bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of low vs. moderate dose of recreational football on cardiovascular risk factors
Authors: Modena Roberto , Impellizzeri Franco M. , Fornasiero Alessandro , Schena Federico 
Published: June 2022

ABSTRACTThis study aimed to compare the effectiveness of recreational football performed once (LOW) vs. twice (MOD) a week on cardiovascular risk factors in healthy, sedentary men. Body composition, resting blood pressure, blood lipid profile and maximal oxygen consumption (VO2max) were measured at baseline, after a 12‐week control and training period, using an interrupted time‐series study (study 1, n = 18: n = 8, LOW and n = 10, MOD) nested in a randomized parallel trial (study 2, n = 34: n = 18 LOW and n = 16 MOD). After the intervention in study 1, LDL‐cholesterol (−12.3 mg·dLˉ1 [−22.7 to −2.0]) and VO2max (4.5 ml·kgˉ1·minˉ1 [1.2–7.8] ) changed in LOW whereas differences were found in weight (−2.1 kg [−3.7 to −0.4]), BMI (−0.7 kg·m−2 [−1.2 to −0.1]), total cholesterol (−22.2 mg·dLˉ1 [−36.0 to −8.4]), no‐HDL‐cholesterol (−17.5 mg·dLˉ1 [−30.5 to −4.5]), LDL‐cholesterol (−14.9 mg·dLˉ1 [−23.6 to −6.2]) and VO2max (5.7 ml·kgˉ1·minˉ1 [2.8–8.6]) in MOD. Study 2 showed no evidence of differences between groups. Our results therefore suggest positive health effects of recreational football even when performed at low frequency as it can happen in real context.Highlights
Moderate and high amount of recreational football practice (i.e. 2 or 3 h a week) have been shown to be effective to improve health‐related factors in both healthy and unhealthy people.
Scarce data are present regarding the effect of a low frequency of recreational football practice (i.e. 1 h a week) that is often usual in a real context.
Our results showed the practice of recreational football, once a week, is effective for improving some cardiovascular risk factors (maximal oxygen consumption and LDL‐cholesterol) in sedentary, healthy middle‐aged men.
Moreover, practising recreational football once or twice a week seems to lead to similar positive health adaptations.
Mapping the scientific knowledge of glomalin-related soil protein with implications for carbon sequestration
Authors: Liu Shanle , Wang Qizhi , Qian Lu , Zhang Binghuang , Chen Xiangwen , Hong Hualong , Wu Shengjie , Liu Jingchun , Yan Chongling , Lu Haoliang 
Published: June 2022

ABSTRACT
Arbuscular mycorrhizal fungi (AMF) derived refractory organic matter, mainly in glomalin-related soil protein (GRSP), stores globally significant amounts of carbon, attracting wide attention in response to climatic change. However, there is no synthesis review has been done so far to
reveal global research progresses on GRSP, especially its ecological role for
climate mitigation. Here,we conducted a bibliometric analysis of the papers on GRSP research from 1998 to 2021, based on the Web of Science (WOS) Core Collection.We collected a total of 634 papers and analyzed the characteristics of publication outputs in various countries and institutions.
In addition, keywords analysis was conducted to reveal the main research
directions and hot trends in the field of GRSP. We confirmed that 1) the number of papers published per year has gradually increased since 2010, and increased sharply in 2019; 2) the United States was the earliest country to conduct GRSP research, while China
currently has the largest number of publications; 3) relevant studies focus on the role from AMF and GRSP in soil health and plant health; 4) the contribution of GRSP to soil carbon and its ecological function in mitigating
climate change are the hotspot of research. The benefits of GRSP have become a consensus, however, the nature of glomalin and the mechanisms of GRSP-associated benefits still need to explore. As an important soil recalcitrant organic carbon, further studies are need to elucidate the land-ocean biogeochemical processes of GRSP and its contribution to global blue carbon.
Selection of best feature reduction method for module-based software defect prediction
Authors: Singh Shiva , Haider Tanwir Uddin 
Published: June 2022

