bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian Quantification of Covariance Matrix Estimation Uncertainty in Optimal Fingerprinting
Authors: Baugh Samuel , McKinnon Karen A. 
Published: August 2022

Abstract

Regression-based optimal fingerprinting techniques for climate change detection and attribution require the estimation of the forced signal as well as the internal variability covariance matrix in order to distinguish between their influences in the observational record. While previously developed approaches have taken into account the uncertainty linked to the estimation of the forced signal, there has been less focus on uncertainty in the covariance matrix describing natural variability, despite the fact that the specification of this covariance matrix is known to meaningfully impact the results. Here we propose a Bayesian optimal fingerprinting framework using a Laplacian basis function parameterization of the covariance matrix. This parameterization, unlike traditional methods based on principal components, does not require the basis vectors themselves to be estimated from climate model data, which allows for the uncertainty in estimating the covariance structure to be propagated to the optimal fingerprinting regression parameter. We show through a CMIP6 validation study that this proposed approach achieves better-calibrated coverage rates of the true regression parameter than principal component-based approaches. When applied to HadCRUT observational data, the proposed approach detects anthropogenic warming with higher confidence levels, and with lower variability over the choice of climate models, than principal-component-based approaches.
The role of HS N-sulfation in the pathogenesis of RSV nephropathy
Authors: Dong Liqun , Wang Ke , Jing Shuolan , Zhang Liang , Guo Yannan , Wu Jin , Yu Ping , Wang Zheng 
Published: August 2022

Abstract
Background Minimal change nephrotic syndrome (MCNS) is the most frequent cause of nephrotic syndrome in childhood. Previous studies have showed that respiratory syncytial virus (RSV) is the common trigger of MCNS. Methods Immunofluorescence of 3G10, 10E4 and HepSS1was performed in the kidneys, lungs and livers of RSV nephropathy rat model and the control. RSV fusion protein (RSVF) was detected by Western blot. The levels of HS domains in the kidneys and lungs of RSV nephropathy rat model were compared with that of RSVF. Results The expression of 10E4 and Hepss1 in kidney and lung of the normal rat was higher than 3G10. In the rat model of RSV nephropathy, RSVF of the kidneys and lungs showed stronger signal than the livers on day 8 and 14 after RSV infected. The expression of 3G10, 10E4 and Hepss1 in kidneys were obvious on day 4, then reduced from day 8 to 120. In the lungs the expression of 10E4 decreased continuously from day 8 to day 120, and Hepss1 reached the highest level on day 14 following by a reduction. While the level of RSVF was highest on day 8 when HS domains appeared weakly.Conclusions In the study, there were two main findings: (1) it was because of the Heterogeneity of HS, that is, rich N-sulfation in the kidney mediating RSV adhesion, which resulted in the progress of MCNS; (2) We firstly demonstrated that the damage directly of RSV and T-cell disorder in the pathogenesis of MCNS were equally important.
Clinical Decision Support Systems Research in Nursing: A Visual Survey
Authors: Qin Lan Fang , Zhu Yi , Liu Chong Bin , Wang Rui , Gao XI Ren , Chen Ping Ping 
Published: August 2022

Abstract
Background：Artificial intelligence (AI) has a big impact on healthcare now and in the future. Nurses, representing the largest proportion of healthcare workers, are set to benefit greatly from this technology. AI-Enabled Clinical Decision Support Systems has received a great deal of attention recently. Bibliometric analysis can offer an objective, systematic, and comprehensive analysis of specific field with a vast background. However, no bibliometric analysis has investigated AI-Enabled Clinical Decision Support Systems research in Nursing.Objective:To determine the characteristics of articles about the global performance and development of AI-Enabled Clinical Decision Support Systems research in Nursing.Methods: In this study, the bibliometric approach was used to estimate the searched data on Clinical Decision Support Systems research in Nursing from 2009 to 2022, and we also utilized CiteSpace and VOSviewer software to build visualizing maps to assess the contribution of different journals, authors, et al, as well as to identify research hot spots and promising future trends in this research field.Result:From 2009 to 2022, a total of 2159 publications were retrieved. The number of publications and citations on AI-Enabled Clinical Decision Support Systems research in Nursing has increased obviously in the last years. However, They are understudied in the field of nursing and there is a compelling need to development more more high-quality research. Conclusion: AI-Enabled Nursing Decision Support System use in clinical practice is still in its early stages. These analyses and results hope to provide useful information and references for future research directions for researchers and nursing practitioners who use AI-Enabled Clinical Decision Support Systems.
Combining palaeontological and neontological data shows a delayed diversification burst of carcharhiniform sharks likely mediated by environmental change
Authors: Brée Baptiste , Condamine Fabien L. , Guinot Guillaume 
Published: August 2022

