bluuebunny/crossref_metadata_2025 huggingface dataset:
Outpatient therapy with piperacillin/tazobactam using elastomeric pumps in patients with Pseudomonas aeruginosa infection
Authors: Ferreiro Jose Luis Lamas , Otero Judith Álvarez , Rivo Ana Sanjurjo , González Lucía González , Conde Irene Rodríguez , Soneira María Fernández , García Javier Posada , de la Fuente Aguado Javier
Published: April 2021

The aim of this study was to evaluate the efficacy and safety of outpatient antimicrobial therapy with piperacillin-tazobactam in continuous infusion using elastomeric pumps and to evaluate the economic impact compared with conventional hospital treatment in patients with Pseudomonas aeruginosa (PA) infections. This is an observational study. Patients with PA infection treated with continuous piperacillin-tazobactam infusion using elastomeric pumps in our hospital between January 2015 and December 2017 were included. Primary outcomes were mortality during antibiotic treatment and mortality at 30 days. Secondary outcomes were reinfection or relapse at 30 days and clinical cure rate. The cost of each episode was compared with theoretical cost of the same treatment using conventional hospitalization. 35 patients were included. One patient (2.9%) died during the treatment. Overall 30-day mortality was 5.7%. No death was related to infection by PA. One patient (2.9%) had a reinfection at 30 days. Cure was achieved in 93% of patients at the end of treatment. There were no severe complications related to elastomeric pumps. Treatment cost with outpatient antimicrobial therapy was 67% lower than theoretical cost with conventional hospital treatment. Oupatient antimicrobial therapy with piperacillin-tazobactam in continuous infusion using elastomeric pumps in patients with PA infections is safe and effective with lower costs.
Immunoglobulin E levels and pregnancy-induced hypertension: Japan Environment and Children’s Study
Authors: Kyozuka Hyo , Murata Tsuyoshi , Fukuda Toma , Endo Yuta , Yamaguchi Akiko , Yasuda Shun , Kanno Aya , Sato Akiko , Ogata Yuka , Hosoya Mitsuaki , Yasumura Seiji , Hashimoto Koichi , Nishigori Hidekazu , Fujimori Keiya ,   The Japan Environment and Children’s Study (JECS) Group, Kamijima Michihiro , Yamazaki Shin , Ohya Yukihiro , Kishi Reiko , Yaegashi Nobuo , Mori Chisato , Ito Shuichi , Yamagata Zentaro , Inadera Hidekuni , Nakayama Takeo , Iso Hiroyasu , Shima Masayuki , Kurozawa Youichi , Suganuma Narufumi , Kusuhara Koichi , Katoh Takahiko
Published: April 2021

High serum immunoglobulin E (IgE) levels are associated with cardiovascular events. We aimed to evaluate the association between total IgE levels during the first trimester of pregnancy and pregnancy-induced hypertension (PIH) development in a large Japanese cohort. We analysed data pertaining to singleton primipara pregnancies recorded in the Japan Environment and Children’s Study involving births from 2011 to 2014. Serum IgE levels were determined using the immunonephelometric technique. High serum IgE was defined as level ≥ 170 IU/ml. Hypertensive disorders in pregnancy (HDP) were categorized into early onset (Eo) PIH (developed < 34 weeks) or late onset (Lo) PIH (developed ≧ 34 weeks). A multiple logistic regression model was used to estimate the risk of high serum IgE levels on PIH, Eo-PIH, and Lo-PIH. Overall, 32,518 participants were enrolled. The prevalence of total, Eo-, and Lo-PIH was 3.2%, 0.6%, and 2.3%, respectively. Patients with high serum IgE levels had an increased risk of Lo-HDP (adjusted odds ratio [aOR]:1.19, 95% confidence interval 1.01–1.40). No correlation was found with either PIH (total) or Eo-PIH. High serum IgE levels during the first trimester were associated with the risk of Lo-PIH. Our results could influence and shape further research regarding the pathogenesis of Lo hypertension.
Author Correction: Donor-derived exosomes induce specific regulatory T cells to suppress immune inflammation in the allograft heart
Authors: Song Jiangping , Huang Jie , Chen Xiao , Teng Xiao , Song Zhizhao , Xing Yong , Wang Mangyuan , Chen Kai , Wang Zheng , Yang Pingchang , Hu Shengshou
Published: April 2021

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Author Correction: Effects of Lactobacillus salivarius isolated from feces of fast-growing pigs on intestinal microbiota and morphology of suckling piglets
Authors: Moturi Joseph , Kim Kwang Yeol , Hosseindoust Abdolreza , Lee Jun Hyung , Xuan Biao , Park Jongbin , Kim Eun Bae , Kim Jin Soo , Chae Byung Jo
Published: April 2021

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Retraction Note: Associations between VDR Gene Polymorphisms and Osteoporosis Risk and Bone Mineral Density in Postmenopausal Women: A systematic review and Meta-Analysis
Authors: Zhang Liang , Yin Xin , Wang Jingcheng , Xu Daolinag , Wang Yongxiang , Yang Jiandong , Tao Yuping , Zhang Shengfei , Feng Xinmin , Yan Caifeng
Published: April 2021

