bluuebunny/crossref_metadata_2025_split huggingface dataset:
Water‐IQ matters as water conflicts mount
Authors: Bishop Kevin , Creed Irena F. , Friedman Kathryn Bryk 
Published: June 2024

AbstractWater crises fuel conflicts that confound efforts to solve the underlying water crises. Water diplomacy is more effective at defusing such conflicts when the parties involved share at least a common understanding of the water involved. We argue that basic, but still up to date knowledge of where water is and how it moves is so important for finding common ground in water conflicts that this knowledge deserves a name of its own—the Water Intelligence Quotient or Water‐IQ. Science has advanced, and what people learn about the water cycle needs to reflect that. Two keystones of Water‐IQ are awareness of how profoundly people have influenced the water cycle and the atmospheric teleconnections that move water between geographic regions. Given the importance of evidence‐based knowledge of the water cycle when trying to overcome water conflicts and seek a basis for water cooperation, Water‐IQ knowledge needs to be spread widely.This article is categorized under:
Human Water > Water Governance
Water and Life > Conservation, Management, and Awareness
Human Water > Water as Imagined and Represented
Role of epigenetics and alterations in RNA metabolism in leukodystrophies
Authors: Rey Federica , Esposito Letizia , Maghraby Erika , Mauri Alessia , Berardo Clarissa , Bonaventura Eleonora , Tonduti Davide , Carelli Stephana , Cereda Cristina 
Published: June 2024

AbstractLeukodystrophies are a class of rare heterogeneous disorders which affect the white matter of the brain, ultimately leading to a disruption in brain development and a damaging effect on cognitive, motor and social‐communicative development. These disorders present a great clinical heterogeneity, along with a phenotypic overlap and this could be partially due to contributions from environmental stimuli. It is in this context that there is a great need to investigate what other factors may contribute to both disease insurgence and phenotypical heterogeneity, and novel evidence are raising the attention toward the study of epigenetics and transcription mechanisms that can influence the disease phenotype beyond genetics. Modulation in the epigenetics machinery including histone modifications, DNA methylation and non‐coding RNAs dysregulation, could be crucial players in the development of these disorders, and moreover an aberrant RNA maturation process has been linked to leukodystrophies. Here, we provide an overview of these mechanisms hoping to supply a closer step toward the analysis of leukodystrophies not only as genetically determined but also with an added level of complexity where epigenetic dysregulation is of key relevance.This article is categorized under:
Regulatory RNAs/RNAi/Riboswitches > Regulatory RNA
RNA in Disease and Development > RNA in Disease
RNA in Disease and Development > RNA in Development
Conceptual Framework
Authors: Ibričević Aida 
Published: June 2024

AbstractThis chapter begins by defining the main theoretical problem and continues by situating it within existing scholarly literature. The conceptual framework is developed by surveying and synthesizing works from political science, human geography, anthropology, sociology and political psychology. The interdisciplinary literature review provides meaning and substance to concepts relevant to my study; forms interlinking relationships between these concepts and identifies gaps where a theoretical contribution can be made. I begin by setting my study within the larger literature on return migration, by examining the “voluntariness” of voluntary return, the specifics of post-conflict return, reintegration strategies and the sustainability of return. The following section develops a substantive definition of the diaspora concept and the third section of the chapter discusses how emotions have been neglected in the social sciences by a dominance of the rational-choice paradigm, by treating emotions as merely personal reactions and thus leaving them outside of the ‘political’ and by overemphasizing the methodological challenges involved in the study of emotions. Scholarly literature on citizenship is presented in the fourth section of the chapter. Next, emotional/affective/intimate citizenship is discussed as the theoretical nexus between citizenship and emotions by looking at how scholars so far have established this connection, primarily through the concepts of home and belonging, elaborated in the next two sections of the chapter. The final section of the chapter concludes by identifying how resolving the central theoretical problem contributes to the existing literature(s).
On the information content of explainable artificial intelligence for quantitative approaches in finance
Authors: Berger Theo 
Published: June 2024

