bluuebunny/crossref_metadata_2025_split huggingface dataset:
A quarterly survey of antibiotic prescribing in small animal and equine practices—Minnesota and North Dakota, 2020
Authors: Bollig Emma R. , Granick Jennifer L. , Webb Teckla L. , Ward Christie , Beaudoin Amanda L. 
Published: May 2022

AbstractAntimicrobials are critical for medicine, but the problem of antimicrobial resistance (AMR) threatens the effectiveness of these valuable drugs. In USA, there are no national‐ or state‐level programs or policies in place to track antibiotic use (AU) in dogs, cats, and horses, despite acknowledgement of this sector's importance to both the AMR problem and its solution. AU measurement is a key part of antibiotic stewardship and AMR prevention. This study aimed to fill existing gaps in the veterinary professions' knowledge of antibiotic prescribing in small animals and horses. To address this aim, medical record data were collected on a single day per quarter for 1 year from 19 Minnesota and North Dakota small animal and equine practices, totaling 1,899 veterinarian consults of dogs, cats, and horses. Overall, 25.8% of all canine, feline, and equine consults involved an antibiotic prescription. Third‐generation cephalosporins were the most commonly prescribed systemic antibiotic drug class, and the long‐acting injectable drug, cefovecin, was the most commonly prescribed antibiotic for cats (34.5%). Topical antibiotic preparations were prescribed frequently, especially in dogs (42.5% of canine prescriptions), though systemic antibiotics were often prescribed concurrently. Common general indications, based on problem or diagnosis recorded in the medical record, for antibiotics in all species combined were skin conditions (24.4%), otitis (22.1%), ophthalmic (9.4%), gastrointestinal (8.3%), respiratory (8.3%), and urinary tract (7.6%) diseases. While 44.2% of patients for which antibiotics were prescribed had cytology performed, only 3.9% had bacterial culture and susceptibility performed. In a pre‐study survey, veterinarians' recommendations for AU differed from actual prescribing, suggesting collection of AU data provides more accurate assessments of veterinary prescribing behaviour than surveys. This study shows feasibility of AU measurement in small animals and horses. The data collection tool and standard operating procedures described prove suitable for national AU data collection.
A Nonlinear Dynamic Model of Flywheel Energy Storage Systems Based on Alternative Concept of Back Propagation Neural Networks
Authors: He Haiting , Liu Yibing , Ba Liming 
Published: May 2022

Abstract
The flywheel energy storage system (FESS) is a closely coupled electric-magnetic-mechanical multiphysics system. It has complex nonlinear characteristics, which is difficult to be described in conventional models of the permanent magnet synchronous motor (PMSM) and active magnetic bearings (AMB). A novel nonlinear dynamic model is developed based on the alternative concept. Using back propagation (BP) neural network as a bridge, alternative mapping functions can be built from parametric calculation data of the finite element method (FEM) models. These functions are implemented in a system level simulation of the FESS. As a serial of linear equations, the alternative mapping function can precisely reproduce the electric-magnetic-mechanical characteristics in a satisfied speed and robust. Study of the cogging torque in the PMSM shows a good coincidence with the theory prediction. The current and displacement stiffness coefficients of the AMB are not constants as conventional linear models but change in different winding current and rotor positions. The influence parameters to the critical speed frequency and vibration amplitude are comprehensively studied, including the rotor mass, moment of inertial, eccentric distance, and the mass centroid offset. An operation boundary of the FESS is summarized to describe the feasible power load in different rotor rotation speed and PMSM winding current.
Characterization of the Finite Element Computational Fluid Dynamics Capabilities in the Multiphysics Object Oriented Simulation Environment
Authors: Weiss Abdullah G. , Zaidan Laith J. , Bani Ahmad Mohammad T. H. , Abdoelatef M. Gomaa , Peterson John W. , Lindsay Alexander D. , Kong Fande , Ahmed Karim , Kimber Mark L. 
Published: May 2022