Abstract
In the Software development life cycle (SDLC) the prediction of software defects is one of the crucial parts. Recent years have witnessed various studies for predicting software defects, and most of them involve machine learning techniques. Before predicting the defects some pre-processing steps are required, such as feature selection, outlier removal, and feature scaling as it helps in improving accuracy and reducing the execution time(ET). The present investigation focuses on feature selection which is a dimensionality reduction technique. Further, we have also proposed a framework on module-based software defect prediction using feature selection techniques. These techniques are divided into three categories i.e filter methods, wrapper methods, and hybrid methods that combine two wrapper methods i.e. Sequential Forward Selection and Sequential Backward Selection that we have developed. Finally, classification has been performed by KNN, Logistic Regression, Decision Tree, and SVM using the above-mentioned feature selection techniques on eight publicly available Promise datasets and compared them with the existing state-of-the-art(SOTA) methods. The result shows that the hybrid method performs better in terms of accuracy by 4.2%, 3.9%, 3.8% on datasets pc4, jm1, kc2 respectively when applied along with machine learning, as compared to filter and wrapper methods.
Cohort study on recognition of plant species using Deep Learning methods
Authors: Barhate Deepti , Pathak Sunil , Dubey Ashutosh Kumar , Nemade Varsha 
Published: June 2022

Abstract
Plants play a vital role in each living organism’s life since it maintains the environment and provides us valuable medicine, food, fragrance etc. Knowledge of species is important for the protection of biodiversity. The identification of species of plants by a manual method by botanist is tedious work besides the complex botanical terms used by an expert are annoying for a non-expert. This may lead to the obstruction for learners interested in procuring knowledge of plant species. By applying the classification of species one can also capture crops from weed for automated weedicide. Species of plant recognition are a matter of huge significance in various areas of farming, maintenance of environmental, natural, manufactured goods and medicine invention, and other related areas. Leaf color leaves contour, shape, leaf size, flowers, texture, margins, etc. are the features of plants which can be used for classification, and however, extraction of traits from selected features is the most important status in the classification. In this paper, a review-based study is done which is based on approaches such as Machine learning algorithm, Deep Learning, Convolutional Neural Networks (CNN), etc. are compared. Various classification methods like K-nearest neighbor (KNN), Naïve baise(NB), Random forest are also studied. Mostly used datasets such as Flavia, swedish, Leafsnap, ICL with their species wise features were studied.
“Comparison of machine learning and deep learning classifier to detect sleep apnea using single-channel ECG and HRV: A Systematic Literature Review”
Authors: Singh Nivedita , Talwekar R H 
Published: June 2022

Abstract
sleep apnea (SA) detection has popularly been performed using the gold standard polysomnography (PSG). This method is complex, time-consuming, and essentially requires a skilled person to record multi-channel sleep data. PSG data acquisition to detect OSA requires a dedicated sleep laboratory and hence it is expensive. The main aim of this paper is to select the most suitable modality single-channel electrocardiogram (ECG) and heart rate variability (HRV) to detect OSA using machine learning and deep learning classifiers. This paper includes selected articles written in the English language and published during the last decade. A total of 273 papers were found and 25 were selected using the preferred reporting items for systematic literature reviews and meta-analyses (PRISMA) approach. It includes articles compiled by searching in google scholar, PubMed, and Web of Science databases. The main contribution of this systematic literature review (SLR) is to identify the research gap and to Adhoc novel, methodologies to fill the gap for sleep apnea detection using ECG and HRV in machine learning (ML) and deep learning (DL) classifiers. The study concludes that DL algorithms for SA using ECG and HRV modalities are easy and robust. It was reported in this review that during the year 2021, most of the research work was carried out in DL for SA detection which establishes its significance. This SLR also provides important information to choose an efficient model for SA detection and characterization using a single-channel modality.
Prediction of concrete properties using machine learning algorithm
Authors: Tipu Rupesh Kumar , Panchal V R , Pandya K S 
Published: June 2022