Editor's Note: this Article has been retracted; the Retraction Note is available at https://doi.org/10.1038/s41598-021-88654-1.
Author Correction: Identifying threshold sizes for enlarged abdominal lymph nodes in different age ranges from about 200,000 individual’s data
Authors: He Lili , Sun Yinghua , Huang Guoying
Published: April 2021

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher Correction: Implicit motor learning within three trials
Authors: Ruttle Jennifer E. , ’t Hart Bernard Marius , Henriques Denise Y. P.
Published: April 2021

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
A novel two-dimensional beryllium diphosphide (BeP2) with superconductivity: the first-principles exploration
Authors: Li Hengtao , Wang Hongyan , Yan Luo , Li Xiumei , Chen Yuanzheng , Wang Hui
Published: April 2021

The 1H-BeP2 monolayer is a moderate-coupling superconductor with the total electron–phonon coupling coefficient λ of 0.427 and the logarithmic average frequency (ωlog) of ∼221.
Intercepting the Banert cascade with nucleophilic fluorine: direct access to α-fluorinated NH-1,2,3-triazoles
Authors: Alexander J. R. , Kevorkian P. V. , Topczewski J. J.
Published: April 2021

The treatment of propargylic azides with silver(i) fluoride in acetonitrile was found to yield α-fluorinated NH-1,2,3-triazoles via the Banert cascade.
Nucleophilic iodonium interactions (NIIs) in 2-coordinate iodine(i) and silver(i) complexes
Authors: Ward Jas S. , Frontera Antonio , Rissanen Kari
Published: April 2021

A range of Nucleophilic Iodonium Interaction (NII) complexes were synthesised by partial cation exchange, leading to the observation of the first NII-complex involving a 2-coordinate silver(i) complex.
A trinuclear chromium(iii) chlorocarbyne
Authors: Kurogi Takashi , Irifune Keiichi , Enoki Takahiro , Takai Kazuhiko
Published: April 2021

Reduction of CCl4 by CrCl2 in THF afforded a trinuclear chromium(iii) carbyne [CrCl(thf)2]3(μ3-CCl)(μ-Cl)3.
Arylpentazoles with surprisingly high kinetic stability
Authors: Bo Xiao-xu , Dong Zhi-yong , Ding Yi-hong
Published: April 2021

A co-stabilization method was proposed to design a series of novel arylpentazoles with very high N2-leaving barriers, one of which reached hitherto the highest value of 40.83 kcal mol−1 at the CBS-QB3 level.
ZnO nanoarrays via a thermal decomposition–deposition method for sensitive and selective NO2 detection
Authors: Lou Chengming , Wang Kai , Mei Houshan , Xie Jiayue , Zheng Wei , Liu Xianghong , Zhang Jun
Published: April 2021

ZnO nanoarrays deposited by a thermal decomposition–deposition (TDD) strategy demonstrate a high response for NO2 detection.
Modulation of perovskite crystallization processes towards highly efficient and stable perovskite solar cells with MXene quantum dot-modified SnO2
Authors: Yang Yingguo , Lu Haizhou , Feng Shanglei , Yang Lifeng , Dong Hua , Wang Jiaou , Tian Chen , Li Lina , Lu Hongliang , Jeong Jaeki , Zakeeruddin Shaik M. , Liu Yuhang , Grätzel Michael , Hagfeldt Anders
Published: April 2021

MQDs-SnO2-modulated perovskite crystallization processes visualized by in situ 2D GIXRD technique.
A material catalogue with glass-like thermal conductivity mediated by crystallographic occupancy for thermoelectric application
Authors: Liu Zihang , Zhang Wenhao , Gao Weihong , Mori Takao
Published: April 2021

We proposed a new crystallographic parameter, namely the site occupancy factor, as an effective indicator to discover a material catalogue with low lattice thermal conductivity for thermoelectric application.
Towards MOFs’ mass market adoption: MOF Technologies’ efficient and versatile one-step extrusion of shaped MOFs directly from raw materials
Authors: Casaban José , Zhang Yuancheng , Pacheco Raul , Coney Ciaran , Holmes Catherine , Sutherland Emmajay , Hamill Conor , Breen John , James Stuart L. , Tufano Diego , Wong Dennis , Stavrakakis Efstratios , Annath Hamza , Moore Ashleigh
Published: April 2021

We demonstrate the one-step mechanochemical production of MOF shaped bodies at large scale with bespoke geometry, strength and stability.
Simultaneous extraction and controlled chemical functionalization of hardwood lignin for improved phenolation
Authors: Bertella Stefania , Luterbacher Jeremy S.
Published: April 2021

Lignin was simultaneously extracted and functionalized with non-native groups in one step from biomass. These groups were then used to increase lignin's reactivity towards phenolation in both acidic and basic conditions in order to improve its incorporation into materials.
Nanocellulose-based mechanically stable immobilization matrix for enhanced ethylene production: a framework for photosynthetic solid-state cell factories
Authors: Rissanen V. , Vajravel S. , Kosourov S. , Arola S. , Kontturi E. , Allahverdiyeva Y. , Tammelin T.
Published: April 2021

