bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid algorithm for multi artifact removal from single channel EEG
Authors: Noorbasha Sayedu Khasim , Florence Sudha Gnanou 
Published: April 2021

Abstract
Electroencephalogram (EEG) signals recorded from the ambulatory systems are mostly contaminated by various artifacts like, electrooculogram (EOG), motion artifacts (MA) and electrocardiogram (ECG) artifacts. These artifacts limit the accuracy in further analysis of EEG in practise. So far, several existing methods have been proposed with the combination of decomposition techniques and independent component analysis (ICA) to remove single artifacts and only few methods to remove multiple artifacts from the single channel EEG. As improperly denoised EEG signals can result in wrong diagnosis, in this work, Singular Spectrum Analysis (SSA) and ICA are jointly combined with Generalized Moreau Envelope Total Variation (GMETV) technique to simultaneously remove combinations of different artifacts from single channel EEG. In this work, the SSA is used to decompose the contaminated single channel EEG, while the ICA is employed to separate the various hidden sources as independent components (ICs). Although the ICA is adequate in source separation, there is still, some essential EEG signal data appearing as artifact in the IC. Hence, eliminating this would allow EEG signal information to be lost. The GMETV approach is proposed in this paper, to estimate the actual artifacts in order to address these issues. The estimated actual artifacts are subtracted from the artifact ICs providing the residue of wanted component of EEG. This residue is added back to the remaining ICs, to obtain the denoised EEG. Simulation results demonstrated that the proposed technique performs better compared to the existing techniques. The Relative Root Mean Square Error (RRMSE) is reduced by 12.02% and 7.22% compared to SSA-ICA and SSA-ICA-thresholding respectively. Similarly, the Correlation Coefficient (CC) is increased by 21.48% and 8.25% with respect to SSA-ICA and SSA-ICA-thresholding respectively.
A two-dimensional air streamer discharge modified model based on artificial stability term under non-uniform electric field at low temperature and sub-atmospheric pressure
Authors: ZHAO Zhihang , WEI Xinlao , SONG Shuang , CUI Lin , YANG Kailun , ZHANG Zhonghua 
Published: April 2021

Abstract
In this paper, an improved air discharge fluid model under non-uniform electric field is constructed based on the plasma module COMSOL Multiphysics with artificial stability term, and the boundary conditions developed in the previous paper are applied to the calculation of photoionization rate. Based on the modified model, the characteristics of low temperature sub-atmospheric air discharge under 13 kV direct current voltage are discussed, including needle-plate and needle-needle electrode structures. Firstly, in order to verify the reliability of the model, a numerical example and an experimental verification were carried out for the modified model respectively. Both verification results show that the model can ensure the accuracy and repeatability of the calculation. Secondly, according to the calculation results of the modified model, under the same voltage and spacing, the reduced electric field under low temperature sub-atmosphere pressure is larger than that under normal temperature and atmospheric pressure. The high electric field leads to the air discharge at low temperature and sub atmospheric pressure entering the streamer initiation stage earlier, and has a faster propagation speed in the streamer development stage, which shortens the overall discharge time. Finally, the discharge characteristics of the two electrode structures are compared, and it is found that the biggest difference between them is that there is a pre-ionization region near the cathode in the needle-needle electrode structure. When the pre-ionization level reaches 1013 cm−3, the propagation speed of the positive streamer remains unchanged throughout the discharge process, and is no longer affected by the negative streamer. The peak value of electric field decreases with the increase of pre-ionization level, and tends to be constant during streamer propagation. Based on the previous paper, this paper constructs the air discharge model under non-uniform electric field, complements with the previous paper, and forms a relatively complete set of air discharge simulation system under low temperature and sub atmospheric pressure, which provides a certain reference for future research.
Elastic behavior analysis of multilayers by finite element method
Authors: Roa Simón , Sirena Martín 
Published: April 2021

