bluuebunny/crossref_metadata_2025_split huggingface dataset:
The association between red blood cell distribution width, C-reactive protein and renal function in patients with type2 diabetes mellitus
Authors: Shao Zehua , Dong Yang , Huo Shuai , Niu Peiyuan , Shao Fengmin 
Published: October 2022

Abstract
Objective
Red cell distribution width (RDW) and C-reactive protein (CRP) were respectively considered as important biomarker of cardiovascular diseases and inflammatory diseases.We aimed to evaluate the association of RDW) ,CRP with renal function in patients with type2 diabetes mellitus(T2DM ).
Methods
Patients with T2DM with a wide range of estimated glomerular filtration rate(eGFR) and proteinuria from 2019 to 2021 at Henan Provincial People’s Hospital were included in this study.. Blood samples from T2DM patients with normal eGFR(n = 146) and T2DM patients with decreased eGFR(n = 246) were collected. Clinical characteristics, routine blood test results and biochemical parameters were recorded, including age, gender, red blood cell, hemoglobin, RDW, platelet, CRP, albumin, total bilirubin, glucose, high-density lipoprotein, uric acid, creatinine, urea nitrogen and cystatin C. The effect of RDW and CRP level on the renal function was evaluated by using multiple linear step.wise regression analysis.
Results
Compared with the T2DM patients with normal eGFR,the the T2DM patients in decreased eGFR group had lower levels of hemoglobin, albumin and platelet, and higher levels of CRP, Uric acid, creatinine and cysC. Moreover, the levels of RDW levels were negatively correlated with eGFR (r=-0.224,p < 0.001), but positively related with CRP (r = 0.211,p < 0.001). Importantly, Multiple linear regression analysis showed that the levels of RDW had significant effects on decline of renal function (β = 0.091, p = 0.002).
Conclusions
RDW were an independent risk factor for for decline in renal function in patients with T2DM, RDW was also positively correlated with CRP.
The effect of biochar on nitrogen availability and bacterial ocommunity diversity in farmland
Authors: Hu Tian , Wei Jiating , Du Li , Chen Jibao , Zhang Jun 
Published: October 2022

Abstract

Purpose:Soil nitrification and denitrification are key factor in the global nitrogen cycle. This study was conducted to investigate the effect of biochar application on soil nitrogen and bacterial diversity.Methods:Pot experiments were conducted to investigate the effects of different biochar-based rate 0% (CK)、0.5% (BC1)、1.0% (BC2)、2.0% (BC3) and 4.0% (BC4) on soil nutrient and bacterial community diversity and composition.Results:The results indicate that the total nitrogen (TN) and ammonium nitrogen (AN) contents in the soil increased by 4.7–32.3% and 8.3–101.5%, respectively. The microbial biomass nitrogen (MBN) content increased with increased amounts of biochar rate. The application of biochar also significantly changed the soil bacterial community composition. The copy number of 16S marker gene of related enzymes to the nitrification process in BC2 was reduced by 20.1%. However, the gene expressions of nitric oxide reductase and nitrous oxide reductase in BC3 increased by 16.4% and 16.0%, respectively, compared to those in CK. AN, nitrate nitrogen (NN), and NN/TN were the main factors affecting the structure of the soil bacterial community. In addition, the expressions of nitrite reductase, hydroxylamine, and nitric oxide reductase (cytochrome c) were also significantly correlated.Conclustion:Therefore, biochar application can improve the availability of soil nitrogen, alter the structure and diversity of the soil bacterial community, and prevent risks caused by soil nitrogen and environmental pollution.
Primary Hyperparathyroidism in Young and Middle-age Patients is Associated With Metabolic Disorders: a Prospective Comparative Study
Authors: Bibik Ekaterina E. , Dobreva Ekaterina A. , Elfimova Alina R. , Miliutina Anastasia P. , Eremkina Anna K. , Gorbacheva Anna M. , Krupinova Julia A. , Koksharova Ekaterina O. , Sklyanik Igor A. , Mayorov Alexander Y. , Mokrysheva Natalia G. 
Published: October 2022

