bluuebunny/crossref_metadata_2025_split huggingface dataset:
DILLo: an Italian lexical database for speech-language pathologists
Authors: Beccaria Federica , Cristiano Angela , Pisciotta Flavio , Usardi Noemi , Borgogni Elisa , Prayer Galletti Filippo , Corsi Giulia , Gregori Lorenzo , Gagliardi Gloria 
Published: March 2024

AbstractA novel lexical resource for treating speech impairments from childhood to senility: DILLo—Database Italiano del Lessico per Logopedisti (i.e., Italian Database for Speech-Language Pathologists) is presented. DILLo is a free online web application that allows extraction of filtered wordlists for flexible rehabilitative purposes. Its major aim is to provide Italian speech-language pathologists (SLPs) with a resource that takes advantage of Information and Communication Technologies for language in a healthcare setting. DILLo’s design adopts an integrated approach that envisages fruitful cooperation between clinical and linguistic professionals. The 7690 Italian words in the database have been selected based on phonological, phonotactic, and morphological properties, and their frequency of use. These linguistic features are encoded in the tool, which includes the orthographic and phonological transcriptions, and the phonotactic structure of each word. Moreover, most of the entries are associated with their respective ARASAAC pictogram, providing an additional and inclusive tool for treating speech impairments. The user-friendly interface is structured to allow for different and adaptable search options. DILLo allows Speech-Language Pathologists (SLPs) to obtain a rich, tailored, and varied selection of suitable linguistic stimuli. It can be used to customize the treatment of many impairments, e.g., Speech Sound Disorders, Childhood Apraxia of Speech, Specific Learning Disabilities, aphasia, dysarthria, dysphonia, and the auditory training that follows cochlear implantations.
A comprehensive environmental exposure indicator and respiratory health in asthmatic children: a case study
Authors: Cilluffo Giovanna , Sottile Gianluca , Ferrante Giuliana , Fasola Salvatore , Malizia Velia , Montalbano Laura , Ranzi Andrea , Badaloni Chiara , Viegi Giovanni , La Grutta Stefania 
Published: March 2024

AbstractThe primary goal of asthma management is to achieve and maintain asthma control, which can be influenced by environmental factors. This longitudinal study aimed to construct a comprehensive environmental indicator to predict asthma control in children with asthma in Palermo, Italy. The study included 179 asthmatic children aged 5–16 years. The Normalized Difference Vegetation Index (NDVI) was used to measure green cover, and the Coordination of Information on the Environment (CORINE) framework was used to assess land use based on each home address. A land use regression (LUR) model centered on the home address estimated NO2 exposure for each child using GIS. An environmental indicator, including environmental and personal exposure, was formulated using an additive value model approach. A logistic regression mixed model assessed the association between the environmental indicator and uncontrolled asthma. A probability map of uncontrolled asthma was constructed. In conclusion, a comprehensive environmental indicator proved effective in identifying areas at higher and lower risk of uncontrolled asthma.
ROBUST: 221 bugs in the Robot Operating System
Authors: Timperley Christopher S. , van der Hoorn Gijs , Santos André , Deshpande Harshavardhan , Wąsowski Andrzej 
Published: March 2024

AbstractAs robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased. To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community.
Sustainability consciousness in primary schools: roles of leaders in the post/digital era
Authors: Uleanya Chinaza 
Published: March 2024

AbstractSustainability consciousness is pivotal to ensuring sustainability in schools. However, the roles of leaders are considered critical towards ensuring sustainability consciousness. Hence, this study explores the roles of school leaders in promoting sustainability consciousness considering scholarly submissions, using the case of South Africa. Systematic review method was adopted. Thus, Google search engine was adopted, and a search was done using identified key terms on SABINET as the selected database. The retrieved literature were sieved using inclusion and exclusion criteria as required by the adopted protocol of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses). From the analysed data, themes were generated. The findings of the study showed that educational changes are not capable of ensuring sustainability consciousness. Meanwhile, factors such as policy, curriculum and collaborative efforts are capable of hindering or promoting sustainability consciousness. Following the submission of scholars in the systematically analysed literature, the roles of leaders are put forward as recommendations towards ensuring sustainability consciousness in their various schools.
Evaluation of the performance of a CdZnTe-based soft $$\gamma $$-ray detector for CubeSat payloads
Authors: de Kuijper Kees , Diwan Rishank , Pal Partha Sarathi , Ritter Andreas , Parkinson Pablo M. Saz , Kong Andy C. T. , Parker Quentin A. 
Published: March 2024

AbstractThe low-energy $$\varvec{\gamma }$$

γ

-ray (0.1-30 MeV) sky has been relatively unexplored since the decommissioning of the COMPTEL instrument on the Compton Gamma-Ray Observatory (CGRO) satellite in 2000. However, the study of this part of the energy spectrum (the “MeV gap”) is crucial for addressing numerous unresolved questions in high-energy and multi-messenger astrophysics. Although several large MeV $$\varvec{\gamma }$$

