bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Gap between Rhetoric and Reality in Community Wellbeing Research: Deliberative Method and the Lens of ‘Pragmatic Complexity’
Authors: Passey Andrew , South Jane , Southby Kris , Gamsu Mark , Bagnall Anne-Marie , Pennington Andy , Corcoran Rhiannon 
Published: May 2024

AbstractGrowing policymaker interest in community wellbeing puts a premium on knowledge about existing community-level challenges and possible policy responses. If evidence-based policy and practice is foregrounded in these developments, there is a risk that lived experience is seen to lack validity in policy-making decisions and that knowledge from and about underrepresented groups is underemphasised. In consequence, the best available evidence on which to make policy decisions affecting these groups might be missed, thus potentially increasing health inequalities. This paper extends debate on this dilemma in this journal by using the lens of ‘pragmatic complexity’ as an alternative view on what works as evidence for policy and practice in community wellbeing. We present an empirical analysis of two expert hearings about community wellbeing. The events used a deliberative approach, allowing participants to probe evidence and consider from multiple perspectives ideas of how to address identified issues. Two overarching themes from the hearings - a perceived gap between the rhetoric and reality of wellbeing evidence, and proposals on ‘what works’ in the (co)-production of knowledge about wellbeing – are articulated and explored. We develop specific features emerging from the hearings that have wider resonance for community wellbeing research and suggest potential responses: what counts as ‘good’ or good-enough evidence about community wellbeing; system responses requiring thinking and engaging with complexity; reflections on the collective and collaborative process of an expert hearing approach. The combination of analysis of knowledge generated deliberatively through an expert hearing approach and a pragmatic complexity lens, delimits our contribution.
Evaluation of fault-sealing: a case study on Xiangguosi underground gas storage, SW China
Authors: Mu Ruoyu , Luo Yu , Zhao Zihan , Zhou Yuan , Zhao Yuchao , Wang Mengyu , Li Limin 
Published: May 2024

AbstractChina vigorously implements the dual carbon strategy, and natural gas consumption continues to grow rapidly. It is urgent to improve the natural gas “production, supply, storage, and sales” system and accelerate the construction of underground gas storage (UGS). UGS requires “storage, injection, and extraction”. Faults are the primary factor of “storage”, the evaluation of fault-sealing is crucial for the safe construction and operation of UGS. Existing researches start from the perspective of the hydrocarbon reservoir, develop an evaluation of the basic characteristics of faults, lithological configuration of the fault’s two blocks, analysis of production performance, Shale Smear Factor (SSF), Shale Gouge Ratio (SGR), properties of fault-filling materials, 3D tectonic model, normal pressure on the fault plane, fault shear index, and fault plugging coefficient. This paper systematically analyzes the adaptability of existing methods and proposes an index to evaluate the fault-sealing capability of UGS. Taking the first UGS in SW China—Xiangguosi UGS as a case, using this workflow to evaluate the fault-sealing capability of 5 major faults. It is believed that the evaluation of fault-sealing on Xiangguosi UGS is good. This conclusion supports the design of construction key indicators and is the important basis point of the construction of the “signpost” UGS. It is of guiding significance and provides a reference for the evaluation of fault-sealing for the rebuilding of depleted gas reservoirs to UGSs.
Machine Learning Assisted Exploration for Affine Deligne–Lusztig Varieties
Authors: Dong Bin , He Xuhua , Jin Pengfei , Schremmer Felix , Yu Qingchao 
Published: May 2024

