bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of surface-to-volume ratio on the plasma activated water characteristics and its anticancer effect
Authors: Liu Zhijie , Wang Sitao , Pang Bolun , Zhang Huaiyan , Gao Yuting , Xu Dehui , Kong Michael G 
Published: February 2021

Abstract
Plasma activated water (PAW), as a green and potential technology, plays a significant role in bio-medicine applications. Surface-to-volume ratio of treated liquid during the preparation of PAW seriously affects the PAW chemistry characteristics, and ultimately results in different biological effects. However, that how does the surface-to-volume ratio affect PAW characteristics and anticancer effect induced by PAW is unclear. In this work, the surface-to-volume ratio is regulated to investigate the dynamic variation of chemical characteristics and cell apoptosis. Results display physicochemical properties including pH, ORP, and liquid temperature are varied with nonlinear trend besides conductivity. While the levels of RONS containing NO2
−, NO3
−, H+ are changed with linear trend except H2O2 ONOO− and O
.

2
−. Furthermore, increasing surface-to-volume ratio could effectively accelerate cell apoptosis, enhance intracellular ROS concentration and strengthen anticancer effects. Thus, it is concluded that tuning surface to volume ratio can effectively enhance the reactive species flux into the liquid that leads to remarkable anticancer activity of PAW rather than the surface-to-volume ratio that is directly responsible for the enhanced impact on the cells. Additionally, the possible apoptosis mechanisms linked with RONS are also discussed. Clarifying the relationship between the surface-to-volume ratio and the PAW characteristics is beneficial to much insights into the chemistry nature of PAW and tailoring biological effect caused by PAW.
Even and odd crystal fields on Fe2+ ions, local lattice distortion parameters, electron-deformation interaction, and magnetoelectric coupling in FeCr2O4
Authors: Vasin K V , Eremin M V 
Published: February 2021

Abstract
Within the framework of the quantum mechanical approach, the available experimental data are analyzed to identify the electronic structure of the multiferroic FeCr2O4. The relative values of the key contributions to the parameters of even and odd crystal fields acting on the 3d electrons of the Fe2+ ion are determined. Data on local lattice distortions are systematized. The parameter of the electron-deformation interaction of the ground term Fe2+ (5
E) is determined considering lattice distortions, and the parameters of binding of the spins of Fe2+ and Cr3+ to the electric field are estimated. The calculation results are compared with the available experimental data on the magnetic and structural characteristics of FeCr2O4, the critical temperature of the transition to an orbitally ordered state, optical conductivity data, the Mössbauer effect study, and measurements of spontaneous electric polarization.
High-temperature stability and phase transformations of titanium carbide (Ti3C2T
x
) MXene
Authors: Wyatt Brian C , Nemani Srinivasa Kartik , Desai Krishay , Kaur Harpreet , Zhang Bowen , Anasori Babak 
Published: February 2021

Abstract
Two-dimensional (2D) transition metal carbides, nitrides, and carbonitrides, known as MXenes, are under increasing pressure to meet technological demands in high-temperature applications, as MXenes can be considered to be one of the few ultra-high temperature 2D materials. Although there are studies on the stability of their surface functionalities, there is currently a gap in the fundamental understanding of their phase stability and transformation of MXenes’ metal carbide core at high temperatures (>700 °C) in an inert environment. In this study, we conduct systematic annealing of Ti3C2T
x
MXene films in which we present the 2D MXene flake phase transformation to ordered vacancy superstructure of a bulk three-dimensional (3D) Ti2C and TiC
y
crystals at 700 °C ⩽ T ⩽ 1000 °C with subsequent transformation to disordered carbon vacancy cubic TiC
y
at higher temperatures (T > 1000 °C). We annealed Ti3C2T
x
MXene films made from the delaminated MXene single-flakes as well as the multi-layer MXene clay in a controlled environment through the use of in situ hot stage x-ray diffraction (XRD) paired with a 2D detector (XRD2) up to 1000 °C and ex situ annealing in a tube furnace and spark plasma sintering up to 1500 °C. Our XRD2 analysis paired with cross-sectional scanning electron microscope imaging indicated the resulting nano-sized lamellar and micron-sized cubic grain morphology of the 3D crystals depend on the starting Ti3C2T
x
form. While annealing the multi-layer clay Ti3C2T
x
MXene creates TiC
y
grains with cubic and irregular morphology, the grains of 3D Ti2C and TiC
y
formed by annealing Ti3C2T
x
MXene single-flake films keep MXenes’ lamellar morphology. The ultrathin lamellar nature of the 3D grains formed at temperatures >1000 °C can pave way for applications of MXenes as a stable carbide material 2D additive for high-temperature applications.
Non-Hermitian semi-Dirac semi-metals
Authors: Banerjee Ayan , Narayan Awadhesh 
Published: February 2021