γ

-ray missions like AMEGO and e-ASTROGAM are being proposed, they are predominantly in the developmental phase, with launches not anticipated until the next decade at the earliest. In recent times, there has been a surge in proposed CubeSat missions as cost-effective and rapidly implementable “pathfinder” alternatives. A MeV CubeSat dedicated to $$\varvec{\gamma }$$

γ

-ray astronomy has the potential to serve as a demonstrator for future, larger-scale MeV payloads. This paper presents a $$\varvec{\gamma }$$

γ

-ray payload design featuring a CdZnTe crystal calorimeter module developed by IDEAS. We report the detailed results of simulations to assess the performance of this proposed payload and compare it with those of previous $$\varvec{\gamma }$$

γ

-ray instruments.
Yet Another Lock-Free Atom Table Design for Scalable Symbol Management in Prolog
Authors: Moreno Pedro , Areias Miguel , Rocha Ricardo , Santos Costa Vítor 
Published: March 2024

AbstractProlog systems rely on an atom table for symbol management, which is usually implemented as a dynamically resizeable hash table. This is ideal for single threaded execution, but can become a bottleneck in a multi-threaded scenario. In this work, we replace the original atom table implementation in the YAP Prolog system with a lock-free hash-based data structure, named Lock-free Hash Tries (LFHT), in order to provide efficient and scalable symbol management. Being lock-free, the new implementation also provides better guarantees, namely, immunity to priority inversion, to deadlocks and to livelocks. Performance results show that the new lock-free LFHT implementation has better results in single threaded execution and much better scalability than the original lock based dynamically resizing hash table.
Health, Wellbeing and Empowerment E-workshops for Mothers of Children with Disabilities: A Non-randomised Comparison Study
Authors: Bourke-Taylor Helen M. , Leo Monica , Tirlea Loredana 
Published: March 2024

AbstractMothers of children with disabilities can experience compromised health. Targeted interventions require investigation to determine effectiveness. Healthy Mothers Healthy Families (HMHF) is a health, wellbeing and empowerment program that addresses mothers need to protect, and or, recover their own health due to caregiving impacts. This study compared the effectiveness of HMHF e-workshops online compared to no intervention. The HMHF e-workshops were delivered to 290 mothers across the 2020–2022 Covid-19 pandemic and 172 participated in research. The HMHF e-workshops included 3 online 2- hour workshops facilitated by credentialled peer-facilitators, closed online group chat, e-workbook and online learning package. Participants in both groups completed surveys pre and post the workshops (or control) over 8–10 weeks. Mothers who participated in HMHF significantly increased health help seeking behaviours (p < .001), and improved mental health and health behaviors over time: health behavior (p < .001), positive wellbeing (p < .004) and depression (p < .001) and stress symptoms (p = .005). Compared to controls, HMHF e-workshop participants significantly improved health behaviours (p < .001) and self-reported symptoms of depression (p = .002) and stress (p = .005) over 8–10 weeks. E-workshops were accessible and effective for mothers of children with high care needs and family responsibilities across the COVID-19 pandemic. Compared to no intervention, the HMHF intervention was more effective for improving healthy behaviours and mental health.
Non-equilibrium Dynamics of Vortices in Two-Dimensional Quantum Gases: Determining the Dynamical Scaling Region Using the Mahalanobis Distance
Authors: Tattersall Richard J. , Baggaley Andrew W. , Billam Thomas P. 
Published: March 2024

AbstractWhen a system undergoes a rapid quench from a disordered to an ordered phase, it does not order instantly but instead relaxes towards equilibrium over time. During this relaxation, the dynamical scaling hypothesis predicts that the length scale of ordered regions increases, with later patterns statistically similar to earlier ones except for a change in global scale. Quantum gases are one of many systems in which such out of equilibrium behaviour is predicted to occur. Here, we present a method for systematically testing when dynamical scaling is taking place, by quantifying the similarity of the rescaled two-point correlation function over time using the Mahalanobis distance. Data on the velocity field of a two-dimensional quantum fluid, generated from point vortex simulations, are used to illustrate the application of this method.
Maximum a posteriori Bayesian methods out-perform non-compartmental analysis for busulfan precision dosing
Authors: Hughes Jasmine H. , Long-Boyle Janel , Keizer Ron J. 
Published: March 2024