A strong and applicable immobilization matrix based on TEMPO-oxidized nanocellulose facilitates efficient ethylene photoproduction in challenging submerged conditions.
Conjugated microporous polymers as a visible light driven platform for photo-redox conversion of biomass derived chemicals
Authors: Chen Bo , Chen Lang , Yan Zijun , Kang Jinyang , Chen Shanyong , Jin Yongdong , Ma Lijian , Yan Hongjian , Xia Chuanqin
Published: April 2021

Novel conjugated microporous polymers for photocatalytic hydrogenation and oxidation reactions of biomass derived chemicals with efficient utilization of natural sunlight have been demonstrated.
Detection of hydrogen isotopes in Zircaloy-4 via femtosecond LIBS
Authors: Kautz Elizabeth J. , Rönnebro Ewa C. E. , Devaraj Arun , Senor David J. , Harilal Sivanandan S.
Published: April 2021

Spatio-temporal mapping of species in a femtosecond laser induced Zircaloy-4 plasma identified conditions well-suited for the detection and analysis of deuterium across a wide range of concentrations.
The synthesis, characterization, and theoretical analysis of novel Si-substituted silylethyl derivatives of 2-mercaptobenzoxazole and 2-mercaptobenzothiazole
Authors: Trofimova Olga , Grebneva Ekaterina , Bolgova Yuliya , Belogolova Elena , Emel’yanov Artem , Albanov Alexander , Borodina Tat’yana , Ivanova Anastasiya , Korzhova Svetlana , Pozdnyakov Alexander
Published: April 2021

Trifluorosilylethyl derivatives of 2-mercaptobenzoxazole and 2-mercaptobenzothiazole C6H4NYCS(CH2)2SiF3 (Y = O, S) have been synthesized in order to study the intramolecular N → Si interaction in compounds with the SiCCSCN fragment.
Design and synthesis of 1,8-naphthalimide functionalized benzothiadiazoles
Authors: Rout Yogajivan , Misra Rajneesh
Published: April 2021

Push-pull derivatives BTD2–BTD5 were designed and synthesized via Pd-catalyzed Sonogashira cross-coupling reaction followed by [2+2] cycloaddition–electrocyclic ring-opening reaction.
Cationic poly-l-amino acid-enhanced selective hydrogen production based on formate decomposition with platinum nanoparticles dispersed by polyvinylpyrrolidone
Authors: Minami Yusuke , Amao Yutaka
Published: April 2021

By using platinum nanoparticles dispersed by polyvinylpyrrolidone (PVP) and cationic poly-l-amino acid, poly(l-lysine) (PLL) (Pt-PVP/PLL), highly selective H2 production based on formate decomposition was achieved about 1.8 times compared to Pt-PVP in a low pH region (pH = 1.8).
Dual modulation sites for a reversible fluorescent probe for GSH over Cys/Hcy
Authors: Ren Haixian , Huo Fangjun , Yin Caixia
Published: April 2021

An abnormal concentration of glutathione (GSH) is a health-associated risk factor, and it is an important signal for diseases such as Parkinson's disease, liver injury and cancer.
Rational design of guiding elements to control folding topology in i-motifs with multiple quadruplexes
Authors: Minasyan Alexander S. , Chakravarthy Srinivas , Vardelly Suchitra , Joseph Mark , Nesterov Evgueni E. , Nesterova Irina V.
Published: April 2021

Nucleic acids are versatile scaffolds that accommodate a wide range of precisely defined operational characteristics.
Near-infrared photoactive Yb-MOF functionalized with a large conjugate ionic liquid: synthesis and application for photoelectrochemical immunosensing of carcinoma embryonic antigen
Authors: Li Huiyue , Li Ying , Zhang Xue , Liu Pan , He Meng , Li Chunya , Wang Yanying
Published: April 2021

Near-infrared photoactive Yb-MOF synthesized from the coordination of Yb3+ with a large conjugate ionic liquid was applied for photoelectrochemical immunosensing of CEA.
Retraction: Size-selected silver nanoparticles for MALDI-TOF mass spectrometry of amyloid-beta peptides
Authors: Ding Feng , Qian Yuna , Deng Zaian , Zhang Jitai , Zhou Yongchao , Yang Lan , Wang Fangyan , Wang Juping , Zhou Zhihua , Shen Jianliang
Published: April 2021

Retraction of ‘Size-selected silver nanoparticles for MALDI-TOF mass spectrometry of amyloid-beta peptides’ by Feng Ding et al., Nanoscale, 2018, 10, 22044–22054, DOI: 10.1039/C8NR07921H.
Effect of nitrogen type on carbon dot photocatalysts for visible-light-induced atom transfer radical polymerization
Authors: Hao Qianqian , Qiao Liang , Shi Ge , He Yanjie , Cui Zhe , Fu Peng , Liu Minying , Qiao Xiaoguang , Pang Xinchang
Published: April 2021

N-Doping significantly enhanced the photo-activity of carbon dots. But only pyridinic N can improved the activity of CDs as catalysts for photo-induced ATRP, compared with pyrrolic N and graphitic N.
Intergenerational Montessori Program for Adults With Memory Concerns
Authors: Bourgeois Michelle , Brush Jennifer
Published: April 2021

Purpose

This study evaluated the effects of an intergenerational Montessori after-school program on the engagement, affect, and quality of life of older adults with memory concerns and on the attitudes of children toward older adults.

