bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors associated with mental health symptoms among UK autistic children and young people and their parents during the COVID-19 pandemic.
Authors: Palmer Melanie , Chandler Susie , Leno Virginia Carter , Mgaieth Farah , Yorke Isabel , Hollocks Matthew , Pickles Andrew , Slonims Vicky , Scott Stephen , Charman Tony , Simonoff Emily 
Published: August 2022

Abstract
Objective: The current study examined the mental health symptoms of autistic children and young people and their parents during the COVID-19 pandemic in two pre-existing well-characterised cohorts. We explored whether child, family or environmental factors were associated with child and parental mental health symptoms during the pandemic. Method: Participants were parents/carers of autistic children in the ASTAR (N=67, Mage 9 years) and QUEST (N=112, Mage 17 years) cohorts. Early in the UK pandemic, parents completed a brief online survey developed specifically to measure the impacts of the COVID-19 pandemic that asked about child and parental mental health, infection experience, and changes to education arrangements, family life, housing and finances. Results: More engagement and enjoyment in education provision and going outside was associated with better child and parental mental health. Multivariate multiple linear regression models were used to test the associations between child, family and environmental factors and pandemic-time mental health symptoms. Amongst pre-adolescent autistic children, pre-existing ADHD was a key factor associated with more behavioural/ADHD symptoms during the pandemic. Higher pre-existing parental mental health problems was also associated with more parental mental health symptoms during the pandemic. Financial concerns were also a risk factor for worse parental mental health during the pandemic. Conclusions: Knowledge of pre-existing mental health and pandemic-related stressors may help care planning. Encouraging engagement and enjoyment in education and promoting physical exercise are important intervention targets. Ensuring access to ADHD medication and support is important, especially if this is managed jointly across school and home.
Revealing a conservation challenge towards floodplain disconnection: Decreasing turnover and increasing nestedness of mollusc metacommunities
Authors: Zhang Kun , Jiang Xiaoming , Zheng Peng 
Published: August 2022

Abstract
Floodplain disconnection (FDC) has become a profound threat to many large river floodplains. Despite current researches examining the impacts of FDC on aquatic biodiversity, little is known about how FDC affected freshwater molluscs from multifaceted biodiversity perspectives, especially at long-term temporal scales. We selected the 7 lakes in the Yangtze River floodplain to evaluate how river-lake disconnection impacted taxonomic, functional and phylogenetic alpha and beta diversity of molluscan assemblages during past 60 years. Our results showed that five disconnected lakes (DLs) experienced dramatic decline in species richness (decreased by 62.4%) and functional richness (54.6%) but increases in functional evenness (20.0%) and Δ+ (5.5%) after disconnection. Whereas such temporal changes in the two connected lakes (CLs) were much slighter. Somewhat unexpectedly, the overall taxonomic (increased by 7.0%) and phylogenetic (12.2%) dissimilarities only slightly increased through time, due to opposite changes in the turnover (40%-50% decrease) and nestedness-resultant (100%-110% increase) components through time. The functional nestedness experienced more significant increase (162.0%), leading to relatively considerable increase in functional overall dissimilarity (64.0%). Such opposite changes in multifaceted turnover and nestedness distinctly modified the structure of beta diversity and highlight the conservation priority of CLs keeping relative high levels of biodiversity. The overall correlations between changes in both alpha and beta diversity among different facets were generally weak, indicating the different diversity facets would provide complementary information for biodiversity conservation and restoration. Thus, we recommended incorporating functional and phylogenetic information of species into traditional taxonomy-based approaches in large river floodplains studies.
Ideological homophily and polarization in political Twitter during the 2017 Norwegian election
Authors: Enjolras Bernard , Salway Andrew 
Published: August 2022

