bluuebunny/crossref_metadata_2025_split huggingface dataset:
TRial to Assess Implementation of New research in a primary care Setting (TRAINS): study protocol for a pragmatic cluster randomised controlled trial of an educational intervention to promote asthma prescription uptake in General Practitioner Practices
Authors: Alyami Rami A , Simpson Rebecca , Oliver Phillip , Julious Steven A. 
Published: June 2022

Abstract
BackgroundThere is a marked increase in unscheduled care visits in school-aged children with asthma after returning to school in September. This is potentially associated with children not taking their asthma preventer medication during the school summer holidays. A cluster randomised controlled trial (PLEASANT) was undertaken with 1,279 school-age children in 141 general practices (71 on intervention and 70 on control) in England and Wales. It found that a simple letter sent from the family doctor during the school holidays to a parent with a child with asthma, informing them of the importance of taking asthma preventer medication during the summer relatively increased prescriptions by 30% in August and reduced medical contacts in the periods September to December. Also, it is estimated there was a cost-saving of £36.07 per patient. We aim to translate the PLEASANT trial findings into practices to optimise outcomes for patients and health services.Methods /design:The TRAINS study - TRial to Assess Implementation of New research in a primary care Setting - is a pragmatic cluster randomised implementation trial. A total of 1389 General Practitioner (GP) practices in England will be recruited into the trial; circa 694 GP practices will be randomised to the intervention group and 695 control group of usual care. The Clinical Practice Research Datalink (CPRD) will send the intervention and obtain all data for the study, including prescription and primary care contacts data. The intervention will be sent in June 2021 by postal and email to the Asthma Lead and Practice Manager. The intervention is a letter to GPs informing them of the PLEASANT study findings with recommendations; it will consist of a letter for GPs with an information leaflet about PLEASANT and suggested reminder letter and SMS text template.DiscussionThe trial will assess if informing GP practices of the PLEASANT trial results will increase prescription uptake before the start of the school year. The hope is that the intervention will increase the implementation of PLEASANT work and then increase prescription uptake during the summer holiday prior to the start of school.Trial registration:ClinicalTrials.gov ID: NCT05226091
Modeling Anaerobic Co-digestion of Food Wastes and Cattle Manure in an Industrial Plant: A System Dynamic Approach
Authors: Azeez Sarafadeen Ayinde , Gwandangaji Danshehu Bagudu 
Published: June 2022

Abstract
PurposeAnaerobic co-digestion is a realistic technique for organic waste management as well as biogas production. To monitor the co-digestion processes because of their high susceptibility to instability, a simple, interpretable, and accurate model is required for control design and process optimization.MethodsTherefore, a modified anaerobic digestion model number 2 (AM2) was built in the system dynamics (SD) model) for the prediction of biogas production in an industrial biogas plant fed with cattle manure and food wastes. The predictive ability of the model using the model parameters (kinetic parameters and yield coefficients) estimated in Premium Solver, was checked by comparing model results (biogas flow and compositions) with anaerobic digestion model number 1(ADMI) simulated results and the experimental data obtained from the literature. Sensitivity analysis of the modified AM2 to biogas flow and methane concentration was conducted by varying the inflow of biodegradable fractions, the initial substrate, and biomass concentrations.ResultsThe simulation results of the modified AM2 model were found to correspond with the measured values with percentage errors of 1.42% and 0.6% for methane concentration and biogas flow respectively. The process variables associated with the methanogenesis stage were obtained to be the most sensitive variables.ConclusionThis study showed that the AM2 which is tractable, reduced, and robust, built in the SD model is a vital tool for the operation of the biogas plant's digester.
Triglyceride Glucose Index is Independently Associated with Aorta Intima-Media Thickness in Patients without Clinical Manifestations of Cardiovascular Disease
Authors: ÖZBİÇER Süleyman , YÜKSEL Gülhan , URGUN Örsan Deniz 
Published: June 2022

