level and ecological risk assessment of metals and As in the Limoncocha lagoon sediments, Ecuadorian Amazon region
Authors: Carrillo Katty Coral , Rodríguez-Romero Araceli , Tovar-Sánchez Antonio , Ruiz-Gutiérrez Gema , Fuente Javier R. Viguri 
Published: October 2021

Abstract
Purpose
The Limoncocha lagoon, inside a Ramsar site in the Ecuadorian Amazon, increasingly hosts ecotourism and energy development activities. This work estimates the local sediments’ baseline of As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, V and Zn using four methods. This makes it possible to apply single and integrated pollution indices to estimate the contamination level and the ecological risk of the sediments.

Methods
Seven sites were analysed for metal(oid)s by ICP-MS. The local baseline was estimated using the relative cumulative frequency method, the iterative 2σ- and 4σ-outlier-techniques and the normalisation method to a “conservative” element. Combinations of single Cf and Ef and integrated indices (NPI, mNPI, mCd, MEQ, RI, mPELq, mERMq and TRI) were applied.

Results
The relative cumulative frequency method had the best performance for the geochemical baselines. Cf and Ef indices classify sediments from a “low contamination” remote site to the “moderate contamination” and “minor enrichment” of the remaining sites due to As, Cd and Zn concentrations. The overall analysis of the integrated indices results in Ni, Zn and Cu being identified as priority pollutants because they have occasionally been associated with adverse biological effects in the centre of the lagoon and in the most anthropised areas. These are classified as moderately polluted with a medium–low priority risk level.

Conclusions
This work provides sediment baseline and contamination indicators for pollutants, which could be incorporated into the sediment quality assessment and monitoring programme of the Limoncocha lagoon. Ni, Cd and Cr due to the high baseline values in comparison with SQGs, and Cu and Zn due to their potential risk, should be of special attention.

Graphical abstract
The Impact of Residents' Leisure Time Allocation Mode on Individual Subjective Well-being: The Case of China
Authors: Wang Pengfei , Wei Xiang , Yingwei Xu , Xiaodan Cao 
Published: October 2021

AbstractAs the main tension in Chinese society has become that between people's growing need for a better life and unbalanced and inadequate development, leisure activities have become a main factor affecting the subjective well-being of Chinese residents. This study uses micro data from the 2019–2020 Chinese Residents’ Economic Life Survey as the sample, applies the latent class analysis (LCA) method to conduct a joint analysis of all leisure activities of individuals, and then divides individual leisure time modes into four types: general leisure, stationary leisure, family-friendly leisure and sports/health care-related leisure. To overcome endogeneity problems from missing variables, sample selection bias, and two-way causality, this paper uses the Heckman two-step and propensity score matching methods to empirically analyse the impacts of residents' leisure time allocation patterns on individual subjective well-being. The study finds that sports/health care-type leisure is most helpful in improving individual subjective well-being, followed by general leisure, family-friendly leisure and stationary leisure, which have relatively weaker impacts on subjective well-being. The estimation results remain robust and reliable after we introduce the idea of ​​misclassification probability to test the robustness of the findings. On this basis, a group heterogeneity analysis by region, income level, education level, marital status and age is carried out. The research conclusions of this article can help guide residents in rationally allocating their leisure time and provide a policy reference for the construction of leisure facilities in China’s cities.
The influence of community structure on opinion expression: an agent-based model
Authors: Cabrera Benjamin , Ross Björn , Röchert Daniel , Brünker Felix , Stieglitz Stefan 
Published: October 2021

AbstractSocial media has become important in shaping the public discourse on controversial topics. Many businesses therefore monitor different social media channels and try to react adequately to a potentially harmful opinion climate. Still, little is known about how opinions form in an increasingly connected world. The spiral of silence theory provides a way of explaining deviations between the perceived opinion climate and true beliefs of the public. However, the emergence of a spiral of silence on social media is hard to observe because only the thoughts of those who express their opinions are evident there. Recent research has therefore focused on modelling the processes behind the spiral of silence. A particular characteristic of social media networks is the presence of communities. Members of a community tend to be connected more with other members of the same community than with outsiders. Naturally, this might affect the development of public opinion. In the present article we investigate how the number of communities in a network and connectivity between them affects the perceived opinion climate. We find that higher connectivity between communities makes it more likely for a global spiral of silence to appear. Moreover, a network fragmented into more, smaller communities seems to provide more “safe spaces” for a minority opinion to prevail.
Genistein-induced Anticancer Effects on Acute Leukemia Cells Involve the Regulation of Wnt Signaling Pathway Through H4K20me1 Rather Than DNA Demethylation
Authors: Zhou Hua-rong , Shen Jian-zhen , Fu Hai-ying , Zhang Feng 
Published: October 2021

