bluuebunny/crossref_metadata_2025_split huggingface dataset:
The influence of individual differences and local ecological conditions on emotional empathy, cognitive empathy, and harm avoidance towards nonhuman animals
Authors: Figueredo Aurelio José , Steklis Netzin Gerald , Peñaherrera-Aguirre Mateo , Fernandes Heitor Barcellos Ferreira , de Tomás Cabeza , Salmon Catherine , Chaves María Gabriela Hernández , Araya Siu Fong Acón , Pérez-Ramos Marisol , Armenta Martha Frías , Verdugo Víctor Corral , Aragonés Juan Ignacio , Sevillano Verónica 
Published: November 2022

Abstract

Increased interest in the study of the relationships between human and nonhuman animals over the past few decades has often focused on what factors shape people’s attitudes and treatment towards nonhuman animals. Some scholars have focused on features of the nonhuman animals (cuteness, intelligence, and utility) and how those features predict human behavior while others have concentrated more on possible human individual differences that influence their attitudes and positive or negative actions towards nonhuman animals. In this study, with 978 participants from five different cross-cultural study sites (Arizona, California, Costa Rica, Mexico, and Spain), we utilized three superordinate categories of animal species representing three “Concentric Circles” surrounding our own (from
Kith-Kin
, to
Domestic
, to
Wild
Animals) to investigate the influence of individual differences and local ecological conditions on empathy and harm avoidance scores across these categories. Specifically, these variables were as follows: (1) a set of variables representing the cross-cultural study sites; (2) a second set of sociodemographic predictors; (3) a developmental Animal Exposure factor; (4) a Dark Inventory factor; (5) an Interpersonal Aggression factor; (6) a KithKin-Empathy factor, measuring emotional and cognitive empathy towards
Kith-Kin
animals; (7) a Domestic-Empathy factor, measuring emotional and cognitive empathy towards
Domestic
animals; (8) a Wild-Empathy factor, measuring emotional and cognitive empathy towards
Wild
animals; and (9) a Harm Avoidance factor. A Cascade Model approach allowed us to integrate many factors (individual differences and local ecological conditions) together in explaining empathy and harm avoidance that have previously been examined only in mutual isolation.
Investigation of thermal stability and crystallization mechanism of Er0.03(GeTe)0.97 phase change material
Authors: Gu Han , Wu Weihua , Xu Shengqing , Zhou Xiaochen , Shen Bo , Zhai Jiwei 
Published: November 2022

Abstract
Er-doped GeTe thin films with different concentrations were prepared by magnetron co-sputtering technique. The chemical compositions of Er0.03(GeTe)0.97 thin films were measured by energy dispersive spectroscopy. The difference between the phase transition behavior of Er0.03(GeTe)0.97 and pure GeTe films was investigated by in-situ electrical measurements. The crystallization temperature, crystallization resistance and optical band gap of GeTe thin films obviously increase with the doping of Er elements. X-ray diffraction and x-ray photoelectron spectroscopy show that proper Er doping can inhibit grain growth and reduce grain size. The surface morphology of Er0.03(GeTe)0.97 and pure GeTe films were observed by atomic force microscopy and it was found that the surface of the film becomes smoother after Er doping. The flatter surface of Er0.03(GeTe)0.97 material means better interfacial properties and reliability. All the outcomes indicate that the proper doping of Er element can effectively improve the comprehensive performance of GeTe thin films for high thermal stability applications.
Eggshell-Graphene Oxide Layer as Membrane Filtration for Removal Methylene Blue in Waste Water
Authors: Maulida G , Fauziah Y , Syakir N , Fitrilawati  
Published: November 2022

Abstract
Eggshell (ES) membrane is a semipermeable membrane that is insoluble in water and has a high surface area. We modified ES membranes with graphene oxide (GO) using self-assembled technique and used it to remove dye pollutants such as methylene blue (MB) in water. The ES membranes were obtained from fresh eggs that have been removed from albumen and yolk, then immersed in 15% acetic acid for 30 minutes. The ES membranes were immersed in 0.5 mg/mL dispersed GO and ultrasonicated for 3 hours. The modified ES-GO membrane was then used to filter 5 mg/L MB solutions. Filtration of MB solution was performed by pouring the solution over the ES-GO membrane with a help of constant pressure of 45 psi. We found that the modified ES-GO membrane could filter MB up to 33.53% and reduce MB concentration from 4.91 mg/L to 3.53 mg/L. The result of membrane permeability is 2.488 x10−3 darcy and the flow rate of the filtration is relatively constant about 4 mL/s.
Photoactivity Enhancement of TiO2 Nanoparticle-decorated ZnO as a Photocatalyst in Methylene Blue Degradation
Authors: Ramadhika L N , Suryaningsih S , Aprilia A 
Published: November 2022