Abstract
Background: Subclinical atherosclerosis develops in the thoracic aorta early in life. Insulin resistance is a well-established risk factor for the development of atherosclerosis. The triglyceride-glucose (TyG) index is a reliable marker of insulin resistance regardless of glucose tolerance or obesity. We aimed to investigate the relationship between the TyG index and aortic intima-media thickness (IMT) in patients without diabetes mellitus and cardiovascular disease undergoing transesophageal echocardiography due to suspected structural heart disease.Methods: One hundred twenty-two patients enrolled in the study between January 2021 and June 2021. Triglyceride-glucose index was calculated using fasting laboratory parameters, and major cardiovascular risk factors and IMT of the thoracic aorta were recorded. Patients were divided into two groups according to their median IMT; patients with an IMT equal to or less than 1.42 mm were low IMT group, and higher than 1.42 mm were high IMT group.Results: Triglyceride-glucose index were higher in the high IMT group (8.69 ± 0.59 vs. 8.37 ± 0.53, p= 0.003). Triglyceride-glucose index was correlated with IMT (r=0.259, p=0.005) and in binary logistic regression analysis age and TyG was independently associated with having high IMT (β = 0.076, exp(B)=1.079 95%CI = 1.041 – 1.118, p<0.001 and β=0.847, exp(B)= 2.334 95%CI= 1.048- 5.199, p=0.038, respectively)Conclusion: We found an independent relationship between TyG and IMT of the thoracic aorta, an early marker of subclinical atherosclerosis in patients without atherosclerotic cardiovascular disease. Therefore, the TyG index can identify high-risk subjects among healthy subjects.
Increasing the Prevalence of Cervical Cancer Screening in Iran: Effectiveness of a Theory-Based Educational Intervention
Authors: Hosseini Zahra , Mohseni Shokrollah , Momeni Rahimeh , Aghamolaei Teamur , Alavi Azin , dadipoor sakineh 
Published: June 2022

Abstract
Purpose: The high mortality rate of cervical cancer in developing countries is mainly related to inefficient screening programs. The aim of the present study was, thus, to determine the effect of an educational intervention based on BASNEF model in increasing cervical cancer screening (CCS) in Bandar Deir in the south of Iran.Methods: A quasi-experimental educational intervention was conducted for 202 women (101 in the intervention group (IG) and 101 in the control group (CG)) between 2019 and 2020. The sampling was convenience in type. The required data were collected using a valid and reliable questionnaire in three parts (demographic part, knowledge part, BASNEF constructs). 14 educational sessions were held each taking 60 minutes long at two levels, personal and interpersonal (family members, health workers and healthcare givers). Finally, the follow-up was completed after three months in December 2021. Results: After the educational intervention, a statistically significant difference was observed between the IG and CG in all model constructs (p<0.001). Before the intervention, in the IG, the personal health score was 4.35±2.52, which was increased to 5.25±0.753 after the educational intervention (p <0.001). However, in the CG, this difference was not statistically significant (p <0.030). 63.4% of women in the IG and 32.7% in the CG underwent CCS and the difference was statistically significant (p <0.001). Attitude, enabling factors and behavioral intention were among the most important predictors of CCS.Conclusion: Our findings showed that the BASNEF-based educational intervention, with limited resources and in a short time, managed to motivate women to undergo CCS. It could maximally remove barriers at both personal and interpersonal levels and provide strategies based on these barriers to achieve a successful screening program.
Artificial Neural Network Approach versus Analytical Solutions for Relativistic Polytropes
Authors: Nouh Mohamed , Abdel-Salam Emad , Azzam Yosry 
Published: June 2022

