bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of Three Organic Fertilizers and Their Influence on the Mobility of Cadmium and Arsenic in a Soil-Rice (Oryza Sativa L.) System
Authors: Tan Xiao , Cao Jinman , Liu Jiahao , Wang Jinhang , Duan Guilan , Zhang Yinjie , Lin Aijun 
Published: January 2022

Abstract
The properties and effects of organic fertilizers are different, including the ability to improve soil fertility and the potential of stabilizing heavy metals in soils that have not been explored in depth. In this study, three organic fertilizers from different raw materials were characterized and evaluated. The mushroom residue organic fertilizer (MO) had higher C, H, and O contents and more functional groups (-OH, C-H, and C=O), and its application significantly increased pH (1.00~1.32 units), organic matter (OM) content (26.58%~69.11%) and cation exchange capacity (CEC) (31.52%~39.91%) of soil. MO treatment also reduced the toxicity characteristic leaching procedure (TCLP)-Cd (24.21%) and TCLP-As (18.44%) concentration in the soil. That inhibited the mobilization of Cd and As from soil to plant, especially to plant shoots, and positively affected the plant growth and biomass. Redundancy analysis (RDA) showed that 40.09 % of total plant variation was related to soil properties (pH, OM, and CEC). Furthermore, the heavy metal risk assessment for all organic fertilizers was at safe levels. This study provides a valuable reference for the selection of organic fertilizers. Besides, it recommends organic fertilizers as economic and multi-effect amendments with safe use and provides a new option for the ‘simultaneous production and remediation’ of farmlands with low pollution.
Feasibility of Diffusion Kurtosis Imaging in Evaluating Cervical Spinal Cord Injury in Multiple Sclerosis
Authors: Bian BingYang , Liu ZhuoHang , Shao ZhiQing , Tian Pu , Liang YaQian , Zhu XiaoNa , Jie YiGe , Li Dan 
Published: January 2022

Abstract
Background：Quantitative evaluation of cervical spinal cord (CSC) injury in multiple sclerosis has always been a difficulty. The present study aimed to evaluate the lesion, normal-appearing gray matter (GM) and white matter (WM) damage, and therapeutic effect using diffusion kurtosis imaging (DKI) on CSC of patients with multiple sclerosis.Methods: A total of 48 patients with MS and 30 healthy adults, underwent routine MR scan and DKI of CSC. DKI-metrics were measured in the lesions and in the normal-appearing gray and white matter. MS patients were divided into those with and without T2-hyperintense lesions. Disability was assessed by the expanded disability status scale before and after therapy.Results：1) Significant differences were detected in MK, MD, and FA values between patients and healthy subjects (P < 0.05) and between patients with CSC T2-hyperintense and patients without T2-hyperintense (P < 0.05); 2) Compared to healthy, GM-MK and WM-FA were statistically reduced in patients without T2-hyperintense (P < 0.05). 3) Significant differences were observed in MK, MD, and FA between patients with T2-hyperintense after therapy (P < 0.05), as well as GM-MK and WM-FA in patients without T2-hyperintense (P < 0.05); 4) EDSS was correlated with MK values, as well as EDSS scores and MK values after therapy.Conclusions：1) DKI-metrics can detect and quantitatively evaluate the changes in cervical spinal cord micropathological structure; 2) MK values are sensitive metrics to detect the damage of gray matter; 3) MK values quantitatively evaluate the clinical disability progression and the therapeutic effect in MS patients.
Deformation Behavior and Damage-Induced Permeability Evolution of Sandy Mudstone Under Triaxial Stress
Authors: Liu Yang , Zhang Tong , Ma Yankun , Song Shuaibing , Tang Ming , Li Yanfang 
Published: January 2022

