bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lightning Distribution in Tropical Cyclones Making Landfall in China
Authors: Zhang Wenjuan , Zhang Yijun , Shu Shoujuan , Zheng Dong , Xu Liangtao 
Published: August 2022

Lightning data from the World Wide Lightning Location Network (WWLLN) are used to document the lightning characteristics in tropical cyclones (TCs) making landfall in China. The landfall period is confined to 48 h prior to and after landfall (t-24∼t+24). Data from a total of 74 TCs are collected from 2010 to 2020, providing 3,293 individual time periods (1-h periods). To examine the radial and asymmetry distributions as a function of TC intensity, landing location, and vertical wind shear, the dataset is classified into two intensity categories, three shear groups, and four landing locations. WWLLN detected lightning activity in all TCs during the 48-h landfall, with lightning rates most frequently appearing between 250 and 600 str h−1. Extreme hourly lightning rates of 3,154 str h−1 and 4,426 str h−1 are observed in the inner core in Tropical Storm Cimaron (2013) and the outer rainbands in Severe Typhoon Matmo (2014), respectively, comparable to lightning activity in mesoscale convection systems on land. TCs landing in Guangdong and Hainan have the largest peak lightning rates, while those landing in Zhejiang and Shanghai show the lowest lightning rates. The maximum lightning density is found in the inner-core region of weak TCs (&lt;32.7 m s−1) that are located approximately 100–200 km away from the coastline. The radial distribution of lightning density at landing stages is consistent with that at mature stages when TCs are over the ocean. However, there is a shift in the lightning maximum from the inner core prior to landfall (t-24∼t0) to the outer rainbands after landfall (t0∼t+24), indicating the effects of dry continental air intrusion and the enhanced surface frictional convergence. Vertical wind shear is the dominant factor in producing lightning and convective asymmetry for TCs landing in all locations. Lightning asymmetries are enhanced with the increase in shear magnitude from low (&lt;5 m s−1) to moderate (5–10 m s−1) and high (&gt;10 m s−1) shear environments, both in weak and strong TCs (≥32.7 m s−1).
Variation in Nutritional and Antioxidant Attributes of Moringa oleifera L. Leaves at Different Maturity Stages
Authors: Qadir Rahman , Anwar Farooq , Bashir Kiran , Tahir Mudassir Hussain , Alhumade Hesham , Mehmood Tahir 
Published: August 2022

The present work reveals variation in the nutritional and antioxidant profiles of Moringaoleifera leaves with regard to four maturity stages (early, mid, penultimate and late). The corresponding yield of 80% methanolic extract (14.21 and 9.69%) and total phenolic contents (TPC) of the extract (95.26 and 38.22 mg GAE/g) from M. oleifera leaves were found to be maximum at early stage and minimum at the later stage. Total flavonoids, ash, protein, vitamin C and β-carotene contents were found to be minimum at the early stage and maximum at later stage (12.26 ± 0.47 to 30.07 ± 1.09 mg/g, 10.36–15.92%,50.3 ± 0.15 to 56 ± 0.77 mg/100 g, 143.14 ± 0.74 to 164.81 ± 0.44 mg/100g, and 89 ± 0.28 to 112.8 ± 1.40 mg/100 g). Amino acids including valine, alanine, leucine and phenylalanine were identified with their least contents at early stages (90.87, 53.07, 55.21, and 48.65 µg/g) and maximum at later stages (197.66, 114.3, 114.2, and 104.5 µg/g, respectively). The levels of different minerals such as Cu, Fe, Mn in M. oleifera leaves at different maturity stages varied from 0.59 to 2.08, 21.96 to 58.68, and 5.56 to 13.84 mg/100 g, respectively. RP-HPLC analysis of the nutritionally rich later-stage leave samples revealed the presence of quercetin as a major component (21.64 mg/kg), followed by benzoic acid, ferulic acid, sinapic acid, gallic acid, and p-coumaric acid with contributions of 13.03, 8.85, 3.39, 2.88, and 1.59 mg/kg, respectively. Overall, a considerable variation in the profile of different nutrients and antioxidants was noted in M. oleifera leaves as maturity progressed. These results support the harvesting of M. oleifera leaves at an appropriate maturity stage to maximize the functional food and nutraceutical benefits of this valuable food commodity.
Significances of magnetic dipole flow and melting heat transfer over suspended dust particles along with carbon nanotubes
Authors: Alfannakh Huda 
Published: August 2022