AbstractWe simulate economic data to apply state-of-the-art machine learning algorithms and analyze the economic precision of competing concepts for model agnostic explainable artificial intelligence (XAI) techniques. Also, we assess empirical data and provide a discussion of the competing approaches in comparison with econometric benchmarks, when the data-generating process is unknown. The simulation assessment provides evidence that the applied XAI techniques provide similar economic information on relevant determinants when the data generating process is linear. We find that the adequate choice of XAI technique is crucial when the data generating process is unknown. In comparison to econometric benchmark models, the application of boosted regression trees in combination with Shapley values combines both a superior fit to the data and innovative interpretable insights into non-linear impact factors. Therefore it describes a promising alternative to the econometric benchmark approach.
Assessing ChatGPT’s Potential in HIV Prevention Communication: A Comprehensive Evaluation of Accuracy, Completeness, and Inclusivity
Authors: De Vito Andrea , Colpani Agnese , Moi Giulia , Babudieri Sergio , Calcagno Andrea , Calvino Valeria , Ceccarelli Manuela , Colpani Gianmaria , d’Ettorre Gabriella , Di Biagio Antonio , Farinella Massimo , Falaguasta Marco , Focà Emanuele , Giupponi Giusi , Habed Adriano José , Isenia Wigbertson Julian , Lo Caputo Sergio , Marchetti Giulia , Modesti Luca , Mussini Cristina , Nunnari Giuseppe , Rusconi Stefano , Russo Daria , Saracino Annalisa , Serra Pier Andrea , Madeddu Giordano 
Published: June 2024

AbstractWith the advancement of artificial intelligence(AI), platforms like ChatGPT have gained traction in different fields, including Medicine. This study aims to evaluate the potential of ChatGPT in addressing questions related to HIV prevention and to assess its accuracy, completeness, and inclusivity. A team consisting of 15 physicians, six members from HIV communities, and three experts in gender and queer studies designed an assessment of ChatGPT. Queries were categorized into five thematic groups: general HIV information, behaviors increasing HIV acquisition risk, HIV and pregnancy, HIV testing, and the prophylaxis use. A team of medical doctors was in charge of developing questions to be submitted to ChatGPT. The other members critically assessed the generated responses regarding level of expertise, accuracy, completeness, and inclusivity. The median accuracy score was 5.5 out of 6, with 88.4% of responses achieving a score ≥ 5. Completeness had a median of 3 out of 3, while the median for inclusivity was 2 out of 3. Some thematic groups, like behaviors associated with HIV transmission and prophylaxis, exhibited higher accuracy, indicating variable performance across different topics. Issues of inclusivity were identified, notably the use of outdated terms and a lack of representation for some communities. ChatGPT demonstrates significant potential in providing accurate information on HIV-related topics. However, while responses were often scientifically accurate, they sometimes lacked the socio-political context and inclusivity essential for effective health communication. This underlines the importance of aligning AI-driven platforms with contemporary health communication strategies and ensuring the balance of accuracy and inclusivity.
Thermal Conductivity of Liquid Cyclohexane, n-Decane, n-Hexadecane, and Squalane at Atmospheric Pressure up to 353 K Determined with a Steady-State Parallel-Plate Instrument
Authors: Berger Bioucas Francisco E. , Rausch Michael H. , Koller Thomas M. , Fröba Andreas P. 
Published: June 2024

AbstractThe present work reports experimental data on the thermal conductivity of the four hydrocarbons cyclohexane, n-decane, n-hexadecane, and squalane in the liquid state at ambient pressure up to temperatures of 353.15 K. Absolute measurements were performed with a steady-state guarded parallel-plate instrument (GPPI) with an average expanded (coverage factor k = 2) measurement uncertainty of 2 %. For the linear alkanes n-decane and n-hexadecane as well as the cyclic compound cyclohexane, the measured thermal conductivities agree with reference correlations in the literature, indicating the reliability of the technique used for the study of fluids with relatively low thermal conductivities and weak absorption of radiation. For the first time, experimental data are determined for the long-branched alkane squalane between (278 and 353) K, which cannot be accurately represented with estimation methods commonly used in the literature. In summary, the present measurement results confirm the existing database for representative linear and cyclic hydrocarbons and provide first experimental thermal conductivities for squalane.
Trust, Risk, Privacy and Security in e-Government Use: Insights from a MASEM Analysis
Authors: Gupta Parul , Hooda Apeksha , Jeyaraj Anand , Seddon Jonathan J.M. , Dwivedi Yogesh K. 
Published: June 2024