AbstractDose personalization improves patient outcomes for many drugs with a narrow therapeutic index and high inter-individuality variability, including busulfan. Non-compartmental analysis (NCA) and model-based methods like maximum a posteriori Bayesian (MAP) approaches are two methods routinely used for dose optimization. These approaches vary in how they estimate patient-specific pharmacokinetic parameters to inform a dose and the impact of these differences is not well-understood. Using busulfan as an example application and area under the concentration–time curve (AUC) as a target exposure metric, these estimation methods were compared using retrospective patient data (N = 246) and simulated precision dosing treatment courses. NCA was performed with or without peak extension, and MAP Bayesian estimation was performed using either the one-compartment Shukla model or the two-compartment McCune model. All methods showed good agreement on real-world data (correlation coefficients of 0.945–0.998) as assessed by Bland–Altman plots, although agreement between NCA and MAP methods was higher during the first dosing interval (0.982–0.994) compared to subsequent dosing intervals (0.918–0.938). In dose adjustment simulations, both NCA and MAP estimated high target attainment (> 98%) although true simulated target attainment was lower for NCA (63–66%) versus MAP (91–93%). The largest differences in AUC estimation were due to different assumptions for the shape of the concentration curve during the infusion phase, followed by how the methods considered time-dependent clearance and concentration–time points collected in earlier intervals. In conclusion, although AUC estimates between the two methods showed good correlation, in a simulated study, MAP lead to higher target attainment. When changing from one method to another, or changing infusion duration and other factors, optimum estimated exposure targets may require adjusting to maintain a consistent exposure.
Neural Data Augmentation for Legal Overruling Task: Small Deep Learning Models vs. Large Language Models
Authors: Sheik Reshma , Siva Sundara K. P. , Nirmala S. Jaya 
Published: March 2024

AbstractDeep learning models produce impressive results in any natural language processing applications when given a better learning strategy and trained with large labeled datasets. However, the annotation of massive training data is far too expensive, especially in the legal domain, due to the need for trained legal professionals. Data augmentation solves the problem of learning without labeled big data. In this paper, we employ pre-trained language models and prompt engineering to generate large-scale pseudo-labeled data for the legal overruling task using 100 data samples. We train small recurrent and convolutional deep-learning models using this data and fine-tune a few other transformer models. We then evaluate the effectiveness of the models, both with and without data augmentation, using the benchmark dataset and analyze the results. We also test the performance of these models with the state-of-the-art GPT-3 model under few-shot setting. Our experimental findings demonstrate that data augmentation results in better model performance in the legal overruling task than models trained without augmentation. Furthermore, our best-performing deep learning model trained on augmented data outperforms the few-shot GPT-3 by 18% in the F1-score. Additionally, our results highlight that the small neural networks trained with augmented data achieve outcomes comparable to those of other large language models.
Sensitivity to morphological spelling regularities in Chinese-English bilinguals and English monolinguals
Authors: Iwao Haruka Sophia , Andrews Sally , Veldre Aaron 
Published: March 2024

AbstractEvidence of sensitivity to graphotactic and morphological patterns in English spelling has been extensively examined in monolinguals. Comparatively few studies have examined bilinguals’ sensitivity to spelling regularities. The present study compared late Chinese-English bilinguals and English monolinguals on their sensitivity to systematic inflectional and derivational spelling regularities. One hundred and twenty-nine undergraduate students completed a forced-choice spelling task, in which nonword pairs were presented in a sentence context requiring a choice of the relevant grammatical form. English ability measures were administered to examine possible inter-individual differences in morphological sensitivity. The results showed that both monolingual and bilingual participants demonstrated knowledge of spelling patterns, but the groups differed in their sensitivity to inflectional and derivational spelling regularities. Specifically, bilinguals showed more consistent use of morphological spelling regularities in guiding their decision on spelling choice compared to monolinguals. The results are argued to be consistent with the predictions of statistical learning accounts of spelling acquisition.
Is Generation Z more Inclined than Generation Y to Purchase Sustainable Clothing?
Authors: Masserini Lucio , Bini Matilde , Difonzo Marica 
Published: March 2024

AbstractIncreasing clothing (over)consumption, supported by the fast fashion industry, has caused a significant reduction in clothing costs, raised major sustainability challenges, and highlighted the need for engaging in more sustainable consumption behaviour to mitigate the negative environmental, social, and economic consequences. Although green purchase behaviour is now well understood, extant literature still lacks a comprehensive approach to explain consumers behaviour (especially that of the younger generations) with respect to sustainable clothing. Using survey data collected through a structured questionnaire, this study aims to assess whether Generation Z is more inclined to buy sustainable or eco-friendly clothing than Generation Y. Given the non-random selection of respondents, analysis was conducted using propensity score matching to correct for potential bias based on a set of observable confounders. The results show that Generation Z is more likely to buy second-hand clothing, whereas Generation Y is more interested in clothes made of organic and eco-sustainable fabrics.
Staggered deployment of gunshot detection technology in Chicago, IL: a matched quasi-experiment of gun violence outcomes
Authors: Connealy Nathan T. , Piza Eric L. , Arietti Rachael A. , Mohler George O. , Carter Jeremy G. 
Published: March 2024

