bluuebunny/crossref_metadata_2025_split huggingface dataset:
Norwegian Population Norms for the EQ-5D-5L: Results From a General Population Survey
Authors: Garratt Andrew Malcolm , Hansen Tonya Moen , Augestad Liv Ariane , Rand Kim , Stavem Knut 
Published: March 2021

Abstract
Purpose: To provide the first Norwegian EQ-5D-5L and EQ VAS population norms for the adult general population. Methods: Postal survey of a random sample of 12,790 Norwegians identified through the National Registry of the Norwegian Tax Administration. Norms are shown for the five EQ-5D-5L dimensions, EQ-5D index and EQ VAS scores for seven age categories, males, females and education level. Results: There were 3,200 (25.9%) respondents to 12,263 correctly addressed questionnaires. The EQ-5D-5L dimensions, EQ VAS and background questions were completed by 3,120 (24.6%) respondents. The mean age (SD) was 50.9 (21.7); range 18 to 97 years. The youngest age group of 18-29 years and oldest of 80 years and over had the highest (n=691) and lowest (n=239) number of respondents respectively. Compared to the general population, the respondents comprised a greater number of females, younger and older ages, and had a higher education level. 32% of respondents reported no health problems on the EQ-5D-5L. From the youngest to oldest age groups, there was a general decline in health as assessed by the EQ-5D-5L. The exception was for anxiety/depression, where the youngest age groups had the poorest health. Apart from self-care, women reported poorer health than men, as assessed by the EQ-5D-5L; EQ VAS scores were similar for men and women. Higher levels of health (EQ-5D index, EQ VAS scores) were found with increasing levels of education. Conclusion: The population norms will improve interpretation of EQ-5D-5L and EQ VAS scores in Norwegian applications including clinical practice, clinical and health services research, and national quality registers where EQ-5D-5L is the most widely used patient-reported instrument.
Spatial Prediction of Groundwater Potentiality Mapping Using Machine Learning Algorithms
Authors: Saha Sunil , Gayen Amiya , Mukherjee Kaustuv , Pourghasemi Hamid Reza , Santosh M. 
Published: March 2021

Abstract
Machine learning techniques offer powerful tools for the assessment and management of groundwater resources. Here, we evaluated the groundwater potential maps (GWPMs) in Md. Bazar Block of Birbhum District, India using four GIS-based machine-learning algorithms (MLA) such as predictive neural network (PNN), decision tree (DT), Naïve Bayes classifier (NBC), and random forest (RF). We used a database of 85 dug wells and one piezometer location identified using extensive field study, and employed 12 influencing factors (elevation, slope, drainage density (DD), topographical wetness index, geomorphology, lineament density, rainfall, geology, pond density, land use/land cover (LULC), geology, and soil texture) for evaluation through GIS. The 85 dug wells and 1 piezometer locations were sub-divided into two classes: 70:30 for training and model validation. The DT, RF, PNN, and NBC MLAs were implemented to analyse the relationship between the dug well locations and groundwater influencing factors to generate GWPMs. The results predict excellent groundwater potential areas (GPA) DT RF of 17.38%, 14.69%, 20.43%, and 13.97% of the study area, respectively. The prediction accuracy of each GWPM was determined using a receiver operating characteristic (ROC) curve. Using the 30% data sets (validation data), accuracies of 80.1%, 78.30%, 75.20%, and 69.2% were obtained for the PNN, RF, DT, and NBC models, respectively. The ROC values show that the four implemented models provide satisfactory and suitable results for GWP mapping in this region. In addition, the well-known mean decrease Gini (MDG) from the RF MLA was implemented to determine the relative importance of the variables for groundwater potentiality assessment. The MDG revealed that drainage density, lineament density, geomorphology, pond density, elevation, and stream junction frequency were the most useful determinants of GWPM. Our approach to delineate the GWPM can aid in the effective planning and management of groundwater resources in this region.
Randomized Double Blind Clinical Trial Evaluating the Ellagic Acid Effects on Insulin Resistance, Oxidative Stress and Sex Hormones Levels in Women With Polycystic Ovarian Syndrome
Authors: Kazemi Mahnaz , Lalooha Fatemeh , Nooshabadi Mohammadreza Rashidi , Dashti Fariba , Kavianpour Maria , Haghighian Hossein Khadem 
Published: March 2021