Abstract
The multiphysics object-oriented simulation environment (moose) is a code package that couples a variety of physics modules, allowing for highly accessible multiphysics simulations. The physics modules include a finite element Navier–Stokes (N–S) module that is designed to solve laminar fluid dynamics problems. The usage of this module in multiple recent studies coupled with the growing interest in moose for usage in nonlight water reactor safety studies by the Nuclear Regulatory Commission (NRC) prompted the authors to investigate the computational fluid dynamics capabilities of moose. A two-dimensional laminar flow past a circular cylinder scenario is simulated in the moose framework to investigate the effectiveness of the N–S module. Simulations assumed an unsteady laminar flow with a Reynolds number of 200. To verify the results from moose, similar simulations were conducted using the well-utilized simulation of turbulent flow in arbitrary regions—computational continuum mechanics C++ (star-ccm+) finite volume code. Results from both codes are also compared to some results from literature. Velocity and pressure profiles of both transient simulations were compared. The numerical and input errors in moose are also visualized with contour plots to qualitatively understand the evolution of the errors across time and space. The comparisons between moose and star-ccm+ showed nearly perfect agreement between the codes for velocity and pressure, especially after the development of the vortex street in later time-steps. The force coefficients showed excellent agreement after the development of the vortex street, but demonstrated notable discrepancies prior to the vortex street development, which is likely due to how each code simulated the approach to the vortex street in earlier time-steps.
Numerical Study of Horizontally Bent Buried Steel Pipelines Subjected to Oblique Faulting
Authors: Nair Gautam S. , Dash Suresh R. , Mondal Goutam 
Published: May 2022

Abstract
Buried pipelines may be subjected to different seismic hazards along their path, among which faulting can severely affect their integrity by causing large strains in the pipeline confined to a local zone during an earthquake. Historically, the most catastrophic pipeline damages are the ones resulting from oblique faulting due to the severity of ground distortion and induction of compression in the pipeline. Moreover, in the areas of potential ground rupture, the presence of bends near the fault crossing may lead to large strains in the pipeline. Most design guidelines recommend laying the pipelines without field bends, elbows, and flanges near to fault zone. However, bends are sometimes inevitable in the construction of pipelines, and a situation may arise when the pipeline crosses the fault line at/near the bends. Past studies on the response of bent buried pipelines subjected to oblique faulting are very limited. Therefore, the present numerical investigation aims to examine the response of buried continuous steel pipelines with field bends crossing an oblique fault by performing an extensive parametric study. The results obtained are reviewed and presented in the paper. Suitable relationships in terms of modification factors over the response of a straight pipeline as a function of a few critical parameters are determined using regression analyses. It is concluded that providing bends to the pipeline can significantly affect its structural response when subjected to oblique faulting, especially when it is operating at its design internal pressure.
Finite Approximations and Similarity of Languages
Authors: Rovan Branislav , Varga András 
Published: May 2022

A new framework to measure distances (similarity) between formal languages and between grammars based on distances between words is introduced. It is based on approximating languages by their finite subsets and using monotone sequences of such finite approximations to define an infinite language in the limit. Distances between finite languages are defined and extended to distances between monotone sequences of finite languages leading to distances between infinite languages. The framework captures several distances studied in the literature. Context-free grammars with energy are introduced to enable finite approximations emphasizing “syntactically important” parts of words. Grammars with energy are also used to extend distances between monotone sequences of finite languages to distances between context-free grammars. A basic toolkit for monotone sequences of finite languages and distances between languages resp. grammars is provided. As part of this toolkit a non-symmetric version of distances is defined, providing additional characterisation of distances in general. Additional properties of distances between grammars are derived by restricting the“energy use” of grammars with energy. Some methods of estimating the distances are presented to be used in cases where the distance is not computable or difficult to compute.
Modeling and Simulation of Basketball Players’ Cardiopulmonary Endurance Sensor under Different Intensity Training
Authors: Dai Yang 
Published: May 2022

In order to explore the effects of HIT and MICT on aerobic endurance of college basketball players. By analyzing the difference between the cardiorespiratory endurance of basketball-specialized college students and the certain correlation between their athletic ability, it can better serve the practice of basketball training and provide certain theoretical guidance and theoretical guidance for the improvement of basketball-specialized college students’ athletic fitness, with a practical application value. 37 male college basketball players were randomly divided into the HIT group and MICT group. They were trained four times a week for 10 weeks. The special indexes of cardiopulmonary and basketball were measured during and before and after exercise. The experiment shows that the heart rate in HIT fast running stage is significantly higher than that in MICT, and the stimulation to cardiopulmonary function is stronger. HIT and MICT are difficult to improve athletes’ VO2max, but they can significantly improve the utilization rate of VO2max of VAT, and the effect of HIT is better than MICT. HIT and MICT have significant effects on improving the performance of