Abstract
Over the last few decades, artificial neural networks (ANN) have played an important role in many areas of human activity and have found application in many branches of natural sciences. ANNs have been widely used to tackle problems related to linear and nonlinear differential equations, and numerous paradigms for ANN architecture have been employed. Based on ANN and the Taylor series, this research proposes a computational technique to solve difficulties connected to the Tolman-Oppenheimer-Volkoff equations (TOV) of the relativistic gas spheres. We used ANN to study two cases related to relativistic polytropes. The first is to simulate both the Emden and the relativistic functions, and the second is to predict the zeros of the Emden function and its corresponding relativistic functions. In its feed-forward back-propagation learning scheme, we used the ANN framework. The efficiency of the proposed algorithm is evaluated by running it through seven models concerning the polytropic indices-relativistic parameter pairs (n = 0, σ = 0.2), (n = 0.5, σ = 0.3), (n = 1, σ = 0.4), (n = 1.5, σ = 0.1), (n = 2, σ = 0.5), (n = 2.5, σ = 0.6), and (n = 3, σ = 0.7). The obtained solutions aided in the resolution improvement of relativistic polytropic gas sphere problems and the comparison between the analytical and the ANN solutions gives good agreement for the two cases under study.
Measurement and evaluation of neural activity in acute tonic cold pain under intense microwave radiation
Authors: Geng Daoshuang , Sun Mingxuan , Yang Daoguo , Liu Dongjing 
Published: June 2022

Abstract
To explore the influence of high-frequency microwave transmission on the power change of EEG in pain-induced brain activity. we propose a method, to measure and evaluate the relative changes in the Electroencephalographic (EEG) power for microwave frequencies 4.5, 5, and 5.5 GHz in no pain (NP) and cold pain (CP) conditions. The relative power changes of EEG frequency bands in delta, theta, alpha1, alpha2, beta1, and beta2 were calculated with and without (Sham) microwave transmission. Then, the standardized low-resolution brain electromagnetic tomography (sLORETA) was used to analyze the source localization of different pain types. In addition, a pain brain activity detection experiment was designed to verify the feasibility and accuracy of microwave detection of pain. At 5 GHz microwave transmission, the average EEG power of delta, beta1, and beta2 increased by 10–35%, which was substantially higher than that of Sham. In source localization analysis, the source activity changes of the activated brain regions were enhanced under high frequency microwave radiation. The proposed method can better reflect the variation of active state EEG power under high-frequency electromagnetic radiation. In the test of pain detection, microwave transcranial (MT) signal has certain correlation with the spectrum characteristics of EEG signal in the same test state, and the experimental results confirm that MT signal is indeed related to pain brain activity. This study provides a basis for microwave detection of neural activity induced by cold pain and has great significance for clinical diagnosis of pain-induced diseases.
Density functional theory of NO and transition metal R (R=Cu, Fe and Mn) adsorbed on TiO2 surface
Authors: JIANG Meiyi , YANG Kun , LIU Yancheng , Yao Li 
Published: June 2022

Abstract
In order to study the electronic interaction and influence of NO-transition metal support, the density functional theory (DFT) method was used to calculate the adsorption energy, physical properties and electronic structure of NO adsorbed transition metal R (R=Cu, Fe and Mn)-anatase TiO2 (101) surface. The above transition metals were adsorbed on anatase TiO2 (101) surface in three different adsorption ratios (single transition metal adsorption model, two different transition metal adsorption at 2:2 ratio model and 1:3 ratio model). On the basis of the study, 13 models were established to study the effects of different adsorption ratios of transition metals on NO oxidation to determine the optimal adsorption ratio of transition metals. The results exhibit that different proportions of adsorbed transition metals have different effects on the oxidation of NO. From the point of view of the stability of adsorption structure, the adsorption structure of transition metal and NO in the mixed adsorption model is more stable, and the influence order is single metal oxide adsorption model < 2:2 ratio model < 1:3 ratio model. The results of electron structure and charge distribution analysis show that a large quantity of active electron clusters are distributed around Mn and Fe atoms and in contact with N atoms of NO in a large area, which mean that they can provide more electrons for catalytic reaction and facilitate electron exchange between catalyst and NO. Among them, the 3Mn+1Fe-TiO2 model has the best effect.
Modification of food additive titanium dioxide (TiO 2 E171) with honey and thyme
Authors: Ahmed Hager Youssef , Ibrahim I. H. , Sallam Abdelsattar M. , Said Alaa Hassan 
Published: June 2022