Abstract

Ideological homophily on social media has received increased scholarly interest as it is associated to the formation of filter-bubbles, echo-chambers and increased ideological polarization. Yet, there is no necessary linkage between ideological homophily, echo chambers, and polarization. In spite of political interactions on social media taking place to a large extent between like-minded individuals, cross-cutting interactions are also frequent. Using Twitter data, we investigate the extent to which ideological homophily, echo-chambers and polarization occur together and characterize the network of political Twitter users during the 2017 election in Norway. We do not find that, in spite of the presence of some degree of ideological homophily, evidence of echo-chambers in the Norwegian political Twittersphere during the 2017 election. Yet, the retweets network is characterized by a significant degree of polarization across ideological blocs. Our findings support the thesis according to which polarization on social media may have other drivers than the technological deterministic effect of social media affordances enhancing the formation of online echo-chambers.
Plasma S-Klotho level affects the risk of hyperuricemia in the middle-aged and elderly people
Authors: Xie Haitao , Li Ning , Zhou Guowei , Liu Qian , Wang Haiyan , Xu Xiaoqing , He Zhiyuan , Han Jie , Shen Le , Yu Peng , Chen Jiandong , Chen Xiaohu 
Published: August 2022

Abstract
Background:Soluble Klotho (S-Klotho) is an anti-aging protein mainly secreted by the kidneys. Hyperuricemia is prevalent among middle-aged and elderly individuals, which affects the development of various chronic diseases. However, there are relatively few studies investigating the association between plasma S-Klotho levels and hyperuricemia in middle-aged and elderly individuals. This study sought to clarify the relationship between S-Klotho and the risk of hyperuricemia in middle-aged and elderly people.Methods:During 2007-2016, a total of 50,588 people participated in the National Health and Nutrition Examination Survey. Finally, 12,498 middle-aged and elderly people (aged 40-79) completed the soluble Klotho tests and had obtained complete data. S-Klotho was detected by ELISA kit, and the relationship between S-Klotho and hyperuricemia was assessd by multiple logistic regression. Hyperuricemia is defined as serum uric acid levels higher than or equal to 420 mmol/L in men and 360 mmol/L in women.Results:In the middle-aged and elderly, plasma S-Klotho levels were negatively correlated with hyperuricemia, and there was a saturation effect. The inflection point of S-Klotho was 850.9 pg/ml (logarithmic likelihood ratio test <0.001). When plasma S-Klotho <850.9 pg/ml, the prevalence of hyperuricemia in middle-aged and elderly individuals with higher levels of S-Klotho decreased by 27.1% compared with those with low levels of S-Klotho[Q4 vs Q1, OR: 0.729, 95%CI: (0.615, 0.863), P < 0.001]; In different age groups, S-Klotho had a significantly greater effect on hyperuricemia in middle-aged people[Age: 40-65years, Q4 vs Q1, OR(95%CI): 0.64, (0.55, 0.76), P <0.001; Age>65 years: Q4 vs Q1, OR(95%CI): 0.67, (0.53, 0.85), P =0.001)] .When the level of S-Klotho was higher, the risk of hyperuricemia in men was lower than that in women [male: Q4 vs Q1, OR(95%CI): 0.64, (0.53, 0.77), P <0.001; female: Q4 vs Q1 (95%CI):0.66, (0.54, 0.81), P <0.001].Conclusions:In middle-aged and elderly individuals, plasma S-Klotho levels were inversely correlated with hyperuricemia, with a saturation effect. Given the limitations of the research results, the underlying mechanism between S-Klotho and hyperuricemia should be further explored.
When a neglected tropical zoonotic disease emerges in non-endemic countries: Need to proactively fill the unveiled knowledge gaps towards human monkeypox among the Lebanese population
Authors: Youssef Dalal , Abboud Edmond , Kawtharni Malak , Zheim Zahraa , Arrage Nisrine Abou , Youssef Janet 
Published: August 2022