Method

Eleven older adults were paired with 11 children to participate in a 45-min after-school activity program. Observations of engagement and affect during the interactions were collected 3 times a week for 4 weeks. The older adults' engagement and affect also were observed during 45-min planning/discussion sessions without the children present before their arrival to the program.

Results

Results revealed significant differences in older adults' engagement and positive affect when the children were present. Significant pre–post improvements in reported quality of life and maintenance of cognitive status were associated with program participation. Children demonstrated more active than passive engagement and more happy than neutral affect during activity sessions. Four of the seven children improved their positive ratings of older adults.

Conclusions

This program documented success in improving engagement and affect in older adults with mild memory concerns while engaging with children. Future studies with a larger sample of participants with varying degrees of memory impairment are needed to investigate the potential of this promising program.
Contrast of multi‐resolution analysis approach to transhumeral phantom motion decoding
Authors: Nsugbe Ejay , William Samuel Oluwarotimi , Asogbon Mojisola Grace , Li Guanglin
Published: April 2021

In signal processing, multiresolution decomposition techniques allow for the separation of an acquired signal into sub levels, where the optimal level within the signal minimises redundancy, uncertainties, and contains the information required for the characterisation of the sensed phenomena. In the area of physiological signal processing for prosthesis control, scenarios where a signal decomposition analysis are required: the wavelet decomposition (WD) has been seen to be the favoured time‐frequency approach for the decomposition of non‐stationary signals. From a research perspective, the WD in certain cases has allowed for a more accurate motion intent decoding process following feature extraction and classification. Despite this, there is yet to be a widespread adaptation of the WD in a practical setting due to perceived computational complexity. Here, for neuromuscular (electromyography) and brainwave (electroencephalography) signals acquired from a transhumeral amputee, a computationally efficient time domain signal decomposition method based on a series of heuristics was applied to process the acquired signals before feature extraction. The results showed an improvement in motion intent decoding prowess for the proposed time‐domain‐based signal decomposition across four different classifiers for both the neuromuscular and brain wave signals when compared to the WD and the raw signal.
Performance analysis of machine learning algorithms on automated sleep staging feature sets
Authors: Satapathy Santosh , Loganathan D , Kondaveeti Hari Kishan , Rath RamaKrushna
Published: April 2021

With the speeding up of social activities, rapid changes in lifestyles, and an increase in the pressure in professional fields, people are suffering from several types of sleep‐related disorders. It is a very tedious task for clinicians to monitor the entire sleep durations of the subjects and analyse the sleep staging in traditional and manual laboratory environmental methods. For the purpose of accurate diagnosis of different sleep disorders, we have considered the automated analysis of sleep epochs, which were collected from the subjects during sleep time. The complete process of an automated approach of sleep stages’ classification is majorly executed through four steps: pre‐processing the raw signals, feature extraction, feature selection, and classification. In this study, we have extracted 12 statistical properties from input signals. The proposed models are tested in three different combinations of features sets. In the first experiment, the feature set contained all the 12 features. The second and third experiments were conducted with the nine and five best features. The patient records come from the ISRUC‐Sleep database. The highest classification accuracy was achieved for sleep staging through combinations with the five feature set. From the categories of the subjects, the reported accuracy results were found to exceed above 90%. As per the outcome from the proposed system the random forest classification techniques achieved best accuracy incomparable to that of the other two classifiers.
DenseConv for 3D point set upsampling
Authors: Lu Jian , Li Zhe , Cheng Haozhe , Jia Xurui , Zhang Kaibing
Published: April 2021

Recently, a data‐driven approach from point cloud upsampling network (PU‐Net) has been used to upsample point set, making it from sparse to dense. However, PU‐Net first needs to downsample the point set before upsampling, and extract the point features of fixed‐level in the sampling area. The local features are not enough to extract, and then restoring its global representation will lead to point cloud coordinates to be inaccurate. In view of the insufficient local feature extraction, EdgeConv module is utilised to merge the points and the information in the local neighbourhood. In addition, a dense connection is proposed to maintain the effective transmission of information across the entire network. In this letter, EdgeConv and dense connection are combined into DenseConv that are nested for recursive use on PU‐Net to ensure the accuracy of the generation of point cloud. The experimental results show that the average error of the proposed method is reduced by about 5% on the PU‐Net dataset and about 10% on the ModelNet10 dataset, which verifies the effectiveness of the proposed method.
Liquid metal frequency‐reconfigurable SIW bandpass filter based on gravity field
Authors: Mei Yuchao , Liu Bao‐Guang , Yi Yao , Xu Hui , Zhang Yerong
Published: April 2021

In this letter, a novel frequency‐reconfigurable substrate integrated waveguide (SIW) bandpass filter (BPF) based on gravity field is proposed. By inverting the proposed filter, the liquid metal would flow into or out of the non‐metallic via‐holes under the influence of gravity, so that the filter centre frequency can be switched from 1.76 GHz (4.54%) in state 1 to 2.02 GHz (5.94%) in state 2, and the insertion losses are maintained at 2.6 dB and 2.4 dB, respectively.
Fault recognition based test score for improving the accuracy of defect diagnosis
Authors: Tian Naiyu , Ouyang Dantong , Song Jincai , Zhang Liming
Published: April 2021