Abstract
Titanium dioxide (TiO2) is a distinguished semiconductor that is used as a coloring agent in many products including paints, plastics, papers, cosmetic creams, and food products. In the food industry TiO2 is Labelled as E171 according to the European Union legislation and it is used in many products such as sugar confectionery, chewing gums, candies, some cheeses and sauces, low-fat products such as skimmed milk, ice creams, and pastries with a percentage up to 3.88 mg of TiO2 per g of product. According to the literature, around 36% of TiO2 E171 particles are nanoparticles (NPs), which can cross the intestinal barrier reach the blood circulation then accumulate in the liver, spleen, kidneys, and lung tissues resulting in serious damage to these organs. The aim of this study is to use honey and thyme as natural coating materials to enhance the biocompatibility of three types of TiO2 E171 (anatase, rutile, and food grade). The physiochemical characteristics and bioactivity of TiO2 E171 before and after modification with honey and thyme were measured. The obtained results demonstrate that the modification of TiO2 E171 with honey and thyme didn’t alter its physicochemical properties and the modified TiO2 E171 showed higher antioxidant activity and lower toxicity.
How ecosystem services change due to human and climate change
Authors: maleki saeideh , Rahdari Vahid , Pahlevanravi Ahmad 
Published: June 2022

Abstract
Human well-being in a large part of the world depends on ecosystem services (ESs). However, humans degrade ESs directly by unsustainable land-use policies and indirectly by climate change. In this regard, how ecosystem services change due to human and climate change is a crucial question to demonstrate the human and climate change effects. This paper aimed to answer this question. The wetland services over 45 years were investigated using remote sensing techniques, InVEST, and Biomod2. Higher restoration priority was determined based on the ES degradation rate, and the importance of each ES. The results of this paper indicated the percentage of ecosystem degradation and the services with the highest priority for restoration measures in arid area. The importance of this paper include applying a functional method to study ESs and running this method by the main components shared between all wetlands. These attributes make this method applicable in all regions to study human and climate change effects and ecosystem restoration prioritization.
M-ar-K-PCA and M-ar-K-FastICA: Robust Feature Extraction for Classification of Non-Gaussian and Entropic Data
Authors: Manaog Marianne Lyne , Parisi Luca 
Published: June 2022

Abstract
The kernel trick has enabled dimensionality reduction techniques to capture a higher extent of non-linearity in the data; however, reproducible, open-source kernels to aid with feature extraction are still limited and are not reliable when projecting features from non-Gaussian and entropic data for a robust classification of data. In fact, traditional kernels are either too simplistic (linear and identity) or have a limited range (sigmoid), thus being unable to handle and transform non-Gaussian and entropic input data adequately. To help in mitigating these challenges, this study presents the m-arcsinh Kernel (’m-ar-K’) Principal Component Analysis (’PCA’) and Fast Independent Component Analysis (’FastICA’) methods for feature extraction, i.e., the ’m-ar-K-PCA’ and ’m-ar-K-FastICA’ respectively. The m-ar-K function, freely available in Python and compatible with its open-source library ’scikit-learn’, is hereby coupled with PCA and FastICA and to achieve more reliable feature extraction in presence of a high extent of non-Gaussianity and randomness in the data, reducing the need for standardisation and pre-whitening respectively. Different classification tasks were considered, as related to five (N = 5) open access datasets of various degrees of non-normality and information entropy, available from scikit-learn and the University California Irvine (UCI) Machine Learning repository. Experimental results demonstrate improvements in the classification performance brought by the proposed feature extraction techniques. The novel m-ar-K-PCA and m-ar-K-FastICA dimensionality reduction approaches are compared to the ’PCA’ and ’FastICA’ gold standard methods respectively, supporting their overall higher reliability and computational efficiency, regardless of the underlying non-Gaussianity and uncertainty in the data. Thus, in particular, m-ar-K-PCA extends the use of PCA to pseudo-Gaussian distributions and m-ar-K-FastICA enables FastICA to withstand not only highly non-normal distributions, but also entropic data.
Numerical analysis of a slope stabilized with piles and anchor cable frame beams
Authors: Du Changcheng , Chen Jianfeng , Chen Sixian , Peng Ming , Shi Zhenming 
Published: June 2022