Abstract
Recently, many novel and exotic phases have been proposed by considering the role of topology in non-Hermitian systems, and their emergent properties are of wide current interest. In this work we propose the non-Hermitian generalization of semi-Dirac semimetals, which feature a linear dispersion along one momentum direction and a quadratic one along the other. We study the topological phase transitions in such two-dimensional semi-Dirac semimetals in the presence of a particle gain-and-loss term. We show that such a non-Hermitian term creates exceptional points (EPs) originating out of each semi-Dirac point. We map out the topological phase diagram of our model, using winding number and vorticity as topological invariants of the system. By means of numerical and analytical calculations, we examine the nature of edge states for different types of semi-Dirac models and establish bulk-boundary correspondence and absence of the non-Hermitian skin effect, in one class. On the other hand, for other classes of semi-Dirac models with asymmetric hopping, we restore the non-Hermitian skin effect, an anomalous feature usually present in non-Hermitian topological systems.
Object detection algorithm based on feature enhancement
Authors: Zheng Qiumei , Wang Lulu , Wang Fenghua 
Published: February 2021

Abstract
Recently, many excellent algorithms have made great progress in object detection, but there are also problems in these algorithms’ performance on targets of different sizes, and in particular in small object detection. Aiming at the problem of insufficient feature representation by the feature extractor, in this paper we propose a lightweight algorithm to improve feature extraction. The algorithm includes three modules. First, considering that the shallow features in feature extraction contain much background noise, in this paper we design a multi-level feedback propagation model based on a Gaussian high-pass filter. The shallow layers are enhanced using the filter and then back-propagated to add the upper shallow layer features and obtain new shallow layer features. This process is performed on the newly generated shallow layer for n iterations, which is beneficial for enhancing targets in the foreground area and suppressing background noise. Second, we form a stacked dilated convolution module with different dilation rates to cover the entire deep feature layer densely, which enlarges the receptive field and enriches the contextual information. Finally, we build a multi-scale fusion module to fuse the above-mentioned enhanced shallow and deep features to obtain output features with powerful representational ability for detection tasks. In addition, the model is easily embedded into existing approaches to enhance their performance. We build the model on the VGG-16 and ResNet-50 backbones and successfully applied it on Darknet-19 and Darknet-53 to verify its effectiveness and stability. The experiments on the COCO dataset prove that the proposed algorithm outperforms the state-of-art methods, with a mean average precision improvement reaching 2% on average. The effect is remarkable on small targets and complex backgrounds. Furthermore, it does not affect the detection speed significantly, so real time detection requirements can still be met.
A graphene-coated silk-spandex fabric strain sensor for human movement monitoring and recognition
Authors: Song Xian , Liu Xiaoting , Peng Yuxin , Xu Zhen , Liu Wenming , Pang Kai , Wang Jianxiang , Zhong Liang , Yang Qiang , Meng Jun 
Published: February 2021

