bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of computational methods for harmonic state estimation of power system networks
Authors: Naji Hassan Saadallah , Hussein Husham Idan 
Published: April 2021

<span>In this study, a novel technique is used to estimate the power system harmonic state, as one of the biggest risks in a power system network. Nonlinear loads are widely used, which inject harmonics into a system. Such injected harmonics make networks unstable and increase power loss. The main objective of this work is to develop a new harmonic state estimator system to increase power system accuracy, stability and the wall operation state. Three computational methods are used in this study, that is, the i) proposed particle swarm optimisation-recursive least squares (PSO-RLS) algorithm, which is developed, presented and compared with the ii) discrete fourier transform (DFT) and iii) PSO algorithms. The three algorithms are tested on an IEEE 14-bus system, and simulation results show that the new PSO-RLS algorithm is more accurate than the other two algorithms (i.e. DFT and PSO algorithms), with a lower error percentage. The proposed algorithm is tested to prove its validity and effectiveness in power system networks. The capability of the PSO-RLS algorithm is apparent in the error percentage compared with that of the other two computational methods, which can be used to provide an excellent prediction rate for measurement errors in system buses. </span>
Simulation for determining the rod pump system parameter values using finite difference method
Authors: Merry Sartika Erwani , Darmawan Arief 
Published: April 2021

<p>Lifting <span>petroleum to the surface requires a mechanism called an artificial lift. This mechanism is useful for increasing the flow of fluids from a well. One that uses this method is the rod pump. The rod pump system needed the appropriate design (through the determination of the value of the parameters that affect) so that the pump runs optimally. But changing the appropriate design in real terms is not economically and time-efficient. The ideal rod pump system analysis procedure is to take downhole data (in the well) which is commonly called a pump card. A pump card calculation simulation is needed to efficiently analyze the rod pump system. The wave equation can describe the model of the rod pump system. A simulation of pump data calculation is performed using the finite difference method for the wave equation solution. Through the process of tuning parameter values using trial and error methods, the steps of tuning the parameter value of the rod pump system are proposed in this paper. For further research, a pump card calculation method based on a surface card can be developed to efficiently analyze the rod pump.</span></p>
Delineation of electrocardiogram morphologies by using discrete wavelet transforms
Authors: Darmawahyuni Annisa , Nurmaini Siti , Habibie Supriansyah Hanif , Rizki Fauzi Muhammad Irham , Naufal Rachmatullah Muhammad , Firdaus Firdaus , Tutuko Bambang 
Published: April 2021

<span>The accuracy of electrocardiogram (ECG) delineation can affect the precise diagnose for cardiac disorders interpretation. Some nonideal ECG presentation can make a false decision in precision medicine. Besides, the physiological variation of heart rate and different characteristics of the different ECG waves in terms of shape, frequency, amplitude, and duration is also affected. <span>This paper proposes a discrete wavelet transform (DWT), non-stationary signal analysis for noise removal, and onset-offset of PQRST feature extraction. A well-known database from Physionet: QT database (QTDB) is used to validate the DWT function for detecting the onset and offset of P-wave, QRS-complex, and T-wave localization. From the results, P-peak detection gets the highest result that achieves 2.19 and 13.62 milliseconds of mean error and standard deviation, respectively. In contrast, Toff has obtained the highest error value due to differences in the T-wave morphology. It can be affected by inverted o</span>r biphasic T-waves and others.</span>
Measuring information security policy compliance: content validity of questionnaire
Authors: Angraini Angraini , Alinda Alias Rose , Okfalisa Okfalisa 
Published: April 2021