AbstractEstimating deep-time species-level diversification processes remains challenging. Both the fossil record and molecular phylogenies allow estimating speciation and extinction rates, but each type of data may still provide an incomplete picture of diversification dynamics. Here, we combine species-level palaeontological (fossil occurrences) and neontological (molecular phylogenies) data to estimate deep-time diversity dynamics through process-based birth-death models for Carcharhiniformes, the most speciose shark order today. Despite their abundant fossil record dating back to the Middle Jurassic, only a small fraction of extant carcharhiniform species is recorded as fossils, which impedes relying only on the fossil record to study their recent diversification. Combining fossil and phylogenetic data, we recover a complex evolutionary history for carcharhiniforms, exemplified by several variations in diversification rates with an early low diversity period followed by a Cenozoic radiation. We further reveal a burst of diversification in the last 30 million years, which is partially recorded with fossil data only. We also find that reef expansion and temperature change can explain variations in speciation and extinction through time. These results pinpoint the primordial importance of these environmental variables in the evolution of marine clades. Our study also highlights the benefit of combining the fossil record with phylogenetic data to address macroevolutionary questions.
Novel machine learning-based point-score model as a non-invasive decision-making tool for infected ascites in patients with hydropic decompensated liver cirrhosis: A retrospective multicentre study.
Authors: Würstle Silvia , Hapfelmeier Alexander , Karapetyan Siranush , Studen Fabian , Isaakidou Andriana , Schneider Tillman , Schmid Roland M. , von Delius Stefan , Gundling Felix , Triebelhorn Julian , Burgkart Rainer , Obermeier Andreas , Mayr Ulrich , Heller Stephan , Rasch Sebastian , Lahmer Tobias , Geisler Fabian , Chan Benjamin , Turner Paul E. , Rothe Kathrin , Spinner Christoph D. , Schneider Jochen 
Published: August 2022

Abstract
Purpose
This study aimed to assess the distinctive features of patients with infected ascites and liver cirrhosis and develop a scoring system allowing to accurately identify patients who do not require abdominocentesis to rule out infected ascites.
Methods
A total of 700 episodes of patients with decompensated liver cirrhosis undergoing abdominocentesis between 2006 and 2020 were included. 532 spontaneous bacterial peritonitis episodes and 37 secondary peritonitis episodes were compared to a control group of 125 patients with 131 episodes of non-infected ascites. Overall, 34 clinical, drug, and laboratory features were evaluated using machine learning to identify key differentiation criteria and integrate them into a point-score model.
Results
The most important distinction criteria between infected and non-infected ascites were inflammatory markers C-reactive protein and leukocyte count, the occurrence of organ failure, fever, and comorbidities. In total, 11 discriminatory features were selected using a Lasso regression model to establish a point-score model. Considering a pre-test probability for infected ascites of 10%, 15%, and 25%, the negative and positive predictive values of the point-score model for infected ascites were 98.1%, 97.0%, 94.6% and 14.9%, 21.8%, and 34.5%, respectively. Besides the main model, a simplified model was generated, containing only features that are fast to collect, and revealed similar predictive values.
Conclusions
Our point-score model appears to be a promising non-invasive approach to rule out abdominocentesis in clinical routine with high negative predictive values in patients with hydropic decompensated liver cirrhosis. Diagnosis of infected ascites, on the other hand, requires abdominocentesis.
Prevalence and factors associated with underweight among 15–49-year-old women in Sierra Leone: A secondary analysis of Sierra Leone Demographic Health Survey of 2019.
Authors: Kitara David Lagoro , Ikoona Eric Nzirakaindi , Toure Mame Awa , Namulemo Lucy , Kamara Kassim , Oyat Freddy Wathum Drinkwater , Aloyo Judith , Njenga Amon , Kaluya Ronald 
Published: August 2022

