bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transforming Used Palm Oil into Biogasoline Investigation of Activity and Selectivity of Mesoporous Silica Catalyst for Hydrocracking Process
Authors: Suseno Ahmad , Wijaya Karna , Heraldy Eddy , Hakim Lukman , Saputri Wahyu Dita 
Published: February 2021

Abstract
Research on mesoporous silica synthesis using CTAB template as well as its activity and selectivity in the hydrocracking of used palm oil has been conducted. This research was initiated with the synthesis of mesoporous silica material by varying the TEOS to CTAB ratios at 2:1, 4:1, and 8:1, later calcined at varying temperatures of 300, 350, and 400 oC. The products were characterized by XRD, SEM-EDX, and GSA. The hydrocracking was performed with a feed ratio of 1:100 and H2 gas flow rate of 20 mL/min for 1 hour. The results showed that the highest activity of mesoporous silica was found in the TEOS:CTAB ratio of 8:1 and calcination temperature of 500 oC. The mesoporous silica produced had higher crystallinity, higher percentages of Si, and larger pore size. The catalyst activity test showed that the application of mesoporous silica increased the amount of biogasoline fraction (C5-C12) produced at the optimum temperature condition of 350°C using the MCT81-500 catalyst.
Grade Diagnosis&nbsp;of Human Glioma Based on Fingerprint&nbsp;and Artificial Neural Network
Authors: Peng Wenyu , Chen Shuo , Kong Dongsheng , Zhou Xiaojie , Lu Xiaoyun , Chang Chao 
Published: February 2021

Abstract
BackgroundThe World Health Organization (WHO) grade diagnosis of cancer is essential for surgical outcomes and patient treatment. Traditional pathological grading diagnosis depends on dyes or other histological approaches, which are time-consuming (usually 1-2 days), resource-wasting, and labor-intensive. Fourier transform infrared (FTIR) spectroscopy is a rapid and nondestructive technique that has been widely used for detecting the molecular component changes, which relies on the resonant frequencies absorbance of the molecular bonds.MethodsTo overcome the disadvantages of traditional pathological diagnosis, this paper proposed a novel diagnostic method based on FTIR and artificial neural network (ANN). Firstly, the spectra of high- and low-grade human glioma that without dye were collected by FTIR spectrometer, then the raw data preprocessed with baseline correction and amide I (1649 cm-1) normalization before input into the input-layer of the ANN, after the nonlinear conversion of the neurons in the hidden-layers, the categories were presented in the output-layer. Corresponding to the decrease of the loss function, the weights of the net updated continuously, and finally, the optimized model has the power of prediction for new samples. ResultsAfter training on 6225 spectra sourced from 77 glioma patients, the ANN model reached the prediction accuracy, specificity and sensitivity evaluation metrics above 99%, which was much superior to the common classification method of principal component analysis-linear discriminate analysis (PCA-LDA) (the prediction accuracy, specificity and sensitivity are only 87%, 89% and 86%, respectively). Moreover, rather than the lipid range of 2800-3000 cm-1, the ANN learned the fingerprint characteristics of the infrared spectrum to classify the major histopathologic classes of human glioma. Especially, the diagnosis process of the novel method only requires several minutes. Compared to the traditional pathological diagnosis, the efficiency raises almost 500 times.ConclusionsThe infrared range of fingerprint is the major indicator for cancer progression, and the ANN-based diagnosis method can be streamlined, and create a complementary pathway that is independent of the traditional pathology laboratory.
Effect of the Dissolving Method on the Dissolution of Dissolving Pulp Cellulose Fibers with Different Dried-States in Different NaOH/additives Aqueous Solutions
Authors: Kong Weiwei , Yu Guangrong , xing Jiong , Kong Rui , Liu Meihua , SHI Yan 
Published: February 2021