15

m
×
17
×
4

run, and the former has obvious advantages. However, in terms of improving the performance of 3/4 sprint, HIT improved significantly.
Effects of Different Anesthetics on Perioperative Organ Protection and Postoperative Cognitive Function in Patients Undergoing Cardiac Valve Replacement with Cardiopulmonary Bypass
Authors: Mei Shenglan , Jia Yifan , Zhou Jinjian , Zhan Ling , Liu Jin , Ming Hao , Liu Huagang 
Published: May 2022

In this paper, we have carried out an experimental study to investigate the effects of different anesthetics on perioperative organ protection and postoperative cognitive function in patients undergoing cardiac valve replacement with cardiopulmonary bypass. To realize this idea, a total of 90 patients with single valve replacement under general anesthesia and hypothermic cardiopulmonary bypass from January 2020 to October 2021 were enrolled. These patients were assigned into three groups, with 30 cases in each group by the digital table method. Group A was anesthetized with sufentanil combined with dexmedetomidine. Group B was anesthetized with sufentanil combined with etomidate. Group C was anesthetized with sufentanil combined with propofol. Perioperative organ protection and postoperative cognitive function of the three groups were compared. At T0 time point, there was no significant difference in blood WBC, blood N, and CRP among groups A, B, and C (

P

> 0.05); At T4 and T5 time points, the indexes of blood WBC, blood N, and CRP in groups A, B, and C were higher compared to the T0 time point. At T4 and T5 time points, the indexes of blood WBC, blood N, and CRP in group A were significantly lower compared to group B and group C. Before treatment, there was no significant difference in ALT and AST among groups A, B, and C (

P

> 0.05). After treatment, the indexes of ALT and AST in group A were significantly lower compared to group B and group C at T4 and T5 time points (

P

< 0.05). Before treatment, there was no significant difference in urea and creatinine among groups A, B, and C (

P

> 0.05). After treatment, the urea and creatinine indexes of group A were significantly lower compared to group B and group C at T4 and T5 time points (

P

< 0.05). Before treatment, there was no significant difference in CK-MB and CTnl among groups A, B, and C (

P

> 0.05); After treatment, the indexes of CK-MB and CTnl in group A were significantly lower compared to group B and group C at T4 and T5 time points (

P

< 0.05). Before treatment, there was no significant difference in MOCA scores among groups A, B, and C (

P

> 0.05). After treatment, the MOCA scores of group A were significantly higher compared to group B and group C at T5 and T6 time points (

P

< 0.05). Sufentanil combined with dexmedetomidine for heart valve replacement under cardiopulmonary bypass can reduce the dosage of anesthetics during the operation and have a certain perioperative protective effect on important organs such as the heart, lung, liver, and kidney, which may be related to reducing intraoperative hemodynamic fluctuations and inhibiting inflammatory stress response.
Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants
Authors: Pourdarbani Raziyeh , Sabzi Sajad , Rohban Mohammad H , García-Mateos Ginés , Molina-Martínez José Miguel , Paliwal Jitendra , Arribas Juan I 
Published: May 2022

Chemical fertilizers are widely applied in agriculture to achieve high yield, enhance produce quality and build resistance to diseases; in our case the plant being tomato ( Solanum lycopersicum L. var. Royal). However, the acidity, size and taste of tomato fruits could change with excess nitrogen (N) application. The present study aims at the early detection of nitrogen-rich tomato leaves using hyperspectral imaging techniques in the visible and near infrared (Vis-NIR) spectrum, in order to improve plant nutrition composition at an early growth stage. A 30% over-dose of nitrogen was applied to half of the tomato pots. Five leaves were randomly collected from each pot for 3 days (classes D0, D1, D2 and D3), and images were captured with a hyperspectral camera. A metaheuristic approach of artificial neural networks and the firefly algorithm (ANN-FA) was used to determine the most discriminative wavelengths. Afterwards, a combination of ANN and particle swarm optimization (ANN-PSO) was used to classify tomato leaves into the four classes. The training/classification process was repeated 200 times, and results indicated that the proposed approach was able to detect the excess of nitrogen even at the first day (D1), with a precision of 92.9%. Considering all the classes, the average correct classification rate was 92.6%, while the best execution achieved 95.5% accuracy. Thus, the method showed a high performance for practical uses.
The association between dietary inflammation scores and non-alcoholic fatty liver diseases in Iranian adults
Authors: Farhadnejad Hossein , Tehrani Asal Neshatbini , Jahromi Mitra Kazemi , Teymoori Farshad , Mokhtari Ebrahim , Salehi-Sahlabadi Ammar , Mirmiran Parvin 
Published: May 2022