Abstract
Introduction: The ongoing multi-country outbreak of monkeypox (MPX) that emerges in non-endemic areas is a rare and unprecedented event that ignited a widespread public health concern. So far, Lebanon has reported four confirmed cases of MPX. Since good knowledge about the MPX virus and its associated disease is paramount for helping the Lebanese population prepare for a possible outbreak, therefore, it is important to assess their current level of knowledge regarding MPX and to identify its associated factors to highlight gaps in knowledge that should be filled.Methods: An online cross-sectional study was conducted over the first two weeks of August 2022 among adults aged 18 years and above recruited from all Lebanese provinces using a convenience sampling technique. An anonymous, Arabic, self-reported questionnaire covering all main aspects of knowledge regarding MPX was developed and adapted based on the available literature. Multivariable logistic regression was performed to identify the factors associated with knowledge level.Results: A total of 793 Lebanese adults participated in the study. The overall level of knowledge level regarding human MPX was poor among the Lebanese population; with only 33.04% of them having a good knowledge level ≥60%. Knowledge gaps and a substantial poor knowledge level were found in the majority of MPX knowledge domains especially those related to the routes of transmission (76.67%), clinical presentation and symptoms (71.63%), treatment (86.25%), and severity of the disease (91.3%). Interestingly, participants have a good knowledge level of the precautionary measures (80.45%), and the response to a suspected infection (65.20%). Female gender, increased age, and living in rural areas were found negatively associated with a good level of knowledge. However, participants with higher educational levels, those working in the medical field, those suffering from chronic disease/immunodeficiency, and participants with moderate/high economic situations were more likely to have a good knowledge score compared to their counterparts.Conclusion: The current study pointed out to poor knowledge level regarding MPX among the Lebanese population with substantial knowledge gaps in the majority of aspects of MPX knowledge. Our findings stress the urgent need to raise awareness and proactively fill the unveiled gaps, especially among less informed groups.
Identifying priority areas using a multispecies approach for the conservation of marine megafauna vulnerable species
Authors: Saüt¹ Maíra Moita , Monteiro¹ Danielle Silveira , Prado² Jonatas Henrique , Pennino³ Maria Grazia , Secchi¹ Eduardo Resende 
Published: August 2022

Abstract

Bycatch is one of the main causes of mortality of marine megafauna over the world. In the coastal waters of southern Brazil, bycatch in gillnet fisheries affects threatened species that use this region as a breeding and feeding area. The identification of hotspot areas of bycatch is necessary to design and prioritize efficient spatial-temporal closures that protect the largest possible number of threatened species of marine megafauna. In this context, the use of a multispecies approach is an important step towards planning effective fisheries management measures. This study has two main objectives: 1) to identify hotspot areas of bycatch in gillnet fisheries for the most threatened marine megafauna species on the continental shelf of Rio Grande do Sul (RS); 2) compare single species and multispecies mapping methods for the identification of these areas. To meet these objectives, data collected by onboard observers during fishing trips in the coastal commercial RS-based gillnet fleet, between 2013 and 2015 and between 2018 and 2020, were analyzed. For the identification of the areas, hierarchical Bayesian spatio-temporal models were implemented, using monospecific and multispecific approaches and a weighting system for the conservation status of the species. Both approaches provide similar results, identifying three bycatch hotspots according to the analyzed time frame. Based on our findings, we propose the creation of specific no-fishing areas in these regions. The suggested spatio-temporal closures would benefit several endangered species, also contributing to the recovery of fish populations.
Downscaling Daily Wind Speed with Bayesian Deep Learning for Climate Monitoring
Authors: Gerges Firas , Boufadel Michel C. , Bou-Zeid Elie , Nassif Hani , Wang Jason T. L. 
Published: August 2022