Abstract
We studied the elastic properties of free-standing multilayered systems using finite element analysis with a rigid spherical indenter. To model and simulate the elastic response of these systems a 2-dimensional axisymmetric solid model was used. In particular, multilayered systems with a total thickness of 10 [μm] and composed by a periodic bilayer array were studied. The bilayers thickness in each multilayered system, as well as the isotropic elastic constants (Young´s modulus and Poisson´s ratio) of each thin film, were fixed to be constant in all the cases. The influence on the mechanical properties of different relative thickness ratios (from 0.11 up to 9) between the two films in the bilayer was carefully studied. Our results indicated that changes in the relative thickness ratios can produce considerable changes in the elastic mechanical response of the multilayered systems, observing important variations up to 19% (for displacements lower than 10% of the first film thickness) on the magnitude of the effective Young´s modulus. The interplay between the structural properties of the layers gives place to the nonlinear behavior of the Young modulus as a function of the volume fraction of the different layers. Due to the non-homogenous nature of the system, a strong dependence of the sample Young´s modulus with respect to the indentation depth was observed. This work contributes to qualitatively understand the impact of different characteristics of multilayered systems, such as the elastic properties and the proportion of the composing materials, on its elastic behavior.
Numerical simulation with experimental validation of the structural reaction injection moulding of 3D continuous fibre reinforced polyurethane foam
Authors: Schäfer Kay , Nestler Daisy , Jahn Kristina , Niedziela Dariusz , Ireka Ikenna , Steiner Konrad , Kroll Lothar 
Published: April 2021

Abstract
Sandwich composite materials are established in the industry. Polyurethane foam reinforced with spacer fabric represents an innovative solution for a core in this field. It is manufactured in the Structural Reaction Injection Moulding (SRIM). This paper describes new investigations that provide the base for component and process design when using this Interpenetrating Phase Composite (IPC). Filling studies were carried out for this purpose in three moulding tools with different cavities with and without spacer fabric. It is shown that the PUR foam expansion and the foam bulk density are clearly influenced by the sprue type, cavity design and spacer fabric. Simulations are necessary to investigate all process-structure-property relationships in detail and to enable a user-friendly and efficient design of material and process. Adequate mathematical models to simulate the transport of mass, heat and momentum in the SRIM are presented in this paper. The resistance to the expansion process caused by the porous structures in the domain were taken into account. The transport of momentum in the mould is described with the Navier–Stokes-Brinkman equations which in the limit of the permeability tensor reduces to the Navier–Stokes equation. The model equations are solved numerically and the results show reasonable agreement with the experimental data.
Strategies for the construction of machine-learning potentials for accurate and efficient atomic-scale simulations
Authors: Miksch April M , Morawietz Tobias , Kästner Johannes , Urban Alexander , Artrith Nongnuch 
Published: April 2021

Abstract
Recent advances in machine-learning interatomic potentials have enabled the efficient modeling of complex atomistic systems with an accuracy that is comparable to that of conventional quantum-mechanics based methods. At the same time, the construction of new machine-learning potentials can seem a daunting task, as it involves data-science techniques that are not yet common in chemistry and materials science. Here, we provide a tutorial-style overview of strategies and best practices for the construction of artificial neural network (ANN) potentials. We illustrate the most important aspects of (a) data collection, (b) model selection, (c) training and validation, and (d) testing and refinement of ANN potentials on the basis of practical examples. Current research in the areas of active learning and delta learning are also discussed in the context of ANN potentials. This tutorial review aims at equipping computational chemists and materials scientists with the required background knowledge for ANN potential construction and application, with the intention to accelerate the adoption of the method, so that it can facilitate exciting research that would otherwise be challenging with conventional strategies.
Single step synthesis of WO3 nanoparticles by wire explosion process and its photocatalytic behaviour
Authors: Ranjan Prem , Suematsu H. , Sarathi R. 
Published: April 2021