Abstract
Flexible and stretchable sensors are emerging and promising wearable devices for motion monitoring. Manufacturing a flexible and stretchable strain sensor with desirable electromechanical performance and excellent skin compatibility plays an essential role in building a smart wearable system. In this paper, a graphene-coated silk-spandex (GCSS) fabric strain sensor is prepared by reducing graphene oxide. The sensor functions as a result of conductive fiber extending and woven structure deforming. The conductive fabric can be stretched towards 60% with high sensitivity, and its performance remains constant after a 1000-cycle test. Based on its superior performance, the GCSS is successfully employed to detect full-range human movement and provide data for deep learning-based gesture recognition. This work offers a desirable method to fabricate low-cost strain sensors for industrial applications such as human movement detection and advanced information science.
A non-invasive reference-based method for imaging the cerebral metabolic rate of oxygen by PET/MR: theory and error analysis
Authors: Narciso Lucas , Ssali Tracy , Iida Hidehiro , St Lawrence Keith 
Published: February 2021

Abstract
Positron emission tomography (PET) remains the gold standard for quantitative imaging of the cerebral metabolic rate of oxygen (CMRO2); however, it is an invasive and complex procedure that requires accounting for recirculating [15O]H2O (RW) and the cerebral blood volume (CBV). This study presents a non-invasive reference-based technique for imaging CMRO2 that was developed for PET/magnetic resonance imaging (MRI) with the goal of simplifying the PET procedure while maintaining its ability to quantify metabolism. The approach is to use whole-brain (WB) measurements of oxygen extraction fraction (OEF) and cerebral blood flow (CBF) to calibrate [15O]O2-PET data, thereby avoiding the need for invasive arterial sampling. Here we present the theoretical framework, along with error analyses, sensitivity to PET noise and inaccuracies in input parameters, and initial assessment on PET data acquired from healthy participants. Simulations showed that neglecting RW and CBV corrections caused errors in CMRO2 of less than ±10% for changes in regional OEF of ±25%. These predictions were supported by applying the reference-based approach to PET data, which resulted in remarkably similar CMRO2 images to those generated by analyzing the same data using a modeling approach that incorporated the arterial input functions and corrected for CBV contributions. Significant correlations were observed between regional CMRO2 values from the two techniques (slope = 1.00 ± 0.04, R
2 > 0.98) with no significant differences found for integration times of 3 and 5 min. In summary, results demonstrate the feasibility of producing quantitative CMRO2 images by PET/MRI without the need for invasive blood sampling.
Frustrated double ionization of atoms in circularly polarized laser fields
Authors: Kang HuiPeng , Chen Shi , Chen Jing , Paulus Gerhard G 
Published: February 2021

Abstract
We theoretically study frustrated double ionization (FDI) of atoms subjected to intense circularly polarized laser pulses using a three-dimensional classical model. We find a ‘knee’ structure of FDI probability as a function of intensity, which is similar to the intensity dependence of nonsequential double ionization probability. The observation of FDI is more favourable when using targets with low ionization potentials and short driving laser wavelengths. This is attributed to the crucial role of recollision therein, which can be experimentally inferred from the photoelectron momentum distribution generated by FDI. This work provides novel physical insights into FDI dynamics with circular polarization.
Automatic Classification of NVST Short-exposure Data Based on Deep Learning
Authors: Li Qiang , Zheng Sheng , Huang Yao , Liu Dejian 
Published: February 2021

Abstract
The New Vacuum Solar Telescope is one of the most important solar telescopes in China. However, in the process of reconstructing high-resolution solar data, the data may be distorted by thin film interference fringes. In this paper, an automatic classification method based on deep learning is proposed to distinguish fringe-contained data and fringe-free data, employing the Adaptive Wavelet Transform to construct the sample data set while transfer learning is utilized to train the classification model. The experimental results show that classification accuracy of the proposed method can reach up to 99.3%. This proposed method can make the high-resolution reconstruction pipeline run automatically whether the solar data contains fringes or not.
Brain sources’ activity in resting state before a visuo-motor task
Authors: Miraglia Francesca , Vecchio Fabrizio , Alù Francesca , Orticoni Alessandro , Judica Elda , Cotelli Maria , Rossini Paolo Maria 
Published: February 2021