The current research letter is materialized to examine the combined effect of thermophoretic dust particle diffusion and magnetic dipole flow toward a stretchable sheet. The slip effect is used in the development of the momentum equation. Water is considered as a base fluid, and single-walled carbon nanotubes and multiwalled carbon nanotubes are nanoparticles. The aforementioned rheological model is formulated in the way of nonlinear partial differential equations (PDEs). The structure of nonlinear biformed ordinary differential equations (ODEs) is obtained from the modeled nonlinear PDEs by incorporating valid sameness transformations. The system of ODEs is then figured out by employing the tool of MATLAB function bvp4c. The significant nature of the contributing parameter for both the single-wall and multiwall cases is presented via graphs. From the results, we conclude that an impact of the melting effect, mounting of Pr, reported a thinner thermal boundary layer thickness. Furthermore, a clear rise of nanofluid temperature is noticed for the greater melting M1 parameter. The slip parameter plays a significant role in the enhancement of the velocity profile.
RETRACTED: Treatment mechanism of hexavalent chromium wastewater in constructed wetland-microbial fuel cell coupling system
Authors: Shi Yucui , Tang Gang , You Shaohong , Jiang Pingping , Zhang Xuehong , Deng Zhenliang 
Published: August 2022

Cr(VI) is toxic to the human body and environment. As a suitable wastewater treatment with low energy requirement technology, constructed wetland-microbial fuel cells (CW-MFCs) can treat Cr(VI) wastewater while generating electricity. In this study, CW-MFC and constructed wetland systems were developed to purify Cr(VI) wastewater. The removal mechanism of Cr(VI) was examined by electron paramagnetic resonance (EPR), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy. The results demonstrated that the average pollutant removal efficiency of the CW-MFC system is 2.99–8.13% higher than that of the constructed wetland system, and the maximum power density is 505.61 mW m−2. Moreover, the XPS and EPR analyses demonstrated that Cr in substrates and Leersia hexandra Swartz primarily is in the form of Cr(III). Moreover, in plants and substrates, the Cr(III) content of the CW-MFC system was higher than that of the control, and the bioconcentration and translocation factors were 0.23 and 0.05 higher than those in the control group, respectively. Therefore, the CW-MFC system can efficiently remove Cr(VI) and promote the accumulation and transport of Cr. Microbial community diversity in the CW-MFC was significantly higher than CW. The abundance of electrogenic bacteria Geobacter and metal dissimilatory reducing bacteria Acinetobacter in CW-MFC is higher than that in CW. To summarize, the study results provide a theoretical basis for the mechanism study of Cr(VI) wastewater treatment using CW-MFC systems.
Sources and migration characteristics of fluorine in the river water of a small karst watershed influenced by coal mining
Authors: Du Shuangxue , An Li , Huang Jiangxun , Li Qingguang , Wu Pan , Guo Xingqiang 
Published: August 2022

In high-fluorine geological background areas, the supergene geochemical process of fluorine has an impact on regional environmental health and safety, which has long been the focus of attention. However, in karst areas characterized by a high incidence of endemic fluorosis, the migration and transformation of fluorine in surface water have not received sufficient attention. This study investigated the joint influence of the weathering and erosion of carbonate rocks and coal-bearing strata on a typical small watershed. Accordingly, 239 samples representing 13 periods of hydrochemical samples were systematically collected to clarify the source, migration, and transformation characteristics of fluorine in surface water. The results revealed that the pH of the Huatan River was low in the rainy season and high in the dry season. The annual variation range of fluorine concentration was 0.11–0.40 mg/L. Although mining development produced acid mine drainage with high fluorine concentration, its impact at the watershed scale appeared to be limited. In terms of spatial scale, the concentration of fluorine in the Huatan River increased gradually from upstream to downstream. The dissolution of fluorite and other fluorine-bearing minerals had not reached the saturation state. The fluorine in the watershed primarily came from the dissolution of fluorine-bearing minerals, followed by the contribution of atmospheric precipitation. The release of fluorine adsorbed on the surface of clay minerals was not the main source of this element. The leaching of the watershed was shown to represent a critical transport process concerning fluorine in the Huatan River, and evaporation had a notable impact on the enrichment of fluorine in water.
The GNB3 c.825C>T (rs5443) polymorphism and protection against fatal outcome of corona virus disease 2019 (COVID-19)
Authors: Möhlendick Birte , Schönfelder Kristina , Zacher Christoph , Elsner Carina , Rohn Hana , Konik Margarethe J. , Thümmler Laura , Rebmann Vera , Lindemann Monika , Jöckel Karl-Heinz , Siffert Winfried 
Published: August 2022

