bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatigue in the general population: associations to age, gender, socioeconomic status, and physical activity -a web-based survey
Authors: RIMAUD DIANA , ESPEIT Loïc , MAT Franck LE , CUDEL Claire , CHAIGNEAU Cyril , LAPOLE Thomas , MILLET Guillaume 
Published: March 2023

Abstract
Background: Though fatigue is common in the general population, most studies investigating its predictors are either outdated or under-sampled, which can lead to conflicting results. This study aims to describe the factors associated with fatigue in the general adult population.
Methods: Using a web-based survey, 3008 participants were asked to self-report fatigue and physical activity status, using the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) questionnaire and the Godin-Shepard Leisure-Time Physical Activity Questionnaire (GSLTPAQ). Questions regarding gender, geographical location and socioeconomic items were also included.
Results: Stepwise regression showed that the FACIT-F score was explained by age, gender and physical activity status (p<0.0001). Women had a highest level of fatigue than men (p<0.0001). Fatigue significantly decreased with age until 75 years, then increased again (p<0.0001). FACIT-F scores correlated positively with GSLTPA scores (r=0.075, p<0.0001). The physical activity status had a significant effect on fatigue (p<0.0001), i.e. insufficiently active respondents presented a significantly higher fatigue than moderately active and active respondents. There were significant effects of socio-professional categories (p<0.001) and standard of living (p<0.01) on fatigue.
Conclusion: Fatigue is strongly associated with female gender, lower age and a lack of physical activity. Lower-income social-professional groups are also more likely to experience fatigue, while the retired seem to be more spared from fatigue than others. Since fatigue is associated with quality of life, it should be considered as a major public health issue, particularly in women, young and insufficiently active people.
Ethnopharmacology and Species diversity of Pteridophyta in Cyathea Park, Bali: A Field study and Literature Review
Authors: Juliasih Ni Ketut Ayu , Adnyana I Made Dwi Mertha 
Published: March 2023

Abstract
Pteridophyta has been studied and conserved at the botanical garden. However, few have found and documented the medicinal properties of Pteridophyta species. The study identified species diversity and ethnopharmacology of Pteridophyta collected in Cyathea Park, Bali. Field exploration research and literature review were used in this study. The research was conducted by directly exploring the species of Pteridophyta collected in Cyathea Park, Bali and literature studies on the benefits and ethnopharmacology of Pteridophyta species are used as candidates and raw materials for traditional medicine. Data search is carried out systematically by utilizing databases and keywords. All the data is examined qualitatively and descriptively. The study's findings indicate nine species: Cyathea contaminans (Wall.ex Hook) Copel, Asplenium nidus L., Asplenium sp., Selaginella sp., Diplazium esculentum., Angiopteris evecta (G.Forst.) Hoffm, Cyatheasp., Nephrolepis hirsutula (Forst), and Dicksonia blumei (Kunze) Moore. The leaves and shoots are the most frequently used raw materials in medicine. At the same time, the roots, stems, and hair are utilized in planting mediums, crafts, games, and food production. Pteridophyta species treat fever, cough, anticonvulsant, antibacterial, anti-inflammatory, antipyretic, antidiuretic, antioxidant, insecticide, larvicide, diabetes, and anti-retroviral. As many as nine identified species Pteridophyta in Cyathea Park, Bali has benefits as traditional medicinal agents and has been widely used by the people as the culture of the archipelago. Its pharmacological, phytochemical and toxicity properties need further investigations.
Lethal and sublethal effects on stingless bee (Partamona helleri) larvae caused by chronic exposure to three agrochemicals
Authors: Botina Lorena Lisbetd , Barbosa Wagner Faria , Acosta João Paulo Lima , Bernardes Rodrigo Cupertino , Cortes Johana Elizabeth Quintero , Pylro Victor Satler , Mendonça Adriana Correa , Barbosa Renata Cristina , Lima Maria Augusta P. , Martins Gustavo Ferreira 
Published: March 2023