Abstract
Zinc Oxide (ZnO) and Titanium Dioxide (TiO2) are metal oxides that are commonly used as photocatalysts material due to photoactivity characteristics. ZnO has a better reduction potential, and high electron mobility, but has a lower contact surface area than TiO2. On the other side, TiO2 has a better photoactivity to degrade pollutants referring to high surface area but has lower electron mobility compared to that ZnO. The combination of these two metal oxides is estimated can produce a better photocatalytic activity due to the advantages of each characteristic. Therefore, in this research, the ZnO-TiO2 (1:1) was prepared and investigated. ZnO nanoparticle was synthesized by the sol-gel method using zinc acetate dihydrate as a precursor, before calcining process, anatase TiO2 powder was added to form the composite. Structural, morphological, and optical characteristics of composite powders were analyzed by using XRD, TEM, UV-Vis Spectroscopy, and PL Spectroscopy. The concentration degradation of methylene blue in a solution containing composite material was observed to determine the photocatalytic activity under UV light irradiation for 30 minutes. The XRD spectrum shows the anatase phase of TiO2 and hexagonal wurtzite of ZnO crystal structure. Based on TEM imaging ZnO nanoparticles were attaching to TiO2 surfaces estimated due to van der walls bond. The ZnO/TiO2 shows a better photoactivity up to 20 minutes reaction with a higher degradation constant rate that indicates faster methylene blue degradation.
Effect of Gas Sources on the Oxygen Transfer Efficiency Produced by Fine Bubbles Generator
Authors: Hanam E S , Sofia D R , Azhary S Y , Panatarani C , Joni I M 
Published: November 2022

Abstract
Fine bubbles (micro to nanometer-sized) have rapidly gained popularity in academia and industry due to their unique properties, such as their high surface area, stability, and longevity. In this study, the performance of oxygen transfer rate efficiency in fine bubbles with high purity oxygen and atmospheric air was analyzed. In this study, the developed fine bubbles generator with power requirement 300 watt was used to evaluate the production of fine bubbles and oxygen transfer efficiency at two type gas sources i.e., ambient air and high-purity oxygen in the small bench aqueous media (5 L water tank). The fine bubbles generator was set up at the pressure in 50 psi and gas flow rate at 0.3 L/min to produce fine bubbles in water medium. The effect of water recirculation process in the bubbles production was measured using particles size analyzer (PSA), zeta potential and dissolved oxygen (DO) meter to measure temperature and dissolved oxygen on the water. Dissolved Oxygen (DO) measurement shows the saturation value of oxygen concentration in water, for high purity oxygen is 30 mg/L higher than air which has a value of 8.64 mg/L. This causes the efficiency of gas transfer in high-purity oxygen to reach 72.09% higher than ambient air at 35.39%. The particle size distribution shows that the mean size of bubbles after 10 minutes recirculation was 465.5 nm and 599.9 nm correspondingly for ambient air and oxygen gas source. High purity oxygen also affect to the zeta potential value tends to be more negative than in ambient air. The type of high-purity oxygen gas can increase the efficiency of the oxygen transfer rate so that the gas containing high-purity oxygen increases the volumetric oxygen transfer rate coefficient which is 2 times higher than using ambient air.
Effect of Protonation Doping of Polyaniline Electrodes using Hydrochloric Acid on Its Pseudocapacitor Capacitance
Authors: Fitriantika L A , Fitrilawati  , Syakir N 
Published: November 2022