Diagnosis is an essential step to improve the yield in semiconductor manufacturing industry. It is performed on a failing chip to determine the location of defects. However, the defect diagnosis procedure may obtain too much candidate faults which lead to difficulties in next physical failure analysis. Recently, the methods based on test score to reduce candidate fault set are proved to be effective. The previous test score diagnosis method based on fault free information computes a score for each test which implies the fault identification ability. This letter proposes a novel fault recognition based test score for diagnosis which considers the fault identification capability of tests more comprehensively to improve the original method. More information provided by unique responses and faults detected of a test is added to evaluate the fault recognition for calculating a test score. Then the novel test score which takes more advantages of diagnostic information is applied to adjusting the fault score and reducing the candidate set. The experimental results show that the novel approach reaches smaller fault candidate set than the previous method and increases the diagnostic resolution and precision, and thus provides an effective improvement on the accuracy of diagnosis.
Blocking artefacts reduction based on a ripple matrix permutation image of high‐frequency images in the wavelet domain
Authors: Du Xiuli , Liu Jinting , Zhang Wei , Lv Ya'na
Published: April 2021

Block compressed sensing (BCS) approaches based on matrix permutations effectively reduce blocking artefacts in the high‐quality reconstruction of images. To further reduce the blocking artefacts, the paper proposes a novel method for their processing in the wavelet domain based on the ripple matrix permutation (RMP) BCS approach. The method makes use of the energy distribution characteristics of images in the wavelet domain. The low‐frequency images contain the basic information. The high‐frequency images contain the edge textures information of the image, and these images are extremely sparse. Then, the proposed method performs matrix permutations only on the high‐frequency images. This avoids the obvious energy differences among the blocks. The method can better balance the textures among blocks; in turn, the blocking artefacts are reduced. The approach involves performing a wavelet decomposition on the image. Then, the transformed high‐frequency image is subjected to a RMP to achieve textures balancing. Finally, compressed sensing processing is performed on the permuted high‐frequency image. As a result, the balancing effect becomes more significant, and the low‐frequency part of the image remains unchanged, the differences among the blocks are reduced. Simulation results demonstrate that the high‐frequency part of the image wavelet domain is texture balanced. When the image is reconstructed after the compressed sensing step, the image quality is significantly improved.
Ensemble machine learning based driving range estimation for real‐world electric city buses by considering battery degradation levels
Authors: Wang Yongxing , Lu Chaoru , Bi Jun , Sai Qiuyue , Zhang Yongzhi
Published: April 2021

Battery electric buses (BEBs) have been regarded as effective options to address the congestion and pollution problems in the field of urban transportation. However, since the limited driving range of BEBs brings challenges for their promotion, the accurate estimation of the driving range with limited available information has become a critical issue for public transport operators. The real‐world data collected from 50 BEBs operated in two different cities is used to develop the driving range estimation method by considering the battery degradation effects. Firstly, the incremental capacity analysis method is introduced to characterize the battery performance, and the battery degradation levels under different charging modes are recognized. Afterward, four types of ensemble machine learning (EML) methods are adopted to model the driving range estimation. The BEB driving data, weather condition data and battery degradation levels are used to train and test the models with consideration of 17 impact factors together with two different charging modes. The results indicate that the ensemble machine learning methods have good performance overall, of which the random forest has the highest accuracy. Furthermore, the importance of influencing factors is analysed, and the relevant insights are discussed.
Co‐delivery of docetaxel and retinoic acid by poly (ethylene glycol)‐retinoic acid conjugates based micelles for synergistic prostate cancer therapy
Authors: Hu Hang , Xu Defeng
Published: April 2021

In the present work, docetaxel (DTX) and retinoic acid (RA) co‐loaded micelles were developed for synergistic prostate cancer therapy. PEG‐RA and RA‐PEG‐RA were synthesized and subsequently used for loading of DTX and RA. The as prepared DTX/RA@RA‐PEG‐RA micelles exhibit smaller size and higher drug loading capacity as compared to DTX/RA@PEG‐RA micelles. The in vitro drug release study shows that DTX/RA@PEG‐RA and DTX/RA@RA‐PEG‐RA micelles exhibit similar drug release behaviours in which DTX exhibits fast release and RA exhibits sustained release. Nile red (NR) was loaded into PEG‐RA and RA‐PEG‐RA micelles to investigate the cellular uptake of the micelles by fluorescence microscope and flow cytometry. The results show that NR@RA‐PEG‐RA micelles exhibit slightly enhanced cellular uptake as compared to NR@PEG‐RA micelles. The cellular uptake of DTX/RA@PEG‐RA and DTX/RA@RA‐PEG‐RA micelles determined by HPLC also show similar results. In in vitro cytotoxicity against C4‐2 and 22Rv1 cells, DTX in combination with RA exhibit synergistic antitumor effect, and DTX/RA@PEG‐RA and DTX/RA@RA‐PEG‐RA micelles exhibit enhanced cytotoxicity against C4‐2 cells and similar cytotoxicity against 22Rv1 cells as compared to DTX/RA. DTX/RA@PEG‐RA and DTX/RA@RA‐PEG‐RA micelles show significant potential for prostate cancer therapy.
Analysis on boundary conditions of soft switching for DC electric spring with parallel topology
Authors: Wang Qingsong , Zha Daojun , Cheng Ming , Deng Fujin , Buja Giuseppe
Published: April 2021