Tungsten (W) wires are exploded in oxygen ambience to get tungsten oxide (WO3) nanoparticles (NPs). Energy stored in the capacitors (EC) is used to overcome the sublimation energy of wire. Energy ratio (K, ratio of EC and sublimation energy) and oxygen pressure (P) are two control parameters for the particle phase and morphology in the wire explosion process. X-ray diffraction (XRD) patterns confirmed the partial oxidation of W for low values of K. For K = 2, oxidation increases with increase in P. For K = 10, complete oxidation was achieved irrespective of P. Particles are spherical in shape as observed from scanning electron microscope (SEM) and transmission electron microscope (TEM) micrographs. Particle size follows a log-normal distribution with a least mean size of 24.1 nm. UV-vis diffuse reflectance spectroscopy (DRS) was used to measure the absorbance of NPs (complete WO3 with least mean size) for band gap measurement. The band gap was found to be 2.92 eV (visible region). NPs are used as photocatalyst to degrade aqueous solution of methylene blue (MB) under visible light irradiation. 500 mg l−1 of WO3 NPs were optimum to degrade 10 mg l−1 MB in 120 min.
Supported Binary and Ternary Nanoalloy Nanoparticle Catalysts-A Green Processing Approach using the Leidenfrost layer as Nanoreactor
Authors: Es-Souni Mohammed 
Published: April 2021

Abstract
When a nanocarbon substrate is heated between 300 °C and 320 °C that is slightly above the Leidenfrost temperature and subsequently quenched in an aqueous solution containing a mixture of noble metal ions, a high density of nanoalloy nanoparticles (NPs) form on the surface. Large surface areas can be decorated in this way by nanoalloy NPs of the system (Au, Pt, Pd). Both binary AuPt, AuPd and PtPd as well as ternary nanoalloys are obtained. The chemical composition of the nanoalloys can be tuned by varying the ion mixture ratio of the solutions. The simultaneous reduction of the noble metal ions on the surface occurs without the need of any reducing agent, presumably owing to charge transfer from ionized species during the quenching process. The method yields nanocarbon-supported, highly adherent nanoalloy NPs, is materials efficient and cost effective because only the surface is modified with the costly noble metals. The supported nanoalloy NPs are exemplary applied to the electrooxidation of methanol and formic acid in acidic solutions, and show an overall high performance.
Lessons from recent medical history: an obsolete anti-reflux device in an older patient with variable gastrointestinal symptoms
Authors: Squires Charlotte , Porter Ross J , Ward Benjamin M 
Published: April 2021

Abstract
A frail 93-year-old lady presented with delirium, on a background of heart failure, cerebrovascular disease, constipation and osteoporosis. A computed tomography (CT) pulmonary angiography, undertaken due to persistent hypoxia, identified no pathology aside from an unusual appearance of the left hypochondrium, necessitating further elucidation with CT abdomen. This unexpectedly reported the presence of a gastric band, leading us to consider possible misidentification. Perusing her General Practitioner (GP) records demonstrated that she underwent surgical insertion of an Angelchik prosthesis in 1984. Angelchik prostheses were anti-reflux devices used for a short period, before falling from favour due to increasing evidence around late developing complications. A collateral history from family revealed that this patient had experienced multiple longstanding symptoms including bloating, reflux and constipation, potentially linked to her prosthesis, a previously unestablished link.
Deciphering the evolution of the ovule genetic network through expression analyses in Gnetum gnemon
Authors: Zumajo-Cardona Cecilia , Ambrose Barbara A 
Published: April 2021

Abstract

Background and aims
The ovule is a synapomorphy of all seed plants (gymnosperms and angiosperms); however, there are some striking differences in ovules among the major seed plant lineages, such as the number of integuments or the orientation of the ovule. The genetics involved in ovule development have been well studied in the model species Arabidopsis thaliana, which has two integuments and anatropous orientation. This study is approached from what is known in arabidopsis, focusing on the expression patterns of homologues of four genes known to be key for the proper development of the integuments in arabidopsis: AINTEGUMENTA (ANT), BELL1, (BEL1), KANADIs (KANs) and UNICORN (UCN).

Methods
We used histology to describe the morphoanatomical development from ovules to seeds in Gnetum gnemon. We carried out spatiotemporal expression analyses in G. gnemon, a gymnosperm, which has a unique ovule morphology with an integument covering the nucellus, two additional envelopes where the outermost becomes fleshy as the seed matures, and an orthotropous orientation.