Abstract
Over the last few decades, agrochemicals have been partially associated with a global reduction in bees. Toxicological assessment is crucial for understanding the overall agrochemical risks to stingless bees. Therefore, the lethal and sublethal effects of agrochemicals commonly used in crops (copper sulfate, glyphosate, and spinosad) on the behavior and gut microbiota of the stingless bee, Partamona helleri, were assessed using chronic exposure during the larval stage. The recommended field doses of CuSO4 (200 Active Ingredient, a.i., µg) and spinosad (8,16 a.i. µg) reduced survival, but not glyphosate (148 a.i. µg). No significant adverse effects on bee development were observed in any treatment with CuSO4 or glyphosate, but spinosad increased the number of deformed bees and reduced their body mass. Agrochemicals changed the behavior of bees and composition of the gut microbiota of adult bees, and metals such as copper accumulated in the bees’ bodies. The response of bees to agrochemicals depends on the class or dose of the ingested compound. In vitro rearing of stingless bees larvae is a useful tool to elucidate the sublethal effects of agrochemicals.
Machine Learning Techniques for the Identification of Risk Factors Associated with Food Insecurity among Adults in Arab countries during the COVID-19 Pandemic
Authors: Qasrawi Radwan , Hoteit Maha , Tayyem Reema , Bookari Khlood , Sabbah Haleama Al , Kamel Iman , Dashti Somaia , Allehdan Sabika , Bawadi Hiba , Waly Mostafa , Ibrahim Mohammad , Polo Stephanny Vicuna , Al-Halawa Diala Abu 
Published: March 2023

Abstract
Background: A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has further aggravated food insecurity among vulnerable communities, and thus has sparked the global conversation of equal food access, food distribution, and improvement of food support programs. This research was designed to identify the key features associated with food insecurity during the COVID-19 pandemic using Machine learning techniques. Seven machine learning algorithms were used in the model, which used a dataset of 32 features. The model was designed to predict food insecurity across ten Arab countries in the Gulf and Mediterranean regions. A total of 13,443 participants were extracted from the international Corona Cooking Survey conducted by 38 different countries during the COVID -19 pandemic.
Results: The findings indicate that Jordanian, Palestinian, Lebanese, and Saudi Arabian respondents reported the highest rates of food insecurity in the region (15.4%,13.7%,13.7% and 11.3% respectively). On the other hand, Oman and Bahrain reported the lowest rates (5.4% and 5.5% respectively). Our model obtained accuracy levels of 70%-82% in all algorithms. Gradient Boosting and Random Forest techniques had the highest performance levels in predicting food insecurity (82% and 80% respectively). Place of residence, age, financial instability, difficulties in accessing food, and depression were found to be the most relevant features associated with food insecurity.
Conclusions: Overall, ML algorithms seem to be an effective method in early detection and prediction of food insecurity. Future research would benefit from utilizing the proposed model in developing more complex and accurate models aiming to enhance granularity, with the ability to share data, to incorporate wide range of variables, and to make use of automation for effective prevention and intervention programs at the regional and individual levels.
Exploring the Impact Mechanism of Executives' Environmental Attention on Corporate Green Transformation—Evidence from MD&amp;A Textual Analysis of Chinese Companies
Authors: Ding Xiaowei , Xu Zhenpeng , Petrovskaya Maria V. , Wu Kaikun , Ye Lyu , Sun Yao , Makarov Vasiliy M. 
Published: March 2023

Abstract
The allocation of executives' environmental attention (EEA) is of great significance in promoting the green upgrading of industrial structures and achieving corporate green transformation. Based on upper echelon theory and the attention-based view, we use panel data of Chinese manufacturing companies from 2015-2020 to construct a two-way fixed effects model to explore the impact mechanism of EEA on corporate green transformation performance (CGTP). Baseline regression shows that EEA significantly improves CGTP. The reliability of findings is verified by reducing time windows, replacing the independent variable, expanding the data source and adding missing variables. In the heterogeneity analysis, the positive effect of EEA on CGTP is significant for eastern companies and does not differ in the property rights grouping. After propensity score matching, environmental attributes grouping shows that the positive effect of EEA on CGTP is more significant for non-heavy polluters. Extended research shows that government subsidies have a positive moderating effect, while female executives play only a symbolic role. Moreover, green innovation activities have positive partial mediating effects. Green innovation is the best way to address environmental pollution and achieve corporate green transformation. Our research provides implications for decision-makers to allocate their attention, and thereby achieve green development appropriately.
On the analysis of a heterogeneous coupled network of memristive Chialvo neurons.
Authors: Ghosh Indranil , Muni Sishu Shankar , Fatoyinbo Hammed Olawale 
Published: March 2023