Abstract
Pseudocapacitor is a supercapacitor that can store charge faradically through a reversible redox reaction. Polyaniline (PANi) is one of the promising active materials for pseudocapacitor electrodes since it can produce theoretical specific capacitance up to 750 F/g. We prepared leucomeraldine base polyaniline (LB-PANi) electrodes by deposition of dissolved LB-PANi powder in N,N-Dimethylformamide (DMF) using spraycoating technique. The LB-PANi electrodes was then doped with 1 M HCl through protonation process to obtain emeraldine salt polyaniline (ES-PANi) electrodes. We used both electrode materials and 1 M KCl to prepare a symmetrical sandwich supercapacitor model of <LB-PANi|KCl|LB-PANi> and <ES-PANi|KCl|ES-PANi>, as well as measured their performance. The results show a significant increase of the specific capacitance of PANi supercapacitor from 15.02 F/kg to 1876.87 F/kg when the electrodes of the LB-PANi were changed with the ES-PANi electrodes.
Effect of Fe Magnetic Impurity to the Crystal Structure and Magnetic Properties of Eu
1.83+y
Ce
0.17−y
Cu
1−y
Fe
y
O
4+α−δ
Authors: Anggia H D , Rochman L P , Pratama R , Maryati Y , Syakuur M A , Widyaiswari U , Sari D P , Saragi T , Risdiana  
Published: November 2022

Abstract
In the overdoped regime of superconductors, both electron- and hole-doped superconductors exhibit intriguing phenomena like the Quantum Critical Point. Other phenomena, such as cooper-pair breaking and stripe pinning, can be observed by eliminating superconductivity by the addition of impurities. In this study, we investigate the crystal structure and magnetic properties of electron-doped superconducting cuprates of Eu2-x+y
Ce
x-y
Cui1-y
Fe
y
O4+α-δ
in the overdoped regime of x = 0.17 for Ce doping with y = 0.005, 0.01 and 0.03 for Fe impurity. The material has a tetragonal T’ structure that matches the ECCO crystal structure, according to the XRD analysis of the crystal structure. The addition of magnetic impurity has no effect on the structure but does decrease the lattice parameter. SQUID was used to measure the magnetic susceptibility at low temperatures between 2 K and 30 K. The spin-glass was observed at y = 0.03, due to the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction as shown in a hole-doped system. Due to the significant contribution from the magnetic moment of the Fe ion, the addition of Fe concentrations increases the effective magnetic moment. The conduction layer’s spin correlation of Cu is dramatically disrupted by the addition of Fe, resulting in the breakage of the copper-pair and the elimination of superconductivity.
Pressure-dependent electronic properties in the rocksalt structure of lithium fluoride: A DFT Study
Authors: Gunawan A F , Astuti F 
Published: November 2022

Abstract
Density functional theory (DFT) calculation are carried out for the cubic structure of lithium fluoride (LiF). Variation of applied pressure is considered, ranging from 0 to 120 GPa with an increment of 30 GPa based on PBE and SCAN functional scheme. In zero pressure and energy-cut off 100 Ry, best result on lattice parameter is obtained by using PBE functional with the value of 4.06 Å, while SCAN functional overestimates the lattice parameter at 4.15 Å. The insulating gap of both results is significantly underestimated with 8.82 eV and 9.26 eV for PBE and SCAN functionals respectively. With the applied hydrostatic pressure, the lattice parameter are reduced exponentially, while still retaining the insulating behaviour with an increased value of gap energy.
First-principle calculation of silicon carbide (SiC) for the superhard material applications
Authors: Alfanny D , Piliang M Z , Ramadhan M R 
Published: November 2022

Abstract
Silicon carbide is considered to be one of the superhard material with the microhardness value more than 20 GPa. Here we report the theoretical study based on density functional theory methods on the SiC system. Three different semilocal functionals of LDA-PZ, GGA-PBE, and SCAN are utilized. The cubic crystal structure of SiC are used in all of our calculations that is fully-relaxed to obtain realistic description of both structural and electronical parameters. For the lattice parameter and insulating gap estimation, SCAN functional gives the best comparison with the experimental value with 4.34 Å and 1.67 eV respectively. The calculated Vickers hardness formula based on the SCAN functional gives the value of 36 GPa
Development of a mass spectrometer for high-precision mass measurements of superheavy elements at JINR
Authors: Yavor M.I. , Gall N.R. , Muradymov M.Z. , Pomozov T.V. , Kurnin I.V. , Monakov A.G. , Arsenev A.N. , Oganessian Yu. Ts. , Karpov A.V. , Rodin A.M. , Krupa L. , Dickel T. , Plaß W.R. , Scheidenberger C. 
Published: November 2022