Background and aims: Albeit several factors which influence the outcome of corona virus disease (COVID-19) are already known, genetic markers which may predict the outcome of the disease in hospitalized patients are still very sparse. Thus, in this study, we aimed to analyze whether the single-nucleotide polymorphism (SNP) rs5443 in the gene GNB3, which was associated with higher T cell responses in previous studies, might be a suitable biomarker to predict T cell responses and the outcome of COVID-19 in a comprehensive German cohort.Methods: We analyzed the influence of demographics, pre-existing disorders, laboratory parameters at the time of hospitalization, and GNB3 rs5443 genotype in a comprehensive cohort (N = 1570) on the outcome of COVID-19. In a sub cohort, we analyzed SARS-CoV-2-specific T cell responses and associated GNB3 rs5443 genotypes. We investigated the influence of all factors on COVID-19 fatality in multivariable analysis.Results: We found a younger patient age, normotension or absence of diabetes mellitus or cardiovascular diseases, normal blood cell counts, and low inflammatory markers at hospital admission were protective factors against fatal course of disease. In addition, the rs5443 TT genotype was significantly associated with protection against COVID-19 fatality (OR: 0.60, 95% CI: 0.40–0.92, p = 0.02). We also observed significantly increased SARS-CoV-2-specific T cell responses in rs5443 TT genotype carriers (p = 0.01). Although we observed a significant association of the factors described previously in univariate analysis, only a younger age of the patients, normal blood cell counts, and the GNB3 rs5443 TT genotype remained independent predictors against COVID-19 fatality in multivariable analysis.Conclusion: Immutable predictors for COVID-19 fatality are relatively rare. In this study we could show that the TT genotype of the SNP rs5443 in the gene GNB3 is associated with protection against COVID-19 fatality. It was as well correlated to higher SARS-CoV-2-specific T cell responses, which could result in a milder course of disease in those patients. Based on those observations we hereby provide a further prognostic biomarker, which might be used in routine diagnostics as a predictive factor for COVID-19 mortality already upon hospitalization.
Engineered nanoceria alleviates thermally induced oxidative stress in free-living Breviolum minutum (Symbiodiniaceae, formerly Clade B)
Authors: Roger Liza M. , Russo Joseph A. , Jinkerson Robert E. , Giraldo Juan Pablo , Lewinski Nastassja A. 
Published: August 2022

The breakdown of symbiotic mutualism between cnidarian hosts and dinoflagellate algae partners (i.e., bleaching) has been linked to an immune-like response pathway brought on by a nitro-oxidative burst, a symptom of thermal stress. Stress induced by reactive oxygen species (ROS)/reactive nitrogen species is a problem common to aerobic systems. In this study, we tested the antioxidant effects of engineered poly(acrylic acid)-coated cerium dioxide nanoparticles (CeO2, nanoceria) on free-living Symbiodiniaceae (Breviolum minutum), a dinoflagellate alga that forms symbiotic relationships with reef-building corals and anemones. Results show that poly(acrylic acid)-coated CeO2 with hydrodynamic diameters of ~4 nm are internalized by B. minutum in under 30 min and subsequently localized in the cytosol. Nanoceria exposure does not inhibit cell growth over time, with the treated cultures showing a similar growth trend over the 25-day exposure. Aerobic activity and thermal stress when held at 34°C for 1 h (+6°C above control) led to increased intracellular ROS concentration with time. A clear ROS scavenging effect of the nanoceria was observed, with a 5-fold decrease in intracellular ROS levels during thermal stress. The nitric oxide (NO) concentration decreased by ~17% with thermal stress, suggesting the rapid involvement of NO scavenging enzymes or proteins within 1 h of stress onset. The presence of nanoceria did not appear to influence NO concentration. Furthermore, aposymbiotic anemones (Exaiptasia diaphana, ex Aiptasia pallida) were successfully infected with nanoceria-loaded B. minutum, demonstrating that inoculation could serve as a delivery method. The ability of nanoceria to be taken up by Symbiodiniaceae and reduce ROS production could be leveraged as a potential mitigation strategy to reduce coral bleaching.
A model for predicting fall risks of hospitalized elderly in Taiwan-A machine learning approach based on both electronic health records and comprehensive geriatric assessment
Authors: Chu Wei-Min , Kristiani Endah , Wang Yu-Chieh , Lin Yen-Ru , Lin Shih-Yi , Chan Wei-Cheng , Yang Chao-Tung , Tsan Yu-Tse 
Published: August 2022