Abstract
Objective: The design of this study was due to the report of the antioxidant properties of Ellagic acid (EA) for its evaluation on the Insulin resistance (IR), oxidative stress and sex hormones levels in women with polycystic ovarian syndrome (PCOS). Methods: In this randomized, double-blind, placebo-controlled clinical trial, 60 patients were recruited. Patients were randomly allocated consumed a capsule containing 200 mg of EA per day (n = 30) or placebo (n = 30) for 8 weeks. The fasting blood sugar (FBS), insulin, IR, total cholesterol (TC), triglycerides (TG), low density lipoprotein (LDL), high density lipoprotein (HDL), total antioxidant capacity (TAC), Malondialdehyde (MDA), C-reactive protein (CRP), Tumor necrosis factor-alpha (TNF-α), sex hormones and anti-mullerian hormone (AMH) were measured at the beginning and end of the study. Result: At the end of the study, the mean of FBS, insulin, IR, TC, TG, LDL, MDA, CRP, TNF-α, total testosterone, prolactin and AMH were significantly decreased in the intervention group compared to the placebo group (P<0.05). Also, there was a significant increase in the mean of TAC after supplementation with EA (P<0.05). At the end of the study, no significant changes were observed in the mean of anthropometric factors, physical activity and food intake (P>0.05). Conclusion: EA supplementation can be helpful as a diet supplement in women with PCOS through improvement in insulin resistance. This supplement may be used to reduce disorders in women, including infertility.Trial Registration: This study was retrospectively (07-07-2019) registered in the Iranian website (www.irct.ir) for registration of clinical trials (IRCT20141025019669N12).
Characterization and Genome Sequence of a Genetically Unique Escherichia Bacteriophage vB_EcoM_IME392
Authors: Hu Yunjia , Tong Shanwei , Li Ping , An Xiaoping , Song Lihua , Fan Huahao , Tong Yigang 
Published: March 2021

Abstract
In this study, a novel Escherichia coli-specific bacteriophage vB_EcoM_IME392 was isolated from chicken farm sewage in Qingdao, China. The genome of IME392 sequenced by Next Generation Sequencing is found to contain 116,460 base pairs in length with a G+C content of 45.4% (deposited in GenBank under the accession MH719082). BLASTN results reveal that only 2% of the genome sequence of IME392 shows homology to known phage sequences in GenBank, which indicates IME392 is a very novel bacteriophage. Transmission electron microscopy showed that IME392 belongs to the family Myoviridae. The host range, multiplicity of infection and one-step growth curve was also determined.
Assessment of the Correlation of Commonly used Laboratory Tests with Clinical Activity, Renal Involvement and Treatment of Systemic Small-vessel Vasculitis with the Presence of ANCA Antibodies.&nbsp;
Authors: Mosakowska Magdalena , Brodowska-Kania Dorota , Szamotulska Katarzyna , Rymarz Aleksandra , Niemczyk Stanisław 
Published: March 2021

Abstract
The aim of the study was to assess the correlation of commonly used laboratory tests with clinical activity, degree of kidney involvement and treatment of systemic small-vessel vasculitis with the presence of ANCA antibodies.Methods.The study included 28 patients with active AAV (BVAS ≥ 3). The following tests were performed: MPO-ANCA, PR3-ANCA, peripheral blood count, ESR, CRP, procalcitonin, creatinine, GFR, urea, albumin, fibrinogen, d-dimer, components of the C3 and C4 complement systems, urinalysis with sediment evaluation and diurnal proteinuria. The assessments were conducted twice: at study entry (A0) and after 6 months (A6) (BVAS = 0).ResultsAt the time of inclusion in the study, the mean creatinine concentration was 3.39 mg/dl (GFR 33.17 ml/min/1.73m²), after achieving remission in 11 patients (39.3%) GFR remained below 30 ml/min/1.73m² , 4 patients (14.3%) continued renal replacement therapy, and 3 patients (10.7%) with advanced renal failure died. Microhematuria occurred in 80.9% of the studied population, withdrew in most patients, strongly correlated with renal involvement p<0.001 and was not related to disease severity p=0.147. CRP, ESR, fibrinogen, d-dimer, albumin and hemoglobin in the peripheral blood showed a strong correlation with the clinical activity of AAV and well identified severe patients. High procalcitonin concentrations correlated with a severe form of the disease, pulmonary involvement with respiratory failure and alveolar hemorrhage (mean 3.41 ng/ml, median 0.91 ng/ml, SD 7.62, p = 0.000), and were associated with the occurrence of infectious complications and the need to administer antibiotic therapy. ANCA antibodies were useful in the evaluation of patients with AAV, the amount of antibodies did not correlate with the severity of vasculitis (p=0.685) and the results in many patients did not match the expected assumptions. ConclusionsCRP, ESR, fibrinogen, d-dimers, albumin and hemoglobin in the peripheral blood correlate well with the activity of vasculitis and identify severe patients. The resolution of microhematuria suggests remission of the disease in the renal area. Procalcitonin may be slightly increased in patients with active AAV without infection, high concentrations are strongly associated with infectious complications. ANCA antibodies should always be interpreted in the context of the observed clinical symptoms.
Immersion Sn Finish Processed on Ag Surface via Galvanic Reduction
Authors: Wu Chen Yu , Lin Yi Xuan , Wang Jyun Yang , Lee Chia Hung , Chiu Chung Yu , Yeh Ching Yu , Huang Bo Rong , Fu Kuan Lin , Chang Jui Sheng , Liu ChengYi 
Published: March 2021