Abstract
Background: Components of metabolic syndrome can be observed in patients with primary hyperparathyroidism (PHPT). The pathogenesis of these disorders remain unclear because of the lack of relevant experimental models and the heterogeneity of examined patient groups. The effect of surgery on metabolic abnormalities is also controversial. We conducted a comprehensive assessment of metabolic parameters in young and middle-age patients with PHPT.
Methods: One-center prospective comparative study was carried out. The participants underwent a complex biochemical and hormonal examination, a hyperinsulinemic euglycemic and hyperglycemic clamps, a bioimpedance analysis of the body composition before and 13 months after parathyroidectomy compared to sex-, age- and body mass index matched healthy volunteers.
Results: 45.8% of patients (n=24) had excessive visceral fat. Insulin resistance was detected in 54.2% cases. PHPT patients had higher serum triglycerides, lower M-value and higher C-peptide and insulin levels in both phases of insulin secretion compared to the control group (p<0.05 for all). There are tendencies to decreased fasting glucose (р=0.031), uric acid (р=0.044) levels and insulin level of second secretion phase (р=0.039) after surgery, but no statistically significant changes of lipid profile and M-value as well as body composition were revealed. Negative correlations between serum calcium and total cholesterol levels as well as percent body fat and osteocalcin, b-CrossLaps and magnesium levels were revealed in patients before surgery.
Conclusions. PHPT is associated with insulin resistance which is the main risk factor of serious metabolic disorders. Radical surgery may potentially improve carbohydrate and purine metabolism.
The novel probiotic preparation based on Lactobacillus spp. mixture on the intestinal bacterial community structure of Cherry Valley Duck
Authors: Zhao Kai , Zhou Duoqi , Liu Wenqi , Zhang Yixun , Gai Mengrui , Han Yu , Li Wenhui , He Guangyu , Xiong Yan , Dong Jinsheng , Hu Jie , Liu Yannan , Shi Shuiqin 
Published: October 2022

Abstract
Purpose
The development and utilization of probiotics have many environmental benefits when they are used to replace antibiotics in animal production. In this study, intestinal lactic acid bacteria were isolated from the intestines of Cherry Valley ducks. Probiotic lactic acid bacterial strains were screened for antibacterial activity and tolerance to produce a Lactobacillus spp. mixture. The effects of the compound on the growth performance and intestinal flora of Cherry Valley ducks were studied.
Method
In this experiment, we isolated and screened lactic acid bacteria from healthy cherry intestine. The dominant lactic acid bacteria were screened by antibacterial test and tolerance test, and then the new probiotic preparation of lactic acid bacteria mixture was prepared by compound culture of lactic acid bacteria. One day old healthy Cherry Valley ducks were divided into two groups. One group was used as the experimental control, and the other group was used to evaluate the new probiotic preparation feeding group of lactic acid bacteria mixture. The 16S rDNA high-throughput sequencing technique was used to analyze the diversity of intestinal microorganisms in Cherry Valley ducks.
Result
Based on the results of the antibacterial activity and tolerance tests, the highly active strains Lactobacillus casei 1.2435, L. salivarius L621, and L. salivarius L4 from the intestines of Cherry Valley ducks were selected. The optimum ratio of L. casei 1.2435, L. salivarius L621, and L. salivarius L4 was 1:1:2, the amount of inoculum used was 1%, and the fermentation time was 14 h. In vivo experiments showed that compared with the control group, the relative abundances of intestinal Lactobacillus and Blautia were significantly increased in the experimental group fed the lactobacillus compound (P < 0.05); the relative abundances of Parabacteroides, [Ruminococcus]_torques_group, and Enterococcus were significantly reduced (P < 0.05), and the growth and development of the dominant intestinal flora were promoted in the Cherry Valley ducks.
Conclusion
The optimal proportion of the new probiotic preparation of lactic acid bacteria mixture is L. casei 1.2435, L. salivarius L621, and L. salivarius L4 was 1:1:2. It can promote the growth and development of the dominant intestinal flora of Cherry Valley ducks, and has made an important contribution to the healthy breeding of Cherry Valley ducks.
Tropical Cyclone-Induced Downwelling: Observational Evidence for an Overlooked Mechanism
Authors: Yang Chien-Yi , Yang Yiing Jang , Tseng Yu-heng , Jan Sen , Chang Ming-Huei , Wei Ching-Ling , Terng Chuen-Teyr 
Published: October 2022