BackgroundsFalls are currently one of the important safety issues of elderly inpatients. Falls can lead to their injury, reduced mobility and comorbidity. In hospitals, it may cause medical disputes and staff guilty feelings and anxiety. We aimed to predict fall risks among hospitalized elderly patients using an approach of artificial intelligence.Materials and methodsOur working hypothesis was that if hospitalized elderly patients have multiple risk factors, their incidence of falls is higher. Artificial intelligence was then used to predict the incidence of falls of these patients. We enrolled those elderly patients aged &gt;65 years old and were admitted to the geriatric ward during 2018 and 2019, at a single medical center in central Taiwan. We collected 21 physiological and clinical data of these patients from their electronic health records (EHR) with their comprehensive geriatric assessment (CGA). Data included demographic information, vital signs, visual ability, hearing ability, previous medication, and activity of daily living. We separated data from a total of 1,101 patients into 3 datasets: (a) training dataset, (b) testing dataset and (c) validation dataset. To predict incidence of falls, we applied 6 models: (a) Deep neural network (DNN), (b) machine learning algorithm extreme Gradient Boosting (XGBoost), (c) Light Gradient Boosting Machine (LightGBM), (d) Random Forest, (e) Stochastic Gradient Descent (SGD) and (f) logistic regression.ResultsFrom modeling data of 1,101 elderly patients, we found that machine learning algorithm XGBoost, LightGBM, Random forest, SGD and logistic regression were successfully trained. Finally, machine learning algorithm XGBoost achieved 73.2% accuracy.ConclusionThis is the first machine-learning based study using both EHR and CGA to predict fall risks of elderly. Multiple risk factors of falls in hospitalized elderly patients can be put into a machine learning model to predict future falls for early planned actions. Future studies should be focused on the model fitting and accuracy of data analysis.
Predicting treat-and-extend outcomes and treatment intervals in neovascular age-related macular degeneration from retinal optical coherence tomography using artificial intelligence
Authors: Bogunović Hrvoje , Mares Virginia , Reiter Gregor S. , Schmidt-Erfurth Ursula 
Published: August 2022

PurposeTo predict visual outcomes and treatment needs in a treat &amp; extend (T&amp;E) regimen in neovascular age-related macular degeneration (nAMD) using a machine learning model based on quantitative optical coherence tomography (OCT) imaging biomarkers.Materials and methodsStudy eyes of 270 treatment-naïve subjects, randomized to receiving ranibizumab therapy in the T&amp;E arm of a randomized clinical trial were considered. OCT volume scans were processed at baseline and at the first follow-up visit 4 weeks later. Automated image segmentation was performed, where intraretinal (IRF), subretinal (SRF) fluid, pigment epithelial detachment (PED), hyperreflective foci, and the photoreceptor layer were delineated using a convolutional neural network (CNN). A set of respective quantitative imaging biomarkers were computed across an Early Treatment Diabetic Retinopathy Study (ETDRS) grid to describe the retinal pathomorphology spatially and its change after the first injection. Lastly, using the computed set of OCT features and available clinical and demographic information, predictive models of outcomes and retreatment intervals were built using machine learning and their performance evaluated with a 10-fold cross-validation.ResultsData of 228 evaluable patients were included, as some had missing scans or were lost to follow-up. Of those patients, 55% reached and maintained long (8, 10, 12 weeks) and another 45% stayed at short (4, 6 weeks) treatment intervals. This provides further evidence for a high disease activity in a major proportion of patients. The model predicted the extendable treatment interval group with an AUROC of 0.71, and the visual outcome with an AUROC of up to 0.87 when utilizing both, clinical and imaging features. The volume of SRF and the volume of IRF, remaining at the first follow-up visit, were found to be the most important predictive markers for treatment intervals and visual outcomes, respectively, supporting the important role of quantitative fluid parameters on OCT.ConclusionThe proposed Artificial intelligence (AI) methodology was able to predict visual outcomes and retreatment intervals of a T&amp;E regimen from a single injection. The result of this study is an urgently needed step toward AI-supported management of patients with active and progressive nAMD.
Day 1 neutrophil-to-lymphocyte ratio (NLR) predicts stroke outcome after intravenous thrombolysis and mechanical thrombectomy
Authors: Chen Siyan , Cheng Jianhua , Ye Qiang , Ye Zusen , Zhang Yanlei , Liu Yuntao , Huang Guiqian , Chen Feichi , Yang Ming , Wang Chuanliu , Duan Tingting , Liu Xiang , Zhang Zheng 
Published: August 2022