<span>Instruments used to measure compliance with information security policies have been developed by many researchers before, but only a few have conducted validity tests per item, especially for variables selected based on qualitative research. This study aims to validate the questionnaire will be used to measure user compliance with policies of information security. This study began by designing a questionnaire and conducting content validation using content ratio validation (CVR) and content index validation (CVI). As many as eight experts from the university assessed the items given. The results of 72 items submitted a questionnaire, as many as 22 items eliminated, and only 50 items that have CVR and CVI values above 0.75. Also, Kappa statistical calculations show that items have excellent reliability among assessors at the item level. This study revealed that this instrument had obtained an appropriate level of validity to measure compliance with information security policies. </span>
High-Density Lipoprotein Anti-Inflammatory Capacity and Incident Cardiovascular Events
Authors: Jia Congzhuo , Anderson Josephine L.C. , Gruppen Eke G. , Lei Yu , Bakker Stephan J.L. , Dullaart Robin P.F. , Tietge Uwe J.F. 
Published: April 2021

Background:
The role of high-density lipoprotein (HDL) function in cardiovascular disease represents an important emerging concept. The present study investigated whether HDL anti-inflammatory capacity is prospectively associated with first cardiovascular events in the general population.

Methods:
HDL anti-inflammatory capacity was determined as its ability to suppress TNFα (tumor necrosis factor α)–induced VCAM-1 (vascular cell adhesion molecule-1) mRNA expression in endothelial cells in vitro (results expressed as achieved percent reduction by individual HDL related to the maximum TNFα effect with no HDL present). In a nested case-control design of the PREVEND (Prevention of Renal and Vascular End Stage Disease) study, 369 cases experiencing a first cardiovascular event (combined end point of death from cardiovascular causes, ischemic heart disease, nonfatal myocardial infarction, and coronary revascularization) during a median of 10.5 years of follow-up were identified and individually matched to 369 controls with respect to age, sex, smoking status, and HDL cholesterol. Baseline samples were available in 340 cases and 340 matched controls.

Results:

HDL anti-inflammatory capacity was not correlated with HDL cholesterol or hsCRP (high-sensitivity C-reactive protein). HDL anti-inflammatory capacity was significantly lower in cases compared with controls (31.6% [15.7–44.2] versus 27.0% [7.4–36.1];
P
<0.001) and was inversely associated with incident CVD in a fully adjusted model (odds ratio [OR] per 1 SD, 0.74 [CI, 0.61–0.90];
P
=0.002). Furthermore, this association was approximately similar with all individual components of the cardiovascular disease end point. The HDL anti-inflammatory was not correlated with cholesterol efflux capacity (
r
=−0.02;
P
>0.05). When combining these 2 HDL function metrics in 1 model, both were significantly and independently associated with incident cardiovascular disease in a fully adjusted model (efflux: OR per 1 SD, 0.74;
P
=0.002; anti-inflammatory capacity: OR per 1 SD, 0.66;
P
<0.001). Adding HDL anti-inflammatory capacity improved risk prediction by the Framingham risk score, with a model likelihood-ratio statistic increase from 10.50 to 20.40 (
P
=0.002).

Conclusions:
The HDL anti-inflammatory capacity, reflecting vascular protection against key steps in atherogenesis, was inversely associated with incident cardiovascular events in a general population cohort, independent of HDL cholesterol and HDL cholesterol efflux capacity. Adding HDL anti-inflammatory capacity to the Framingham risk score improves risk prediction.
“No other name!” The Contribution of Byang H. Kato to the Salvation Debate
Authors: van Veelen Wouter Theodoor 
Published: April 2021

Abstract
This article attempts to investigate the contribution of the African evangelical theologian and church leader Byang H. Kato (1936–1975) to the salvation debate in the early 1970s. Due to his radical standpoint and at times uncompromising tone, Kato’s soteriological proposals have been characterized as a reproduction of western theology. This article aims to demonstrate that, rather than reiterating a specific American or western concept of theology, Kato’s soteriology should be read as a contextual evangelical response to the ongoing theological debates of his time.
“Close Enough”: Images of the Failure of the 1990s’ Political Transformation in Poland as Exemplified by Władysław Pasikowski’s “Psy” [Pigs] and Andrzej Żuławski’s “Szamanka” [She-Shaman]
Authors: Szczepanek Tomasz 
Published: April 2021