Abstract
Tropical cyclones (TCs) cause intense natural hazards and drive upper ocean cooling via vertical mixing and upwelling through a series of processes involving air-sea interaction. Among these processes, TC-induced upper ocean warming and the underlying mechanisms have rarely been noted. Here, we analyzed upper ocean responses to 32 TC events observed by two buoys in the western North Pacific from 2016 to 2021. Supplemented with numerical experiments, we suggest that downwelling, a long-neglected response, frequently occurs around the radius of the 34-knot wind speed during and after TC passage. Downwelling was identified via pronounced warming anomalies under a shallow mixed layer depth. We further found that a negative wind stress curl and current-induced convergence are two primary mechanisms of downwelling. These findings highlight downwelling existence, which is crucial for understanding the relationship between TCs and biogeochemical processes in the upper ocean.
Kinematics of a Platform Stabilization using 3-PRS Parallel Manipulator
Authors: Udomsap Tossaporn , Chinchouryrang Sakda , Liampipat Siwat , Chanthasopeephan Teeranoot 
Published: October 2022

Abstract
In this paper, a 3-PRS (prismatic, revolute, and spherical) parallel manipulator for platform stabilization is designed. The main purpose of this device is to stabilize visual equipment, which is placed on top of a car to inspect electrical transmission cables as part of routine maintenance. Due to the bulky and heavy infrared cameras used during inspections, a stabilizer platform has been designed to handle the weight of camera equipment up to 10 kg. This device consists of two major mechanisms. The first mechanism is able to adjust the angle of the camera. Thus, the user can focus the camera along the electric transmission lines. The second mechanism is for stabilization. The mechanism serves to stabilize the orientation and position of the camera in roll, pitch, and heave directions. To test the performance of the stabilization mechanism, the device is fed with the known value of the angle as regards input. As such, the device is trying to compensate for the change in angle. Results show that errors between input angles and compensated angles are in the range of 0.4-3%. Errors are seen to be within an acceptable range. It is significant that the resultant errors do not affect the orientation of the camera.
Domination Number Based on Fuzzy Bridges in Fuzzy Graphs and Applications
Authors: Hamidi Mohammad , Nikfar Mohammad Esmaiel 
Published: October 2022

Abstract
In this paper, we consider the notion of (crisp)domination set of fuzzy graphs via fuzzy bridges and compute domination numbers in this regard. Indeed it is tried to combine the fuzzy values of both vertices and edges to present this domination number in fuzzy graphs. The main method in this research is based on the computation of domination number of complete fuzzy graphs with vertices depend on the distinct fuzzy value and generalization of domination number of complete fuzzy graphs with vertices depending on the indistinct fuzzy value. As a result of this study is to compute of domination number of cyclic strong fuzzy graphs with vertices depending on the distinct fuzzy value. Also, it is analyzed some critical vertices in cyclic strong fuzzy graphs such that by linking some edges in these vertices to cyclic strong fuzzy graphs, the domination number of complete fuzzy graphs is obtained. Thus there is a relationship between the domination number of cyclic strong fuzzy graphs and the domination number of complete fuzzy graphs by removing some special edges in complete fuzzy graphs. The paper includes implications for the development of fuzzy graphs, and for modeling the uncertainty problems by domination numbers and applications in some complex networks. The new conception of domination number in fuzzy graphs based on fuzzy bridges was given for the first time in this paper. We find an Algorithm that can compute the domination number of complete and cyclic strong fuzzy graphs and can apply it in the modeling of real problems of complex networks.
Bias Analysis in Healthcare Time-Series (BAHT) Decision Support Systems from Meta Data
Authors: Dakshit Sagnik , Dakshit Sristi , Khargonkar Ninad , Prabhakaran Balakrishnan 
Published: October 2022