Abstract
The permeability and mechanical behavior in sandy mudstone are crucial to the hazard prevention and safety mining. In this study, to investigate the evolution and characteristic of permeability and mechanical properties of mudstone during the in-site loading process, triaxial compression-seepage experiments were performed. The increase of permeability and decrease of mechanical strength gradually evaluated to the decrease of permeability and increase of mechanical strength subjected to the increase of confining stress from 5 to 15 MPa, which corresponds to the transformation from brittleness to ductility of mudstone, and the transformation threshold of 10 MPa confining stress was determined. The shear fractures across the sample at brittle regime, while shear fracture does not cross the sample or even be not generated at semibrittle and ductile state. The dynamic decrease, slight decrease, and residual response were determined in axial strain, and the divided zone increases with the increase of confining stress. The relatively higher permeability corresponds to the higher pore pressure as the increase of confining stress. The volumetric strain increases as the increase of confining stress, compared to that decrease correspond to the increase of the pore pressure, and the higher volumetric strain and the lower permeability. In addition, an improved permeability model was developed to describe the loading-based permeability behavior considering the Klinkenberg effect.
Failure Properties and Stability Monitoring of Strip and Column Cemented Gangue Backfill Bodies Under Uniaxial Compression In Constructional Backfill Mining
Authors: Ran Hongyu , Guo Yuxia , Feng Guorui , Li Chunqing 
Published: January 2022

Abstract
The strip and column cemented gangue backfill bodies (CGBBs) are the main supporting components in the design of constructional backfill mining for coal mining, which determines the stability of goaf. Previous researches have mostly focused on the mechanical properties of column CGBB, but the mechanical properties of strip CGBB are still unclear. Herein, the uniaxial compression experiments for strip and column CGBBs were conducted to compare the failure properties. The acoustic emission (AE) and two types of resistivity monitoring were used to monitor the damage evolution. The effect of the length-height ratio on the mechanical characteristic of strip CGBB was analyzed by discrete element simulation. The results show that: the strength and peak strain of strip CGBB under uniaxial compression is higher than those of column CGBB, and the strip CGBB shows better ductility. The stress of column CGBB decreases significantly faster than that of strip CGBB at the post-peak stage. The strength and ductility of strip CGBB increase with the increase of length-height ratio. The strip CGBB is destroyed from both ends to the middle under uniaxial compression, and the core bearing area is reduced correspondingly. The AE signal evolution of CGBBs under uniaxial compression before the peak stress contains three stages, and the AE signals of strip CGBB at the peak stress will not rise sharply compared with column CGBB. The resistivity monitoring effect of the horizontally symmetrical conductive mesh is better than that of the axial. The horizontal resistivity increases gradually with the increase of stress under uniaxial compression, and increases sharply at the peak stress, and then drops after the peak stress. The damage constitutive models and the stability monitoring models of the CGBBs are established based on the experimental results. This work would be instructive for the design and stability monitoring of CGBB.
Effects of Tillage and Cropping Sequences On Crop Production And Environmental Benefits in the North China Plain
Authors: Liu Wen-Xuan , Liu Wen-Sheng , Yang Mu-Yu , Wei Yu-Xin , Chen Zhe , Virk Ahmad Latif , Lal Rattan , Zhao Xin , Zhang Hai-Lin 
Published: January 2022

Abstract
The ever-increasing trend of greenhouse gas (GHGs) emissions is accelerating global warming and threatening food security. Environmental benefits and sustainable food production must be pursued locally and globally. Thus, a field experiment was conducted in 2015 to understand how to balance the trade-offs between agronomic productivity and environment quality in the North China Plain (NCP). Eight treatments consisted of two factors, i.e., (i) tillage practices: rotary tillage (RT) and no-till (NT), and (ii) cropping sequences (CS): maize-wheat-soybean-wheat (MWSW), soybean-wheat-maize-wheat (SWMW), soybean-wheat (SW), and maize-wheat (MW). The economic and environmental benefits were evaluated by multiple indicators including the carbon footprint (CF), maize equivalent economic yield (MEEY), energy yield (EY), carbon sustainability index (CSI), etc. Compared with NT, RT increased the EY and MEEY, but emitted 9.4% higher GHGs. Among different CSs, no significant reduction was observed in CF. The lowest (2.0 Mg CO2-eq ha-1 yr-1) and the highest (5.6 Mg CO2-eq ha-1 yr-1) CF values were observed under MW and SWMW, respectively. However, CSs with soybean enhanced MEEY and the net revenue due to its higher price compared to that of MW. Although the highest CSI was observed under RT-MW, soybean-based crop rotation could offset the decline in CSI under NT when compared to that for RT. These findings suggest that conservation agriculture (CA) could enhance the balance in trade-offs between economic and environmental benefits. Additional research is needed on how to achieve high crop production by establishing a highly efficient conservation agriculture system in the NCP.
Research on the Relationship Between Self-Management Efficacy and Quality of Life for Breast Cancer Patients Receiving Endocrine Therapy
Authors: Yi Hongjie , Jiang Haoran , Wang Aiping , Zong Wei , Dong Yu , Li Yao 
Published: January 2022