Abstract
Objective
To investigate the effects and mechanisms of genistein on the gene expression in the Wnt pathway in acute leukemia (AL) cells.

Methods
The expression of Wnt pathway genes and cell cycle-related genes were analyzed in two AL cell lines. Pyrophosphate sequencing was performed to determine the methylation degree. Then, the enrichment of H4K20me1 and H3K9ac was determined using ChIP-qPCR. Flow cytometry was used to analyze the cell cycle.

Results
The IC50 of genistein in the two AL cell lines was lower than that for the bone marrow mesenchymal stem cell line. Genistein upregulated H4K20me1, KMT5A and Wnt suppressor genes, including Wnt5a, and downregulated the downstream target genes of Wnt, such as c-myc and β-catenin. The methylation degree and H3K9ac enrichment in the Wnt5a promoter region remained unchanged. However, the enrichment of H4K20me1 in the Wnt5a promoter and coding regions increased. In addition, genistein upregulated Phospho-cdc2, Myt1, Cyclin A, Cyclin E2, p21 and Phospho-histone H3, but downregulated Phospho-wee1. Cell cycle arrest was induced in the G2/M phase.

Conclusion
Genistein inhibits the activation of the Wnt pathway by promoting the expression of Wnt5a through the activation of KMT5A and enrichment of H4K20me1 in the Wnt5a gene promoter and coding regions, rather than demethylation. Genistein also blocks the cell cycle in the G2/M phase. Therefore, genistein is a potential anti-leukemia drug.
In Situ Bulk Observations and Ab Initio Calculations Revealing the Temperature Dependence of Stacking Fault Energy in Fe–Cr–Ni Alloys
Authors: Neding Benjamin , Gorbatov Oleg I. , Tseng Jo-Chi , Hedström Peter 
Published: October 2021

Abstract
The dependence of stacking fault energy (

$${\gamma }_{\text{SFE}}$$

γ
SFE

) on temperature in austenitic Fe–Cr–Ni alloy powders was investigated by in situ high energy synchrotron X-ray diffraction and ab initio calculations in the temperature range from − 45 °C to 450 °C. The X-ray diffraction peak positions were used to determine the stacking fault probability and subsequently the temperature dependence of γ
SFE. The effect of temperature on the diffraction peak positions was found to be mainly reversible; however, recovery of dislocations occurred above about 200 °C, which also gave an irreversible contribution. Two different ab initio-based models were evaluated with respect to the experimental data. The different predictions of the models can be explained by their respective treatment of the magnetic moments for Cr and Ni, which is critical for the alloy compositions investigated. Ab initio calculations, taking longitudinal spin fluctuations (LSF) into consideration within the quasi-classical phenomenological model, predict a temperature dependence of

$${\gamma }_{\rm SFE}$$

γ
SFE

in good agreement with the experimentally evaluated trend of increasing γ
SFE with increasing temperature:

$$\left|\Updelta {\gamma }_{\rm SFE}/\Updelta T\right|=0.05 {\text{mJ}} {\text{m}}^{-2}/{\text{K}}.$$

Δ

γ
SFE

/
Δ
T

=
0.05

mJm

-
2

/
K
.