Abstract

Objective. In modern neuroscience, the underlying mechanisms of the elaboration and reaction to different kinds of stimuli of the brain hemispheres remain still very challenging to understand, together with the possibility to anticipate certain behaviors to improve the performance. Approach. The purpose of the present study was to investigate the brain rhythms characteristics of electroencephalographic (EEG) recordings and in particular, their interhemispheric differences in resting state condition before a visuo-motor task in a population of healthy adults. During the task, subjects were asked to react to a sequence of visual cues as quick as possible. The reaction times (RTs) to the task were measured, collected and correlated with the EEG signals recorded in a resting state condition immediately preceding the task. The EEG data were analyzed in the space of cortical sources of EEG rhythms by the computation of the global spectra power density (GSPD) in the left and in the right hemisphere, and of an index of brain laterality (L). Main results. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open (EO) and eyes closed (EC) conditions. A close to significant and negative correlation was found in the parietal areas. Furthermore, RTs negatively correlated with L in the central areas in EC condition. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both EO and EC conditions. Significance. The correlations between the brain activity before a task and the RTs to the task can represent an interesting tool for exploring the brain state characterization for the upcoming tasks performance.
Retraction: A Methodology for the Synthesis of E-Commerce (Journal of Physics: Conference Series
1230 012004)
Authors: Amri Imti Tsalil , Yamalia Ikke , Rico  , Rohayani Hetty , Lestari Dewi 
Published: February 2021

This article has been retracted by IOP Publishing on 18 February 2021 in light of clear evidence that it was computer generated. IOP Publishing is investigating why this was not identified during the submission and peer review process by the conference. As a member of the Committee for Publication Ethics (COPE) this has been investigated in accordance with COPE guidelines and it was agreed the article should be retracted.
Retraction published: 18 February 2021
Retraction: Newton Categories for a Solvable Element (Journal of Physics: Conference Series
1637 012123)
Authors: Wan Fang 
Published: February 2021

This article has been retracted by IOP Publishing on 18 February 2021 in light of clear evidence that it was computer generated. IOP Publishing is investigating why this was not identified during the submission and peer review process by the conference. As a member of the Committee for Publication Ethics (COPE) this has been investigated in accordance with COPE guidelines and it was agreed the article should be retracted.
Retraction published: 18 February 2021
Some More Results on at Most Twin Extendable Separated Domination Number of a Graphs
Authors: Anuthiya S. , Mahadeven G. 
Published: February 2021

Abstract
Previously, G. Mahadevan et. al., has invented the concept of At most twin Extendable separate Domination number of a graph and obtained many resluts. A set S ⊆ V is said to be At most twin extendable separated dominating set, if for every vertex υ ∈ V − S, 1 ⩽ | N (V) ∩ S| ⩽ 2 and < V − S > is a perfect matching. The minimum cardinality taken over all At most twin extendable separated dominating sets is called At most twin extendable separated domination number of a graph and it is denoted by ATES (G). In this research paper, this number is evaluated for some intersting special types of graphs.
Distance-2 Irregular chromatic numbers for some graphs
Authors: Yokesh D. , Nirmala G. , Anitha K. 
Published: February 2021

Abstract
Let G be a graph and let c:V(G)→{1,2…..k} be a coloring of the vertices of G for some positive integer k (where adjacent vertices may be colored the same). The color code of a vertex v of G (with respect to c) is the ordered (k+1)-tuple code (v) = (a0, a1, a2….ak) where a0 is the color assigned to v and for 1 ⩽ i ⩽ k, ai is the number of the vertices of G adjacent to that are colored i. The coloring c is called recognizable if distinct vertices have distinct color codes and the recognition number of G is the minimum positive integer k for which G has a recognizable k-coloring. In this paper we introduced a new variation of above parameter namely distance-2 irregular coloring. We initiate a study of this parameter and also find the distance 2-irregular chromatic number of some standard graphs.
Generalization of New Degree Based Topological Indices of Silicate Network Graph
Authors: Selvarani P. , Dhanalakshm K. , Irudaya Monica Catherine J. 
Published: February 2021