Key Results
Our anatomical and developmental descriptions provide a framework for expression analyses in the ovule of G. gnemon. Our expression results show that although ANT, KAN and UCN homologues are expressed in the inner integument, their spatiotemporal patterns differ from those found in angiosperms. Furthermore, all homologues studied here are expressed in the nucellus, revealing major differences in seed plants. Finally, no expression of the studied homologues was detected in the outer envelopes.

Conclusions
Altogether, these analyses provide significant comparative data that allows us to better understand the functional evolution of these gene lineages, providing a compelling framework for evolutionary and developmental studies of seeds. Our findings suggest that these genes were most likely recruited from the sporangium development network and became restricted to the integuments of angiosperm ovules.
Cloning, expression, and characterization of Baeyer–Villiger monooxygenases from eukaryotic Exophiala jeanselmei strain KUFI-6N
Authors: Yamamoto Taisei , Kobayashi Kento , Hasegawa Yoshie , Iwaki Hiroaki 
Published: April 2021

ABSTRACT
The fungus Exophiala jeanselmei strain KUFI-6N produces a unique cycloalkanone monooxygenase (ExCAMO) that displays an uncommon substrate spectrum of Baeyer–Villiger oxidation of 4-10-membered ring ketones. In this study, we aimed to identify and sequence the gene encoding ExCAMO from KUFI-6N and overexpress the gene in Escherichia coli. We found that the primary structure of ExCAMO is most closely related to the cycloalkanone monooxygenase from Cylindrocarpon radicicola ATCC 11011, with 54.2% amino acid identity. ExCAMO was functionally expressed in E. coli and its substrate spectrum and kinetic parameters were investigated. Substrate profiling indicated that ExCAMO is unusual among known Baeyer–Villiger monooxygenases owing to its ability to accept a variety of substrates, including C4-C12 membered ring ketones. ExCAMO has high affinity and catalytic efficiency toward cycloalkanones, the highest being toward cyclohexanone. Five other genes encoding Baeyer–Villiger monooxygenases were also cloned and expressed in E. coli.
Cuttlefish: fast, parallel and low-memory compaction of de Bruijn graphs from large-scale genome collections
Authors: Khan Jamshed , Patro Rob 
Published: April 2021

Abstract

Motivation
The construction of the compacted de Bruijn graph from collections of reference genomes is a task of increasing interest in genomic analyses. These graphs are increasingly used as sequence indices for short- and long-read alignment. Also, as we sequence and assemble a greater diversity of genomes, the colored compacted de Bruijn graph is being used more and more as the basis for efficient methods to perform comparative genomic analyses on these genomes. Therefore, time- and memory-efficient construction of the graph from reference sequences is an important problem.

Results
We introduce a new algorithm, implemented in the tool Cuttlefish, to construct the (colored) compacted de Bruijn graph from a collection of one or more genome references. Cuttlefish introduces a novel approach of modeling de Bruijn graph vertices as finite-state automata, and constrains these automata’s state-space to enable tracking their transitioning states with very low memory usage. Cuttlefish is also fast and highly parallelizable. Experimental results demonstrate that it scales much better than existing approaches, especially as the number and the scale of the input references grow. On a typical shared-memory machine, Cuttlefish constructed the graph for 100 human genomes in under 9 h, using ∼29 GB of memory. On 11 diverse conifer plant genomes, the compacted graph was constructed by Cuttlefish in under 9 h, using ∼84 GB of memory. The only other tool completing these tasks on the hardware took over 23 h using ∼126 GB of memory, and over 16 h using ∼289 GB of memory, respectively.

Availability and implementation
Cuttlefish is implemented in C++14, and is available under an open source license at https://github.com/COMBINE-lab/cuttlefish.