AbstractThis paper presents a novel, interdisciplinary study that leverages a Machine Learning (ML) assisted framework to explore the geometry of affine Deligne–Lusztig varieties (ADLV). The primary objective is to investigate the non-emptiness pattern, dimension, and enumeration of irreducible components of ADLV. Our proposed framework demonstrates a recursive pipeline of data generation, model training, pattern analysis, and human examination, presenting an intricate interplay between ML and pure mathematical research. Notably, our data-generation process is nuanced, emphasizing the selection of meaningful subsets and appropriate feature sets. We demonstrate that this framework has a potential to accelerate pure mathematical research, leading to the discovery of new conjectures and promising research directions that could otherwise take significant time to uncover. We rediscover the virtual dimension formula and provide a full mathematical proof of a newly identified problem concerning a certain lower bound of dimension. Furthermore, we extend an open invitation to the readers by providing the source code for computing ADLV and the ML models, promoting further explorations. This paper concludes by sharing valuable experiences and highlighting lessons learned from this collaboration.
Experimental investigation of the heat transfer characteristics, operating limits, and temperature distribution of a prototypically 3 m long two-phase closed thermosyphon for spent fuel pool passive cooling
Authors: Castro Sergio Iván Cáceres , Kirsch Marc , Kulenovic Rudi , Starflinger Jörg 
Published: May 2024

AbstractThe current study investigated the heat transfer performance, operation limits, and temperature distribution of a 3 m prototype model for a large-scale straight two-phase closed thermosyphon with deionized water designed for passive cooling of nuclear spent fuel pools with a filling ratio ranging from 20% to 100% and a heat source temperature ranging from 45 to 80 °C. After the accident at the Fukushima Daiichi nuclear power plant, the need for a reliable cooling system for these pools increased, with thermosyphons emerging as a promising solution for passive cooling. The experimental procedure implemented in this study yielded a comprehensive understanding of the operation and phenomena inside a thermosyphon, providing crucial data for the validation and enhancement of numerical models that simulate relevant phenomena within nuclear power plants, including passive residual heat removal with thermosyphons. The results indicated that the optimal heat transfer performance was achieved at a filling ratio of 30%, where the thermosyphon begins operation at a heat source temperature of 45 °C. Additionally, the temperature distribution along the thermosyphon confirmed the operation limits, including partial dryout at a 20% filling ratio and geyser boiling and flooding (entrainment) limits at 75% and 100% filling ratios, respectively.
The impact of the COVID 19 pandemic on stock market volatility: evidence from a selection of developed and emerging stock markets
Authors: Khan Muhammad Niaz , Fifield Suzanne G. M. , Power David M. 
Published: May 2024

AbstractThis study examines the impact of the COVID 19 pandemic on the stock markets of China, India, Pakistan, the UK and the US using Generalised Autoregressive Conditional Heteroscedasticity (GARCH) and Threshold GARCH models with COVID 19 as an exogenous dummy variable in the variance equation. The sample period of 2016–2021 is divided into two sub-periods: the pre-COVID 19 period and the COVID 19 period. The results of the study indicate that there was persistent volatility in these markets and that this volatility increased as a result of the pandemic. In addition, the Threshold GARCH results indicate that the asymmetric term was significant in all markets indicating that bad news, such as the pandemic, had a stronger impact on the conditional variance of the returns as compared to good news. In addition, the results further confirm that the US market had no significant impact on the volatility of the Chinese market during the pandemic. The results have important implications for (1) international investors regarding portfolio management and investment risk minimisation in situations like the COVID 19 pandemic; and (2) policy-makers in terms of how they respond to any future pandemic.
Investigation of clinicopathological characteristics and prognosis of abdominal Desmoid tumors
Authors: Jiang Yujuan , Shao Xinxin , Li Weikun , Hu Haitao , Lu Yiming , Tian Yantao 
Published: May 2024

Abstract
Background
Abdominal desmoid tumors (DTs) are rare soft-tissue neoplasms known for their relatively high local recurrence rate. This study aims to elucidate the clinicopathological features and investigate prognostic factors related to abdominal DTs across various tumor locations.

Methods
From January 2000 to January 2021, patients diagnosed with abdominal DTs who underwent complete resection at the Cancer Hospital, Chinese Academy of Medical Sciences, were included in this study. Thorough collection and review of clinicopathologic characteristics and follow-up data were performed. Prognostic factors, including age at presentation, sex, tumor location, size, and proximity to nerves or vasculature, were meticulously analyzed to assess their impact on recurrence-free survival.