Abstract
We perform a numerical study on the application of electromagnetic flux on a heterogeneous network of Chialvo neurons represented by a ring-star topology. Heterogeneities are realized by introducing additive noise modulations on both the central-peripheral and the peripheral-peripheral coupling links in the topology not only varying in space but also in time. The variation in time is understood by two coupling probabilities, one for the central-peripheral connections and the other for the peripheral-peripheral connections respectively, that update the network topology with each iteration in time. We have further reported the rich spatiotemporal patterns like two-cluster states, chimera states, coherent, and asynchronized states that arise throughout the network dynamics. We have also investigated the appearance of a special kind of asynchronization behavior called "solitary nodes" that have a wide range of applications pertaining to real-world nervous systems. In order to characterize the behavior of the nodes under the influence of these heterogeneities, we have studied two different metrics called the "cross-correlation coefficient" and the "synchronization error". Additionally, to capture the statistical property of the network, for example, how complex the system behaves, we have also studied a measure called "sample entropy". Various two-dimensional color-coded plots are presented in the study to exhibit how these metrics/measures behave with the variation of parameters.
A microdeletion del(12)(p11.21p11.23) with a cryptic unbalanced translocation t(7;12)(q21.13;q23.1) implicates new candidate loci for intellectual disability and Kallmann syndrome
Authors: Ben-Mahmoud Afif , Kishikawa Shotaro , Gupta Vijay , Leach Natalia T. , Shen Yiping , Moldovan Oana , Goel Himanshu , Hopper Bruce , Ranguin Kara , Gruchy Nicolas , Maas Saskia M , Lacassie Yves , Kim Soo-Hyun , Kim Woo-Yang , Quade Bradley J. , Morton Cynthia C. , Kim Cheol-Hee , Layman Lawrence C. , Kim Hyung-Goo 
Published: March 2023

Abstract
In an apparently balanced translocation t(7;12)(q22;q24)dn exhibiting both Kallmann syndrome (KS) and intellectual disability (ID), we detected a cryptic heterozygous 4.7 Mb del(12)(p11.21p11.23) unrelated to the translocation breakpoint. This new finding raised the possibility that KS combined with neurological disorder in this patient could be caused by gene(s) within this deletion at 12p11.21-12p11.23 instead of disrupted or dysregulated genes at the genomic breakpoints. Screening of five candidate genes at both breakpoints in 48 KS patients we recruited found no mutation, corroborating our supposition. To substantiate this hypothesis further, we recruited six additional subjects with small CNVs and analyzed eight individuals carrying small CNVs in this region from DECIPHER to dissect 12p11.21-12p11.23. We used multiple complementary approaches including a phenotypic-genotypic comparison of reported cases, a review of knockout animal models recapitulating the human phenotypes, and analyses of reported variants in the interacting genes with corresponding phenotypes. The results identified one potential KS candidate gene (TSPAN11), seven candidate genes for the neurodevelopmental disorder (TM7SF3, STK38L, ARNTL2, ERGIC2, TMTC1, DENND5B, and ETFBKMT), and four candidate genes for KS with ID (INTS13, REP15, PPFIBP1, and FAR2). The high-level expression pattern in the relevant human tissues further suggested the candidacy of these genes. We propose that the dosage alterations of the candidate genes may contribute to sexual and/or cognitive impairment in patients with KS and/or ID. Further identification of point mutations through next generation sequencing will be necessary to confirm their causal roles.
Influence of China’s Green Finance on Enterprises’ Green Technology Innovation
Authors: Zeng Qian , Tong Yijie , Yang Yiying 
Published: March 2023