Abstract
Purpose

To investigate the status quo and relationship between self-management efficacy and quality of life (QOL) of patients with breast cancer undergoing endocrine therapy, and to explore the influencing factors of QOL.
Methods

The convenience sampling method was used to select 240 patients who received endocrine therapy after breast cancer surgery in the First Hospital of China Medical University, the self-designed general data questionnaire, self-management efficacy questionnaire for breast cancer patients with endocrine therapy and quality of life scale for breast cancer patients were used to investigate. The frequency, percentage, mean ± standard deviation were used to describe patients' self-management efficacy and quality of life. Pearson correlation analysis was used to analyze the relationship between self-management efficacy and quality of life, and univariate analysis and multiple stepwise regression were used to analyze the influencing factors of QOL.
Results

The scores of self-management efficacy and QOL of patients with breast cancer endocrine therapy were 125.21 ± 25.57 and 153.33 ± 19.31 respectively, which were at the middle level; self-management efficacy was significantly positively correlated with quality of life ( p < 0.01 ) ; multiple stepwise regression results showed that self-management efficacy, the number of physical symptoms, monthly family income and recurrence and metastasis were the influencing factors of QOL.
Conclusion

The self-management efficacy of endocrine therapy was positively correlated with QOL in breast cancer patients. The higher the self-management efficacy of endocrine therapy, the better QOL in breast cancer patients. Self-management efficacy is the main factor affecting the quality of life of breast cancer patients undergoing endocrine therapy. Improving the level of self-management efficacy can improve their quality of life.
Designing a New Multi-Echelon Multi-Period Closed-Loop Supply Chain Network by Forecasting Demand Using Time Series Model: A Genetic Algorithm
Authors: Safaei Shahab , Ghasemi Peiman , Goodarzian Fariba , Momenitabar Mohsen 
Published: January 2022

Abstract
In the closed-loop supply chain, demand plays a critical role. The flow of materials and commodities in the opposite direction of the normal chain is inevitable too. So, in this paper, a new multi-echelon multi-period closed-loop supply chain network is addressed to minimize the total costs of the network. The considered echelons include suppliers, manufacturers, distribution centers, customers, and recycling and recovery units of components in the proposed network. Also, a linear programming model considering factories' vehicles and rental cars of transportation companies is formulated for the proposed problem. Moreover, the products demand is predicted by Auto-Regressive Integrated Moving Average (ARIMA) time series model to decrease the amount of shortage may happens in the network. To solve the proposed model, GAMS software is used in small-sized problems and a genetic algorithm in large-sized problems is employed. Numerical results show that the proposed model is closer to the real situation and the proposed solution method is efficient. Accordingly, sensitivity analysis is performed on important parameters to show the performance of the proposed model.
Determination of the Area of Energy-efficient Working Equipment Position and Effective Digging Radius of Hydraulic Excavators in Open-pit Mining
Authors: Markov Sergey , Tyulenev Maxim 
Published: January 2022

Abstract
Since the end of the last century, a significant number of hydraulic excavators have arrived on Russian quarries. Most of these excavators are equipped with backhoe operating equipment. The widespread use of such excavators in open-pit mining proves their exceptional efficiency. However, at the same time there is no clear understanding of the conditions under which a hydraulic excavator will be most effective: a theory of the face block of hydraulic shovels has not yet been developed. The available scientific studies are limited to determining the rational height of the excavation layer for efficient operation. If to take the quality of preparation of rock mass and the scheme of its loading into dump trucks as external parameters, i.e. not depending on the features of excavator design, then the position of its working equipment relative to the rock block has a decisive influence on operation of the hydraulic drive and fuel consumption. This is due to the changing value of digging force at various points of the bucket teeth position in the range of their possible positions at constant power of the hydraulic drive. Thus, application of optimal position of hydraulic excavator working equipment elements (bucket, arm, and boom) relative to the rotary platform and the rock massive during the digging cycle allows both to reduce fuel consumption and to increase the digging force. The application of the developed methodology is promising in terms of improving the energy efficiency of both individual excavation and loading units and the enterprise as a whole.
Training a Machine Learning Classifier to Identify ADHD Based on Real-World Clinical Data From Medical Records
Authors: Mikolas Pavol , Vahid Amirali , Bernardoni Fabio , Süß Mathilde , Martini Julia , Beste Christian , Bluschke Annet 
Published: January 2022