Results
A cohort of 226 patients diagnosed with abdominal DTs was categorized into two groups based on tumor site: the abdominal wall group (n = 132) and the intra-abdominal cavity group (n = 94). Distinct clinicopathological features and prognoses were observed between abdominal wall DTs and intra-abdominal DTs. During a median follow-up of 60 months, 24 patients (10.2%) experienced local recurrence. Univariate and multivariate analyses identified intra-abdominal tumors, tumor size >10cm, and positive margins as independent risk factors associated with poor prognosis.

Conclusion
Abdominal wall DTs demonstrate different clinicopathological characteristics and better prognoses compared to intra-abdominal DTs. By achieving negative margins, patients with abdominal wall DTs can achieve favorable therapeutic outcomes and prognosis through curative resection.
SQEAIR: an Improved Infectious Disease Dynamics Model
Authors: Wang Chenxi , Jin Yongchao , Zhou Lihui , Hou Wei , Liu Dongmei , Wang Jianjun , Wang Xiyin 
Published: May 2024

Abstract
The Covid-19 pandemic poses a significant threat to human health and life. Timely and accurate prediction of the epidemic’s trajectory is crucial for devising effective prevention and control strategies. Traditional infectious disease models may not capture the complexity of modern epidemics, especially when governments implement diverse policies. Drawing from China’s epidemic prevention strategies and Covid-19 transmission characteristics, this study introduces two distinct categories quarantined cases and asymptomatic cases to enhance the traditional SEIR model in depicting disease dynamics. To address the intricate nature of prevention and control efforts, the quarantined cases are further segmented into three subgroups: exposed quarantined, asymptomatic quarantined, and infected quarantined cases. Consequently, a novel SQEAIR model is proposed to model the dynamics of Covid-19. Evaluation metrics such as the Akaike information criterion (AIC) and Absolute Percentage Error (MAE) are employed to assess the efficacy and accuracy of both the newly proposed and traditional models. By fitting the models to the number of infected cases in Shanghai (March to May 2022) and Guangzhou (November 2022), it was observed that the SQEAIR model exhibited a lower AIC value compared to the SEIR model, indicating superior fitting accuracy for Covid-19 infections. Moreover, the high accuracy of the SQEAIR model enabled precise predictions of confirmed cases in Guangzhou. Leveraging the SQEAIR model, various parameters were tested to simulate the impact of different influencing factors, enabling the evaluation of defense strategies. These findings underscore the effectiveness of key epidemic control measures, such as quarantining exposed cases, in enhancing public health and promoting awareness of personal protection.
Acquisition of key clinical communication skills through simulation-based education: findings from a program for postgraduate psychiatry trainees (ComPsych)
Authors: Ditton-Phare Philippa , Sandhu Harsimrat , Kelly Brian , Loughland Carmel 
Published: May 2024

Abstract
Objective
Few studies have investigated the maintenance of skills acquired in classroom-based clinician education. Using an advanced simulation-based clinical communication skill training program for postgraduate psychiatry education (ComPsych), we aimed to investigate skill acquisition through assessing changes in competence (abilities) and performance (practice).

Methods
Forty trainee psychiatrists (15 males; age range 26–48) participated. Video-recorded Standardized Patient Assessments (SPAs) were delivered twice pre- and post-training to assess learning. Skills were coded by independent psychologists using the Core Communication Skills (CCS) coding system. Simulated patients (SPs) rated trainees' communication performance using the Sim-Patient SPA checklist. Paired t-tests, linear mixed models and logistic mixed models assessed changes in communication skills over time.

Results
For SPAs, reliability of coder ratings was deemed acceptable (ICC range 0.67 to 0.87). Mean post-training communication performance significantly increased for skills in agenda setting (p < 0.001), information organization (p < 0.001), empathic skills (p = 0.046), and overall skills performance (p = 0.001). Significant decreases for questioning skills were indicative of reduced reliance on these skills post-training. SPs rated all skillsets higher post-training. A modest relationship was detected between frequency (coded) and (SP-rated) quality of communication skills. Improvements in agenda setting and information organisation skills were retained ~ 6 weeks post-training.