Abstract
Background
Potential dietary inflammation can precursor chronic diseases such as hepatic disorders. We aimed to examine the association of empirical dietary inflammatory patterns (EDIP) and dietary inflammation scores (DIS) with the risk of nonalcoholic fatty liver diseases (NAFLD) in Iranian adults.

Methods
This case–control study was conducted on 225 newly diagnosed NAFLD cases and 450 controls aged 20–60 years. The individuals’ dietary data were collected using a validated food frequency questionnaire. The detection of NAFLD in subjects was done using the ultrasonography scan of the liver and confirmation of gastroenterologists. To calculate of EDIP score, the average daily intakes of each item (15 food items) were multiplied by the proposed weights, and then all the weighted values were summed. Also, to calculate the DIS score, each food item (18 food items) is multiplied by its specific weight to obtain the weighted values of each item. The weighted values were then standardized using the Z-score. Finally, the standardized weighted values of all the items were summed to get the overall DIS score for the individuals. Logistic regression models, adjusted for potential confounders, were used to estimate the odds ratios and 95% confidence interval (CI) of NAFLD across tertiles of EDIP and DIS.

Results
The mean (SD) age and BMI of the study population (53% male) were 38.1 (8.8) years and 26.8 (4.3) kg/m2, respectively. The median (IQR) of EDIP and DIS scores in individuals were 0.52 (0.34, 0.73), and 0.04 (− 0.55, 0.59), respectively. Based on the multivariable-adjusted model, after controlling for age, sex, physical activity, smoking, marital status, waist-to-hip ratio, and dietary energy intake, individuals in the second (OR 2.01, 95% CI 1.07–3.76) and third tertiles of DIS (OR 2.54, 95% CI 1.39–4.63) had a higher odds of NAFLD compared to the lowest tertile of DIS (Ptrend = 0.003). Also, in the final model, there is a significant direct association between EDIP score and odds of NAFLD [(OR T2 vs. T1 = 0.88, 95% CI 0.50–1.57) and (OR T3 vs. T1 = 1.82, 95% CI 1.02–3.23)], (Ptrend = 0.031).

Conclusion
Our results suggested that higher scores of EDIP and DIS, indicating the high inflammatory potential of dietary pattern, are associated with increased odds of NAFLD in Iranian adults.
Automatic lesion segmentation using atrous convolutional deep neural networks in dermoscopic skin cancer images
Authors: Kaur Ranpreet , GholamHosseini Hamid , Sinha Roopak , Lindén Maria 
Published: May 2022

Abstract
Background
Melanoma is the most dangerous and aggressive form among skin cancers, exhibiting a high mortality rate worldwide. Biopsy and histopathological analysis are standard procedures for skin cancer detection and prevention in clinical settings. A significant step in the diagnosis process is the deep understanding of the patterns, size, color, and structure of lesions based on images obtained through dermatoscopes for the infected area. However, the manual segmentation of the lesion region is time-consuming because the lesion evolves and changes its shape over time, making its prediction challenging. Moreover, it is challenging to predict melanoma at the initial stage as it closely resembles other skin cancer types that are not malignant as melanoma; thus, automatic segmentation techniques are required to design a computer-aided system for accurate and timely detection.

Methods
As deep learning approaches have gained significant attention in recent years due to their remarkable performance, therefore, in this work, we proposed a novel design of a convolutional neural network (CNN) framework based on atrous convolutions for automatic lesion segmentation. This architecture is built based on the concept of atrous/dilated convolutions which are effective for semantic segmentation. A deep neural network is designed from scratch employing several building blocks consisting of convolutional, batch normalization, leakyReLU layer, and fine-tuned hyperparameters contributing altogether towards higher performance.