AbstractBackground Women are at risk of being underweight due to biological, socio-economic, and cultural factors. Underweight women have higher risks of poor obstetric outcomes. We aimed to determine the prevalence and factors associated with being underweight among women of reproductive age (15–49 years) in Sierra Leone. Methods We used the Sierra Leone Demographic and Health Survey (2019-SLDHS) data of 5,714 women aged between 15 to 49 years, excluding the pregnant, post-natal, lactating, and post-menopausal women. A multistage stratified sampling approach was used to select study participants, and data was collected using a validated questionnaire. A multivariable logistic regression analysis determined factors associated with underweight among 15–49-year-old women in Sierra Leone. Results The prevalence of underweight was 6.7% (502/7,514). Women who belonged to the 25–34-year age group (Adjusted Odds Ratio) (AOR) = 1.670,95%CI:1.254–2.224; p < 0.001 were least likely to be underweight compared to 15–24 and 35-49-year age groups. Unmarried women AOR = 0.594, 95%CI:0.467–0.755; p < 0.001 were less likely to be underweight compared to married women. Women residing in the Northern region AOR = 0.734,95%CI:0.559–0.963; p = 0.026 were least likely to be underweight compared to those residing in the Northwest AOR = 0.840,95%CI:0.609–1.160; p = 0.290; South AOR = 0.776,95%CI:0.588–1.204; p = 0.073 and Western regions of Sierra Leone AOR = 1.385,95%CI:0.954–2.01; p = 0.087. Women who did not listen to radios AOR = 95%CI:0.673–0.826; p < 0.001 were less likely to be underweight compared to those who listened to radios. Conclusion The current study showed that age, marital status, region of residence, and listening to radios are associated with being underweight in Sierra Leone. There is a need to address the socio-economic determinants of undernutrition in women, mainly due to poverty and regional inequalities.
Using genetic analysis to understand the relationship of cognitive traits with peptic ulcer and Alzheimer’s disease
Authors: Adewuyi Emmanuel , O'Brien Eleanor , Porter Tenielle , Laws Simon 
Published: August 2022

Abstract
Cognitive decline is typical of Alzheimer’s disease (AD). While studies suggest links between the gut and the brain in the risk of AD, the relationship of gastrointestinal tract (GIT) disorders with cognition is poorly understood. Leveraging large-scale genome-wide association study summary statistics, we assess the relationship of ten cognition-related traits with peptic ulcer disease (PUD) and AD. Similar to AD, we demonstrate a highly significant negative genetic correlation between PUD and intelligence (rg = -0.33, P = 2.11 × 10− 11), cognitive performance (rg = -0.32, P = 9.00 × 10− 16), educational attainment (rg = -0.46, P = 5.50 × 10− 33) and other cognitive traits (rg = -0.27 – -0.47, P = 8.41 × 10− 4 – 5.75 × 10− 25). Mendelian randomisation analysis suggests a risk-decreasing causal influence of genetically predicted intelligence (Odds ratio, OR = 0.77, P = 3.92 × 10− 7), educational attainment (OR = 0.56, P = 6.68 × 10− 21), and cognitive performance (OR = 0.75, P = 2.11 × 10− 6) on PUD’s risk. Genes with nominal association (Pgene < 0.05), in gene-based analyses, were significantly enriched (Pbinomial−test = 1.18 × 10− 3 – 3.85 × 10− 4) across cognitive traits, PUD and AD—indicating evidence of gene-level genetic overlap. Combining gene-based association results, we identify many shared genes reaching genome-wide significance (PFisher’s−combined−analysis <2.68 × 10− 6) for cognitive traits, PUD and AD. These findings highlight the protective role of cognitive traits on the risk of PUD and AD, provide additional insights into the genetic relationship of AD with GIT disorders and identify new targets for further investigation.
Modeling, Design and Kinetics of Novel Fred – Ugi Environmental Wastes Converter Reactor Plant For Crude Oil Distillates, Minerals and Petrochemical Synthesis
Authors: Ugi F. B. , O Ehirim E. , Wordu A. A , U Ugi B. 
Published: August 2022