The concept of DC electric spring (DCES) has been introduced some years ago to solve the voltage stabilisation issue caused by the high penetration of intermittent renewable energy sources (RESs) into DC power systems. Recently, a featured DCES topology has been proposed, comprising an isolated three‐port DC/DC converter and an embedded energy storage system. The three ports are connected to a DC power system at the supply side, the critical load (CL) and the non‐critical load (NCL) at the user side, whilst the energy storage system is paralleled at the CL port. To improve the performance of the topology, this paper investigates the chance of making soft the switching of the DCES converters. After the DCES operation is analysed, equations describing the currents transients during switching have been worked out, from which the boundary conditions for zero‐voltage switching (ZVS) to occur are formulated and the resultant ZVS zone is illustrated with the help of visual graphs. The boundary conditions are examined to evaluate how the circuit parameters influence the extension of the ZVS zone. The examination shows that a suitable selection of the parameters widens the ZVS zone notably; its optimal extension is then found for a case study. The effectiveness of the ZVS findings for the featured DCES topology is validated by both simulation and experiment results.
A new family of boost active neutral point clamped inverter topology with reduced switch count
Authors: Siddique Marif Daula , Reddy B. Prathap , Iqbal Atif , Mekhilef Saad
Published: April 2021

A new family of inverter topology for active neutral point clamped (ANPC) is proposed. The traditional ANPC gives the output voltage of half the input voltage which necessitates the use of higher input dc‐link voltage. To fix this problem, a floating capacitor is used to increase the voltage of the output, which decreases the dc‐link requirement. Moreover, no sensors are needed to stabilize the floating condenser for the proposed topology, which minimizes inverter complexities. The neutral point is connected directly to the load terminals, which decreases the leakage current and makes it suitable for solar PV integration. Two modes of operation of the proposed topology have been discussed while considering the voltage of the floating capacitor used in the topology. Furthermore, two extensions of the proposed topology with generalized structure have also been provided in the paper. A detailed comparison with similar topologies has been provided. The level‐shifted pulse width modulation technique has been used for the control of the proposed active neutral point clamped topology. In order to illustrate the idea of the proposed active neutral point clamped inverter, the theory of operation and analysis is accompanied by simulation, and experimental waveforms obtained from a laboratory prototype are provided.
Modified grey wolf optimisation based reduced device count 17‐level hybrid multilevel inverter
Authors: Routray Abhinandan , Singh Rajeev Kumar , Mahanty Ranjit
Published: April 2021

A 17‐level hybrid multilevel inverter (HMLI) using modified grey wolf optimisation (MGWO) is proposed here. The proposed HMLI requires only a single dc source and a lesser number of circuit elements to obtain a multilevel voltage level. The proposed HMLI can also enhance the input voltage and has reverse current carrying capability. The selective harmonic elimination pulse width modulation technique is implemented through MGWO for determining the optimal switching angles of the proposed HMLI to eliminate lower order harmonics. The MGWO algorithm gives improved results as compared to other existing optimisation algorithms in terms of fitness value, convergence speed and harmonic profile of the output voltage. The proposed HMLI is also compared with some of the other existing HMLIs in terms of the number of circuit elements, peak inverse voltage and total blocking voltage to exhibit its advantages. Finally, a 550 W prototype is fabricated in the laboratory to evaluate the effectiveness of the proposed HMLI.
Model‐based control of four‐leg inverter for UPS applications considering the effect of neutral line inductor
Authors: Seyedalipour S. Sajjad , Shahparasti Mahdi , Hajizadeh Amin , Savaghebi Mehdi
Published: April 2021

A control approach for three‐phase four‐leg LC‐filtered voltage source inverters (VSIs) is proposed for an uninterruptible power supply (UPS) application. A filter inductor in the fourth (neutral) leg of the VSI is considered to enhance the output voltage quality when feeding different types of loads in such a system. The proposed approach is based on the modelling of UPS VSI system in the dq0 synchronous frame. First, the switching functions of the inverter under study are extracted from the achieved system model. Afterward, the control approach is developed by introducing a virtual time constant, which simultaneously affects the system's damping ratio, and a virtual undamped natural frequency in the switching functions. It offers flexibility for improving the system dynamic and steady‐state responses as desired. While the final time constant decreases the transient response time and overshoot, the resulting undamped natural frequency leads to alleviation of steady‐state error in the output voltage. The performance of the proposed control approach is evaluated via SIMULINK‐based and real‐time simulation results.
State‐of‐charge estimation technique for lithium‐ion batteries by means of second‐order extended Kalman filter and equivalent circuit model: Great temperature robustness state‐of‐charge estimation
Authors: Fang Yanyan , Zhang Qiang , Zhang Hang , Xu Weicheng , Wang Linshu , Shen Xueling , Yun Fengling , Cui Yi , Wang Lin , Zhang Xin
Published: April 2021