AbstractDespite considerable research on the factors influencing the use of e-government, citizens are apprehensive of e-government services due to the concerns primarily related to trust, risk, security and privacy. This study presents a meta-analytic structural equation modeling (MASEM) analysis of the findings reported by 68 prior empirical studies on e-government adoption. Specifically, the model examined the direct effects of trust in government, trust in internet, perceived risk, and perceived privacy and security on e-government trust, and its impact on users’ behavioral intention to use e-government. The findings bear significant theoretical and practical implications.
Enhancing Preschool Teachers' Use of Pyramid Model Practices Through Coaching Intervention
Authors: Rakap Salih , Balikci Serife 
Published: June 2024

AbstractThe social-emotional development of young children has been shown to have a significant impact on their long-term success in life. The Pyramid Model is a widely recognized framework that preschool teachers can use to support socio-emotional development. The present study investigated the effects of a professional development program, including teacher training and coaching, on preschool teachers' utilization of social-emotional teaching practices associated with the Pyramid Model. Three preschool teachers and three children participated in this study, which employed a multiple baseline across behaviors design, implemented across participants. The combined training and coaching intervention had a positive impact on all participating teachers' implementation of social-emotional teaching practices. Moreover, the study established a clear correlation between increased implementation of these practices and a gradual reduction in challenging behaviors displayed by the children. The participating teachers expressed high acceptability and perceived relevance of the professional development intervention and Pyramid Model practices. The study contributes to the existing literature on supporting social-emotional development in early childhood settings and highlights the potential of professional development interventions to enhance teacher practices. Recommendations for future research and implications for practice are discussed.
Sensing of Co2+ and Cu2+ Ions Using Dimethylamino-functionalized Poly(azomethine-1,3,4-oxadiazole)s
Authors: Homocianu Mihaela , Hamciuc Elena , Hamciuc Corneliu 
Published: June 2024

AbstractThe ability of OxT and OxFl azomethines to recognize metal ions in THF solutions was investigated using UV-vis absorption techniques. Various metal ions, including Cd2+, Hg2+, Co2+, Sn2+, Cu2+, Ni2+, Zn2+ and Ag+, were tested. The absorption spectra revealed two distinct π-π* transition bands in the 273–278 nm and 330–346 nm wavelength ranges. Additionally, OxFl displayed an absorption peak at 309 nm, attributed to the fluorene group. Spectral titrations were used to study the fluorescence behavior in the presence of these metal ions. The results showed significant quenching with Co2+ and Cu2+ ions, while other metal ions had minimal effects on the fluorescence intensity. The quenching mechanism was further analyzed using the Stern-Volmer and Lehrer equations, and the binding constants ($${\mathrm{K}}_{\mathrm{b}}^{\mathrm{fl}}$$

K

b

fl

) were calculated using the Benesi-Hildebrand relations. The results confirm that Co2+ has a 1:2 stoichiometry and Cu2+ has a 1:1 stoichiometry, indicating the strong affinity of OxFl and OxT for these ions. The negative values of ΔG (Gibbs free energy) suggest that complex formation occurs spontaneously at room temperature.
A Vacuum Waveguide Filter Bank Spectrometer for Far-Infrared Astrophysics
Authors: Nie Rong , Filippini Jeffrey , Brooks Elyssa , Barry Peter , Connors Jake , Gradziel Marcin , Mercado Dale , Razavimaleki Vesal , Shirokoff Erik , Spencer Locke , Tramm Serena , Trappe Neil , Zemcov Michael 
Published: June 2024