BackgroundThe neutrophil-to-lymphocyte ratio (NLR) is a biomarker reflecting the balance between inflammation (as indicated by the neutrophil count) and adaptive immunity (as indicated by the lymphocyte count). We aimed to estimate ability of NLR at admission and at day 1 for predicting stroke outcome after two reperfusion therapies: intravenous thrombolysis (IVT) and mechanical thrombectomy (MT).MethodsA retrospective analysis was performed on patients who received recombinant human tissue plasminogen activator (IVT) and/or underwent MT for acute ischemic stroke (AIS) at the First Affiliated Hospital of Wenzhou Medical University (Wenzhou, China) from January 2018 to December 2020. Blood samples were taken on admission to hospital and on day 1 after stroke onset. Binary logistic regression models were applied to investigate potential associations between NLR at admission or day 1 and the following outcomes: symptomatic intracerebral hemorrhage (sICH), dependence, and mortality at 90 days. The ability of NLR to predict AIS outcome was analyzed using receiver operating characteristic (ROC) curves.ResultsData for 927 patients (576 IVT and 351 MT) were reviewed. High admission NLR was associated with dependence in IVT treatment [adjusted odds ratio (OR) 1.21, 95% confidence interval (CI) 1.14–1.23] and 90-day mortality in MT patients (OR 1.09, 95% CI 1.04–1.13). In IVT patients, high NLR at day 1 predicted dependence (OR 1.09, 95% CI 1.02–1.11), sICH (OR = 1.07, 95% CI 1.01–1.12), and 90-day mortality (OR 1.06, 95% CI 1.01–1.15). In MT patients, high NLR at day 1 also predicted dependence (OR 1.08, 95% CI 1.02–1.11) and sICH (OR 1.03, 95% CI 1.01–1.09). ROC analysis confirmed that NLR at day 1 could predict dependence (cut-off 4.2; sensitivity 68.7%; specificity 79.6%), sICH (cut-off 5.1; sensitivity 57.9%, specificity 73.5%), and death (cut-off 5.4; sensitivity 78.8%; specificity 76.4%) in IVT patients. Z values of area under the curves were compared between admissioin and day 1 NLR in IVT patients and showed day 1 NLR can better predict dependence (Z = 2.8, p = 0.004) and 90-day death (Z = 2.8, p = 0.005).ConclusionsNLR is a readily available biomarker that can predict AIS outcome after reperfusion treatment and day 1 NLR is even better than admission NLR.
The relationship between ultra-processed food intake and cardiometabolic risk factors in overweight and obese women: A cross-sectional study
Authors: Hosseininasab Dorsa , Shiraseb Farideh , Noori Sahar , Jamili Shahin , Mazaheri-Eftekhar Fatemeh , Dehghan Mahshid , da Silva Alessandra , Bressan Josefina , Mirzaei Khadijeh 
Published: August 2022

BackgroundCardiovascular diseases (CVDs) are the leading cause of death globally. Based on recent studies, one of the factors that can have detrimental effects on CVD is the consumption of ultra-processed foods (UPFs). The current study investigated the relationship between UPF intake and cardiometabolic risk factors among Iranian women.MethodsThe current cross-sectional study was conducted on 391 women aged 18–65 years with a body mass index (BMI) ≥ 25 kg/m2. Dietary intake was assessed using a 147-item food frequency questionnaire (FFQ). Anthropometric and biochemistry parameters were also collected. UPFs were identified using the NOVA classification.ResultsIn the present study, women had a mean (standard deviation) age of 36.67 (9.10) years and the mean BMI of 31.26 (4.29) kg/m2. According to our findings, there was a significant association between UPF consumption and transforming growth factor (TGF) (β: 0.101, 95% CI: 0.023, 0.180, p = 0.012), atherogenic coefficient (AC) (β: 0.011, 95% CI: 0.001, 0.032, p = 0.034), visceral fat level (VFL) (β: 0.006, 95% CI: −0.017, 0.029, p = 0.076), and the quantitative insulin sensitivity check index (QUICKI) (β: −3.775, 95%CI: 0.001, 0.001, p = 0.042).ConclusionIn conclusion, an increase in consumption of one gram of UPFs is associated with an increase in TGF, AC, and VFL but with a decrease in QUICKI. Despite this, further experimental studies are necessary to draw a more definite conclusion and disentangle the mechanisms by which UPFs may affect health.