Abstract
This present research thrives to design a waste converter reactor plant (WCRP) with which waste from various sources subjected to combustion and distillation process will generate bio-fuels, solid minerals and petrochemical feed stocks for further applications. Material and energy balance principles were applied in hands with some principles of thermodynamics, mathematics and kinetics. Volume and functional parameters such as length, space time and space velocity, diameter and length of the stirrer and also heat generated per unit volume and temperature of the WCRP were considered in the design process. Simulation of the design models and results were obtained using MATrix LABoratory (MATLAB-Simulink) and other data analyses simulators. Reactor performance equations for the reactor and major equipment were developed from first principle by the application of the principles of conservation of mass and energy. Dimensional and functional parameters of the waste converter reactor plant (WCRP) was also calculated. The results obtained for the dimensional and functional parameters at fractional conversion of 90% are: volume = 1.8m3, length = 1.0m, space time = 16.6hrs, space velocity = 0.06hr-1, heat load = 5.55*105J.
Stacked kinship CNN vs. GBLUP for genomic predictions of additive and complex continuous phenotypes
Authors: Nazzicari Nelson , Biscarini Filippo 
Published: August 2022

Abstract
Deep learning is impacting many fields of data science with often spectacular results. However, its application to whole-genomepredictions in plant and animal science or in human biology has been rather limited, with mostly underwhelming results.While most works focus on exploring alternative network architectures, in this study we propose an innovative representation ofmarker genotype data. Different types of genomic kinship matrices are stacked together in a 3D pile from where 2D grayscaleslices are extracted and fed to a deep convolutional neural network (DNN). We tested nine scenarios of simulated phenotypeswith combinations of additivity, dominance and epistasis, and compared the DNN to GBLUP-A (Genomic BLUP computedusing only the additive kinship matrix) and GBLUP-optim (Genomic BLUP with additive, dominance, and epistasis kinshipmatrices, as needed).Results varied depending on the accuracy metric employed, with DNN performing better in terms of Root Mean Squared Error(1%-12% lower than GBLUP-A; 1%-9% lower than GBLUP-optim) but worse in terms of Pearson’s correlation (0.505 for DNNcompared to 0.672 and 0.669 of GBLUP-A and GBLUP-optim for fully additive case; 0.274 for DNN, 0.279 for GBLUP-A, and0.477 for GBLUP-optim for fully dominant case).
Bioprospecting of Actinomycetes from Diverse Ecosystems: A Potential Source of Pharmaceutically Active Metabolites
Authors: Godbole Amita , Wadetwar Rita , Bundale Sunita , Nashikkar Nandita , Kanojiya Pranita 
Published: August 2022

Abstract

Present work includes isolation of actinomycetes from marine, mangrove, and terrestrial environments followed by their screening for bioactivity. Study led to the isolation of 109 actinomycete isolates. Broth supernatants and ethyl acetate crude extracts were analyzed for bioactivity of which, 19 isolates showed a potent inhibition against E. coli, 17 isolates showed activity against S. aureus, 10 isolates exhibited activity against K. pneumoniae and B. subtilis each, and 9 isolates showed zone of inhibition against C. albicans. Potential actinomycetes were and identified by 16S rRNA gene analysis and their sequences were deposited in GenBank. Two isolates belonging to non-Streptomyces genera viz., Micromonospora and Nocardiopsis were obtained. The broad-spectrum antimicrobial activity against all the test organisms at very low concentration was shown by soil isolates D, D2, F30 (brown pigment), TS13 (Orange red), TS14 (green), TS4 (cherry red), and marine isolate M11 (yellow).
Prurigo Nodularis Onset during IL-17A Inhibitor Treatment of Psoriasis: A Case Report
Authors: Yang Qingqing , LYU Jiajie , Gui Yu , Yu Shuling , Chen Jiajie , Zhang Haoxue , Liu shengxiu 
Published: August 2022

Abstract
Background: secukinumab has been approved by the U.S. FDA and the European Medicines Agency for the treatment of moderate-to-severe plaque psoriasis and psoriatic arthritis. Here we report a case of prurigo nodularis during the treatment of psoriasis with secukinumab, which has never been reported before. Case introduction: the patient was a 22-years-old male with a 6-month history of severe plaque paoriasis vulgaris, who received regular treatment with satisfactory control of the psoriatic rash, and was seen for 1 week for red papules and nodules with pruritus on the trunk and extremities. Dermatologic condition: multiple edematous red firm papules on the trunk and extremities in the form of soy or hemispherical nodules, with some tops visible as ulcerated crusts, red in color, firm to touch, and negative Auspitz sign. Pathological examination confirmed prurigo nodularis (PN). Conclusion: This case is shared to inform clinicians about yet another adverse effect of the IL-17A inhibitor in the treatment of psoriasis. It is recommended that patients be carefully informed of the possible risk of prurigo nudularis before starting treatment.
MP2 study of the absorption of CO2 onto the water monomer, dimer and trimer
Authors: Lawson Daniel B. , Pappas Jordan 
Published: August 2022