AbstractObjectivesWe examine the potential effects of gunshot detection technology longitudinally in Chicago through a synthetic control quasi-experiment.MethodsPolice districts receiving gunshot detection technology were compared to a synthetic control unit via a staggered difference-in-difference design. Across eleven unique gunshot detection technology deployment phases, the analyses produce results for aggregate, initial versus expanded, and phase-specific deployment effects across five gun violence outcome measures.ResultsGunshot detection technology had no effect on fatal shootings, non-fatal shootings, general part I gun crimes, or shots fired calls for service. Gun recoveries significantly increased in the aggregate, initial, and expanded models, and in several individual phases relative to controls.ConclusionsThe results align with prior literature that has found a procedural benefit, but not a crime prevention benefit, of gunshot detection technology. Law enforcement agencies seeking crime prevention or reduction solutions may be better served by investing in other options.
Development of sustainable hydromorphic Technosols within artificial wetlands in mining landscapes: the effects of wastewater and hydrothermal geological materials
Authors: Díaz-Ortega J. , Rivera-Uria Y. , López-Mendoza E. , Sedov S. , Romero F. , Solleiro-Rebolledo E. , Martínez-Jardines L. G. 
Published: March 2024

Abstract
Purpose
The Buenavista del Cobre mine is in a semiarid environment in NW Mexico. A part of the mine tailings dam has been flooded with wastewater from Cananea, generating an artificial wetland. The main objectives of this work were to evaluate the effect of wastewater on the pedogenesis of wetland Technosols developed on mine tailings and to compare them with the soil of non-irrigated tailings and with a natural soil profile.

Materials and methods
Three profiles were studied inside the dam as follows: a profile under waterlogging conditions, a profile under conditions of periodic sewage saturation, and a profile with no waterlogging conditions. Laboratory methods included the micromorphological analysis of the soil structure and pedo-features, fertility properties, identification of clay minerals, and analysis of bulk chemical composition.

Results and discussion
It was found that the biogenic structure and voids associated with organic materials were the main micromorphological features of the studied wetland Technosols. Primary sulfides remained unaltered in the Technosols irrigated with wastewater, whereas incipient sulfide oxidation was observed in the non-irrigated tailings. Chlorite and smectite were detected in the Technosols. Such mineral assemblage was found to be mostly generated by hydrothermal processes.

Conclusion
Irrigation of tailings with wastewater supported the biological aggregation and porosity formation within the soil matrix, supplied plant nutrients, and enhanced the ecological soil quality of the studied hydromorphic Technosols. Saturation with wastewater hampered the oxidation of primary sulfides in the hydromorphic Technosols, preventing soil acidification and the mobilization of heavy metal contaminants.
Abundance, distribution, and ecological/environmental risks of critical rare earth elements (REE) in phosphate ore, soil, tailings, and sediments: application of spectroscopic fingerprinting
Authors: Khelifi Faten , Batool Sadia , Kechiched Rabah , Padoan Elio , Ncibi Kaouther , Hamed Younes 
Published: March 2024

Abstract
Purposes
This research focuses on the characterization of phosphate ore, its solid effluents, and nearby contaminated soils in the southwest Tunisia (Gafsa-Metlaoui Basin). It aims also at evaluating the vertical distribution and abundance of critical rare earth elements (REE) in the different materials and their ecological and environmental risks.

Materials and methods
The sampled materials went through physical, chemical, and mineralogical characterization which involved XRF, XPS, XRD, and ICP-MS analyses. The REE anomalies and the environmental and ecological indices were calculated.

Results and discussions
Results show relatively high concentrations of nine rare REEs, following the sequence La > Ce > Nd > Y > Gd > Eu > Sm > Yb > Tb and trace metal elements (TME) such as Cd, Cr, Mn, Zn, Co, Fe, Sr, Cu, Ni, Pb, Ba that surpass, in some cases, international standards. The vertical distribution of the studied elements within a sediment, tailings, and soil profiles (beyond 20 cm of depth) indicates their likely in-depth migration. TME- and REE-bearing phosphate samples reflect mostly oxic conditions in the southern area with high positive Eu anomalies signifying possible mixing of sources. The environmental assessment indicate no contamination and a moderate enrichment of REEs, except for Eu, which displays significant contamination and extreme enrichment. Whereas, a deficiency of Y has been detected in most of the studied samples except for sludge sample which was also found significantly enriched with REE.

Conclusions
There are fundamental similarities between the different studied samples with high carbonate mineral concentrations. Statistical analysis confirmed the spectroscopic fingerprints demonstrating that the different materials share a similar composition. All of these similarities are most likely linked to the impact of mining activities on sediments and soils. Overall, our findings highlight the global effect of ore processing in determining the geochemical and the mineralogical characteristics of the surrounding environments of mines.