Conclusions
Training improved patient-centered communication skills in psychiatry trainees, particularly skills in agenda setting and information organization, with skills retained ~ 6 weeks post-training. There was reduced reliance on questioning skills, which are well utilised generally. The study supports the benefits of this method of communication skills training into postgraduate psychiatry education.
Development of prediction model for structural behavior and gradation of porous asphalt pavement
Authors: Lokesh Yateen , Parate Harshad R. , Swamy H. M. Rajashekhar , Ali Humaira 
Published: May 2024

AbstractThis study is aimed at developing prediction model for structural behavior of Porous Asphalt Pavement (PAP) using ABAQUS software and also developing ANN (Artificial Neural Network) model to predict void percentages in Porous Asphalt mix gradations. Data from the past literatures were used to analyze various mixing parameters affecting the properties of Porous Asphalt gradation mixes. The study analyzed PAPs using KENPAVE software. The findings indicated that fewer allowable repetitions to fatigue and rutting failures were observed for thinner Porous Asphalt Concrete (PAC) layer thicknesses. This suggests that thicker PAC layers may offer better resistance to fatigue and rutting failures in pavement systems. The study found that the nature of subgrade material significantly influenced the rutting performance of PAP systems. Specifically, clayey soils exhibited a 77.74% reduction in the design life of the pavement compared to gravelly soil subgrades. This highlights the importance of considering subgrade characteristics in pavement design and construction to optimize pavement performance and longevity. Higher contact pressures resulted in higher tensile stresses at the bottom of PAC layer which in turn reduced the fatigue life of PAP. The findings from ABAQUS analysis indicated that an increase in the void percentage in Porous Asphalt Concrete (PAC) mixes led to a significant increase in horizontal tensile strain at the bottom of the PAC layer, with a 12.3% increase observed. Additionally, there was a noticeable increase in tensile strain for a PAC mix with 28% voids compared to a mix with 16% voids. This suggests that higher void percentages in the PAC mixes can potentially enhance the flexibility and deformation resistance of the pavement structure, which may contribute to improved performance under various loading conditions, hence leading to 92.8% reduction in allowable load repetitions to fatigue failure.The study further revealed that an increased void percentage in Porous Asphalt Concrete (PAC) mixes resulted in a decrease in vertical stress and deflection in the PAP system. However, no significant effect on the allowable repetitions to rutting failure was observed. This suggests that higher void percentages may lead to better load distribution and reduced vertical stresses within the pavement structure, contributing to improved performance in terms of stress and deflection.Moreover, Asphalt Pavement mixes were compiled to develop an Artificial Neural Network (ANN) prediction model. The results demonstrated good conformity between predicted and actual data, with a mean square error of 0.109 and a coefficient of correlation of 0.994. This indicates that the ANN model accurately predicts pavement performance based on the compiled asphalt pavement mixes, providing a valuable tool for pavement design and analysis.
Calculating premium principles from the mode of a unimodal weighted distribution
Authors: Psarrakos Georgios 
Published: May 2024

AbstractThe theory of utility is a well-known method of constructing insurance premiums (see e.g., Newton et al. (1986) Actuarial Mathematics. Itasca, Illinois: The Society of Actuaries.). Furman and Zitikis ((2008) Insurance: Mathematics and Economics, 42, 459–465.) proposed an alternative method using the mean value of a weighted random variable. According to this approach, for various choices of weighting, popular premiums such as net premium, modified variance premium, Esscher premium, and Kamps premium are obtained. On the other hand, some premiums cannot be obtained with this method, such as the premium of the exponential principle. In this paper, we provide a complementary theory by introducing a family of unimodal weighted distributions for which the mode is a premium principle.
How to co-create content moderation policies: the case of the AutSPACEs project
Authors: Aitkenhead Georgia , Fantoni Susanna , Scott James , Batchelor Sophia , Duncan Helen , Llewellyn-Jones David , Mole Callum , Smith Otis , Stoffel Martin , Taylor Robin , Whitaker Kirstie , Greshake Tzovaras Bastian 
Published: May 2024