Supplementary information
Supplementary data are available at Bioinformatics online.
Visual exploration of large metabolic models
Authors: Aichem Michael , Czauderna Tobias , Zhu Yan , Zhao Jinxin , Klapperstück Matthias , Klein Karsten , Li Jian , Schreiber Falk 
Published: April 2021

AbstractMotivationLarge metabolic models, including genome-scale metabolic models, are nowadays common in systems biology, biotechnology and pharmacology. They typically contain thousands of metabolites and reactions and therefore methods for their automatic visualization and interactive exploration can facilitate a better understanding of these models.ResultsWe developed a novel method for the visual exploration of large metabolic models and implemented it in LMME (Large Metabolic Model Explorer), an add-on for the biological network analysis tool VANTED. The underlying idea of our method is to analyze a large model as follows. Starting from a decomposition into several subsystems, relationships between these subsystems are identified and an overview is computed and visualized. From this overview, detailed subviews may be constructed and visualized in order to explore subsystems and relationships in greater detail. Decompositions may either be predefined or computed, using built-in or self-implemented methods. Realized as add-on for VANTED, LMME is embedded in a domain-specific environment, allowing for further related analysis at any stage during the exploration. We describe the method, provide a use case and discuss the strengths and weaknesses of different decomposition methods.Availability and implementationThe methods and algorithms presented here are implemented in LMME, an open-source add-on for VANTED. LMME can be downloaded from www.cls.uni-konstanz.de/software/lmme and VANTED can be downloaded from www.vanted.org. The source code of LMME is available from GitHub, at https://github.com/LSI-UniKonstanz/lmme.
Differential gene expression analysis for multi-subject single-cell RNA-sequencing studies withaggregateBioVar
Authors: Thurman Andrew L , Ratcliff Jason A , Chimenti Michael S , Pezzulo Alejandro A 
Published: April 2021

AbstractMotivationSingle-cell RNA-sequencing (scRNA-seq) provides more granular biological information than bulk RNA-sequencing; bulk RNA sequencing remains popular due to lower costs which allows processing more biological replicates and design more powerful studies. As scRNA-seq costs have decreased, collecting data from more than one biological replicate has become more feasible, but careful modeling of different layers of biological variation remains challenging for many users. Here, we propose a statistical model for scRNA-seq gene counts, describe a simple method for estimating model parameters and show that failing to account for additional biological variation in scRNA-seq studies can inflate false discovery rates (FDRs) of statistical tests.ResultsFirst, in a simulation study, we show that when the gene expression distribution of a population of cells varies between subjects, a naïve approach to differential expression analysis will inflate the FDR. We then compare multiple differential expression testing methods on scRNA-seq datasets from human samples and from animal models. These analyses suggest that a naïve approach to differential expression testing could lead to many false discoveries; in contrast, an approach based on pseudobulk counts has better FDR control.Availability and implementationA software package, aggregateBioVar, is freely available on Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/aggregateBioVar.html) to accommodate compatibility with upstream and downstream methods in scRNA-seq data analysis pipelines.Supplementary informationRaw gene-by-cell count matrices for pig scRNA-seq data are available as GEO accession GSE150211. Supplementary data are available at Bioinformatics online.
Alignment free sequence comparison methods and reservoir host prediction
Authors: Lee Bill , Smith David K , Guan Yi 
Published: April 2021

Abstract

Motivation
The emergence and subsequent pandemic of the SARS-CoV-2 virus raised urgent questions about its origin and, particularly, its reservoir host. These types of questions are long-standing problems in the management of emerging infectious diseases and are linked to virus discovery programs and the prediction of viruses that are likely to become zoonotic. Conventional means to identify reservoir hosts have relied on surveillance, experimental studies and phylogenetics. More recently, machine learning approaches have been applied to generate tools to swiftly predict reservoir hosts from sequence data.

Results
Here, we extend a recent work that combined sequence alignment and a mixture of alignment-free approaches using a gradient boosting machines machine learning model, which integrates genomic traits and phylogenetic neighbourhood signatures to predict reservoir hosts. We add a more uniform approach by applying Machine Learning with Digital Signal Processing-based structural patterns. The extended model was applied to an existing virus/reservoir host dataset and to the SARS-CoV-2 and related viruses and generated an improvement in prediction accuracy.

Availability and implementation
The source code used in this work is freely available at https://github.com/bill1167/hostgbms.

Supplementary information
Supplementary data are available at Bioinformatics online.