Abstract
This paper examines the impact of a green financial reform pilot zone policy on the enterprises’ green technology innovation level. This is done in tandem with the emergence of a market-driven sustainable technology innovation system and the rapid growth of green finance. In this paper, a difference-in-differences model is built using panel data of A-share listed companies from 2012 to 2020. The findings indicate that the sustainable technology innovation of enterprises has been considerably aided by the green finance reform pilot zone policy. In terms of enterprise heterogeneity, the implementation of this regulation will make a greater contribution to the innovative activities of large-scale firms, state-owned enterprises, and non-heavily polluting enterprises. Further examination of the influence mechanism reveals that green financial policies can encourage sustainable technology innovation by firms by easing finance funding limitations and improving signaling effects. Simultaneously, the mechanism of improving enterprises' green technology innovation through external market surveillance is not effective. This paper proposes policy recommendations to help green finance improve the sustainable transformation of enterprises.
The Predictive Accuracy of Barrett Toric Calculator Using Measured Posterior Corneal Astigmatism Derived from Swept Source-OCT and Scheimpflug Camera
Authors: Yang Xiaotong , Jiang Yuanfeng , Lin Song , Bai Xiaomei , Yin Yufan , Zhao Fangyu , Yang Jun , Chen Xiteng , Tian Fang , Liang Jingli , Bu Shaochong 
Published: March 2023

Abstract
PURPOSE:
To compare the performance of Barrett toric calculator incorporated with measured posterior corneal astigmatism (PCA) derived from IOL Master 700 and Pentacam HR versus predicted PCA.
METHODS:
The predicted residual astigmatism using Barrette toric IOL calculator with predicted PCA, measured PCA from IOL Master 700 and measured PCA from Pentacam were calculated with the preoperative keratometry and intended IOL axis with modification. The vector analysis was performed to calculate the mean absolute prediction error (MAE), the centroid of the prediction error and the percentage of eyes with a prediction error within ±0.50 D, ± 0.75 D, and ± 1.00 D.
RESULTS: In 57 eyes of 57 patients with mean age of 70.42±10.75 years, the MAE among the three calculation methods were 0.59±0.38 D (Predicted PCA) , 0.60±0.38 D (Measured PCA from IOL Master 700) and 0.60±0.36 D (Measured PCA from Pentacam) with no significant difference, either in the whole sample, the WTR eyes and the ATR eyes (F = 0.078, 0.306 and 0.083, p=0.925, 0.739 and 0.920, respectively). Measured PCA obtained from IOL Master 700 resulted in one level reduction (from Tn to Tn-1) in 49.12% eyes in cylindrical model selection, while measured PCA obtained from Pentacam resulted in one level reduction of toric model selection in 18.18% eyes.
CONCLUSION:
The present study suggested that the incorporation of measured PCA values derived from IOL Master 700 and Pentacam produce comparable clinical outcome with the predicted PCA mode in Barrette toric calculator.
Coherent manipulation of extreme-ultraviolet Bessel vortex beam from solids by active wavefront shaping of driving fundamental beam
Authors: Kim Byunggi , Choi Seungman , Won Seung Jai , Kim Yong Woo , Kim Young-Jin , Kim Seung-Woo 
Published: March 2023

Abstract
High-harmonic generation (HHG) of extreme ultraviolet (EUV) radiation enables ultrafast spectroscopy and nanoscale coherent imaging with timing resolutions down to the attosecond regime. However, beam manipulations such as steering and focusing remain a major challenge for handy implementation of such applications towards the achievement of a wavelength-scale spatial resolution. Here, we present a solid-based non-collinear HHG scheme mediating the propagation control and helical wavefront generation commanded via a spatial light modulator. The phase-matching-insensitive nature of the solid-HHG leads to the coherent multi-fold conversion of wavefronts enabling active control of the EUV harmonic beam propagation. Further, EUV harmonics generated by double-annular beams were converted to the Bessel vortex beam, for the first time, narrowing the beam diameter to 3.4 wavelengths with a long millimetre-level depth-of-focus without extra EUV-dedicated optical components. Our results will suggest a solid-HHG as a powerful tool for high photon-energy applications with a nanoscale spatial resolution.
Measuring children’s engagement in early childhood education and care settings: a scoping literature review
Authors: Ritosa Andrea , Åström Frida , Björck Eva , Borglund Lisa , Karlsson Elin , Nylander Elisabeth , McHugh Elaine 
Published: March 2023