Abstract
This paper presents a machine learning model for the prediction of two mechanical properties, namely concrete compressive strength and chloride penetration depth. A total of five machine learning algorithms, including Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVR), Gradient Boosting (GB), and Artificial Neural Network (ANN), are employed on the collected data set. The winner model is then selected, and its hyperparameters are tuned using the particle swarm optimization (PSO) algorithm. To avoid overfitting of the model on the test data set 10 k-fold cross-validations are used. Features are handled for missing data set values using mean values of available data for the same features. The model performance results are measured using Root Mean Squared Error (RMSE) and coefficient of determination (R2). The proposed model yielded 97% accuracy with a 4 MPa value of RMSE, which indicates an efficient model. Out of all the models, Random Forest Regressor and Gradient Boosting Regressor Model performed well.
Growth of silver nanoparticles on unpolished silicon substrate by used of microwave-assisted technique to enhance the Raman spectrum of glucose
Authors: Isnaeni  , Yudasari Nurfina , Hidayah Affi Nur 
Published: June 2022

Abstract
Silver nanoparticle is useful metallic nanoparticle due to plasmonic property. One of the most important application of silver nanoparticle is enhancing Raman spectrum using so-called surface-enhanced Raman spectroscopy (SERS). Mostly, researchers synthesize colloidal silver nanoparticles and deposite on substrate to form SERS substrates. In this work, we simplified the synthesis of SERS substrate by use of microwave. We have successfully grown silver nanoparticles on unpolished silicon substrate using single step microwave-assisted technique. The unpolished silicon substrate has micro-size chambers that are useful for Raman measurement. The silver nanoparticles on silicon substrate were approximately 88 nm in diameter. Our experiment using corn syrup revealed that our SERS substrate enhance Raman peaks spectra of glucose and galactose by more than 16 times.
The development of the real-time Michelson interferometer for the measurement of thermal expansion coefficients of dental composites nanofiller
Authors: Apsari R. , Sya’dyyah Halimatus , Ningsih Kristia , Yhuwana Y. G. Y. 
Published: June 2022

Abstract
This study aims to design a thermal time-based expansion coefficient sensor system using a nickel interferometer that uses a 6 Watts heater to produce a similar oral cavity temperature of 30°C to 60°C. The light source used was the He-Ne Laser, with a wavelength of 632.8 nm. Hollow cylindrical samples with an outer diameter of 1.1 cm, an inner diameter of 1 cm, and a height of 1.5 cm were placed in the sample box behind one of the Michelson Interferometer mirrors. The interference pattern (fringes) formed was recorded using a webcam and counted using the principle of motion detection in the Delphi program. The temperature sensor used was LM 35 with LM 358 amplifier. The resulting voltage output was converted to a temperature value with Arduino. The data were then displayed on a PC with the Delphi interface. The purposely written Delphi program has four functions: recording and counting fringes, displaying temperature, and calculating the thermal expansion coefficient of acrylic resin and nanofiller composite. The generated data in the study included the heating time for 25,421 seconds to produce a temperature of 60°C, delay of (0,802 ± 0,006) second with the sensor performance of 99,76%, and software performance of 98,18%. In three data collections, the average thermal expansion coefficient of resin acrylic was (111.37 ± 10.93). 10-6 / ° C with an error percentage of 23.74% from the literature, while for the composite nanofiller samples, we obtained (49.6 ± 0.95). 10-6 / ° C with an error percentage of 6.9% from previous studies.
The influence of surface roughness to particle optical characteristics by a study of Chebyshev particles
Authors: Fikry Hilman , Iskandar Alexander A. 
Published: June 2022

Abstract
In this work, Chebyshev particles are used to study the influence of surface roughness and nonsphericity to the optical characteristics of particles by exploiting the parameters of Chebyshev particles, namely the waviness parameter and the deformation parameter. This is analyzed by comparing the scattering, extinction, and absorption cross sections, asymmetry parameter, single-scattering albedo, phase function, and linear polarization degree of different types of particles, including spheres and several types of Chebyshev particles. To calculate the optical characteristics, Extended Boundary Condition Method is utilized. The results show that there are some deviations affected by nonsphericity or surface roughness of particles, especially in relatively large size parameter, real part of refractive index is larger than 1, and imaginary part of refractive index is equal to 0. By approximating the surface roughness of particles by Chebyshev particles, larger waviness and deformation parameters tend to give larger difference from ideal particles in optical characteristics, so the optical characteristics could be controlled by modifying these parameters.
River direction prediction of Shuangliu District Fu River based on ArcSWAT model
Authors: Pan YongHao , Liao Jie , Peng Ran , Wang HongJie 
Published: June 2022