Abstract
A NaOH/urea (or thiourea) solvent system capable of dissolving cellulose at lower temperatures is a breakthrough in cellulose chemistry, and it was reported that cellulose rapidly dissolved when it was added to a precooled aqueous solution of sodium hydroxide (NaOH) and additives. Therefore, this work compared the effectiveness of the direct dissolution method and freezing-thaw method in dissolving pulp fiber and pure cellulose. Three aqueous solutions were examined: 7% NaOH/12% urea, 9.5% NaOH/4.5% thiourea, and 8% NaOH/8% urea/6.5% thiourea. The dissolving capacity of three NaOH/additives aqueous solutions was analyzed by polarized optical microscopy and the dissolved cellulose proportion was determined. The results showed that the never-dried softwood dissolving pulp and bamboo dissolving pulp achieved better dissolution using freezing-thaw method than using direct dissolution method in the three aqueous solutions. The dissolving method had a negligible effect on the dissolution of each dissolving pulp in the 8% NaOH/8% urea/6.5% thiourea solution. It seems that the direct dissolution method was more suitable for oven-dried microcrystalline cellulose with a low degree of polymerization (DP) and the freezing-thaw method was more suitable for never-dried pulp cellulose fibers with a higher DP.
Mesenchymal Stem Cell Immunomodulation: A Novel Intervention Mechanism in Cardiovascular Disease
Authors: Wang Yueyao , Qi Zhongwen , Yan Zhipeng , Ji Nan , Yang Xiaoya , Gao Dongjie , Zhang Junping , Li Meng 
Published: February 2021

Abstract
Mesenchymal stem cells (MSCs) belong to the family of pluripotent stem cells, which have an obvious multi-directional differentiation potential and can regulate the immune response of the organism by influencing immune cell subsets, thus they have excellent prospects for application in inflammation, immune diseases, and organ transplantation. Numerous studies have shown that MSCs are a promising strategy for the treatment of cardiovascular disease by modulating immune cell subsets and coordinating local and systemic innate and adaptive immune responses, thereby enabling the formation of a stable inflammatory microenvironment in damaged cardiac tissues. In this review, we summarize the mechanisms by which MSCs interact with immune cells and exert immunomodulatory effects, and explain the therapeutic effects of this mechanism in the treatment of cardiovascular diseases. A feasibility analysis is provided for the application of MSCs in cardiovascular diseases.
Variations in Soil Properties Rather than Functional Gene Abundances Dominate Soil Phosphorus Dynamics under Short-Term Nitrogen Input
Authors: Han Bing , Li Jingjing , Liu Kesi , Zhang Hui , Wei Xiaoting , Shao Xinqing 
Published: February 2021

Abstract
Background and aims Microorganisms play a vital role in regulating soil phosphorus (P) dynamics in terrestrial ecosystems. However, how nitrogen (N) inputs trigger the functional traits of P transformation-related microorganisms to affect P fates in soil needs to be explored further. Our aims were to reveal the soil microbial functional profiles for P turnover in response to N input and to explore the relationships between soil P dynamics, soil properties and functional genes.Methods We collected soil samples from field experiments with three levels of N input over three years in an alpine meadow of the Qinghai-Tibet Plateau to determine soil P dynamics and other properties and functional genes via metagenomics.Results The soil available P and microbial biomass P were significantly affected by N inputs and significantly associated with soil properties (including soil pH, alkaline phosphatase activity, and soil total N and NO3--N contents). Meanwhile, high N input decreased the relative abundance of the pstS gene, and low N input reduced the relative abundances of ugpQ and C-P lyase genes. The pstS gene was a determinant of soil microbial biomass P and significantly correlated with soil pH. Moreover, Alphaproteobacteria with C-P lyase and Actinobacteria related to alkaline phosphatases and phosphate-specific transport were the most abundant taxa but not affected by N input.Conclusions We found relationships between the pstS gene, microbial biomass P and soil pH, and the microbial functional gene abundance was less important than soil properties in regulating soil P dynamics under short-term N inputs.
Urbanization decreased the multitrophic fish richness and ecosystem functioning in neotropical streams
Authors: Moi Dieison André , de Mello Franco Teixeira 
Published: February 2021