Abstract
In the fields of chemical graph theory and mathematical chemistry, a topological index also known as a connectivity index is a type of a molecular descriptor that is calculated based on the molecular graph of a chemical compound. Topological indices are numerical parameters of a graph. Topological indices are used for example in the development of quantitative structure-activity relationships (QSARs) and other properties of molecules are correlated with their chemical structure, in that Silicates are the most common minerals in the Earth’s crust and mantle, it has a wide variety of physical properties which paved way to find the topological indices. In this paper gives us the generalized new form of topological indices such as Arithmetic-Geometric Index (AG Index), SK Index, SK1 Index and SK2 Index of Silicate network graphs.
TODIM method based on bipolar intuitionistic fuzzy soft set
Authors: Anita Shanthi S. , Jayapalan Prathipa 
Published: February 2021

Abstract
This paper deals with TODIM(an acronym in Portuguese for iterative Multi-criteria decision making) method based on bipolar intuitionistic fuzzy soft set (BIFSS). Entropy measure on BIFSS is developed and it serves as a tool in computing the weight values. Further, a score function is defined and based on it a score matrix is constructed. A BIFS normalized euclidean distance is developed and by using this a dominance degree matrix is computed. An illustration is given to show the applicability of this method in solving the decision making problem.
RETRACTED: Harmless Treatment and Comprehensive Utilization of Dairy Farming Waste Based on Artificial Intelligence
Authors: Ji Bin , Du Jinhao , Qi Hongshan , Peng Yinan , Zhu Ruiqing , Wu Chenghao , Wang Zhiye 
Published: February 2021

Abstract
With the rapid development of social economy, people’s living standards are constantly improving. Dairy farming, as the main source of people’s demand for dairy products, plays an important role in the current social development. However, the disposal of its waste has always been a thorny issue. Therefore, the purpose of this paper is to study the harmless treatment and comprehensive utilization of dairy farming waste based on artificial intelligence. Finally, according to the actual investigation and comprehensive combination of artificial intelligence technology, this paper puts forward a dairy farming wastewater treatment system. The system uses artificial intelligence, multistage solid-liquid separation, biodegradation and other technologies, which can effectively treat the wastewater produced during dairy farming with good treatment effect and stable effluent index. In this paper, through experimental research, it is found that the quality of the treated wastewater is higher than the farmland irrigation standard by using the dairy farming wastewater treatment system based on artificial intelligence, and the effluent quality is lower than 200ml/g after advanced treatment. This will greatly improve the current ecological environment pollution, improve the scale process of aquaculture industry, provide an institutional system for the construction of waste discharge and utilization, and also provide new impetus for the green development of dairy farming industry.
Design of digital business center of enterprise project management system based on Information Technology
Authors: Zhao Lei , Deng Junhua , Ma Yulong , Zhu Yan 
Published: February 2021

Abstract
Under the current network economy and e-commerce environment, the market competition is increasingly fierce, and the customer demand is increasingly diversified. The traditional enterprise project management system digital business center is difficult to achieve efficient enterprise project management. Therefore, this paper proposes the digital business center design of enterprise project management system based on information technology. The data processing structure of project management business center is designed, and the overall framework of enterprise level project management system is constructed. The enterprise digital management mode and decision-making steps are optimized through the division of enterprise level project information management level, and the enterprise level project management business category level is classified. Finally, the design of enterprise level project management system digital business center is realized. Experimental results show that the proposed method can solve the problem of information transmission between enterprises, and make corresponding linkage adjustment quickly according to the changes of market environment, ensure the smooth, flexible and rapid response of enterprise supply chain, and can timely and quickly find and meet customer needs, and achieve efficient project management.