Abstract
The division and prediction of river basins provide important theoretical support for mountain torrents, flow direction control and governance. This paper takes Shuangliu District of Chengdu as the main research area. The experiment is supported by the elevation data of Fuhe River in Huanglongxi Town, Yong’an Town, Shuangliu District of Chengdu from 2020 to 2021. By constructing the model database, dividing the spatial unit of the basin and predicting the river trend, the arcswat model for the River Basin of Shuangliu District of Chengdu is established. The results show that the preliminary watershed area obtained by introducing elevation image analysis is the best. In the follow-up test, by combining the calculated results of hydrological system characteristics in the database with the weather data obtained from the world weather database, it better fitted the water conditions of Shuangliu area and showed excellent performance.
Research on scheduling optimization of internal trucks for inter-terminal transportation
Authors: Xiao Qing , Li Fengxiang , Ge Xiaofangg , Yu Xuhui 
Published: June 2022

Abstract
Based on the operation mode of inter-terminal transportation in a container port, an optimization method of internal trucks scheduling was proposed to cooperate among multiple terminals in a port. In order to minimize the remaining workload of each terminal, a mixed integer programming model for internal trucks scheduling optimization was established by considering the transportation time and energy consumption of internal trucks. The improved genetic algorithm was used to solve the model, and an example was given to verify the validity of the model. The results show that the scheduling optimization model based on inter-terminal transportation mode can effectively reduce the total operating cost of each terminal and improve the utilization rate of internal trucks.
Research on Steering Control of Modern Trackless Train with Multi-Articulated Distributed Drive
Authors: Song Peipei 
Published: June 2022

Abstract
Modern trackless train has the characteristics of long body and many articulated modules, and the steering control is extremely difficult. This paper first established its Adams dynamic model, and then designed a fuzzy PID controller to generate the yaw moment and rear wheel angle. So that the vehicle can track the trajectory of the first axle when turning. Finally, the control model was established in Matlab and simulated jointly with Adams model. The simulation experiments under step input and sinusoidal input were carried out. The results show that the active steering control strategy based on the combination of direct yaw moment and rear wheel angle can meet the requirements of vehicle steering stability and trajectory following.
Application of comprehensive diagnosis technology in fault analysis of 35kV box transformer in wind farm
Authors: Shoubao Liu , Yanyang Dang , Wei Guo , Lang Wang , Jiajun Song 
Published: June 2022

Abstract
Using on-line monitoring means to monitor the state quantity of power equipment is the trend of equipment diagnosis and evaluation, but it is usually difficult to accurately judge the hidden dangers of equipment by using a single means. This paper puts forward the transformer comprehensive on-line monitoring technology, which can effectively identify the equipment faults through multi state quantity and long-time comprehensive analysis. The relevant achievements are applied to the fault analysis of 35kV box-type transformer in a wind farm. The qualitative classification of fault category is realized by integrating three state quantities: temperature, oil color spectrum and iron core grounding current; Through disassembly inspection, the effectiveness of the integrated on-line monitoring system is proved; The analysis of fault mechanism is realized by using finite element electromagnetic field calculation. The technology of transformer comprehensive diagnosis in this paper has a very important reference for the defect analysis of transformer equipment.
Control of Inner Flow Field Inside A Transonic Centrifugal Compressor with Splitter Through Chordwise Sweep
Authors: Liang Dong , Chen Huixin , Ou Jun , Jin Donghai , Gui Xingmin 
Published: June 2022