Abstract
One of the hindrances in the widespread acceptance of deep learning-based decision support systems in healthcare is bias. Bias in its many forms occurs in the datasets used to train and test deep learning models and is amplified when deployed in the real-world, leading to challenges such as model drift. Recent advancements in the field of deep learning have led to the deployment of deployable automated healthcare diagnosis decision support systems at hospitals as well as tele-medicine through IoT devices. Research has been focused primarily on the development and improvement of these systems leaving a gap in the analysis of the fairness. The domain of FAccT ML (Fairness, Accountability, and Transparency) accounts for the analysis of these deployable machine learning systems. In this work, we present a framework for Bias Analysis in Healthcare Time-Series (BAHT) signals such as Electrocardiogram (ECG) and Electroencephalogram (EEG). BAHT provides a graphical interpretive analysis of bias in the training, testing datasets in terms of protected variables, and analysis of bias amplification by the trained model for time-series healthcare decision support systems. We thoroughly investigate three prominent time-series ECG and EEG healthcare datasets used for model training and research. We show the extensive presence of bias in the datasets leads to potentially biased or unfair machine learning models. Our experiments also demonstrate the amplification of identified bias with an observed maximum of 66.66%. We investigate the effect of model drift due to unanalyzed bias in datasets and algorithms. Bias mitigation though prudent, is a nascent area of research. We present experiments and analyze the most prevalently accepted bias mitigation strategies of under-sampling, oversampling, and the use of synthetic data for balancing the dataset through augmentation. It is important that healthcare models, datasets, and bias mitigation strategies should be properly analyzed for a fair unbiased delivery of service.
IABC: A Toolbox for Intelligent Analysis of Brain Connectivity
Authors: Du Yuhui , Kong Yanshu , He XingYu 
Published: October 2022

Abstract
Brain functional networks and connectivity have played an important role in exploring brain function for understanding the brain and disclosing the mechanisms of brain disorders. Independent component analysis (ICA) is one of the most widely applied data-driven methods to extract brain functional networks/connectivity. However, it is hard to guarantee the reliability of networks/connectivity due to the randomness of component order and the difficulty in selecting an optimal component number in ICA. To facilitate the analysis of brain functional networks and connectivity using ICA, we developed a MATLAB toolbox called Intelligent Analysis of Brain Connectivity (IABC). IABC incorporates our previously proposed group information guided independent component analysis (GIG-ICA), NeuroMark, and splitting-merging assisted reliable ICA (SMART ICA) methods, which can estimate reliable individual-subject brain functional features for further analysis. After the user arranges functional magnetic resonance imaging (fMRI) data files and clicks a few buttons to set parameters, IABC will automatically output brain functional networks, their related time courses, and functional network connectivity. All these neuroimaging measures are promising for providing clues in understanding brain function and differentiating brain disorders.
The incidence rate, serological characteristics and cytokines profile of occult HBV infection in clinic
Authors: Chen Shu-xiang , Liu Xin , Liu Hui , Lou Jin-li 
Published: October 2022

Abstract
Background
At present, the clinical research on OBI patients is still insufficient. Cytokines are small molecular proteins with immune regulation and immune effects, and are important indicators for judging immune function and inflammatory response. This study analyzed the prevalence rate of OBI patients in clinical HBV infection, the characteristics of HBV serological markers and serum levels of 48 cytokines/chemokines/growth factors.
Methods
A total of 76,428 HBV-infected patients with different related illnesses who were admitted to the Capital Medical University, Beijing Youan Hospital from May 2018 to May 2021 were Screened for OBI. Among them, 279 OBI patients were enrolled and 279 chronic HBV infection patients who were persistently positive for HBsAg and HBV DNA were matched. Analyze the basic medical records and laboratory data of patients with OBI, such as HBV serological markers, serum HBV DNA load, liver function index, etc. Serum samples from 30 OBI patients, 20 matched HBsAg positive patients and 16 healthy people were tested for 48 cytokines/chemokines/growth factors to determine the heterogeneity of serum cytokines, chemokines, and growth factors among the three groups.
Results
Of 76428 HBV-infected patients enrolled, 358 (0.47%) were defined as OBI patients.The prevalence of different disease categories varies. The main serological patterns of OBI patients were HBsAg negative, anti-HBs negative, HBeAg negative, anti-HBe positive and anti-HBc positive, accounting for 47.67%. 94.98% of OBI patients had HBV DNA load < 200IU/ml. The level of serum sCD40L, G-CSF, IFN-γ, MIP-1α, RANTES and Eotaxin in the OBI group was significantly higher than that in HBsAg positive group(P༜0.05), but the level of IL-4, IL-6, IL-8, IL-13, IL-17A, PDGF-AA, TGF-α and TNF-β in the OBI group was lower than that in the HBsAg positive group(P < 0.05). The levels of various serum cytokines, chemokines, and growth factors were also different between the OBI group and the healthy control group.
Conclusions
The levels of HBV DNA replication and transcription are low in most patients with OBI. A variety of serum cytokines, chemokines and growth factors may be involved in the inhibition of HBV DNA replication and transcription levels in OBI patients, and then promote HBsAg and viral clearance.
Aneurysmal Subarachnoid Hemorrhage After Cesarean Section Under Spinal Anesthesia: A Case Report
Authors: Eddin Adnan Saad , Shaikh Nissar 
Published: October 2022