Abstract
The purpose of this scoping review was to identify studies where young children’s engagement in early childhood education and care (ECEC) settings was measured and to investigate conceptualizations and operationalizations of child engagement. The literature search conducted in March 2021 included ERIC, PsychInfo, Scopus and Web of Science databases and it resulted in 5965 articles, of which 286 were included in this review. Eligibility criteria were measurements of child engagement in any formal ECEC setting before starting first grade. Data was extracted about engagement conceptualization, theoretical frameworks, study population, study design, and engagement measurement tools and methods. The results showed variations both in the definitions and in the measurement of child engagement. The most common method of measuring children’s engagement in ECEC was observations by an external observer, followed by teacher surveys. Measures of general child engagement in ECEC have a focus on behavioral aspects of engagement while measures that focus on academic activities are more likely to include additional cognitive and emotional aspects of engagement. Child self-reports were rarely used and only present in measures of academic engagement of young children. About one-third of the identified studies relied on unestablished measures of child engagement. Seventy-seven unique established measures of child engagement were identified.
Imaging quality of an artificial intelligence denoising algorithm: validation in 68Ga PSMA-11 PET for patients with biochemical recurrence of prostate cancer
Authors: Margail Charles , Merlin Charles , Billoux Tommy , Wallaert Maxence , Otman Hosameldin , Sas Nicolas , Molnar Ioana , Guillemin Florent , Boyer Louis , Guy Laurent , Tempier Marion , Levesque Sophie , Revy Alban , Cachin Florent , Chanchou Marion 
Published: March 2023

Abstract
Background
68Ga-PSMA PET is the leading prostate cancer imaging technique, but the image quality remains noisy and could be further improved using an Artificial Intelligence-based denoising algorithm. To address this issue, we analyzed the overall quality of reprocessed images compared to standard reconstructions. We also analyzed the diagnostic performances of the different sequences and the impact of the algorithm on lesion intensity and background measures.
Material and Methods
We retrospectively included 30 patients with biochemical recurrence of prostate cancer who had undergone 68Ga-PSMA-11 PET-CT. We simulated images produced using only a quarter, half, three-quarters, or all of the acquired data material reprocessed using the SubtlePET® denoising algorithm. Three physicians with different levels of experience blindly analyzed every sequence and then used a 5-level Likert scale to assess the series. The binary criterion of lesion detectability was compared between series. We also compared lesion SUV, background noise, and diagnostic performances of the series (sensitivity, specificity, accuracy).
Results
VPFX-derived series were classified differently but better than standard reconstructions (p < 0.001) using half the data. Q.Clear series were not classified differently using half the signal. Some series were noisy but had no significant effect on lesion detectability (p > 0.05). The SubtlePET® algorithm significantly decreased lesion SUV values (p < 0.005) and increased liver background (p < 0.005) and had no substantial effect on the diagnostic performance of each reader.
Conclusion
We show that the SubtlePET® can be used for 68Ga-PSMA scans using half the signal with similar image quality to Q.Clear series and superior quality to VPFX series. However, it significantly modifies quantitative measurements and should not be used for comparative examinations in case of anteriorities reconstructed with standard algorithm.
TMBpred: A bioinformatics tool for precise prediction of the Tumor Mutation Burden in 14 cancer types
Authors: Marino-Buslje Cristina , Martínez-Pérez Elizabeth , Torres Agustina , Iserte Javier , Molina-Vila Miguel 
Published: March 2023

Abstract
Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the current panels for next generation sequencing (NGS) of tumor samples are focused on drivers and actionable genes and give inaccurate predictions of TMB. TMBpred provides an easy to use web server for the selection of NGSs panels and models that can offer reliable and clinically relevant estimates of TMBs for 14 human malignancies. It also gives a TMB prediction based on preexisting sequencing data, which can be of help to improve the selection of patients that will benefit from the ICB therapy. The best panels provided by our server have between 0.23 and 1.49 Mb, in range with the panels currently used in clinical labs.