AbstractTraditional technologies for far-infrared (FIR) spectroscopy generally involve bulky dispersive optics. Integrated filter bank spectrometers promise more compact designs, but implementations using superconducting transmission line networks become lossy at terahertz frequencies. We describe a novel on-chip spectrometer architecture designed to extend this range. A filter bank spectrometer is implemented using vacuum waveguide etched into a silicon wafer stack. A single trunk line feeds an array of resonant cavities, each coupled to a kinetic inductance detector fabricated on an adjacent wafer. We discuss the design and fabrication of a prototype implementation, initial test results at ambient temperature, and prospects for future development.
Efficient path integral approach via analytical asymptotic expansion for nonlinear systems under Gaussian white noise
Authors: Di Matteo Alberto , Pirrotta Antonina 
Published: June 2024

AbstractIn this paper an efficient formulation of the Path integral (PI) approach is developed for determining the response probability density functions (PDFs) and first-passage statistics of nonlinear oscillators subject to stationary and time-modulated external Gaussian white noise excitations. Specifically, the evolution of the response PDF is obtained in short time steps, by using a discrete version of the Chapman-Kolmogorov equation and assuming a Gaussian form for the conditional response PDF. Next, the technique involves proceeding to treating the problem via an analytical asymptotic expansion procedure, namely the Laplace’s method of integration. In this manner, the repetitive double integrals involved in the standard implementation of the PI approach are evaluated in a closed form, while the response and first-passage PDFs are obtained by mundane step-by-step application of the derived approximate analytical expression. It is shown that the herein proposed formulation can drastically decrease the associated computational cost by several orders of magnitude, as compared to both the standard PI technique and Monte Carlo solution (MCS) approach. A number of nonlinear oscillators are considered in the numerical examples. Notably, for these systems both response PDFs and first-passage probabilities are presented, whereas comparisons with pertinent MCS data demonstrate the efficiency and accuracy of the technique.
Improving accuracy of code smells detection using machine learning with data balancing techniques
Authors: Khleel Nasraldeen Alnor Adam , Nehéz Károly 
Published: June 2024

AbstractCode smells indicate potential symptoms or problems in software due to inefficient design or incomplete implementation. These problems can affect software quality in the long-term. Code smell detection is fundamental to improving software quality and maintainability, reducing software failure risk, and helping to refactor the code. Previous works have applied several prediction methods for code smell detection. However, many of them show that machine learning (ML) and deep learning (DL) techniques are not always suitable for code smell detection due to the problem of imbalanced data. So, data imbalance is the main challenge for ML and DL techniques in detecting code smells. To overcome these challenges, this study aims to present a method for detecting code smell based on DL algorithms (Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Unit (GRU)) combined with data balancing techniques (random oversampling and Tomek links) to mitigate data imbalance issue. To establish the effectiveness of the proposed models, the experiments were conducted on four code smells datasets (God class, data Class, feature envy, and long method) extracted from 74 open-source systems. We compare and evaluate the performance of the models according to seven different performance measures accuracy, precision, recall, f-measure, Matthew’s correlation coefficient (MCC), the area under a receiver operating characteristic curve (AUC), the area under the precision–recall curve (AUCPR) and mean square error (MSE). After comparing the results obtained by the proposed models on the original and balanced data sets, we found out that the best accuracy of 98% was obtained for the Long method by using both models (Bi-LSTM and GRU) on the original datasets, the best accuracy of 100% was obtained for the long method by using both models (Bi-LSTM and GRU) on the balanced datasets (using random oversampling), and the best accuracy 99% was obtained for the long method by using Bi-LSTM model and 99% was obtained for the data class and Feature envy by using GRU model on the balanced datasets (using Tomek links). The results indicate that the use of data balancing techniques had a positive effect on the predictive accuracy of the models presented. The results show that the proposed models can detect the code smells more accurately and effectively.
Occurrence and Consequences of Matrix Effects in Simultaneous Multi-class LC-MS/MS Determination of Pesticides, Pharmaceuticals and Perfluoroalkylsubstances in Different Types of Groundwater
Authors: Keršňáková Zuzana , Lemak Ivana , Bajtoš Peter , Vabcová Jana , Hrouzková Svetlana 
Published: June 2024