The temperature effect on γ
SFE is similar for all three investigated alloys: Fe–18Cr–15Ni, Fe–18Cr–17Ni, Fe–21Cr–16Ni (wt pct), while their room temperature

$${\gamma }_{\rm SFE}$$

γ
SFE

are evaluated to be 22, 25, 20 mJ m−2, respectively.
Spatiality of Social Stress Experienced by Refugee Women in Initial Reception Centers
Authors: Nassim Mehran , Jinan Abi Jumaa , Felicia Lazaridou , Naika Foroutan , Andreas Heinz , Ulrike Kluge 
Published: October 2021

Abstract
This study takes an interdisciplinary approach to understanding the multi-dimensionality of social stress within the spatiality of initial refugee reception centers in Berlin. By focusing particularly on the experiences of women who fled from Syria and Afghanistan, it situates this humanitarian issue within an analytical framework of gender-sensitive and culturally sensitive research and policymaking. Through qualitative interviews with 11 refugee women, the connection between the spatiality of initial reception centers and social stress is explored. This is done by thematically coding the data collected in the context of nine different initial reception centers across various districts in the city of Berlin. The study shows that in terms of the intercultural needs and practices of these women, social stress is triggered by a lack of essential privacy within the spatiality of these structures. However, privacy is not limited to a physical enclosure—it is about having control/freedom over different aspects of everyday life. This article highlights intercultural gaps in gender-sensitive and protection considerations during humanitarian responses.
Dispositional and situational moral emotions, bullying and prosocial behavior in adolescence
Authors: Oriol Xavier , Miranda Rafael , Amutio Alberto 
Published: October 2021

AbstractStudies that distinguish the role of dispositional and situational moral emotions in bullying situations remain limited in the international literature. This work, therefore, aims to analyze the role of dispositional and situational moral emotions in bullying and prosocial behavior in adolescents. Two studies were conducted: a cross-sectional study including 644 adolescents aged 14–18 years (M = 15.6, DT = 1.4) and a repeated measures design including 235 adolescents aged 10–15 years (M = 12.5, DT = 0.9). The objectives of Study 1 were 1) to validate two scales for the situational moral emotions elicited in bullying situations (elevation and moral disgust) and 2) to examine the relationships between dispositional and situational moral emotions and prosocial behavior toward victims and bullying behavior. The results show adequate psychometric properties for both elevation and moral disgust scales. Furthermore, both situational moral emotions are negatively related to bullying behavior, whereas dispositional emotions such as compassion and gratitude have a positive effect on prosocial behavior. Study 2 assessed the prospective relationship between dispositional gratitude and prosocial behavior toward victims and bullying behavior. The results of this study indicate that dispositional gratitude has a positive prospective effect on prosocial behavior towards victims and a negative effect on bullying behavior. In conclusion, the relevance of moral emotions for the prevention of bullying behavior is highlighted and the role that self-transcendent dispositional emotions have on prosocial behavior from the perspective of developmental psychology.
The Basque socioeconomic model (BSEM): a Lonergan perspective
Authors: Hoyt-O’Connor Paul , Cermelli Massimo , Calvo-Sotomayor Inigo 
Published: October 2021

AbstractBernard Lonergan maintained that economies are goods of order which, when properly disposed, make possible the regular provision of the material conditions for the fuller flourishing human. Lonergan’s economic thought tried to understand the economy related to a society’s civic institutions, political orders, and cultural traditions. In addition, he wished to explain the normative rhythms of economic development and the conditions of its dynamic equilibrium. In this sense, Lonergan’s analysis presents an alternative to conventional accounts of the kind of economic progress the Basque Country has enjoyed in recent decades, in ways that still resonate with the Basque Country’s emphasis on the centrality of the productive process and the values of its people.
Feature Engineering Techniques and Spatio-Temporal Data Processing
Authors: Forke Chris-Marian , Tropmann-Frick Marina 
Published: October 2021

AbstractMore and more applications nowadays use spatio-temporal data for different purposes. In order to be processed and used efficiently, this unique type of data requires special handling. This paper summarizes methods and approaches for feature selection of spatio-temporal data and machine learning algorithms for spatio-temporal data engineering. Furthermore, it highlights relevant work in specific domains. The range of possible approaches for data processing is quite wide. However, in order to use these approaches with the spatio-temporal data in a meaningful and practical way, individual data processing steps need to be adapted. One of the most important steps is feature engineering.
Knowledge distillation on neural networks for evolving graphs
Authors: Antaris Stefanos , Rafailidis Dimitrios , Girdzijauskas Sarunas 
Published: October 2021