Abstract
Typically, Sn cannot be finished on Ni and Ag surfaces via the immersion process. In this work, through galvanic reaction, immersion Sn finish was processed on an immersion Ag finish coexisting with a Ni surface. Herein, the detailed mechanism of the reduction of Sn2+ ions on the immersion Ag surface through galvanic reaction is reported. Through transmission electron microscopy and X-ray diffraction analysis, the uncommon Ag4Sn phase, instead of the common Ag3Sn phase, was confirmed to form during the Sn immersion of the Ag immersion layer. The Ag4Sn phase was found to form between the Ag grains in the immersion Sn layer. The mixed Ag/Ag4Sn structure in the immersion Sn layer can be explained by the galvanic reaction. The preferred formation of the Ag4Sn during the Sn immersion of the Ag immersion layer is discussed from the viewpoint of thermodynamics. The changes in the Gibbs free energy of the formation of the Ag3Sn and Ag4Sn phases were calculated as −3.67 and −8.89 kJ/mol, respectively. This confirms that the Ag4Sn phase is the favorable phase formed in the immersion Sn over the immersion Ag layer.
Frequency and Distribution of Biopsied Non-Dental Plaque-Induced Gingival Diseases in a Chinese Population According to the Classification of Gingival Health and Gingival Disease/Conditions
Authors: Li Xiaotian , Zhang Jianyun , Zhang Heyu , Li Tiejun 
Published: March 2021

Abstract
Background: While inflammatory diseases such as gingivitis and periodontitis induced by dental plaque biofilms constitute the majority of gingival lesions, gingiva can also be affected by a variety of diseases that show etiologies different from bacterial biofilms. The aim of this study was to retrospectively analyze the frequency and distribution of non-dental plaque-induced gingival diseases (NDPIGDs) in a Chinese population. Methods: A total of 6859 samples of biopsied gingival diseases during the period of 2000-2019 were obtained from the Department of Pathology, Peking University Hospital of Stomatology. Lesions were categorized by histopathological diagnosis, pathological nature and the new classification of gingival health and gingival diseases/conditions. Demographic information, such as gender, location, and age, were also analyzed. Results: Among 6859 biopsied NDPIGD samples, the five most frequent diagnoses included oral squamous cell carcinoma (OSCC, n=2094), fibrous hyperplasia (n=2026), pyogenic granuloma (n=478), epithelial dysplasia (n=477), and epithelial hyperplasia/hyperkeratosis (n=436). All types could be grouped into nine categories according to their pathological characteristics. The most frequently common biopsied NDPIGDs category was “hyperplastic lesions” (n=2648, 38.61%), followed by “malignant neoplasms” (n=2275, 33.17%). The most common diagnosis types in each category were fibrous hyperplasia and OSCC. Of all NDPIGDs, most lesions could be categorized into the new classification of gingival health and gingival diseases/conditions; only 7.07% did not fit the current classification system. Conclusions: The present study represents the first report on the frequency and distribution of biopsied NDPIGDs in a Chinese population. Unlike previous studies, the most prevalent categories were “hyperplastic lesions” and “malignant neoplasms”. The proportion of “malignant neoplasms” and “oral potentially malignant disorders” was remarkably higher than in previous research. Nevertheless, the study provided epidemiological information for many NDPIGDs, which could be useful for future health policies as well as screening programs.
The Self-organizing Vector of Atom-pairs Proportions: Use to Develop Models for Melting Points
Authors: Toropova Alla P. , Toropov Andrey A. , Benfenati Emilio 
Published: March 2021