Abstract
A landslide located in northern Sichuan Province, China, was investigated. A series of numerical models of the landslide stabilized with piles and anchor cable frame beams were developed using a three-dimensional finite element method. The Strength Reduction Method was employed to investigate the stability of slopes, the internal forces of piles, and the axial forces of anchor cables. A parametric study consisting of pile position, pile length, and pile spacing was carried out. The results show that compared to anchor cable frame beams, the combination of piles and anchor cable frame beams is a more effective retaining structure to improve slope stability. During slope destabilization, the proportion of thrust shared by piles gradually increases while the proportion of thrust shared by anchor cables gradually decreases. Piles installed on the leading edge of a trail-mode landslide can make the slope mostly stable. As the piles move from the leading, middle, and trailing edges of the slope, the proportion of thrust shared by the anchor cables gradually increases while local instability may occur in front of the pile. Increasing the pile length can improve the stability of the slope. However, excessive embedded length of piles has little effect on further improving the slope stability. The critical embedment length of piles found in this paper is 1/3 of the total length of the pile. The critical pile spacing found in this paper is 2.5 times the width of the pile section. Beyond this spacing, the effective soil arch between the piles is difficult to develop and the anchor cables may share more proportion of the landslide thrust. This paper provides a reference for reinforcement system design of engineering projects considering piles and anchor cable frame beams.
How does carbon emission trading scheme affect enterprise green technology innovation:Evidence from China's A-share non-financial listed companies
Authors: Ma Xiaodong , Xue Yongxuan 
Published: June 2022

Abstract
More and more emphasis is placed on the common development of economy and ecological environment in China's development strategy, and one of the key solution is green technology innovation of enterprises. This paper takes the carbon emission trading scheme carried out in China in 2013 as a quasi-natural experiment, uses the data of China's A-share non-financial listed companies and the DID method to empirically test the impact of the scheme on enterprise green technology innovation from the micro level. The results suggest that the carbon emission trading scheme has a significant role in promoting enterprise green technology innovation, mainly through the innovation of green practical patents and alternative energy-based patent. Using a series of robustness tests such as dynamic effect test, placebo test and PSM-DID etc., it is found that the results are still valid. Further analysis finds that debt financing will weaken the role of carbon emission trading scheme in promoting enterprise green technology innovation. And the carbon emission trading scheme plays a greater role in promoting green technology innovation in state-owned enterprises, enterprises belonging to areas with strong pollution control intensity and high pollution industry.
A Wheat 660K SNP array based high-density genetic map facilitates QTL mapping of flag leaf related traits in wheat
Authors: Niu Jianqing , Si Yaoqi , Tian Shuiquan , Liu Xiaolin , Shi Xiaoli , Ma Shengwei , Yu Zhongqing , Ling Hong-Qing , Zheng Shusong 
Published: June 2022

Abstract
Flag leaf plays an important role in photosynthetic capacity and yield potential in wheat. In this study, we used a recombinant inbred line (RIL) population containing 188 lines derived from a cross between Lankao86 (LK86) and Ermangmai (EMM) to construct a genetic map using the Wheat 660K single nucleotide polymorphism (SNP) array. The high-density genetic map contains 122,620 SNP markers spanning 5,185.06 cM. It shows good collinearity with the physical map of Chinese Spring, and anchors multiple sequences of previously unplaced scaffolds (ChrUn) onto chromosomes. Based on the high-density genetic map, we identified seven and twelve quantitative trait loci (QTL) for flag leaf length (FLL) and width (FLW) across eight environments, respectively. Among them, three QTL for FLL and one for FLW are major and stably express in more than five environments. The physical distance between the flanking markers for QFll.igdb-3B is only 444 kb containing eight high confidence genes. These results suggested that we could directly map the candidate genes in a relatively small region by the high-density genetic map constructed with the Wheat 660K array. Furthermore, the identification of environmentally stable QTL for flag leaf morphology laid a foundation for the following gene cloning and flag leaf morphology improvement.