Abstract
Matrix effects are a recent remarkable feature in quantitative LC-MS/MS analysis. In this work, the matrix effects of a multiclass mixture of 46 analytes - pesticides, pharmaceuticals and perfluoroalkylsubstances in different types of natural groundwater were studied. Groundwater samples were spiked with different standards from different chemical groups and determined by direct injection and liquid chromatography coupled to tandem mass spectrometry. Matrix effects were assessed by matrix factors calculated using the slope ratio technique. Groundwater samples were sampled in different boreholes in several places in Slovakia. The relationship with the various detected inorganic parameters was investigated and discussed. Most of the studied analytes showed negative matrix effects. Some analytes showed weak negative or positive matrix effects. The results show that average matrix factors obtained from different sampling sites are not a reliable tool and matrix effects need to be monitored depending on the sampling location. Only weak or no correlation of the matrix factors with the determined inorganic parameters was found. Geochemical composition of boreholes samples was determined and the differences in the macrochemical composition of the samples was evaluated. Model samples of ultrapure water enriched with NaCl, Na2CO3 and NaNO3 at various concentration levels were tested and the matrix effects were not observed. Other content of sample than cations Na+ were responsible for the matrix effects. It was found that the most affected compounds are sulfamethoxazole, sulfadiazine, metamitron, chloridazon and also caffeine. The results show that the detailed study is suitable as a tool for a deeper understanding of matrix effects in different types of groundwater. The proper ground water sample must be selected for reliable results of quantitative analysis.

Graphical Abstract
Silently Navigating Ethical Paradoxes in the Israel-Hamas Conflict: A Short Note
Authors: Bekerman Zvi 
Published: June 2024

AbstractI embark on the writing of this short note not as an expert in ethics or a seasoned war analyst but rather as an involved observer nudged into the spotlight by a colleague’s overestimation of my insight into the Israel–Hamas conflict. I approach this task with scepticism yet hoping to morph it into a form of therapy. My own therapy, a means to break the shackles of silence that have gripped not only myself but, I suspect, many others in Israel.
Examining the elements of culturally relevant pedagogy captured and missed in a measure of high-quality mathematics instruction
Authors: Thomas Casedy Ann , Berry III Robert Q. , Sebastian Rose 
Published: June 2024

AbstractMathematics instruction is not race or culture neutral. For students who have been historically marginalized in mathematics classrooms, high-quality mathematics instruction, instruction that helps students build conceptual understanding, on its own might not be enough to disrupt inequities. These students might also need instruction that is culturally relevant, with teachers who demonstrate cultural competence, build critical consciousness, and support student learning. Our goal in this study was to understand which components of culturally relevant pedagogy (CRP) are captured and which are missed in a typical U.S. framework of high-quality mathematics instruction. To find the overlaps and gaps, we analyzed the mathematics lessons of three elementary teachers through both the lens of CRP and the Mathematics-Scan, a mathematics observation tool. We found the strongest overlap between the two frameworks in the patterns of strengths and weaknesses in the teachers’ lessons. When the teachers were delivering high-quality instruction, they were also often supporting students’ learning or showing cultural competence. When the teachers were delivering lower quality instruction, they were also often missing opportunities to enact CRP. At the same time, key elements of CRP including linguistic support for students, high expectations, critical consciousness, and nuances within cultural competence, were missed by the high-quality instruction framework. High-quality instruction was the foundation for CRP in the teachers’ classrooms, but CRP was more than just high-quality instruction. We conclude with recommendations for increasing the alignment between the frameworks and implications for international educators also grappling with equity in their own frameworks of mathematics instruction.