This article problematizes the Polish cinema of the 1990s by analyzing it in terms of the aesthetic of failure. Of crucial importance for that interpretation is the postcolonial perspective. Seen from this perspective, Poland of the political transformation period appears a land of unfulfilled dreams of being-like-the-West. One of the spheres where this is visible is the Polish cinematography of that time.
Disgrace, Weakness, Rubbish? Material Culture of the GDR in Selected German Films After 1990
Authors: Brzezińska-Pająk Marta 
Published: April 2021

The article focuses on the material culture of the German Democratic Republic (GDR) as portrayed in selected German films made after 1990 and set in the GDR. The objects that are used in the films serve as a special kind of artefacts, symbolizing the reality of the GDR and defining it as imperfect, below expectations, and inefficient in meeting consumer demand. An important point of reference in the article is the context of post-communist nostalgia, which is a source of interesting symbolic redefinitions.
A Record-Breaking Trans-Atlantic African Dust Plume Associated with Atmospheric Circulation Extremes in June 2020
Authors: Pu Bing , Jin Qinjian 
Published: April 2021

AbstractHigh concentrations of dust can affect climate and human health, yet our understanding of extreme dust events is still limited. A record-breaking trans-Atlantic African dust plume occurred during 14–28 June 2020, greatly degrading air quality over large areas of the Caribbean Basin and the United States. Daily PM2.5 concentrations exceeded 50 µg m−3 in several Gulf States, while the air quality index reached unhealthy levels for sensitive groups in more than 11 states. The magnitude and duration of aerosol optical depth over the tropical North Atlantic Ocean were the greatest ever observed during summer over the past 18 years based on satellite retrievals. This extreme trans-Atlantic dust event is associated with both enhanced dust emissions over western North Africa and atmospheric circulation extremes that favor long-range dust transport. An exceptionally strong African easterly jet and associated wave activities export African dust across the Atlantic toward the Caribbean in the middle to lower troposphere, while a westward extension of the North Atlantic subtropical high and a greatly intensified Caribbean low-level jet further transport the descended, shallower dust plume from the Caribbean Basin into the United States. Over western North Africa, increased dust emissions are associated with strongly enhanced surface winds over dust source regions and reduced vegetation coverage in the western Sahel. While there are large uncertainties associated with assessing future trends in African dust emissions, model-projected atmospheric circulation changes in a warmer future generally favor increased long-range transport of African dust to the Caribbean Basin and the United States.
Empirical formulation for multiple groups of primary biological ice nucleating particles from field observations over Amazonia
Authors: Patade Sachin , Phillips Vaughan T. J. , Amato Pierre , Bingemer Heinz G. , Burrows Susannah M. , DeMott Paul J. , Goncalves Fabio L. T. , Knopf Daniel A. , Morris Cindy E. , Alwmark Carl , Artaxo Paulo , Pöhlker Christopher , Schrod Jann , Weber Bettina 
Published: April 2021