Abstract
Urbanization is regarded a major global threat to biodiversity and ecosystem functioning. Streams are among the most severely affected ecosystems due to worldwide urbanization. An increase in urbanization causes water quality deterioration and loss of habitat heterogeneity in streams. However, it is unclear how water quality deterioration and loss of habitat heterogeneity due to urbanization affect multitrophic diversity and performance of ecosystem functioning. We conducted 2,400 samplings in six streams across Uruguay to investigate how increases in urbanization (area and percentage of urbanization) affect the richness of three trophic groups of fishes and the standing stock biomass of the streams. We investigated the direct and indirect effects, mediated by water quality deterioration and habitat heterogeneity of the urbanization on carnivore, omnivore, and detritivore fish richness and standing stock biomass of streams. The increase in urbanization (area and percentagem) in the streams significantly decreased the richness of carnivores, omnivores, and detritivores fishes. The increase in urbanization also strongly decreased habitat heterogeneity and increased water quality deterioration, which indirectly decreased the carnivore, omnivore, and detritivore fish richness. Urbanization also had strong negative effects on the standing stock biomass of the streams. Our study illustrates that urbanization promotes water quality deterioration and loss of habitat heterogeneity in streams, which indirectly causes loss of multitrophic fish richness and biomass production of streams.
Advanced Treatment of Effluent Extended Aeration Process Using Biological Aerated Filter (BAF) With Natural Media: Modiﬁcation in Media, Design, and Backwashing Process
Authors: Toolabi Ali , malakootian mohammad , hosseini saeed 
Published: February 2021

Abstract
Due to their tolerance of hydraulic and organic shocks, biological aerated filters (BAFs) have high filtration efficiency and are suitable for the treatment of complex and sanitary wastewater. In this study, for the first time, natural media of date kernel from Bam city was used as the BAF reactor media, with a meshing sand filter separated by a standard metal grid from the natural filter section used at the end of the reactor. This can be considered an innovation in the media and filtration. Aeration in the related reactor with 160 cm height was performed bilaterally as up-flow and continuously by nozzles throughout the reactor media. In this work, the actual effluent of the hospital wastewater treatment plant was employed as the inflow wastewater to the reactor, and its organic and inorganic parameters were measured before and after the treatment by the BAF reactor. The backwashing process was also studied in three ways: bottom backwashing (TB), top backwashing (BB), and top and bottom backwashing (TBBS), to determine the amount of water consumed and to achieve the desired result. According to the results obtained in this study, the removal efficiencies of inorganic and microbial contaminants, amoxicillin and azithromycin were obtained as follows: BOD5: 98.48%, COD: 92.42.8%, NO-3: 99.4%, P: 93.3%, Coliforms: 97%, Color: 42.8%, Turbidity: 95%, Sulphate: 30%, TSS: 98.9%, Amoxicillin: 20% and azithromycin: 13%. The TBBS method was selected as the optimal method. The effect of backwashing effluent return was evaluated on the results of the parameters. The concentration of most of the outflow parameters was less or in accordance with EPA agriculture standard 2012.
Detecting Urban Landscape Factors Controlling Seasonal Land Surface Temperatures: From the Perspective of Urban Function Zones
Authors: Li Tong , Xu Ying , Yao Lei 
Published: February 2021

Abstract
Understanding of the impact on the thermal effect by urbanization is of great significance for urban thermal regulation, it is essential to determine the relationship between the urban heat island (UHI) effect and the complexities of urban function and landscape structure. For this purpose, we conducted a case research in the metropolitan region of Beijing, China, and >5000 urban blocks assigned with different urban function zones (UFZs) were identified as the basic spatial analysis units. Seasonal land surface temperature (LST) retrieved from remote sensing data were used to represent the UHI characteristics of the study area, and surface biophysical parameters, building forms, and landscape pattern metrics were selected as the urban landscape factors. Then, the effects of urban function and landscape structure on the UHI effect were examined by spatial regression models. The results indicated that: (1) Significant spatio-temporal heterogeneity of LST were found in the study area, and there was obvious temperature gradient with “working-living-resting” UFZs; (2) All the types of urban landscape factors showed significant contribution to seasonal LST, and sorted by surface biophysical factors > building forms > landscape factors. However, their contributions varied in different seasons; (3) The major contribute factors showed a certain difference due to the variation of urban function and landscape complexity. This study expands understanding on the complex relationship among urban landscape, function, and thermal environment, which could benefit urban landscape planning for UHI alleviation.
Predictive Model and Feature Importance for Early Detection of Type II Diabetes Mellitus
Authors: Adua Eric , Kolog Emmanuel Awuni , Afrifa-Yamoah Ebenezer , Amankwah Bright , Obirikorang Christian , Anto Enoch Odame , Acheampong Emmanuel , Wang Wei , Tetteh Antonia Yarney 
Published: February 2021