Abstract
The diagnostic process of attention deficit hyperactivity disorder (ADHD) is complex and relies on criteria sensitive to subjective biases. This may cause significant delays in appropriate treatment initiation. An automated analysis relying on subjective and objective measures might not only simplify the diagnostic process and reduce the time to diagnosis, but also improve reproducibility. While recent machine learning studies have succeeded at distinguishing ADHD from healthy controls, the clinical process requires differentiating among other or multiple psychiatric conditions. We trained a linear support vector machine (SVM) classifier to detect participants with ADHD in a population showing a broad spectrum of psychiatric conditions using anonymized data from clinical records (N = 299 participants). We differentiated children and adolescents with ADHD from those not having the condition with an accuracy of 66.1 %. SVM using single features showed slight differences between single features and overlapping standard deviations of the achieved accuracies. An automated feature selection achieved the best performance using a combination 19 features. Real-life clinical data from medical records can be used to automatically identify individuals with ADHD among help-seeking individuals using machine learning. The relevant diagnostic information can be reduced using an automated feature selection without loss of performance. A broad combination of symptoms across different domains, rather than specific domains, seems to indicate an ADHD diagnosis.
Representation of Land-Atmosphere Coupling Processes Over Africa in CMIP6 Models
Authors: Mwanthi Anthony , Mutemi Joseph , Dyer Ellen , James Rachel , Opijah Franklin , Webb Thomas , Mutua Francis , Washington Richard , Senior Catherine , Zewdu Segele , Artan Guleid 
Published: January 2022

Abstract
Climate models are useful tools that aid in short to long term prediction of the evolution of climate. In this study we assess how CMIP6 models represent coupling between processes over the land and atmosphere, based on terrestrial and atmospheric indices, to show the nature and strength of the coupling relative to the ERA5 datasets over Africa, with a particular focus on the March-May season. Characterization of the annual cycle indicates that model biases are highest during the peak of the rainfall season, and least during the dry season, while soil moisture biases correspond with rainfall amounts. Models show appreciable sensitivity to regional characteristics; there was model consensus in representing East Africa as a limited soil moisture regime, while major differences were noted in the wet regime over Central Africa. Most CMIP6 models tend to over-estimate the strength of the terrestrial and atmospheric pathways over East and Southern Africa. Inter-model differences in coupling indices could be traced to their inter-annual variability rather than to the mean biases of the variables considered. These results are good indicators towards scientific advancement of land surface schemes in the next generation of climate models for better applications in Africa.
Assessment of The Incidence of Insomnia In The Group of Poles Aged 18-25 Years During The Covid-19 Pandemic
Authors: Wolińska Weronika , Gebel Agata , Mroczek Bożena 
Published: January 2022

Abstract
Background: Insomnia is the most recognized sleep disorder. The time of the COVID-19 pandemic brings with it new challenges. During the COVID-19 pandemic, maintaining sleep hygiene is highly recommended as it helps to strengthen the immune system, and people infected with COVID-19 may be more prone to sleep problems.The aim of this study was to determine the incidence of insomnia among people aged 18-25 during the COVID-19 pandemic. Methods: The study involved 302 individuals. It was conducted using Google Forms. The mean age of the respondents was 23 ± 1.84 years. The research instruments used in the study were the Athenian Insomnia Scale (AIS), the Beck Depression Inventory (BDI), and the author’s questionnaire concerning sociodemographic data. Results: Insomnia was found in 29.5% (n = 89) of the respondents. Higher mean values (8 ± 4.19) in the AIS were noted in the group of people with higher education and those currently studying. Moderate depression was demonstrated in 12.6% (n = 38) of the subjects. One third (30.1%; n = 91) of the respondents indicated greater sleep problems during the COVID-19 pandemic than before. Conclusions: Insomnia and depression are significant problems in the study group of 18-25 year olds. Therefore, psychological and psychiatric care should be extended to this group of young people.
Spatio-temporal Variability of Lightning Climatology and Its Association With Thunderstorm Indices Over India
Authors: Mondal Unashish , Panda Subrat Kumar , Das Someshwar , Sharma Devesh 
Published: January 2022