Abstract
Atom-pairs proportions are the transparent quality of a molecule: if a molecule has two atoms of oxygen and three atoms of nitrogen, the atom-pair atom1-atom2 can be expressed as a code 'atom1-atom2-n1-n2', indicating the different atoms and their numbers. These codes for a group of atoms (nitrogen, oxygen, sulfur, phosphorus, fluorine, chlorine, bromine, as well as, double and triple covalent bonds) are applied to build up the so-called optimal molecular descriptor calculated with special coefficients named correlation weights of corresponding pairs. The numerical data on the correlation weights are calculated by the Monte Carlo technique using the CORAL software (http://www.insilico.eu/coral). The one-variable model for melting points of 8653 various organic compounds is characterized by the following statistical quality: n=6483, r2=0.6452; RMSE=61.9’C; n=2170, r2=0.7941, RMSE=39.2’C.
Overview of Agaricus Subrufescens Strains used in the Last 15 Years in Brazil and other Countries and Current Potential Materials for the Future
Authors: Zied Diego Cunha , Junior Wagner G. Vieira , Soares Douglas M. M. , Stevani Cassius V. , Dias Eustáquio S. , Iossi Matheus R. , Pardo-Giménez Arturo 
Published: March 2021

Abstract
The mushroom Agaricus subrufescens has been synonymous with Agaricus blazei and Agaricus brasiliensis during the last decades and there has been much discussion with regards to the origin, distribution, and nomenclature of this mushroom. Therefore, we conducted a genetic and morphological characterization of the mycelium and mushroom of four commercial strains currently cultivated in Brazil (ABL CS7, ABL 18/01, ABL 98/11, and ABL 16/01) together with an assessment of their agronomic behavior and compared these results with those of other strains used during the last 15 years. All the A. subrufescens strains characterized here are phylogenetically related to the Americas/Europe specimens, bearing an internal transcribed spacer region of type A (ABL 16/01) or both types A and B (ABL 18/01, ABL 98/11, and ABL CS7). We did not find any correlation between the morphological characteristics of the mycelial colonies and the agronomic behavior of the strains. Strains ABL 98/11 and ABL 16/01 produced the best yields and morphological characteristics for the mushrooms, indicating their high weight, which enhances the commercialization of the mushroom and justifies their longstanding commercial use over the last 15 years.
Prevalence and Predictive Factors of Transient and Permanent Congenital Hypothyroidism in Fars Province, Iran
Authors: Habib Ashkan , Shojazadeh Alireza , Molayemat Mohadeseh , Habib Asadollah , Jeddi Marjan , Arabsolghar Rita , Nahas Mitra , Rahimi Nazila , Ardekani Fariba Moradi 
Published: March 2021

Abstract
Introduction: There is no data on the number as well as the prevalence of congenital hypothyroidism (CH) in the Fars province. Hence, we designed this study to analyze the latest data and the possible predictive factors on transient and permanent CH in this province.Method: This cross sectional study is based on the Fars province screening data from 2013 till 2016. A total of 294,214 newborns were screened with 938 confirmed cases of CH, which were included in this study. After recall and completion of the missing data, follow-up data for 642 CH cases with thyroid stimulating hormone (TSH) concentrations and levothyroxine doses for ten outpatient visits and final transient vs. permanent CH diagnosis were included.Results: The incidence rate was 1:313.66, and out of the 642 CH cases, 66.04% had permanent CH, while 33.96% had transient CH. TSH level trend during the outpatient visits were not statistically different between the two groups (P=0.312). A cutoff point of >2.25 levothyroxine µg/kg (sensitivity: 76.11%, specificity: 58.52%) at the third year and a TSH concentration of >43.35 mIU/L at the venous sampling (initial TSH) (sensitivity: 31.66%, specificity: 90.32%) were the predictive factors for permanent CH.Conclusion: Fars province has one of the highest incidence rate of CH in Iran. Levothyroxine dose at the 3rd year and the 1st venous TSH sample are the predictive factors for permanent CH in the Iranian population; however, TSH concentrations during follow ups are unreliable predictors.
Polyacrylonitrile/CoCl2 Nanofibers Based Humidity Sensor for Human Breath and Ambient Humidity Monitoring
Authors: Li Xiaoqiang , Zengyuan Pang , Mengjuan Li , Yang Jin 
Published: March 2021