Abstract
A multiple-reflection time-of-flight (MR TOF) mass spectrometer for mass measurements of superheavy elements is currently being developed for an experimental cave of the Superheavy Element Factory at the Joint Institute for Nuclear Research in Dubna. Its conceptual and ion-optical designs are described in the present paper. The spectrometer is designed to achieve a mass measurement accuracy of 10^-7 at low measurement statistics (~5 events) for nuclides with half-lives down to 50 ms. To reach this goal, a new generation MR TOF analyzer with an ultra-high mass resolving power and highly-stable power supplies has been designed. An advanced set of ion-optical solutions for preparation and mass separation of the sample and calibrant ion beams is proposed for the spectrometer: a radiofrequency multiplexer trap separator of charge states, high vacuum quadrupole filters with two-stage differential pumping, operated in the “beat node coincidence” mode, a focused beam transport through the gate valve gaps, as well as a fullerene soot electron ionization calibrant ion source.
Agroecosystem engineering extended from plant-microbe interactions revealed by multi-omics data
Authors: Fujiwara Fuki , Miyazawa Kae , Nihei Naoto , Ichihashi Yasunori 
Published: November 2022

ABSTRACT
In an agroecosystem, plants and microbes coexist and interact with environmental factors such as climate, soil, and pests. However, agricultural practices that depend on chemical fertilizers, pesticides, and frequent tillage often disrupt the beneficial interactions in the agroecosystem. To reconcile the improvement of crop performance and reduction in environmental impacts in agriculture, we need to understand the functions of the complex interactions and develop an agricultural system that can maximize the potential benefits of the agroecosystem. Therefore, we are developing a system called the agroecosystem engineering system, which aims to optimize the interactions between crops, microbes, and environmental factors, using multi-omics analysis. This review first summarizes the progress and examples of omics approaches, including multi-omics analysis, to reveal complex interactions in the agroecosystem. The latter half of this review discusses the prospects of data analysis approaches in the agroecosystem engineering system, including causal network analysis and predictive modeling.
PlDBPred: a novel computational model for discovery of DNA binding proteins in plants
Authors: Pradhan Upendra Kumar , Meher Prabina Kumar , Naha Sanchita , Pal Soumen , Gupta Ajit , Parsad Rajender 
Published: November 2022

Abstract
DNA-binding proteins (DBPs) play crucial roles in numerous cellular processes including nucleotide recognition, transcriptional control and the regulation of gene expression. Majority of the existing computational techniques for identifying DBPs are mainly applicable to human and mouse datasets. Even though some models have been tested on Arabidopsis, they produce poor accuracy when applied to other plant species. Therefore, it is imperative to develop an effective computational model for predicting plant DBPs. In this study, we developed a comprehensive computational model for plant specific DBPs identification. Five shallow learning and six deep learning models were initially used for prediction, where shallow learning methods outperformed deep learning algorithms. In particular, support vector machine achieved highest repeated 5-fold cross-validation accuracy of 94.0% area under receiver operating characteristic curve (AUC-ROC) and 93.5% area under precision recall curve (AUC-PR). With an independent dataset, the developed approach secured 93.8% AUC-ROC and 94.6% AUC-PR. While compared with the state-of-art existing tools by using an independent dataset, the proposed model achieved much higher accuracy. Overall results suggest that the developed computational model is more efficient and reliable as compared to the existing models for the prediction of DBPs in plants. For the convenience of the majority of experimental scientists, the developed prediction server PlDBPred is publicly accessible at https://iasri-sg.icar.gov.in/pldbpred/.The source code is also provided at https://iasri-sg.icar.gov.in/pldbpred/source_code.php for prediction using a large-size dataset.
From single- to multi-omics: future research trends in medicinal plants
Authors: Yang Lifang , Yang Ye , Huang Luqi , Cui Xiuming , Liu Yuan 
Published: November 2022

AbstractMedicinal plants are the main source of natural metabolites with specialised pharmacological activities and have been widely examined by plant researchers. Numerous omics studies of medicinal plants have been performed to identify molecular markers of species and functional genes controlling key biological traits, as well as to understand biosynthetic pathways of bioactive metabolites and the regulatory mechanisms of environmental responses. Omics technologies have been widely applied to medicinal plants, including as taxonomics, transcriptomics, metabolomics, proteomics, genomics, pangenomics, epigenomics and mutagenomics. However, because of the complex biological regulation network, single omics usually fail to explain the specific biological phenomena. In recent years, reports of integrated multi-omics studies of medicinal plants have increased. Until now, there have few assessments of recent developments and upcoming trends in omics studies of medicinal plants. We highlight recent developments in omics research of medicinal plants, summarise the typical bioinformatics resources available for analysing omics datasets, and discuss related future directions and challenges. This information facilitates further studies of medicinal plants, refinement of current approaches and leads to new ideas.
PhaTYP: predicting the lifestyle for bacteriophages using BERT
Authors: Shang Jiayu , Tang Xubo , Sun Yanni 
Published: November 2022