Abstract
BackgroundAccurate prediction and early recognition of type II diabetes (T2DM) will lead to timely and meaningful interventions, while preventing T2DM associated complications. In this context, machine learning (ML) is promising, as it can transform vast amount of T2DM data into clinically relevant information. This study compares multiple ML techniques for predictive modelling based on different T2DM associated variables in an African population, Ghana. MethodsThe study involves 219 T2DM patients and 219 healthy individuals who were recruited from the hospital and the local community, respectively. Anthropometric and biochemical information including glycated haemoglobin (HbA1c), body mass index (BMI), blood pressure, fasting blood sugar (FBS), serum lipids [(total cholesterol (TC), triglycerides (TG), high and low-density lipoprotein cholesterol (HDL-c and LDL-c)] were collected. From this data, four ML classification algorithms including Naïve-Bayes (NB), K-Nearest Neighbor (KNN), Support Vector Machines (SVM) and Decision Tree (DT) were used to predict T2DM. Precision, Recall, F1-Scores, Receiver Operating Characteristics (ROC) scores and the confusion matrix were computed to determine the performance of the various algorithms while the importance of the feature attributes was determined by recursive feature elimination technique.ResultsAll the classifiers performed beyond the acceptable threshold of 70% for the Precision, Recall, F-score and Accuracy. After building the predictive model, 82% of diabetic test data was detected by the NB classifier, of which 93% were accurately predicted. The SVM classifier was the second-best performing classifier which yielded an overall accuracy of 84%. The non-T2DM test data yielded an accurate prediction score of 75% from the 98% of the proportion of the non-T2DM test data. KNN and DT yielded accuracies of 83% and 81%, respectively. NB has the best performance (AUC=0.87) followed by SVM (AUC= 0.84), KNN (AUC= 0.85) and DT (AUC= 0.81). The best three feature attributes, in order of importance, are HbA1c, TC and BMI whereas the least three importance of the features are Age, HDL-c and LDL-c.ConclusionBased on the predictive performance and high accuracy, the study has shown the potential of ML as a robust forecasting tool for T2DM. Our results can be a benchmark for guiding policy decisions in T2DM surveillance in resource and medical expertise limited countries such as Ghana.
Wheat Root and Rhizosphere Microbiome Structures and Functions Along Plant Growth
Authors: Usyskin-Tonne Alla , Minz Dror , Hadar Yitzhak 
Published: February 2021