Abstract
The moderation of user-generated content on online platforms remains a key solution to protecting people online, but also remains a perpetual challenge as the appropriateness of content moderation guidelines depends on the online community that they aim to govern. This challenge affects marginalized groups in particular, as they more frequently experience online abuse but also end up falsely being the target of content-moderation guidelines. While there have been calls for democratic, community-moderation, there has so far been little research into how to implement such approaches. Here, we present the co-creation of content moderation strategies with the users of an online platform to address some of these challenges. Within the context of AutSPACEs—an online citizen science platform that aims to allow autistic people to share their own sensory processing experiences publicly—we used a community-based and participatory approach to co-design a content moderation solution that would fit the preferences, priorities, and needs of its autistic user community. We outline how this approach helped us discover context-specific moderation dilemmas around participant safety and well-being and how we addressed those. These trade-offs have resulted in a moderation design that differs from more general social networks in aspects such as how to contribute, when to moderate, and what to moderate. While these dilemmas, processes, and solutions are specific to the context of AutSPACEs, we highlight how the co-design approach itself could be applied and useful for other communities to uncover challenges and help other online spaces to embed safety and empowerment.
Characterization of N+ Abundances in the Terrestrial Polar Wind Using the Multiscale Atmosphere‐Geospace Environment
Authors: Albarran R. M. , Varney R. H. , Pham K. , Lin D. 
Published: May 2024

AbstractThe High‐latitude Ionosphere Dynamics for Research Applications (HIDRA) model is part of the Multiscale Atmosphere‐Geospace Environment model under development by the Center for Geospace Storms NASA DRIVE Science Center. This study employs HIDRA to simulate upflows of H+, He+, O+, and N+ ions, with a particular focus on the relative N+ concentrations, production and loss mechanisms, and thermal upflow drivers as functions of season, solar activity, and magnetospheric convection. The simulation results demonstrate that N+ densities typically exceed He+ densities, N+ densities are typically ∼10% O+ densities, and N+ concentrations at quiet‐time are approximately 50%–100% of N+ concentrations during storm‐time. Furthermore, the N+ and O+ upflow fluxes show similar trends with variations in magnetospheric driving. The inclusion of ion‐neutral chemical reactions involving metastable atoms is shown to have significant effects on N+ production rates. With this metastable chemistry included, the simulated ion density profiles compare favorably with satellite measurements from Atmosphere Explorer C and Orbiting Geophysical Observatory 6.
Interpreting the Seasonality of Atmospheric Methane
Authors: East James D. , Jacob Daniel J. , Balasus Nicholas , Bloom A. Anthony , Bruhwiler Lori , Chen Zichong , Kaplan Jed O. , Mickley Loretta J. , Mooring Todd A. , Penn Elise , Poulter Benjamin , Sulprizio Melissa P. , Worden John R. , Yantosca Robert M. , Zhang Zhen 
Published: May 2024

AbstractSurface and satellite observations of atmospheric methane show smooth seasonal behavior in the Southern Hemisphere driven by loss from the hydroxyl (OH) radical. However, observations in the Northern Hemisphere show a sharp mid‐summer increase that is asymmetric with the Southern Hemisphere and not captured by the default configuration of the GEOS‐Chem chemical transport model. Using an ensemble of 22 OH model estimates and 24 wetland emission inventories in GEOS‐Chem, we show that the magnitude, latitudinal distribution, and seasonality of Northern Hemisphere wetland emissions are critical for reproducing the observed seasonality of methane in that hemisphere, with the interhemispheric OH ratio playing a lesser role. Reproducing the observed seasonality requires a wetland emission inventory with ∼80 Tg a−1 poleward of 10°N including significant emissions in South Asia, and an August peak in boreal emissions persisting into autumn. In our 24‐member wetland emission ensemble, only the LPJ‐wsl MERRA‐2 inventory has these attributes.