Abstract
Background

The incidence of cerebral aneurysms in the pregnant population is similar to that of the non-pregnant population. Subarachnoid hemorrhage occurs in 5.8 per 100,000 deliveries among women between 15- and 44-year-old. Studies have found that the incidence of aneurysmal rupture is higher during the third trimester and lower during the first trimester. The risk of aneurysmal rupture and subarachnoid hemorrhage during general anesthesia or spinal anesthesia is unclear. We report a case of aneurysm rupture in the postpartum period.

Case

We describe a case of a 28-year-old woman, Gravida 3 Para 2, who went elective Cesarean delivery under spinal anesthesia at 39 weeks. She developed a headache, right-sided body weakness, and left-sided focal seizures postoperatively. Computed Tomography (CT) scan showed basal ganglia hemorrhage with intraventricular extension, subarachnoid hemorrhage, and midline shift to the right side. The World Federation of Neurological Surgeons (WFNS) grade was 4, and the modified Fischer grade was 4. A right frontal external ventricular drain was inserted, and the patient was admitted to the intensive care unit (ICU). Magnetic Resonance Angiography (MRA) and Magnetic Resonance Venography (MRV) showed a small left supraclinoid aneurysm, and the patient underwent balloon-assisted coiling. Seven days later, the Glasgow Coma Scale (GCS) dropped again, the Computed Tomography (CT) scan showed brain edema, and decompressive craniectomy was done. The patient subsequently improved, and later the external ventricular drain (EVD) was removed, and the patient was referred to a rehabilitation center. Cranioplasty was done three months later. Glasgow Outcome Scale (GOS-E) after six months was 6 (moderate disability).

Conclusion

The use of vasopressors and cerebrospinal fluid (CSF) leakage may increase the risk of cerebral aneurysm rupture after spinal anesthesia.
Predicting Rare Earth Elements Concentration in Coal Ashes with Multi-Task Neural Networks
Authors: Song Yu , Zhao Yifan , Ginella Alex , Gallagher Benjamin , Sant Gaurav , Bauchy Mathieu 
Published: October 2022

Abstract
The increasing demand for rare earth elements (REEs) makes them a scarce strategic resource for technical developments. In that regard, harvesting REEs from coal ashes—a waste byproduct from coal power plants—offers an alternative solution to conventional ore-based extraction. However, this approach is bottlenecked by our ability to screen coal ashes bearing large concentrations of REEs from feedstocks—since measuring the REE content in ashes is a time-consuming and costly task requiring advanced analytical tools. Here, we propose a machine learning approach to predict the REE contents based on the bulk composition of coal ashes (which is easily measurable under the current testing protocol). We introduce a multi-task neural network that simultaneously predicts the contents of different REEs and, importantly, exhibits notably improved accuracy than the single-task models. Further model analyses reveal key data patterns for screening coal ashes with high REE concentrations. Teaser: With machine learning, high-throughput screening of REE-bearing coal ashes can be fulfilled based on a simple measurement.
Development and Parameter Estimation of a Low Order Model for a Hyperelastic Cantilever Plate Exhibiting 2:1 Resonant Response
Authors: Jaber Nizar , Bilal Nasir , Bajaj A K 
Published: October 2022

Abstract
This work presents the results of an experimental investigation and a low-order model development for complex resonant dynamics of a cantilever macro-plate. The plate is fabricated from a material using 3D additive manufacturing technology and the material is assumed to be ‘hyperelastic’. The geometry of the plate with cut-outs is analytically optimized assuming a linear elastic material such that the second bending mode frequency 𝜔02 is approximately twice the first twisting mode frequency 𝜔11. Based on the observed ‘near’ 2:1 resonant response under harmonic excitation near 𝜔02, a low-order 2 DOF nonlinear dynamic model is developed to simulate the plate response. A unique and novel stepwise iterative approach is developed for the modal parameter extraction. The unknown modal parameters are extracted using Harmonic Balance solutions, constructing frequency response curves, and curve-fitting techniques. The results are then validated using long-time integration for the developed model. A good agreement is observed between the analytical and experimental results for the different excitation levels considered.