Abstract
Wind dynamics are extremely complex and have critical impacts on the level of damage from natural hazards, such as storms and wildfires. In the wake of climate change, wind dynamics are becoming more complex, making the prediction of future wind characteristics a more challenging task. Nevertheless, having long-term projections of some wind characteristics, such as daily wind speed, is crucial for effective monitoring of climate change, and for efficient disaster risk management. Furthermore, accurate projections of wind speed result in optimized generation of wind-based electric power. General Circulation Models (GCMs) provide long-term simulations (often till year 2100 or more) of multiple climate variables. However, simulations from a GCM are at a grid with coarse spatial resolution, rendering them ineffective to resolve and analyze climate change at the local regional level. Spatial downscaling techniques are often used to map such global large-scale simulations to a local small-scale region. In this paper, we present a novel deep learning framework for spatial downscaling, specifically for forecasting the daily average wind speed at a local station level using GCM simulations. Our framework, named Wind Convolutional Neural Networks with Transformers, or WCT for short, consists of multi-head convolutional neural networks, followed by stacked transformers, and an uncertainty quantification component based on Bayesian inference. Experimental results show the suitability of WCT when applied on four wind stations in New Jersey and Pennsylvania, United States. Moreover, we use the trained WCT on future GCM simulations to produce local-scale daily wind speed projections up to year 2100.
Novel ZnO Nanoparticles for Rapid Photocatalytic Degradation of Organic Dyes: Synthesis and Kinetics
Authors: B Sreelekshmi P , Pillai Reshma R , S Unnimaya , L Anju A , Parameswaran Meera Ayyappan , Parameswaran Meera Ayyappan 
Published: August 2022

Abstract
The removal of persistent dye pollutants from wastewater streams has drawn a lot of interest from the scientific community because photocatalysis is the most widely used practical strategy for addressing environmental contamination. Transition-metal oxides are seen to be the most prospective catalysts for efficient and environmental friendly wastewater treatment because of their significant photocatalytic activity, excellent solubility, and durability. In this study, we describe the simple, eco-sustainable and cost effective synthesis of ZnO nanoparticles and their use as photocatalysts to break down organic dyes like Congo red (CR) and Malachite Green (MG) in aqueous media. In aqueous solution at ambient temperature, ZnO nanoparticles showed outstanding photocatalytic degradation efficiency of 98.9% for the MG dye and 92.8% for the CR dye. The kinetics of photodegradation were also investigated and followed a pseudo-first-order mechanism, with rate constants of 0.0204 min− 1 MG and 0.0123 min− 1 for CR in accordance with the Langmuir-Hinshelwood model. Excellent recycling properties were displayed by ZnO nanoparticles for both dyes and the combined effects of their high adsorption capacity and photodegradation of organic dyes make them an extremely effective and affordable catalyst.
GNet4FL: Effective Fault Localization via Graph Convolutional Neural Network
Authors: Qian Jie , Ju Xiaolin , Chen Xiang 
Published: August 2022

Abstract
Fault localization aims to efficiently locate faults when debugging programs , reducing software development and maintenance costs. Spectrum-based fault location (SBFL) is the mainstream fault location technology, which calculates and ranks the suspicious value of each program entity with a specific formula by counting the coverage information of all the program entities and execution results of test cases. However, previous SBFL techniques suffered from low accuracy due to the sole use of execution coverage. This paper proposed an approach GNet4FL based on the graph convolutional neural network. GNet4FL first collects static features based on code structure and dynamic features based on test case results. Then, GNet4FL uses GraphSAGE to obtain node representation of source codes and performs feature fusion on an entity consisting of multiple nodes, which preserves the topological information of the graph. Finally, the representation of each entity is input to the multi-layer perceptron for training and ranking entities. The results show that GNet4FL successfully located 160 out of 262 faults, outperforming the three state-of-the-art methods, 94,42,14 higher in Top-1, and having close results to Grace with less cost. Furthermore, we investigated the impact of each component (i.e., graph neural network , pruning, and dynamic features) of GNet4FL on the results. We found that they all have a positive impact on our proposed approach.
Genetic screening for hypertension and COVID-19 reveals functional variant of SPEG associated with severe COVID-19 in female
Authors: Cheng Zhong-shan , Luo Yusi , Zhang Ke , Li Wei , Wu Guo-Feng , Yang Xiao-Meng , Guo Ming-Yang , Chen Fang , Shen Hu-Yan , Zhang Ping-Ping , Gao Han , Nie Ying , Wu Jia-Hong , Mou Rong , Shen Xiang-Chun 
Published: August 2022

Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 6.4 million deaths worldwide and is still spreading among global populations. The prevalent comorbidity between hypertension and severe COVID-19 suggests common genetic factors may affect the outcome of both diseases. As both hypertension and severe COVID-19 demonstrate sex-specific prevalence, common genetic factors among the two diseases may display gender-based differential associations. By evaluating COVID-19 association signals of 172-candidate hypertension single nucleotide polymorphisms derived from more than one million European individuals in two severe COVID-19 genome-wide association studies from UK BioBank with European ancestry, we revealed one functional cis expression quantitative trait locus of SPEG (rs12474050) associating with both hypertension and severe COVID-19 in female. The risk allele of rs12474050*T is correlated with lower SPEG expression in muscle-skeletal, heart-atrial appendage, and heart-left ventricle; among these tissues the SPEG expression is higher in female than in male COVID-19 patients. Further analysis revealed SPEG is mainly expressed in cardiomyocytes in heart and is upregulated upon SARS-CoV-2 infection, with significantly higher folder change of SPEG expression observed in female compared to male COVID-19 patients. Taken together, our analyses strongly suggest the involvement of SPEG in both hypertension and severe COVID-19 in female, which provides new insights for sex-specific effect of severe COVID-19 in female.
Is Intraoperative MRI Use in Malignant Brain Tumor Surgery a Health Care Burden? A Matched Analysis of MarketScan Database
Authors: Sharma Mayur , Wang Dengzhi , Palmisciano Paolo , Ugiliweneza Beatrice , Woo Shiao , Nelson Megan , Miller Donald , Savage Jesse , Boakye Maxwell , Andaluz Norberto , Mistry Akshitkumar M. , Chen Clark C. , Williams Brian J. 
Published: August 2022

Abstract
Background
Intraoperative magnetic resonance imaging (iMRI) is a useful adjunct for resection of primary malignant brain tumors (MBTs). The aim of our study is to investigate the impact of iMRI on health care utilization in patients who underwent craniotomy for resection of MBTs.
Materials and methods
MarketScan database were queried using the ICD-9/10 and CPT 4th edition, from 2008 to 2020. We included patients ≥ 18 years of age who underwent a craniotomy with at-least one year follow-up. Outcomes were length of stay (LOS), discharge disposition, hospital/emergency room (ER) re-admissions, outpatient services, medication refills and corresponding payments.
Results
Of 6,640 patients who underwent craniotomy for MBTs, 465 patients (7%) had iMRI used during the procedure with 0.7% per year increase in iMRI use during the study period. Patients without iMRI use had higher complications at index hospitalization compared to those with iMRI use (19% vs 14%, p = 0.04). There was no difference in the ER admission rates among the patients who underwent surgery with and without iMRI use at 6-months and 1-year after the index procedure. In terms of post-discharge payments, no significant differences were noted among the patients without and with iMRI use at 6-months ($81,107 vs. $ 81,458, p = 0.26) and 1-year ($132,657 vs. $ 118,113, p = 0.12).
Conclusion
iMRI use during craniotomy for MBT gradually increased during the study period. iMRI did not result in higher payments at index hospitalization, 6-months, and 1-year after the index procedure.
A Bayesian-Network-Based Quantum Procedure for Failure Risk Analysis
Authors: Carrascal Gines , Botella Guillermo , Barrio Alberto , Kremer David 
Published: August 2022

Abstract
Studying the propagation of failure probabilities in interconnected systems such as electrical distribution networks is traditionally performed by means of Monte Carlo simulations. In this paper, we propose a procedure for creating a model of the system on a quantum computer using a restricted representation of Bayesian networks. We present examples of this implementation on sample models using Qiskit and test them using both quantum simulators and IBM Quantum hardware. The results show a correlation in the precision of the results when considering the number of Monte Carlo iterations alongside the sum of shots in a single quantum circuit execution.