AbstractTo resolve the various types of biological ice nuclei (IN) with atmospheric models, an extension of the empirical parameterization (EP) (Phillips et al. 2008; 2013) is proposed to predict the active IN from multiple groups of primary biological aerosol particles (PBAPs). Our approach is to utilize coincident observations of PBAP sizes, concentrations, biological composition, and ice-nucleating ability. The parameterization organizes the PBAPs into five basic groups: fungal spores, bacteria, pollen, viral particles, plant/animal detritus, algae, and their respective fragments. This new biological component of the EP was constructed by fitting predicted concentrations of PBAP IN to those observed at the Amazon Tall Tower Observatory (ATTO) site located in the central Amazon. The fitting parameters for pollen and viral particles, plant/animal detritus, which are much less active as IN than fungal and bacterial groups, are constrained based on their ice nucleation activity from the literature. The parameterization has empirically derived dependencies on the surface area of each group (except algae), and the effects of variability in their mean sizes and number concentrations are represented via their influences on the surface area. The concentration of active algal IN is estimated from literature-based measurements.Predictions of this new biological component of the EP are consistent with previous laboratory and field observations not used in its construction. The EP scheme was implemented in a 0D parcel model. It confirms that biological IN account for most of the total IN activation at temperatures warmer than −20°C and at colder temperatures dust and soot become increasingly more important to ice nucleation.
Transfer to the clinic: refining forward programming of hPSCs to megakaryocytes for platelet production in bioreactors
Authors: Evans Amanda L. , Dalby Amanda , Foster Holly R. , Howard Daniel , Waller Amie K. , Taimoor Momal , Lawrence Moyra , Mookerjee Souradip , Lehmann Marcus , Burton Annie , Valdez Jorge , Thon Jonathan , Italiano Joseph , Moreau Thomas , Ghevaert Cedric 
Published: April 2021

Abstract
The production of in vitro–derived platelets has great potential for transfusion medicine. Here, we build on our experience in the forward programming (FoP) of human pluripotent stem cells (hPSCs) to megakaryocytes (MKs) and address several aspects of the complex challenges to bring this technology to the bedside. We first identify clinical-grade hPSC lines that generate MKs efficiently. We design a bespoke media to maximize both production and maturity of MKs and improve platelet output. Crucially, we transition the lentiviral-based FoP of hPSCs to a nonviral inducible system. We also show how small molecules promote a definitive hematopoiesis phenotype during the differentiation process, thereby increasing the quality of the final product. Finally, we generate platelets using a bioreactor designed to reproduce the physical cues that promote platelet production in the bone marrow. We show that these platelets are able to contribute to both thrombus formation in vitro and have a hemostatic effect in thrombocytopenic mice in vivo.
scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data
Authors: Ranjan Bobby , Schmidt Florian , Sun Wenjie , Park Jinyu , Honardoost Mohammad Amin , Tan Joanna , Arul Rayan Nirmala , Prabhakar Shyam 
Published: April 2021

AbstractBackgroundClustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on differentially expressed genes. In contrast, supervised methods use a reference panel of labelled transcriptomes to guide both clustering and cell type identification. Supervised and unsupervised clustering approaches have their distinct advantages and limitations. Therefore, they can lead to different but often complementary clustering results. Hence, a consensus approach leveraging the merits of both clustering paradigms could result in a more accurate clustering and a more precise cell type annotation.ResultsWe presentscConsensus, an$${\mathbf {R}}$$Rframework for generating a consensus clustering by (1) integrating results from both unsupervised and supervised approaches and (2) refining the consensus clusters using differentially expressed genes. The value of our approach is demonstrated on several existing single-cell RNA sequencing datasets, including data from sorted PBMC sub-populations.ConclusionsscConsensuscombines the merits of unsupervised and supervised approaches to partition cells with better cluster separation and homogeneity, thereby increasing our confidence in detecting distinct cell types.scConsensusis implemented in$${\mathbf {R}}$$Rand is freely available on GitHub athttps://github.com/prabhakarlab/scConsensus.
Performance improvement for a 2D convolutional neural network by using SSC encoding on protein–protein interaction tasks
Authors: Wang Yang , Li Zhanchao , Zhang Yanfei , Ma Yingjun , Huang Qixing , Chen Xingyu , Dai Zong , Zou Xiaoyong 
Published: April 2021