Abstract
Background Roots select their associated microbiome and affect its composition and activities through exudates that provide a nutrient-rich environment based on distance from the root. Root-exudation patterns depend on the plant's developmental stage. We followed field-grown wheat from emergence to spike maturation and compared the structure and functions of the microbiomes in two niches: adjacent, root-associated bacteria and the rhizosphere. The effects of growth stage on root-associated and rhizospheric communities structure and functions were investigated to enhance our understanding of plant–microbe interactions. Results A significant impact of wheat developmental stage during the transition from vegetative growth to spike formation was observed on structure and functions of both root-associated and rhizosphere microbiomes. On the root surface, abundance of the well-known wheat colonizers Proteobacteria and Actinobacteria decreased and increased, respectively, during spike formation, whereas abundance of Bacteroidetes was independent of spike formation. Three microbiome functional clusters were specifically associated with root proximity: (1) biofilm and sensorial movement; (2) antibiotic production and resistance; and (3) carbon biosynthesis, degradation and transporters, and amino acid biosynthesis and transporters. Interestingly, in the root-associated microbiome, genes related to all of these functions were influenced by spike formation. Abundance of genes related to nine other functions (lipopolysaccharide transporter and biosynthesis, beta-lactam resistance, metabolism of methane, alanine-aspartate-glutamate and arginine-proline, and biosynthesis of peptidoglycan, lysine and enediyne antibiotics) was significantly influenced by spike formation in both roots and rhizosphere. All of these genes were abundant in the rhizosphere, more so before spike formation when root exudation is high, supporting the notion that some of the root exudates are not fully utilized by the root-associated bacteria and subsequently diffuse into the surrounding soil, creating the rhizosphere. Conclusions We demonstrated functional division in the microbiome of the wheat root zone in both time and space: pre- and post-spike formation and root-associated vs. rhizospheric niches. The responses of the root microbiome were driven by both the plant and the microbial physiology and activities, both of which respond to environmental cues. These findings shed light on the dynamics of plant–microbe and microbe–microbe interactions in the root zone.
Effect of Mn Doping on The Structural, Optical, Magnetic Properties and Antibacterial Activity of ZnO Nanospheres
Authors: JEYASINGH EBENEZAR , Charles Kelvin Adaikalam , Thangaraj Pandiyarajan , Chandrasekaran Karthikeyan , Viswanathan Mangalaraja Ramalinga 
Published: February 2021

Abstract
In this work, a systematic study of structural, optical, magnetic and antibacterial properties of Mn doped ZnO has been investigated. Zinc oxide (ZnO) and Mn2+ doped zinc oxide (ZnMnO) nanoparticles (NPs) were prepared through co-precipitation method. The X-ray diffraction studies confirmed that the synthesize nanoparticles did not modify the crystal structure upon Mn doping, but the microstructural parameters were changed considerably while increasing the concentration of Mn dopant. The HRTEM images showed that the ZnO NPs were exhibited nanospheres like morphology and a reduction in the average particle size from 41 nm to 33 nm were observed upon Mn2+ doping. The elemental composition of Zn, Mn and O atoms were identified by EDAX spectra. The Zn-O stretching bands were observed at 539 and 525cm-1 in the FTIR spectra and, the zinc and oxygen vacancies defects were confirmed by PL spectra. From the UV-Vis spectra, the band gap was estimated as 2.7 eV for pure and 2.9 eV for Mn doped ZnO NPs. The Mn doped ZnO NPs showed greater antibacterial effect than the pure ZnO NPs. The magnetization measurements for Mn doped ZnO samples under room temperature ferromagnetism (RTFM) showed the ferromagnetic phase that could originated from the interactions between Mn2+ ions and oxygen vacancies and the defects incorporated in the ZnO matrix.
Estimation of The Electrical and Dielectric Properties For Se98Te2 and Se96Te2X2 (X = Zn and Cd) Amorphous Films.
Authors: Shakra Amira , Fadel M. , Kalila A.E. 
Published: February 2021

Abstract
Bulk glassy Se98Te2 and Se96Te2X2 (X = Zn and Cd) were prepared by melting quenching method. Thin films of various thicknesses (200 – 670 nm) were obtained by the thermal evaporation method. The structure of the prepared compositions was investigated by X-ray and EDX analysis. We studied the effect of Zn and Cd addition on the electric and dielectric properties of Se98Te2 thin films. Our measurements were studied in the temperature range (298-323K) below the glass transition temperature and frequency range (100 Hz-1 MHz). DC conductivity showed a single conduction mechanism by hopping of charge carriers at the band edges for the studied system. The dependence of Ac conductivity on frequency is linear with frequency exponent s lies very close to unit and is independent of temperature. This can be explained by the correlated barrier hopping (CBH) model. The dielectric constant ε1 and dielectric loss ε2 noticed to decrease with frequency and increase with temperature. The maximum barrier height Wm was calculated according to Guinitin.