AbstractGraph representation learning on dynamic graphs has become an important task on several real-world applications, such as recommender systems, email spam detection, and so on. To efficiently capture the evolution of a graph, representation learning approaches employ deep neural networks, with large amount of parameters to train. Due to the large model size, such approaches have high online inference latency. As a consequence, such models are challenging to deploy to an industrial setting with vast number of users/nodes. In this study, we propose DynGKD, a distillation strategy to transfer the knowledge from a large teacher model to a small student model with low inference latency, while achieving high prediction accuracy. We first study different distillation loss functions to separately train the student model with various types of information from the teacher model. In addition, we propose a hybrid distillation strategy for evolving graph representation learning to combine the teacher’s different types of information. Our experiments with five publicly available datasets demonstrate the superiority of our proposed model against several baselines, with average relative drop$$40.60\%$$40.60%in terms of RMSE in the link prediction task. Moreover, our DynGKD model achieves a compression ratio of 21:100, accelerating the inference latency with a speed up factor$$\times 30$$×30, when compared with the teacher model. For reproduction purposes, we make our datasets and implementation publicly available athttps://github.com/stefanosantaris/DynGKD.
The socioeconomic determinants of sustainable residential water consumption in Athens: empirical results from a micro-econometric analysis
Authors: Kostakis Ioannis 
Published: October 2021

AbstractThis paper provides empirical evidence on the effects of socioeconomic characteristics on residential water consumption. The case of Athens is taken as an example for the empirical investigation, using data from the 2019 Household Budget Survey. Employing ordinary, two- and three-stage least squares, seemingly unrelated regression equations and simultaneous quantile specifications, we found that residential water demand is highly price inelastic. Furthermore, empirical results show that water consumption is positively related to household age while more educated households and unemployed persons seem to follow more environmentally friendly behaviour with respect to water demand. Income, gender, house ownership and population density seem to insignificantly affect residential water demand. Our empirical findings might have important national and regional policy implications in the design of sustainable water demand management.
The duty to cooperate in state interactions for the sustainable use of international watercourses
Authors: Oranye Nkechinyelu Patricia , Aremu Abimbola W. 
Published: October 2021

AbstractThe duty to cooperate is a universal principle engrained in International Law. A sequel to this principle is the concept of equitable participation and taking all appropriate measures not to cause significant harm. These principal norms in International Water Law can only function through the cooperation of states. Bilateral and multilateral treaties make this duty a mandatory obligation for contracting parties. Nevertheless, disputes still exist among riparian states over their use of international shared waters. This paper, therefore, seeks to determine how the application of the duty to cooperate in the development of transboundary water can be achieved through the procedural norm of equitable participation and the substantive norm of taking all appropriate measures not to cause significant harm. Through a doctrinal (analytical) approach, empirical studies, as well as the legal framework on international watercourses management will be examined to understand the various roles of states on a transboundary river. The duty to cooperate will also be appraised to ascertain the modalities for its application in International Water Law. This study aims to foster a sustainable pathway to ensuring cooperation in the use of international waters in state interactions. This is relevant for equitable utilization of the waters and their resources.
Entrepreneurial Ecosystems
Authors: Ozkazanc-Pan Banu , Clark Muntean Susan 
Published: October 2021

Based on extensive fieldwork, this book demonstrates how gender is an organizing principle of entrepreneurial ecosystems and makes a difference in how ecosystem resources are assembled and how they can be accessed. By bringing visibility to how ecosystem actors are heterogeneous across identities, interactions and experiences, the book highlights the role and complexity of individual, organizational, and institutional factors working in concert to create and maintain gendered inequities. Entrepreneurial Ecosystems provides research-driven insights around effective organizational practices and policies aimed at remedying gendered and intersectional inequalities associated with entrepreneurship activities and economic growth. Proposing a typology of four ecosystem identities, it highlights how some might be more amenable and organized towards gender inclusion and change, while others may be much more difficult to change, reorganize and restructure. It offers scholars, students, practitioners and policymakers insights about gender in relation to analyzing entrepreneurial ecosystems and for fostering inclusive economic development policies.