AbstractBackgroundThe interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabolism, which is of extraordinary significance to modern proteomics research. Despite advances in experimental technology, it is still expensive, laborious, and time-consuming to determine protein–protein interactions (PPIs), and there is a strong demand for effective bioinformatics approaches to identify potential PPIs. Considering the large amount of PPI data, a high-performance processor can be utilized to enhance the capability of the deep learning method and directly predict protein sequences.ResultsWe propose the Sequence-Statistics-Content protein sequence encoding format (SSC) based on information extraction from the original sequence for further performance improvement of the convolutional neural network. The original protein sequences are encoded in the three-channel format by introducing statistical information (the second channel) and bigram encoding information (the third channel), which can increase the unique sequence features to enhance the performance of the deep learning model. On predicting protein–protein interaction tasks, the results using the 2D convolutional neural network (2D CNN) with the SSC encoding method are better than those of the 1D CNN with one hot encoding. The independent validation of new interactions from the HIPPIE database (version 2.1 published on July 18, 2017) and the validation of directly predicted results by applying a molecular docking tool indicate the effectiveness of the proposed protein encoding improvement in the CNN model.ConclusionThe proposed protein sequence encoding method is efficient at improving the capability of the CNN model on protein sequence-related tasks and may also be effective at enhancing the capability of other machine learning or deep learning methods. Prediction accuracy and molecular docking validation showed considerable improvement compared to the existing hot encoding method, indicating that the SSC encoding method may be useful for analyzing protein sequence-related tasks. The source code of the proposed methods is freely available for academic research athttps://github.com/wangy496/SSC-format/.
Long-term TE persistence even without beneficial insertion
Authors: Kremer Stefan C. , Linquist Stefan , Saylor Brent , Elliott Tyler A. , Gregory T. Ryan , Cottenie Karl 
Published: April 2021

AbstractThis correspondence responds to the critique by Butler et al. (BMC Genomics 22:241, 2021) of our recent paper on transposable element (TE) persistence. We address the three main objections raised by Butler et al. After running a series of additional simulations that were inspired by the authors’ criticisms, we are able to present a more nuanced understanding of the conditions that generate long-term persistence.
Characterization and transcriptomic analysis of a novel yellow-green leaf wucai (Brassica campestris L.) germplasm
Authors: Nie Libing , Zheng Yushan , Zhang Liting , Wu Ying , Zhu Shidong , Hou Jinfeng , Chen Guohu , Tang Xiaoyan , Wang Chenggang , Yuan Lingyun 
Published: April 2021

Abstract
Background
Leaf color mutants are the ideal materials to explore the pathways of chlorophyll (Chl) metabolism, chloroplast development, and photosynthesis system. In this study, a spontaneous yellow-green leaf wucai (Brassica campestris L.) mutant “WY16–13” was identified, which exhibited yellow-green leaf color during its entire growth period. However, current understanding of the molecular mechanism underlying Chl metabolism and chloroplast development of “WY16–13” is limited.

Results
Total Chl and carotenoid content in WY16–13 was reduced by 60.92 and 58.82%, respectively, as compared with its wild type parental line W16–13. Electron microscopic investigation revealed fewer chloroplasts per cell and looser stroma lamellae in WY16–13 than in W16–13. A comparative transcriptome profiling was performed using leaves from the yellow-green leaf type (WY16–13) and normal green-leaf type (W16–13). A total of 54.12 million (M) (WY16–13) and 56.17 M (W16–13) reads were generated. A total of 40,578 genes were identified from the mapped libraries. We identified 3882 differentially expressed genes (DEGs) in WY16–13 compared with W16–13 (i.e., 1603 upregulated genes and 2279 downregulated genes). According to the Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, these DEGs are involved in porphyrin and Chl metabolism [i.e., chlorophyllase (CLH), heme oxygenase (HO), chlorophyll (ide) b reductase (NYC), and protochlorophyllide oxidoreductase (POR) genes], carbohydrate metabolism, photosynthesis, and carbon fixation in photosynthetic organisms. Moreover, deficiency in Chl biosynthetic intermediates in WY16–13 revealed that the formation of the yellow-green phenotype was related to the disorder of heme metabolism.

Conclusions
Our results provide valuable insights into Chl deficiency in the yellow-green leaf mutant and a bioinformatics resource for further functional identification of key allelic genes responsible for differences in Chl content.