Abstract
Bacteriophages (or phages), which infect bacteria, have two distinct lifestyles: virulent and temperate. Predicting the lifestyle of phages helps decipher their interactions with their bacterial hosts, aiding phages’ applications in fields such as phage therapy. Because experimental methods for annotating the lifestyle of phages cannot keep pace with the fast accumulation of sequenced phages, computational method for predicting phages’ lifestyles has become an attractive alternative. Despite some promising results, computational lifestyle prediction remains difficult because of the limited known annotations and the sheer amount of sequenced phage contigs assembled from metagenomic data. In particular, most of the existing tools cannot precisely predict phages’ lifestyles for short contigs. In this work, we develop PhaTYP (Phage TYPe prediction tool) to improve the accuracy of lifestyle prediction on short contigs. We design two different training tasks, self-supervised and fine-tuning tasks, to overcome lifestyle prediction difficulties. We rigorously tested and compared PhaTYP with four state-of-the-art methods: DeePhage, PHACTS, PhagePred and BACPHLIP. The experimental results show that PhaTYP outperforms all these methods and achieves more stable performance on short contigs. In addition, we demonstrated the utility of PhaTYP for analyzing the phage lifestyle on human neonates’ gut data. This application shows that PhaTYP is a useful means for studying phages in metagenomic data and helps extend our understanding of microbial communities.
A Bayesian model for identifying cancer subtypes from paired methylation profiles
Authors: Fan Yetian , S Chan April , Zhu Jun , Yi Leung Suet , Fan Xiaodan 
Published: November 2022

Abstract
Aberrant DNA methylation is the most common molecular lesion that is crucial for the occurrence and development of cancer, but has thus far been underappreciated as a clinical tool for cancer classification, diagnosis or as a guide for therapeutic decisions. Partly, this has been due to a lack of proven algorithms that can use methylation data to stratify patients into clinically relevant risk groups and subtypes that are of prognostic importance. Here, we proposed a novel Bayesian model to capture the methylation signatures of different subtypes from paired normal and tumor methylation array data. Application of our model to synthetic and empirical data showed high clustering accuracy, and was able to identify the possible epigenetic cause of a cancer subtype.
A bilateral lung transplant and giant pulmonary artery aneurysm reconstruction with an aortic graft in a woman with pulmonary hypertension
Authors: Poveda David , Fadel Elie , Lorenzi William , Menager Jean Baptiste 
Published: November 2022

Abstract
An aneurysm of the pulmonary artery is a rare but severe complication in patients suffering from pulmonary arterial hypertension. For these patients, a lung or heart-lung transplant is the only definitive therapy available. Our goal was to show a reconstruction strategy in a patient with a mismatch between the pulmonary artery and the donor aorta.
ArabidopsisN6-methyladenosine methyltransferase FIONA1 regulates floral transition by affecting the splicing ofFLCand the stability of floral activatorsSPL3andSEP3
Authors: Cai Jing , Hu Jianzhong , Amara Umme , Park Su Jung , Li Yuxia , Jeong Daesong , Lee Ilha , Xu Tao , Kang Hunseung 
Published: November 2022

AbstractN 6-methyladenosine (m6A) RNA methylation has been shown to play a crucial role in plant development and floral transition. Two recent studies have identified FIONA1 as an m6A methyltransferase that regulates the floral transition in Arabidopsis through influencing the stability of CONSTANS (CO), SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1), and FLOWERING LOCUS C (FLC). In this study, we confirmed that FIONA1 is an m6A methyltransferase that installs m6A marks in a small group of mRNAs. Furthermore, we show that, in addition to its role in influencing the stability of CO, SOC1, and FLC, FIONA1-mediated m6A methylation influences the splicing of FLC, a key floral repressor, and the stability of SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE 3 (SPL3) and SEPALLATA3 (SEP3), floral activators, which together play a vital role in floral transition in Arabidopsis. Our study confirms the function of FIONA1 as an m6A methyltransferase and suggests a close molecular link between FIONA1-mediated m6A methylation and the splicing of FLC and the destabilization of SPL3 and SEP3 in flowering time control.