Abstract
A novel humidity sensor was constructed using the hybrid nanofibers of polyacrylonitrile/CoCl2 (PAN/CoCl2), which were fabricated by electrospinning. Scanning electron microscopy (SEM) image demonstrated that the diameter of PAN/CoCl2 nanofibers ranged from 100 - 500 nm. Energy-dispersive X-ray spectrometer (EDS) analysis confirmed that Co and Cl elements were homogeneously dispersed on the PAN nanofibers. CoCl2 on the surface of PAN nanofibers play a dual function in humidity sensing performances. First, CoCl2 serves as an indicator, which can change the color of nanofibers from blue to white-pink as the relative humidity changed from 11 to 98 %, to realize the colorimetric sensing. Second, CoCl2 could remarkably improve the electric sensing performance. As a result, the PAN/CoCl2 nanofibers offered much enhanced response currents compared to the pristine PAN nanofibers, as the humidity changed from RH 11 to 98 %. In addition, the PAN/CoCl2 nanofibers based humidity sensor was employed to monitor human breath and the ambient humidity, which demonstrated the excellent sensitivity of this humidity sensor. Therefore, we believe that the highly sensitive and simply designed PAN/CoCl2 humidity sensor is a promising candidate for various applications in the field of humidity monitoring.
Radar Signals Modulation Recognition Based on Bispectrum Feature Processing
Authors: mi xinping , Chen xihong , Cao yufei , liu qiang , song xincheng 
Published: March 2021

Abstract
Modulation recognition of radar signals is an important part of modern electronic intelligence reconnaissance and electronic support systems. In this paper, to solve the problem of low recognition accuracy and low noise resistance of radar signals under low signal-to-noise ratio(SNR), a recognition method based on variational mode decomposition(VMD) and bispectrum feature extraction is proposed. Based on the feature that bispectrum can suppress Gaussian noise, the feasibility of signals modulation recognition under low SNR is analyzed and the noise item is introduced. Due to the interference of noise item, the noise suppression effect of bispectrum is worse under 0dB. An improved VMD algorithm based on artificial bee colony(ABC) algorithm optimization and envelope entropy evaluation is proposed to preprocess the signal to improve the SNR. Finally, we designed a convolution neural network(CNN) classifier to recognize signals of different modulation types. The simulation results show that this method has better noise resistance than traditional methods, and can effectively identify different types of signals under low SNR.
Polarization Domain Dynamics of Barium Titanate Ultrathin Films Using Piezoresponse Force Microscopy.
Authors: salamo gregory , Zamani-Alavijeh Mohammad , Morgan Timothy , Kuchuk Andrian 
Published: March 2021

Abstract
Piezoresponse force microscopy is used to study the velocity of the polarization domain wall in ultrathin ferroelectric barium titanate films grown on strontium titanate substrates by molecular beam epitaxy. The electric field due to the cone of the atomic force microscope tip is proposed as the dominant electric field of the tip in thin films for domain expansion at lateral distances greater than about one tip diameter away from the tip. The velocity of the domain wall under the applied electric field by the tip in barium titanate for thin films (less than 40 nm) followed an expanding process given by Merz’s law. The material constants in a fit of the data to Merz’s law for very thin films are reported as about 4.2 KV/cm for activation field, Ea, and 0.05 nm/s for limiting velocity, v∞. These material constants showed a dependence on the level of strain in the films but no fundamental dependence on thickness.
Cauchy Particle Swarm Optimization (CPSO) based Migrations of tasks in a virtual machine
Authors: R Vadivel , T SUDALAIMUTHU 
Published: March 2021

Abstract
Cloud computing technology helps to resolve the problem in storage management by providing virtual resources to the end users. But, the overloading of virtual machines results in degradation of performances as well as it increases in the energy consumption of the virtual machines. Several techniques were used to determine the workloads of the cloud and then apply the migration algorithm for efficient utilization of resources. But, the process depends on the past outputs and only few step ahead predictions. Most of the techniques allocate the resources based on all the attributes. This results in higher processing time for the allocation. Hence, in this, an attribute based resource allocation is proposed to allocate and utilize the resources effectively based on the user demands. The modified Principal component analysis and relief is used for the attribute selection. Then, the selected attribute is processed with the hybrid Cauchy particle swarm algorithm for the allocation of resources. The proposed method is tested google cluster dataset and its performance is evaluated in terms of migration count and power consumption. The proposed method performance is compared with the automated migration technique (ALM) and forecast based migration technique (CF-LA). The proposed method outperforms both the existing technique by reducing the power consumption and the migration count between the virtual machines. Hence, the proposed MPCA and relief basedCPSO is best for allocating the resources dynamically in the cloud.