Conclusion
The network was tested on three benchmark datasets provided by International Skin Imaging Collaboration (ISIC), i.e., ISIC 2016, ISIC 2017, and ISIC 2018. The experimental results showed that the proposed network achieved an average Jaccard index of 90.4% on ISIC 2016, 81.8% on ISIC 2017, and 89.1% on ISIC 2018 datasets, respectively which is recorded as higher than the top three winners of the ISIC challenge and other state-of-the-art methods. Also, the model successfully extracts lesions from the whole image in one pass in less time, requiring no pre-processing step. The conclusions yielded that network is accurate in performing lesion segmentation on adopted datasets.
Evaluation of C-shaped canals in maxillary molars in a Chinese population using CBCT
Authors: Qian Yuyan , Li Yamei , Song Jukun , Zhang Ping , Chen Zhu 
Published: May 2022

Abstract
Introduction
The aim of this study was to evaluate the prevalence and characteristics of C-shaped root canals in maxillary first (MFMs) and second (MSMs) molars in a Southwestern Chinese population using cone-beam computed tomographic (CBCT).

Methods
CBCT images of MFMs (n = 1488) and MSMs (n = 1547) from 1508 subjects enrolled in Guiyang Hospital of Stomatology between July 2018 to February 2021 were evaluated for the incidence and types of C-shaped root canals. Differences by age, sex, left or right side, and bilateral symmetry were also evaluated.

Results
C-shaped root canals were present in 2.93% MFMs and MSMs (n = 3035) in the Southwestern Chinese population. A significant higher incidence was observed in the MSMs (5.24%) than in the MFMs (0.54%). Increased incidences were noted in teeth with fused root. Two major types and 5 subtypes of C-shaped canal system of maxillary molars were defined, and the most common type of C-shaped canals is fusion of mesial-buccal (MB) and distal-buccal (DB) canals (Type I subtype C). No significant gender and age differences were noted in the prevalence of C-shaped root canals in this population, and no significant difference was seen in its incidence in the left or right MFMs and MSMs. The bilateral occurrence was observed in 1.27% of the patients.

Conclusion
C-shaped root canals are more frequently present in MSMs than in MFMs in the Southwestern Chinese population, with Type I subtype C (MB-DB canal fusion) as the most common subtype and low incidence of bilateral symmetry.
Grading of IDH-mutant astrocytoma using diffusion, susceptibility and perfusion-weighted imaging
Authors: Yang Xiefeng , Xing Zhen , She Dejun , Lin Yu , Zhang Hua , Su Yan , Cao Dairong 
Published: May 2022

Abstract
Background
The accurate grading of IDH-mutant astrocytoma is essential to make therapeutic strategies and assess the prognosis of patients. The purpose of this study was to investigate the usefulness of DWI, SWI and DSC-PWI in grading IDH-mutant astrocytoma.

Methods
One hundred and seven patients with IDH-mutant astrocytoma who underwent DWI, SWI and DSC-PWI were retrospectively reviewed. Minimum apparent diffusion coefficient (ADCmin), intratumoral susceptibility signal intensity(ITSS) and maximum relative cerebral blood volume (rCBVmax) values were assessed. ADCmin, ITSS and rCBVmax values were compared between grade 2 vs. grade 3, grade 3 vs. grade 4 and grade 2 + 3 vs. grade 4 tumors. Logistic regression, tenfold cross-validation,and receiver operating characteristic (ROC) curve analyses were used to assess their diagnostic performances.

Results
Grade 4 IDH-mutant astrocytomas showed significantly lower ADCmin and higher rCBVmax as compared to grade 3 tumors (adjusted P < 0.001). IDH-mutant grade 3 astrocytomas showed significantly lower ITSS levels as compared with grade 4 tumors (adjusted P < 0.001). ITSS levels between IDH-mutant grade 2 and grade 3 astrocytomas were significantly different (adjusted P = 0.002). Combined the ADCmin, ITSS and rCBVmax resulted in the highest AUC for differentiation grade 2 and grade 3 tumors from grade 4 tumors.

Conclusion
ADCmin, rCBVmax and ITSS can be used for grading the IDH-mutant astrocytomas. The combination of ADCmin, ITSS and rCBVmax could improve the diagnostic performance in grading of IDH-mutant astrocytoma.