The present work focuses on the state‐of‐charge (SOC) estimation of a lithium‐ion battery in terms of a second‐order extended Kalman filter (EKF). First, an equivalent circuit model is introduced to describe the performance of lithium‐ion batteries. The model parameters are then identified through hybrid pulse power characterization experiments conducted over a wide range of temperatures (−10 to 55°C). A two‐dimensional mathematical relationship is established with respect to the SOC and temperature based on a dual‐fifth polynomial expression. The main effects and sensitivities of the SOC and temperature on the parameters are analysed according to the principle of variance analysis and partial derivatives. An estimation algorithm is developed, which combines the two‐dimensional parameter model and second‐order EKF. Finally, the proposed approach is validated compared to other estimation schemes through discharge experiments under extreme temperatures and dynamic loading profiles, which yields experimental results that estimate the SOC with an absolute error of less than 4.5% under harsh conditions. This not only demonstrates that it can characterize dependency of the model parameters on the operating conditions and address the uncertainty of model parameters, but also verifies the advantage of present method at low temperatures especially at sub‐zero temperatures.
Data‐driven models for short‐term ocean wave power forecasting
Authors: Ni Chenhua
Published: April 2021

In order to integrate wave farms into the grid, the power from wave energy converters (WEC) must be forecasted. This study presents a novel data‐driven modelling (DDM) method to predict very short‐term (15 min–4 h) and short‐term (0–72 h) power generation from a WEC. The model is tested using data from an oscillating body converter. Several other methods are tested as well. These include support vector machines (SVM), neural networks (NN), and recurrent neural networks (RNN). Of these, the best is the long‐short‐term memory (LSTM) network, which is trained and updated on observed values. The experiments demonstrate both the SVM and NN forecast well. However, the proposed deep learning models predict them more accurately. The models work well over short horizons. At horizons longer than three days, accuracy deteriorates, and the models cannot fit the data well.
Modeling, simulation, and optimization of biogas‐diesel hybrid microgrid renewable energy system for electrification in rural area
Authors: Araoye Timothy Oluwaseun , Ashigwuike Evans Chinemezu , Egoigwe Sochima Vincent , Ilo Frederick Udebunu , Adeyemi Adeyinka Cornelius , Lawal Rasheed Segun
Published: April 2021

This research performed a techno‐economic analysis of diesel‐biogas hybrid microgrid system. The paper modeled, designed, and simulated the microgrid system using MATLAB/SIMULINK and performed system optimization using HOMER software. The anaerobic digestion (AD) processes were designed and simulated with the aid of Simulink to obtain the methane yield from the reactor. Results show that the methane yield is 95.04 kg/day at a reactor temperature of 55°C. The synchronous generator was modeled and simulated for the application of both diesel fuel and biogas fuel system. The HOMER software was used to optimize the hybrid micro‐grid system with the diesel system taken as the base case. Biogas production was varied between 1 and 5 tons while the calculated energy demand of the village was 271925 kWh. At a biomass production of 4 tons and above, the hybrid system became powered by only the biogas system for total energy production. The energy produced by biogas is 452820 kWh and a cost of energy (COE) of $0.0484. The net present cost (NPC) of the base case system is $1141292 while that of the hybrid system is $176600 and that of the biogas system is $170085 which shows the saving cost of 84.5% and 85.1%, respectively, compared to the base case system over the project lifetime.
Modelling battery energy storage systems for active network management—coordinated control design and validation
Authors: Parthasarathy Chethan , Sirviö Katja , Hafezi Hossein , Laaksonen Hannu
Published: April 2021

Control of battery energy storage systems (BESS) for active network management (ANM) should be done in coordinated way considering management of different BESS components like battery cells and inverter interface concurrently. In this paper, a detailed and accurate lithium‐ion battery model has been used to design BESS controls, thereby allowing improved overall power system control design optimisation studies by simultaneously considering both component and system‐level aspects. This model is utilised to develop a multi‐objective ANM scheme (a) to enhance utilisation of wind power generation locally by means of active power (P)‐ control of BESSs; (b) to utilise distributed energy resources (i.e. BESS and wind turbine generators) to maintain system voltage within the limits of grid code requirements by reactive power/voltage (QU)‐ and active power/voltage (PU)‐ controls. BESS control strategies to implement the ANM scheme, are designed and validated through real‐time simulation in an existing smart grid pilot, Sundom Smart Grid (SSG), in Vaasa, Finland.
A dummy peak elimination based MPPT technique for PV generation under partial shading condition
Authors: Sai Boni Satya Varun , Khadtare Sarang A. , Chatterjee Debashis
Published: April 2021

The increased energy demand with recent advancement in technology has led the global energy producers to move towards solar energy. Partial shading is a phenomenon that can severely affect the production of the solar power in the photovoltaic system. With partial shading situation, the cascaded solar panels show numerous dummy peaks both in power–voltage (P–V) and current–voltage (I–V) curves, resulting in difficulty of extracting maximum power. A dummy peak elimination based MPPT technique is introduced in proposed work for accurate tracking of maximum power. The proposed dummy peak elimination based MPPT estimates the dummy peaks without imposing any high computational burden for the processor. The proposed technique has better dynamic response and is more compatible for real time application compared to existing optimization‐based techniques. The proposed dummy peak elimination based MPPT is tested on a practical system with 3S configuration having three 249 W PV panels for different shading patterns, which displays acceptable outputs with good dynamic performance and better efficiency.
Risk‐based optimal operation of coordinated natural gas and reconfigurable electrical networks with integrated energy hubs
Authors: Hemmati Mohammad , Abapour Mehdi , Mohammadi‐Ivatloo Behnam , Anvari‐Moghaddam Amjad
Published: April 2021