Abstract
The strategy of sweep design should be based on the inner flow field of the compressor. In this paper, a transonic centrifugal compressor within the splitter is discussed in detail, and both forward sweep and backward sweep are studied with numerical simulation for optimization. Splitter introduces extra leakage and it’s worth noting that the high-entropy region is shifted from the suction side of the main blade to the suction side of the splitter. Different from the transonic axial rotor, the leakage of the main blade mainly occurs after the passage shock and will be mixed with the leakage of the splitter in the suction side of the splitter. Therefore, the flow control on the middle and rare part of the compressor is more essential for the performance of the stage. In this regard, the backward sweep of the main blade exhibits a good effect by reducing the mixing loss of secondary leakage. Due to the redistribution of the airflow, the mainstream velocity in the tip area is accelerated in the forepart and reduced in the rare part, the aerodynamic loss in the high-entropy zone is then improved, and the flow capacity of the compressor is also increased. The best performance is achieved by an 8° backward sweep for the centrifugal compressor in this work, the pressure ratio is increased by 2.84% and isentropic efficiency is increased by 1.40%, compared to the prototype.
Influence of converging slot-holes (consoles) with different transition surfaces on film cooling performance
Authors: Yu Manshuang , Xuan Dong 
Published: June 2022

Abstract
To investigate the influence of the transition surfaces of consoles on film cooling performance, a series of numerical simulations were performed under two typical blowing ratio (M). Four different consoles were designed by changing the transition surface of the console, and their film cooling performance was studied under the same boundary conditions. The purpose of the present work is to determine the best configuration of the transition surface. The results show that whether at M=0.5 or M=1.0, compared with the reference case, the console with anti-s-shaped transition surface has the best spatially-averaged adiabatic film cooling effectiveness (ηad,av
), and the ηad,av
is improved by 6.4% and 7.0% respectively, meanwhile, the discharge coefficient (Cd
) is decreased by 2.9% and 3.2% respectively. Besides, the detailed flow and heat transfer mechanism of consoles with different transition surfaces under different blowing ratios are also investigated.
Study on analytical model of gas diffusion in underground pipe network
Authors: Zhou Tian , Yang Fan , Liu Wei , Tan Yue 
Published: June 2022

Abstract
Through the analysis of gas pipeline leakage causes and gas leakage diffusion model, the preventive measures for gas leakage accidents are put forward, which is of great significance for the harm of gas leakage and explosion accidents. In this paper, the mathematical model of gas leakage is established through hydrodynamics and pipeline gas motion equation, and the leakage process is analyzed by means of numerical simulation, the change law of gas dynamic leakage is obtained from the aspects of gas leakage conditions, gas movement and diffusion law.
Influence of fan-shaped holes with different transition surfaces on film cooling performance
Authors: Liu Hansong 
Published: June 2022

Abstract
A series of numerical simulations were conducted to investigate the fan-shaped film holes with different transition surfaces on film cooling performance. In the present study, four fan-shaped holes different with the conventional fan-shaped hole were designed by changing the transition surfaces of fan-shaped holes, and their film cooling effectiveness and discharge coefficient were studied under the same boundary conditions. The results show that the anti-s-shaped fan-shaped hole has the best film cooling performance. Under the blowing ratio of M=1 and M=2, compared with the reference fan-shaped hole, the spatially-averaged cooling effectiveness is improved by 8.7% and 23.8% respectively, and the discharge coefficient is increased by 3.9% and 6.4% respectively.
Influence of front wheel air dam and diversion channel on heat dissipation performance of brake disc
Authors: Guan Qingyun , Zhou Yang , Liang Yizheng , Xiao Ling , Yuan Xiayi 
Published: June 2022

Abstract
In order to improve the heat dissipation performance of the brake disc and reduce the air drag coefficient of the vehicle, the influence mechanism of the front wheel air dam and brake cooling guide structure is studied. Firstly, according to the flow field around the front wheel, six feasible air dam and guide flow optimization solutions are designed; then, CFD simulation method is used to simulate the flow rate, heat transfer coefficient and cooling time; secondly, for the air drag coefficient and brake cooling time of the whole vehicle, aerodynamic-acoustic wind tunnel and road test are used to test and verify respectively; finally, we get the solution of small front wheel air dam and open a guide flow channel around the plate (solution 4), the air drag coefficient is only increased by 3ct, and the brake cooling performance is much better.