Abstract
Lightning is an electrical discharge - a'spark' or 'flash' as charged regions in the atmosphere instantly balance themselves through this discharge. It is a beautiful and deadly naturally occurring phenomenon. In June 2020, more than a hundred people died in the state Bihar of India only in three days’ span due to lightning events. In this work, Lightning Imaging Sensor (LIS) information from the Tropical Rainfall Measuring Mission (TRMM) satellite with a very high spatial resolution of 0.1 X 0.1 degree has been utilized to create the climatology of India for 16 years from 1998 to 2013. Diurnal, monthly, and seasonal variations in the occurrence of lightning flash rate density have also been analyzed. TRMM satellite low-resolution monthly time series (LRMTS) with 2.5-degree resolution datasets have been used for lightning trend analysis. The diurnal lightning event mainly occurs in the afternoon/evening (1400-1900 Hrs) time duration around 0.001 flashes/km2/hr. The highest lightning occurred in May (0.04 flashes/km2/day) and the least in December (0.005 flashes/km2/day). The distribution of lightning flash counts by season over India landmass is mainly in pre-monsoon (MAM) ranges from 0.248 – 0.491 flashes/km2/day, and monsoon (JJA) ranges from 0.284 – 0.451 flashes/km2/day and decreases afterward. Spatially, the distribution of lightning flashes mainly at North-Eastern region along with Bangladesh, Bihar, Jharkhand, Orissa, and Jammu & Kashmir region. The CAPE and K Index have positively correlated with the flash rate density seasonally but CAPE is more significantly correlated. This study also focused on finding of lightning hotspots region of India district wise and Rajouri district in Jammu and Kashmir got the highest lightning with 121 flashes/km2/yr.
In-Silico Assisted Development of Supersaturable Preconcentrated Isotropic Mixture of Atazanavir for Augmenting Biopharmaceutical Performance in Presence of H2-Receptor Antagonist
Authors: Sethi Sheshank , Rana Vikas 
Published: January 2022

Abstract
The therapeutic potential of atazanavir (BCS Class II drug), a highly selective inhibitor of human immunodeficiency virus (HIV-1) has been largely limited due to its low intrinsic solubility at elevated pH resulting in low oral bioavailability. Thus, the current work describes the systematic development, optimization and evaluation of HPMC-AS based supersaturable preconcentrate isotropic mixture (SP-IM) containing long chain triglyceride to improve intestinal lymphatic transport and augment oral bioavailability of atazanavir (ATZ). A D-optimal mixture design was employed for optimization of plain IM containing Corn Oil, Oleic acid, Tween 80 and Propylene Glycol, evaluating CQAs like particle size, PDI, self-emulsification time, % transmittance and drug content. In-silico analysis and in-vitro supersaturation test facilitated the selection of HPMC-AS as a best suited polymeric precipitation inhibitor (PPI) for formulating ATZ loaded SP-IM (ATZ-SP-IM). In-vitro dissolution data indicated that ATZ-SP-IM exhibits superior performance in 0.025N HCl and pH 6.8 over pure drug. Ex-vivo permeation and in-vivo pharmacokinetic study of ATZ-SP-IM corroborated enhanced permeation (2.03 fold) and improved drug absorption via lymphatic transport in wistar rats. Further, the pharmacokinetic performance of ATZ-SP-IM was not affected in presence of H2 receptor antagonist. Therefore, the results showed that ATZ-SP-IM can significantly improve the biopharmaceutical attributes of ATZ so as to lay a foundation of further research on the new dosage form of ATZ.