This paper elaborates on optimal scheduling of coordinated power and natural gas (NG) networks in the presence of interconnected energy hubs considering reconfiguration as a flexibility source. With regard to the energy hub system consisting of several generation units, storage and conversion technologies, as well as natural gas‐fired units, the high interdependency between gas and electricity carriers should be captured. The hourly reconfiguration capability is developed for the first time in a multi‐energy system to enhance the optimal power dispatch and gas consumption pattern. The realistic interdependency of electrical and NG grids is investigated by employing the steady‐state Weymouth equation and AC‐power flow model for power and gas networks, respectively. Furthermore, to handle the risk associated with strong uncertainty of wind power, load, and real‐time power price, the conditional value at risk approach is employed. The proposed model is implemented on the integrated test system and simulation results are presented for different cases. The impact of the risk aversion level on operating cost and optimal scheduling of controllable units is examined. Numerical results demonstrate that reconfigurable capability reduces the operational cost up to 7.82%.
A benchmark of dynamic versus static methods for facial action unit detection
Authors: Alharbawee L. , Pugeault N.
Published: April 2021

Action Units activation is a set of local individual facial muscle parts that occur in time constituting a natural facial expression event. AUs occurrence activation detection can be inferred as temporally consecutive evolving movements of these parts. Detecting AUs automatically can provide explicit benefits since it considers both static and dynamic facial features. Our work is divided into three contributions: first, we extracted the features from Local Binary Patterns, Local Phase Quantisation, and dynamic texture descriptor LPQTOP with two distinct leveraged network models from different CNN architectures for local deep visual learning for AU image analysis. Second, cascading the LPQTOP feature vector with Long Short‐Term Memory is used for coding longer term temporal information. Next, we discovered the importance of stacking LSTM on top of CNN for learning temporal information in combining the spatially and temporally schemes simultaneously. Also, we hypothesised that using an unsupervised Slow Feature Analysis method is able to leach invariant information from dynamic textures. Third, we compared continuous scoring predictions between LPQTOP and SVM, LPQTOP with LSTM, and AlexNet. A competitive substantial performance evaluation was carried out on the Enhanced CK dataset. Overall, the results indicate that CNN is very promising and surpassed all other methods
Coal breakage features and fragment size distribution in water jet drilling for coalbed methane development
Authors: Xiao Songqiang , Ren Qingyang , Wang Haiyang , Liu Jialiang
Published: April 2021

Water jet drilling (WJD) technology has been widely used to extract coalbed methane. Coal breakage features and fragment size in WJD determine the drilling efficiency. The smaller the coal fragments, the easier the fragments are discharged from hydraulic boreholes. This study discloses the coal breakage features and size distributions of fragments, field experiments under the original in‐situ stress condition were conducted to obtain the coal fragments generated in WJD. The effects of the jet pressure and coal strength on fragment size distributions were investigated based on the Weibull distribution and fractal model. The results indicate that fine particles dominate the coal fragments and its proportion increases with the increase of jet pressure and the decrease of coal strength. The fragment size distributions accord with the Weibull distribution. The breakage degree index of fragments decreases in the logarithmic form as the jet pressure increases. The coal fragments have the fractal characteristic, and the fractal dimension increases with the increasing jet pressure and decreases with the increasing coal strength. Additionally, the fractal dimension increases with the decreases in breakage degree index. This work could provide a guide for research on the coal fragments transportation and the selections of hydraulic parameters in WJD.
Correction of atmospheric stray light in restored slit spectra
Authors: Saranathan S. , van Noort M. , Solanki S. K.
Published: April 2021

Context. A long-standing issue in solar ground-based observations has been the contamination of data due to stray light, which is particularly relevant in inversions of spectropolarimetric data.

Aims. We aim to build on a statistical method of correcting stray-light contamination due to residual high-order aberrations and apply it to ground-based slit spectra.

Methods. The observations were obtained at the Swedish Solar Telescope, and restored using the multi-frame blind deconvolution restoration procedure. Using the statistical properties of seeing, we created artificially degraded synthetic images generated from magneto-hydrodynamic simulations. We then compared the synthetic data with the observations to derive estimates of the amount of the residual stray light in the observations. In the final step, the slit spectra were deconvolved with a stray-light point spread function to remove the residual stray light from the observations.

Results. The RMS granulation contrasts of the deconvolved spectra were found to increase to approximately 12.5%, from 9%. Spectral lines, on average, were found to become deeper in the granules and shallower in the inter-granular lanes, indicating systematic changes to gradients in temperature. The deconvolution was also found to increase the redshifts and blueshifts of spectral lines, suggesting that the velocities of granulation in the solar photosphere are higher than had previously been observed.