Abstract
The nature of the CO2-nH2O interaction where n=1,2 and 3 is explored to evaluate the energetics of the CO2 molecule and small water clusters using ab initio MP2 and CCSD(T). We are interested in the absorbance of CO2 onto the water cluster and not those interactions that significantly alter the original water cluster. Thus, we characterize the interaction energy in terms of CO2 binding to an intact water cluster. We provide 3 lowest energy isomers of the CO2-water trimer not previously reported. We include a description of the bond lengths between the CO2 and the water and include AIM critical points to identify the hydrogen bond interactions.
A new method for guiding the use of cement reinforced screws: The combination method was used to determine osteoporosis
Authors: xu wei , Zhang Xiangyang , Chen liwei , Li Yifan , Silian Wang , Shichao Tong , Xiaojian Ye , Zhikun Li 
Published: August 2022

Abstract
Objective
To accurately judge the preoperative osteoporosis of patients, it is planned to develop a more accurate evaluation method of osteoporosis and better guide the use of bone cement reinforced screws.
Method
The patients WHO had undergone posterior lumbar decompression and fusion internal fixation in Shanghai Tongren Hospital were retrospectively analyzed. The general information, bone mineral density assessment data, Fracture risk prediction rate(WHO Fracture Risk Assessment Tool (FRAX)), and whether to use cement reinforced screws were collected.Definition of combination method: T value<-2.5 or HU value < 110 or VBQ > 3.5.The diagnostic rates of osteoporosis were compared between DXA, HU, VBQ, NBHA, and combination methods, and the correlation between different methods was analyzed. Binary logistic regression was used to analyze the significant influencing factors of the use of cement-reinforced screws.
Result
A total of 178 patients were enrolled in the study, aged 65.73 ± 14.43 years, 121 female, 57 male, BMI was 22.88 ± 3.52, 57 (32.0%) used cement reinforced screws, and 14 (7.9%) had previous fracture history.The diagnostic rates of osteoporosis by DXA, HU, VBQ, NBHA and combination method were 22.5% (40/178), 47.2% (84/178), 56.2% (100/178), 64.0% (114/178) and 75.8% (135/178), respectively.HU, VBQ, NBHA, and combination methods were significantly different from DXA in the diagnosis rate of osteoporosis (P < 0.001). Binary Logistics regression showed that age, T value, HU value, and VBQ value significantly influenced bone cement screw use, and the odds ratio of VBQ was 4.315. The prediction accuracy of the regression equation was 90.4%, the area under the ROC curve was 0.974, and the Youden index was 0.830.
Conclusion
At present, the most widely used DXA method for the diagnosis of osteoporosis has false negative results, and there are great differences among different methods for the diagnosis of osteoporosis. The detection rate of the combined method for osteoporosis is higher than other methods (75.8%). Age, T value, HU value, and VBQ value were significant influencing factors for the use of cement screws, and the accuracy of the regression equation was 90.4%. Cement-reinforced screws are recommended when osteoporosis is determined by a combination method.
Artificial Neural Network Modeling For California Bearing Ratio (CBR) Prediction in Clayey Soil Stabilised with Tyre Buffings and Lime
Authors: Erzin Yusuf , CABALAR Ali Firat , KARABASH Zuheir , ERZİN Selin 
Published: August 2022

Abstract

In this study, artificial neural network (ANN) and multiple regression (MR) models were developed to predict the California Bearing Ratio (CBR) values of clayey soil stabilised with tyre buffings and lime. To achieve this, a series of the CBR tests were performed on clayey soil mixed with tyre buffings and lime in ratios of 0, 5, 10, and 15%, and 0, 2, 4, and 6% of dry weight of the specimens, respectively. The results of the CBR tests were used in the development of both models. The predicted CBR values from both ANN and MR models were compared with experimentally measured CBR values. It is found that the ANN model gives more reliable predictions than the MR model. Moreover, several performance indices called as the determination coefficient, variance account for, mean absolute error, root mean square error, and the scaled percent error were used as the criteria for measuring the performance of the ANN and MR models. Based on these indices, the proposed ANN model yielded better performance than MR model in predicting the CBR values of clayey soil stabilized with tyre buffings and lime.